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Anomaly Detection in Power Distribution Networks with Unsupervised Learning Algorithms

Anomaly Detection in Power Distribution Networks with Unsupe...

2024 International Conference on Innovative Computing, Intelligent Communication and Smart electrical Systems, ICSES 2024

作者： Sundaravelrani, K. Charles Prabu, V. Palle, Kowstubha Mallala, Balasubbareddy Nithya, G. Rao, Nynalasetti Kondala Kameswara Sathyabama Institute of Science and Technology Department of Information Technology Tamil Nadu Chennai600 119 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science & Engineering Tamil Nadu Chennai600062 India Chaitanya Bharathi Institute of Technology Department of Electrical and Electronics Engineering Telangana Hyderabad500075 India Bannari Amman Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu Sathyamangalam638401 India Sagi Rama Krishnam Raju Engineering Department Computer Science & Engineering Andhra Pradesh Bhimavaram534204 India

ISBN: (纸本)9798331543617

The identification of anomalies in power distribution networks is a critical component in ensuring the reliability and stability of energy systems. This investigation aims to find anomalous patterns and vulnerabilities within applications used for power grids by examining how unsupervised literacy algorithms function. Because conventional monitoring techniques typically miss subtle or developing irregularities, unsupervised procedures are especially helpful. This is a result of unsupervised routine monitoring techniques. We create algorithms that can learn from unlabeled data to identify departures from the standard geste. To create these models, some methods are applied, including insulating timbers, autoencoders, and k-means clustering. It is possible to test these methods using data from the global power distribution system and assess how well they relate to abnormalities such as equipment failures, power outages, and unexpected consumption patterns. The purpose of this examination is to ascertain the practicality of certain styles. Results show that algorithms for unsupervised literacy can provide rapid and accurate discovery, lower the danger of network failures, and increase the effectiveness of functional activities. Furthermore, these algorithms can increase the effectiveness of functional processes. The study's findings provide insight into the possibility of using machine literacy to improve the sustainability and adaptability of cutting-edge electricity distribution networks. © 2024 IEEE.

关键词： Power distribution networks

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Tutorial on laser-based visible light communications[Invited]

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Chinese Optics Letters 2024年第9期22卷 126-136页

作者： Yuqi Hou Yue Wang Zengxin Li Meixin Liu Shulan Yi Xiaoqian Wang Liang Xia Guangyi Liu Jianyang Shi Ziwei Li Junwen Zhang Nan Chi Tien Khee Ng Boon S.Ooi Chao Shen Key Laboratory for Information Science of Electromagnetic Waves Ministry of EducationSchool of Information Science and TechnologyFudan UniversityShanghai 200433China ZGC Institute of Ubiquitous-X Innovation and Applications Beijing 100876China Photonics Laboratory Electrical and Computer EngineeringDivision of ComputerElectrical and Mathematical Sciences and EngineeringKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia China Mobile Research Institute Beijing 100876China

Facing escalating demands for high-speed,large-bandwidth,and low-latency wireless data links,laser communication technology has emerged as a promising *** free-space optical communication conventionally utilizes nearinfrared light sources,there has been growing interest in exploring new spectral resources,including visible ***,laser-based white light has been demonstrated in visible light communication(VLC),with a unique capability to seamlessly integrate with illumination and display *** review summarizes the key devices and system technologies in semiconductor-laser-based white light for VLC-related *** recent advances and many emerging applications in the evolution of lighting,display,and communication are discussed.

