Difference between revisions of "Time"
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− | |keywords=artificial, intelligence, machine, learning, models | + | |keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools |
− | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | + | |
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− | [ | + | [https://www.youtube.com/results?search_query=ai+clock+time+keep+GPS+position+~navigation+timing YouTube] |
− | [ | + | [https://www.quora.com/search?q=time ... Quora] |
+ | [https://www.google.com/search?q=ai+clock+time+keep+GPS+position+~navigationtiming ...Google search] | ||
+ | [https://news.google.com/search?q=ai+clock+time+keep+GPS+position+~navigationtiming ...Google News] | ||
+ | [https://www.bing.com/news/search?q=ai+clock+time+keep+GPS+position+~navigationtiming&qft=interval%3d%228%22 ...Bing News] | ||
+ | |||
+ | * [[Time]] ... [[Time#Positioning, Navigation and Timing (PNT)|PNT]] ... [[Time#Global Positioning System (GPS)|GPS]] ... [[Causation vs. Correlation#Retrocausality| Retrocausality]] ... [[Quantum#Delayed Choice Quantum Eraser|Delayed Choice Quantum Eraser]] ... [[Quantum]] | ||
+ | * [[Government Services]]: | ||
+ | ** [[National Institute of Standards and Technology (NIST)]] ... [https://www.nist.gov/pml/time-and-frequency-division Time and Frequency Division, Physical Measurement Laboratory] | ||
+ | ** [[U.S. Department of Homeland Security (DHS)]] ... [https://www.dhs.gov/science-and-technology/pnt-program Science and Technology (S&T) Positioning, Navigation, and Timing (PNT) Program] | ||
+ | ** [[Defense]] ... [https://www.cnmoc.usff.navy.mil/Our-Commands/United-States-Naval-Observatory/Precise-Time-Department/ Precise Time Department ... U.S. Naval Observatory has maintained a Time Service Department since 1880] | ||
+ | * [[Perspective]] ... [[Context]] ... [[In-Context Learning (ICL)]] ... [[Transfer Learning]] ... [[Out-of-Distribution (OOD) Generalization]] | ||
+ | * [https://www.npl.co.uk/ntc National Timing Centre] ... Assured Time and Frequency for the UK | ||
+ | * [https://en.wikipedia.org/wiki/Time Time] ...[https://en.wikipedia.org/wiki/Coordinated_Universal_Time Coordinated Universal Time UTC] ... [https://en.wikipedia.org/wiki/Clock Clock] ...[https://en.wikipedia.org/wiki/History_of_timekeeping_devices Timekeeping | Wikipedia] | ||
+ | * [https://interestingengineering.com/the-very-long-and-fascinating-history-of-clocks The Very Long and Fascinating History of Clocks | Christopher McFadden - Interesting Engineering] | ||
+ | ** [https://www.youtube.com/watch?v=t-_VPRCtiUg The Surprising Secret of Synchronization | Veritasium] | ||
+ | * [https://www.timeanddate.com/time/leapseconds.html What Is a Leap Second? | Konstantin Bikos and Anne Buckle - timeanddate.com] | ||
+ | * [https://www.amazon.com/s?k=atomic+clock&ref=nb_sb_noss_1 Atomic clocks] ...[https://www.amazon.com/s?k=tide+clock&ref=nb_sb_noss_1 Tide Clock | ][[Amazon]] | ||
+ | ** [https://www.sciencenews.org/article/atomic-clock-general-relativity-time-warp-millimeter-physics An atomic clock measured how general relativity warps time across a millimeter | Emily Conover - ScienceNews] | ||
+ | * [https://en.wikipedia.org/wiki/Clock_synchronization Clock synchronization] | ||
+ | * [https://bigthink.com/the-well/is-time-an-illusion/ Time: Do the past, present, and future exist all at once? | BigThink (video)] ... astrophysicist Michelle Thaller, science educator Bill Nye, author James Gleick, and neuroscientist Dean Buonomano discuss how the human brain perceives of the passage of time, the idea in theoretical physics of time as a fourth dimension, and the theory that space and time are interwoven. | ||
+ | * [https://primo.ai/index.php?title=Cybersecurity Cybersecurity] | ||
+ | ** [https://www.crownsterling.io/ Crown Sterling] ... changing the face of digital security with its non-integer-based algorithms that leverage time, AI and irrational numbers. | ||
+ | ** [https://www.csoonline.com/article/3235970/what-is-quantum-cryptography-it-s-no-silver-bullet-but-could-improve-security.html Quantum cryptography] ... the infosec industry looks to quantum cryptography and quantum key distribution (QKD) | ||
+ | * [https://spectrum.ieee.org/qa-creating-time-crystals-using-quantum-computers What’s a Time Crystal? | Charles Q. Choi - IEEE Spectrum] ... And how do Google researchers use quantum computers to make them? ... quantum system of many particles that organize themselves into a periodic pattern of motion—periodic in time rather than in space—that persists in perpetuity. | ||
+ | * [https://spectrum.ieee.org/time-reversal-interface This Mirror Reverses How Light Travels in Time There are already applications in wireless, radar, and optical-computing | Charles Q. Choi - IEEE Spectrum] ... There are already applications in wireless, radar, and optical-computing ... These applications often reverse the order of signals to help process them. | ||
+ | |||
+ | = Sequence/Time-based Algorithms = | ||
+ | * [https://www.advancinganalytics.co.uk/blog/2021/06/22/10-incredibly-useful-time-series-forecasting-algorithms 10 Incredibly Useful Time Series Forecasting Algorithms] | ||
+ | * [https://www.tableau.com/data-insights/ai/algorithms Artificial intelligence (AI) algorithms: a complete overview] | ||
+ | * [https://science.nasa.gov/technology/technology-highlights/new-ai-algorithms-streamline-data-processing-for-space-based-instruments New AI Algorithms Streamline Data Processing for Space-based Instruments] | ||
+ | * [https://www.forbes.com/sites/forbestechcouncil/2021/08/11/unlocking-the-power-of-predictive-analytics-with-ai/ Unlocking The Power Of Predictive Analytics With AI - Forbes] | ||
+ | * [https://blog.netsil.com/a-comparison-of-time-series-databases-and-netsils-use-of-druid-db805d471206 A Comparison of Time Series Databases and Netsil’s Use of Druid | Netsil] | ||
+ | * [https://azure.microsoft.com/en-us/blog/microsoft-announces-the-general-availability-of-azure-time-series-insights/ Microsoft announces the general availability of Azure Time Series Insights | Ryan Waite - Microsoft] | ||
+ | * [https://www.outlyer.com/blog/top10-open-source-time-series-databases/ Top 10 Time Series Databases | Outlyer] | ||
+ | |||
+ | Time-based AI algorithms are algorithms that use time series data to make predictions or analyses. Time series data are data that are collected over time and have a temporal order. For example, the daily temperature, the stock prices, or the number of visitors to a website are all time series data. These algorithms can be used for a variety of purposes, such as forecasting future values, detecting trends and patterns, and making informed decisions based on historical data. They can be applied to many different fields, including finance, economics, meteorology, and healthcare. | ||
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+ | <hr><center> | ||
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+ | <b><i>Whenever we have developed better clocks, we’ve learned something new about the world. </i></b><br> - Alexander Smith [https://scitechdaily.com/new-time-dilation-phenomenon-revealed-timekeeping-theory-combines-quantum-clocks-and-einsteins-relativity/ New Time Dilation Phenomenon Revealed: Timekeeping Theory Combines Quantum Clocks and Einstein’s Relativity - Dartmouth College] | ||
+ | |||
+ | </center><hr> | ||
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− | + | There are different types of sequence/time-based AI algorithms, depending on the goal and the method of the algorithm. Some of the most common ones are: | |
+ | * Time Series Forecasting: | ||
+ | ** [[Forecasting#Time Series Forecasting - Statistical|Statistical]]: | ||
+ | *** <b>Autoregressive (AR)</b>: uses past values of the time series to predict future values. It assumes that the current value is a linear function of previous values. For example, AR can be used to forecast the weather based on historical data. | ||
+ | *** <b>Autoregressive Integrated Moving Average (ARIMA)</b>: is an extension of AR that also accounts for the trend and the seasonality of the time series. It uses differencing to make the time series stationary (i.e., having constant mean and variance) and then applies AR and moving average (MA) models. For example, ARIMA can be used to forecast the sales of a product based on past sales and seasonal patterns. | ||
+ | *** <b>Seasonal Autoregressive Integrated Moving Average (SARIMA)</b>: is a further extension of ARIMA that also accounts for the cyclic variations of the time series. It uses seasonal differencing and seasonal AR and MA models to capture the periodic fluctuations of the time series. For example, SARIMA can be used to forecast the electricity demand based on past demand and seasonal factors. | ||
+ | *** <b>Exponential Smoothing (ES)</b>: uses weighted averages of past values of the time series to predict future values. It gives more weight to recent values than older values, and it can also incorporate trend and seasonality components. For example, ES can be used to forecast the inventory level based on past demand and supply. | ||
+ | ** [[Forecasting#Time Series Forecasting - Deep Learning|Deep Learning]]: | ||
+ | *** <b>Prophet</b>: is a modern and flexible approach to time series forecasting developed by [[Meta|Facebook]]. It uses a decomposable model that consists of trend, seasonality, and holiday components, and it allows for adding custom effects and prior information. For example, Prophet can be used to forecast the web traffic for a data science blog website based on past traffic and special events. | ||
+ | *** <b>[[Neural Turing Machine]] (NTM)</b>: the fuzzy pattern matching capabilities of [[Neural Network]]s with the algorithmic power of programmable computers. NTMs are an instance of [[Memory]] Augmented [[Neural Network]]s, a new class of [[Recurrent Neural Network (RNN)]]s which decouple computation from [[memory]] by introducing an external [[memory]] unit. NTMs have demonstrated superior performance over Long Short-Term [[Memory]] Cells in several sequence learning tasks. | ||
+ | * [[Neural Network]]s: | ||
+ | ** <b>[[Recurrent Neural Network (RNN)]]</b>: is a type of [[Deep Learning]] model that can process sequential data such as time series. It uses a network of neurons that have feedback loops, which enable them to store information from previous inputs. For example, RNN can be used to forecast the prices of Bitcoin based on past prices and other factors. | ||
+ | *** <b>[[Gated Recurrent Unit (GRU)]]</b>: are a gating mechanism in [[Recurrent Neural Network (RNN)]] architecture. Like other RNNs, a GRU can process sequential data such as time series, natural language, and speech1. The GRU is similar to a [[Long Short-Term Memory (LSTM)]] with a forget gate, but has fewer parameters than LSTM, as it lacks an output gate. This means that GRUs are generally easier and faster to train than their LSTM counterparts. GRUs have been found to perform similarly to LSTMs on certain tasks such as polyphonic music modeling, speech signal modeling, and natural language processing. They have shown that gating is indeed helpful in general. | ||
+ | *** <b>[[Long Short-Term Memory (LSTM)]]</b>: is a special type of RNN that can handle long-term dependencies in sequential data. It uses a [[memory]] cell that can store, update, and forget information over time, and it has gates that control the flow of information in and out of the cell. For example, LSTM can be used to forecast the generation of wind power based on past generation and weather conditions: | ||
+ | **** <b>[[Bidirectional Long Short-Term Memory (BI-LSTM)]]</b>: is a type of [[Recurrent Neural Network (RNN)]] architecture that processes data in both forward and backward directions. It consists of two LSTMs: one taking the input in a forward direction, and the other in a backward direction. BI-LSTMs effectively increase the amount of information available to the network, improving the context available to the algorithm. For example, knowing what words immediately follow and precede a word in a sentence. Compared to LSTM, BI-LSTM combines the forward hidden layer and the backward hidden layer, which can access both the preceding and succeeding contexts¹. This feature of flow of data in both directions makes the BI-LSTM different from other LSTMs. BI-LSTMs have been successfully applied to various tasks such as natural language processing, speech recognition, and traffic forecasting. | ||
+ | **** <b>Bidirectional Long Short-Term Memory (BI-LSTM) with Attention Mechanism</b>: is a type of [[Recurrent Neural Network (RNN)]] architecture that processes data in both forward and backward directions, and uses an attention mechanism to weigh the importance of different parts of the input sequence. The attention mechanism allows the network to focus on specific parts of the input sequence when making predictions, rather than treating all parts of the sequence equally. This can be particularly useful when dealing with long input sequences, where some parts of the sequence may be more relevant to the prediction than others. BI-LSTMs with Attention Mechanism have been successfully applied to various tasks such as text classification, [[Sentiment Analysis]], and human activity recognition. | ||
+ | **** <b>[[Average-Stochastic Gradient Descent (SGD) Weight-Dropped LSTM (AWD-LSTM)]]</b>: is a variant of LSTM that employs DropConnect for regularization, as well as NT-ASGD for optimization. NT-ASGD stands for non-monotonically triggered averaged stochastic gradient descent, which returns an average of the last iterations of weights. AWD-LSTM has shown great results on both word-level and character-level models. It has been used in research papers on word-level models and has shown great results on character-level models as well. | ||
+ | *** <b>[[Sequence to Sequence (Seq2Seq)]]</b>: can map a variable-length input sequence to a variable-length output sequence. It is often used for natural language processing tasks, such as machine translation, text summarization, conversational models, and question answering. The Seq2Seq algorithm consists of two main components: an encoder and a decoder. The encoder reads the input sequence one timestep at a time and produces a hidden vector representation of the input. The decoder then uses the hidden vector as the initial state and generates the output sequence one timestep at a time, using the previous output as the input context. | ||
