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2023 International conference on Intelligent systems, Communications, and Computer networks, ISCCN 2023

作者： Lei Dai, Ji Yu Zhang, Qiu Yan Ou, Jia Xiang Deng, Yue Dan Zhou, Honbo Pan, Rong Zhen Electric Power Research Institute Guizhou Power Grid Co. Ltd Guiyang China GuiZhou UbiLink Co Ltd Guiyang China Beijing Kyland Co. Ltd Beijing China

ISBN: (纸本)9781510666238

Some of the traditional power distribution network fault location, isolation, and service restoration (FLISR) tasks were conducted with feeder automation (FA), which is part of the distribution automation (DA) system. Existing FA scheme have issues such as long fault processing time, due to centralized decision making. In this paper, a FLISR scheme for distribution network based on edge computing and 5G is proposed. Three key technologies of the scheme are introduced: Edge computing servers with local terminal units (LTU);FLISR algorithms with software-defined control and edge-cloud collaboration;5G integrated with edge computing (MEC). The proposed scheme is the first case with integrated 5G and MEC in DA applications, which can effectively shorten the fault processing time as evidenced by the deployed system s performance. © 2023 SPIE. All rights reserved.

关键词： Electric power distribution

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An Overview on Security and Privacy of Data in IoMT Devices: performance Metrics, Merits, Demerits, and Challenges 19

An Overview on Security and Privacy of Data in IoMT Devices:...

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19th International conference on Wearable Micro and Nano Technologies for Personalized Health (pHealth)

作者： Khatiwada, Pankaj Yang, Bian Norwegian Univ Sci & Technol Dept Informat Secur & Commun Technol Gjovik Norway

ISBN: (纸本)9781643683485;9781643683492

The internet of Medical Things (IoMT) emerges with new trendsetter device applications, where it defines the incorporation of medical devices with the internet of Things (IoT). The healthcare sector continues to encounter challenging obstacles that have an impact on the quality of treatment provided to patients. To get rid of this problem, IoMT is being deployed to achieve the high reliability and efficiency of the health system. The IoMT devices are superimposed with clinical information as they contain the details of patient health data, address, and other patient identifiers. By containing such amount of sensitive information, it becomes cumbersome to preserve data privacy and security. Due to inadequate security and privacy precautions, patient health data is susceptible to leakage, which has a direct impact on the patient's life. In addition, the majority of medical devices are susceptible to cyberattacks, putting patient information at risk. Inadequate control of life-support equipment can have a devastating effect on patient outcomes. Thus, this survey intends to review the various security models of IoMT devices using standard techniques to support health care systems. It provides a wide range of literature reviews regarding IoMT systems and compares them with traditional methodologies. This review work exhibits the motivation for current technologies to maintain the security and privacy of patients' data with IoMT devices. The systematic review entails background on security in IoMT devices, techniques for security, usage of diverse validation measures, and also discusses the problems and motivation for future research work.

关键词： internet of Medical Things Security and Privacy of Data Encryption Blockchain Authentication performance metrics

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An internet of Things (IoT) Based Block Chain Technology to Enhance the quality of Supply Chain Management (SCM)

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MATHEMATICAL PROBLEMS IN ENGINEERING 2022年第1期2022卷

作者： Rizwan, Ali Karras, Dimitrios A. Kumar, Jitendra Sanchez-Chero, Manuel Taboada, Marlon Martin Mogollon Altamirano, Gilder Cieza King Abdulaziz Univ Fac Engn Dept Ind Engn Jeddah 21589 Saudi Arabia Univ Athens NKUA Sch Sci Natl & Kapodistrian 34400 Athens Greece GLA Univ Dept Elect & Commun Engn Mathura Utter Pradesh India Univ Nacl Frontera Fac Ingn Ind Alimentarias & Biotecnol Sullana Peru Univ Nacl Frontera Fac Ciencias Empresariales & Ambientales Sullana Peru Univ Nacl Autonoma Chota Cajamarca Peru

