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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Yangchen Palmo Shigeaki Tanimoto Hiroyuki Sato Atsushi Kanai Faculty of Social System Science Chiba Institute of Technology Narashino Japan Information Technology Center The University of Tokyo Tokyo Japan Faculty of Science and Engineering Hosei University Koganei Japan

ISBN: (纸本)9781665424219

Software Defined Perimeter (SDP), a zero trust model developed by Cloud Security Alliance, has been attracted attention in the technological industry since its introduction to a world adapting to digital transformation. The SDP market is expected to grow from USD 3,141 million in 2019 to USD 10,613.87 million by 2025 globally at a Compound Annual Growth Rate (CAGR) of 22.49% during the forecast period. Many trust models have been introduced since the realization for the need of cyber security, such as public key infrastructure, software defined network, and virtual private network. SDP gained importance as a zero trust model since in the digital world no one can be trusted. With the introduction of new models and technical devices, there arises the need to improve newly introduced technology on various grounds when customers adapt to devices. Hence, we discussed overcoming current issues of SDP of scalability, reliability, and usability, etc. With the number of organizations sharing information online expanding, there is need for scalable and reliable SDP that is easy to maintain and cost efficient for evolving organizations. Thus, we newly proposed several scalable SDP models that enable easier installation management of real networks of organizations with different organizational structures.

关键词： Adaptation models Scalability Public key Organizations Software Virtual private networks Software reliability

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Radar Sensing via OTFS Signaling: A Delay Doppler Signal Processing Perspective

Radar Sensing via OTFS Signaling: A Delay Doppler Signal Pro...

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IEEE International Conference on Communications (ICC)

作者： Kecheng Zhang Weijie Yuan Shuangyang Li Fan Liu Feifei Gao Pingzhi Fan Yunlong Cai Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Department of Electrical Electronic and Computer Engineering University of Western Australia Perth WA Australia Department of Automation Tsinghua University Beijing China Information Coding Transmission Key Lab of Sichuan Province CSNMT Int. Coop. Res. Centre (MoST) Southwest Jiaotong University Chengdu Sichuan China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China

The recently proposed orthogonal time frequency space (OTFS) modulation multiplexes data symbols in the delay-Doppler (DD) domain. Since the range and velocity, which can be derived from the delay and Doppler shifts, are the parameters of interest for radar sensing, it is natural to consider implementing DD signal processing for radar sensing. In this paper, we investigate the potential connections between the OTFS and DD domain radar signal processing. Our analysis shows that the range-Doppler matrix computing process in radar sensing is exactly the demodulation of OTFS with a rectangular pulse shaping filter. Furthermore, we propose a two-dimensional (2D) correlation-based algorithm to estimate the fractional delay and Doppler parameters for radar sensing. Simulation results show that the proposed algorithm can efficiently obtain the delay and Doppler shifts associated with multiple targets.

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Optimization strategy of automatic generation control in frequency regulation market based on improved particle swarm optimization algorithm

Optimization strategy of automatic generation control in fre...

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Chinese Control and Decision Conference, CCDC

作者： Dianyang Li Meishan Zhang Junjie Sun Qingsong Zhao Ning Zhao Bowen Wang State Grid Liaoning Electric Power Co.LTD Power Dispatching Control Cener Shenyang China College of Information Science and Engineering Northeastern University Shenyang China Power System and New Energy Technology Research Center State Grid LiaoNing Electric Power Supply Co. LTD Electric Power Research Institute Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Frequency stability is the most important prerequisite for the safe operation of the power grid. To ensure the safe and stable operation of all kinds of power equipment in the power supply system. The frequency of the power supply system must be maintained within a reasonable range. In this paper, a simulation study on the frequency modulation performance of the combined automatic generation control system based on the improved particle swarm optimization is proposed, and the bidding constraints of the energy storage market are introduced. In the aspect of regulation strategy, the thermal power unit is mainly responsible for the low frequency command, and the energy storage system is responsible for the high frequency command. The real-time management of state of charge can not only improve the performance index of frequency modulation, but also ensure the efficient and stable operation of energy storage system. The operation strategy of energy storage power station to participate in the market in real time. The influence of different types of disturbances and the demand of intraday frequency modulation market are also fully considered. Through the above methods, the frequency modulation performance index can be improved, the wear degree of thermal power units can be reduced, and the reliability of operation can be improved.

