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Solar Conference (MENA-SC), Middle East and North Africa

作者： Fahad Alam Nazek El-Atab Electrical and Computer Engineering Computer Electrical Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

The current work demonstrates 3D printing of transparent sheets embedded with zinc oxide (ZnO) nanoparticles for the encapsulation of solar panels for protection and thermal management. Thin transparent sheets were prepared via a vat-photopolymerization-based 3D printing technique. The optimized sheet showed >90% transparency with a UV ray preventing capability from the range of 200–400 nm. Due to blocking of UV rays from the solar spectrum, reduction in around ~8°C in the temperature from the surface of the solar panel was observed when the solar panel coated with ZnO embedded resin was exposed to sunlight for 30 min as compared to the surface temperature from the reference panel with resin coating only. The demonstrated sheet would thus be promising as an encapsulant and in assisting in the thermal management of the solar panel.

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Knowledge Graph Completion Based on Graph Attention Networks and Text Information 5

Knowledge Graph Completion Based on Graph Attention Networks...

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5th IEEE International Conference on computer and Communication engineering technology, CCET 2022

作者： Hong, Shengyi Qian, Heng Gao, Yongchao Lyu, Hongli Qilu University of Technology School of Computer Science and Technology Jinan China Shandong Computer Science Center National Supercomputing Center in Jinan Jinan China Lakehead University Department of Electrical and Computer Engineering Thunder Bay Canada

ISBN: (数字)9781665467353

ISBN: (纸本)9781665467353

In knowledge graphs (KGs), there exist some unsolved problems such as incomplete data, hidden information with incomplete mining and so on. In the most completion models, the information of the triples in the KG is generally utilized, but the neighborhood information and rich entity description information are not included in the triples. In this paper, the knowledge graph completion (KGC) method is improved based on graph attention networks (GATs) with text information by using the neighborhood information of aggregated triples and entity description information. And the embedding capability of semantic information is enhanced in KGs. First, the feature vector of entity description information is extracted by the Bi-LSTM model and concatenated with the entity embedding in the triples. Then the joint vectors are trained by GATs to aggregate the neighborhood information. Next, the KGC task is realized by a decoder. Finally, the effectiveness of the proposed method is verified by the link prediction experiments in the public datasets FB15K-237 and WNISRR and comparison is investigated with several other existing methods. The test results show that most of the indicators in the two datasets are improved. Furthermore, it is proved that the model combined with multi-source information has better representation ability for entities, which can further improve the accuracy and comprehensive performance of KGC tasks. © 2022 IEEE.

关键词： Knowledge graph

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Analysis of Water Quality in Cauvery River by Using PCA with Various Classifications Technique

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Procedia computer science 2025年 258卷 1391-1403页

作者： Karpagalakshmi R C Prabhu Selvam Sakthivel S Kalaivanan K Rajesh Sharma R Akey Sungheetha Sheila Mahapatra Department of Computer Science and Engineering Alliance University Bangalore-India School of Computing SRM Institute of Science and Technology Tiruchirappalli India Department of Electrical and Electronics Engineering Alliance University Bangalore-India

Water quality assessment is a complex endeavour that involves identifying pollutants in water resources. The importance of this process lies in its objective to evaluate water quality for human use. Machines and deep learning algorithms play a vital role in this evaluation. In this context, feature selection methods were employed to identify critical factors that ensure optimal accuracy. Subsequently, these selected features were used as input for various classifiers for classification purposes. The Cauvery River dataset, obtained from the Tamil Nadu Pollution Control Board, was utilized to assess the performance of the proposed approach. This research was implemented using Python as the programming language. The performance of the PCA-RF model was evaluated using various metrics, including an accuracy of 0.96, precision of 0.97, recall of 0.94, and an F1-score of 0.95. The results demonstrate that the PCA-RF model outperforms conventional machine learning approaches, achieving a high R-squared score of 0.95.

关键词： Water quality Prediction Machine Learning SVM DT RF

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An IoT-Oriented Gesture Recognition System Based on ResNet-Mediapipe Hybrid Model 5

An IoT-Oriented Gesture Recognition System Based on ResNet-M...

