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Estimating Lower Extremity joint Angles During Gait Using Reduced Number of Sensors Count Via Deep Learning 14

Estimating Lower Extremity Joint Angles During Gait Using Re...

引用

14th international conference on Digital Image Processing, ICDIP 2022

作者： Bin Hossain, Md Sanzid Choi, Hwan Guo, Zhishan Department of Electrical and Computer Engineering University of Central Florida OrlandoFL United States Department of Mechanical and Aerospace Engineering Biionix Cluster University of Central Florida OrlandoFL United States

ISBN: (纸本)9781510657564

Estimating lower extremity joint angle during gait is essential for biomechanical analysis and clinical purposes. Traditionally infrared light-based motion capture systems are used to get the joint angle information. However, such an approach is restricted to the lab environment, limiting the applicability of the method in daily living. Inertial measurement Units (IMU) sensors can solve this limitation but are needed in each body segment, causing discomfort and impracticality in everyday living. As a result, it is desirable to build a system that can measure joint angles in daily living while ensuring user comfort. For this reason, this paper uses deep learning to estimate joint angle during gait using only two IMU sensors mounted on participants' shoes under four different walking conditions, i.e., treadmill, overground, stair, and slope. Specifically, we leverage Gated Recurrent Unit (GRU), 1D, and 2D convolutional layers to create sub-networks and take their average to get a final model in an end-to-end manner. Extensive evaluations are done on the proposed method, which outperforms the baseline and improves the Root Mean Square Error (RMSE) of joint angle prediction by up to 32.96%. © 2022 SPIE.

关键词： Wearable sensors

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A Cloud-Based Software Architecture for a Course Recommender System

A Cloud-Based Software Architecture for a Course Recommender...

引用

international conference on Software, Telecommunications and computer Networks (SoftCOM)

作者： Anna Draganova Milen Petrov Adelina Aleksieva-Petrova Department of Software Technologies Sofia University “St. Kl. Ohridski” Sofia Bulgaria Department of Computer Systems Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9789532901382

ISBN: (纸本)9798350354614

Main contribution of the paper is to design cloud architecture and validate that architecture via real example in university recommendation system. Paper investigates state of the art, goes briefly trough analysis and design process, continues with development and validation of the architecture and the results from the experiments. The architecture was developed with the idea of meeting the need for a high-performance and scalable recommender system, which eliminates the need to purchase and maintain expensive servers with large computing power. Additionally, a dataset for training the course recommendation model, sourced from the extensive data available on the Coursera platform, was created.

关键词： Training Cloud computing Computational modeling Volume measurement computer architecture Logic gates Security Time factors Recommender systems Business

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Analysis and Design of In-Situ Q-Factor measurement Circuit With Power Reduction

Analysis and Design of In-Situ Q-Factor Measurement Circuit ...

引用

IEEE international conference on Electronics, Circuits and systems (ICECS)

作者： Ming Zhang Nicolas Llaser C2N-CNRS University of Paris-Saclay Palaiseau France Computer Science College LPO Dorian Paris France

ISBN: (数字)9798350377200

ISBN: (纸本)9798350377217

A time-domain Q-factor measurement approach offers the potential of an on-chip Q-factor measurement. To make a step forward towards the final goal, further power reduction of such an implementation system is mandate. This paper delves into a detailed analysis of power consumption of existing circuits, offers an average power consumption model deduced from the analysis made and proposes an improved circuit, which allows greatly further power reduction. The improved circuit was designed in a CMOS $0.35\mu \mathrm{m}$ technology. The simulation results have shown nearly 40% power reduction compared with the previous circuit while still maintaining a wide range of operation frequences from 0.1 to 1.5 MHz and a high Q-factor measurement accuracy of 0.2%.

关键词： Q-factor Analytical models Power measurement Power demand Simulation Circuits Time measurement Frequency measurement Integrated circuit modeling Time-domain analysis

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Genetic Algorithm and Latent Semantic Analysis based Documents Summarization Technique 14

Genetic Algorithm and Latent Semantic Analysis based Documen...