Recent technological developments indicate possible advancements in supply chain management (SCM). These innovations have attracted a lot of interest from industries including logistics, manufacturing, packaging, and transportation. The conventional systems, however, use centralised servers to control all operations, including the exchange of raw materials, making orders, dealing with buyers and sellers, and updating orders. The network's supply chain may thus be insecure as a result of every activity being routed via centralised servers. The danger is additionally increased by a number of difficulties, including scalability, data integrity, security, and availability. Block chain technology may be used in these circumstances to decentralise transaction processing and eliminate the need for a centralised controller. In this approach, the performance of the resource-constrained supply chain network is improved by the effective use of edge computing and priority data access. The Intelligent K-Means (IKM) clustering algorithm is suggested across the edge nodes in the current research to categorise the priority level of each piece of data. This classifier determines if the edge node has received data that is high priority or low priority. Low priority data is recorded in the log files for future data analysis. Then, to allow safe data flow in the open block chain while excluding outside parties, the High Priority Access based Smart Contract (HPASC) technique is deployed. The whole experiment was conducted in a Python environment, and variables including scalability, reaction time, throughput, and accuracy were studied. Current systems' constrained block sizes and fork creation lengthen the time transactions must wait before being processed. The suggested methodology is quicker and uses less storage space than current block chain systems. The results show that the suggested approach works better than current blockchain technology to raise the standard of supply chain man

关键词： Supply chain management

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3D-O-RAN: Dynamic Data Driven Open Radio Access network systems

3D-O-RAN: Dynamic Data Driven Open Radio Access Network Syst...

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IEEE Military Communications conference (MILCOM)

作者： Restuccia, Francesco Blasch, Erik Ashdown, Andrew Ashdown, Jonathan Turck, Kurt Northeastern Univ Inst Wireless Internet Things Boston MA 02115 USA Air Force Off Sci Res Arlington VA USA Air Force Res Lab Arlington VA USA

ISBN: (纸本)9781665485340

This position paper introduces a Dynamic Data Driven Open Radio Access network System (3D-O-RAN). The key objective of 3D-O-RAN is to support congested, contested and contaminated tactical settings where multimedia sensors, application constraints and operating wireless conditions may frequently change over space, time and frequency. 3D-O-RAN is compliant with the O-RAN specification for beyond 5G cellular systems to reduce costs and guarantee interoperability among vendors. Moreover, 3D-O-RAN integrates computational, sensing, and cellular networking components in a highly-dynamic, feedbackbased, data-driven control loop. Specifically, 3D-O-RAN is designed to incorporate heterogeneous data into the network control loop to achieve a system-wide optimal operating point. Moreover, 3D-O-RAN steers the multimedia sensor measurement process in real time according to the required application needs and current physical and/or environmental constraints. 3D-O-RAN uses (i) a semantic slicing engine, which takes into account the semantic of the application to optimally compress the multimedia stream without losing in classification accuracy;(ii) a dynamic data driven neural network certification system that translates mission-level constraints into technical-level constraints on neural network latency/accuracy, and occupation of hardware/software resources. Realistic use-case scenarios of 3D-O-RAN in a tactical context demonstrate system performance.

关键词： Semantics

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Design and modeling PV converter with hysteresis control 8

Design and modeling PV converter with hysteresis control

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8th IEEE International conference on Energy Smart systems, ESS 2022

作者： Denysiuk, Serhii Bielokha, Halyna Derevianko, Denys Vadym, Bronytskyi Igor Sikorsky Kyiv Polytechnic Institute Power Supply Department Kyiv Ukraine Igor Sikorsky Kyiv Polytechnic Institute Department of Geoengineering Kyiv Ukraine

ISBN: (数字)9798350334418

ISBN: (纸本)9798350399202

Solar energy is one of the most widely used renewable energy sources. A power converter is required to match the parameters of PV modules and the load (network). The article features a PV converter with a hysteresis control system, which consists of a boost converter and inverter. The inverter generates a sinusoidal current in the load (network) according to power quality standards. Digital simulation was carried out for two cases, namely: at variable temperature (constant irradiance) and at variable irradiance (constant temperature). In all operating modes, the power consumption was maximum and the output current was sinusoidal. There was developed a control system with hysteresis controllers, which made it possible to ensure high performance, accuracy, electromagnetic compatibility of the output current of the inverter with the network. THD was less than 5% within the entire range of studies. Inverter circuits, which were connected to a four-wire network, provided better current quality results than three-wire ones. This is due to the fact that there is phase interference in three-wire networks. In both cases, efficiency was almost the same and depended on the power of the PV modules. © 2022 IEEE.

关键词： Wire

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Sliding Mode-Based Load Frequency control of a Power System with Multi-Source Power Generation

Sliding Mode-Based Load Frequency Control of a Power System ...