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5th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2022

作者： Huang, Zhuo Li, Jian Liang, Jiye Zen, Baizhi Tan, Jiani University of South China School of Electrical Engineering China Shanxi University School of Computer Science and Technology Shanxi China

ISBN: (数字)9781665499163

ISBN: (纸本)9781665499163

In this paper, we propose the ResNet-Mediapipe hybrid model and a new Internet of things (IoT) control system in order to implement gesture control of IoT devices. In the process of designing the ResNet-Mediapipe workflow, we improve the ResNet-50 and integrate it with Mediapipe to improve recognition speed and accuracy. Besides, we also create a brand-new gesture dataset with more than 5700 pictures, which is richer than other open-source gesture datasets. Experiments show that ResNet-Mediapipe can capture hand position in a variety of situations and recognize gestures in real-time with an accuracy rate of over 98.5% and recognition speed up to 45 fps, which is more accurate and faster than other gesture recognition methods. The new gesture-controlled IoT system we propose is equipped with hardware that includes Raspberry Pi, STM32F103, ESP8266, EG200U, and various IoT devices. This system can realize gesture recognition based on ResNet-Mediapipe and control numerous IoT devices. Besides, we design a human-computer interface for the system on the Ali IoT cloud platform and a set of gestures used for human-computer interaction, which enable the users to monitor IoT devices' information on the Web page and choose different IoT devices to control. The experiment proves that this project provides a precise and convenient way for people to interact with gestures. © 2022 IEEE.

关键词： Internet of things

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Mechanically Reconfigurable Terahertz Quasi-Optical Components for Spectral Filtering and Polarization Control

Mechanically Reconfigurable Terahertz Quasi-Optical Componen...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Quader, Sakib Lv, Xiaojing You, Xiaolong Ako, Rajour T. Bhaskaran, Madhu Sriram, Sharath Fumeaux, Christophe Withayachumnankul, Withawat Terahertz Engineering Laboratory The University of Adelaide Adelaide Australia School of Mechanical and Mechatronic Engineering University of Technology Sydney Sydney Australia Functional Materials and Microsystems Research Group RMIT University Melbourne Australia School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia

ISBN: (纸本)9798350379693

Terahertz technologies present unique opportunities for high throughput communications, short-distance high-resolution radar, and spectral sensing/imaging. This spectral range presents some interesting challenges in terms of tunability of transmissive quasi-optical components for spectral filtering or polarization control. The concept of multi-layer periodic structures with sub-wavelength elements, such as frequency-selective surfaces or metasurfaces, allows to create terahertz optical components with unique properties. In this context, this paper reviews three distinctive realizations of such multilayer transmissive devices with reconfigurable properties. The controlled dynamic adaptation of transmission properties is achieved through mechanical reconfiguration based on relative translation or rotation of layers. These presented devices are illustrative of three efficient implementations based on different physical mechanisms, with application for tunable spectral filtering and dynamic polarization control. © 2024 IEEE.

关键词： Terahertz waves

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Sunflower Disease Identification using Deep Learning: A data-driven approach 26

Sunflower Disease Identification using Deep Learning: A data...

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26th International Conference on computer and Information technology, ICCIT 2023

作者： Sohel, Amir Alam Sarker, Md. Murshidul Das, Utpal Chandra Das, Pranajit Kumar Siddiquee, Shah Md Tanvir Haider Noori, Sheak Rashed Thien Le, Ngoc Daffodil International University Computer Science and Engineering Dhaka1216 Bangladesh Chulalongkorn University Ctr. of Excellence in Artif. Intell. Mach. Lrng. and Smart Grid Technology Electrical Engineering Bangkok10330 Thailand Sylhet Agricultural University Computer Science and Engineering Sylhet3100 Bangladesh

ISBN: (纸本)9798350359015

The sunflower (Helianthus annuus) is considered to possess a low to moderate susceptibility to drought conditions. However, production has reduced as a result of some of its illnesses. Therefore, it is necessary to take steps to identify the diseases of plants earlier. Disease identification is a time-consuming process that cannot be achieved simultaneously. In this study we have proposed a novel strategy utilizing deep learning techniques to precisely detect and classify three distinct diseases affecting sunflower leaves, as well as molds, based on image analysis. A collection of 466 images depicting four distinct types, namely Gray mold, downy mildew, leaf scars, and healthy leaves, were gathered from sunflower leaves and molds found in the agricultural fields of Bangladesh. The dataset undergoes several images preprocessing techniques, including rescaling, augmentation, histogram equalization, contrast stretching, gamma correction, Gaussian noise, and Gaussian filtering. Subsequently, feature extraction methodologies are employed for figuring out the underlying cause of infection in a picture. Four separate evaluation metrics have been implemented in order to assess the performance of each classifier. We have employed a total of five deep-learning methodologies named as InceptionV3, VGG19, MobileNetV2, ResNet152V2, DenseNet201. Among the models taken into consideration, DenseNet201 had the most optimal performance, with a notable accuracy rate of 98.7%. © 2023 IEEE.

