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46th International Conference on Telecommunications and Signal Processing, TSP 2023

作者： Nako, Julia Tsirimokou, Georgia Psychalinos, Costas University of Patras Department of Physics Electronics Laboratory Rio Patras Greece University of Ioannina Department of Computer Science & Engineering Ioannina Greece

ISBN: (纸本)9798350303964

Generalized structures capable of implementing both fractional-order and power-law controllers are presented in this work. The first one is an active-RC scheme, realized using one active element, while the second one is a Field Programmable Analog Array implementation offering digital programming of the realized controller functions. The derivation of the rational integer-order approximation functions is achieved, in both cases, through the employment of a curve fitting based algorithm. The behavior of the presented structures is evaluated through simulation and experimental results. © 2023 IEEE.

关键词： Controllers

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A novel deep generative model for mRNA vaccine development: Designing 5′ UTRs with N1-methyl-pseudouridine modification

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Acta Pharmaceutica Sinica B 2024年第4期14卷 1814-1826页

作者： Xiaoshan Tang Miaozhe Huo Yuting Chen Hai Huang Shugang Qin Jiaqi Luo Zeyi Qin Xin Jiang Yongmei Liu Xing Duan Ruohan Wang Lingxi Chen Hao Li Na Fan Zhongshan He Xi He Bairong Shen Shuai Cheng Li Xiangrong Song Institute of Systems Genetics Department of Critical Care MedicineFrontiers Science Center for Disease-related Molecular NetworkState Key Laboratory of Biotherapy and Cancer CenterWest China HospitalSichuan UniversityChengdu 610000China Department of Computer Science City University of Hong KongHong Kong 99907China Department of Biology Brandeis UniversityBostonMA 02453USA

Efficient translation mediated by the 5'untranslated region(5'UTR)is essential for the robust efficacy of mRNA ***,the N1-methyl-pseudouridine(m1)modification of mRNA can impact the translation efficiency of the 5'*** discovered that the optimal 5'UTR for m1y-modified mRNA(m1y-5'UTR)differs significantly from its unmodified counterpart,high-lighting the need for a specialized tool for designing mly-5'UTRs rather than directly utilizing high-expression endogenous gene 5'*** response,we developed a novel machine learning-based tool,Smart5UTR,which employs a deep generative model to identify superior m1y-5'UTRs in *** tailored loss function and network architecture enable Smart5UTR to overcome limitations inherent in existing *** a result,Smart5UTR can successfully design superior 5'UTRs,greatly benefiting mRNA vaccine ***,Smart5UTR-designed superior 5'UTRs significantly enhanced antibody titers induced by COVID-19 mRNA vaccines against the Delta and Omicron variants of SARS-CoV-2,surpassing the performance of vaccines using high-expression endogenous gene 5'UTRs.

关键词： mRNA vaccine Machine learning 5'UTR mRNA design Sequence design N1-Methyl-pseudouridine COVID-19 SARS-CoV-2

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Delving into the Realm of Information-Theoretic Security Emerging Trends and Future Directions

Delving into the Realm of Information-Theoretic Security Eme...

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2024 International Conference on Communication, computer sciences and Engineering, IC3SE 2024

作者： Srilekha, Gopu Santosh Kumar, B. Singh, Navdeep Singh, Jay Bhavana, Munugapati Jabbar, Ahmed Sabah Abed AL-Zahra Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India New Horizon College Of Engineering Department Of Computer Science Engineering Bangalore India Lovely Professional University Phagwara India Gl Bajaj Institute Of Technology & Management U.P. Greater Noida India Mlr Institute Of Technology Department Of Computer Science And Information Technology Telangana Hyderabad India College Of Medical Technology The Islamic University Medical Laboratory Technology Department Najaf Iraq

ISBN: (纸本)9798350366846

QKD, ECC, PQC, SMPC, and biometric-based authentication are examined in this work as essential information-theoretic security approaches. Each solution improves information-theoretic security by improving communication, error reduction, quantum-resistant cryptography, project collaboration, and identity verification. Quantum Key Distribution employs quantum entanglement and regular transmission to secure key exchange in a 12-step flowchart. Error-Correcting Code Implementation employs Reed-Solomon codes to discover and rectify errors in delivered messages in 10 steps, protecting data. Post-Quantum Cryptography uses a 10-step graphic to demonstrate lattice-based solutions for post-quantum security and secure communication. A 10-step 'safe multi-party computing' procedure enables individuals to collaborate on a computer project while safeguarding their privacy. It uses homomorphic encryption to secure protected data computations. Biometric authentication employs biometric data to verify a person's name in 10 steps with complicated arithmetic. Tables and graphs indicate that the information-theoretic approach outperforms other security techniques in key size, quantum attack resistance, authentication strength, and total security. These results demonstrate that the suggested strategy may considerably increase information-theoretic security in many scenarios. The response to the developing field of information security is robust. © 2024 IEEE.

