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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Rao, Junhui Zhang, Yujie Murch, Ross Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Institute for Advanced Study Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong

ISBN: (纸本)9781665442282

The design of a reconfigurable intelligent surface (RIS) for mm-waves with arbitrary polarization is proposed. At mm-wave frequencies, the RF switches needed in the RIS suffer from low isolation, and therefore a parasitic enhancing structure (PES) is also proposed to improve switch performance. In the RIS element, a dual-port dual-polarized patch antenna is used for scattering. Both ports of the antenna are connected to independent phase-reconfigurable circuits based on diodes, with PES, and these can provide 180-degree phase shifts. Simulation results show that the RIS can operate effectively for two orthogonal polarized waves and therefore an arbitrarily polarized wave. © 2023 IEEE.

关键词： Microstrip antennas

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Provably Efficient Multi-Cancer Image Segmentation Based on Multi-Class Fuzzy Entropy

Informatica (Slovenia)

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Informatica (Slovenia) 2023年第8期47卷 77-88页

作者： Jasim, Hend Muslim Ghrabat, Mudhafar Jalil Jassim Abdulrahman, Luqman Qader Nyangaresi, Vincent Omollo Ma, Junchao Abduljabbar, Zaid Ameen Abduljaleel, Iman Qays Department of Computer Science College of Education for Pure Sciences University of Basrah Basrah61004 Iraq Iraqi Commission for Computers and Informatics The Informatics Institute for Postgraduate Studies Baghdad Iraq Computer Science Department Al-Turath University College Baghdad10013 Iraq College of Health Science Hawler Medical University Erbil Iraq Jaramogi Oginga Odinga University of Science and Technology Bondo40601 Kenya College of Big Data and Internet Shenzhen Technology University Shenzhen518118 China Technical Computer Engineering Department AL-Kunooze University College Basrah6100 Iraq Huazhong University of Science and Technology Shenzhen Institute Shenzhen518000 China Department of Computer Science College of Computer Science and Information Technology University of Basrah Basrah61004 Iraq

One of the segmentation techniques with the greatest degree of success used in numerous recent applications is multi-level thresholding. The selection of appropriate threshold values presents difficulties for traditional methods, however, and, as a result, techniques have been developed to address these difficulties multidimensionally. Such approaches have been shown to be an efficient way of identifying the areas affected in multi-cancer cases in order to define the treatment area. Multi-cancer methods that facilitate a certain degree of competence are thus required. This study tested storing MRI brain scans in a multidimensional image database, which is a significant departure from past studies, as a way to improve the efficacy, efficiency, and sensitivity of cancer detection. The evaluation findings offered success rates for cancer diagnoses of 99.08%, 99.87%, 94%;97.08%, 98.3%, and 93.38% sensitivity;the success rates of in particular were 99.99%;98.23%, 99.53%, and 99.98%. © 2023 Slovene Society Informatika. All rights reserved.

关键词： Image segmentation

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Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural Network 38

Regularized Adaptive Momentum Dual Averaging with an Efficie...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Huang, Zih-Syuan Lee, Ching-Pei Department of Computer Science and Information Engineering National Taiwan University Taipei106 Taiwan Department of Advanced Data Science Institute of Statistical Mathematics Tachikawa Tokyo190-8562 Japan

We propose a Regularized Adaptive Momentum Dual Averaging (RAMDA) algorithm for training structured neural networks. Similar to existing regularized adaptive methods, the subproblem for computing the update direction of RAMDA involves a nonsmooth regularizer and a diagonal preconditioner, and therefore does not possess a closed-form solution in general. We thus also carefully devise an implementable inexactness condition that retains convergence guarantees similar to the exact versions, and propose a companion efficient solver for the subproblems of both RAMDA and existing methods to make them practically feasible. We leverage the theory of manifold identification in variational analysis to show that, even in the presence of such inexactness, the iterates of RAMDA attain the ideal structure induced by the regularizer at the stationary point of asymptotic convergence. This structure is locally optimal near the point of convergence, so RAMDA is guaranteed to obtain the best structure possible among all methods converging to the same point, making it the first regularized adaptive method outputting models that possess outstanding predictive performance while being (locally) optimally structured. Extensive numerical experiments in large-scale modern computer vision, language modeling, and speech tasks show that the proposed RAMDA is efficient and consistently outperforms state of the art for training structured neural network. Implementation of our algorithm is available at https://***/ismoptgroup/RAMDA/. © 2024 Neural information processing systems foundation. All rights reserved.

