Relevant bibliographies by topics / Dynamic time warping algorithm

Academic literature on the topic 'Dynamic time warping algorithm'

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Published: 30 May 2022
Last updated: 8 June 2024

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Journal articles on the topic "Dynamic time warping algorithm"

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Jeong, Seung-Do. "Speaker Identification Using Dynamic Time Warping Algorithm." Journal of the Korea Academia-Industrial cooperation Society 12, no. 5 (May 31, 2011): 2402–9. http://dx.doi.org/10.5762/kais.2011.12.5.2402.

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Stübinger, Johannes, and Dominik Walter. "Using Multi-Dimensional Dynamic Time Warping to Identify Time-Varying Lead-Lag Relationships." Sensors 22, no. 18 (September 12, 2022): 6884. http://dx.doi.org/10.3390/s22186884.

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This paper develops a multi-dimensional Dynamic Time Warping (DTW) algorithm to identify varying lead-lag relationships between two different time series. Specifically, this manuscript contributes to the literature by improving upon the use towards lead-lag estimation. Our two-step procedure computes the multi-dimensional DTW alignment with the aid of shapeDTW and then utilises the output to extract the estimated time-varying lead-lag relationship between the original time series. Next, our extensive simulation study analyses the performance of the algorithm compared to the state-of-the-art methods Thermal Optimal Path (TOP), Symmetric Thermal Optimal Path (TOPS), Rolling Cross-Correlation (RCC), Dynamic Time Warping (DTW), and Derivative Dynamic Time Warping (DDTW). We observe a strong outperformance of the algorithm regarding efficiency, robustness, and feasibility.
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Gao, Cuifang, Junjie Li, Wanqiang Shen, and Ping Yin. "Two-dimensional dynamic time warping algorithm for matrices similarity." Intelligent Data Analysis 26, no. 4 (July 11, 2022): 859–71. http://dx.doi.org/10.3233/ida-215908.

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Dynamic Time Warping (DTW algorithm) provides an effective method to obtain the similarity between unequal-sized signals. However, it cannot directly deal with high-dimensional samples such as matrices. Expanding a matrix to one dimensional vector as the input data of DTW will decrease the measure accuracy because of the losing of position information in the matrix. Aiming at this problem, a two-dimensional dynamic time warping algorithm (2D-DTW) is proposed in this paper to directly measure the similarity between matrices. In 2D-DTW algorithm, a three dimensional distance-cuboid is constructed, and its mapped distance matrix is defined by cutting and compressing the distance-cuboid. By introducing the dynamic programming theory to search the shortest warping path in the mapped matrix, the corresponding shortest distance can be obtained as the expected similarity measure. The experimental results suggest that the performance of 2D-DTW distance is superior to the traditional Euclidean distance and can improve the similarity accuracy between matrices by introducing the warping alignment mechanisms. 2D-DTW algorithm extends the application ranges of traditional DTW and is especially suitable for high-dimensional data.
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Ali, Aya Hamdy, Ayman Atia, and Mostafa-Sami M. Mostafa. "Recognizing Driving Behavior and Road Anomaly using Smartphone Sensors." International Journal of Ambient Computing and Intelligence 8, no. 3 (July 2017): 22–37. http://dx.doi.org/10.4018/ijaci.2017070102.

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Road traffic accidents are caused 1.25 million deaths per year worldwide. To improve road safety and reducing road accidents, a recognition method for driving events is introduced in this paper. The proposed method detected and classified both driving behaviors and road anomalies patterns based on smartphone sensors (accelerometer and gyroscope). k-Nearest Neighbor and Dynamic Time Warping algorithms were utilized for method evaluation. Experiments were conducted to evaluate k-nearest neighbor and dynamic time warping algorithms accuracy for road anomalies and driving behaviors detection, moreover, driving behaviors classification. Evaluation results showed that k-nearest neighbor algorithm detected road anomalies and driving behaviors with total accuracy 98.67%. Dynamic time warping algorithm classified (normal and abnormal) driving behaviors with total accuracy 96.75%.
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Hagen, Cedric J., Brendan T. Reilly, Joseph S. Stoner, and Jessica R. Creveling. "Dynamic time warping of palaeomagnetic secular variation data." Geophysical Journal International 221, no. 1 (January 9, 2020): 706–21. http://dx.doi.org/10.1093/gji/ggaa004.

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SUMMARY We present and make publicly available a dynamic programming algorithm to simultaneously align the inclination and declination vector directions of sedimentary palaeomagnetic secular variation data. This algorithm generates a library of possible alignments through the systematic variation of assumptions about the relative accumulation rate and shared temporal overlap of two or more time-series. The palaeomagnetist can then evaluate this library of reproducible and objective alignments using available geological constraints, statistical methods and expert knowledge. We apply the algorithm to align previously (visually) correlated medium to high accumulation rate northern North Atlantic Holocene deposits (101–102 cm ka–1) with strong radiocarbon control. The algorithm generates plausible alignments that largely conform with radiocarbon and magnetic acquisition process uncertainty. These alignments illustrate the strengths and limitations of this numerical approach.
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Hale, Dave. "Dynamic warping of seismic images." GEOPHYSICS 78, no. 2 (March 1, 2013): S105—S115. http://dx.doi.org/10.1190/geo2012-0327.1.

