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11th International Symposium on Computing and Networking Workshops, CANDARW 2023

作者： Takanashi, Yuya Kimura, Shigetomo University of Tsukuba Graduate School of Science and Technology Tsukuba Japan University of Tsukuba Faculty of Engineering Information and System Tsukuba Japan

ISBN: (纸本)9798350306941

DNS over HTTPS (DoH) enhances user privacy by encrypting DNS communications over HTTPS instead of plaintext. When all DNS messages are sent in plaintext, DNS queries can be examined and domain filtering applied if the queried domain name is identified as a phishing site or other such undesirable site. However, if DNS messages are encrypted over HTTPS, it can create many problems for network administrators. This paper proposes a method for detecting DoH communications from only non-encrypted information on a middlebox between user and resolvers by exploiting the fact that users always send a DNS query before they access a new domain. The middlebox can also identify the destination of the detected DoH traffic so that network administrators can recommend users to send DNS messages to a local DoH resolver with domain filtering instead of sending them to an open DoH resolver. In experiments to detect DoH communications during real communication from a web browser we achieved detection accuracy rates reaching 100% under certain parameters when the number of access IP addresses exceeded 350. To confirm the accuracy and generalizability of our experiments, the proposed method was also applied to captured HTTPS traffic data involving different web browsers and different DoH resolvers with an almost identical level of detection accuracy. © 2023 IEEE.

关键词： Web browsers

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Empowering Deaf Children with Sinhala Sign Language, Emotion Detection, and Sound Recognition 5

Empowering Deaf Children with Sinhala Sign Language, Emotion...

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5th International Conference on Advancements in Computing, ICAC 2023

作者： Fernando, W.H.K. Perera, P.L.D.N. Fernando, M.I.N. Gunasekara, P.T.E.W. Fernando, Harinda De Zoysa, Rivoni Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Science Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798350358131

This study describes a broad endeavor to use cutting-edge technologies to empower deaf primary school students in Sri Lanka. Three key elements make up the study: a sound recognition and classification system, an Android software for translating gestures in Sinhala Sign Language (SSL), and a mobile app for emotion recognition and text-tospeech in Sinhala. By promptly alerting caregivers to potential dangers, the sound recognition technology secures the security of deaf children at home, providing an invaluable layer of security. The Android software bridges the communication gap and improves family interactions by translating SSL gestures captured by the device's camera into textual representations. This promotes successful communication between deaf children and their parents. Convolutional Neural Networks (CNNs) are used in the mobile application to detect and understand emotions based on facial expressions. This enables non-verbal youngsters to communicate successfully through Sinhala textto-speech output with adaptive tone modulation. This research aims to build a caring and inclusive atmosphere, enabling increased independence and enhanced communication skills in deaf children by combining these advances. The suggested solutions could significantly improve the lives of deaf kids, providing them with opportunities for better learning, social interaction, and emotional health. © 2023 IEEE.

关键词： Emotion Recognition

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The Effect of Coherent Frequency Diverse Array on Watson-Watt Direction-Finding system 4

The Effect of Coherent Frequency Diverse Array on Watson-Wat...

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4th International Conference on Neural Networks, information and Communication engineering, NNICE 2024

作者： Liu, Qiang Xiong, Kunlai Guo, Fucheng Xu, Tao National University of Defense Technology State Key Lab. of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Hunan Changsha410073 China

ISBN: (纸本)9798350394375

Frequency diverse array(FDA) offer potential applications for enhancing the RF safety performance of FDA systems. This is due to the time-varying angle-distance coupling characteristics of the transmit beam map, which are caused by small frequency shifts between subarray elements. In this paper, we investigate the impact of coherent FDA signals on amplitude-based direction-finding systems, taking the Watson-Watt direction-finding system as an example. Firstly, we establish receiving model for direction finding of FDA signals. Secondly, we evaluate the error of the direction-finding system when using coherent FDA signals and analyze it with the Cramér-Rao lower bound(CRLB). Finally, we conduct a simulation analysis to validate the proposed theory. Both the theoretical analysis and simulation results demonstrate that coherent FDA signals can improve the radio frequency(RF) stealth performance. Specifically, the analysis and simulation results reveal that coherent FDA signals exhibit superior low-intercept performance for the Watson-Watt direction-finding system. These findings can be applied to all amplitude direction-finding systems. © 2024 IEEE.