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2023 International conference on System Science and Engineering, ICSSE 2023

作者： Tran, Phong Thanh Huynh, Van Van Dong, Chau Thien Si Dinh, Bach Hoang Ton Duc Thang University Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical & Electronics Engineering Ho Chi Minh City Viet Nam International University- Vnuhcmc Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350322941

The chattering phenomena of high-frequency switching make it challenging to perform sliding-mode control (SMC) for load frequency control of power networks. Actuators utilized in power systems are highly vulnerable to this chattering issue in SMC. In this study, a load frequency controller based on decentralized SMC is developed for multi-area multi-source interconnected power systems (MMIPS) with matching uncertainties. To enhance the dynamic performance of the system in achieving intervals, the proportional and integral switching surface is built for each region. In addition to guaranteeing the resilience of the multi-area multi-source power network, the suggested second order sliding mode control (SOSMC) legislation avoids chattering phenomena in control input. The reaching law approach suggests the robust controller to ensure that, following a load and operation point modification, frequency fluctuation converges to zero. Additionally, the simulation report shows that the suggested controller maintains the quality requirement by dealing with operating conditions in a wider range, rejecting disturbance, lowering the transient response of frequency, and removing the overshoot issue. To demonstrate the effectiveness of the suggested decentralized SMC approach, a two-area multi-area multi-source linked power system is explored. The result of the MATLAB/SIMULINK simulation is presented, and its findings are contrasted with recently developed traditional control systems. © 2023 IEEE.

关键词： Sliding mode control

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Automated Alzheimer's Disease Diagnosis Using Convolutional Neural networks and Magnetic Resonance Imaging 11

Automated Alzheimer's Disease Diagnosis Using Convolutional ...

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11th IEEE International conference on systems and control, ICSC 2023

作者： Mohammed, Asmaa Nasr Albagul, Abdulgani Ahmad, Moamer Musbah College of Electronic Technology Dept. Control Engineering Bani Walid Libya Libyan Center for Engineering Research and Information Technology Bani Walid Libya University of Baniwalid Faculty of Engineering Bani Walid Libya

ISBN: (纸本)9798350304886

Alzheimer's disease is a debilitating neurological condition impacting millions globally. Therefore, an accurate diagnosis plays a major role in treating or managing it effectively. Convolutional neural networks (CNNs), popular deep learning algorithms applied to image processing tasks, offer such an opportunity in this study where a CNN model for classifying Alzheimer's patients was proposed. The research yielded impressive results: recall and precision scores as high as 0.9958 which indicate trustworthy identification of true positives while maintaining few false positives;test accuracy exceeding 99% confirming desirable generalization capabilities from the training dataset to live scenarios;ROC AUC score at an astronomical height of 0.9999 signifying great potential in distinguishing between afflicted individuals from their non-affected counterparts accurately. The proposed network achieved a good classification accuracy. Comparing the proposed model alongside two state of the art models VGG19 and ResNet50 resulted in superior performance for the proposed model demonstrating CNNs can increase diagnostic precision and effectiveness of Alzheimer's disease, leading to early detection, enhanced treatment plans, and enriching the quality of life for those affected. © 2023 IEEE.

关键词： Convolutional neural networks

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Exploiting Hybrid Medium Access control and Relaying Strategies to Overcome Duty-Cycle Limitations in LoRa-Based Sensor networks

Exploiting Hybrid Medium Access Control and Relaying Strateg...

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IEEE International Instrumentation and Measurement Technology conference (I2MTC) - Rising Above Covid-19

作者： Fedullo, Tommaso Mahmood, Aamir Tramarin, Federico Morato, Alberto Gidlund, Mikael Rovati, Luigi Univ Padua Dept Management & Engn Padua Italy Mid Sweden Univ Dept Comp & Elect Engn S-85170 Sundsvall Sweden Univ Modena & Reggio Emilia Dept Engn Enzo Ferrari Modena Italy CNR IEIIT Natl Res Council Italy Via Gradenigo 6-B Padua Italy