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The problem of estimating relative time (or depth) shifts between two seismic images is ubiquitous in seismic data processing. This problem is especially difficult where shifts are large and vary rapidly with time and space, and where images are contaminated with noise or for other reasons are not shifted versions of one another. A new solution to this problem requires only simple extensions of a classic dynamic time warping algorithm for speech recognition. A key component of that classic algorithm is a nonlinear accumulation of alignment errors. By applying the same nonlinear accumulator repeatedly in all directions along all sampled axes of a multidimensional image, I obtain a new and effective method for dynamic image warping (DIW). In tests where known shifts vary rapidly, this new method is more accurate than methods based on crosscorrelations of windowed images. DIW also aligns seismic reflectors well in examples where shifts are unknown, for images with differences not limited to time shifts.
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Liu, Zhen Wu, Zhi Wu Shang, Ya Feng Li, and Tai Yong Wang. "A Fault Diagnosis System Based on Bistable Stochastic Resonance and Dynamic Time Warping." Key Engineering Materials 693 (May 2016): 1294–99. http://dx.doi.org/10.4028/www.scientific.net/kem.693.1294.

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Stator current signal of driving motor can be easily measured. Using it in the gearbox fault diagnosis system is inexpensive and suitable for remote monitoring. According to the application of the Motor Current Signal Analysis in machinery fault detection, we present a new gearbox fault diagnosis system. In modern signal processing technology, Stochastic Resonance theory is widely used to improve SNR (signal to noise ratio). Dynamic time warping algorithm is a simple and efficient way of the pattern identified. Combine the Stochastic Resonance theory and dynamic time warping algorithm as the basic theory of fault diagnosis. To realize the development of fault diagnosis software, we use the mixed-programming of MATLAB algorithms library and VC++.
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Wang, Hairong, and Qiufang Zheng. "Improvement and Application of Hale’s Dynamic Time Warping Algorithm." Symmetry 16, no. 6 (May 23, 2024): 645. http://dx.doi.org/10.3390/sym16060645.

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Due to the different generation and propagation mechanisms of P- and S-waves, there may be significant differences in the seismic data collected by the two, which poses a great obstacle to the time domain matching of P- and S-waves in multiwave exploration. Furthermore, the quality and accuracy of the matching effect will directly affect the subsequent multiwave joint inversion and interpretation effect. Therefore, the study of P and S-wave-matching methods plays a crucial role in seismic exploration. In 2013, Hale improved the classical Dynamic Time Warping (DTW) algorithm applied to solve the problem of speech recognition, and obtained the DTW algorithm suitable for solving the matching of P-waves and S-waves. The seismic wave-matching results generated by this algorithm are horizontal discontinuous (different trajectories) and need further processing. This study analyses the algorithm based on simulations of seismic waves using Ricker wavelets. In response to existing problems, this paper proposes strategies to improve the DTW algorithm. The algorithm in this study significantly improved the continuity of the registration results of the actual seismic wave data in the horizontal direction (different traces).
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Pielmus, Alexandru-Gabriel, Michael Klum, Timo Tigges, Reinhold Orglmeister, and Mike Urban. "Progressive Dynamic Time Warping for Noninvasive Blood Pressure Estimation." Current Directions in Biomedical Engineering 6, no. 3 (September 1, 2020): 579–82. http://dx.doi.org/10.1515/cdbme-2020-3148.

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AbstractArterial blood pressure is one of the most important cardiovascular parameters. Yet, current-generation devices for continuous, noninvasive acquisition are few, expensive and bulky. Novel signal processing applied to easily acquired unimodal signals can alleviate this issue, reducing size, cost and expanding the use of such devices to ambulatory, everyday settings. The features of pulse waves acquired by photo- or impedance-plethysmography can be used to estimate the underlying blood pressure. We present a progressive dynamic time warping algorithm, which implicitly parametrizes the morphological changes in these waves. This warping method is universally applicable to most pulse wave shapes, as it is largely independent of fiducial point detection or explicit parametrization. The algorithm performance is validated in a feature selection and regression framework against a continuous, noninvasive Finapres NOVA monitor, regarding systolic, mean and diastolic pressures during a light physical strain test protocol on four clinically healthy subjects (age18- 33, one female). The obtained mean error is 2.13 mmHg, the mean absolute error is 5.4 mmHg and the standard deviation is 5.6 mmHg. These results improve on our previous work on dynamic time warping. Using single-sensor, peripherally acquired pulse waves, progressive dynamic time warping can thus improve the flexibility of noninvasive, continuous blood pressure estimation.
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C.Bhokse, Bhushan, and Bhushan S. Thakare. "Devnagari Handwriting Recognition System using Dynamic Time Warping Algorithm." International Journal of Computer Applications 52, no. 9 (August 30, 2012): 7–13. http://dx.doi.org/10.5120/8228-0241.

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Dissertations / Theses on the topic "Dynamic time warping algorithm"

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Operti, Felipe Gioachino. "Interpolation strategy based on Dynamic Time Warping." reponame:Repositório Institucional da UFC, 2015. http://www.repositorio.ufc.br/handle/riufc/11446.

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OPERTI, Felipe Gioachino. Interpolation strategy based on Dynamic Time Warping. 2015. 53 f. Dissertação (Mestrado em Física) - Programa de Pós-Graduação em Física, Departamento de Física, Centro de Ciências, Universidade Federal do Ceará, Fortaleza, 2015.
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In oil industry, it is essential to have the knowledge of the stratified rocks’ lithology and, as consequence, where are placed the oil and the natural gases reserves, in order to efficiently drill the soil, without a major expense. In this context, the analysis of seismological data is highly relevant for the extraction of such hydrocarbons, producing predictions of profiles through reflection of mechanical waves in the soil. The image of the seismic mapping produced by wave refraction and reflection into the soil can be analysed to find geological formations of interest. In 1978, H. Sakoe et al. defined a model called Dynamic Time Warping (DTW)[23] for the local detection of similarity between two time series. We apply the Dynamic Time Warping Interpolation (DTWI) strategy to interpolate and simulate a seismic landscape formed by 129 depth-dependent sequences of length 201 using different values of known sequences m, where m = 2, 3, 5, 9, 17, 33, 65. For comparison, we done the same operation of interpolation using a Standard Linear Interpolation (SLI). Results show that the DTWI strategy works better than the SLI when m = 3, 5, 9, 17, or rather when distance between the known series has the same order size of the soil layers.
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Sinkus, Skirmantas. "Kinect įrenginiui skirtų gestų atpažinimo algoritmų tyrimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20140806_143213-09689.