关键词： Radio direction finding systems

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Polarization-Multiplexed Fibre Spectrometer Based on Radiant Tilted Fibre Grating

Polarization-Multiplexed Fibre Spectrometer Based on Radiant...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Dai, Yuze Song, Qingguo Zou, Meng Xiao, Xiangpeng Zhao, Weiliang Sun, Qizhen Yan, Zhijun National Engineering Laboratory for Next Generation Internet Access System The School of Optical and Electronic Information Huazhong University of Science and Technology Hubei Wuhan430074 China

We have proposed a polarization-multiplexed fibre spectrometer based on Au-coated Radiant Tilted Fibre Grating (RTFG) and Faraday Rotator Mirror (FRM). The spectrometer can realize the simultaneous measurement of two ... 详细信息

ISBN: (纸本)9781957171395

关键词： Laser mirrors

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BAV-DSS: Blockchain Assisted Verifiable Data Sharing Scheme with Fast Encryption and Outsourced Decryption for IoT 24th

BAV-DSS: Blockchain Assisted Verifiable Data Sharing Scheme ...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Huang, Yao Yu, Zhongyuan Wang, Guijuan Chai, Baobao Zhang, Hongliang Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan250353 China School of Information Science and Engineering Lanzhou University Lanzhou730000 China School of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9789819615414

Many sophisticated cloud platforms are available to provide services such as storage and computation for Internet of Things (IoT) applications. However, with the concerns about the semi-trusted nature of cloud platforms, data security and privacy have been gaining broad attention. In this paper, we propose a blockchain-assisted verifiable data sharing scheme (BAV-DSS) for IoT. The BAV-DSS features fine-grained access control, fast encryption, and outsourced decryption with verifiability. Specifically, with the application of ciphertext-policy attribute-based encryption (CP-ABE), flexible access control is enabled. Blockchain is employed to store public keys, generate account addresses, and perform data verification. Furthermore, the selective replayable chosen ciphertext attacks (sRCCA) security of BAV-DSS is proved, and the simulation results indicate that BAV-DSS obtains high efficiency and practicality compared to other schemes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud platforms

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Adaptive SOM neural network algorithm 3

Adaptive SOM neural network algorithm

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3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Wang, Xin Yan, Taishan School of Information Science and Engineering Hunan Institute of Science and Technology Hunan Yueyang China Hunan Institute of Science and Technology School of Information Science and Engineering China Key Laboratory of Hunan Province on Intelligent Control and Optimization of Complex Industrial Logistics System Hunan Yueyang China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

In order to improve the performance of traditional SOM model, an adaptive SOM neural network algorithm is proposed. By introducing the error square sum solution formula, the clustering error of the model sub-data set is calculated by using the method of cutting the data set, and the change trend of the clustering error is quickly obtained. Then the learning rate of the SOM network is adaptively adjusted according to this, and the convergence speed is accelerated on the basis of ensuring that the network is fully trained, thereby improving the performance of the SOM network. © 2023 SPIE.

关键词： Errors

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engineering Program 'Freshmen Motivation Week' 53

Engineering Program 'Freshmen Motivation Week'

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Brito, Claudio R Ciampi, Melany M Copec Science and Education Research Organization Santos Brazil World Organization on System Engineering and Information Technology Wcseit Braga Portugal

ISBN: (纸本)9798350336429

- COPEC's educational research team designed the engineering Program Freshmen Motivation Week for 2023. It was specially designed to provide first-year engineering students with time to receive guidance and be motivated to keep going even when things are not going well. just as good in years to come. The proposal is to show future engineers the good and bad sides of any undertaking in life and that giving up is not an option. They have special classes the week before the beginning of the semester with special subjects related to 'thinking outside the box', with practical exercises and guest speakers. The central core is the vision of the whole of being an engineer with a focus on the aspect of contributions to human well-being. This is a proposal for an engineering course at a private university, whose objective is student retention over the years. A first experiment was carried out and another week is planned for the next semester to reinforce and collect data on the effects of the 'Out of the Box' week, as it was designated. They are 100% in-class, and face-to-face due to the nature of the activities carried out throughout the week. © 2023 IEEE.

关键词： Creative Flow Motivation Perseverance Retention Special Classes

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EdgeMove: Pipelining Device-Edge Model Training for Mobile Intelligence 23

EdgeMove: Pipelining Device-Edge Model Training for Mobile I...