关键词： Frequency modulation Power supplies Heuristic algorithms Automatic generation control Real-time systems Performance analysis State of charge

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Research on Dual-Layer Coordinated Optimization Scheduling Model of Power system Based on Flow Battery for Renewable Energy Integration

Research on Dual-Layer Coordinated Optimization Scheduling M...

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Chinese Control and Decision Conference, CCDC

作者： Xinwei Li Dianyang Li Zhuang Cai Zhi Zhou Guangdong Zhao Jian Feng Power System and New Energy Technology Research Center State Grid LiaoNing Electric Power Supply Co. LTD Electric Power Research Institute Shenyang China Power Dispatching Control Center State Grid Liaoning Electric Power Co. LTD Shenyang China College of Information Science and Engineering Northeastern University Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

The integration of intermittent and fluctuating renewable energy sources such as wind and solar power into the power grid poses significant challenges for load balancing in the electricity system. To address the insufficient peak load regulation capability after the large-scale integration of renewable energy sources, a dual-layer coordinated optimization scheduling model is proposed by leveraging the rapidly evolving electrochemical energy storage device, namely the flow battery. In the first layer of the model, the objective is to enhance the overall peak load regulation capability of the power system by flattening load peaks and filling load valleys to improve the system's flexibility in load regulation and balance the supply-demand fluctuations. In the second layer of the model, the goal is to minimize the total cost of the power system operation while satisfying the optimization results of the first layer. This is achieved by re-planning the output of each component, including thermal power generation, renewable energy generation, and flow battery energy storage, to minimize the difference between costs and profits, thus reducing expenses. Finally, an improved IEEE 30-node system is used as a case study for simulation validation. The results demonstrate that with the integration of renewable energy sources, leveraging flow batteries for system load regulation enhances the overall peak load regulation capability and reduces the total cost of the system.

关键词： Renewable energy sources Costs Fluid flow Regulation Power grids Batteries Thermal loading

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HMAMP: Hypervolume-Driven Multi-Objective Antimicrobial Peptides Design

arXiv

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arXiv 2024年

作者： Wang, Li Liu, Yiping Fu, Xiangzheng Ye, Xiucai Shi, Junfeng Yen, Gary G. Zeng, Xiangxiang The College of Computer Scienceand Electronic Engineering Hunan University Hunan Changsha China The School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74078 United States The School of System Information and Engineering University of Tsukuba Ibaraki Japan Neher’s Biophysics Laboratory for Innovative Drug Discovery State Key Laboratory of Quality Research in Chinese Medicine Macau Institute for Applied Research in Medicine and Health Macau University of Science and Technology 999078 China

Antimicrobial peptides (AMPs) have exhibited unprecedented potential as biomaterials in combating multidrugresistant bacteria. Despite the increasing adoption of artificial intelligence for novel AMP design, challenges pertaining to conflicting attributes such as activity, hemolysis, and toxicity have significantly impeded the progress of researchers. This paper introduces a paradigm shift by considering multiple attributes in AMP design. Presented herein is a novel approach termed Hypervolume-driven Multi-objective Antimicrobial Peptide Design (HMAMP), which prioritizes the simultaneous optimization of multiple attributes of AMPs. By synergizing reinforcement learning and a gradient descent algorithm rooted in the hypervolume maximization concept, HMAMP effectively expands exploration space and mitigates the issue of pattern collapse. This method generates a wide array of prospective AMP candidates that strike a balance among diverse attributes. Furthermore, we pinpoint knee points along the Pareto front of these candidate AMPs. Empirical results across five benchmark models substantiate that HMAMP-designed AMPs exhibit competitive performance and heightened diversity. A detailed analysis of the helical structures and molecular dynamics simulations for ten potential candidate AMPs validates the superiority of HMAMP in the realm of multiobjective AMP design. The ability of HMAMP to systematically craft AMPs considering multiple attributes marks a pioneering milestone, establishing a universal computational framework for the multi-objective design of AMPs. Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

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Risk Management of Silent Cyber Risks in Consideration of Emerging Risks

Risk Management of Silent Cyber Risks in Consideration of Em...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Ryuya Mishina Shigeaki Tanimoto Hideki Goromaru Hiroyuki Sato Atsushi Kanai Faculty of Social System Science Chiba Institute of Technology Chiba Japan Information Technology Center The University of Tokyo Tokyo Japan Faculty of Science and Engineering Hosei University Tokyo Japan