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Microsoft Kinect įrenginys išleistas tik 2010 metais. Jis buvo skirtas Microsoft Xbox 360 vaizdo žaidimų konsolei, vėliau 2012 metais buvo pristatytas Kinect ir Windows personaliniams kompiuteriams. Taigi tai palyginus naujas įrenginys ir aktualus šiai dienai. Daugiausiai yra sukurta kompiuterinių žaidimų, kurie naudoja Microsoft Kinect įrenginį, bet šį įrenginį galima panaudoti daug plačiau ne tik žaidimuose, viena iš sričių tai sportas, konkrečiau treniruotės, kurias būtų galima atlikti namuose. Šiuo metu pasaulyje yra programinės įrangos, žaidimų, sportavimo programų, kuri leidžia kontroliuoti treniruočių eigą sekdama ar žmogus teisingai atlieka treniruotėms numatytus judesius. Kadangi Lietuvoje panašios programinės įrangos nėra, taigi reikia sukurti įrangą, kuri leistų Lietuvos treneriams kurti treniruotes orientuotas į šio įrenginio panaudojimą. Šio darbo pagrindinis tikslas yra atlikti Kinect įrenginiui skirtų gestų atpažinimo algoritmų tyrimą, kaip tiksliai jie gali atpažinti gestus ar gestą. Pagrindinis dėmesys skiriamas šiai problemai, taip pat keliami, bet netyrinėjami kriterijai kaip atpažinimo laikas, bei realizacijos sunkumas. Šiame darbe sukurta programa, judesius bei gestus atpažįsta naudojant Golden Section Search algoritmą. Algoritmas palygina du modelius ar šablonus, ir jei neranda atitikmens, tai pirmasis šablonas šiek tiek pasukamas ir lyginimo procesas paleidžiamas vėl, taipogi tam tikro kintamojo dėka galime keisti algoritmo tikslumą. Taipogi... [toliau žr. visą tekstą]
Microsoft Kinect device was released in 2010. It was designed for Microsoft Xbox 360 gaming console, later on in 2012 was presented Kinect device for Windows personal computer. So this device is new and current. Many games has been created for Microsoft Kinect device, but this device could be used not only in games, one of the areas where we can use it its sport, specific training, which can be performed at home. At this moment in world are huge variety of games, software, training programs which allows user to control training course by following a person properly perform training provided movements. Since in Lithuania similar software is not available, so it is necessary to create software that would allow Lithuania coaches create training focused on the use of this device. The main goal of this work is to perform research of the Kinect device gesture recognition algorithms to study exactly how they can recognize gestures or gesture. It will focus on this issue mainly, but does not address the criteria for recognition as the time and difficulty of realization. In this paper, a program that recognizes movements and gestures are using the Golden section search algorithm. Algorhithm compares the two models or templates, and if it can not find a match, this is the first template slightly rotated and comparison process is started again, also a certain variable helping, we can modify the algorithm accuracy. Also for comparison we can use Hidden Markov models algorhithm received... [to full text]
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Кононенко, Олексій Сергійович. "Дослідження системи розпізнавання голосових сигналів в умовах обмеженої обчисленої потужності." Master's thesis, Київ, 2018. https://ela.kpi.ua/handle/123456789/23167.

