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10th International Conference on Digital Arts, Media and Technology and 8th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2025

作者： Mekruksavanich, Sakorn Jitpattanakul, Anuchit University of Phayao School of Information and Communication Technology Department of Computer Engineering Phayao Thailand King Mongkut's University of Technology North Bangkok Intelligent and Nonlinear Dynamic Innovations Research Center Department of Mathematics Faculty of Applied Science Bangkok Thailand

ISBN: (纸本)9798331543273

Sensor-based human activity recognition (HAR) is a widely explored research area focused on identifying human behaviors by analyzing sensor-generated data, particularly one-dimensional time series signals. Such HAR systems have many real-world applications, including elderly health monitoring and athlete performance evaluation. This paper presents Ens-DeepNet, a novel ensemble learning approach designed for recognizing complex human activities using data from wearable sensors. While deep neural networks have proven effective for HAR tasks, their performance can be further improved through ensemble strategies. To this end, we propose an ensemble architecture that combines five distinct deep learning models - convolutional neural network (CNN), long short-term memory (LSTM), bidirectional LSTM (BiLSTM), gated recurrent unit (GRU), and bidirectional GRU (BiGRU). These models are integrated using a majority voting scheme to boost classification accuracy. The proposed method is evaluated using the UTwente dataset, which includes sensor data collected from ten individuals via tri-axial accelerometers and gyroscopes. Experimental findings demonstrate that the ensemble model achieves an impressive accuracy of 99.28%, surpassing the performance of each standalone model, whose accuracies range from 92.77%to 97.34%. This performance gain is particularly notable in recognizing complex activities such as eating, drinking coffee, smoking, and conversing. © 2025 IEEE.

关键词： Deep neural networks

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AI-Empowered Quality-of-Experience: Power Adaptation for Situation Aware Streaming of Live Surveillance Videos

AI-Empowered Quality-of-Experience: Power Adaptation for Sit...

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IEEE Conference on Wireless Communications and Networking

作者： Suvadip Batabyal Ozgur Ercetin Department of Computer Science & Engineering NIT Durgapur India Faculty of Engineering & Natural Sciences Sabanci University Istanbul Turkey

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

While artificial intelligence (AI) based algorithms have become an epitome of video quality analysis (VQA) for streaming services, the true power of AI is still to be harnessed for situation aware streaming in power constrained wireless networks. In this work, we propose an architecture for situation-aware streaming, that identifies important events from live-feeds of the surveillance cameras, and allocates optimal power that reduces the long-term power consumption. Real-time video surveillance is a crucial technology for smart cities, that requires deployment of large number of cameras; both road-side and aerial. The proposed architecture is designed to (i) reduce the total power consumption of all the surveillance cameras, thus reducing the greenhouse emissions, (ii) improve flight duration of aerial cameras (e.g. drones), (iii) reduce the manual searching of desired events/objects, and (iv) improve the overall QoE. It is imperative that only the important events (example, a car violating a red light) are of interest to a law enforcement officers. Hence, if the important sections of the video are received with high quality, the long-term QoE increases. The architecture has two modules, viz., a tiny neural network (having a small number of hidden layers) at the source, that incurs a small computational resource, albeit at the cost of low accuracy; and a deep neural network (DNN) (with many hidden layers) at the destination that is capable of determining events with high accuracy. We show that there exists an optimal number of frames that provides optimal QoE and is able to reduce the required power consumption of the transmitter compared to when situation awareness is not used.

