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共 413 条记录，以下是21-30 订阅

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Federated Anomaly Detection

Federated Anomaly Detection

引用

IEEE/IFIP International Conference on Dependable Systems and networks â€“ Supplemental Volume (DSN-S)

作者： Chunjiong Zhang Byeong-Hee Roh Gaoyang Shan Dept. of AI Convergence Network Ajou University Suwon Korea Dept. of Software and Computer Engineering Ajou University Suwon Korea

ISBN: (数字)9798350395709

ISBN: (纸本)9798350395716

More and more portable intelligent devices are connected to the Internet in recent years. A way to effectively use the isolated cyber data without involving privacy and realize the cyber intrusion anomaly detection on the portable intelligent devices with relatively limited hardware storage resources and computing power is worth exploring. In this paper, we propose a framework of federated anomaly detection, which enables the device effectively detect the anomaly by sharing the parameters of the federated model in a fully distributed fashion. We formulate the model training problem as a distributed robust optimization problem and subsequently devise an efficient algorithm for it. Experimental studies have also been carried out to reveal the superior performance of the proposed framework and underscore the significant benefits of federated anomaly detection.

关键词： Training Performance evaluation Data privacy Federated learning Computational modeling Hardware Internet

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Performance Analysis for Biometric Identification Systems with Nonlegitimate Users

Performance Analysis for Biometric Identification Systems wi...

引用

2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Yagi, Hideki Hirasawa, Shigeichi University of Electro-Communications Dept. of Computer and Network Engineering Tokyo Japan Waseda University Center for Data Science Tokyo Japan

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

The biometric identification system, introduced by Willems et al., is a mathematical model to identify users based on their physical features. Although the maximum rate of the number of users which are reliably dealt with in the system (identification capacity) and the exponential behavior of the average error probability (error exponents) of the legitimate users have been revealed via information theoretic approaches, optimum error exponents has not been shown when there exists a nonlegitimate user in the system. In this paper, we formally define the reliability function as the optimum error exponent for legitimate users for a given rate of the number of legitimate users and a given error exponent for the nonlegitimate users. It is shown that the reliability function can be completely characterized by the well-known random coding exponent and the hypothesis testing error exponent. © 2022 IEEE.

关键词： Biometrics

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Differential Co-expression network Analysis to Investigate Sexual Dimorphism in Colon Cancer

Differential Co-expression Network Analysis to Investigate S...

引用

2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Alfano, Caterina Farina, Lorenzo Petti, Manuela Sapienza University of Rome PhD Program in Network Oncology and Precision Medicine Rome Italy Sapienza University of Rome PhD Program in Network Oncology and Precision Medicine Dept. of Computer Control and Management Engineering Rome Italy Sapienza University of Rome Dept. of Computer Control and Management Engineering Rome Italy

ISBN: (纸本)9781665468190

Colorectal cancer is the third most diagnosed cancer in the world, but it has a higher mortality rate in men compared to women. However, we are not close to understanding how and why sex influences the outcome of the disease. This study focuses on mRNA expression profiles of colon cancer patients to look for molecular differences in the development of colon cancer between men and women. We used paired expression data (i.e., data collected in pairs of normal and cancer cells, by taking samples from the same individual), we identified differentially expressed genes (cancer vs normal) and computed co-expression and differential co-expression gene networks (men vs women). Doing so, we inferred the main changes and alterations happening in cancer tissues, and specifically how these changes were different among men and women. We found that the co-expression networks of women and men affected by colon cancer are quite different and we reported the genes that show the most differences in this comparison, checking if they could also be associated to sexual dimorphism or sexual hormones. Among these genes we found a interesting presence of genes associated to the Wnt signaling pathway which has been found to be regulated by estrogen and whose activation is strongly linked with colon cancer. © 2022 IEEE.

关键词： Diseases

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Combining AF-based Relay and Multiantenna for Over-the-Air Computation

Combining AF-based Relay and Multiantenna for Over-the-Air C...

