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international conference on computing, Intelligence and Data Analytics, ICCIDA 2022

International Conference on Computing, Intelligence and Data...

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international conference on computing, Intelligence and Data Analytics, ICCIDA 2022

ISBN: (纸本)9783031270987

The proceedings contain 44 papers. The special focus in this conference is on computing, Intelligence and Data Analytics. The topics include: Preface;Priority-Based Pollution Management ITS;security Issues for Banking Systems;smart Autonomous Bike Hardware Safety Metrics;demand Side Management Based Cost-Centric Solution for a grid Connected Microgrid System with Pico-Hydro Storage System;impact of Multimodal Model Complexity on Classification of Diabetic Retinopathy Level;secure Image Data Encryption Scheme for 5G Internet of Things applications;Symptom Based Health Status Prediction via Decision Tree, KNN, XGBoost, LDA, SVM, and Random Forest;Multiband Microstrip Elliptical Monopole Antenna Design with Mushroom-Like Loadings for DCS, 5G and Ku-Band applications;an IoT-Based Modular Avionics and Electrical System for Nanosatellite Systems;reinforcement Learning for Intrusion Detection;comparison of Small-Sized Deep Neural Network Models for Hyperspectral Image Classification;autonomous Mobile Robot Mapping and Exploration of an Indoor Environment;time-Sensitive Embedding for Understanding Customer Navigational Behavior in Mobile Banking;do Lunar Cycles Affect Bitcoin Prices?;Stock Price Prediction in Response to US Dollar Exchange Rate Using Machine Learning Techniques;A Service of RSU Communication in Internet of Vehicles (IoV) in Urban Environment;a Comparative Study on Subdural Brain Hemorrhage Segmentation;deep Learning Based Spectrum Sensing Method for Cognitive Radio System;Colour Image Encryption Based on HACS and Knuth-Durstenfeld Algorithm;Turkish Sign Language Recognition by Using Wearable MYO Armband;effects of Different Parameters on Sleep Quality;predictive Maintenance on Industrial Data Using Soft Voted Ensemble Classifiers;Medical Image Transmission Using a Secure Cryptographic Approach for IoMT applications;volume Forecasting in Supply Chain: A Mixed Study of Boosting and Prophet Algorithms;blockchain-Based System for Traceability of Counterfeit Med

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Intrusion Detection in Power Cyber-Physical Systems Using Denoising Autoencoder and EQL v2 Loss Function 20th

Intrusion Detection in Power Cyber-Physical Systems Using De...

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20th international conference on Intelligent computing (ICIC)

作者： Zhang, Yiying Dong, Yanping Liu, Ke Zhang, Xiankun Sun, Xianfan Li, Siwei Tianjin Univ Sci & Technol Tianjin 300457 Peoples R China State Grid Tianjin Informat & Telecommun Co Tianjin 300000 Peoples R China Beijing Fibrlink Commun Co Beijing 100070 Peoples R China

ISBN: (纸本)9789819756056;9789819756063

The network connection of the power cyber-physical system (PCPS) makes it easy to become a potential attack target, leading to serious consequences such as paralysis of the power system. The existence of class imbalance and noise in the PCPS network traffic dataset limits the intrusion detection accuracy. In response to the above difficulties, this article combines the denoising autoencoder and the CNN-Attention network to define the AE-CNA NIDS architecture. The BatchSwapNoise method DAE is used to denoise, compress and reconstruct features of the data, and extract local spatiotemporal features in theCNAblock formed by CNN and Attention. Multiple CNA blocks are stacked together to comprehensively learn the multi-layer spatiotemporal characteristics of network attack data. In addition, for the network intrusion dataset imbalance problem, equalization loss v2 (EQL v2) is used to balance the weight attention of the minority class. Experimental results show that AE-CNA performs well in terms of accuracy, precision, and recall value, with an accuracy rate of 98.3%, effectively improving intrusion detection performance and minority class detection rate.