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2023 World Wide Web Conference, WWW 2023

作者： Dong, Zeqian He, Qiang Chen, Feifei Jin, Hai Gu, Tao Yang, Yun School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computing Technologies Swinburne University of Technology Australia School of Information Technology Deakin University Australia School of Computing Macquarie University Australia National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450394161

Training machine learning (ML) models on mobile and Web-of-Things (WoT) has been widely acknowledged and employed as a promising solution to privacy-preserving ML. However, these end-devices often suffer from constrained resources and fail to accommodate increasingly large ML models that crave great computation power. Offloading ML models partially to the cloud for training strikes a trade-off between privacy preservation and resource requirements. However, device-cloud training creates communication overheads that delay model training tremendously. This paper presents EdgeMove, the first device-edge training scheme that enables fast pipelined model training across edge devices and edge servers. It employs probing-based mechanisms to tackle the new challenges raised by device-edge training. Before training begins, it probes nearby edge servers' training performance and bootstraps model training by constructing a training pipeline with an approximate model partitioning. During the training process, EdgeMove accommodates user mobility and system dynamics by probing nearby edge servers' training performance adaptively and adapting the training pipeline proactively. Extensive experiments are conducted with two popular DNN models trained on four datasets for three ML tasks. The results demonstrate that EdgeMove achieves a 1.3 × -2.1 × speedup over the state-of-the-art scheme. © 2023 ACM.

关键词： Internet of things

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A Hybrid WSVM-Levy Approach for Energy-Efficient Manufacturing Using Big Data and IoT

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Computers, Materials & Continua 2024年第12期81卷 4895-4914页

作者： Surbhi Bhatia Khan Mohammad Alojail Mahesh Thyluru Ramakrishna Hemant Sharma School of Science Engineering and EnvironmentUniversity of SalfordManchesterM68HDUK University Centre for Research and Development Chandigarh UniversityMohali140307India Management Information System Department College of Business AdministrationKing Saud UniversityRiyadh11495Saudi Arabia Department of Computer Science and Engineering JAIN(Deemed-to-be University)Bangalore560030India Department of Computer Science and Engineering IES College of TechnologyBhopal462044India

In Intelligent Manufacturing,Big Data and industrial information enable enterprises to closely monitor and respond to precise changes in both internal processes and external environmental factors,ensuring more informed decision-making and adaptive system *** also promotes decision making and provides scientific analysis to enhance the efficiency of the operation,cost reduction,maximizing the process of production and so *** methods are employed to enhance productivity,yet achieving sustainable manufacturing remains a complex challenge that requires careful *** study aims to develop a methodology for effective manufacturing sustainability by proposing a novel Hybrid Weighted Support Vector-based Lévy flight(HWS-LF)*** objective of the HWS-LF method is to improve the environmental,economic,and social aspects of manufacturing *** this approach,Support Vector Machines(SVM)are used to classify data points by identifying the optimal hyperplane to separate different classes,thereby supporting predictive maintenance and quality control in *** Forest is applied to boost efficiency,resource allocation,and production optimization.A Weighted Average Ensemble technique is employed to combine predictions from multiple models,assigning different weights to ensure an accurate system for evaluating manufacturing ***,Lévy flight Optimization is incorporated to enhance the performance of the HWS-LF method *** method’s effectiveness is assessed using various evaluation metrics,including accuracy,precision,recall,F1-score,and *** show that the proposed HWS-LF method outperforms other state-of-the-art techniques,demonstrating superior productivity and system performance.

关键词： Sustainable manufacturing support vector machine random forest levy flight optimization weighted average ensemble

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Stock Monitoring and Localization systems for FIFO Method Using RFID Based Pressure Sensing Tag and AI

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and systems 2024年第9期144卷 894-900页

作者： Hadi, Danang Kumara Song, Zequn Rahmadya, Budi Sun, Ran Takeda, Shigeki Graduate School of Science and Engineering Ibaraki University 4-12-1 Nakanarusawa Ibaraki Hitachi316-8511 Japan Department of Agroindustrial Technology Universitas Muhammadiyah Jember Jember68124 Indonesia Computer System Department Faculty of Information Technology Andalas University Padang25175 Indonesia

This research introduces real-time monitoring and localizing product stock using the First-In-First-Out (FIFO) method with radio frequency identification (RFID) pressure sensing tags. The proposed FIFO system has RFID pressure sensing tags that detect pressure changes, generate sensor codes, and estimate a stock location. Integrating artificial intelligence (AI) improves location estimation accuracy of up-to-date stock visibility. The ability of RFID pressure sensing tags and AI to detect stock from sensor code data enables more effective asset management, optimizes stock management, reduces product waste, and contributes to better efficiency in product inventory management. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Inventory control

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