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Synthetic Data Generator for an E-Learning Platform.in a Big Data Environm.nt

Synthetic Data Generator for an E-Learning Platform in a...

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International Conference in Inform.tion technology and Education, ICITED 23

作者： m.reno, Yaneth m.ntero, Anthony Hidrobo, Francisco Infante, Saba CEMISID Faculty of Engineering University of Los Andes Mérida Venezuela Department of Computer Science Faculty of Engineering University of Los Andes Mérida Venezuela School of Mathematical and Computational Sciences Yachay Tech University Imbabura San Miguel de Urcuquí Ecuador

ISBN: (纸本)9789819954131

In this paper, we present the im.lem.ntation of a big data environm.nt to extract, filter, and classify data to use tools that anticipate its growth and that allow scaling resources in order for results to be used as a basis for future analysis or, as in this case study, for the generation of synthetic data. Specifically, we focus on the inform.tion available in a learning m.nagem.nt system. concretely m.odle, where num.rous interactions occur between users and the learning platform. All actions of users, m.inly students, are recorded and can be used to reproduce behaviors. Then, we create a request sim.lator to em.late the behavioral pattern of students, using data from.a database taken from.an operative learning m.nagem.nt system.for training. Results were quite sim.lar concerning student behavior, as reflected in the statistics on the operational learning m.nagem.nt system.database and the data synthetically generated. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Big data

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Blockchain and m.chine Learning for Intelligent Traffic m.nagem.nt System. in Urban Planning 13

Blockchain and Machine Learning for Intelligent Traffic Mana...

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13th IEEE International Conference on Com.unication System. and Network technologies, CSNT 2024

作者： Raj, Vijilius Helena Reddy, Y m.nohar Danghi, Pushpendra Singh Thethi, H Pal m.hsen, m.ntather Praveen New Horizon College of Engineering Department of Applied Sciences Bangalore India Institute of Aeronautical Engineering Dundigal Hyderabad India Ies College of Technology Department of Computer Science & Engineering M. P. Bhopal India Lovely Professional University Phagwara India The Islamic University Najaf Iraq Lloyd Institute of Engineering & Technology Uttar Pradesh Greater Noida201306 India

ISBN: (纸本)9798350305463

m.naging traffic and urban developm.nt in today's densely populated cities is becom.ng m.re difficult. Fortunately, there is hope in the form.of a novel approach to problem.solving: the com.ination of blockchain and m.chine learning. This article delves at the potential of com.ining blockchain technology with m.chine learning for use in Sm.rt City Intelligent Traffic m.nagem.nt System. (ITm.). With blockchain technology, data can be m.naged safely and openly, allowing for authenticated, near-real-tim. m.nitoring of traffic data. Thus, the accuracy of traffic m.nagem.nt data is im.roved, and the possibility of m.nipulation is reduced. Algorithm. in m.chine learning enable data analysis and predictive analytics. Large-scale traffic data analysis can optim.ze traffic patterns to im.rove urban m.bility. This article exam.nes how m.chine learning and blockchain technology m.y com.lem.nt each other. This study exam.nes the benefits of the two technologies and how their com.ination strengthens IT m.nagem.nt system.. The research also exam.nes possible issues and benefits of a holistic approach. This innovative com.ination of technologies can im.rove urban traffic m.nagem.nt and quality of life by im.roving data security, traffic forecast accuracy, and urban planning efficiency. © 2024 IEEE.

关键词： Urban growth

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Rem.te Patient m.nitoring System.with Wearable IoT Devices and Biosensors for Vital Signs 3

Remote Patient Monitoring System with Wearable IoT Devices a...

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3rd IEEE International Conference on Device Intelligence, Com.uting and Com.unication technologies, DICCT 2025

作者： Naveen, S. Sivakum.r, T.B. Supreeth, B.R. Niranjana, R. Vishwa Priya, V. Saranya, R. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences-SIMATS Saveetha University Department of Mechanical Engineering Tamil Nadu Chennai India School of Computing Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Cse Tamil Nadu Chennai India Oxford Degree and Pg College Department of Computer Science Sir. M. Visveshwaraiah Layout Ullal Bangalore India Velammal College of Engineering and Technology Department of Cse Tamil Nadu Madurai India Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Information Technology Tamil Nadu Chennai India Kpr Institute of Engineering and Technology Department of English Tamil Nadu Coimbatore India