关键词： visible light communication LiFi laser lighting GaN laser semiconductor laser

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Evolutionary Dynamic Optimization-Based Calibration Framework for Agent-Based Financial Market Simulators 13

Evolutionary Dynamic Optimization-Based Calibration Framewor...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Yang, Zhenhua Zhong, Muyao Yang, Peng Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Department of Statistics and Data Science Shenzhen518055 China

ISBN: (纸本)9798350308365

The agent-based financial market simulators serve as an important validation tool for trading strategies. For high-fidelity simulation, it is pivotal to calibrate the parameters of a simulator so that the generated simulation data resembles the observed real market data of interest. In traditional calibration methods, it is typical that the parameters of the simulator are set to be time-invariant. However, the dynamic nature of the real financial market introduces various variability into the behaviors of the market participants over different time intervals, posing in-herent limitations to the traditional methods. A more reasonable approach might involve employing a simulator with time-variant parameters. This suggests that the model parameters can be dynamically adjusted at different stages of the simulation to adapt to the evolving market. Consequently, the calibration problem of the financial market simulators can be treated as a dynamic optimization problem. To dynamically calibrate the simulators, we introduce an Evolutionary Dynamic Optimization (EDO) framework. By monitoring the changes of the best fitness, the whole simulation time interval is adaptively divided into multiple stages. Then the Negatively Correlated Search (NCS) algorithm is employed to effectively adjust the parameters at different simulation stages to better simulate the real financial market. Empirical results on both synthetic and real data verify that our dynamic calibration framework significantly outperforms traditional calibration methods that fixing a parameter for the whole simulation interval. The proposed strategy of detecting dynamic changes is also shown to be more reliable than the naive method of manually segmenting stages. In terms of calibration time, our proposed method significantly improves by nearly 93% compared to the fixed parameter setting, and approximately 61% compared to manual segmentation calibration. © 2024 IEEE.

关键词： Financial markets

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CRISP - DM Process in Smart Building Management 11

CRISP - DM Process in Smart Building Management

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11th International Conference on electrical and Electronics engineering, ICEEE 2024

作者： Dursun, Mahir Sabyrzhan, Moldir Gazi University Faculty of Technology Dept. of Electrical and Electronics Engineering Ankara Turkey Graduate School of Informatics Gazi University Department of Computer Science Ankara Turkey

ISBN: (纸本)9798350362541

Smart Buildings are buildings that integrate and combine intelligence, management, control, materials, and construction as a single system to meet all the needs of the building, such as comfort, energy efficiency, and durability. In universities, laboratories are used less frequently than other facilities and classrooms. Courses and students may change in the same classroom, and the period of use of such classrooms is much more extended than in laboratories. However, classrooms may only be used for classes during long breaks or for short periods of non-use between exams. In addition, there is no provision for when the heating system will start to heat up before classes or when it will be turned off after classes. By planning heating and lightning, energy and costs will be saved. This paper presents data acquisition methods for preparing a dataset to create a machine learning (ML) model to save energy loss in university laboratories. The developed model will predict energy consumption in classrooms and laboratories based on weather conditions. The study is being conducted in two stages. The first stage describes how to collect data using electronic devices such as Internet of Things (IoT) controllers of Smart Building Management Systems. The second stage gave possibilities for data analysis and preparation using the phases of the Cross-Industry Standard Process for Data Mining (CRISP-DM). © 2024 IEEE.

关键词： Information management

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DLMetaChain: An IoT Data Lake Architecture Based on the Blockchain 13

DLMetaChain: An IoT Data Lake Architecture Based on the Bloc...

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13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022

作者： Pingos, Michalis Christodoulou, Panayiotis Andreou, Andreas Cyprus University of Technology Computer Engineering and Informatics Department of Electrical Engineering Limassol Cyprus Neapolis University Department of Computer Science Pafos Cyprus

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

Nowadays, the IoT ecosystem is evolving rapidly, with multiple heterogeneous sources producing high volumes of data and processes transforming this data into meaningful or 'smart' information. These volumes of data, including IoT data, need to be stored in repositories that can host raw, unprocessed, relational and non-relational types of data, such as Data Lakes. Due to the weakness of metadata management, security & access control is one of the main challenges of Big Data storage architectures as Data Lakes can be replaced without oversight of the contents. Recently, the Blockchain technology has been introduced as an effective solution to build trust between different entities, where trust is either nonexistent or unproven, and to address security and privacy concerns. In this paper we introduce DLMetaChain, an extended Data Lake metadata mechanism that consists of data from heterogeneous data sources which interact with IoT data. The extended mechanism mainly focuses on developing an architecture to ensure that the data in the Data Lake is not modified or altered by taking into advantage the capabilities of the Blockchain. © 2022 IEEE.

