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A CNN-Based Approach Combining Temporal Shift Module and Attention for Motor Imagery Classification 7

A CNN-Based Approach Combining Temporal Shift Module and Att...

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7th international conference on Advanced Algorithms and Control engineering, ICAACE 2024

作者： Cai, Miao Zeng, Yu School Of Information Science And Engineering Yunnan University Kunming China

ISBN: (纸本)9798350361445

This paper addresses the challenge of extracting spatial features from EEG signals and integrating temporal features when reorganizing electrodes into 3D data. The proposed method utilizes Convolutional Neural Networks (CNN) with Temporal Shift Module (TSM) and attention mechanism to capture spatio-temporal features of motor imagery EEG signals. Traditional EEG classification methods struggle with temporal dynamics and noise interference, affecting accuracy. To overcome this, an end-to-end classification network is designed, incorporating TSM for interacting with EEG information at different time points and attention mechanism for emphasizing important information. The model is validated using the BCI Competition IV 2a dataset and compared against methods like FBCSP and EEGNet. Experimental results demonstrate the model's superior performance, achieving approximately 10% improvement over FBCSP and an average accuracy increase of 4% compared to EEGNet. Ablation experiments verify the effectiveness of the TSM module. This method provides a stable and effective solution for classifying motor imagery EEG signals, benefiting the development and optimization of brain-computer interface systems. © 2024 ieee.

关键词： Brain computer interface

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Structural-Parametric Synthesis of complex Technical systems Under Conditions of Uncertainty Based on Statistical Analysis of Experimental Data

Structural-Parametric Synthesis of Complex Technical Systems...

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2024 international Russian Automation conference, RusAutoCon 2024

作者： Grishko, Alexey Penza State University Department of Design and Production of Radio Equipment Penza Russia

A generalized formulation of the problem of structural and parametric synthesis of complex technical systems under conditions of uncertainty based on the results of experimental data is presented, complementing the methodology of system engineering in life cycle management. Approaches to solving the problem of restoring design and functional relationships and clarifying the design parameters and characteristics of unmanned systems obtained from the results of field tests are proposed. As an example, a prototype of a subsonic unmanned system with specified design requirements is considered. the methodological basis is the theory of structural-parametric synthesis and statistical analysis of complex systems, as well as methods of mathematical statistics and parametric optimization. the problem of structural-parametric synthesis is formed by supplementing it with operators for the disclosure of uncontrolled factors. In order to find an analytical solution, the decomposition of the problem was carried out and the need to solve a set of interrelated tasks to find the correspondence of design parameters and experimental data was shown. the quality of the restored dependencies was assessed by the criterion of regularity and non-bias. A software and methodological complex for the statistical synthesis of an unmanned system is presented. the solution of the task allows us to analyze the compliance of design parameters and characteristics of unmanned systems with experimental data, which allows us to restore the design and functional connections of the designed unmanned system. This will allow for more efficient use of financial, production and time resources in the design of unmanned systems. © 2024 ieee.

关键词： Large scale systems

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A Decision Support Framework for Sustainable Waste Disposal Technology Selection

A Decision Support Framework for Sustainable Waste Disposal ...

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2024 ASU international conference in Emerging Technologies for Sustainability and Intelligent systems, ICETSIS 2024

作者： Lakkireddy, Venkateswara Reddy Mohana, R. Madana Ganesh, B. Rama Reddy, Lakkireddy Udanth Gochhait, Saikat Chogle, Shrish Hyderabad India Chaitanya Bharathi Institute of Technology Department of Artificial Intelligence and Data Science Hyderabad India Sri Venkatesa Perumal College of Engineering and Technology Department of Computer Science and Engineering Tirupathi India Ap University Dept. of Electronics and Communication Engineering Vit Amaravathi India Symbiosis Institute of Digital and Telecom Management Symbiosis International Deemed University India