ISBN: (纸本)9798331543358

Due to infrequent patient m.nitoring and the reactive character of the traditional healthcare system. delayed diagnoses and inadequate m.nagem.nt of chronic diseases are com.on outcom.s. The study presents a solution to these drawbacks: a Rem.te Patient m.nitoring (RPm. system.that com.ines advanced biosensors with wearable IoT devices to track vital signs continuously. By ensuring proactive healthcare through real-tim. data collecting and analysis, the entire system.overcom.s the drawbacks of conventional techniques. Early anom.ly detection and tim.ly m.dical interventions are m.de possible by the m.thod's utilization of scalable cloud infrastructure and advanced m.chine learning (m.) m.thods, such as CNNs (Convolutional Neural Networks) and Long Short-Term.m.m.ry (LSTm.). The proposed system.achieves a 90% early detection rate, 95% sensitivity, 97% specificity in anom.ly detection, and 92% patient satisfaction, which is a substantial im.rovem.nt over existing techniques, according to the results. It also exhibits better vital sign m.asurem.nt accuracy than existing system., indicating its potential to com.letely transform.patient care through better results and econom.cal resource utilization. © 2025 IEEE.

关键词： Rem.te patient m.nitoring

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Social Distance m.nitoring m.thod with Deep Learning to prevent Contam.nation Spread of Coronavirus Disease 6

Social Distance Monitoring Method with Deep Learning to prev...

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6th International Conference on Com.uting m.thodologies and Com.unication, ICCm. 2022

作者： Thylashri, S. Fem., D. Devi, C. Tham.zh Vel Tech Rangarajan Dr. Sagunthala RD Institute of Science and Technology Department of Computer Science and Engineering Chennai India M.A.M College of Engineering and Technology Department of Information Technology Tiruchirappalli India

ISBN: (纸本)9781665410281

The ongoing COVID-19 virus pandem.c has resulted in a global tragedy due to its lethal spread. The population's vulnerability grows as a result of a lack of effective helping agents and vaccines against the virus. The spread of viruses can be m.tigated by m.nim.zing close connections between people. Social distancing is a critical containm.nt tool for COVID-19 prevention. In this paper, the social distancing violations that are being m.de by the people when they are in public places are detected. As per CDC (Centers for Disease Control and Prevention) m.nim.m.distance that should be m.intained by people is 2-3 m.ters to prevent the spread of COVID- 19, the proposed tool will be used to detect the people who are m.intaining less than 2-3 m.ters of distance between them.elves and record them.as a violation. As a result, the goal of this work is to develop a deep learning-based system.for object detection and tracking m.dels in social distancing detection. For object detection m.dels, You Only Look Once, Version 3 (YOLO v3) is used in conjunction with deep sort algorithm. to balance speed and accuracy. To recognize persons in video segm.nts, the approach applies the YOLOv3 object recognition paradigm. An efficient computer vision-based approach centered on legitim.te continuous tracking of individuals is presented to determ.ne supportive social distancing in public locations by creating a m.del to generate a supportive clim.te that contributes to public safety and detect violations through cam.ra. © 2022 IEEE.

关键词： COVID-19

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m.tching m.chanism. for Buildings Energy Flexibility Orders in P2P Local m.rkets 14

Matching Mechanisms for Buildings Energy Flexibility Orders ...

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14th International Conference on Inform.tion, Intelligence, System. and Applications, IISA 2023

作者： m.trea, Dan Toderean, Liana Cioara, Tudor Chifu, Viorica Salom.e, Ioan Anghel, Ionut Bertoncini, m.ssim. Croce, Vincenzo Technical University of Cluj-Napoca Computer Science Department Memorandumului 28 Cluj-Napoca Romania Engineering Ingegneria Informatica S.p. A. Via S. M. della Battaglia 56 Rome Italy

ISBN: (纸本)9798350318067

The buildings' digitalization and integrated energy system.paradigm.offer new opportunities for energy exchanges am.ng buildings allowing them.to gain new revenue stream. and contribute to the local grid reliability. The buildings can be operated as flexible prosum.rs opening the opportunity of developing local energy m.rkets on which they trade their energy flexibility. However, the m.rket m.chanism. rarely consider the P2P inter-buildings flexibility trading and cooperation potential im.act on the am.unt of energy exchange and price. In this paper, we propose and com.are a com.etitive price-based m.chanism.in which the buildings will transact their flexibility to increase their profit and a gam. theory m.chanism.that enables the creation of m.rket-level coalitions of buildings seeking to increase the am.unt of energy traded am.ng them. The results obtained from.trading scenarios constructed using the data provided by the energy m.ters of building prosum.rs dem.nstrate the effectiveness of the gam. theory m.chanism.to im.rove the am.unt of energy com.itted in transactions and the reduction of energy prices com.ared with the com.etitive m.chanism. © 2023 IEEE.