关键词： Power cyber-physical systems Intrusion detection Denoising autoencoder Attention mechanism Abnormal traffic

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Deep Reinforcement Learning Based Economic Dispatch with Cost Constraint in Cyber Physical Energy System 18th

Deep Reinforcement Learning Based Economic Dispatch with Co...

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18th international conference on Wireless Artificial Intelligent computing Systems and applications, WASA 2024

作者： Chen, Xue Cui, Chen Wang, Ning Zhang, Zhaogong He, Jinghong Guan, Xin Heilongjiang University Harbin150080 China State Grid Heilongjiang Electric Power Company Limited Harbin150090 China

ISBN: (纸本)9783031714696

The integration of renewable energy sources and carbon capture system in cyber physical energy system is the basis for coping with the challenge of global warming. It is very important to give full play to the role of carbon capture equipment to maximize carbon emission reduction. First of all, we propose a joint dispatch model for wind power, energy storage, and thermal power units, which may minimize the operation costs of system. Then an optimal dispatch model for wind power, energy storage, carbon capture, and thermal power units is established. In this model, the optimal operation cost of the economic dispatch with no carbon capture equipment is considered as one of the constraints, and the optimization goal is to minimize the carbon emissions of the economic dispatch. Due to the fact that the dispatch problem can be defined as a Markov decision process, deep reinforcement learning model is employed to solve the optimal dispatch problem in cyber physical energy system. The experimental results indicate that the proposed scheduling model can effectively reduce operation costs and carbon emissions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Carbon capture and utilization

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Modeling, Analysis, and Design of 48/12V Digitally Controlled Non-Isolated DAB-Type Converters for Automotive and Data Center applications

Modeling, Analysis, and Design of 48/12V Digitally Controlle...

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2023 IEEE international conference on Power Electronics, Smart grid, and Renewable Energy, PESGRE 2023

作者： Majumder, Prantik Kapat, Santanu Kastha, Debaprasad Patel, Ayush Indian Institute of Technology Embedded Power Management Lab Department of Electrical Engineering West Bengal Kharagpur721302 India

ISBN: (纸本)9798350310573

In this paper, a discrete-time (DT) framework is proposed in a non-isolated DAB-type two-stage 48-to-12 V converter, which is useful for automotive and data center applications. Using the proposed framework, both DT large-signal and small-signal models are derived. Using SIMPLIS switch simulation, the accuracy of the large-signal DT models is validated at every sampling instants, including the behavior after large-step transients. The DT small-signal is used to analyze the closed-loop stability analysis under digital control. The digital voltage controller is designed using DT small-signal transfer functions. Simulation case studies are presented for a single-stage 24 V to 12 V converter. Further, a simulated load transient case study of the complete two-stage 48 V to 12 V, 48 W is shown to demonstrate a fast dynamic response. Closed-loop steady-state hardware results are presented for a 24 V to 12 V non-isolated DAB-type converter, which shows stable cycle-by-cycle behavior. © 2023 IEEE.

关键词： 48 V to 12 V DAB Digital control Discrete-Time Modeling Non-isolated Transformer-less

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Faster Algorithms for grid and Layered Drawings of Plane 3-Trees 17th

Faster Algorithms for Grid and Layered Drawings of Plane ...

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17th international conference on Combinatorial Optimization and applications, COCOA 2024

作者： Hossain, Ahmed Islam, Md. Hasanul Mondal, Debajyoti Rahman, Md. Saidur Dhaka Bangladesh Department of Computer Science University of Saskatchewan Saskatoon Canada