ISBN: (纸本)9798350372229

Waste Disposal Technology (WDT) selection is a primary issue in Municipal Solid Waste (MSW) that affects the development of the environmental and economic perspectives/aspects, particularly in developing countries. The selection of appropriate WDT is a complex Multi-Attribute Decision-Making (MADM) problem with both qualitative and quantitative elements. The existent MADM approaches with fuzzy sets (removal of uncertainty), different subjective weight methods (significance of attributes), and rank reversal phenomenon leads to improper selection of WDT due to the involvement of different opinions of decision-makers. To avoid this, a Decision Support Framework (DSF) was proposed for optimal WDT selection for the growth of economic and environmental development. The proposed DSF integrates Preference Selection Index (PSI) and a Modified-Comprehensive distance Based Ranking (M-COBRA) approaches to determine the significance of attributes and ranking the alternatives, respectively. The DSF is illustrated using a case study collected from Iran and compared with state-of-the-art MADM approaches. Further, the DSF is validated in terms of sensitivity analysis, rank reversal phenomenon, and Pearson's rank correlation coefficient to ensure the stability of ranking. © 2024 ieee.

关键词： multi-attribute decision-making Municipal solid waste preference selection index rank reversal phenomenon sensitivity analysis waste disposal technology

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A3RT: Attention-Aware AR Teleconferencing with Life-Size 2.5D Video Avatars 31

A3RT: Attention-Aware AR Teleconferencing with Life-Size 2.5...

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ieee conference on Virtual Reality and 3D User Interfaces (VR)

作者： Wang, Xuanyu Zhang, Weizhan Fu, Hongbo Xi An Jiao Tong Univ Sch Comp Sci & Technol Xian Peoples R China City Univ Hong Kong Sch Creat Media Hong Kong Peoples R China

ISBN: (纸本)9798350374025;9798350374032

Augmented Reality (AR) teleconferencing aims to enable remotely separated users to meet with each other in their own physical spaces as if they are face-to-face. Among all solutions, the video-avatar-based approach has the advantage of balancing fidelity and the sense of co-presence using easy-to-setup devices, including only a camera and an AR Head-Mounted Display (HMD). However, non-verbal cues indicating "who is looking at whom" are always lost or misdelivered in multiparty teleconferencing experiences. To make users aware of such non-verbal cues, existing solutions explore screen-based visualizations, incorporate additional hardware, or alter to use a virtual avatar representation. However, they lack immersion, are less feasible for everyday usage due to complex installations, or lose the fidelity of remote users' authentic appearances. In this paper, we decompose such attention awareness into the awareness of being looked at and the awareness of attention between other users and address them in a decoupled process. Specifically, through a user study, we first find an unobtrusive and reasonable layout "Attention Circle" to retarget a looker's head gaze to the one being looked at. We then conduct the second user study to find an effective and intuitive "rotatable 2.5D video avatar with attention thumbnail" visualization to aid users in being aware of other users' attention. With the design choice distilled from the studies, we implement A3RT, a proof-of-concept prototype system that empowers attention-aware 2.5D-video-avatar-based multiparty AR teleconferencing in an easy, everyday setup. Ablation and usability studies on the prototype verify the effectiveness of our proposed components and the full system.

关键词： Computing methodologies-computer graphics-Graphics systems and interfaces-Mixed / augmented reality Human-centered computing-Human computer interaction (HCI)

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Exploring Driver Diversity in Post-Takeover Stabilization Based on Demographic Data 4

Exploring Driver Diversity in Post-Takeover Stabilization Ba...

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4th international conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2024

作者： Gruden, Timotej Jakus, Grega University of Ljubljana Faculty of Electrical Engineering Ljubljana Slovenia

ISBN: (纸本)9798350391183

Introduction: Conditionally automated vehicles promise significant advances in road safety, efficiency, and comfort. Objective: This study investigates the effects of driver demographic characteristics on stabilization times after taking over from fully automated driving. Methods: Using data sets from two driving simulator studies, we analyzed 704 takeover attempts by 58 drivers with diverse backgrounds. The study used linear mixed models to assess the influence of age, gender, driving experience, and previous simulator experience on stabilization times for speed, deceleration, heart rate, pupil diameter and off-road gaze duration ratio. Results: The analysis showed that age had a significant effect on driver speed, while gender, driving experience and simulator experience affected deceleration. Discussion: These results suggest that current models of post-Takeover stabilization do not apply uniformly to all demographic groups and should better account for demographic differences. This highlights the need for personalized approaches in automated vehicle systems to improve safety and user experience. © 2024 ieee.