+ | ** <b>[[Transformer]]</b>: is a state-of-the-art [[Deep Learning]] model that can process sequential data such as time series. It uses layers of attention mechanisms that can learn how to focus on relevant parts of the input data, and it can handle long-term dependencies and parallel computations efficiently. For example, [[Transformer]] can be used to forecast the spread of COVID-19 based on past cases and interventions. [[Transformer]] can process sequential data using layers of attention mechanisms, without using recurrent or convolutional layers. It can handle long-term dependencies and parallel computations efficiently, and it can achieve better results than RNN-based Seq2Seq models on various tasks. | ||
+ | *** <b>[[Generative Pre-trained Transformer (GPT)]]</b>: are a family of language models that use [[Deep Learning]] techniques to generate natural language text. They are based on the [[transformer]] architecture and can be fine-tuned for various natural language processing tasks such as text generation, language translation, and text classification. The first GPT was introduced in 2018 by the American artificial intelligence (AI) company [[OpenAI]]. GPT models are artificial [[Neural Network]]s that are based on the [[transformer]] architecture, pre-trained on large data sets of unlabelled text, and able to generate novel human-like content | ||
+ | *** <b>[[Attention]] Mechanism</b>: allows the decoder to selectively focus on different parts of the input sequence when generating the output, instead of relying on a single fixed vector. This can improve the performance and accuracy of the Seq2Seq model, especially for long sequences | ||
+ | **** <b>[[Transformer-XL]]</b>: is a transformer-based language model that introduces the notion of recurrence to the deep self-attention network. It was designed to enable learning dependency beyond a fixed length without disrupting temporal coherence. The model consists of a segment-level recurrence mechanism and a novel positional encoding scheme. This method not only enables capturing longer-term dependency, but also resolves the context fragmentation problem. As a result, Transformer-XL learns dependency that is 80% longer than RNNs and 450% longer than vanilla [[Transformer]]s, achieves better performance on both short and long sequences, and is up to 1,800+ times faster than vanilla [[Transformer]]s during evaluation. | ||
+ | *** <b>Beam search</b>: is a technique to find the most probable output sequence given the input sequence, by keeping track of multiple candidate sequences and expanding them based on their probabilities. This can improve the quality and diversity of the output, compared to using a greedy or random search. | ||
+ | ** <b>Convolutional Neural Network (CNN)</b>: is another type of [[Deep Learning]] model that can process sequential data such as time series. It uses layers of filters that can extract features from local regions of the input data, and it can capture complex patterns and relationships in the data. For example, CNN can be used to forecast an avalanche in a famous ski resort based on past snowfall and temperature data. | ||
+ | ** <b>[[Spatial-Temporal Dynamic Network (STDN)]]</b>: a [[Deep Learning]] framework proposed to address the challenge of modeling complex spatial dependencies and temporal dynamics in traffic prediction. A flow gating mechanism is introduced to learn the dynamic similarity between locations, and a periodically shifted attention mechanism is designed to handle long-term periodic temporal shifting. This approach has been shown to be effective in predicting taxi demand | ||
+ | * Other: | ||
+ | ** <b>Gaussian Process (GP)</b>: is a type of probabilistic model that can handle uncertainty and noise in time series data. It uses a function that defines how similar any two points in the input space are, and it produces a distribution over possible outputs for any given input. For example, GP can be used to forecast the depletion level of stocks in stores based on past sales and inventory data. | ||
+ | ** <b>[[End-to-End Speech]]</b>: translation is an approach to speech translation that is gaining high interest from the research world in the last few years. It consists of using a single [[Deep Learning]] model that learns to generate translated text of the input audio in an end-to-end fashion. This approach, known as “end-to-end” or “direct” ST, supposes many advantages over the former, such as avoiding the concatenation of errors, the direct use of prosodic from speech and a lower inference time. | ||
+ | ** <b>[[(Tree) Recursive Neural (Tensor) Network (RNTN)]]</b>: type of [[Neural Network]] that is mostly used for natural language processing. It has a tree structure with a neural net at each node. The purpose of these nets is to analyze data that have a hierarchy of structure. An RNTN is a powerful tool for deciphering and labeling patterns. Structurally, an RNTN is a binary tree with three nodes: a root and two leaves. The root and leaf nodes are not neurons, but instead, they are groups of neurons – the more complicated the input data, the more neurons are required. RNTNs have been successfully applied to [[Sentiment Analysis]], where the input is a sentence in its parse tree structure, and the output is the classification for the input sentence, i.e., whether the meaning is very negative, negative, neutral, positive, or very positive | ||
+ | ** <b>[[Temporal Difference (TD) Learning]]</b>: refers to a class of model-free [[Reinforcement Learning (RL)]] methods which learn by bootstrapping from the current estimate of the value function. These methods sample from the environment, like Monte Carlo methods, and perform updates based on current estimates, like dynamic programming methods. While Monte Carlo methods only adjust their estimates once the final outcome is known, TD methods adjust predictions to match later, more accurate, predictions about the future before the final outcome is known. | ||
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+ | <hr> | ||
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+ | <i>[https://iohk.io/en/blog/posts/2021/10/27/ouroboros-chronos-provides-the-first-high-resilience-cryptographic-time-source-based-on-blockchain/ Time is an indispensable concept within computer programs and applications. Without this concept, we would not be able to access any transport layer security (TLS) based websites, exchange data, or utilize various cryptographic algorithms. | Olga Hryniuk - Input Output] </i> | ||
<hr> | <hr> | ||
− | [ | + | = What Time Is It? = |
+ | * [https://www.darpa.mil/news-events/2019-08-20 DARPA Making Progress on Miniaturized Atomic Clocks for Future PNT Applications | ][[Defense#US Defense Advanced Research Projects Agency (DARPA)|US Defense Advanced Research Projects Agency (DARPA)]] | ||
− | <img src=" | + | <img src="https://www.darpa.mil/DDM_Gallery/nist-csac-619-316.jpg" width="1000"> |
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− | <youtube> | + | <youtube>hzLTgtFaPLY</youtube> |
− | <b> | + | <b>Atomic Clocks Are Reinventing Time |
− | </b><br> | + | </b><br>Though humans don't experience it in their daily lives, gravity and movement can change how time elapses. Ultra-precise atomic clocks are now able to measure these tiny changes, known as time dilation. It's a technological advance that could revolutionize our understanding of time. |
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− | <youtube> | + | <youtube>h07U0fWZaXM</youtube> |
− | <b> | + | <b>How Far Back is the James Webb able to See? with Dr. Klaus Pontoppidan |
− | </b><br> | + | </b><br>How Far Back is the James Webb able to See? |
+ | Project scientist for the James Webb Space Telescope Dr. Klaus Pontoppidan explains the science revealed in the first full-color images released from the JWST. | ||
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<youtube>URK9Z2G71j8</youtube> | <youtube>URK9Z2G71j8</youtube> | ||
<b>A Brief History of Timekeeping | <b>A Brief History of Timekeeping | ||
− | </b><br>SciShow It’s time for another leap second! Join SciShow as we celebrate by exploring the long and strange history of timekeeping. Hosted by: Michael Aranda Dooblydoo thanks go to the following Patreon supporters -- we couldn't make SciShow without them! Shout out to Justin Ove, Justin Lentz, David Campos, John Szymakowski, Peso255, Jeremy Peng, Avi Yaschin, and Fatima Iqbal. Like SciShow? Want to help support us, and also get things to put on your walls, cover your torso and hold your liquids? Check out our awesome products over at DFTBA Records: | + | </b><br>SciShow It’s time for another leap second! Join SciShow as we celebrate by exploring the long and strange history of timekeeping. Hosted by: Michael Aranda Dooblydoo thanks go to the following Patreon supporters -- we couldn't make SciShow without them! Shout out to Justin Ove, Justin Lentz, David Campos, John Szymakowski, Peso255, Jeremy Peng, Avi Yaschin, and Fatima Iqbal. Like SciShow? Want to help support us, and also get things to put on your walls, cover your torso and hold your liquids? Check out our awesome products over at DFTBA Records: https://dftba.com/scishow Or help support us by becoming our patron on Patreon: https://www.patreon.com/scishow |
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<youtube>1JBHG6fipr4</youtube> | <youtube>1JBHG6fipr4</youtube> | ||
<b>This 3D Quantum Gas Clock Could Redefine Time | <b>This 3D Quantum Gas Clock Could Redefine Time | ||
− | </b><br>Seeker Time may be a human construct but that hasn't stopped physicists from perfecting it. Read More: JILA’s 3-D Quantum Gas Atomic Clock Offers New Dimensions in Measurement | + | </b><br>Seeker Time may be a human construct but that hasn't stopped physicists from perfecting it. Read More: JILA’s 3-D Quantum Gas Atomic Clock Offers New Dimensions in Measurement https://www.nist.gov/news-events/news... “JILA physicists have created an entirely new design for an atomic clock, in which strontium atoms are packed into a tiny three-dimensional (3-D) cube at 1,000 times the density of previous one-dimensional (1-D) clocks. In doing so, they are the first to harness the ultra-controlled behavior of a so-called “quantum gas” to make a practical measurement device.” Jun Ye: Let There Be Light (and Thus, Time) https://www.youtube.com/watch?v=bbBmk... Dr. Jun Ye, professor of physics at the University of Colorado at Boulder and a fellow of both the National Institute of Standards and Technology and JILA, explains how lasers are used to manipulate atoms inside and out for ultra-precise clocks. Ultra-Accurate Clocks Lead Search for New Laws of Physics https://www.quantamagazine.org/ultra-.. Atomic clocks are letting physicists tighten the lasso around elusive phenomena such as dark matter. Sign Up For The Seeker Newsletter Here - https://bit.ly/1UO1PxI Seeker inspires us to see the world through the lens of science and evokes a sense of curiosity, optimism and adventure. |
− | Visit the Seeker website | + | Visit the Seeker website https://www.seeker.com/ |
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<b>David Wineland Public Lecture: Keeping Better Time - The Era of Optical Atomic Clocks | <b>David Wineland Public Lecture: Keeping Better Time - The Era of Optical Atomic Clocks | ||
− | </b><br>Perimeter Institute for Theoretical Physics David Wineland, 2012 Nobel Laureate in Physics, will explore the theoretical and technological know-how needed to build ultra-precise atomic clocks during his Perimeter Institute Public Lecture on Wednesday, Nov. 4, 2015. Find information about future Perimeter institute Public Lectures here: | + | </b><br>Perimeter Institute for Theoretical Physics David Wineland, 2012 Nobel Laureate in Physics, will explore the theoretical and technological know-how needed to build ultra-precise atomic clocks during his Perimeter Institute Public Lecture on Wednesday, Nov. 4, 2015. Find information about future Perimeter institute Public Lectures here: https://ow.ly/UiOr5 |
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<b>A brief History of the Calendar and Time Keeping | <b>A brief History of the Calendar and Time Keeping | ||
</b><br>School of Business and Economics Tuesday 23 February, 20h00 • Aula Minderbroedersberg 4-6 • Dr. Donna Carroll, Lecturer of Physics, Maastricht University How many times a day do you check your calendar or look at your clock? These days our lives are driven by deadlines, schedules and timetables. Time and its many divisions (hours, days, weeks, months, and years) have completely shaped our lives and yet we seldom take the time to consider how these concepts arose. The calendar is inextricably linked to the mechanics of our solar system, and the way in which we describe our periods of time has arisen from ancient speculation in astronomy, mathematics and religion. | </b><br>School of Business and Economics Tuesday 23 February, 20h00 • Aula Minderbroedersberg 4-6 • Dr. Donna Carroll, Lecturer of Physics, Maastricht University How many times a day do you check your calendar or look at your clock? These days our lives are driven by deadlines, schedules and timetables. Time and its many divisions (hours, days, weeks, months, and years) have completely shaped our lives and yet we seldom take the time to consider how these concepts arose. The calendar is inextricably linked to the mechanics of our solar system, and the way in which we describe our periods of time has arisen from ancient speculation in astronomy, mathematics and religion. | ||