关键词： Power demand Accuracy Wireless networks computer architecture Artificial neural networks Streaming media Cameras

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A New Handover Management Model for Two-Tier 5G Mobile Networks

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computers, Materials & Continua 2022年第6期71卷 5491-5509页

作者： Mohammad Arifin Rahman Khan Mohammed Golam Kaosar Mohammad Shorfuzzaman Kire Jakimoski Department of Computer Science and Engineering Bangladesh UniversityDhaka1207Bangladesh Discipline of IT Media and CommunicationsMurdoch UniversityPerthWA6150Australia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Faculty of Informatics AUE-FON UniversitySkopjeRepublic of North Macedonia

There has been an exponential rise in mobile data traffic in recent times due to the increasing popularity of portable devices like tablets,smartphones,and *** rapid rise in the use of these portable devices has put extreme stress on the network service providers while forcing telecommunication engineers to look for innovative solutions to meet the increased *** solution to the problem is the emergence of fifth-generation(5G)wireless communication,which can address the challenges by offering very broad wireless area capacity and potential cut-power *** application of small cells is the fundamental mechanism for the *** use of small cells can enhance the facility for higher capacity and ***,it must be noted that small cells deployment will lead to frequent handovers of mobile *** the importance of small cells in 5G,this paper aims to examine a new resource management scheme that can work to minimize the rate of handovers formobile phones through careful resources allocation in a two-tier ***,the resource management problem has been formulated as an optimization issue thatwe aim to overcome through an optimal *** find a solution to the existing problem of frequent handovers,a heuristic approach has been *** solution is then evaluated and validated through simulation and testing,during which the performance was noted to improve by 12%in the context of handover ***,this model has been observed to be more efficient as compared to the existing model.

关键词： Two-tier mobile networks small cell densification management of mobility handover cost average throughput power consumption

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Electrochemical Carbon Dioxide Reduction to Ethylene:From Mechanistic Understanding to Catalyst Surface engineering

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Nano-Micro Letters 2023年第10期15卷 382-415页

作者： Junpeng Qu Xianjun Cao Li Gao Jiayi Li Lu Li Yuhan Xie Yufei Zhao Jinqiang Zhang Minghong Wu Hao Liu Joint International Laboratory on Environmental and Energy Frontier Materials School of Environmental and Chemical EngineeringShanghai UniversityShanghai 200444People’s Republic of China Centre for Clean Energy Technology Faculty of ScienceUniversity of Technology SydneyBroadwaySydneyNSW 2007Australia Department of Electrical and Computer Engineering University of Toronto35 St George StreetTorontoON M5S 1A4Canada

Electrochemical carbon dioxide reduction reaction(CO_(2)RR)provides a promising way to convert CO_(2)to *** multicarbon(C_(2+))products,especially ethylene,are of great interest due to their versatile industrial ***,selectively reducing CO_(2)to ethylene is still challenging as the additional energy required for the C–C coupling step results in large overpotential and many competing ***,mechanistic understanding of the key steps and preferred reaction pathways/conditions,as well as rational design of novel catalysts for ethylene production have been regarded as promising approaches to achieving the highly efficient and selective CO_(2)*** this review,we first illustrate the key steps for CO_(2)RR to ethylene(e.g.,CO_(2)adsorption/activation,formation of~*CO intermediate,C–C coupling step),offering mechanistic understanding of CO_(2)RR conversion to *** the alternative reaction pathways and conditions for the formation of ethylene and competitive products(C_1 and other C_(2+)products)are investigated,guiding the further design and development of preferred conditions for ethylene *** strategies of Cu-based catalysts for CO_(2)RR-ethylene are further summarized,and the correlations of reaction mechanism/pathways,engineering strategies and selectivity are ***,major challenges and perspectives in the research area of CO_(2)RR are proposed for future development and practical applications.

关键词： Key steps in CO_(2)RR-ethylene Preferable reaction pathways Mechanism understanding Surface engineering strategies of Cu-based catalysts

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Flexible Localization Method with Motion Estimation for Underwater Wireless Sensor Networks 26

Flexible Localization Method with Motion Estimation for Unde...