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PQS-AKA: Post-Quantum Secure Lightweight Authenticated Lattice-Based Key Agreement for IoT Communications 4th

PQS-AKA: Post-Quantum Secure Lightweight Authenticated Latti...

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4th International Conference on Emerging Trends and Technologies on Intelligent Systems, ETTIS 2024

作者： Singh, Ajeet Tentu, Appala Naidu Rao, K. Gangadhara Department of Computer Science and Engineering Acharya Nagarjuna University Andhra Pradesh Guntur522 510 India C.R. Rao Advanced Institute of Mathematics Statistics and Computer Science University of Hyderabad Campus Telangana Hyderabad500 046 India

ISBN: (纸本)9789819757022

As the Internet of Things (IoT) ecosystem expands, the need for secure and private communication over public networks becomes increasingly crucial. A fundamental component of this security paradigm is the establishment of a secret session key among IoT devices, enabling the secure transmission of confidential data over the Internet. In this paper, we introduce a Post-Quantum Secure Lightweight Authenticated Lattice-based Key Agreement (PQS-AKA) protocol, specifically developed for the rapidly evolving IoT ecosystem. Traditional Authenticated Key Agreement (AKA) protocols, predominantly based on concepts like Diffie–Hellman or prime factorization, are becoming obsolete due to their vulnerability to quantum computing advancements and their inefficiency in the resource-constrained IoT environment. Current quantum-resistant methods, although leveraging lattice cryptography for security, are impeded by issues such as high certificate management overheads and substantial communication and computational costs. PQS-AKA not only offers a defense against the threats posed by quantum computing through the inherent hardness of lattice problems but also simplifies the process by removing the need for extensive certificate management. The core security strength of our protocol is thoroughly evaluated under the random-natured oracle model, demonstrating its robustness against both present and future quantum computing attacks. Performance evaluations reveal that the proposed protocol offers a significant improvement over existing solutions in terms of efficiency and practicality, making it a viable and secure choice for industrial IoT applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Quantum computers

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Efficient Feature Selection Techniques for Accurate Cancer Analysis Using Krill Heard Optimization 4

Efficient Feature Selection Techniques for Accurate Cancer A...

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4th International Conference on Emerging Systems and Intelligent Computing, ESIC 2024

作者： Singh, Shubham Narendra Mishra, Shruti Satapathy, Sandeep Kumar Cho, Sung-Bae Mallick, Pradeep Kumar Vellore Institute of Technology Computer Science and Engg Tamil Nadu Chennai India Vellore Institute of Technology Centre for Advanced Data Science Tamil Nadu Chennai India Yonsei University Department of Computer Science 50 Yonsei-ro Sudaemoon-gu Seoul03722 Korea Republic of Kiit University School of Computer Engineeing Odisha India

ISBN: (纸本)9798350349856

In this research, we introduce a novel biologically-inspired optimization algorithm known as Krill Herd (KH) to address feature selection challenges in cancer analysis. Inspired by the collective behaviour of krill individuals, the KH algorithm optimizes feature subsets by minimizing individual krill distances from food sources and herd density. We model the dynamic positions of krill individuals considering factors such as interactions with peers, foraging behaviour, and random diffusion. To enhance the algorithm's performance, we incorporate adaptive genetic operators. Our method's efficiency is evaluated across various benchmark optimization problems, demonstrating its capability to outperform eight established algorithms. In parallel, we delve into the critical domain of Cancer Feature Selection and classification in computational molecular biology. Identifying cancer-causing genes is pivotal for precise treatments and drug discovery. To address these challenges, we propose an enhanced Krill Herd Optimization (KHO) technique for gene selection, combined with Random Forest (RF) for classification. RF is chosen for its high classification accuracy. This research advances the field of cancer analysis by offering efficient and accurate feature selection techniques, providing insights into cancer-related genes, and facilitating more precise treatments and drug discoveries. © 2024 IEEE.

关键词： Feature Selection

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Enhanced Proof of Authentication(E-PoA) Consensus Blockchain-Based Secured Health Care Data Transmission in Internet of Things

Enhanced Proof of Authentication(E-PoA) Consensus Blockchain...