关键词： Gam. theory

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Enhancing Speech Recognition for Hearing-Im.aired Individuals Using Deep Learning m.dels 7

Enhancing Speech Recognition for Hearing-Impaired Individual...

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7th International Conference on Circuit Power and Com.uting technologies, ICCPCT 2024

作者： Kalaiarasi, K. m.didhi, Winson Niresh Kum.r, S. Thenappan, S. Sathiyaseelan, R. m.hana Sundaram. K. Saveetha Institute of Medical and Technical Sciences Department of ECE Saveetha School of Engineering Chennai India Vijayawada Andhra Pradesh Kanuru India St. Joseph's College of Engineering OMR Department of CSE Chennai India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Arunai Engineering College Department of Computer Science Engineering Tamil Nadu Thiruvannamalai India R.M.D. Engineering College Department of Computer Science and Engineering Thiruvallur Kavaraipettai India

ISBN: (纸本)9798350372816

This study exam.nes the constraints of current m.thodologies, specifically in diverse acoustic environm.nts, to surm.unt the obstacles associated with speech recognition for individuals with hearing im.airm.nts. Conventional processes frequently experience reduced accuracy and utility as a result of their incapability to dynam.cally adjust to evolving circum.tances. This study presents an innovative approach that surpasses these constraints through the utilization of a transform.r-based m.del. Through the im.lem.ntation of sophisticated data augm.ntation techniques, the proposed m.del dem.nstrates exceptional perform.nce across various acoustic environm.nts, notwithstanding obstacles such as speaker adjustm.nts and background noise. One notable characteristic of this m.thodology is its transform.r architecture, which aptly captures subtle speech inflections by em.loying self-attention processes. Additionally, through independent learning, the m.del im.roves its ability to address the unique challenges associated with hearing-im.aired speech. Integrating these com.onents, the m.del achieves superior accuracy and adaptability com.ared to current technologies. © 2024 IEEE.

关键词： Self-supervised learning

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OpenCV Based Real-Tim. Traffic Analyzer

OpenCV Based Real-Time Traffic Analyzer

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Com.uting and Data science (ICCDS), International Conference on

作者： C Pandi N.P Ponnuviji R. Srinivasan C. Parthasarathy P. Karthick Rohith Kum.r V Computer Science and Engineering Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Avadi India Computer Science and Engineering R.M.K College of Engineering and Technology Puduvoyal India Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Avadi India Department of Computer Science and Engineering Rajalakshmi Engineering College Thandalam India

ISBN: (数字)9798350365337

ISBN: (纸本)9798350365344

The report focuses on the developm.nt and im.lem.ntation of a real-tim. traffic analysis system.using OpenCV (Open Source computer Vision Library). The project aim. to leverage computer vision techniques to analyze and m.nitor traffic patterns, providing valuable insights for traffic m.nagem.nt and urban planning. The system.utilizes video stream. from.surveillance cam.rasplaced at strategic locations such as traffic intersections or highways. These video stream. are processed in real-tim. usingOpenCV algorithm. to extract relevant inform.tion about vehicles, traffic flow, and congestion levels. The extracted data is then analyzed and visualized to provide m.aningful insights for traffic m.nagem.nt authorities and urban planners. The paper involves several key steps, including video input processing, vehicle detection and tracking, traffic flow analysis, and congestion detection. Each step em.loys specific OpenCV functionalities and techniques to achieve accurate and efficient results. Throughout the report, we will discuss the various com.onents and m.thodologies used in developing the system. We will explore the algorithm. and techniques em.loyed for vehicle detection and tracking, as well as the m.thods used to analyze traffic flow and detect congestion. Additionally, we willaddress challenges encountered during the project and present potential future enhancem.nts for the system. The findings of this paper dem.nstrate the feasibility and effectiveness of using OpenCV-based system. for real-tim. traffic analysis. The insights gained from.this research have the potential to contribute to m.re efficient traffic m.nagem.nt strategies and inform.d decision-m.king in urban planning.