ISBN: (纸本)9789819644445

A grid drawing of a plane graph G is a planar drawing of G such that each vertex is mapped to an integer grid point and each edge is mapped to a straight line segment with the endpoints determined by its end vertices. The area of a grid drawing is the area of the smallest axis-aligned rectangle that encloses the drawing. A k-layer drawing of G is a planar drawing on a set L of k horizontal lines such that each vertex is mapped to a point on L and each edge is mapped to a straight line segment. A minimum area (minimum-layer) drawing of G is a straight-line grid (layered) drawing of G where the area (number of layers) is minimized. In this paper we examine the grid and layered drawing of a well-studied class of planar graphs called plane 3-tree. Given a n-vertex plane 3-tree, one can compute a straight line drawing with minimum number of layers or area in O(n5) and O(n9logn) time, respectively [Mondal et al., JGAA, 15(2), 2011]. Here we improve the running times to O(n3) and O(n7logn), respectively. We then give a fast approximation algorithm for computing minimum-layer drawings for a nontrivial subclass of plane 3-trees. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Drawing (graphics)

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Efficient Context-Aware Edge computing Algorithm in Mobile Cloud 3

Efficient Context-Aware Edge Computing Algorithm in Mobile C...

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3rd international conference on Computer Science and Management Technology, ICCSMT 2022

作者： Chang, Jian Yang, Muchuan Gong, Yan Liu, Jiayu Tian, Yuan Li, Qi State Grid Sichuan Information & Communicatioon Company Chengdu China

ISBN: (纸本)9798350320404

Edge computing provides a feasible technical solution to solve the problem of resource and energy supply constraints in terminal device deep learning applications. By migrating part of the deep learning application computing from the terminal to the cloud edge server, the computing pressure of the terminal device can be greatly relieved, and the energy consumption of the terminal can also be reduced to a certain extent. However, in the process of computing migration, the context switching loss of deep learning applications results in a long delay. This paper studies the problem of minimizing the completion time of deep learning applications under edge computing. We model the deep learning application as a task graph, and consider the constraints such as task switching delay, energy consumption and task dependency. Without changing the structure of the task graph, we transform it into a task scheduling-based application completion time minimization problem. In this paper, we first design a parallel scheduling algorithm based on greedy search. Considering the loss of context switching and the dependence of task data, we can allocate tasks to multiple processors for parallel processing by calculating the expected completion time of tasks, thus reducing the completion time of applications. Based on the experimental results, the greedy scheduling algorithm and comparison algorithm are analyzed and verified to optimize the completion time of different depth learning applications. © 2022 IEEE.

关键词： Energy utilization

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Identity Authentication Method of IoT Equipment Based on Alliance Chain 6th

Identity Authentication Method of IoT Equipment Based on All...

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6th international conference on Innovative computing, IC 2023

作者： Xiang, Zhongzheng Hu, Yanjun Chai, Xiaokang Zheng, Kai Shen, Xuemei State Grid Zhejiang Electric Power Co. Ltd. Hangzhou310007 China State Grid Zhejiang Electric Power Co. Ltd. Hangzhou Electric Power Company Hangzhou310001 China

ISBN: (纸本)9789819920914

IoT applications play an important role in today's society, where devices from different domains collaborate on the same task, and device authentication technologies are urgently needed to ensure the security of IoT applications. In addition, due to the wide distribution of IoT devices, complex application scenarios, and large differences in node performance, their identity authentication efficiency is low. The existing authentication methods have problems such as high key management overhead and reliance on trusted third parties. Therefore, an overall architecture of distributed storage for IoT device identity authentication is proposed. It mainly includes the distributed IoT device identity authentication mechanism and the detailed process of device registration consortium chain and consortium chain verification device. The performance analysis of the identity authentication method shows that the block creation time of different devices is less than 0.55 s, the IoT devices can join the alliance chain, and the identity authentication mechanism is real and effective. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Smart contract

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Three Phase Reduction of Inter Harmonic Analysis of PV-MPPT grid Connected Systems under Partial Shading Conditions

Three Phase Reduction of Inter Harmonic Analysis of PV-MPPT ...