ISBN: (纸本)9781665424219

In recent years, new cyber attacks such as targeted attacks have caused extensive damage. With the continuing development of the IoT society, various devices are now connected to the network and are being used for various purposes. The Internet of Things has the potential to link cyber risks to actual property damage, as cyberspace risks are connected to physical space. With this increase in unknown cyber risks, the demand for cyber insurance is increasing. One of the most serious emerging risks is the silent cyber risk, and it is likely to increase in the future. However, at present, security measures against silent cyber risks are insufficient. In this study, we conducted a risk management of silent cyber risk for organizations with the objective of contributing to the development of risk management methods for new cyber risks that are expected to increase in the future. Specifically, we modeled silent cyber risk by focusing on state transitions to different risks. We newly defined two types of silent cyber risk, namely, Alteration risk and Combination risk, and conducted risk assessment. Our assessment identified 23 risk factors, and after analyzing them, we found that all of them were classified as Risk Transference. We clarified that the most effective risk countermeasure for Alteration risk was insurance and for Combination risk was measures to reduce the impact of the risk factors themselves. Our evaluation showed that the silent cyber risk could be reduced by about 50%, thus demonstrating the effectiveness of the proposed countermeasures.

关键词： Electric breakdown Insurance Focusing Cyberspace Organizations Risk management Security

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HealthEdge: A Machine Learning-Based Smart Healthcare Framework for Prediction of Type 2 Diabetes in an Integrated IoT, Edge, and Cloud Computing system

arXiv

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arXiv 2023年

作者： Hennebelle, Alain Materwala, Huned Ismail, Leila Melbourne Australia Research Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates National Water and Energy Center United Arab Emirates University United Arab Emirates Lab School of Computing and Information Systems The University of Melbourne Australia

Diabetes Mellitus has no permanent cure to date and is one of the leading causes of death globally. The alarming increase in diabetes calls for the need to take precautionary measures to avoid/predict the occurrence of diabetes. This paper proposes HealthEdge, a machine learning-based smart healthcare framework for type 2 diabetes prediction in an integrated IoT-edge-cloud computing system. Numerical experiments and comparative analysis were carried out between the two most used machine learning algorithms in the literature, Random Forest (RF) and Logistic Regression (LR), using two real-life diabetes datasets. The results show that RF predicts diabetes with 6% more accuracy on average compared to LR. © 2023, CC BY-NC-ND.

关键词： Edge computing

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First-Principles Study of Electronic Structure and Metallization of Mg2pb Under High Pressure

SSRN

引用

SSRN 2023年

作者： Li, Yuqiang Li, Yuhong Zhang, Qiang Su, Ningning Sun, Jinlu Xiao, Ningru Liu, Yang Liu, Yuyao Ning, Pingfan Liu, Hongwei Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems School of Electronics and Information Engineering Tiangong University Tianjin300387 China Key Laboratory of Smart Grid of Ministry of Education School of Electrical and Information Engineering Tianjin University Tianjin300072 China School of Semiconductor and Physics North University of China Taiyuan030051 China Engineering Research Center of High Power Solid State Lighting Application System Ministry of Education Tiangong University Tianjin300387 China School of Physical Science and Technology Tiangong University Tianjin300387 China

The high-pressure electronic structure and electrical properties of Mg2Pb are investigated from ambient pressure to 42 GPa by first-principles calculation. Mg2Pb undergoes reversible structural transitions from Fm-3m structure to Pnma structure and then to P63/mmc structure. The structural phase transitions are determined respectively at around 6 GPa and 28 GPa using pressure-dependent enthalpy calculations, which are also reflected from the cell volume collapse and discontinuous axial ratios of lattice constants. The sliding of Mg and Pb atomic layers is revealed via the Mg1-Pb-Mg2 atom pair during structural phase transitions, corresponding to abrupt decrease of c/b and a/b. The semimetal-to-metal transition is also observed at approximately 28 GPa owing to energy-band closure, whilst metallic character is strengthened with increasing pressure. The paper is prone to explore the structural phase transition and metallization of Mg2Pb-type family in theory under extreme conditions. © 2023, The Authors. All rights reserved.