关键词： Smart contract

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A hybrid channel transmission method for effective spectrum access in cognitive radio networks

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International Journal of Ad Hoc and Ubiquitous Computing 2023年第4期44卷 221-232页

作者： Dhurandher, Sanjay Kumar Kumar, Bhoopendra Woungang, Isaac Chao, Han-Chieh Department of Information Technology Netaji Subhas University of Technology New Delhi India National Institute of Electronics and Information Technology Delhi Centre New Delhi India CAITFS Division of Information Technology Netaji Subhas Institute of Technology University of Delhi Delhi India KIET Group of Institutions Delhi-NCR Ghaziabad India Department of Computer Science Ryerson University TorontoON Canada Department of Electrical Engineering National Dong Hwa University Hualien Taiwan Department of Computer Science and Information Engineering National Ilan University I-Lan Taiwan Institute of Computer Science and Innovation UCSI University Kuala Lumpur Malaysia

Cognitive radio is considered as a very influencing technique and has the great potential to solve the problem of shortage of the radio spectrum. A secondary user also called as a cognitive user may access the primary channel(s) with a certain restrictions in a cognitive radio network. Spectrum sensing is a very important activity during the process of spectrum access. This paper proposes a Markov chain-based proactive hybrid spectrum access method for maximising the radio spectrum usage by optimising the channel sensing process and establishing the channel switching conditions. Using the OMNeT++ simulator, the proposed method (proactive hybrid access) is compared against that of the conventional (reactive hybrid access), overlay, and underlay access methods, showing its superiority by about 20% in terms of performance improvement with respect to throughput, service delay, and PU detection probability. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Cognitive radio

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Water Quality Prediction Using Random Forest Algorithm 2

Water Quality Prediction Using Random Forest Algorithm

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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Jude, P.Sebastian Vindro Brighty, S.Prince Sahaya Gandhi, R.Rubia Balamurguan, K. Krishnakumar, R. Sri Ramakrishna Engineering College Electrical and Electroinces Engineering Tamilnadu Coimbatore India Sri Ramakrishna Engineering College Department of Computer Science and Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9798350308846

Water is an essential requirement for every living thing in the globe. The massive growth of technology helps to attain water purity and quality for the betterment of people. Because of industries, chemical wastes mingle with water resources by contaminating water and land. People who drink the contaminated water suffer from waterborne diseases like cholera, Diarrhea, typhoid, etc. Water scarcity has been rapidly increasing with the increase in population and pollution. Nearly two lakh people are dying in India due to water scarcity and waterborne diseases. So we came forward to solve a complex problem regarding water. This article suggests a machine learning-based method for determining the purity of water. This method uses a collection of water quality variables, including pH, turbidity, conductivity, and temperature, to train a model using a classification algorithm. The model's accuracy in determining the purity of the water is next assessed using a new set of data. The outcomes show how effective the suggested method is at assessing the purity of the water. Consequently, this method is a reliable and efficient tool for determining the purity of water, which can significantly lower the danger of water pollution. Monitoring water quality to regulate it, safeguard public health, and save the environment is crucial. With the support of various machine learning classifiers and related stacking ensemble models, the WQI was primarily used to categorize the WQ data. Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), Decision Tree (DT), and Naive Bayes are a few of the classifiers that were used. In total, 3996 samples collected during nine years were included in the dataset used for the study, along with supporting data. © 2023 IEEE.

关键词： Classification Data mining Decision Tree Machine Learning SVM Water Quality Index (WQI)

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Enhancing the Prediction of Underwater Wireless Communication using Machine Learning Techniques and Related Issues

Enhancing the Prediction of Underwater Wireless Communicatio...