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Актуальність теми. Зараз систем розпізнавання мовлення набувають все більшої популярності та зустрічаються все частіше. Успішними прикладами використання технології розпізнавання мови в мобільних додатках є: введення адреси голосом в Яндекс.Навігатор, голосовий пошук Google Now. Крім мобільних пристроїв, технологія розпізнавання мови знаходить широке поширення в різноманітних сферах людської діяльності: ● Телефонія: автоматизація обробки вхідних і вихідних дзвінків шляхом створення голосових систем самообслуговування зокрема для: отримання довідкової інформації та консультування, замовлення послуг, товарів, зміни параметрів чинних послуг, проведення опитувань, анкетування, збору інформації, інформування та будь-які інші сценарії; ● Рішення "Розумний будинок": голосовий інтерфейс управління системами «Розумний будинок»; ● Побутова техніка і роботи: голосовий інтерфейс електронних роботів; голосове керування побутовою технікою тощо; ● Автомобілі: голосове управління в салоні автомобіля - наприклад, навігаційною системою; ● Соціальні сервіси для людей з обмеженими можливостями; ● Комплексні системи захисту інформації. Голосова аутентифікація. ● Визначення емоційного забарвлення голосу диктора. Об’єктом дослідження є процес розпізнавання голосових сигналів. Предметом дослідження є методи та моделі розпізнавання голосових сигналів в умовах обмеженої обчислювальної потужності. Мета роботи: підвищення ефективності процесу розпізнавання голосових сигналів в умовах обмеженої обчислювальної потужності. Методи дослідження. В роботі використовуються методи математичного моделювання, методи оптимізації, методи системного аналізу, чисельні методи.
Theme urgency. Speech recognition systems are becoming increasingly popular and increasingly common. Successful examples of using speech recognition technology in mobile applications are: entering a voice address in Yandex.Navigator, Google Now voice search. In addition to mobile devices, speech recognition technology is widely used in various areas of human activity: ● Telephony: automates the processing of incoming and outgoing calls by creating voice self-service systems in particular for: receiving background information and advice, ordering services, goods, changing the parameters of current services, conducting surveys, questionnaires, collecting information, informing and any other scenarios; ● “Smart House” solutions: voice interface for intelligent home systems management; ● Household appliances and work: voice interface of electronic robots; voice control of home appliances, etc .; ● Cars: voice control in the car - for example, the navigation system; ● Social services for people with disabilities; ● Comprehensive information security systems. Voice authentication. ● Determination of the emotional color of the speaker's voice. Object of research are systems and algorithms for voice recognition. Subject of research is a usage of dynamic time warping algorithm in speech recognition systems in the conditions of limited computing power Research objective: development and modification of the dynamic time warping algorithm for recognizing a limited vocabulary. Research methods. Methods of mathematical modeling, methods of optimization, methods of system analysis, numerical methods are used in this work.
Актуальность темы. Сейчас системы распознавания речи приобретают все большую популярность и встречаются все чаще. Успешными примерами использования технологии распознавания речи в мобильных приложениях являются: ввод адреса голосом в Яндекс.Навигатор, голосовой поиск Google Now. Кроме мобильных устройств, технология распознавания речи находит широкое распространение в различных сферах человеческой деятельности: ● Телефония: автоматизация обработки входящих и исходящих звонков путем создания голосовых систем самообслуживания в частности для: получения справочной информации и консультирование, заказ услуг, товаров, изменения параметров действующих услуг, проведения опросов, анкетирования, сбора информации, информирование и любые другие сценарии; ● Решение "Умный дом": голосовой интерфейс управления системами «Умный дом»; ● Бытовая техника и работы: голосовой интерфейс электронных роботов голосовое управление бытовой техникой и т.д.; ● Автомобили: голосовое управление в салоне автомобиля - например, навигационной системой; ● Социальные сервисы для людей с ограниченными возможностями; ● Комплексные системы защиты информации. Голосовая аутентификация. ● Определение эмоциональной окраски голоса диктора. Объектом исследования являются системы и алгоритмы распознавания голосовых сигналов. Предметом исследования является алгоритм динамической трансформации временной шкалы в системах распознавания голосовых сигналов в условиях ограниченной вычислительной мощности. Цель работы: разработка и модификация алгоритма динамической трансформации временной шкалы для распознавания ограниченного словаря. Методы исследования. В работе используются методы математического моделирования, методы оптимизации, методы системного анализа, численные методы.
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Fitriani. "Multiscale Dynamic Time and Space Warping." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45279.

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Thesis (S.M.)--Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2008.
Includes bibliographical references (p. 149-151).
Dynamic Time and Space Warping (DTSW) is a technique used in video matching applications to find the optimal alignment between two videos. Because DTSW requires O(N4) time and space complexity, it is only suitable for short and coarse resolution videos. In this thesis, we introduce Multiscale DTSW: a modification of DTSW that has linear time and space complexity (O(N)) with good accuracy. The first step in Multiscale DTSW is to apply the DTSW algorithm to coarse resolution input videos. In the next step, Multiscale DTSW projects the solution from coarse resolution to finer resolution. A solution for finer resolution can be found effectively by refining the projected solution. Multiscale DTSW then repeatedly projects a solution from the current resolution to finer resolution and refines it until the desired resolution is reached. I have explored the linear time and space complexity (O(N)) of Multiscale DTSW both theoretically and empirically. I also have shown that Multiscale DTSW achieves almost the same accuracy as DTSW. Because of its efficiency in computational cost, Multiscale DTSW is suitable for video detection and video classification applications. We have developed a Multiscale-DTSW-based video classification framework that achieves the same accuracy as a DTSW-based video classification framework with greater than 50 percent reduction in the execution time. We have also developed a video detection application that is based on Dynamic Space Warping (DSW) and Multiscale DTSW methods and is able to detect a query video inside a target video in a short time.
by Fitriani.
S.M.
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Hounsinou, Sena Gladys N. "Hardware realization of speech-time warping algorithm /." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1650508391&sid=1&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Júnior, Sylvio Barbon. "Dynamic Time Warping baseado na transformada wavelet." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/76/76132/tde-15042008-211812/.

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Dynamic Time Warping (DTW) é uma técnica do tipo pattern matching para reconhecimento de padrões de voz, sendo baseada no alinhamento temporal de um sinal com os diversos modelos de referência. Uma desvantagem da DTW é o seu alto custo computacional. Este trabalho apresenta uma versão da DTW que, utilizando a Transformada Wavelet Discreta (DWT), reduz a sua complexidade. O desempenho obtido com a proposta foi muito promissor, ganhando em termos de velocidade de reconhecimento e recursos de memória consumidos, enquanto a precisão da DTW não é afetada. Os testes foram realizados com alguns fonemas extraídos da base de dados TIMIT do Linguistic Data Consortium (LDC)
Dynamic TimeWarping (DTW) is a pattern matching technique for speech recognition, that is based on a temporal alignment of the input signal with the template models. One drawback of this technique is its high computational cost. This work presents a modified version of the DTW, based on the DiscreteWavelet Transform (DWT), that reduces the complexity of the original algorithm. The performance obtained with the proposed algorithm is very promising, improving the recognition in terms of time and memory allocation, while the precision is not affected. Tests were performed with speech data collected from TIMIT corpus provided by Linguistic Data Consortium (LDC).
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Coelho, Mariana Sátiro. "Patterns in financial markets: Dynamic time warping." Master's thesis, NSBE - UNL, 2012. http://hdl.handle.net/10362/9539.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
This work project introduces the performance of the algorithm Dynamic Time Warping amidst trading strategies in the financial markets. The employed procedure allows the comparison between any two sequences of data with different time lengths. Different features for the method were implemented, although those did not improve its promptness or accuracy in the outcomes obtained. Two potential investment strategies are presented within this theme. One yielded satisfactory outcomes whilst the other resulted in inconsistent values. The results point to the possible existence of patterns in the Equity Indexes’ behaviour, as well as their distortion across the time axis.
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Ko, Ming Hsiao. "Using dynamic time warping for multi-sensor fusion." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/384.