ISBN: (纸本)9781665453837

The industrial internet-of-things (IIoT) paradigm is reshaping the way industrial measurement systems are designed. Industrial systems require collecting accurate and timely measurements from the field using smart sensor networks distributed in wide production areas. In this context, wireless connectivity of sensors acquires undeniable importance, and in turn, opens significant research challenges. Therefore, the research community is actively analyzing the suitability of different wireless technologies, for instance, Wi-Fi, 5G-and-beyond, and low-power wide area networks (LPWANs), toward their possible industrial applications and optimizing them to realize high-performance and accurate smart measurement systems. In this paper, we focus on long range (LoRa)-based LPWANs (i.e., LoRaWAN), especially to overcome the duty cycle (DC) limitations of the adopted ALOHA-based medium access control (MAC) strategy in the industrial, scientific, and medical (ISM) bands. The ISM bands are subjected to an hourly constraint on the number of packet transmissions or inter-message delay, where the devices using higher spreading factors (SFs) can quickly consume the available transmission time. In this paper, we propose and assess the hybrid MAC designs in a LoRa network by combining carrier sense multiple access (CSMA) with ALOHA in two different ways i) exploiting different channel plans for the access mechanisms, ii) relay-assisted access, with devices using small SFs assisting neighboring higher-SF devices with listen-before-talk (LBT) mechanism. Our simulation results reveal that the proposed access strategies lead to a higher packet delivery rate (PDR) as well as lower mean and standard deviation of the communication delay;thus, increasing the overall measurement accuracy.

关键词： ALOHA CSMA Duty cycle limitations Factory Automation ISM bands LoRa LPWANs

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Enhanced Dependency-Based Feature Selection to Improve Anomaly network Intrusion Detection 1

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18th International conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Bennaceur, K. Sahraoui, Z. Nacer, M. A. Ecole Mil Polytech Dept Comp Sci Algiers Algeria Univ Sci & Technol Houari Boumedienne Dept Comp Sci Algiers Algeria

ISBN: (数字)9783031083334

ISBN: (纸本)9783031083334;9783031083327

In daily live, online computer systems are becoming more pervasive and integrated. However, the access to the internet can produce significant issues like cyber-attacks. The network intrusion detection system (NIDS) is a promising security solution that is used to detect attacks. It recently used Deep Learning in the detection process to obtain high performance. The performance of an NIDS depends on the used training dataset and the quality of features, where irrelevant features may decrease the detection performance, oppositely to relevant ones that are able to improve it. Feature selection is a good solution to select only relevant features to participate in the detection process. Chi-square is a supervised feature selection method that select only the most dependent features of the class feature. In this work, an Enhanced Chi-square (EChi2) method is proposed to select and weight features considering its degree of relevance. Experiments results, using the well-known NSLKDD dataset, shows that the proposed method outperforms the Chi-square.

关键词： Feature selection Chi-square Enhanced Chi-square Anomaly network intrusion detection

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Real-Time Communication over LoRa networks 7

Real-Time Communication over LoRa Networks

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7th ACM/IEEE conference on internet-of-Things Design and Implementation (IoTDI)

作者： Fahmida, Sezana Modekurthy, Venkata Prashant Ismail, Dali Jain, Aakriti Saifullah, Abusayeed Wayne State Univ Detroit MI 48202 USA Univ Nevada Las Vegas NV 89154 USA Southern Illinois Univ Edwardsville IL USA Iowa State Univ Ames IA USA

ISBN: (纸本)9781665496414

Today, industrial internet of Things (IIoT) are emerging in large-scale and wide-area applications (e.g., oilfield management). Traditional wireless solutions for industrial automation depend on short-range wireless technologies (WirelessHART, ISA100.11a), posing a big challenge to support the scale of today's IIoT. To address this limitation, we propose to adopt LoRa, a prominent low-power wide-area network technology, for industrial automation. Adopting LoRa for industrial automation poses some unique challenges. The fundamental building blocks of any industrial automation system are feedback control loops that largely rely on real-time communication. LoRa usually adopts a simple protocol based on ALOHA with no collision avoidance to minimize energy consumption which is less suitable for real-time communication. Existing real-time protocols for short-range technologies cannot be applied to a LoRa network due to its unique characteristics such as asymmetry between downlink and the uplink spectrum, predefined modes (class) of operation, and concurrent reception through orthogonal spreading factors. In this paper, we address these challenges and propose RTPL- a Real-Time communication Protocol for LoRa networks. RTPL is a low-overhead and conflict-free communication protocol allowing autonomous real-time communication of low-energy devices and exploits LoRa's capability of parallel communication. We implement our approach on LoRa devices and evaluate through both physical experiments and large scale simulations. All results show that RTPL achieves on average 75% improvement in real-time performance without sacrificing throughput or energy compared to traditional LoRa.

关键词： LoRa Low Power Wide Area networks Real-Time Industrial internet-of-Things Closed Loop internet-of-Things Cyber Physical systems

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