− | In this talk, Donna Carroll will provide a brief history of our calendar and an introduction to time measurement. A fascinating field where astronomy, astrology, mathematics, politics, agriculture, superstition and religion all come together. For more information please visit: SG Maastricht: | + | In this talk, Donna Carroll will provide a brief history of our calendar and an introduction to time measurement. A fascinating field where astronomy, astrology, mathematics, politics, agriculture, superstition and religion all come together. For more information please visit: SG Maastricht: https://www.sg.unimaas.nl/ Talkin'Business: https://www.talkinbusiness.nl/ University Maastricht: https://www.maastrichtuniversity.nl/ |
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<youtube>CKJuC5CUMgU</youtube> | <youtube>CKJuC5CUMgU</youtube> | ||
<b>WSU: Space, Time, and Einstein with Brian Greene | <b>WSU: Space, Time, and Einstein with Brian Greene | ||
− | </b><br>World Science Festival Join Brian Greene, acclaimed physicist and author, on a wild ride into the mind of Albert Einstein, revealing deep aspects of the world that defy everyday experience. Using a visually rich canvas of animations, Greene leads you through all the startling conclusions of special relativity, from time travel to space warps to E = mc2. In the span of 2+ hours, this short master class will change your conception of reality. This is a mostly non-mathematical version of the WSU Master Class “Special Relativity with Brian Greene.” | + | </b><br>World Science Festival Join Brian Greene, acclaimed physicist and author, on a wild ride into the mind of Albert Einstein, revealing deep aspects of the world that defy everyday experience. Using a visually rich canvas of animations, Greene leads you through all the startling conclusions of special relativity, from time travel to space warps to E = mc2. In the span of 2+ hours, this short master class will change your conception of reality. This is a mostly non-mathematical version of the WSU Master Class “Special Relativity with Brian Greene.” https://youtu.be/XFV2feKDK9E #WorldSciU |
The Special Theory of Relativity - 00:05 | The Special Theory of Relativity - 00:05 | ||
Speed - 00:05:50 | Speed - 00:05:50 | ||
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<youtube>g54sxScqd-c</youtube> | <youtube>g54sxScqd-c</youtube> | ||
<b>The Importance of Time Synchronization - I&C Short Tips | <b>The Importance of Time Synchronization - I&C Short Tips | ||
− | </b><br>Affinity Energy Learn more at | + | </b><br>Affinity Energy Learn more at https://affinityenergy.com - Time synchronization is overlooked in terms of specification of applications in terms of hardware, proper controls, and data acquisition. Here's an example of why time synchronization is so important in a double ended substation. |
+ | |} | ||
+ | |}<!-- B --> | ||
+ | |||
+ | |||
+ | <hr> | ||
+ | |||
+ | <b><i> | ||
+ | The Earth's rotation is so accurate it varies only in milliseconds ...do you feel the Earth rotation slowing down? | ||
+ | </i></b> | ||
+ | |||
+ | <hr> | ||
+ | |||
+ | == <span id="Light Clock 1905 - Einstein's Thought Experiment"></span>Light Clock 1905 - Einstein's Thought Experiment == | ||
+ | |||
+ | Imagine you have a special clock that works with light. This clock has two mirrors facing each other, and a beam of light bounces up and down between them. Every time the light goes from the bottom mirror to the top and back down, it counts as one tick of the clock. Einstein's light clock thought experiment shows that when things move fast, time slows down for them. This surprising idea helps us understand the nature of time and motion in our universe. Now, let's think about this clock in two different situations. | ||
+ | |||
+ | |||
+ | <b>Situation 1: Standing Still: </b>First, picture the clock sitting on a table, not moving at all. The light goes straight up to the top mirror and straight back down to the bottom mirror. If you measured the time it takes for the light to do this, you would see it takes a certain amount of time for one tick. | ||
+ | |||
+ | <b>Situation 2: Moving Clock: </b>Now, imagine you place the clock on a skateboard and push it so it's moving. As the clock moves, the light beam has to travel a different path. Instead of going straight up and down, it now has to go in a diagonal path because the mirrors are moving while the light is traveling. It's like when you throw a ball to a friend while running; the ball has to cover more distance because both of you are moving. | ||
+ | |||
+ | |||
+ | <i>What This Means</i> ... Because the light in the moving clock has to travel a longer, diagonal path, it takes more time for one tick to happen compared to when the clock is standing still. This means that for someone watching the moving clock, time appears to run slower for the moving clock compared to a clock that's not moving. This idea is called time dilation. It means that time actually passes at different rates depending on how fast something is moving. If you were riding on the skateboard with the clock, you wouldn't notice anything different about the clock's ticks. But someone standing still and watching you would see that your clock ticks more slowly. | ||
+ | |||
+ | |||
+ | </i>Why It Matters</i> ... This thought experiment helps us understand that time isn't the same everywhere and can be different depending on how fast things are moving. This concept is a key part of Einstein's theory of special relativity, which helps scientists understand how the universe works, especially when things are moving very fast, like spaceships or particles in a collider. | ||
+ | |||
+ | <youtube>b2Vd9HGB5XQ</youtube> | ||
+ | |||
+ | = <span id="Precision Time Protocol (PTP)"></span>Precision Time Protocol (PTP) = | ||
+ | [https://www.youtube.com/results?search_query=Precision+Time+Protocol+PTP+artificial+intelligence+ai YouTube search...] | ||
+ | [https://www.google.com/search?q=Precision+Time+Protocol+PTP+artificial+intelligence+ai ...Google search] | ||
+ | |||
+ | * [https://endruntechnologies.com/pdf/PTP-1588.pdf Precision Time Protocol PTP-1588 | IEEE] ...High precision clock synchronization that computes latency and offset | ||
+ | * [https://engineering.fb.com/2022/11/21/production-engineering/precision-time-protocol-at-meta/ How Precision Time Protocol is being deployed at Meta | Oleg Obleukhov & Ahmad Byagowi - CONNECTIVITY, NETWORKING & TRAFFIC, OPEN SOURCE, PRODUCTION ENGINEERING, UNCATEGORIZED, WEB] | ||
+ | * [https://www.juniper.net/documentation/us/en/software/junos/time-mgmt/topics/topic-map/precion-time-protocol.html#id_bpx_2ch_lrb PTP IEEE 1588v2 | Juniper Networks] ...Time Management Administration Guide | ||
+ | |||
+ | The Precision Time Protocol (PTP) is a protocol used to synchronize clocks throughout a computer network. On a local area network, it achieves clock accuracy in the sub-microsecond range, making it suitable for measurement and control systems.[1] PTP is currently employed to synchronize financial transactions, mobile phone tower transmissions, sub-sea acoustic arrays, and networks that require precise timing but lack access to satellite navigation signals.[https://en.wikipedia.org/wiki/Precision_Time_Protocol Wikipedia] | ||
+ | |||
+ | Overall, its structure is similar to NTP in that there are different levels within it and GPS satellites can serve as its time source. However, the major difference between Network Time Protocol (NTP) and PTP is that PTP is accurate to microseconds, meaning that it is more exact than NTP | ||
+ | |||
+ | |||
+ | |||
+ | {|<!-- T --> | ||
+ | | valign="top" | | ||
+ | {| class="wikitable" style="width: 550px;" | ||
+ | || | ||
+ | <youtube>kJcmPg-qIFA</youtube> | ||
+ | <b>Precision Time Protocol (PTP) IEEE-1588 | ||
+ | </b><br>a basic overview of how the Precision Time Protocol (PTP) is used to synchronize, and set the correct time of day within a network. Potentially Nano Second accuracy can be achieved. | ||
+ | |} | ||
+ | |<!-- M --> | ||
+ | | valign="top" | | ||
+ | {| class="wikitable" style="width: 550px;" | ||
+ | || | ||
+ | <youtube>WX5E8x3pYqg</youtube> | ||
+ | <b>How Computers Synchronize Their Clocks - NTP and PTP Explained | ||
+ | </b><br>It is important for computers to know the correct time. Everything from online shopping to stock market trades rely on accurate time keeping. But how do computers know what time it is? Here is a quick look at how computers synchronize their clocks including a look at NTP and PTP. | ||
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= <span id="Positioning, Navigation and Timing (PNT)"></span>Positioning, Navigation and Timing (PNT) = | = <span id="Positioning, Navigation and Timing (PNT)"></span>Positioning, Navigation and Timing (PNT) = | ||
− | [ | + | [https://www.youtube.com/results?search_query=Navigation+positioning+Aid+radar+waves+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=Navigation+positioning+Aid+radar+waves+artificial+intelligence+ai ...Google search] |
+ | * [[Time]] ... [[Time#Positioning, Navigation and Timing (PNT)|PNT]] ... [[Time#Global Positioning System (GPS)|GPS]] ... [[Causation vs. Correlation#Retrocausality| Retrocausality]] ... [[Quantum#Delayed Choice Quantum Eraser|Delayed Choice Quantum Eraser]] ... [[Quantum]] | ||
* [[Case Studies]] | * [[Case Studies]] | ||
** [[Smart Cities]] | ** [[Smart Cities]] | ||
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** [[Defense]] | ** [[Defense]] | ||
* [[Autonomous Drones]] | * [[Autonomous Drones]] | ||
− | * [ | + | * [https://thenextweb.com/artificial-intelligence/2019/03/04/deepmind-teaches-ai-to-follow-navigational-directions-like-humans/ Deepmind teaches AI to follow navigational directions like humans | Tristan Greene] |
− | * [ | + | * [https://en.wikipedia.org/wiki/History_of_navigation History of Navigation | Wikipedia] |
− | ** [ | + | ** [https://www.amazon.com/Longitude-Genius-Greatest-Scientific-Problem/dp/080271529X/ref=sr_1_1?crid=3KYYCAGJ2JJD6 Longitude: The True Story of a Lone Genius Who Solved the Greatest Scientific Problem of His Time | Dava Sobel][[Amazon]] ...[https://tpplayer-video-featured-snippets.googleusercontent.com/player.html?video=x2z5wg8&start=0&end=70 Video: "Lost at Sea: The Search for Longitude"] [https://www.pbs.org/wgbh/nova/longitude/ Nova companion Web site] |
− | * [ | + | * [https://www.dhs.gov/science-and-technology/pnt-program Department of Homeland Security (DHS) Science and Technology (S&T) Positioning, Navigation, and Timing (PNT) Program] |
− | * [ | + | * [https://www.faa.gov/air_traffic/publications/atpubs/aim_html/chap1_section_1.html Navigation Aids | Department of Transportation, Federal Aviation Administration] |
− | * [ | + | * [https://www.vectornav.com/products/vn-200 VN-300 | Vectornav] ...miniature, high-performance Dual Antenna Global Navigation Satellite Systems (GNSS)-Aided Inertial Navigation System (INS) that combines micro-electromechanical systems (MEMS) inertial sensors, two high-sensitivity GNSS receivers, and advanced Kalman filtering algorithms to provide optimal estimates of position, velocity, and orientation. |
− | Navigation is a field of study that focuses on the process of monitoring and controlling the movement of a craft or vehicle from one place to another.[1] The field of navigation includes four general categories: land navigation, marine navigation, aeronautic navigation, and space navigation. [ | + | Navigation is a field of study that focuses on the process of monitoring and controlling the movement of a craft or vehicle from one place to another.[1] The field of navigation includes four general categories: land navigation, marine navigation, aeronautic navigation, and space navigation. [https://en.wikipedia.org/wiki/Navigation Navigation | Wikipedia] |
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<b>How did Planes Fly Before GPS? | <b>How did Planes Fly Before GPS? | ||
</b><br>How did Planes Fly Before GPS?: | </b><br>How did Planes Fly Before GPS?: | ||
− | The Wright Brothers first took to the skies in 1903 but GPS wasn't publicly available until 1983, so how did planes traverse the world in those 80 years? From celestial navigation to dead reckoning, to the firsts forms of radio telemetry (like adock range stations and LORAN) we'll be discussing them all in this video. Discord: | + | The Wright Brothers first took to the skies in 1903 but GPS wasn't publicly available until 1983, so how did planes traverse the world in those 80 years? From celestial navigation to dead reckoning, to the firsts forms of radio telemetry (like adock range stations and LORAN) we'll be discussing them all in this video. Discord: https://discord.gg/DUvyS8n Amazon Affiliate Link*: https://amzn.to/3kNTHhK |
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== <span id="Global Positioning System (GPS)"></span>Global Positioning System (GPS) == | == <span id="Global Positioning System (GPS)"></span>Global Positioning System (GPS) == | ||
− | [ | + | [https://www.youtube.com/results?search_query=GPS+Global+Positioning+GNSS+clock+time+keeping+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=GPS+Global+Positioning+GNSS+clock+time+keeping+artificial+intelligence+ai ...Google search] |
− | * [[ | + | * [[Time]] ... [[Time#Positioning, Navigation and Timing (PNT)|PNT]] ... [[Time#Global Positioning System (GPS)|GPS]] ... [[Causation vs. Correlation#Retrocausality| Retrocausality]] ... [[Quantum#Delayed Choice Quantum Eraser|Delayed Choice Quantum Eraser]] ... [[Quantum]] |
− | * GPS has been copied by [[Government Services#Russia|Russia's]] [ | + | * [[Astronomy]] |
− | * [ | + | * GPS has been copied by [[Government Services#Russia|Russia's]] [https://en.wikipedia.org/wiki/GLONASS GLONASS], Europe’s [https://en.wikipedia.org/wiki/Galileo_(satellite_navigation) Galileo], [[Government Services#China|China's]] [https://en.wikipedia.org/wiki/BeiDou BeiDou], India’s IRNSS, and Japan’s [https://en.wikipedia.org/wiki/Quasi-Zenith_Satellite_System QZSS] |
− | * RoadTagger: [ | + | * [https://ieeexplore.ieee.org/document/5608862 Artificial intelligence in GPS navigation systems | Jeffrey L. Duffany] |
− | * [ | + | * RoadTagger: [https://newatlas.com/technology/gps-system-ai-upgrade/ GPS system upgrade utilizes AI to make sure you're in the right lane | David Nield - New Atlas] ...[https://www.inceptivemind.com/artificial-intelligence-roadtagger-digital-maps-improve-gps-navigation/11525/ Artificial intelligence to update digital maps and improve GPS navigation | Amit Malewar - InceptiveMind] |