引用

14th international conference on Knowledge Engineering and Ontology Development, KEOD 2022 as part of 14th international joint conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2022

作者： Tanfouri, Imen Jarray, Fethi LIMTIC Laboratory UTM University Tunisia Higher Institute of Computer Science of Medenine Tunisia

ISBN: (纸本)9789897586149

Automatic text summarization (ATS) is the process of generating or extracting a shorter text of the original document while preserving relevant and important information. Nowadays, it is a hot research topic in natural language processing with various applications, including social networks and the healthcare domain. The task of summarizing can be divided into two categories, extractive and abstractive. In this paper, we are concerned with extractive summarization for a single Arabic document. In this contribution, we propose a combination of semantic and combinatorial methods to summarize a document by clustering its content through topic modeling techniques and subsequently generating an extractive summary for each of the identified topics using genetic algorithms. This approach ensures that the final summary covers all important topics in the document. We achieve state-of-the-art performance on the common Arabic summarization benchmark datasets. The obtained results show the effectiveness of combining genetic algorithms (GA) and latent semantic analysis (LSA) for document summarization. Copyright © 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Genetic algorithms

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A Vision-Based Behavioral measurement Using Facial Expression for Detecting Student Concentration in Classrooms

A Vision-Based Behavioral Measurement Using Facial Expressio...

引用

Smart systems for applications in Electrical Sciences (ICSSES), international conference on

作者： R Raghav Reddy Preethi S. H. Darius Koppala Rakshith Department of CSE CMR Institute of Technology Bengaluru India

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

Effective teaching requires the facilitator to gauge the students' concentration levels during a lecture and accordingly elaborate on a particular topic or repeat a concept that students did not understand. The current methodology for in-classroom monitoring of concentration levels is by asking the students whether they have understood, or conducting a postassessment quiz. We propose a minimally intrusive computer vision-based approach to obtain facial expressions for behavioral measurements. Deep Learning models are used to detect emotions. A pairwise comparison and rank reciprocal is used for assigning weights for various emotions corresponding to behavioral engagement in the class. A sampling method is proposed to reduce computation time and calculate the aggregate concentration index over a time horizon. The results show that the facial expression of students during a lecture is a reasonably accurate metric in detecting the concentration levels of a class and may be implemented to provide real-time feedback.

关键词： Deep learning measurement Image resolution Head Computational modeling Smart systems Sampling methods Real-time systems Indexes Monitoring

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On Some General Methods for Mathematical modeling of the Dynamics of Manipulators with Parallel Kinematics

On Some General Methods for Mathematical Modeling of the Dyn...

引用

2022 international conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2022

作者： Krasinskiy, Aleksandr Ya Dept. of Physical and Mathem. Disciplines Moscow Russia Moscow Aviation Institute National Research University Dept. of Computer Modeling and Probability Theory Moscow Russia

ISBN: (纸本)9781665483698

The level of development of technology for obtaining and processing measurement information, power electronics and actuators allows the use of the results of mathematical control theory with incomplete information in modern mechatronic systems. These results create the possibility of minimizing interference in the behavior of the object by minimizing the amount of measurement information and the number of actuators involved. A necessary condition for the realization of this possibility is the presence of an adequate nonlinear mathematical model of the control object. The development of methods for creating such models is hampered not so much by the technical complexity of the system under study, but by the fact that fundamentally new problems often arise in the study of a specific actually functioning device, which have never been encountered before in the relevant theory. Their solution requires research by theoretical specialists on the further development of the complex application of areas of analytical mechanics, nonlinear theory of stability, mathematical control theory with incomplete information, information technologies, etc., which were previously quite distant from each other. Rigorous justification of methods for obtaining such mathematical models, is based on complex sections of mathematics, mechanics and control theory, which have never been included in the curricula of standard engineering education. However, in our opinion, a significant expansion of the practical application of the latest results in engineering practice is possible due to such a presentation of algorithms for their qualified application, which does not require a complete understanding of all the abstract-theoretical foundations of their justification. © 2022 IEEE.

关键词： Control theory

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Decoupled Non-Local Attention for Single Image Super-Resolution

Decoupled Non-Local Attention for Single Image Super-Resolut...

