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28th IEEE Pacific Rim International Symposium on Dependable Computing, PRDC 2023

作者： Mukta, Rahma Pal, Shantanu Mishra, Shailesh Paik, Hye-Young Kanhere, Salil S. Hitchens, Michael University of New South Wales School of Computer Science and Engineering Sydney Australia Deakin University School of Information Technology Melbourne Australia School of Computer and Communication Sciences Switzerland Macquarie University School of Computing Sydney Australia

ISBN: (纸本)9798350358766

With the improvement of Internet of Things (IoT) technologies, services, and applications, there is a proliferation of access to smart devices in everyday life. However, granting access and controlling access rights for each resource is challenging in highly dynamic and large-scale IoT deployments. In particular, multiple access information may need to be provided to an entity when granting access rights to several resources. The situation becomes more complex when an entity is required to share its identity attribute to receive the access information. These raise the question of what identity information an entity needs to provide to obtain the required access to a particular resource and, subsequently, what access information needs to be provided when accessing that resource. That said, there is a need for a flexible approach where an entity can share a distinct identity and access attributes for accessing a resource without revealing additional information. Such flexibility in sharing information is significant given the privacy risk of an entity's identity. This paper presents an architecture that delivers access rights to an entity with selective disclosure of information. Our approach ensures the minimum exchange of information (identity and access attribute) to enhance an entity's privacy when granting access rights to an entity. We use blockchain to provide data authenticity (i.e., tamper-proof), transparency and automatic execution of access rights based on shared attributes using smart contracts. We implement a proof of concept of the proposed system using Hyperledger fabric as a permissioned blockchain network. Our results demonstrate the feasibility of the proposed system showing efficiency in granting access rights. © 2023 IEEE.

关键词： Blockchain

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Intelligent Manufacturing Transformation Development Strategy of Jilin City Automobile Industry: A Research Based on SWOT-AHP Model 2nd

Intelligent Manufacturing Transformation Development Strateg...

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2nd International Conference on Intelligent systems Design and engineering Applications, ISDEA 2023

作者： Jia, Li Xu, Ding Shuang, Guo School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China School of Computer Science Northeast Electric Power University Jilin132012 China Science and Technology Institute of Jilin City Jilin132022 China

ISBN: (纸本)9789819963027

This paper proposes the development strategy for Intelligent manufacturing transformation, with the help of both SWOT analysis and AHP analysis, in the case of focusing on the Jilin city Automobile Industry. Firstly found the influence factors of Jilin city automobile industry’s intelligent manufacturing transformation, based on SWOT analysis. Secondly, the AHP quantitative analysis model is constructed, and the Delphi survey method is used for quantitative calculation that had been taken Consistency checking results. Then determine the strategic quadrilateral, to obtain the development strategy azimuth and strategic strength. The strategic positioning and trend of the intelligent transformation and development of the automobile industry in Jilin City are determined, and the implementation countermeasures of the development strategy are formulated. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry

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Applications of IoT and Various Attacks on IoT 8th

Applications of IoT and Various Attacks on IoT

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8th International Conference on Soft Computing: Theories and Applications, SoCTA 2023

作者： Dhillon, Sumeet Mishra, Nishchol Shakya, Devendra Kumar Computer Science and Engineering Department SATI Vidisha India School of Information Technology RGPV Bhopal Bhopal India Department of Electronics Engineering SATI Vidisha India

ISBN: (纸本)9789811998577

Internet of Things (IoT) is the unification of digital/technical world with the real world and its applications, enabling the ease of communication between people, devices, processes, and objects present in the surroundings. IoT is the newest technological modernization with the ability to boost efficiency, enhance environmental sustainability, and upgrade security covering numerous evolving domains as well as assist in smoothing the everyday task and activities. The IoT researches accomplished till date certify the enormous progress in the field of Internet of Things. IoT applications are progressively fabricating their existence in nearly every sector surrounding humans. Few of the omnipresent applications of IoT are smart homes and city, smart health care, hi-tech wearable’s, and smart agriculture which are further elaborated in the survey. This survey paper presents an exhaustive description of applications of IoT, with the possible vulnerabilities and attacks on numerous IoT applications. Thus, the study also includes the mitigation methods to prevents these attacks and attain trustworthy and reliable IoT applications. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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A Vehicle Classification Model Based on Multi-scale Feature Fusion 41

A Vehicle Classification Model Based on Multi-scale Feature ...