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26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Ismail, A.S. Hawbani, Ammar Wang, Xingfu Aziz, Samah Abdel Zhao, Liang Saeed, Nasir School of Computer Science and Technology University of Science and Technology of China Anhui Hefei230027 China Zagazig University Faculty of Science Zagazig44519 Egypt School of Computer Science Shenyang Aerospace University Shenyang110136 China United Arab Emirates University Department of Electrical and Communication Engineering Al Ain15551 United Arab Emirates

ISBN: (纸本)9791188428120

Due to the challenging conditions of underwater environments, such as node mobility and large-scale networks, achieving localization in large-scale mobile underwater sensor networks (UWSN) is a difficult task. This paper introduces a scheme known as the Flexible Localization Method with Mobility Estimation (FLMME) for UWSNs by utilizing the expected mobility patterns of underwater objects. FLMME performs localization hierarchically by splitting the process into anchor and ordinary node localization. Each node estimates its next mobility pattern based on previous location information, enabling estimates about its next location. Anchor nodes, holding known locations, manage the localization process to balance accuracy and error trade-offs. Extensive simulations demonstrate that FLMME reduces localization errors and hence increases localization accuracy. © 2024 Global IT Research Institute - GIRI.

关键词： Location

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Generating A New Shilling Attack for Recommendation systems

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computers, Materials & Continua 2022年第5期71卷 2827-2846页

作者： Pradeep Kumar Singh Pijush Kanti Dutta Pramanik Madhumita Sardar Anand Nayyar Mehedi Masud Prasenjit Choudhury Department of Computer Science&Engineering National Institute of TechnologyDurgapurIndia Graduate School Duy Tan UniversityDa NangVietnam Faculty of Information Technology Duy Tan UniversityDa NangVietnam Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

A collaborative filtering-based recommendation system has been an integral part of e-commerce and *** keep the recommendation systems reliable,authentic,and superior,the security of these systems is very *** the existing shilling attack detection methods in collaborative filtering are able to detect the standard attacks,in this paper,we prove that they fail to detect a new or unknown *** develop a new attack model,named Obscure attack,with unknown features and observed that it has been successful in biasing the overall top-N list of the target users as *** Obscure attack is able to push target items to the top-N list as well as remove the actual rated items from the *** proposed attack is more effective at a smaller number of k in top-k similar user as compared to other existing *** effectivity of the proposed attack model is tested on the MovieLens dataset,where various classifiers like SVM,J48,random forest,and naïve Bayes are utilized.

关键词： Shilling attack recommendation system collaborative filtering top-N recommendation biasing shuffling hit ratio

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Spatial-channel attention-based stochastic neighboring embedding pooling and long-short-Term memory for lung nodules classification 12

Spatial-channel attention-based stochastic neighboring embed...

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12th International Conference on computer and Knowledge engineering, ICCKE 2022

作者： Saihood, Ahmed Karshenas, Hossein Nilchi, Ahmad Reza Naghsh University of Isfahan Faculty of Computer Engineering Artificial Intelligence Department Isfahan Iran University of Thi-Qar Nasiriyah Faculty of Computer Science and Mathematics Thi-Qar Iraq

ISBN: (数字)9781665476133

ISBN: (纸本)9781665476133

Handling lesion size and location variance in lung nodules are one of the main shortcomings of traditional convolutional neural networks (CNNs). The pooling layer within CNNs reduces the resolution of the feature maps causing small local details loss that needs processing by the following layers. In this article, we proposed a new pooling-based stochastic neighboring embedding method (SNE-pooling) that is able to handle the long-range dependencies property of the lung nodules. Further, an attention-based SNE-pooling model is proposed that could perform spatial and channel attention. The experimental results conducted on LIDC and LUNGx datasets show that the attention-based SNE-pooling model significantly improves the performance for the state of the art. © 2022 IEEE.