− | * [ | + | * [https://www.gps.gov/ GPS.gov] ...[https://www.gps.gov/applications/timing/ Timing] |
− | * [ | + | * [https://insidegnss.com/ Inside GNSS] ...Global Navigation Satellite Systems |
− | * [ | + | * [https://www.space.com/19794-navstar.html Navstar | Space.com] ...is a network of U.S. satellites that provide GPS services |
− | * [ | + | * [https://wtop.com/science/2020/11/spacex-launches-third-generation-gps-navigation-satellite/ SpaceX launches third-generation GPS navigation satellite | CBS News] ...GPS-3 satellite — the fourth in a series of more powerful third-generation navigation stations built by Lockheed Martin — was expected to be deployed about a 90 minutes after liftoff. Assuming tests and checkout go well, it will join a globe-spanning constellation of 31 GPS satellites. |
− | * [ | + | * [https://www.militaryaerospace.com/sensors/article/14187009/navigation-and-guidance-asic-gps Air Force asks three U.S. contractors to develop miniature ASIC technology for next-gen GPS receivers | John Keller - Military & Aerospace Electronics] ...small low-power-consumption GPS enabling technologies to include a next-generation ASIC for secure GPS land navigation. |
− | * [ | + | * [https://spectrum.ieee.org/tech-talk/aerospace/satellites/final-piece-of-chinas-beidou-navigation-satellite-system-comes-online [[Government Services#China|China]] Launches Beidou, Its Own Version of GPS | Andrew Jones - IEEE Spectrum] ...[[Government Services#China|China]] places the final Beidou navigation system satellite into orbit |
+ | * [https://eurasiantimes.com/the-indian-navigation-satellite-system-irnss-approved-by-imp-for-global-operations/ Big News For ISRO! Indian Navigation System (IRNSS) Gets Approval By IMP For Global Operations | Smriti Chaudhary - The EurAsuan Times] | ||
− | GPS receivers that use the L5 band can pinpoint to within 30 centimeters or 11.8 inches. The GPS concept is based on [[time]] and the known position of GPS specialized satellites. The satellites carry very stable atomic clocks that are synchronized with one another and with the ground clocks. Any drift from time maintained on the ground is corrected daily. In the same manner, the satellite locations are known with great precision. GPS receivers have clocks as well, but they are less stable and less precise. Each GPS satellite continuously transmits a radio signal containing the current time and data about its position. Since the speed of radio waves is constant and independent of the satellite speed, the time delay between when the satellite transmits a signal and the receiver receives it is proportional to the distance from the satellite to the receiver. A GPS receiver monitors multiple satellites and solves equations to determine the precise position of the receiver and its deviation from true time. At a minimum, four satellites must be in view of the receiver for it to compute four unknown quantities (three position coordinates and clock deviation from satellite time). [ | + | GPS receivers that use the L5 band can pinpoint to within 30 centimeters or 11.8 inches. The GPS concept is based on [[time]] and the known position of GPS specialized satellites. The satellites carry very stable atomic clocks that are synchronized with one another and with the ground clocks. Any drift from time maintained on the ground is corrected daily. In the same manner, the satellite locations are known with great precision. GPS receivers have clocks as well, but they are less stable and less precise. Each GPS satellite continuously transmits a radio signal containing the current time and data about its position. Since the speed of radio waves is constant and independent of the satellite speed, the time delay between when the satellite transmits a signal and the receiver receives it is proportional to the distance from the satellite to the receiver. A GPS receiver monitors multiple satellites and solves equations to determine the precise position of the receiver and its deviation from true time. At a minimum, four satellites must be in view of the receiver for it to compute four unknown quantities (three position coordinates and clock deviation from satellite time). [https://en.wikipedia.org/wiki/Global_Positioning_System Global Positioning System | Wikipedia] |
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<youtube>aDWbpRXblMk</youtube> | <youtube>aDWbpRXblMk</youtube> | ||
<b>Satellite Navigation Systems Overview with John Pottle | <b>Satellite Navigation Systems Overview with John Pottle | ||
− | </b><br>Royal Institute of Navigation. John Pottle, Director of the Royal Institute of Navigation, will put into context what the hundreds of navigation satellites in space are all for and how they work together. This webinar will explain the similarities and differences between global and regional satellite navigation systems, how they are co-ordinated, and by whom. The space-based augmentation systems will also be covered: what are these and how do they help? *During the webinar Q&A there was a question about whether or not GNSS could be used for moon missions - please see: Website: | + | </b><br>Royal Institute of Navigation. John Pottle, Director of the Royal Institute of Navigation, will put into [[context]] what the hundreds of navigation satellites in space are all for and how they work together. This webinar will explain the similarities and differences between global and regional satellite navigation systems, how they are co-ordinated, and by whom. The space-based augmentation systems will also be covered: what are these and how do they help? *During the webinar Q&A there was a question about whether or not GNSS could be used for moon missions - please see: Website: https://rin.org.uk/ |
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<b>GPS, How does it work? | ICT #12 | <b>GPS, How does it work? | ICT #12 | ||
− | </b><br>GPS has already become an integral part of our lives, and you can see a few useful applications from these examples. GPS is really an interesting technology. It uses a system of 24 satellites continuously orbiting the earth, and requires at least four satellites to track your location; it uses an atomic clock, and the time error of your mobile phone is also a matter of great concern. Moreover, Albert Einstein’s theory of relativity plays an important role in GPS technology, finally, a real-life application for the theory of relativity! Let’s put aside all these complications and understand the technology of GPS in a step by step and logical manner. Be a Learn Engineering supporter or contributor: | + | </b><br>GPS has already become an integral part of our lives, and you can see a few useful applications from these examples. GPS is really an interesting technology. It uses a system of 24 satellites continuously orbiting the earth, and requires at least four satellites to track your location; it uses an atomic clock, and the time error of your mobile phone is also a matter of great concern. Moreover, Albert Einstein’s theory of relativity plays an important role in GPS technology, finally, a real-life application for the theory of relativity! Let’s put aside all these complications and understand the technology of GPS in a step by step and logical manner. Be a Learn Engineering supporter or contributor: https://www.youtube.com/channel/UCqZQ... |
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<b>GPS vs AI: The Challenges of Losing Satellite Signal | Roborace | <b>GPS vs AI: The Challenges of Losing Satellite Signal | Roborace | ||
− | </b><br>How do trees affect satellite and GPS acquisition during a Roborace test run? #Education #Roborace #AutonomousVehicles Trees have a detrimental effect on the GPS and Satellite system for the DevBot 2.0, as it is one of the most important factors for autonomous racing. Roborace is the world’s first competition for human + machine teams, using both self-driving and manually-controlled cars. Race formats will feature new forms of immersive entertainment to engage the next generation of racing fans. Through sport, innovations in machine-driven technologies will be accelerated. Roborace will redefine the way you think about autonomous technology. To be a part of our autonomous journey, subscribe to our channel: | + | </b><br>How do trees affect satellite and GPS acquisition during a Roborace test run? #Education #Roborace #AutonomousVehicles Trees have a detrimental effect on the GPS and Satellite system for the DevBot 2.0, as it is one of the most important factors for autonomous racing. Roborace is the world’s first competition for human + machine teams, using both self-driving and manually-controlled cars. Race formats will feature new forms of immersive entertainment to engage the next generation of racing fans. Through sport, innovations in machine-driven technologies will be accelerated. Roborace will redefine the way you think about autonomous technology. To be a part of our autonomous journey, subscribe to our channel: https://goo.gl/TNbPAB |
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− | <youtube> | + | <youtube>0k2QdX6yZiw</youtube> |
− | <b> | + | <b>Brian Cox Just Announced Mind-Bending Theory Of Time |
− | </b><br> | + | </b><br>Everything in our universe seems perfect. There are laws governing the entire universe, but certain mysteries have remained unsolved despite decades of research. Why does time travel in one direction? What is the nature of reality? Why does Gravity exist? Why does time slow down when we travel at the speed of light? These are questions that have fascinated us for millennia. |
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<b>A9G GPS & GPRS Module Tutorial | Ai-Thinker | AT Commands | <b>A9G GPS & GPRS Module Tutorial | Ai-Thinker | AT Commands | ||
− | </b><br>PCBWAY: | + | </b><br>PCBWAY: https://www.pcbway.com/ Wanna help us out? [https://github.com/akarsh98/A9G-Supporting-material GitHub] Consider donating any amount: https://www.paypal.me/akarsh98 CETech@FB: https://www.facebook.com/CETech4u/ Our email: akarshagarwal98@gmail.com Track: Raiko - Revenger [NCS Release] Music provided by NoCopyrightSounds. Watch: https://youtu.be/Vj_V0RfdTSY Free Download / Stream: https://ncs.io/Revenger [[Meta|Facebook]] |
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− | <youtube> | + | <youtube>8eOEhphQz6k</youtube> |
− | <b> | + | <b>Using AI to get city and weather from GPS |
− | </b><br> | + | </b><br>A quick demo of how Noodl AI and the Function Co-pilot node can be used to call different API's from a simple text prompts to gather location and weather data from location coordinates. |
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=== <span id="Deep-Space Positioning System (DPS)"></span>Deep-Space Positioning System (DPS) === | === <span id="Deep-Space Positioning System (DPS)"></span>Deep-Space Positioning System (DPS) === | ||
− | [ | + | [https://www.youtube.com/results?search_query=outer+space+Positioning+Navigation+Timing+PNT+GPS+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=outer+space+Positioning+Navigation+Timing+PNT+GPS+artificial+intelligence+ai ...Google search] |
− | * [ | + | * [https://futurism.com/the-byte/planetary-navigation-nasa-space-gps NASA is Making An AI-Based GPS For Space | Kristin Houser] |
− | * [ | + | * [https://frontierdevelopmentlab.org/#!/ Frontier Development Lab (FDL)] ...Artificial Intelligence Research for Space Science, Exploration & All Humankind |
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<b>Space Is Hard | There Is No GPS in Space | <b>Space Is Hard | There Is No GPS in Space | ||
− | </b><br>There is no mapping app for deep space, at least not yet. If we're going to explore there we'll need new navigation tools. Here's how NASA is going to keep its rockets on target. Still haven’t subscribed to WIRED on YouTube? | + | </b><br>There is no mapping app for deep space, at least not yet. If we're going to explore there we'll need new navigation tools. Here's how NASA is going to keep its rockets on target. Still haven’t subscribed to WIRED on YouTube? https://wrd.cm/15fP7B7 CONNECT WITH WIRED Web: https://wired.com |
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− | |||
== <span id="Jamming and Spoofing"></span>Jamming and Spoofing == | == <span id="Jamming and Spoofing"></span>Jamming and Spoofing == | ||
− | [ | + | [https://www.youtube.com/results?search_query=Jamming+Spoofing+Positioning+Navigation+Timing+PNT+GPS+GNSS+GB-GRAM+INS+CSAC+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=Jamming+Spoofing+Positioning+Navigation+Timing+PNT+GPS+GNSS+GB-GRAM+INS+CSAC+artificial+intelligence+ai ...Google search] |
− | * [ | + | * [https://RNTFnd.org/ The Resilient Navigation and Timing Foundation] |
− | ** [ | + | ** [https://rntfnd.org/wp-content/uploads/Multi-LayerFinal.jpg Multi‐level resiliency model] |
− | ** [ | + | ** [https://rntfnd.org/2020/11/27/china-research-paper-on-differential-eloran-sensors-journal/ China Research Paper on Differential eLoran – Sensors Journal] |
− | ** [ | + | ** [https://rntfnd.org/wp-content/uploads/Resilient-National-Timing-Architecture-16-Oct-2020.pdf A Resilient National Timing Architecture – 16 October 2020] |
− | ** [ | + | ** [https://rntfnd.org/2020/12/05/gps-jamming-spoofing-2020-year-in-review-spirents-guy-buesnel/ GPS Jamming & Spoofing, 2020 Year in Review – Spirent’s Guy Buesnel] |
− | ** [ | + | ** [https://rntfnd.org/2021/06/05/the-russia-trap-single-points-of-failure-gps/ “The Russia Trap” – Single Points of Failure & GPS | Blog Editor / George Beebe] |
− | * [ | + | * [https://www.dhs.gov/publication/st-resilient-pnt-conformance-framework Department of Homeland Security (DHS) Science and Technology (S&T) Resilient Positioning, Navigation, and Timing (PNT) Conformance Framework] |
− | * [ | + | * [https://www.forbes.com/sites/steveforbes/2020/11/13/the-space-force-a-conversation-with-united-states-secretary-of-the-air-force-barbara-barrett/?sh=61d1c90a41fa The Space Force: A Conversation With United States Secretary Of The Air Force Barbara Barrett | Steve Forbes - Forbes] ... We are vulnerable. For example, the U.S. and the global economy are totally dependent on satellites, most especially the GPS, which is operated by the Space Force. |