关键词： Electronic structure

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iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud

arXiv

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arXiv 2022年

作者： Xu, Fei Xu, Jianian Chen, Jiabin Chen, Li Shang, Ruitao Zhou, Zhi Liu, Fangming The Shanghai Key Laboratory of Multidimensional Information Processing School of Computer Science and Technology East China Normal University 3663 N. Zhongshan Road Shanghai200062 China The School of Computing and Informatics University of Louisiana at Lafayette 301 East Lewis Street LafayetteLA70504 United States The Guangdong Key Laboratory of Big Data Analysis and Processing School of Computer Science and Engineering Sun Yat-sen University 132 E. Waihuan Road Guangzhou510006 China The National Engineering Research Center for Big Data Technology and System The Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology 1037 Luoyu Road Wuhan430074 China

GPUs are essential to accelerating the latency-sensitive deep neural network (DNN) inference workloads in cloud datacenters. To fully utilize GPU resources, spatial sharing of GPUs among co-located DNN inference workloads becomes increasingly compelling. However, GPU sharing inevitably brings severe performance interference among co-located inference workloads, as motivated by an empirical measurement study of DNN inference on EC2 GPU instances. While existing works on guaranteeing inference performance service level objectives (SLOs) focus on either temporal sharing of GPUs or reactive GPU resource scaling and inference migration techniques, how to proactively mitigate such severe performance interference has received comparatively little attention. In this paper, we propose iGniter, an interference-aware GPU resource provisioning framework for cost-efficiently achieving predictable DNN inference in the cloud. iGniter is comprised of two key components: (1) a lightweight DNN inference performance model, which leverages the system and workload metrics that are practically accessible to capture the performance interference;(2) A cost-efficient GPU resource provisioning strategy that jointly optimizes the GPU resource allocation and adaptive batching based on our inference performance model, with the aim of achieving predictable performance of DNN inference workloads. We implement a prototype of iGniter based on the NVIDIA Triton inference server hosted on EC2 GPU instances. Extensive prototype experiments on four representative DNN models and datasets demonstrate that iGniter can guarantee the performance SLOs of DNN inference workloads with practically acceptable runtime overhead, while saving the monetary cost by up to 25% in comparison to the state-of-the-art GPU resource provisioning strategies. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep neural networks

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MXene-Composite-Enabled Ultra-long-Distance Detection and Highly Sensitive Self-Powered Noncontact Triboelectric Sensors and Their Applications in Intelligent Vehicle Perception

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Advanced Functional Materials 2023年第52期33卷

作者： Zhao, Cong Wang, Zhaoyang Wang, Yawei Qian, Zian Tan, Zheng Chen, Qingyu Pan, Xinxiang Xu, Minyi Lai, Ying-Chih Dalian Key Lab of Marine Micro/Nano Energy and Self-powered Systems Marine Engineering College Dalian Maritime University Dalian116026 China Transportation Engineering College Dalian Maritime University Dalian116026 China Information Science and Technology College Dalian Maritime University Dalian116026 China School of Electronics and Information technology Guangdong Ocean University Zhanjiang524088 China Department of Materials Science and Engineering National Chung Hsing University Taichung40227 Taiwan Innovation and Development Center of Sustainable Agriculture i-Center for Advanced Science and Technology National Chung Hsing University Taichung40227 Taiwan

With the ongoing advancement in sensor technologies, the development of intelligent, secure, and low-carbon vehicles will be possible in the near future. However, providing continuous power to numerous onboard sensors consumes substantial amounts of power from vehicle, resulting in the shortened running times. Herein, a self-powered noncontact triboelectric nanogenerator (SNC-TENG) with ultralong-distance detection and a high sensitivity is proposed, which can be used as ambient perception sensors for smart vehicles. The SNC-TENG is constructed from a MXene/silicone nanocomposite with a fully embedded conductive sponge, which significantly enriches the tribo-charges and leads to an excellent capability and performance. This SNC-TENG is capable of perceiving human activity from a distance of 2 m. To the best of authors knowledge, the perceiving distance per unit area of this SNC-TENG is the highest among previously reported non-contact TENGs. Furthermore, the applicability of the SNC-TENG is explored for vehicle sentry mode and blind spot detection for the first time. The use of this technology in a real vehicle demonstrates its feasibility for use in practical applications. Overall, this study provides a new design scheme for contactless self-powered sensors, and the presented SNC-TENG is expected to be applicable in various fields where non-contact sensing is required. © 2023 Wiley-VCH GmbH.

关键词： Nanogenerators

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