引用

International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Suhua Tang Sadao Obana Dept. of Computer and Network Engineering The University of Electro-Communications Tokyo Japan The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Over-the-air computation has attracted much attention in wireless data aggregation, which collects and processes data simultaneously with high efficiency. Different propagation distances from nodes to the sink or channel fading may lead to misalignment in signal magnitude and result in computation error. In our previous work, amplify and forward (AF) based relay has been investigated. With multiantenna available at the sink, it is possible to achieve better performance by the misalignment allowed optimization (Miso), compared with zero forcing (ZF) which requires all signals aligned in signal magnitude. But Miso does cause many signals misaligned in signal magnitude, leading to a biased result. Aiming to further improve system performance, in this work, we study how to combine the AF based relay with Miso by a joint optimization, and solve it with an iterative algorithm. Extensive simulations verify the effectiveness of the proposed method.

关键词： Wireless networks Computational modeling System performance Transmitting antennas MISO communication Data aggregation Iterative methods

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Low Earth Orbit Satellite Scheduling Optimization Based on Deep Reinforcement Learning

Low Earth Orbit Satellite Scheduling Optimization Based on D...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Junyoung Kim Soyi Jung Dept. Artificial Intelligence Convergence Network Ajou University Suwon South Korea Dept. Electrical and Computer Engineering Ajou University Suwon South Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

In next-generation 6G scenarios, non-terrestrial net-works employing low Earth orbit (LEO) satellites will be pivotal in achieving ultra-wide coverage, ultra-connectivity, and ultra-precision. Although LEO satellites provide comprehensive global coverage, their rapid mobility introduces frequent handovers, requiring sophisticated scheduling to maintain uninterrupted service. This paper proposes a deep reinforcement learning-based scheduling algorithm in order to improve service rate and continuity for terrestrial users in multi-LEO) environments.

关键词： Satellites Scheduling algorithms Low earth orbit satellites Handover Deep reinforcement learning Timing Information and communication technology Optimization Next generation networking Convergence

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CNN-LSTM Based Prediction of LoS Duration in Satellite Communication network

CNN-LSTM Based Prediction of LoS Duration in Satellite Commu...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Huiyeon Jang Soyi Jung Dept. Artificial Intelligence Convergence Network Ajou University Suwon South Korea Dept. Electrical and Computer Engineering Ajou University Suwon South Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Satellite communication system is crucial to the advancement of sixth-generation (6G) networks, providing global connectivity and supporting applications that demand ultraspeed high and low latency. However, the high mobility of low Earth orbit (LEO) satellites poses significant challenges to maintaining consistent communication links, primarily due to the frequent handover required by user equipment. Traditional signal strength-based handover technique, which is effective in terrestrial networks, struggles in the satellite network due to the minimal signal strength variation across overlapping cells. This leads to frequent and unnecessary handovers, resulting in reduced network performance. To address these challenges, we propose an CNN-LSTM based predictive line-of-sight (LoS) duration estimation method that allows user terminals to anticipate satellite connection stability, minimizing unnecessary handovers and improving network efficiency in dynamic satellite environments.

关键词： Satellite constellations Satellites Low earth orbit satellites Line-of-sight propagation Handover Predictive models Stability analysis Low latency communication Satellite communications Long short term memory

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A Survey of Behavior Tree-Based Task Planning Algorithms for Autonomous Robotic Systems

A Survey of Behavior Tree-Based Task Planning Algorithms for...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Mingyu Shin Soyi Jung Dept. Artificial Intelligence Convergence Network Ajou University Suwon South Korea Dept. Electrical and Computer Engineering Ajou University Suwon South Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Behavior trees (BTs) have gained recognition for their modularity and scalability, establishing them as a robust framework for task automation and planning in various domains, including robotics, game AI, and autonomous systems. This paper presents a comprehensive review of the integration of BTs with reinforcement learning (RL) and learning-from-demonstration (LfD) to enhance decision making and task planning in robotic systems. The review emphasizes the advantages of BTs, such as increased adaptability and efficiency through RL integration and the simplification of robot programming via LfD. Despite these benefits, challenges persist in the areas of computational complexity, scalability in multi-agent systems, and the automatic generation of BTs. This paper concludes by identifying key areas for future research to address these challenges and further advance the development of autonomous robotic systems.