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<youtube>L2fZGVVH5lg</youtube> | <youtube>L2fZGVVH5lg</youtube> | ||
<b>2019-06-19_The History of GPS Spoofing | <b>2019-06-19_The History of GPS Spoofing | ||
− | </b><br>Incose Chesapeake Mr Dana Goward discussed the development of Global Positioning System (GPS) spoofing from a fiction account in film to being an everyday problem. | + | </b><br>Incose Chesapeake Mr Dana Goward discussed the [[development]] of Global Positioning System (GPS) spoofing from a fiction account in film to being an everyday problem. |
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=== <span id="Assured-Positioning, Navigation and Timing (A-PNT)"></span>Assured-Positioning, Navigation and Timing (A-PNT) === | === <span id="Assured-Positioning, Navigation and Timing (A-PNT)"></span>Assured-Positioning, Navigation and Timing (A-PNT) === | ||
− | [ | + | [https://www.youtube.com/results?search_query=Assured+Positioning+Navigation+Timing+PNT+GPS+GNSS+GB-GRAM+INS+CSAC+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=Assured+Positioning+Navigation+Timing+PNT+GPS+GNSS+GB-GRAM+INS+CSAC+artificial+intelligence+ai ...Google search] |
* [[Cybersecurity]] | * [[Cybersecurity]] | ||
− | * [ | + | * [https://www.esd.whs.mil/Portals/54/Documents/DD/issuances/dodi/465008p.pdf DOD INSTRUCTION 4650.08 Positioning, Navigation and Timing Warfare] |
− | ** [ | + | ** [https://www.gao.gov/products/gao-21-320sp DOD is Developing Positioning, Navigation, and Timing Technologies to Complement GPS | GAO] DOD is pursuing approaches, such as creating common standards and interfaces, to aid in integrating and fielding new PNT technologies faster and at lower cost. DOD is developing its PNT modeling and simulation capabilities to evaluate the performance of new PNT technologies. |
− | * [ | + | ** [https://www.youtube.com/watch?v=NCOcliI-nkM Tactical Radio (TR) A-PNT Overview | COL Daniel F. Kuntz, USA - TRADOC Capabilities Manager Tactical Radios (TCM TR) - U.S. Army Cyber Center of Excellence & Fort Gordon] |
− | * [ | + | * [https://apps.dtic.mil/sti/pdfs/ADA494614.pdf National Positioning, Navigation, and Timing Architecture | Lt Col Patrick Huested, USAF National Security Space Office and Paul D. Popejoy The Aerospace Corporation] |
+ | * [https://rntfnd.org/wp-content/uploads/Resilient-National-Timing-Architecture-16-Oct-2020.pdf A Resilient National Timing Architecture: Securing Today's, Enabling Tomorrow's | Dr. Marc Weiss, Dr. Patrick Diamond, and Mr. Dana A. Goward] | ||
− | * [ | + | * [https://www.curtisswrightds.com/technologies/open-architecture/assured-position-navigation-timing.html A-PNT: Assured Position, Navigation and Timing | Curtiss-Wright] |
− | * [ | + | * [https://www.express.co.uk/news/science/1358337/china-vs-us-beijing-wipe-out-gps-space-conflict-moon-mars-satellite-taiwan-joe-biden-spt China tipped to 'wipe out' GPS with 'dire consequences' after conflict catalyst exposed | Callum Hoare - The Daily Express] ...[[Government Services#China|China]] could bring the world to its knees by "wiping out" GPS, a key system used by the US military and its NATO allies, an expert on space policy has told Express.co.uk [https://www.marinelink.com/news/gps-unreliability-483109 GPS Unreliability | Dennis L. Bryant - MarineLink] |
− | Like the GPS units in many automobiles today, a simple receiver and some processing power is all that is needed for accurate navigation. But, what if the GPS satellites suddenly became unavailable due to malfunction, enemy action or simple interference, such as driving into a tunnel? Unavailability of GPS would be inconvenient for drivers on the road, but could be disastrous for military missions. [ | + | Like the GPS units in many automobiles today, a simple receiver and some processing power is all that is needed for accurate navigation. But, what if the GPS satellites suddenly became unavailable due to malfunction, enemy action or simple interference, such as driving into a tunnel? Unavailability of GPS would be inconvenient for drivers on the road, but could be disastrous for military missions. [https://www.darpa.mil/news-events/2013-04-10 Extreme Miniaturization: Seven Devices, One Chip to Navigate without GPS | ] [[Defense#US Defense Advanced Research Projects Agency (DARPA)|US Defense Advanced Research Projects Agency (DARPA)]] |
− | <img src=" | + | <img src="https://rntfnd.org/wp-content/uploads/National-PNT-Architecture.jpg" width="1000"> |
− | [ | + | [https://cms7.dot.gov/pnt/national-positioning-navigation-and-timing-pnt-architecture National Positioning, Navigation, and Timing (PNT) Architecture | U.S. Department of Transportation] |
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<youtube>rDplstBfxp0</youtube> | <youtube>rDplstBfxp0</youtube> | ||
<b>System Performance and Resilience or: What could possibly go wrong? with Prof Marek Ziebart | <b>System Performance and Resilience or: What could possibly go wrong? with Prof Marek Ziebart | ||
− | </b><br>Royal Institute of Navigation. Presenter: Prof Marek Ziebart, Director, Space Geodesy and Navigation Group, University College London Website: | + | </b><br>Royal Institute of Navigation. Presenter: Prof Marek Ziebart, Director, Space Geodesy and Navigation Group, University College London Website: https://rin.org.uk/ |
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</b><br>GPSPATRON GNSS Interference Issues What is GNSS Spoofing? Spoofing Detection Solution In this video, we describe GNSS spoofing/jamming and how to detect it. | </b><br>GPSPATRON GNSS Interference Issues What is GNSS Spoofing? Spoofing Detection Solution In this video, we describe GNSS spoofing/jamming and how to detect it. | ||
GPSPATRON is facilitated to protect GNSS-dependent infrastructure against spoofing/jamming or other GNSS signals anomalies that cause time/position accuracy degradation | GPSPATRON is facilitated to protect GNSS-dependent infrastructure against spoofing/jamming or other GNSS signals anomalies that cause time/position accuracy degradation | ||
− | More about GNSS spoofing detection: | + | More about GNSS spoofing detection: https://gpspatron.com/detecting-gnss-... Links: https://rntfnd.org/2018/04/24/5-gps-s... https://www.c4reports.org/aboveusonly... |
− | + | https://www.gpsworld.com/ https://insidegnss.com/ https://www.gps.gov/ | |
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<youtube>5T6v1HK-a6s</youtube> | <youtube>5T6v1HK-a6s</youtube> | ||
<b>When GNSS fails, what will you do? - MarRINav! | <b>When GNSS fails, what will you do? - MarRINav! | ||
− | </b><br>Royal Institute of Navigation. This webinar, called 'When GNSS fails, what will you do? - MarRINav! ' features presentations and comments form Jonathan Turner (NLA Int.), Dr Alan Grant (GLA), and Dana Goward (RNTF). The webinar provides analysis and insights from Phase 1 of the Maritime Resilience and Integrity of Navigation (MarRINav) project. To download the full transcript of Jonathan's presentation please follow this link: https://rin.org.uk/resource/resmgr/fi... Many thanks to all co-sponsors of this webinar: Resilient Navigation and Timing Foundation, Institute of Navigation, GPS World, The Maritime Executive, and of course the MarRINav project. Website: | + | </b><br>Royal Institute of Navigation. This webinar, called 'When GNSS fails, what will you do? - MarRINav! ' features presentations and comments form Jonathan Turner (NLA Int.), Dr Alan Grant (GLA), and Dana Goward (RNTF). The webinar provides analysis and insights from Phase 1 of the Maritime Resilience and Integrity of Navigation (MarRINav) project. To download the full transcript of Jonathan's presentation please follow this link: https://rin.org.uk/resource/resmgr/fi... Many thanks to all co-sponsors of this webinar: Resilient Navigation and Timing Foundation, Institute of Navigation, GPS World, The Maritime Executive, and of course the MarRINav project. Website: https://rin.org.uk/ |
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<youtube>WDATFeVTUHs</youtube> | <youtube>WDATFeVTUHs</youtube> | ||
<b>Enabling the Next Generation of GPS Technology with Supercorrelation with Dr Ramsey Faragher | <b>Enabling the Next Generation of GPS Technology with Supercorrelation with Dr Ramsey Faragher | ||
− | </b><br>Royal Institute of Navigation. Focal Point Positioning have developed a new method for processing GNSS radio signals called Supercorrelation which dramatically improves the performance of the earliest stage of radio processing. The software update removes multipath interference at the correlator level, and provides the ability to determine signal arrival angle without adding any new hardware to a standard GNSS device. In this webinar Dr Ramsey Faragher, Founder/CEO of FocalPoint will explain how the technology works, will cover some of the challenges that FocalPoint have overcome in deploying it on very low cost platforms, and will show off the new capabilities that it unlocks. Website: | + | </b><br>Royal Institute of Navigation. Focal Point Positioning have developed a new method for processing GNSS radio signals called Supercorrelation which dramatically improves the performance of the earliest stage of radio processing. The software update removes multipath interference at the correlator level, and provides the ability to determine signal arrival angle without adding any new hardware to a standard GNSS device. In this webinar Dr Ramsey Faragher, Founder/CEO of FocalPoint will explain how the technology works, will cover some of the challenges that FocalPoint have overcome in deploying it on very low cost platforms, and will show off the new capabilities that it unlocks. Website: https://rin.org.uk/ |
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<youtube>k2XQQuQrWbw</youtube> | <youtube>k2XQQuQrWbw</youtube> | ||
<b>GRCon20 - Software defined radio based Global Navigation Satellite System real time spoofing.... | <b>GRCon20 - Software defined radio based Global Navigation Satellite System real time spoofing.... | ||
− | </b><br>Software defined radio based Global Navigation Satellite System real time spoofing detection and cancellation Presented by Jean-Michel Friedt,, D. Rabus and G. Goavec-Merou at GNU Radio Conference 2020 | + | </b><br>Software defined radio based Global Navigation Satellite System real time spoofing detection and cancellation Presented by Jean-Michel Friedt,, D. Rabus and G. Goavec-Merou at GNU Radio Conference 2020 https://gnuradio.org/grcon20 Global Navigation Satellite Systems (GNSS) -- most significantly the Global Positioning System (GPS) -- have become ubiquitous to most daily activities, from positioning and navigation to long range time synchronization or distributed energy production ("smart grid"). While initially developed as a military system hardly accessible to civilians, the advent of Software Defined Radio jamming and spoofing capabilities emphasize the low security of GNSS weak signals emitted from satellites orbiting the Earth 20000 km away. While a properly spoofing signal cannot be detected after a consumer-grade receiver has decoded the radiofrequency signal, addressing at the radiofrequency wave level the signal integrity provides the solution of identifying spoofing with all satellites appearing at the same direction of arrival. This classical beamforming analysis -- Controlled Reception Pattern Antenna (CRPA) with multiple antenna reception and phase analysis -- is demonstrated using commercial, off the shelf software defined radio platform receivers (Ettus Research B210) running the real-time GNSS decoder gnss-sdr based on GNU Radio running on embedded boards such as the Raspberry Pi4. |
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<youtube>JKY03NV3C2s</youtube> | <youtube>JKY03NV3C2s</youtube> | ||
<b>PULP-DroNet -- Autonomous Artificial Intelligence-powered Nano-Drone | <b>PULP-DroNet -- Autonomous Artificial Intelligence-powered Nano-Drone | ||
− | </b><br>PULP-DroNet is a | + | </b><br>PULP-DroNet is a [[Deep Learning]]-powered visual navigation engine that enables autonomous navigation of a pocket-size quadrotor in a previously unseen environment. |
− | Thanks to PULP-DroNet the nano-drone can explore the environment, avoiding collisions also with dynamic obstacles, in complete autonomy -- no human operator, no ad-hoc external signals, and no remote laptop! This means that all the complex computations are done directly aboard the vehicle and very fast. The visual navigation engine is composed of both a software and a hardware part. The former is based on the previous DroNet [1] project developed by the RPG [2] from the University of Zürich (UZH). DroNet is a shallow convolutional neural network (CNN) which has been used to control a standard-size quadrotor in a set of environments via remote computation. The hardware soul of PULP-DroNet is embodied by the PULP-Shield an ultra-low power visual navigation module featuring a Parallel Ultra-Low-Power (PULP) GAP8 System-on-Chip (SoC) from GreenWaves Technologies [3], an ultra-low power camera, and off-chip Flash/DRAM memory; the shield is designed as a pluggable PCB for the Crazyflie 2.0 [4] nano-drone. Then, we developed a general methodology for deploying state-of-the-art | + | Thanks to PULP-DroNet the nano-drone can explore the environment, avoiding collisions also with dynamic obstacles, in complete autonomy -- no human operator, no ad-hoc external signals, and no remote laptop! This means that all the complex computations are done directly aboard the vehicle and very fast. The visual navigation engine is composed of both a software and a hardware part. The former is based on the previous DroNet [1] project developed by the RPG [2] from the University of Zürich (UZH). DroNet is a shallow convolutional neural network (CNN) which has been used to control a standard-size quadrotor in a set of environments via remote computation. The hardware soul of PULP-DroNet is embodied by the PULP-Shield an ultra-low power visual navigation module featuring a Parallel Ultra-Low-Power (PULP) GAP8 System-on-Chip (SoC) from GreenWaves Technologies [3], an ultra-low power camera, and off-chip Flash/DRAM [[memory]]; the shield is designed as a pluggable PCB for the Crazyflie 2.0 [4] nano-drone. Then, we developed a general methodology for deploying state-of-the-art [[Deep Learning]] algorithms on top of ultra-low power embedded computation nodes, like a miniaturized drone. Our novel methodology allowed us first to deploy DroNet on the PULP-Shield, and then demonstrating how it enables the execution the CNN on board the CrazyFlie 2.0 within only 64-284mW and with a throughput of 6-18 frame-per-second! Finally, we field-prove our methodology presenting a closed-loop fully working demonstration of vision-driven autonomous navigation relying only on onboard resources, and within an ultra-low power budget. We release here, as open source, all our code, hardware designs, datasets, and trained networks. Reference: D. Palossi, F. Conti, and L. Benini An Open Source and Open Hardware [[Deep Learning]]-powered Visual Navigation Engine for Autonomous Nano-UAVs Preprint: https://arxiv.org/abs/1905.04166 PULP-Platform Project Webpage: https://www.pulp-platform.org/ |