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2022 international conference on Edge computing and applications, ICECAA 2022

作者： Ramkumar, M. Siva Sakthikumar, S. Amudha, A. Emayavaramban, G. Department of EEE Karpagam Academy of Higher Education India

ISBN: (数字)9781665482325

ISBN: (纸本)9781665482325

In Photovoltaic (PV) grid-connected systems, interharmonics represent a new power quality concern. Earlier research and field analysis have corroborated presence of interharmonic emission from PV connected inverters, with MPPT being amongst the main driving forces of interharmonics. In this sense, MPPT factors like sampling rate have a significant impact on PV system's interharmonic characteristic. While choosing sample rate of MPPT method, there is a trade-off among interharmonic emission and MPPT performance in general. Using a faster MPPT sample rate, for example, will enhance MPPT efficiency while also increasing interharmonic emission levels. To address the issue, this proposal proposes a new solution for interharmonics in PV systems. Because of frequency spectrum distribution, interharmonics in output current may be efficiently decreased. conversely, the suggested technique's MPPT performance can be maintained in the same way as when a fast MPPT sampling rate is used. suggested interharmonic mitigation's efficacy has been tested using a three-phase reduction on a PV- grid-connected system under partial shading condition. The research was carried out with the support of a MATLAB-SIMULINK system. © 2022 IEEE.

关键词： Harmonic analysis

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Research on the Rapid Realization of SM4 in CBC Mode 8th

Research on the Rapid Realization of SM4 in CBC Mode

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8th international conference on computing, Control and Industrial Engineering, CCIE 2024

作者： Lin, Xiuqing Jiang, Wenqian Li, Jinjin Chen, Jueyu Huang, Keying Measurement Center of Guangxi Power Grid Co. Ltd. Nanning China

ISBN: (纸本)9789819769339

The GSMA RSP standard defines a number of security mechanisms including secure communication assurance, data encryption and identity authentication. Profile encryption technology is the core algorithm of the RSP standard to ensure data confidentiality, and the symmetric encryption algorithm AES is used to encrypt data to ensure data confidentiality. The SM4 algorithm is a symmetric cryptographic technique developed by the Chinese National Cryptographic Administration and standardized as part of the State Encryption Standard in China. SM4 is widely adopted in various applications, including wireless communication systems and secure data transmissions. In this paper, a fast implementation method of SM4 in CBC mode is proposed to replace the RSP standard AES algorithm. We calculate the possible parallelization operations in CBC mode using the operational relationship between the SM4 algorithm round functions, and ensure the correctness of SM4 CBC encryption through a feedback compensation method. Which can effectively ensure the confidentiality of the SM2 eSIM platform. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Encryption algorithms

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Photovoltaic Power Forecasting in Dunhuang based on Recurrent Neural Network 23

Photovoltaic Power Forecasting in Dunhuang based on Recurren...

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23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Lv, Qingquan Ma, Ming Jiang, Xuetao Jiang, Meiyu Yong, Binbin Shen, Jun Zhou, Qingguo School of Information Science and Engineering Lanzhou University Lanzhou China State Grid Gansu Electric Power Research Institute Lanzhou China

ISBN: (纸本)9781665494571

Photovoltaic power generation is a new energy mode in modern smart city, and photovoltaic power forecasting plays an important role in the development and regulation of smart city, especially for emerging cities with very different geographical, meteorological and environmental factors. It is still a challenging subject to develop a high-precision photovoltaic power prediction system with little or even missing historical data. Recurrent neural network (RNN) is the mainstream time series forecasting model in deep learning, but it still has defects in the application scenario of photovoltaic power prediction, such as complex calculation, large sample demand and so on. Aiming at this situation, this paper studies the photovoltaic power forecasting method in the case of small samples, and the prediction effects of different RNN models are compared and analyzed. © 2021 IEEE.

关键词： Photovoltaic systems Recurrent neural networks Smart cities Computational modeling Time series analysis Predictive models Data models

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