关键词： Automobile driver simulators

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Deep Learning Techniques for Enhancing Near-Field Spatially Varying Channels In Wireless Communications

Deep Learning Techniques for Enhancing Near-Field Spatially ...

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2024 international conference on Communication, computer Sciences and engineering, IC3SE 2024

作者： Srividhya, Ch. Sapthami, I. Nagpal, Amandeep Pachauri, Praveen Chandrashekar, Rakesh Jabbar, Ahmed Sabah Abed AL-Zahra Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India Mlr Institute Of Technology Department Of Computer Science And Engineering Telangana Hyderabad India Lovely Professional University Phagwara India Government Polytechnic Siwan India New Horizon College Of Engineering Bangalore India College Of Medical Technology The Islamic University Medical Laboratory Technology Department Najaf Iraq

ISBN: (纸本)9798350366846

In the ever-growing field of radio communications, better ways of modeling and boosting channels are needed, especially for channels that change location in the near field. Here, we present a new way to use deep learning to improve the performance of radio communication channels. Our plan, called the 'Proposed Method,' uses complex neural network structures to model and improve channel features. We tested the proposed method against six well-known ones, including Orthogonal Matching Pursuit, Maximum Likelihood Estimation, Least Squares, Compressive Sensing, Singular Value Decomposition, and Beamforming, to see how well it works. To rate how well something works, we use things like Mean Absolute Error (MAE), Signal-to-Noise Ratio (SNR), Bit Error Rate (BER), Computational complexity, and Root Mean Squared Error (RMSE). The results show that the Proposed Method is better because it models and estimates channels more accurately and has lower RMSE, MAE, BER, and MSE. The Proposed Method also has a higher signal-to-noise ratio (SNR), which means the quality of the data is better. In addition, because it is simple to compute, it is a good answer for real-world problems. © 2024 ieee.

关键词： Beamforming

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A Study on Formal Verification of Smart Contracts in Distributed Ledger Technology 3

A Study on Formal Verification of Smart Contracts in Distrib...

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3rd ieee international conference on Recent Advances in systems Science and engineering, RASSE 2023

作者： Gokulnath, G. Kizhakkethottam, Jubilant J APJ Abdul Kalam Technological University Kerala India Department of Computer Science and Engineering India

ISBN: (纸本)9798350341676

This study paper explores the critical topic of formal verification of smart contracts in distributed ledger technology (DLT) systems. Smart contracts, self-executing code running on blockchain platforms, have gained widespread adoption in various industries due to their automation and transparency benefits. However, the decentralized and immutable nature of DLT raises concerns regarding smart contract security, leading to vulnerabilities and potential exploits. Formal verification methods offer a systematic approach to analyze smart contracts for correctness and safety. This paper provides an overview of smart contracts, DLT, and the importance of formal verification. It reviews various formal verification techniques and presents state-of-The-Art tools and frameworks. The paper concludes with discussions on challenges, future research opportunities, and the role of formal verification in enhancing DLT-based applications' security and usability. © 2023 ieee.

关键词： Smart contract

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Advancements in Object Detection for Accurate and Efficient Visual Recognition Using Machine Learning 2

Advancements in Object Detection for Accurate and Efficient ...

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2nd ieee international conference on Advances in Information Technology, ICAIT 2024

作者： Fernandez, F. Mary Harin Ramachandran, A. Ganesh Saravanan, S.K. Bhanumathi, M. Sangeetha, M. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Computer Science Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Computers Science and Engineering BigData and Network Security Saveetha School of Engineering SIMATS Tamil Nadu Chennai India Chennai India Computer Engineering Department University of Technology and Applied Sciences Nizwa Oman