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<youtube>AOlZMw_secI</youtube> | <youtube>AOlZMw_secI</youtube> | ||
<b>Securing Positioning & Timing 7: Improving Performance by Augmenting GPS/GNSS | <b>Securing Positioning & Timing 7: Improving Performance by Augmenting GPS/GNSS | ||
− | </b><br>Royal Institute of Navigation. The seventh, and final, of a series of webinars from the Securing Positioning & Timing short course. This webinar covers Improving Performance by Augmenting GPS/GNSS. Presented by Prof Terry Moore. Supported by the UK Space Agency. Website: | + | </b><br>Royal Institute of Navigation. The seventh, and final, of a series of webinars from the Securing Positioning & Timing short course. This webinar covers Improving Performance by Augmenting GPS/GNSS. Presented by Prof Terry Moore. Supported by the UK Space Agency. Website: https://rin.org.uk/ |
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=== <span id="Geolocation: Locating GPS/GNSS Jamming and Spoofing"></span>Geolocation: Locating GPS/GNSS Jamming and Spoofing === | === <span id="Geolocation: Locating GPS/GNSS Jamming and Spoofing"></span>Geolocation: Locating GPS/GNSS Jamming and Spoofing === | ||
− | [ | + | [https://www.youtube.com/results?search_query=Assured+Positioning+Navigation+Timing+PNT+GPS+GNSS+GB-GRAM+INS+CSAC+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=Assured+Positioning+Navigation+Timing+PNT+GPS+GNSS+GB-GRAM+INS+CSAC+artificial+intelligence+ai ...Google search] |
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<youtube>lKnavLpgISc</youtube> | <youtube>lKnavLpgISc</youtube> | ||
<b>Securing Positioning & Timing 3: Detecting and Characterising GPS/GNSS Jamming & Spoofing | <b>Securing Positioning & Timing 3: Detecting and Characterising GPS/GNSS Jamming & Spoofing | ||
− | </b><br>Royal Institute of Navigation. The third of a series of webinars from the Securing Positioning & Timing short course. This webinar covers Detecting and Characterising GPS/GNSS Jamming & Spoofing. Presented by Dr Mark Dumville. Supported by the UK Space Agency. Website: | + | </b><br>Royal Institute of Navigation. The third of a series of webinars from the Securing Positioning & Timing short course. This webinar covers Detecting and Characterising GPS/GNSS Jamming & Spoofing. Presented by Dr Mark Dumville. Supported by the UK Space Agency. Website: https://rin.org.uk/ |
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<youtube>nQR8F4Hia2o</youtube> | <youtube>nQR8F4Hia2o</youtube> | ||
<b>Securing Positioning & Timing 4: Locating GPS/GNSS Jamming and Spoofing | <b>Securing Positioning & Timing 4: Locating GPS/GNSS Jamming and Spoofing | ||
− | </b><br>Royal Institute of Navigation. The fourth of a series of webinars from the Securing Positioning & Timing short course. This webinar covers Locating GPS/GNSS Jamming and Spoofing. Presented by Mike Jones. Supported by the UK Space Agency. Website: | + | </b><br>Royal Institute of Navigation. The fourth of a series of webinars from the Securing Positioning & Timing short course. This webinar covers Locating GPS/GNSS Jamming and Spoofing. Presented by Mike Jones. Supported by the UK Space Agency. Website: https://rin.org.uk/ |
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<youtube>i6-tNzUIo0E</youtube> | <youtube>i6-tNzUIo0E</youtube> | ||
<b>Why isn’t my GPS receiver consistently more accurate? with John Pottle | <b>Why isn’t my GPS receiver consistently more accurate? with John Pottle | ||
− | </b><br>Royal Institute of Navigation. Presenter: John Pottle, Director of the RIN Website: | + | </b><br>Royal Institute of Navigation. Presenter: John Pottle, Director of the RIN Website: https://rin.org.uk/ |
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<youtube>v-hDEJEsBso</youtube> | <youtube>v-hDEJEsBso</youtube> | ||
<b>Current threats to GNSS: An update of incidents and impacts with Guy Buesnel | <b>Current threats to GNSS: An update of incidents and impacts with Guy Buesnel | ||
− | </b><br>Royal Institute of Navigation. Presenter: Guy Buesnel, PNT Security Technologist Spirent Communications plc. Website: | + | </b><br>Royal Institute of Navigation. Presenter: Guy Buesnel, PNT Security Technologist Spirent Communications plc. Website: https://rin.org.uk/ |
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== <span id="Software-defined Global Navigation Satellite Systems (GNSS)"></span>Software-defined Global Navigation Satellite Systems (GNSS) == | == <span id="Software-defined Global Navigation Satellite Systems (GNSS)"></span>Software-defined Global Navigation Satellite Systems (GNSS) == | ||
− | [ | + | [https://www.youtube.com/results?search_query=Software+defined+Global+Navigation+Satellite+System+GNSS+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=Software+defined+Global+Navigation+Satellite+System+GNSS+artificial+intelligence+ai ...Google search] |
* [[Telecommunications#Cognitive Radio (CR) / Software-defined radio (SDR)|Cognitive Radio (CR) / Software-defined radio (SDR)]] | * [[Telecommunications#Cognitive Radio (CR) / Software-defined radio (SDR)|Cognitive Radio (CR) / Software-defined radio (SDR)]] | ||
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<youtube>k2XQQuQrWbw</youtube> | <youtube>k2XQQuQrWbw</youtube> | ||
<b>GRCon20 - Software defined radio based Global Navigation Satellite System real time spoofing.... | <b>GRCon20 - Software defined radio based Global Navigation Satellite System real time spoofing.... | ||
− | </b><br>Software defined radio based Global Navigation Satellite System real time spoofing detection and cancellation Presented by Jean-Michel Friedt,, D. Rabus and G. Goavec-Merou at GNU Radio Conference 2020 | + | </b><br>Software defined radio based Global Navigation Satellite System real time spoofing detection and cancellation Presented by Jean-Michel Friedt,, D. Rabus and G. Goavec-Merou at GNU Radio Conference 2020 https://gnuradio.org/grcon20 Global Navigation Satellite Systems (GNSS) -- most significantly the Global Positioning System (GPS) -- have become ubiquitous to most daily activities, from positioning and navigation to long range time synchronization or distributed energy production ("smart grid"). While initially developed as a military system hardly accessible to civilians, the advent of Software Defined Radio jamming and spoofing capabilities emphasize the low security of GNSS weak signals emitted from satellites orbiting the Earth 20000 km away. While a properly spoofing signal cannot be detected after a consumer-grade receiver has decoded the radiofrequency signal, addressing at the radiofrequency wave level the signal integrity provides the solution of identifying spoofing with all satellites appearing at the same direction of arrival. This classical beamforming analysis -- Controlled Reception Pattern Antenna (CRPA) with multiple antenna reception and phase analysis -- is demonstrated using commercial, off the shelf software defined radio platform receivers (Ettus Research B210) running the real-time GNSS decoder gnss-sdr based on GNU Radio running on embedded boards such as the Raspberry Pi4. |
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== <span id="Long Range Navigation (LORAN)"></span>Long Range Navigation (LORAN) == | == <span id="Long Range Navigation (LORAN)"></span>Long Range Navigation (LORAN) == | ||
− | [ | + | [https://www.youtube.com/results?search_query=Long+Range+Navigation+Loran+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=Long+Range+Navigation+Loran+artificial+intelligence+ai ...Google search] |
− | * [ | + | * [https://www.intelligent-aerospace.com/home/article/14181475/eloran-loran-c-gps-gnss Public-private partnership to launch enhanced LOng RAnge Navigation (eLORAN) technology to back-up and accompany GPS | Jamie Whitney - Intelligent Aerospace] |
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== <span id="Quantum Sensors in Navigation"></span>[[Quantum]] Sensors in Navigation == | == <span id="Quantum Sensors in Navigation"></span>[[Quantum]] Sensors in Navigation == | ||
− | [ | + | [https://www.youtube.com/results?search_query=Quantum+Sensors+Navigation+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=Quantum+Sensors+Navigation+artificial+intelligence+ai ...Google search] |
* [[Quantum]] | * [[Quantum]] | ||
− | * [ | + | * [https://www.ukri.org/ UK Research and Innovation] |
− | * [ | + | * [https://iopscience.iop.org/article/10.1088/1755-1315/237/3/032027/pdf Review of [[Quantum]] Navigation | Donghui Feng - IOP Conference Series: Earth and Environmental Science] |
− | * [ | + | * [https://idstch.com/technology/quantum/quantum-sensing-technology-growing-rapidly-to-enable-ultra-sensitive-quantum-radars-imaging-and-navigation/ [[Quantum]] Sensing Technology Growing Rapidly to Enable Ultra Sensitive Quantum RADARS, Imaging, and Navigation | Rajesh Uppal - International Defence Security & Technology] |
− | Typically, the performance of measurement devices is limited by deleterious effects such as thermal noise and vibration. Notable exceptions are atomic clocks, which operate very near their fundamental limits. Driving devices to their physical limits will open new application spaces critical to future DoD systems. Indeed, many defense-critical applications already require exceptionally precise time and frequency standards enabled only by atomic clocks. The Global Positioning System (GPS) and the internet are two key examples. Measurement systems based on atomic physics benefit from the exquisite properties of the atom. Among these are (a) precise frequency transitions, (b) the ability to initialize, control, and readout the atomic state and (c) environmental isolation. In addition, atomic properties are absolute, and do not “drift” over time. In this sense, atoms are self-calibrated, making them ideal for precision sensing. [ | + | Typically, the performance of measurement devices is limited by deleterious effects such as thermal noise and vibration. Notable exceptions are atomic clocks, which operate very near their fundamental limits. Driving devices to their physical limits will open new application spaces critical to future DoD systems. Indeed, many defense-critical applications already require exceptionally precise time and frequency standards enabled only by atomic clocks. The Global Positioning System (GPS) and the internet are two key examples. Measurement systems based on atomic physics benefit from the exquisite properties of the atom. Among these are (a) precise frequency transitions, (b) the ability to initialize, control, and readout the atomic state and (c) environmental isolation. In addition, atomic properties are absolute, and do not “drift” over time. In this sense, atoms are self-calibrated, making them ideal for precision sensing. [https://www.darpa.mil/program/quantum-assisted-sensing-and-readout Quantum-Assisted Sensing and Readout (QuASAR) | ] [[Defense#US Defense Advanced Research Projects Agency (DARPA)|US Defense Advanced Research Projects Agency (DARPA)]] |
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<youtube>eP-_vEloIRc</youtube> | <youtube>eP-_vEloIRc</youtube> | ||
<b>Quantum Sensors in Navigation with Roger McKinlay, George Shaw and Kai Bongs | <b>Quantum Sensors in Navigation with Roger McKinlay, George Shaw and Kai Bongs | ||
− | </b><br>Royal Institute of Navigation Co-hosted by the UK Quantum Technology Hub Sensors and Timing and the Royal Institute of Navigation Presenters: Professor Kai Bongs, Principal Investigator at the UK Quantum Technology Hub Sensors and Timing; Roger McKinlay, Challenge Director for Quantum Technologies, UK Research and Innovation; George Shaw, Principal Systems Engineer, General Lighthouse Authority In this trio of presentations Roger, George and Kai discuss quantum sensors in navigation... Roger covers systems considerations in PNT and vulnerabilities in GNSS, UK industry opportunities and IUK programmes George covers current maritime navigation challenges, the resilient PNT system-of-systems approach and opportunity for Quantum Sensor technology insertion Kai covers quantum Sensor | + | </b><br>Royal Institute of Navigation Co-hosted by the UK Quantum Technology Hub Sensors and Timing and the Royal Institute of Navigation Presenters: Professor Kai Bongs, Principal Investigator at the UK Quantum Technology Hub Sensors and Timing; Roger McKinlay, Challenge Director for Quantum Technologies, UK Research and Innovation; George Shaw, Principal Systems Engineer, General Lighthouse Authority In this trio of presentations Roger, George and Kai discuss quantum sensors in navigation... Roger covers systems considerations in PNT and vulnerabilities in GNSS, UK industry opportunities and IUK programmes George covers current maritime navigation challenges, the resilient PNT system-of-systems approach and opportunity for Quantum Sensor technology insertion Kai covers quantum Sensor [[development]]s towards navigation solutions Website: https://rin.org.uk/ |
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<b>Nanoscale Quantum Sensing - Prof. Jorg Wrachtrup | <b>Nanoscale Quantum Sensing - Prof. Jorg Wrachtrup | ||