关键词： Surveys Autonomous systems Reviews Scalability Decision making Reinforcement learning Planning Information and communication technology Robot programming Multi-agent systems

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Reinforcement Learning-Based Motion Planning for Robotic Manipulators in Smart Industry

Reinforcement Learning-Based Motion Planning for Robotic Man...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Junhyung Cho Soyi Jung Dept. Artificial Intelligence Convergence Network Ajou University Suwon South Korea Dept. Electrical and Computer Engineering Ajou University Suwon South Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

The advent of smart industry, propelled by the inte-gration of digital technologies and automation, has revolutionized manufacturing and industrial processes. Robotics and artificial intelligence (AI) are at the forefront of this transformation, driving extensive research into robotic automation and motion planning. Traditional motion planning algorithms, such as artificial potential fields, bio-inspired heuristics, and sampling-based methods, often falter in complex environments due to their high computational demands and tendency to produce non-optimal solutions. Reinforcement learning (RL) has emerged as a powerful alternative, offering real-time adaptation and optimal decision-making in dynamic settings. This paper reviews the inherent limitations of classical motion planning approaches and explores contemporary trends in RL-based methods, with a focus on their application in smart industry. It highlights the advantages of RL in enhancing adaptability, efficiency, and robustness, particularly in high-dimensional and dynamic environments. Key discussions include the integration of RL with traditional techniques, the extension of RL applications across various domains, and the role of sensor-based approaches in improving motion control.

关键词： Industries Automation Service robots Dynamics Reinforcement learning Robot sensing systems Real-time systems Robustness Planning Artificial intelligence

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New Constructions of Even-Length Perfect Gaussian Integer Sequences

New Constructions of Even-Length Perfect Gaussian Integer Se...

引用

IEEE International Conference on Signal and Image Processing (ICSIP)

作者： Chong-Dao Lee Kun-Lin Lee Dept. of Intelligent Network Technology I-SHOU University Kaohsiung City TAIWAN Dept. of Electrical and Computer Engineering TAMKANG University New Taipei City TAIWAN

ISBN: (数字)9798350350920

ISBN: (纸本)9798350350937

Perfect Gaussian integer sequences (PGISs) with ideal periodic autocorrelation functions have been extensively used to communication systems and cryptosystems. This paper propose several new families of even-length PGISs based on novel base sequences. The resulting sequences consists of at most 12 Gaussian integers. The new developed construction method is to use Gaussian integers of different Euclidean norms as the coefficients of a linear combination of the newly presented and previously developed base sequences. Both theoretical proofs and illustrated examples for new PGISs are given. The advantages of these new PGISs are either low energy or large degree when compared to the existing sequences.

关键词： OFDM Image processing Multiaccess communication Autocorrelation

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Fuzzy C-Means Clustering Approach for Green IoT in Smart Cities

Fuzzy C-Means Clustering Approach for Green IoT in Smart Cit...

引用

Power, Control and Computing Technologies (ICPC2T), Conference on

作者： Aya Ayad Hussein Hazem N. Abdulrazzak Department of Network Engineering Faculty of Engineering Al-Iraqia University Baghdad Iraq Computer Communication Engineering Dept. Al-Rafidain University College Baghdad Iraq

Cluster-based routing or Hierarchical is a widely recognized approach with particular benefits in terms of scalability and communication efficiency. In Wireless Sensor networks supported $IoT$ , the utilization of clustered routing is a cost-effective method of data collection and transmission, where nodes with the most energy remaining can be utilized to collect and transmit data. This paper proposed a soft Fuzzy C-Means Dynamic Clustering (FCM-DC) Approach. A new Cluster Head (CH) selection technique was presented also. The proposed model was compared with an existing cluster based routing protocol, LEACH protocol, and LEACH-C protocol. The proposed FCM-DC model reduce the packet delay about 16% in 50 nodes scenario and 86% in 100 nodes scenario compared with LEACH.

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