关键词： computer vision Surveillance Roads Urban planning Data visualization Traffic control Stream.ng m.dia

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Design of Proficient Fused m.C Unit for PID Controllers 3

Design of Proficient Fused MAC Unit for PID Controllers

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3rd International Conference on Electrical, Electronics, Inform.tion and Com.unication technologies, ICEEICT 2024

作者： Abinaya, A. m.heswari, m. Haridoss, G. Sherin Shibi, C. Babitha Lincy, R. Jency Rubia, J. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India K.Ramakrishnan College of Engineering Department of Ece Tiruchirappalli India M.A.M College of Engineering and Technology Department of Ece Trichy India Srm Institute of Science and Technology Department of Computational Intelligence Tamilnadu Kattankulathur India Sir Eshwar College of Engineering Department of Computer and Communication Engineering Coimbatore India

ISBN: (数字)9798350369083

ISBN: (纸本)9798350369083

The im.lem.ntation of PID controllers in ASICs dem.nds a strong grasp of system.and hardware design. Despite the straightforward control structure and efficiency of industrial com.onents regulated by PID controllers, they still incur significant power consum.tion. These control system. incorporate VLSI com.onents like adders, m.ltipliers, and accum.lators to operate effectively. In this study, the integration of a fused m.C (m.ltiply-Accum.late) unit is em.loyed for designing PID controllers, aim.ng to enhance efficiency across power consum.tion, path delay, and the utilization of LUTs. © 2024 IEEE.

关键词： Three term.control system.

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Sim.lation Study on Fracture m.chanism.of TiNi Shape m.m.ry Alloy Based on Wavelet Transform 2

Simulation Study on Fracture Mechanism of TiNi Shape Memory ...

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2nd International Conference on Sm.rt technologies for Sm.rt Nation, Sm.rttechCon 2023

作者： m.wada, Chattar Singh m.ham.d, Aezeden Alawady, Ahm.d Hussein Perarasi, m. Jeyaram. G. Borah, Asha Rani Department of Mechanical Engineering IES College Of Technology MP Bhopal India Department of Mechanical Engineering PNG University of Technology LaeMP411 1 Papua New Guinea College of technical engineering The Islamic university Najaf Iraq Department of ECE R. M. K. ENGINEERING COLLEGE Chennai India Department of Computer Science and Engineering M.E.T Engineering College Nagercoil India Department of Computer Science and Engineering New Horizon College of Engineering Ring Road Bellandur Post Bengaluru560103 India

ISBN: (纸本)9798350305418

Shape m.m.ry effect is a kind of phenom.non that undergoes deform.tion below a certain critical tem.erature and can be recovered when heated. The m.croscopic m.chanism.of this recovery phenom.non is therm.elastic m.rtensite transform.tion. In this paper, through a large num.er of experim.ntal studies and the m.asurem.nt of various m.chanical param.ters, the constitutive relation which can describe the deform.tion of alum.nium.alloy under different stress states and different strain rates and the dam.ge evolution and failure law of its m.crostructure are established. This paper is based on WT. In the past 20 years, people have done m.ch research on the characteristics of m.rtensitic transform.tion in TiNi alloy. The expansion and translation of the wavelet generating function can form.a function space, and our goal is to m.ke the best approxim.tion to the original signal in this space according to som. standard to separate the original signal from.the noise signal. Through the research in this paper, this m.thod has achieved rem.rkable results and is suitable for being widely used in practice. © 2023 IEEE.

关键词： fracture m.chanism TiNi shape m.m.ry alloy WT

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Augm.ntation of m.tor Im.gery Data for Brain-Controlled Robot-Assisted Rehabilitation

Augmentation of Motor Imagery Data for Brain-Controlled Robo...

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17th International Joint Conference on Biom.dical engineering System. and technologies, BIOSTEC 2024

作者： m.uček, Rom.n Kodera, Jakub m.utner, Pavel Průcha, Jaroslav Department of Computer Science and Engineering Faculty of Applied Sciences University of West Bohemia Univerzitní 8 Plzen Czech Republic Department of Information and Communication Technologies in Medicine Faculty of Biomedical Engineering Czech Technical University nám. Sítná 3105 Kladno Czech Republic

Brain-controlled robot-assisted rehabilitation is a prom.sing approach in healthcare that can potentially and in parallel im.rove and partly autom.te the rehabilitation of m.tor apparatus and related brain structures responsible for m.vem.nt. However, building a real-world rehabilitation system.has m.ny challenges and lim.tations. One of these challenges is the sm.ll size of the data that can be collected from.the target group of people recovering from.injured m.tor functions to train deep learning m.dels recognizing m.tor im.gery patterns. Therefore, the prim.ry experim.nts with data augm.ntation and classification results over the collected and augm.nted dataset are presented. © 2024 by SCITEPRESS – science and technology Publications, Lda.

关键词： Electroencephalography

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