</b><br>Bar-Ilan University Nanoscale Quantum Sensing - a lecture by Prof. Jorg Wrachtrup of the Institute for Quantum Science and Technology in Germany. This lecture was given during the conference QUEST - Quantum Entanglement Science & Technology, held by Bar-Ilan University's Physics Department in June 2017. | </b><br>Bar-Ilan University Nanoscale Quantum Sensing - a lecture by Prof. Jorg Wrachtrup of the Institute for Quantum Science and Technology in Germany. This lecture was given during the conference QUEST - Quantum Entanglement Science & Technology, held by Bar-Ilan University's Physics Department in June 2017. | ||
+ | |} | ||
+ | |}<!-- B --> | ||
+ | |||
+ | |||
+ | == <span id="Spacetime"></span>Spacetime == | ||
+ | [https://www.youtube.com/results?search_query=Spacetime YouTube search...] | ||
+ | [https://www.google.com/search?q=Spacetime ...Google search] | ||
+ | |||
+ | {|<!-- T --> | ||
+ | | valign="top" | | ||
+ | {| class="wikitable" style="width: 550px;" | ||
+ | || | ||
+ | <youtube>YpyXVkqkQgg</youtube> | ||
+ | <b>Time Does Not Exist. Let me explain with a graph. | ||
+ | </b><br>How do we really move through spacetime? Sadly the books have sold out. | ||
+ | |} | ||
+ | |<!-- M --> | ||
+ | | valign="top" | | ||
+ | {| class="wikitable" style="width: 550px;" | ||
+ | || | ||
+ | <youtube>CuMJbePKEtI</youtube> | ||
+ | <b>IT'S NOT REAL! Physicists PROVE Time Does NOT Exist | ||
+ | </b><br>We, humans, are fascinated with the idea of traveling back or ahead in time. Time Travel Machines and Devices have been a staple for a lot of science fiction and even fantasy stories catering to our desire to either change something in the past to make our lives better or just skip ahead in time to find out if life gets better on its own in the future. Ever wonder why we may never develop a Time Machine? Because Time probably doesn’t even EXIST! Welcome to Factnomenal, and today let’s find out why some physicists insist that TIME exists only in our heads. | ||
+ | |} | ||
+ | |}<!-- B --> | ||
+ | {|<!-- T --> | ||
+ | | valign="top" | | ||
+ | {| class="wikitable" style="width: 550px;" | ||
+ | || | ||
+ | <youtube>GZcXNBYcfe4</youtube> | ||
+ | <b>This Is Why Time Might Not Actually Exist | ||
+ | </b><br>Quantum Entanglement May Reveal a Reality We Can't Handle | ||
+ | |} | ||
+ | |<!-- M --> | ||
+ | | valign="top" | | ||
+ | {| class="wikitable" style="width: 550px;" | ||
+ | || | ||
+ | <youtube>yPVQtvbiS4Y</youtube> | ||
+ | <b>What Actually Are Space And Time? | ||
+ | </b><br>If you like this video, check out writer Geraint Lewis´ excellent book, co-written with Chris Ferrie: | ||
+ | [https://www.amazon.com/Where-Universe-Other-Cosmic-Questions/dp/1728238811 Where Did the Universe Come From? And Other Cosmic Questions: Our Universe, from the Quantum to the Cosmos] AND check out his [https://www.youtube.com/c/AlasLewisAndBarnes Youtube channel] | ||
+ | |} | ||
+ | |}<!-- B --> | ||
+ | |||
+ | == <span id="Longitude"></span>Longitude == | ||
+ | [https://www.youtube.com/results?search_query=Longitude YouTube search...] | ||
+ | [https://www.google.com/search?q=Longitude ...Google search] | ||
+ | |||
+ | * [https://en.wikipedia.org/wiki/Longitude_(book) Longitude: The True Story of a Lone Genius Who Solved the Greatest Scientific Problem of His Time | Wikipedia] | ||
+ | |||
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+ | {| class="wikitable" style="width: 550px;" | ||
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+ | <youtube>LHvt48S9l4w</youtube> | ||
+ | <b>Longitude | ||
+ | </b><br>Dava Sobel's book is a captivating story, such a good film with an impressive cast. What a genius Mr Harrison was. Such determination. A lesson to us all.. | ||
+ | |} | ||
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+ | <youtube>T-g27KS0yiY</youtube> | ||
+ | <b>The Clock That Changed the World (BBC History of the World) | ||
+ | </b><br> | ||
+ | SciShow It’s time for another leap second! Join SciShow as we celebrate by exploring the long and strange history of timekeeping. Hosted by: Michael Aranda Dooblydoo thanks go to the following Patreon supporters -- we couldn't make SciShow without them! Shout out to Justin Ove, Justin Lentz, David Campos, John Szymakowski, Peso255, Jeremy Peng, Avi Yaschin, and Fatima Iqbal. Like SciShow? Want to help support us, and also get things to put on your walls, cover your torso and hold your liquids? Check out our awesome products over at DFTBA Records: https://dftba.com/scishow Or help support us by becoming our patron on Patreon: https://www.patreon.com/scishow | ||
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== <span id="Natural Navigation"></span>Natural Navigation == | == <span id="Natural Navigation"></span>Natural Navigation == | ||
− | [ | + | [https://www.youtube.com/results?search_query=Animal+Navigation+Incredible+Bees+Journeys+intelligence YouTube search...] |
− | [ | + | [https://www.google.com/search?q=Animal+Navigation+Incredible+Bees+Journeys+intelligence ...Google search] |
− | * [ | + | * [https://www.amazon.com/Incredible-Journeys-Exploring-Wonders-Navigation/dp/1473656826 Incredible Journeys: Exploring the Wonders of Animal Navigation Hardcover | David Barrie] |
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= <span id="Time & Music"></span>Time & Music = | = <span id="Time & Music"></span>Time & Music = | ||
− | [ | + | [https://www.youtube.com/results?search_query=time+music+artificial+intelligence+ai YouTube search...] |
− | [ | + | [https://www.google.com/search?q=time+music+artificial+intelligence+ai ...Google search] |
− | * [[ | + | * [[End-to-End Speech]] ... [[Synthesize Speech]] ... [[Speech Recognition]] ... [[Music]] |
<youtube>gk17N6cDKqQ</youtube> | <youtube>gk17N6cDKqQ</youtube> |
Latest revision as of 15:36, 27 May 2024
YouTube ... Quora ...Google search ...Google News ...Bing News
- Time ... PNT ... GPS ... Retrocausality ... Delayed Choice Quantum Eraser ... Quantum
- Government Services:
- National Institute of Standards and Technology (NIST) ... Time and Frequency Division, Physical Measurement Laboratory
- U.S. Department of Homeland Security (DHS) ... Science and Technology (S&T) Positioning, Navigation, and Timing (PNT) Program
- Defense ... Precise Time Department ... U.S. Naval Observatory has maintained a Time Service Department since 1880
- Perspective ... Context ... In-Context Learning (ICL) ... Transfer Learning ... Out-of-Distribution (OOD) Generalization
- National Timing Centre ... Assured Time and Frequency for the UK
- Time ...Coordinated Universal Time UTC ... Clock ...Timekeeping | Wikipedia
- The Very Long and Fascinating History of Clocks | Christopher McFadden - Interesting Engineering
- What Is a Leap Second? | Konstantin Bikos and Anne Buckle - timeanddate.com
- Atomic clocks ...Tide Clock | Amazon
- Clock synchronization
- Time: Do the past, present, and future exist all at once? | BigThink (video) ... astrophysicist Michelle Thaller, science educator Bill Nye, author James Gleick, and neuroscientist Dean Buonomano discuss how the human brain perceives of the passage of time, the idea in theoretical physics of time as a fourth dimension, and the theory that space and time are interwoven.
- Cybersecurity
- Crown Sterling ... changing the face of digital security with its non-integer-based algorithms that leverage time, AI and irrational numbers.
- Quantum cryptography ... the infosec industry looks to quantum cryptography and quantum key distribution (QKD)
- What’s a Time Crystal? | Charles Q. Choi - IEEE Spectrum ... And how do Google researchers use quantum computers to make them? ... quantum system of many particles that organize themselves into a periodic pattern of motion—periodic in time rather than in space—that persists in perpetuity.
- This Mirror Reverses How Light Travels in Time There are already applications in wireless, radar, and optical-computing | Charles Q. Choi - IEEE Spectrum ... There are already applications in wireless, radar, and optical-computing ... These applications often reverse the order of signals to help process them.
Contents
- 1 Sequence/Time-based Algorithms
- 2 What Time Is It?
- 3 Precision Time Protocol (PTP)
- 4 Positioning, Navigation and Timing (PNT)
- 5 Time & Music
Sequence/Time-based Algorithms
- 10 Incredibly Useful Time Series Forecasting Algorithms
- Artificial intelligence (AI) algorithms: a complete overview
- New AI Algorithms Streamline Data Processing for Space-based Instruments
- Unlocking The Power Of Predictive Analytics With AI - Forbes
- A Comparison of Time Series Databases and Netsil’s Use of Druid | Netsil
- Microsoft announces the general availability of Azure Time Series Insights | Ryan Waite - Microsoft
- Top 10 Time Series Databases | Outlyer
Time-based AI algorithms are algorithms that use time series data to make predictions or analyses. Time series data are data that are collected over time and have a temporal order. For example, the daily temperature, the stock prices, or the number of visitors to a website are all time series data. These algorithms can be used for a variety of purposes, such as forecasting future values, detecting trends and patterns, and making informed decisions based on historical data. They can be applied to many different fields, including finance, economics, meteorology, and healthcare.
Whenever we have developed better clocks, we’ve learned something new about the world.
- Alexander Smith New Time Dilation Phenomenon Revealed: Timekeeping Theory Combines Quantum Clocks and Einstein’s Relativity - Dartmouth College
Common
There are different types of sequence/time-based AI algorithms, depending on the goal and the method of the algorithm. Some of the most common ones are:
- Time Series Forecasting:
- Statistical:
- Autoregressive (AR): uses past values of the time series to predict future values. It assumes that the current value is a linear function of previous values. For example, AR can be used to forecast the weather based on historical data.
- Autoregressive Integrated Moving Average (ARIMA): is an extension of AR that also accounts for the trend and the seasonality of the time series. It uses differencing to make the time series stationary (i.e., having constant mean and variance) and then applies AR and moving average (MA) models. For example, ARIMA can be used to forecast the sales of a product based on past sales and seasonal patterns.
- Seasonal Autoregressive Integrated Moving Average (SARIMA): is a further extension of ARIMA that also accounts for the cyclic variations of the time series. It uses seasonal differencing and seasonal AR and MA models to capture the periodic fluctuations of the time series. For example, SARIMA can be used to forecast the electricity demand based on past demand and seasonal factors.
- Exponential Smoothing (ES): uses weighted averages of past values of the time series to predict future values. It gives more weight to recent values than older values, and it can also incorporate trend and seasonality components. For example, ES can be used to forecast the inventory level based on past demand and supply.
- Deep Learning:
- Prophet: is a modern and flexible approach to time series forecasting developed by Facebook. It uses a decomposable model that consists of trend, seasonality, and holiday components, and it allows for adding custom effects and prior information. For example, Prophet can be used to forecast the web traffic for a data science blog website based on past traffic and special events.
- Neural Turing Machine (NTM): the fuzzy pattern matching capabilities of Neural Networks with the algorithmic power of programmable computers. NTMs are an instance of Memory Augmented Neural Networks, a new class of Recurrent Neural Network (RNN)s which decouple computation from memory by introducing an external memory unit. NTMs have demonstrated superior performance over Long Short-Term Memory Cells in several sequence learning tasks.
- Statistical:
- Neural Networks:
- Recurrent Neural Network (RNN): is a type of Deep Learning model that can process sequential data such as time series. It uses a network of neurons that have feedback loops, which enable them to store information from previous inputs. For example, RNN can be used to forecast the prices of Bitcoin based on past prices and other factors.
- Gated Recurrent Unit (GRU): are a gating mechanism in Recurrent Neural Network (RNN) architecture. Like other RNNs, a GRU can process sequential data such as time series, natural language, and speech1. The GRU is similar to a Long Short-Term Memory (LSTM) with a forget gate, but has fewer parameters than LSTM, as it lacks an output gate. This means that GRUs are generally easier and faster to train than their LSTM counterparts. GRUs have been found to perform similarly to LSTMs on certain tasks such as polyphonic music modeling, speech signal modeling, and natural language processing. They have shown that gating is indeed helpful in general.
- Long Short-Term Memory (LSTM): is a special type of RNN that can handle long-term dependencies in sequential data. It uses a memory cell that can store, update, and forget information over time, and it has gates that control the flow of information in and out of the cell. For example, LSTM can be used to forecast the generation of wind power based on past generation and weather conditions:
- Bidirectional Long Short-Term Memory (BI-LSTM): is a type of Recurrent Neural Network (RNN) architecture that processes data in both forward and backward directions. It consists of two LSTMs: one taking the input in a forward direction, and the other in a backward direction. BI-LSTMs effectively increase the amount of information available to the network, improving the context available to the algorithm. For example, knowing what words immediately follow and precede a word in a sentence. Compared to LSTM, BI-LSTM combines the forward hidden layer and the backward hidden layer, which can access both the preceding and succeeding contexts¹. This feature of flow of data in both directions makes the BI-LSTM different from other LSTMs. BI-LSTMs have been successfully applied to various tasks such as natural language processing, speech recognition, and traffic forecasting.