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第41届中国控制会议

作者： Xuanhong Wang Shiyu Yang Zengguo Sun Xiaojun Li Yun Xiao School of Telecommunication and Information Engineering Xi'an University of Posts and Telecommunications School of Computer Science Shaanxi Normal University China Academy of Space Technology (Xi'an) School of Information Science and Technology Northwest University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In the field of intelligent transportation,the classification of vehicle types plays a very important *** paper presents a model of SPP-RepVGG to overcome the problems of long training time and low classification accuracy of existing vehicle types classification ***,the RepVGG is employed in extracting effective feature data of the vehicle ***,the Spatial Pyramid Pooling(SPP) is connected between the convolution layer and the fully connected layer of the model,and the multi-scale features of the image are extracted through three different sizes of pooling windows,thus feature extraction and fusion of the vehicle image are ***,the classification results are obtained using the fully connected *** Stochastic Gradient Descent(SGD) method with Gradient Centralization(GC) is used to accelerate the network *** classification models are applied to the BIT-Vehicle data sets for comparative *** experimental results demonstrate that the training time of SPP-RepVGG model is shortened,and the accuracy on the test sets is 96.653%.Compared with the VGG-16,ResNet-18 and RepVGG-A0 models,the Top-1 accuracy of the proposed model is increased by 3.034%,2.197% and 1.988% respectively,this illustrates that our proposed model can extract vehicle image features more effectively,which can provide help for intelligent traffic management.

关键词： Vehicle Types Classification RepVGG Multi-scale Feature SPP GC

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A Unified Decision-Making Technique for Analysing Treatments in Pandemic Context

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computers, Materials & Continua 2022年第11期73卷 2591-2618页

作者： Fawaz Alsolami Abdullah Saad Al-Malaise Alghamdi Asif Irshad Khan Yoosef B.Abushark Abdulmohsen Almalawi Farrukh Saleem Alka Agrawal Rajeev Kumar Raees Ahmad Khan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow226028India

The COVID-19 pandemic has triggered a global humanitarian disaster that has never been seen *** experts,on the other hand,are undecided on the most valuable treatments of therapy because people ill with this infection exhibit a wide range of illness indications at different phases of ***,this project aims to undertake an experimental investigation to determine which treatments for COVID-19 disease is the most effective and *** research analysis is based on vast data gathered from professionals and research journals,making this study a comprehensive *** solve this challenging task,the researchers used the HF AHPTOPSIS Methodology,which is a well-known and highly effective MultiCriteria Decision Making(MCDM)*** technique assesses the many treatment options identified through various research papers and guidelines proposed by various countries,based on the recommendations of medical practitioners and *** review process begins with a ranking of different treatments based on their effectiveness using the HF-AHP approach and then evaluates the results in five different hospitals chosen by the authors as *** also perform robustness analysis to validate the conclusions of our *** a result,we obtained highly corroborative results that can be used as a *** results suggest that convalescent plasma has the greatest rank and priority in terms of effectiveness and demand,implying that convalescent plasma is the most effective treatment for SARS-CoV-2 in our *** also has the lowest priority in the estimation.

关键词： AHP-TOPSIS hesitant fuzzy sets SARS-CoV-2 healthcare sector preventive drugs

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Enhancing thyroid disease prediction and comorbidity management through advanced machine learning frameworks

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Clinical eHealth 2025年 8卷 7-16页

作者： Sanju, P. Ahmed, N. Syed Siraj Ramachandran, P. Sajid, P. Mohamed Jayanthi, R. Department of Computer Science and Engineering University College of Engineering Tindivanam Anna University India School of Computer Science Engineering and Information Science Presidency University Bangalore India Department of MCA Parul Institute of Engineering and Technology Parul University P.O.Limda Tal.waghodia Dist. Vadodra India Department of ECE C. Abdul Hakeem College of Engineering and Technology Melvisharam India Department of MCA Dayananda Sagar College of Engineering Kumaraswamy Layout Bangalore 560078 India

Thyroid disease is one of the most prevalent endocrine disorders worldwide, necessitating precise and efficient diagnostic models for improved clinical outcomes. This study proposes a Hybrid Feature Selection and Deep Learning Framework (HFSDLF) that integrates Random Forests with Principal Component Analysis (PCA) and L1 regularization for effective feature selection and classification. Utilizing the UCI Thyroid Dataset, the framework combines the strengths of deep learning-based feature extraction and traditional machine learning classifiers. The Random Forest classifier achieved the highest accuracy of 96.30 %, outperforming other models such as Decision Trees and Logistic Regression, with notable improvements in sensitivity and specificity. The novelty of this work lies in its hybrid approach to feature selection, which reduces dimensionality while retaining the most informative features, and its application of an optimized Random Forest model for enhanced classification accuracy. Comparative analysis with existing methods further highlights the superiority of the proposed framework in terms of accuracy and processing efficiency. This research addresses key limitations of existing approaches and contributes to the field by demonstrating a scalable and interpretable solution for thyroid disease diagnosis. The proposed framework provides a benchmark for future studies, underscoring the importance of hybrid methodologies in medical data analysis. © 2025

关键词： Endocrine disorder Machine learning Thyoid eye disease Thyroid disease

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Joint Waveform and Passive Beamforming Design for IRS-Aided ISAC via Deep Unfolding 16

Joint Waveform and Passive Beamforming Design for IRS-Aided ...