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Distributed Systems, computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： T. Keerthana D.R. Krithika Department of Computer Application Vels Institute of Science Technology and Advanced Studies Chennai India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Blockchain and the Internet of Things (IoT) are revolutionizing healthcare, presenting the potential for transformation. The IoT is achieving more and more confidence as the infrastructure for future applications. Therefore, based on the comprehensive integration of Blockchain (BC) technology with IoT, security requirements are provided through security frameworks built into BC. Healthcare IoT applications in BC technology are revolutionizing industries. It also analyzes the potential benefits of BC implementation in IoT and healthcare for securely transferring medical data. Blockchain's decentralized and immutable nature of medical data sharing offers secure ways to store and transmit data. However, it is necessary to protect the data's privacy stored and shared securely. This review paper evaluates the algorithm based on Rivest, Shamir, and Adelman (RSA), advanced Encryption Standard (AES), Lionized Golden Eagle-based Homomorphic Elapid Security (LGE-HES), and BC-Assisted Secure Data Management Framework (BSDMF). This survey paper describes Blockchain technology-based medical data transfer based on IoT medical systems. The performance evaluation regarding Root Mean Square Error (RMAE), MSE, time complexity, and security performance compared to standard technologies can be analyzed.

关键词： Surveys Privacy Data privacy Medical services Blockchains Security Internet of Things Time complexity Standards Systematic literature review

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Food-Health-Chain: A Food Supply Chain for Internet of Health Things Using Blockchain

Food-Health-Chain: A Food Supply Chain for Internet of Healt...

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International Conference on Network Security and Blockchain Technology, ICNSBT 2023

作者： Das, Puja Haldar, Amrita Singh, Moutushi Pise, Anil Audumbar Guha Roy, Deepsubhra Department of Computer Science HMM College for Women Dakshineswar Kolkata700035 India Department of Computer Science and Business Studies IEM Kolkata700091 India Department of Information Technology IEM Salt Lake Kolkata700091 India Department of Data Science and Machine Learning Computer Science University of the Witwatersrand Johannesburg South Africa Institute of Engineering and Management Kolkata700091 India

ISBN: (纸本)9789819944323

Foodborne disease is still a major public health concern in both advanced and emerging economies. In terms of adopting new technology, the health industry continues to lag behind all other sectors. India has traditionally relied on food farming to make money but which food item is good for whom we have no proper idea. Especially when it comes to healthcare sectors, the Internet of health things (IoHT) and blockchain can play an important role. It can enhance the quality of care for its users and reduce costs by allocating the correct food chain to the targeted users. We are currently employing blockchain in supply chain management to cluster the patients based on their health care type. For example, diabetic patients prefer a particular type of food. Segregating the food type within the supply chain can reduce a lot of effort and cost. Blockchain can provide a solution to the issues that arise in the healthcare-based supply chain system because of its decentralized and immutable nature. The service's execution has been depicted in pictures and accompanied by detailed descriptions. The ultimate result of this study was to demonstrate the immutability, availability, and transparency security of blockchain in the healthcare-based supply chain. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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Elite-guided equilibrium optimiser based on information enhancement:Algorithm and mobile edge computing applications

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CAAI Transactions on Intelligence Technology 2024年第5期9卷 1126-1171页

作者： Zong-Shan Wang Shi-Jin Li Hong-Wei Ding Gaurav Dhiman Peng Hou Ai-Shan Li Peng Hu Zhi-Jun Yang Jie Wang School of Information Science and Engineering Yunnan UniversityKunmingChina Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhenChina Academic Affairs Office Yunnan University of Finance and EconomicsKunmingChina Faculty of Management and Economics Kunming University of TechnologyKunmingChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirutLebanon Department of Computer Science and Engineering University Centre for Research and DevelopmentChandigarh UniversityChennaiIndia Department of Computer Science and Engineering Graphic Era Deemed to Be UniversityDehradunIndia School of Computer Science Fudan UniversityShanghaiChina Rackham Graduate School University of MichiganAnn ArborMIUSA Research and Development Department Youbei Technology Co.LTDKunmingChina School of Mechanical and Power Engineering Zhengzhou UniversityZhengzhouChina