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Fusion is a fundamental human process that occurs in some form at all levels of sense organs such as visual and sound information received from eyes and ears respectively, to the highest levels of decision making such as our brain fuses visual and sound information to make decisions. Multi-sensor data fusion is concerned with gaining information from multiple sensors by fusing across raw data, features or decisions. The traditional frameworks for multi-sensor data fusion only concern fusion at specific points in time. However, many real world situations change over time. When the multi-sensor system is used for situation awareness, it is useful not only to know the state or event of the situation at a point in time, but also more importantly, to understand the causalities of those states or events changing over time.Hence, we proposed a multi-agent framework for temporal fusion, which emphasises the time dimension of the fusion process, that is, fusion of the multi-sensor data or events derived over a period of time. The proposed multi-agent framework has three major layers: hardware, agents, and users. There are three different fusion architectures: centralized, hierarchical, and distributed, for organising the group of agents. The temporal fusion process of the proposed framework is elaborated by using the information graph. Finally, the core of the proposed temporal fusion framework – Dynamic Time Warping (DTW) temporal fusion agent is described in detail.Fusing multisensory data over a period of time is a challenging task, since the data to be fused consists of complex sequences that are multi–dimensional, multimodal, interacting, and time–varying in nature. Additionally, performing temporal fusion efficiently in real–time is another challenge due to the large amount of data to be fused. To address these issues, we proposed the DTW temporal fusion agent that includes four major modules: data pre-processing, DTW recogniser, class templates, and decision making. The DTW recogniser is extended in various ways to deal with the variability of multimodal sequences acquired from multiple heterogeneous sensors, the problems of unknown start and end points, multimodal sequences of the same class that hence has different lengths locally and/or globally, and the challenges of online temporal fusion.We evaluate the performance of the proposed DTW temporal fusion agent on two real world datasets: 1) accelerometer data acquired from performing two hand gestures, and 2) a benchmark dataset acquired from carrying a mobile device and performing pre-defined user scenarios. Performance results of the DTW based system are compared with those of a Hidden Markov Model (HMM) based system. The experimental results from both datasets demonstrate that the proposed DTW temporal fusion agent outperforms HMM based systems, and has the capability to perform online temporal fusion efficiently and accurately in real–time.
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Ko, Ming Hsiao. "Using dynamic time warping for multi-sensor fusion." Curtin University of Technology, Department of Computing, 2009. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=129032.

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Fusion is a fundamental human process that occurs in some form at all levels of sense organs such as visual and sound information received from eyes and ears respectively, to the highest levels of decision making such as our brain fuses visual and sound information to make decisions. Multi-sensor data fusion is concerned with gaining information from multiple sensors by fusing across raw data, features or decisions. The traditional frameworks for multi-sensor data fusion only concern fusion at specific points in time. However, many real world situations change over time. When the multi-sensor system is used for situation awareness, it is useful not only to know the state or event of the situation at a point in time, but also more importantly, to understand the causalities of those states or events changing over time.
Hence, we proposed a multi-agent framework for temporal fusion, which emphasises the time dimension of the fusion process, that is, fusion of the multi-sensor data or events derived over a period of time. The proposed multi-agent framework has three major layers: hardware, agents, and users. There are three different fusion architectures: centralized, hierarchical, and distributed, for organising the group of agents. The temporal fusion process of the proposed framework is elaborated by using the information graph. Finally, the core of the proposed temporal fusion framework – Dynamic Time Warping (DTW) temporal fusion agent is described in detail.
Fusing multisensory data over a period of time is a challenging task, since the data to be fused consists of complex sequences that are multi–dimensional, multimodal, interacting, and time–varying in nature. Additionally, performing temporal fusion efficiently in real–time is another challenge due to the large amount of data to be fused. To address these issues, we proposed the DTW temporal fusion agent that includes four major modules: data pre-processing, DTW recogniser, class templates, and decision making. The DTW recogniser is extended in various ways to deal with the variability of multimodal sequences acquired from multiple heterogeneous sensors, the problems of unknown start and end points, multimodal sequences of the same class that hence has different lengths locally and/or globally, and the challenges of online temporal fusion.
We evaluate the performance of the proposed DTW temporal fusion agent on two real world datasets: 1) accelerometer data acquired from performing two hand gestures, and 2) a benchmark dataset acquired from carrying a mobile device and performing pre-defined user scenarios. Performance results of the DTW based system are compared with those of a Hidden Markov Model (HMM) based system. The experimental results from both datasets demonstrate that the proposed DTW temporal fusion agent outperforms HMM based systems, and has the capability to perform online temporal fusion efficiently and accurately in real–time.
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Aguiar, Rogerio Oliveira de. "Classificador Automático e Não-Supervisionado de Batimentos Cardíacos Baseado no Algoritmo Dynamic Tiime Warping." Universidade Federal do Espírito Santo, 2008. http://repositorio.ufes.br/handle/10/4066.