关键词： Embeddings

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A Way to Mark Attentance using Face Recognition using PL

A Way to Mark Attentance using Face Recognition using PL

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Vivek V Mahesh TR Department of Computer Science and Engineering Faculty of Engineering and Technology Jain (Deemed-to-be University) Bangalore

The computer system that is used to take attendance online is going to be upgraded as part of this project. This attendance tracking system is able to hold the technology known as facial recognition, which is a useful feature. This device helps students take attendance by utilizing both a biometric technology and artificial intelligence algorithms in one convenient package. When pupils enter the classroom, the face recognition software can identify them, making it useful for educational institutions of any kind. The existing system has a number of flaws that make it difficult to accurately record the attendance of both students and teachers. The approach makes it simpler to mark attendance and lowers the number of mistakes that might occur when doing *** students and teachers will gain a significant amount by utilizing these techniques. The ability to recognize people based on their faces is becoming increasingly significant in practically every industry. Face recognition techniques will be used to understand the faces. An attendance record is compared to the record that corresponds to it that was previously saved in the database. A student's photograph is used as a check point for this comparison.

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Advanced Traffic Framework for Managing Congestion 9

Advanced Traffic Framework for Managing Congestion

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9th International Conference on Computing for Sustainable Global Development, INDIACom 2022

作者： Alharbi, Awad Saleh Sen, Adnan Ahmed Abi Yamin, Mohammad Alhudhaif, Abdullah Alaboudi, Abdulellah A. School of Mathematics Computer Science and Engineering Department of Electrical Engineering London United Kingdom Islamic University Faculty of Computer and Information Systems Al-Madinah Saudi Arabia College of Engineering and Computer Science Australian National University Canberra Australia King Abdulaziz University Faculty of Economics and Administration Jeddah Saudi Arabia Shaqra University Department of Computer Sciences Shaqra Saudi Arabia

ISBN: (纸本)9789380544441

The most important challenge for any traffic system is to address traffic congestion and reduce it as much as possible. This process is complicated even for smart systems, as it requires the integration between many solutions, technologies, and services because a single solution cannot effectively address this issue. In this paper, we present a framework to support cooperation of many solutions, technologies, tools, and services in the traffic domain. To achieve this, the different service providers must be enabled to contribute to providing solutions, support services, and cooperate to obtain better quality, performance, availability, and greater flexibility in the available options. Therefore, we have added a new module that is responsible for supporting interoperability between devices and different heterogeneous services. We also added a special privacy protection component which is also a challenge that limits the ability to collaborate and share data between different apps and services. Finally, we discuss the benefits of the advanced traffic framework, with a case study that proves its importance. © 2022 Bharati Vidyapeeth, New Delhi.

关键词： Interoperability

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Hybrid optimization for integration of renewable energy systems into smart grids

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Measurement: Sensors 2024年 33卷

作者： Verma, Vikas Sorathiya, Vishal Sonowal, Gunikhan Reddy, M. Sudhakara Department of Computer Science & Engineering Vivekananda Global University Rajasthan Jaipur India Department of Electronics and Communication Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Gujarat Vadodara India Department of Computer Science and Engineering Assam down town University Assam Guwahati India Bangalore560027 India

The significant increase in the human population, energy consumption in daily living is increasing. One approach is to raise the amount of power produced to match the growth in human population, although this is typically practically unfeasible. By controlling demand, electricity consumption and associated expenses may be reduced. As a consequence, we employ Demand-side Management (DSM) to plan different gadgets on loads to reduce energy usage. Incorporating renewable energy sources and reducing energy costs are two significant roles that the smart grid plays. As a result, we suggest a hybrid swarm based Harris Hawks' optimization (S–HHO) algorithm to overcome the optimization difficulties. The suggested approach includes loads of home and business variety. The proposed technique was compared to binary particle swarm optimization (BPSO), multi-objective particle swarm optimization (MOPSO), wind driven optimization (WDO), and multi-objective genetic algorithms (MOGA). Results from simulations were produced using MATLAB software. The results show that the improved hybrid optimization S–HHO reduces the Peak-to-average ratio (PAR) and computational time better than other methods such as WDO, BPSO, MOPSO, and MOGA. © 2024 The Authors

关键词： Particle swarm optimization (PSO)

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