关键词： Quantum cryptography

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Normalization in R2-Based Hypervolume and Hypervolume Contribution Approximation

Normalization in R2-Based Hypervolume and Hypervolume Contri...

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Wu, Guotong Shu, Tianye Shang, Ke Ishibuchi, Hisao Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9781665430654

In this paper, we examine the effect of normalization in R2-based hypervolume and hypervolume contribution approximation. The fact is that the region with different scales on objective space brings approximation bias. The basic idea of normalization is to perform a coordinate transformation to make the shape of the approximated region more regular, and then transform it to obtain the final value according to the property of hypervolume and hypervolume contribution. The performance of normalization is evaluated on different datasets by comparing it with the original R2-based method. We use two different metrics to evaluate hypervolume and hypervolume contribution separately, and the results indicate that normalization does exactly improve the approximation accuracy and outperforms the original R2-based method. © 2023 IEEE.

关键词： Hypervolume Normalization ─Multi-objective Optimization

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A Lightweight AI Model for Anomaly Detection in Wireless Networks 2

A Lightweight AI Model for Anomaly Detection in Wireless Net...

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2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Kopcho, Thomas J. Fouda, Mostafa M. Krome, Cameron J. Idaho State University Department of Computer Science PocatelloID United States Idaho State University Department of Electrical and Computer Engineering PocatelloID United States Idaho National Laboratory Ai Data & Visualization Idaho FallsID United States

ISBN: (纸本)9798331529529

Detecting network anomalies is critical for wireless network security and reliability. Traditional AI methods often require substantial computational resources, particularly when deployed on cloud servers, leading to increased network load and latency. In contrast, deploying AI models directly on end devices enables real-time data processing at the source, facilitating faster anomaly detection and mitigation. We propose a lightweight hierarchical AI model where initial inferences are made by a simple model and outputs confidence scores. Using a modified TOPSIS-based method, we determine an optimal confidence score threshold. Inferences below this threshold are forwarded to a more complex model for accurate analysis, reducing overall computational demands while maintaining high detection performance. Our approach is tested on a 5 G network dataset, demonstrating competitive performance compared to other anomaly detection models. © 2024 IEEE.

关键词： 5G mobile communication systems

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Analyzing the Impact of Security Measures on Wi-Fi Quality of Service 2

Analyzing the Impact of Security Measures on Wi-Fi Quality o...

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2nd International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2024

作者： Kopcho, Thomas J. Fouda, Mostafa M. Krome, Cameron J. Quach, Anna T. Olaveson, Israel G. Idaho State University Department of Computer Science PocatelloID United States Idaho State University Department of Electrical and Computer Engineering PocatelloID United States Ai Data & Visualization Idaho National Laboratory Idaho FallsID United States

ISBN: (纸本)9798331529529

This study examines the relationship between Quality of Service (QoS) and security in Wi-Fi networks. Using a detailed dataset consisting of QoS metrics of file transfers under various security configurations, we analyze the impact of these settings on network performance. Our findings provide a quantification to accurately show that different encryption protocols, such as TKIP and CCMP, significantly affect QoS, with disabling security generally improving performance. The study provides a framework for optimizing security settings to enhance both security and QoS in future wireless networks. © 2024 IEEE.

关键词： Wireless local area networks (WLAN)

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Privacy Preserving Fingerprint Authentication based on Homomorphic Encryption and Blockchain 1

Privacy Preserving Fingerprint Authentication based on Homom...

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1st International Conference on computer Communications and Intelligent Systems, I3CIS 2022

作者： Yousra, Ali Zouaghi Meriama, Mahamdioua Atidel, Lahoulou Mohamed Seddik Ben Yahia University Faculty of Exact Sciences and Computer Science Computer Science Department Jijel Algeria Laoti Laboratory Mohamed Seddik Ben Yahia University Computer Science Department Jijel Algeria

ISBN: (纸本)9781665461887

Biometric authentication methods generally rely on centralized authority such as centralized database servers to store biometric templates and manage authentication. These methods suffer from different points of attack. If the central entity is compromised, the system becomes vulnerable and unable to ensure integrity of stored templates. This paper proposes a distributed scheme of biometric authentification, eliminating the need for a central entity. The proposal is based on the Ethereum blockchain, which offers decentralized and irreversible properties for the storage and management of biometric templates. For each user, the fingerprint template is encrypted using homomorphic encryption and stored on the smart card. The hashed encrypted vector is then stored on the blockchain to ensure its confidentiality. Our proposed scheme, allows authentication of users using a smart contract, while the distance calculation is performed on the encrypted domain that achieves the integrity of the calculation results. By using hashed vectors, the proposal is efficient and cost-effective. These improvements provide solutions to many problems in biometric systems such as template modification, channel interception, and override comparator. © 2022 IEEE.