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Made available in DSpace on 2016-08-29T15:32:29Z (GMT). No. of bitstreams: 1 tese_2739_DissRogerio.pdf: 1432885 bytes, checksum: b8457c304a8ccffb2eed042bbebb5614 (MD5) Previous issue date: 2008-07-23
O Projeto Telecardio é um projeto de pesquisa em telemonitoramento de pacientes cardíacos e identificação automática de situações de risco. Neste contexto, está sendo proposto um sistema de análise de eletrocardiograma como uma ferramenta de auxílio ao diagnóstico médico. O sistema classifica os batimentos de um registro de ECG ambulatorial tendo como referência o batimento predominante do paciente. A classificação se dá através de uma abordagem original não supervisionada que faz uso do método Alinhamento Temporal Dinâmico na comparação entre batimentos com tamanhos e formas diferentes. Além disso, é tratado neste trabalho o problema da classificação de batimentos prematuros a partir do estudo de rótulos feitos por cardiologistas nos batimentos da base utilizada neste trabalho. Por fim, é proposta uma interface gráfica que apresenta o resultado da análise realizada pelo sistema de classificação, destacando-se informações importantes e a morfologias dos batimentos predominantes ao longo de trechos do ECG. Os batimentos predominantes são determinados por um algoritmo original que realiza o cálculo do batimento médio a partir de um conjunto de batimentos. O sistema foi testado na MIT-BIH Arrhythmia Database e os resultados alcançados validaram a estratégia proposta.
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Books on the topic "Dynamic time warping algorithm"

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Koehler, Loren M. Cursive script recognition using a dynamic time warping method. 1988.

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Book chapters on the topic "Dynamic time warping algorithm"

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Bringmann, Karl, Nick Fischer, Ivor van der Hoog, Evangelos Kipouridis, Tomasz Kociumaka, and Eva Rotenberg. "Dynamic Dynamic Time Warping." In Proceedings of the 2024 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 208–42. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2024. http://dx.doi.org/10.1137/1.9781611977912.10.

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Bugdol, Marcin, Zuzanna Segiet, and Michał Kręcichwost. "Pronunciation Error Detection Using Dynamic Time Warping Algorithm." In Advances in Intelligent Systems and Computing, 345–54. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06596-0_32.

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Tsinaslanidis, Prodromos E., and Achilleas D. Zapranis. "Dynamic Time Warping for Pattern Recognition." In Technical Analysis for Algorithmic Pattern Recognition, 193–204. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23636-0_9.

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Sood, Meenakshi, and Shruti Jain. "Speech Recognition Employing MFCC and Dynamic Time Warping Algorithm." In Innovations in Information and Communication Technologies (IICT-2020), 235–42. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66218-9_27.

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Chen, Bo-Xian, Kuo-Tsung Tseng, and Chang-Biau Yang. "A Minimum-First Algorithm for Dynamic Time Warping on Time Series." In Communications in Computer and Information Science, 449–56. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9190-3_48.

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Zhou, Mi. "An OGS-Based Dynamic Time Warping Algorithm for Time Series Data." In Contributions to Economics, 115–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41585-2_10.

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Buchin, Maike, Anne Driemel, Koen van Greevenbroek, Ioannis Psarros, and Dennis Rohde. "Approximating Length-Restricted Means Under Dynamic Time Warping." In Approximation and Online Algorithms, 225–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18367-6_12.

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Maouche, Fadila, and Mohamed Benmohammed. "Dynamic Time Warping Inside a Genetic Algorithm for Automatic Speech Recognition." In Modelling and Implementation of Complex Systems, 180–92. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05481-6_14.

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Long, Wei, Shuyan Pan, and Hai Wu. "Distribution Network Differential Protection Method Based on Dynamic Time Warping Algorithm." In Lecture Notes in Electrical Engineering, 29–42. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7156-2_3.

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Graniero, Paolo, and Marco Gärtler. "Prediction of Batch Processes Runtime Applying Dynamic Time Warping and Survival Analysis." In Machine Learning for Cyber Physical Systems, 53–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62746-4_6.

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AbstractBatch runs corresponding to the same recipe usually have different duration. The data collected by the sensors that equip batch production lines reflects this fact: time series with different lengths and unsynchronized events. Dynamic Time Warping (DTW) is an algorithm successfully used, in batch monitoring too, to synchronize and map to a standard time axis two series, an action called alignment. The online alignment of running batches, although interesting, gives no information on the remaining time frame of the batch, such as its total runtime, or time-to-end. We notice that this problem is similar to the one addressed by Survival Analysis (SA), a statistical technique of standard use in clinical studies to model time-to-event data. Machine Learning (ML) algorithms adapted to survival data exist, with increased predictive performance with respect to classical formulations. We apply a SA-ML-based system to the problem of predicting the time-to-end of a running batch, and show a new application of DTW. The information returned by openended DTW can be used to select relevant data samples for the SA-ML system, without negatively affecting the predictive performance and decreasing the computational cost with respect to the same SA-ML system that uses all the data available. We tested the system on a real-world dataset coming from a chemical plant.
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Conference papers on the topic "Dynamic time warping algorithm"

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Zaharia, Tiberius, Svetlana Segarceanu, Marius Cotescu, and Alexandru Spataru. "Quantized Dynamic Time Warping (DTW) algorithm." In 2010 8th International Conference on Communications (COMM). IEEE, 2010. http://dx.doi.org/10.1109/iccomm.2010.5509068.

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Lou, Yuansheng, Huanhuan Ao, and Yuchao Dong. "Improvement of Dynamic Time Warping (DTW) Algorithm." In 2015 14th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES). IEEE, 2015. http://dx.doi.org/10.1109/dcabes.2015.103.