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international joint conference on Neural Networks (IJCNN)

作者： Yi-Gang Zhao Jian-Nan Su Guang-Yong Chen Yu-Bin Liu College of Computer and Data Science Fuzhou University Fuzhou China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Self-similarity-based deep Single Image Super-Resolution (SISR) methods have gained popularity in recent years, especially with the integration of Non-Local Attention (NLA) in deep SISR. However, NLA suffers from the drawback of mixing relevant and irrelevant features, as it computes the response of each query by aggregating information from all non-local features. In this work, we propose a novel approach to exploit self-similarity more effectively using FlyHash, which is inspired by the fruit fly olfactory circuit and has exhibited outstanding performance in approximate similarity search. By limiting the association area of non-local features with FlyHash, we develop the Decoupled Non-Local Attention (DNLA) method, which tackles the difficulties of modeling a large amount of irrelevant non-local features while considerably lowering the computational complexity from quadratic to nearly linear. We verify the effectiveness of our DNLA approach with comprehensive ablation studies to show its capability of capturing nonlocal information for deep SISR. Furthermore, we build a deep Decoupled Non-Local Attention Network (DNLAN) with DNLA, which attains excellent results in both objective evaluation and subjective perception for SISR.

关键词： measurement Limiting Computational modeling Superresolution Olfactory Neural networks computer architecture

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Mitigation of Covert Communications in MQTT Topics Through Small Language Models

Mitigation of Covert Communications in MQTT Topics Through S...

引用

international Symposium on modeling, Analysis and Simulation of computer and Telecommunication systems (MASCOTS)

作者： Camilla Cespi Polisiani Marco Zuppelli Maria Carla Calzarossa Luca Caviglione Massimo Guarascio University of Pavia Pavia Italy CNR - IMATI Genoa Italy CNR - ICAR Rende Italy

ISBN: (数字)9798331531300

ISBN: (纸本)9798331531317

Modern IoT ecosystems face many security issues. An aspect often neglected concerns covert channels, which allow for exfiltrating data or preventing detection. To this aim, the Message Queuing Telemetry Transport (MQTT) protocol can be abused to create various hidden communication paths, mainly due to its textual nature. Alas, simpler detection metrics could be ineffective and their optimization requires a vast number of test cases. Therefore, this paper proposes to use a small language model trained over real MQTT topics to automatically generate the required test cases. Results indicate the need for optimizations to make popular detection metrics usable “in the wild”.

关键词： measurement Analytical models Protocols Computational modeling Prevention and mitigation Telecommunications Telemetry Security Optimization Faces

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Enhanced Machine Learning Algorithms for Classification in Agricultural Advisory systems and Agricultural Data Analysis

Enhanced Machine Learning Algorithms for Classification in A...

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Electronic systems and Intelligent Computing (ICESIC), international conference on

作者： Logesh M Domnic S J. Nelson Raja Electrical & Electronics Engineering (SG & EV) Sastra Deemed University Thanjavur Tamil Nadu India Department of Computer Application National Institute of Technonology Tiruchirappalli Tamil Nadu India Department of Computer Science Thiagarajar College Madurai Tamil Nadu India

ISBN: (数字)9798331522988

ISBN: (纸本)9798331522995

Agricultural technology, ensuring reliability, and optimizing processes are paramount. This work explores the application of machine learning algorithms (ML) to two critical areas: agricultural advisory systems (AAS) and agricultural data analysis (ADA). By leveraging historical data and advanced algorithms, this work aims to enhance predictive accuracy and operational efficiency in ADA and AAS. The proposed work focuses on various ML models for classification tasks, comparing their performance metrics, and discussing their applicability in agricultural sector. The findings highlight the ML model to significantly improve outcomes in agricultural management.

关键词： measurement Machine learning algorithms Data analysis Accuracy Computational modeling Prediction algorithms Classification algorithms Reliability

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A Power Split Strategy for a Vehicular Hybrid Energy Storage System Using Adaptive Neuro Fuzzy Inference System 8

A Power Split Strategy for a Vehicular Hybrid Energy Storage...

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8th IEEE international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Li, Jiao Zhang, Lijun Yang, Longzhi Wang, Bo School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Huazhong University of Science and Technology Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan430074 China Northumbria University Faculty of Engineering and Environment Department of Computer Science and Digital Technologies Newcastle upon TyneNE1 8ST United Kingdom

ISBN: (纸本)9798350300178

This paper presents a real-time power split strategy for a battery-supercapacitor hybrid energy storage system. The objective of the proposed strategy is to alleviate battery degradation through effective supercapacitor utilization. The proposed strategy employs an adaptive neural fuzzy inference system, which is capable of learning a power split strategy from offline optimization results and distributing power in real-time. The performance of the strategy proposed and a low pass filtering technique is compared through simulations. The results demonstrate that the proposed method can effectively reduce battery capacity loss and perform well under unknown driving cycles in real time. © 2023 IEEE.

关键词： Supercapacitor

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