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2023 International Conference on Data science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Saravanan, M.S. Naveen, V. Kumar, S.Selvin Pradeep Dilli Ganesh, V. Sivashankar, S. Bhaskar, K. Vijaya Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamilnadu Chennai India Madanapalle Institute of Technology & Science Department of Computer Science & Technology Madanapalle India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Electrical and Communication Engineering Tamilnadu Chennai India Saveetha School of Engineering Chennai India Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Computer Science Engineering Tamilnadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350348910

This research aims to enhance the prediction of underwater wireless communication for underwater wireless sensor networks using Logistic Regression compared with Linear Regression Algorithms. To forecast the functionality of underwater wireless sensor networks Linear Regression and Novel Logistic Regression algorithms were used with different training and testing splits with Underwater Acoustic Wireless Sensor. A sample size of 20 (Each 10 from Group 1 and Group 2) is calculated by fixing a G-power of 0.8, alpha and beta values of 0.05 and 0.2, and a confidence interval of 95%. With a statistical significance value of 0.001 (p © 2023 IEEE.

关键词： Wireless sensor networks

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Secure Communication Protocols for Enhancing Privacy in 5G Mobile Networks 13

Secure Communication Protocols for Enhancing Privacy in 5G M...

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13th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2024

作者： Pillai, Sanjaikanth E Vadakkethil Somanathan Vaddadi, Srinivas A School of Electrical Engineering and Computer Science University of North Dakota Grand Forks United States University of the Cumberlands Department of Information Technology WilliamsburgKY United States

ISBN: (纸本)9798350305463

The 5G mobile network is innovative in providing low-latency conversation services. However, this new era brings massive issues around privacy and safety. With the boom in linked and Internet of Things (IoT) gadgets, the danger of touchy information being accessed through unauthorized activities will increase. Cozy communication protocols are essential to decorating privacy in 5G mobile networks. The protocols use advanced encryption and authentication techniques to protect records transmitted over the net. Further, they deploy at-ease channels among devices to prevent interception and manipulation of the use of malicious actors. One of the number one protocols for securing conversation in 5G networks is the 5G Authentication and Key settlement. This protocol employs mutual authentication and a significant era of the equipment and the network, ensuring that the handiest prison devices can accurately enter the network and that the transmitted records are encrypted and protected. © 2024 IEEE.

关键词： Wireless networks

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Coverage Enhancement Using UAVs for Cognitive Marine Network

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IEEE Access 2025年 13卷 95548-95562页

作者： Waqas Mustafa Huma Ghafoor Insoo Koo School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad Pakistan Department of Electrical Electronic and Computer Engineering University of Ulsan Ulsan South Korea

Like terrestrial communications, marine users also need stable network paths between any source and destination pair. Besides the rough sea surface, another issue in this network is the communication range. Marine users in deep sea are distant from the base stations (BS) onshore, resulting in fragile links. To solve this problem, the literature has suggested the use of multiple relay nodes to stabilize the network. But more relays need more bandwidth to establish a stable link between any two communicating nodes. However, the dedicated spectrum for marine communications has been found to be scarce due to the increase in number of users and their service demands. Therefore, we propose a cognitive routing scheme in marine environments, which uses unmanned aerial vehicles (UAVs) as mobile BS and/or relays to handle the above-mentioned issues. Preferring a satellite-free network for marine users, we opt for UAVs to enhance the communication range. Because spectrum is a precious resource, we apply spectrum sensing technique to address spectrum scarcity by keeping primary user activity undisturbed. Finally, we ensure an optimal path for the cognitive marine environment that exhibits a high packet delivery ratio, less delay and overhead, and prove it by comparing our scheme to various reference schemes.

关键词： Routing Relays Sensors Routing protocols Marine vehicles Sea surface Autonomous aerial vehicles High frequency Energy efficiency Edge computing

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