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Taghavi, Nazita, Jacob Berdichevsky, Namrata Balakrishnan, Karla C. Welch, Sumit Kumar Das, and Dan O. Popa. "Online Dynamic Time Warping Algorithm for Human-Robot Imitation." In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021. http://dx.doi.org/10.1109/icra48506.2021.9562110.

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Tai, James Shueyen, Kin Fun Li, and Haytham Elmiligi. "Dynamic Time Warping Algorithm: A Hardware Realization in VHDL." In 2013 International Conference on IT Convergence and Security (ICITCS). IEEE, 2013. http://dx.doi.org/10.1109/icitcs.2013.6717829.

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Ying, Rex, Jiangwei Pan, Kyle Fox, and Pankaj K. Agarwal. "A simple efficient approximation algorithm for dynamic time warping." In SIGSPATIAL'16: 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2996913.2996954.

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Junhua, Chang, Li Hua, Li Xinhao, and Li Xianing. "Application of Dynamic Time Warping Algorithm in Oilfield Development." In 2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2019. http://dx.doi.org/10.1109/icaica.2019.8873502.

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Angus, J. A. S., and M. T. Whitaker. "An algorithm for increasing speed in dynamic time warping." In European Conference on Speech Technology. ISCA: ISCA, 1987. http://dx.doi.org/10.21437/ecst.1987-43.

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Bisht, Yashwant Singh. "Low Energy Data Aggregation Using Dynamic Time Warping Algorithm." In 2024 3rd International Conference for Innovation in Technology (INOCON). IEEE, 2024. http://dx.doi.org/10.1109/inocon60754.2024.10511314.

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Zhou, Mi. "An OGS-based Dynamic Time Warping algorithm for time series data." In 2013 International Conference on Engineering, Management Science and Innovation (ICEMSI). IEEE, 2013. http://dx.doi.org/10.1109/icemsi.2013.6913981.

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Yuxin, Zhang, and Yoshikazu Miyanaga. "An improved dynamic time warping algorithm employing nonlinear median filtering." In 2011 11th International Symposium on Communications and Information Technologies (ISCIT). IEEE, 2011. http://dx.doi.org/10.1109/iscit.2011.6089967.

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Reports on the topic "Dynamic time warping algorithm"

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Eslami, Keyvan, and Thomas M. Phelan. The Art of Temporal Approximation: An Investigation into Numerical Solutions to Discrete and Continuous-Time Problems in Economics. Federal Reserve Bank of Cleveland, May 2023. http://dx.doi.org/10.26509/frbc-wp-202310.

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A recent literature within quantitative macroeconomics has advocated the use of continuous-time methods for dynamic programming problems. In this paper we explore the relative merits of continuous-time and discrete-time methods within the context of stationary and nonstationary income fluctuation problems. For stationary problems in two dimensions, the continuous-time approach is both more stable and typically faster than the discrete-time approach for any given level of accuracy. In contrast, for convex lifecycle problems (in which age or time enters explicitly), simply iterating backwards from the terminal date in discrete time is superior to any continuous-time algorithm. However, we also show that the continuous-time framework can easily incorporate nonconvexities and multiple controls—complications that often require either problem-specific ingenuity or nonlinear root-finding in the discrete-time context. In general, neither approach unequivocally dominates the other, making the choice of one over the other an art, rather than an exact science. Code can be found at https://github.com/tphelanECON/The Art of Temporal Approximation WP.
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Kuznetsov, Victor, Vladislav Litvinenko, Egor Bykov, and Vadim Lukin. A program for determining the area of the object entering the IR sensor grid, as well as determining the dynamic characteristics. Science and Innovation Center Publishing House, April 2021. http://dx.doi.org/10.12731/bykov.0415.15042021.

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Currently, to evaluate the dynamic characteristics of objects, quite a large number of devices are used in the form of chronographs, which consist of various optical, thermal and laser sensors. Among the problems of these devices, the following can be distinguished: the lack of recording of the received data; the inaccessibility of taking into account the trajectory of the object flying in the sensor area, as well as taking into consideration the trajectory of the object during the approach to the device frame. The signal received from the infrared sensors is recorded in a separate document in txt format, in the form of a table. When you turn to the document, data is read from the current position of the input data stream in the specified list by an argument in accordance with the given condition. As a result of reading the data, it forms an array that includes N number of columns. The array is constructed in a such way that the first column includes time values, and columns 2...N- the value of voltage . The algorithm uses cycles that perform the function of deleting array rows where there is a fact of exceeding the threshold value in more than two columns, as well as rows where the threshold level was not exceeded. The modified array is converted into two new arrays, each of which includes data from different sensor frames. An array with the coordinates of the centers of the sensor operation zones was created to apply the Pythagorean theorem in three-dimensional space, which is necessary for calculating the exact distance between the zones. The time is determined by the difference in the response of the first and second sensor frames. Knowing the path and time, we are able to calculate the exact speed of the object. For visualization, the oscillograms of each sensor channel were displayed, and a chronograph model was created. The chronograph model highlights in purple the area where the threshold has been exceeded.
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Morkun, Vladimir S., Natalia V. Morkun, and Andrey V. Pikilnyak. Augmented reality as a tool for visualization of ultrasound propagation in heterogeneous media based on the k-space method. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3757.