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16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Zhang, Jifa Liu, Mingqian Tang, Jie Zhao, Nan Niyato, Dusit Wang, Xianbin School of Information and Communication Engineering Dalian University of Technology Dalian China Xidian University State Key Laboratory of Integrated Service Networks Xi'an China School of Electronic and Information Engineering South China University of Technology Guangzhou China School of Computer Science and Engineering Nanyang Technological University Singapore Western University Department of Electrical and Computer Engineering LondonONN6A 5B9 Canada

ISBN: (纸本)9798350390643

Integrated sensing and communication (ISAC) has become a promising technique to alleviate the spectrum congestion via sharing the same spectrum for communication and sensing. Nevertheless, many ISAC schemes encounter the challenges of high complexity. In this paper, we propose a dual-functional waveform design scheme for reconfigurable intelligent surface (RIS) aided ISAC based on deep unfolding learning. Specifically, the weighted sum of multi-user interference energy and waveform discrepancy is minimized via the joint waveform and phase-shift design. We first develop an alternating direction method of multipliers (ADMM) based iterative algorithm to handle the non-convex optimization problem. Then, we develop a deep unfolding neural network (NN), named ADMM-NET, which unfolds the proposed ADMM-based iterative algorithm to a layer-wise architecture. Simulation results verify the effectiveness of the proposed ADMM-NET. © 2024 IEEE.

关键词： Convex optimization

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Enlightening the Student in Knowledge Distillation 48

Enlightening the Student in Knowledge Distillation

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Zheng, Yujie Wang, Chong Chen, Yi Qian, Jiangbo Wang, Jun Wu, Jiafei Ningbo University Faculty of Electrical Engineering and Computer Science China China University of Mining and Technology School of Information and Control Engineering China SenseTime Research China

ISBN: (纸本)9781728163277

Knowledge distillation is a common method of model compression, which uses large models (teacher networks) to guide the training of small models (student networks). However, the student may find a hard time absorbing the knowledge from a sophisticated teacher due to the capacity and confidence gaps between them. To address this issue, a new knowledge distillation and refinement (KDrefine) framework is proposed to enlighten the student by expending and refining its network structure. In addition, a confidence refinement strategy is utilized to generate adaptive soften logits for efficient distillation. The experiments show that the proposed framework outperforms state-of-the-art methods on both CIFAR-100 and Tiny-ImageNet datasets. The code is available at https://***/YujieZheng99/KDrefine. © 2023 IEEE.

关键词： knowledge distillation model compression structural re-parameterization

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Multi-stream Convolutional Neural Networks Fusion for Palmprint Recognition 16th

Multi-stream Convolutional Neural Networks Fusion for Palmpr...

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16th Chinese Conference on Biometric Recognition, CCBR 2022

作者： Zhou, Qing Jia, Wei Yu, Ye School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China

ISBN: (纸本)9783031202322

In recent years, researchers have carried out palmprint recognition study based on deep learning, and proposed a variety of methods based on deep learning. In these methods, convolution neural networks (CNN) were directly applied to the original ROI image of palmprint for training and recognition. In fact, after processing, palmprint can have other representations, such as directional representation, and magnitude representation, etc. However, researchers have not investigated the problem that applied CNNs to other representations of palmprint for recognition. In this paper, we propose a novel framework of multi-stream CNNs fusion for palmprint recognition. In this framework, palmprint are firstly processed into other different representations. Next, CNNs are applied to different palmprint representations for recognition, and then, the information fusion is conducted to effectively improve the recognition accuracy. Under this framework, we propose a concrete implementation, i.e., three-stream CNNs fusion for palmprint recognition. We evaluate the proposed method on five palmprint database. Experimental results show that the recognition accuracy of the proposed method is obviously better than some classical traditional methods and deep learning methods. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Palmprint recognition

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A Novel Thermo-Optic Phase Shifter Based on Anti-Symmetric Bragg Grating

A Novel Thermo-Optic Phase Shifter Based on Anti-Symmetric B...

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2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Liu, Shengping Li, Qiang Zhao, Yang Wang, Wei Yao, Guoguang Gao, Shang Feng, Junbo Zhan, Qipeng Tang, Yong Silicon Optoelectronics Center United Microelectronics Center Chongqing China School of Electronics and Information Engineering Anhui University Hefei China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350312614

Thermooptic phase shifter (TOPS) plays an important role in the silicon photonics integrated circuits. In this article, we proposed and experimentally demonstrated a novel TOPS based on the anti-symmetric Bragg grating (ASBG). By using the ASBG and anti-directional coupler, the overlap integral of light field and thermal field is increased by three times. The TOPS has been fabricated on CUMEC's standard CSiP180Al and CSiP130Cu silicon photonics platform. The experimental results show that the efficiency of the TOPS is about 6.75\textmW/\pi, which is only about a third of the conventional TOPS. At the same time, the rise time and drop time are only 7.1 \mus and 9.7 \mus. The proposed TOPS based on the ASBG paves the way for a high efficiency TOPS for the silicon photonics integrated circuits without sacrificing the switching time. © 2023 IEEE.

关键词： anti-symmetric Bragg grating silicon photonics thermos-optic phase shifter

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