The Equilibrium Optimiser(EO)has been demonstrated to be one of the metaheuristic algorithms that can effectively solve global optimisation *** the paradox between exploration and exploitation operations while enhancing the ability to jump out of the local optimum are two key points to be addressed in EO *** alleviate these limitations,an EO variant named adaptive elite-guided Equilibrium Optimiser(AEEO)is ***,the adaptive elite-guided search mechanism enhances the balance between exploration and *** modified mutualism phase reinforces the information interaction among particles and local optima *** cooperation of these two mechanisms boosts the overall performance of the basic *** AEEO is subjected to competitive experiments with state-of-the-art algorithms and modified algorithms on 23 classical benchmark functions and IEE CEC 2017 function test *** results demonstrate that AEEO outperforms several well-performing EO variants,DE variants,PSO variants,SSA variants,and GWO variants in terms of convergence speed and *** addition,the AEEO algorithm is used for the edge server(ES)placement problem in mobile edge computing(MEC)*** experimental results show that the author’s approach outperforms the representative approaches compared in terms of access latency and deployment cost.

关键词： ANT COLONY optimization CLOUD COMPUTING GENETIC ALGORITHMS SWARM intelligence

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Efficient Cross-Frequency Beam Prediction in 6G Wireless Using Time Series Data

Efficient Cross-Frequency Beam Prediction in 6G Wireless Usi...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Bhosale, Vaibhav Saxena, Navrati Bhardwaj, Ketan Gavrilovska, Ada Roy, Abhishek School of Computer Science Georgia Institute of Technology Atlanta United States San Jose State University Department of Computer Science San Jose United States Mediatek Inc Advanced Communication Technology San Jose United States

ISBN: (纸本)9798350364910

Next generation 6G wireless envisions a much higher data rate and a lower latency compared to 5G wireless networks. Directional antennas with narrow beams across high mmWave frequencies hold the key to achieving such high data rates. However, Beam Management (BM), which is the process of finding appropriate transmit and receive beams, offers significant challenges. Dynamic channel variation, user mobility, and narrow beams in high frequency mmWave channels further complicate these challenges. Efficient Machine Learning (ML) strategies can be used to alleviate this overhead. In spite of their underlying differences, sub-6 GHz and high frequency mmWave channels share some similarities in array geometry, number of paths, and surrounding environment. As sub-6 GHz channel characteristics are relatively easier to acquire and learn, we introduce a new machine learning framework, using transformer and LSTM to learn sub-6 GHz channel information over time for efficient beam prediction across high frequency mmWave channels. System Level simulation results point out that when using time-series data-based learning of beam patterns with transformers or LSTMs in sub-6 GHz channels, our proposed scheme achieves up to 99.5% top-5 beam prediction accuracy while reducing the BM overhead by over 50% compared to existing work. © 2024 IEEE.

关键词： 5G mobile communication systems

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Improved determination of the weights in a clustering approach based on a weighted dissimilarity measure between fuzzy data

Improved determination of the weights in a clustering approa...

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2022 IEEE International Conference on Fuzzy Systems, FUZZ 2022

作者： Eskandari, Elham Khastan, Alireza Tomasiello, Stefania Institute for Advanced Studies in Basic Sciences Department of Mathematics Zanjan Iran University of Tartu Institute of Computer Science Tartu Estonia

ISBN: (数字)9781665467100

ISBN: (纸本)9781665467100

In the literature, a popular dissimilarity measure between each pair of fuzzy data is defined as a weighted sum of the squared Euclidean distances among the centers and the spreads. The flexible weights introduced by D'Urso and Giordani in [Computational Statistics & Data Analysis 50 (2006) 1496-1523] may be helpful in certain situations as shown in that paper. The flexible weights are obtained by the minimization algorithm, and a larger weight is given to the center distance than the spread *** the present study, the weights are proposed to be fixed and equal to 0.5, which can contribute to higher performances of clustering methods in some cases. For instance, where the distance among the spreads is longer than that among the centers, i.e., the centers do not play a relevant role while the spreads play the predominant role, it is clear that a clustering method that takes the advantage of equal weights would outperform the other. Indeed, when there is no external condition, choosing the weights fixed and equal to 0.5 would be the best *** deeply investigate our claim, we provide a wide simulation study to show whether and under what circumstances the flexible weights are (not) helpful. The results furnished by numerical experiments on both simulated and benchmark datasets demonstrate the merit of using the fixed and equal to 0.5 weights suggested in the present paper. © 2022 IEEE.

关键词： Cluster analysis

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