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For programming the AR tools, interactive objects and creating the markers, the method of fiber spaces (k-space) for modeling of ultrasonic wave propagation in an inhomogeneous medium using coarse grids, with maintaining the required accuracy was used. The algorithm and tools of augmented reality were introduced into the adaptive control system of the pulp gas phase in the iron ore flotation process using a control action on the basis of high-energy ultrasound dynamic effects generated by ultrasonic phased arrays. The tools of augmented reality based on k-space methods allow to facilitate wider adoption of ultrasound technology and visualize the ultra-sound propagation in heterogeneous media by providing a specific correspondence between the ultrasound data acquired in real- time and a sufficiently detailed augmented 3D scene. The tools of augmented reality allow seeing the field of ultrasound propagation, its characteristics, as well as the effect of the dynamic effects of ultrasound on the change in the gas phase during the flotation process.
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Witzig, Andreas, Camilo Tello, Franziska Schranz, Johannes Bruderer, and Matthias Haase. Quantifying energy-saving measures in office buildings by simulation in 2D cross sections. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541623658.

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A methodology is presented to analyse the thermal behaviour of buildings with the goal to quantify energy saving measures. The solid structure of the building is modelled with finite elements to fully account for its ability to store energy and to accurately predict heat loss through thermal bridges. Air flow in the rooms is approximated by a lumped element model with three dynamical nodes per room. The dynamic model also contains the control algorithm for the HVAC system and predicts the net primary energy consumption for heating and cooling of the building for any time period. The new simulation scheme has the advantage to avoid U-values and thermal bridge coefficients and instead use well-known physical material parameters. It has the potential to use 2D and 3D geometries with appropriate automatic processing from BIM models. Simulations are validated by comparison to IDA ICE and temperature measurement. This work aims to discuss novel approaches to disseminating building simulation more widely.
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BARKHATOV, NIKOLAY, and SERGEY REVUNOV. A software-computational neural network tool for predicting the electromagnetic state of the polar magnetosphere, taking into account the process that simulates its slow loading by the kinetic energy of the solar wind. SIB-Expertise, December 2021. http://dx.doi.org/10.12731/er0519.07122021.

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The auroral activity indices AU, AL, AE, introduced into geophysics at the beginning of the space era, although they have certain drawbacks, are still widely used to monitor geomagnetic activity at high latitudes. The AU index reflects the intensity of the eastern electric jet, while the AL index is determined by the intensity of the western electric jet. There are many regression relationships linking the indices of magnetic activity with a wide range of phenomena observed in the Earth's magnetosphere and atmosphere. These relationships determine the importance of monitoring and predicting geomagnetic activity for research in various areas of solar-terrestrial physics. The most dramatic phenomena in the magnetosphere and high-latitude ionosphere occur during periods of magnetospheric substorms, a sensitive indicator of which is the time variation and value of the AL index. Currently, AL index forecasting is carried out by various methods using both dynamic systems and artificial intelligence. Forecasting is based on the close relationship between the state of the magnetosphere and the parameters of the solar wind and the interplanetary magnetic field (IMF). This application proposes an algorithm for describing the process of substorm formation using an instrument in the form of an Elman-type ANN by reconstructing the AL index using the dynamics of the new integral parameter we introduced. The use of an integral parameter at the input of the ANN makes it possible to simulate the structure and intellectual properties of the biological nervous system, since in this way an additional realization of the memory of the prehistory of the modeled process is provided.
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Tan, Peng, and Nicholas Sitar. Parallel Level-Set DEM (LS-DEM) Development and Application to the Study of Deformation and Flow of Granular Media. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, March 2023. http://dx.doi.org/10.55461/kmiz5819.

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We present a systematic investigation of computational approaches to the modeling of granular materials. Granular materials are ubiquitous in everyday life and in a variety of engineering and industrial applications. Despite the apparent simplicity of the laws governing particle-scale interactions, predicting the continuum mechanical response of granular materials still poses extraordinary challenges. This is largely due to the complex history dependence resulting from continuous rearrangement of the microstructure of granular material, as well as the mechanical interlocking due to grain morphology and surface roughness. X-Ray Computed Tomography (XRCT) is used to characterize the grain morphology and the fabric of the granular media, naturally deposited sand in this study. The Level-Set based Discrete Element Method (LS-DEM) is then used to bridge the granular behavior gap between the micro and macro scale. The LS-DEM establishes a one-to-one correspondence between granular objects and numerical avatars and captures the details of grain morphology and surface roughness. However, the high-fidelity representation significantly increases the demands on computational resources. To this end a parallel version of LS-DEM is introduced to significantly decrease the computational demands. The code employs a binning algorithm, which reduces the search complexity of contact detection from O(n2) to O(n), and a domain decomposition strategy is used to elicit parallel computing in a memory- and communication-efficient manner. The parallel implementation shows good scalability and efficiency. High fidelity LS avatars obtained from XRCT images of naturally deposited sand are then used to replicate the results of triaxial tests using the new, parallel LS-DEM code. The result show that both micro- and macro-mechanical behavior of natural material is well captured and is consistent with experimental data, confirming experimental observation that the primary source of peak strength of sand is the mechanical interlocking between irregularly shaped grains. Specifically, triaxial test simulations with a flexible membrane produce a very good match to experimentally observed relationships between deviatoric stress and mobilized friction angle for naturally deposited sand. We then explore the viability of modeling dynamic problems with a new formulation of an impulse based LS-DEM. The new formulation is stable, fast, and energy conservative. However, it can be numerically stiff when the assembly has substantial mass differences between particles. We also demonstrate the feasibility of modeling deformable structures in the rigid body framework and propose several enhancements to improve the convergence of collision resolution, including a hybrid time integration scheme to separately handle at rest contacts and dynamic collisions. Finally, we extend the impulse-based LS-DEM to include arbitrarily shaped topographic surfaces and exploit its algorithmic advantages to demonstrate the feasibility of modeling realistic behavior of granular flows. The novel formulation significantly improves performance of dynamic simulations by allowing larger time steps, which is advantageous for observing the full development of physical phenomena such as rock avalanches, which we present as an illustrative example.
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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