- Bidirectional Long Short-Term Memory (BI-LSTM) with Attention Mechanism: is a type of Recurrent Neural Network (RNN) architecture that processes data in both forward and backward directions, and uses an attention mechanism to weigh the importance of different parts of the input sequence. The attention mechanism allows the network to focus on specific parts of the input sequence when making predictions, rather than treating all parts of the sequence equally. This can be particularly useful when dealing with long input sequences, where some parts of the sequence may be more relevant to the prediction than others. BI-LSTMs with Attention Mechanism have been successfully applied to various tasks such as text classification, Sentiment Analysis, and human activity recognition.
- Average-Stochastic Gradient Descent (SGD) Weight-Dropped LSTM (AWD-LSTM): is a variant of LSTM that employs DropConnect for regularization, as well as NT-ASGD for optimization. NT-ASGD stands for non-monotonically triggered averaged stochastic gradient descent, which returns an average of the last iterations of weights. AWD-LSTM has shown great results on both word-level and character-level models. It has been used in research papers on word-level models and has shown great results on character-level models as well.
- Sequence to Sequence (Seq2Seq): can map a variable-length input sequence to a variable-length output sequence. It is often used for natural language processing tasks, such as machine translation, text summarization, conversational models, and question answering. The Seq2Seq algorithm consists of two main components: an encoder and a decoder. The encoder reads the input sequence one timestep at a time and produces a hidden vector representation of the input. The decoder then uses the hidden vector as the initial state and generates the output sequence one timestep at a time, using the previous output as the input context.
- Transformer: is a state-of-the-art Deep Learning model that can process sequential data such as time series. It uses layers of attention mechanisms that can learn how to focus on relevant parts of the input data, and it can handle long-term dependencies and parallel computations efficiently. For example, Transformer can be used to forecast the spread of COVID-19 based on past cases and interventions. Transformer can process sequential data using layers of attention mechanisms, without using recurrent or convolutional layers. It can handle long-term dependencies and parallel computations efficiently, and it can achieve better results than RNN-based Seq2Seq models on various tasks.
- Generative Pre-trained Transformer (GPT): are a family of language models that use Deep Learning techniques to generate natural language text. They are based on the transformer architecture and can be fine-tuned for various natural language processing tasks such as text generation, language translation, and text classification. The first GPT was introduced in 2018 by the American artificial intelligence (AI) company OpenAI. GPT models are artificial Neural Networks that are based on the transformer architecture, pre-trained on large data sets of unlabelled text, and able to generate novel human-like content
- Attention Mechanism: allows the decoder to selectively focus on different parts of the input sequence when generating the output, instead of relying on a single fixed vector. This can improve the performance and accuracy of the Seq2Seq model, especially for long sequences
- Transformer-XL: is a transformer-based language model that introduces the notion of recurrence to the deep self-attention network. It was designed to enable learning dependency beyond a fixed length without disrupting temporal coherence. The model consists of a segment-level recurrence mechanism and a novel positional encoding scheme. This method not only enables capturing longer-term dependency, but also resolves the context fragmentation problem. As a result, Transformer-XL learns dependency that is 80% longer than RNNs and 450% longer than vanilla Transformers, achieves better performance on both short and long sequences, and is up to 1,800+ times faster than vanilla Transformers during evaluation.
- Beam search: is a technique to find the most probable output sequence given the input sequence, by keeping track of multiple candidate sequences and expanding them based on their probabilities. This can improve the quality and diversity of the output, compared to using a greedy or random search.
- Convolutional Neural Network (CNN): is another type of Deep Learning model that can process sequential data such as time series. It uses layers of filters that can extract features from local regions of the input data, and it can capture complex patterns and relationships in the data. For example, CNN can be used to forecast an avalanche in a famous ski resort based on past snowfall and temperature data.
- Spatial-Temporal Dynamic Network (STDN): a Deep Learning framework proposed to address the challenge of modeling complex spatial dependencies and temporal dynamics in traffic prediction. A flow gating mechanism is introduced to learn the dynamic similarity between locations, and a periodically shifted attention mechanism is designed to handle long-term periodic temporal shifting. This approach has been shown to be effective in predicting taxi demand
- Recurrent Neural Network (RNN): is a type of Deep Learning model that can process sequential data such as time series. It uses a network of neurons that have feedback loops, which enable them to store information from previous inputs. For example, RNN can be used to forecast the prices of Bitcoin based on past prices and other factors.
- Other:
- Gaussian Process (GP): is a type of probabilistic model that can handle uncertainty and noise in time series data. It uses a function that defines how similar any two points in the input space are, and it produces a distribution over possible outputs for any given input. For example, GP can be used to forecast the depletion level of stocks in stores based on past sales and inventory data.
- End-to-End Speech: translation is an approach to speech translation that is gaining high interest from the research world in the last few years. It consists of using a single Deep Learning model that learns to generate translated text of the input audio in an end-to-end fashion. This approach, known as “end-to-end” or “direct” ST, supposes many advantages over the former, such as avoiding the concatenation of errors, the direct use of prosodic from speech and a lower inference time.
- (Tree) Recursive Neural (Tensor) Network (RNTN): type of Neural Network that is mostly used for natural language processing. It has a tree structure with a neural net at each node. The purpose of these nets is to analyze data that have a hierarchy of structure. An RNTN is a powerful tool for deciphering and labeling patterns. Structurally, an RNTN is a binary tree with three nodes: a root and two leaves. The root and leaf nodes are not neurons, but instead, they are groups of neurons – the more complicated the input data, the more neurons are required. RNTNs have been successfully applied to Sentiment Analysis, where the input is a sentence in its parse tree structure, and the output is the classification for the input sentence, i.e., whether the meaning is very negative, negative, neutral, positive, or very positive
- Temporal Difference (TD) Learning: refers to a class of model-free Reinforcement Learning (RL) methods which learn by bootstrapping from the current estimate of the value function. These methods sample from the environment, like Monte Carlo methods, and perform updates based on current estimates, like dynamic programming methods. While Monte Carlo methods only adjust their estimates once the final outcome is known, TD methods adjust predictions to match later, more accurate, predictions about the future before the final outcome is known.
What Time Is It?
- DARPA Making Progress on Miniaturized Atomic Clocks for Future PNT Applications | US Defense Advanced Research Projects Agency (DARPA)
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The Earth's rotation is so accurate it varies only in milliseconds ...do you feel the Earth rotation slowing down?
Light Clock 1905 - Einstein's Thought Experiment
Imagine you have a special clock that works with light. This clock has two mirrors facing each other, and a beam of light bounces up and down between them. Every time the light goes from the bottom mirror to the top and back down, it counts as one tick of the clock. Einstein's light clock thought experiment shows that when things move fast, time slows down for them. This surprising idea helps us understand the nature of time and motion in our universe. Now, let's think about this clock in two different situations.
Situation 1: Standing Still: First, picture the clock sitting on a table, not moving at all. The light goes straight up to the top mirror and straight back down to the bottom mirror. If you measured the time it takes for the light to do this, you would see it takes a certain amount of time for one tick.
Situation 2: Moving Clock: Now, imagine you place the clock on a skateboard and push it so it's moving. As the clock moves, the light beam has to travel a different path. Instead of going straight up and down, it now has to go in a diagonal path because the mirrors are moving while the light is traveling. It's like when you throw a ball to a friend while running; the ball has to cover more distance because both of you are moving.
What This Means ... Because the light in the moving clock has to travel a longer, diagonal path, it takes more time for one tick to happen compared to when the clock is standing still. This means that for someone watching the moving clock, time appears to run slower for the moving clock compared to a clock that's not moving. This idea is called time dilation. It means that time actually passes at different rates depending on how fast something is moving. If you were riding on the skateboard with the clock, you wouldn't notice anything different about the clock's ticks. But someone standing still and watching you would see that your clock ticks more slowly.
Why It Matters ... This thought experiment helps us understand that time isn't the same everywhere and can be different depending on how fast things are moving. This concept is a key part of Einstein's theory of special relativity, which helps scientists understand how the universe works, especially when things are moving very fast, like spaceships or particles in a collider.
Precision Time Protocol (PTP)
YouTube search... ...Google search
- Precision Time Protocol PTP-1588 | IEEE ...High precision clock synchronization that computes latency and offset
- How Precision Time Protocol is being deployed at Meta | Oleg Obleukhov & Ahmad Byagowi - CONNECTIVITY, NETWORKING & TRAFFIC, OPEN SOURCE, PRODUCTION ENGINEERING, UNCATEGORIZED, WEB
- PTP IEEE 1588v2 | Juniper Networks ...Time Management Administration Guide
The Precision Time Protocol (PTP) is a protocol used to synchronize clocks throughout a computer network. On a local area network, it achieves clock accuracy in the sub-microsecond range, making it suitable for measurement and control systems.[1] PTP is currently employed to synchronize financial transactions, mobile phone tower transmissions, sub-sea acoustic arrays, and networks that require precise timing but lack access to satellite navigation signals.Wikipedia
Overall, its structure is similar to NTP in that there are different levels within it and GPS satellites can serve as its time source. However, the major difference between Network Time Protocol (NTP) and PTP is that PTP is accurate to microseconds, meaning that it is more exact than NTP
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YouTube search... ...Google search
- Time ... PNT ... GPS ... Retrocausality ... Delayed Choice Quantum Eraser ... Quantum
- Case Studies
- Autonomous Drones
- Deepmind teaches AI to follow navigational directions like humans | Tristan Greene
- History of Navigation | Wikipedia
- Department of Homeland Security (DHS) Science and Technology (S&T) Positioning, Navigation, and Timing (PNT) Program
- Navigation Aids | Department of Transportation, Federal Aviation Administration
- VN-300 | Vectornav ...miniature, high-performance Dual Antenna Global Navigation Satellite Systems (GNSS)-Aided Inertial Navigation System (INS) that combines micro-electromechanical systems (MEMS) inertial sensors, two high-sensitivity GNSS receivers, and advanced Kalman filtering algorithms to provide optimal estimates of position, velocity, and orientation.
Navigation is a field of study that focuses on the process of monitoring and controlling the movement of a craft or vehicle from one place to another.[1] The field of navigation includes four general categories: land navigation, marine navigation, aeronautic navigation, and space navigation. Navigation | Wikipedia
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Global Positioning System (GPS)
YouTube search... ...Google search
- Time ... PNT ... GPS ... Retrocausality ... Delayed Choice Quantum Eraser ... Quantum
- Astronomy
- GPS has been copied by Russia's GLONASS, Europe’s Galileo, China's BeiDou, India’s IRNSS, and Japan’s QZSS
- Artificial intelligence in GPS navigation systems | Jeffrey L. Duffany
- RoadTagger: GPS system upgrade utilizes AI to make sure you're in the right lane | David Nield - New Atlas ...Artificial intelligence to update digital maps and improve GPS navigation | Amit Malewar - InceptiveMind
- GPS.gov ...Timing
- Inside GNSS ...Global Navigation Satellite Systems
- Navstar | Space.com ...is a network of U.S. satellites that provide GPS services
- SpaceX launches third-generation GPS navigation satellite | CBS News ...GPS-3 satellite — the fourth in a series of more powerful third-generation navigation stations built by Lockheed Martin — was expected to be deployed about a 90 minutes after liftoff. Assuming tests and checkout go well, it will join a globe-spanning constellation of 31 GPS satellites.
- Air Force asks three U.S. contractors to develop miniature ASIC technology for next-gen GPS receivers | John Keller - Military & Aerospace Electronics ...small low-power-consumption GPS enabling technologies to include a next-generation ASIC for secure GPS land navigation.
- China Launches Beidou, Its Own Version of GPS | Andrew Jones - IEEE Spectrum ...China places the final Beidou navigation system satellite into orbit
- Big News For ISRO! Indian Navigation System (IRNSS) Gets Approval By IMP For Global Operations | Smriti Chaudhary - The EurAsuan Times
GPS receivers that use the L5 band can pinpoint to within 30 centimeters or 11.8 inches. The GPS concept is based on time and the known position of GPS specialized satellites. The satellites carry very stable atomic clocks that are synchronized with one another and with the ground clocks. Any drift from time maintained on the ground is corrected daily. In the same manner, the satellite locations are known with great precision. GPS receivers have clocks as well, but they are less stable and less precise. Each GPS satellite continuously transmits a radio signal containing the current time and data about its position. Since the speed of radio waves is constant and independent of the satellite speed, the time delay between when the satellite transmits a signal and the receiver receives it is proportional to the distance from the satellite to the receiver. A GPS receiver monitors multiple satellites and solves equations to determine the precise position of the receiver and its deviation from true time. At a minimum, four satellites must be in view of the receiver for it to compute four unknown quantities (three position coordinates and clock deviation from satellite time). Global Positioning System | Wikipedia
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Deep-Space Positioning System (DPS)
YouTube search... ...Google search
- NASA is Making An AI-Based GPS For Space | Kristin Houser
- Frontier Development Lab (FDL) ...Artificial Intelligence Research for Space Science, Exploration & All Humankind
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Jamming and Spoofing
YouTube search... ...Google search
- The Resilient Navigation and Timing Foundation
- Department of Homeland Security (DHS) Science and Technology (S&T) Resilient Positioning, Navigation, and Timing (PNT) Conformance Framework
- The Space Force: A Conversation With United States Secretary Of The Air Force Barbara Barrett | Steve Forbes - Forbes ... We are vulnerable. For example, the U.S. and the global economy are totally dependent on satellites, most especially the GPS, which is operated by the Space Force.
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