ISBN: (纸本)9798350383867

Object detection in images and videos is a vital task in computer vision where its application goes beyond the automobile driving and surveillance, to healthcare. The paper introduces an object detection model which is specific and powerful, that is able to recognize visually with machine learning. The framework is constructed on the basis of the recent innovations in deep learning and attentive mechanisms, which not only lead to the best performance in object detection today but also guarantee the widest applicability. Using an extensive experiment which reveals the described model superiority over the current state-of-the-art algorithms by evaluating mAP indices, whereas the latter has a normal complexity. The ablation study uncovers the impact of core parameters including attention mechanisms and semi-supervised techniques, underlining their importance in the growth of detection precision. Moreover, the illustrative comparison of outcomes from detecting objects on the framework calls for attention to the capacity of the networks to objectify in different categories. Our outcome also suggest that although the proposed framework has a human-level performance in task of object detection there is still a scope to enhance their performance above the human level. Summarizing, this work concludes the conversation and can be considered in the progress of research developments of the object detection systems aimed at practical object meeting situations. © 2024 ieee.

关键词： computer Vision Deep Learning Machine Learning Object Detection Visual Recognition

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Smart Home Automation with IoT Sensor systems for Energy Conservation using Zigbee and Wifi 5

Smart Home Automation with IoT Sensor Systems for Energy Con...

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5th international conference on Electronics and Sustainable Communication systems, ICESC 2024

作者： Jagannathan, Srinivasan Deepa, V. Sakthi Karthi Durai, B. Rajan, M. Sundar Celin, J. Jeya A. Dhamodaran, Sasikala Madanapalle Institute of Technology & Science Department of Computer Applications Madanapalle India Tiruppur Kumaran College for Women Pg and Research Department of Computer Science Tamil Nadu Tiruppur India Kalasalingam Academy of Research and Education Computer Science and Engineering India Arbaminch Institute of Technology Arbaminch University Faculty of Electrical and Computer Engineering Ethiopia Kalasalingam Academy of Research and Education Department of Information Technology Viruthunagar Krishnankoil626126 India Rajasthan Jaipur India

ISBN: (纸本)9798350379945

This study presents a comprehensive study on smart home automation systems utilizing Internet of Things (IoT) sensor technology to achieve efficient energy conservation. The proposed system integrates ZigBee and WiFi communication protocols for effective and reliable connectivity across various smart devices within a home. Through the deployment of interconnected sensors and intelligent controllers, the system allows real-time monitoring and management of household energy usage, optimizing energy consumption and reducing waste. The combination of ZigBee for low-power, long-range sensor networks and WiFi for high-speed data transmission enables seamless interaction between smart appliances, lighting, heating, and cooling systems. Proposesd approach offers a scalable, cost-effective solution for enhancing home automation with an emphasis on energy conservation and sustainability. Also discussed the implementation, challenges, and future potential of IoT-based smart home systems for improved energy efficiency. © 2024 ieee.

关键词： Smart homes

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A Mathematical Model for the Selection of Software Requirements Elicitation Techniques 14

A Mathematical Model for the Selection of Software Requireme...

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14th international conference on Cloud Computing, Data Science and engineering, Confluence 2024

作者： Saxena, Virat Raj Yadav, Rajeev Parveen, Azra Sadiq, Mohd. Mangalayatan University Department of Computer Science and Engineering Uttar Pradesh Aligarh202001 India Indraprastha Institute of Information Sciences Private Limited Indraprastha Research Laboratory New Delhi110025 India Upfet Jamia Millia Islamia A Central University Software Engineering Laboratory Computer Engineering Section New Delhi110025 India

ISBN: (纸本)9798350344837

Various techniques have been developed for the identification of different types of requirements like interview, questionnaire, group elicitation techniques, attributed goal-oriented requirements analysis, fuzzy based goal-oriented requirements analysis method, non-functional requirements framework, etc. Based on the critical analysis of requirements elicitation methods, we found that single elicitation technique is not suitable to understand the need of the stakeholders. In real life applications, multiple elicitation techniques are required to elicit and select the requirements of an information system because each technique has its strength and limitations. Therefore, to address this issue, this paper presents a mathematical model for the selection of requirements elicitation techniques so that complete set of requirements along with its priority can be identified before the development of an information system. The institute examination system is considered to show the applicability of the proposed mathematical model. © 2024 ieee.

关键词： Information systems

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