关键词： Smart contract

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Empirical Hypervolume Optimal μ-Distributions on Complex Pareto Fronts

Empirical Hypervolume Optimal μ-Distributions on Complex Pa...

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Shang, Ke Shu, Tianye Wu, Guotong Nan, Yang Pang, Lie Meng Ishibuchi, Hisao Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9781665430654

Hypervolume optimal μ-distribution is the distribution of μ solutions maximizing the hypervolume indicator of μ solutions on a specific Pareto front. Most studies have focused on simple Pareto fronts such as triangular and inverted triangular Pareto fronts. There is almost no study which focuses on complex Pareto fronts such as disconnected and partially degenerate Pareto fronts. However, most real-world multi-objective optimization problems have such a complex Pareto front. Thus, it is of great practical significance to study the hypervolume optimal μ-distribution on the complex Pareto fronts. In this paper, we study this issue by empirically showing the hypervolume optimal μ-distributions on the Pareto fronts of some representative artificial and real-world test problems. Our results show that, in general, maximizing the hypervolume indicator does not lead to uniformly distributed solution sets on the complex Pareto fronts. We also give some suggestions related to the use of the hypervolume indicator for performance evaluation of evolutionary multi-objective optimization algorithms. © 2023 IEEE.

关键词： complex Pareto front Hypervolume multi-objective optimization optimal μ-distribution

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Ensemble R2-based Hypervolume Contribution Approximation

Ensemble R2-based Hypervolume Contribution Approximation

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2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023

作者： Wu, Guotong Shu, Tianye Nan, Yang Shang, Ke Ishibuchi, Hisao Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9781665430654

The hypervolume-based multi-objective evolutionary algorithms (HV-MOEAs) have proven to be highly effective in solving multi-objective optimization problems. However, the computation time of the hypervolume calculation increases significantly as the number of objectives increases. To address this issue, an R2-based hypervolume contribution approximation (R2-HVC) method was proposed. Nevertheless, the original R2-HVC generates a large number of vectors and computes the HVC only once. In this study, we propose an ensemble method based on the R2-HVC method. By using a small number of vectors for repetitive computation and majority voting, the ensemble method can reduce the probability of making incorrect choices. Experimental results show that the proposed method can improve the approximation accuracy while maintaining a similar computation time to the original R2-HVC method. © 2023 IEEE.

关键词： Ensemble Method Hypervolume Contribution Majority Voting Multi-objective Optimization

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Semi-supervised Medical Image Segmentation via Feature-perturbed Consistency

Semi-supervised Medical Image Segmentation via Feature-pertu...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Yang, Yang Wang, Ruixuan Zhang, Tong Su, Jingyong Harbin Institute of Technology School of Computer Science and Technology Shenzhen China Peng Cheng Laboratory Department of Network Intelligence Shenzhen China Sun Yat-sen University School of Computer Science and Engineering Guangzhou China

ISBN: (纸本)9798350337488

Although deep convolutional neural networks have achieved satisfactory performance in many medical image segmentation tasks, a considerable annotation challenge still needs to be solved, which is expensive and time-consuming for radiologists. Most existing popular semi-supervised methods mainly impose data-level perturbations (e.g., rotation, noising) or feature-level perturbations (e.g., MC dropout) on unlabeled data. In this paper, we propose a novel semi-supervised segmentation strategy with meaningful perturbations at the feature level to leverage abundant useful information naturally embedded in the unlabeled data. Specifically, we develop a dual-task network where the segmentation head produces multiple predictions with a perturbation module, and the reconstruction head further utilizes the semantic information to enhance segmentation performance. The proposed framework subtly perturbs the network at the feature-level to generate predictions which should be similar and consistent. However, enforcing them roughly to be consistent at all pixels harms stable training and neglects much delicate information. To better utilize those predictions and estimate the uncertainty, we further propose feature-perturbed consistency to exploit reliable regions for our framework to learn from. Extensive experiments on the public BraTS2020 dataset and the 2017 ACDC dataset confirm the efficiency and effectiveness of our method. In particular, the proposed method demonstrates remarkable superiority in the segmentation of boundary regions. The project is available at https://***/youngyzzZ/SFPC. © 2023 IEEE.

关键词： Image segmentation Semi-supervised learning Uncertainty estimation

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