关键词： deep learning DenseNet201 Recognition Sunflower Diseases

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Enhanced Optimization-based Node Localization Scheme for WSN 8

Enhanced Optimization-based Node Localization Scheme for WSN

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8th International Conference on Communication and Electronics Systems, ICCES 2023

作者： Senthil Murugan, M. Ravindranath, P.V. Jayareka, K.S. Sundareswaran, T. Singh, Charanjeet Subbaiyan, Arunmurugan St.Joseph's Institute of Technology Omr Electrical and Electronics Chennai119 India School of Computer Studies Coimbatore Sulur641402 India Sona College of Technology Department of Computer Science and Engineering Salem India Rmk College of Engineering and Technology Physics Chennai India Deenbandhu Chhotu Ram University of Science and Technology Electronics and Communication Department Murthal India Periyar Maniammai Institute of Science and Technology Ece Tamilnadu Thanjavur India

ISBN: (纸本)9798350396638

The location of a sensor node is crucial for several uses of WSN, including environmental sensing, search and rescue, geographical routing and tracking, and so on. The accuracy with which individual sensor terminals in a wireless sensor system can be located has a substantial bearing on the network's overall effectiveness. Using information about the locations of anchor nodes gathered from a variety of measures to pinpoint the unknown target nodes' placements is known as localization. This is a problem classed as NP-hard, which means it cannot be solved using classical deterministic methods. To overcome this difficulty in wireless sensor networks, presented an enhanced version of a swarm intelligence technique called the whale optimization method. This implementation, using a quasi-reflected-based learning method, fixes the problems with the original whale optimization approach. In order to ensure that the proposed metaheuristic performs as well as existing state-of-the-art metaheuristics, it is evaluated using the same network architecture and experimental settings. Proposed method use a Gaussian-modified RSSI to achieve a more accurate reading of the range and a new whale optimization algorithm to optimize the positioning of the nodes to boost the positioning accuracy, both of which are designed to compensate for the shortcomings of the positioning algorithm of both Received signal strength indicator (RSSI) ranging model. Based on the results of 20 separate benchmark function tests, the upgraded whale algorithm outperforms the whale optimization method and other swarm intelligence systems. The suggested location algorithm provides more precise placement than the original RSSI method. It is mentioned that the cluster intelligence algorithm has significant benefits over the currently implemented RSSI in positioning WSN nodes, and the improved algorithm that is described in this work has even more benefits compared to various cluster intelligence methods in tends to

关键词： Swarm intelligence

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Optimal Utilization of the Electric Vehicle in a Various Market Approach 5

Optimal Utilization of the Electric Vehicle in a Various Mar...

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5th IEEE International Conference on Smart Systems and Technologies, SST 2022

作者： Mišljenović, Nemanja Knežević, Goran Žnidarec, Matej Dubravac, Marina Josip Juraj Strossmayer University of Osijek Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

In order to reduce greenhouse gases, it is necessary to transit to renewable energy sources and electric vehicles. The electricity consumer becomes a prosumer by installing a distributed generation from renewable energy sources or providing ancillary services to the system. The prosumer can buy energy from the grid when needed and sell the excess energy to the grid. However, current market conditions encourage prosumers to maximize self-consumption because the price when buying electricity is significantly higher than the price of selling electricity to the grid. This paper proposes and compares two market models for end customers with their own electricity generation currently applied in Croatia. The first model consists of electricity generation, an electric vehicle, and stationary battery storage. The second model features electricity generation and an electric vehicle, and the grid operates similarly to energy storage. The research is aimed at reducing investment and operating costs. The results show that savings can be achieved without additional investment in energy storage to increase flexibility depending on the chosen market model. © 2022 IEEE.

关键词： Investments

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Nonlinear wave-spin interactions in nitrogen-vacancy centers

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Physical Review Applied 2024年第4期21卷 044057-044057页

作者： Zhongqiang Hu Qiuyuan Wang Chung-Tao Chou Justin T. Hou Zhiping He Luqiao Liu Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA

Nonlinear phenomena represent one of the central topics in the study of wave-matter interactions and constitute the key blocks for various applications in optical communication, computing, sensing, and imaging. In this work, we show that by employing the interactions between microwave photons and electron spins of nitrogen-vacancy (N-V) centers, one can realize a variety of nonlinear effects, ranging from the resonance at the sum or difference frequency of two or more waves to electromagnetically induced transparency from the interference between spin transitions. We further verify the phase coherence through two-photon Rabi-oscillation measurements. The highly sensitive optically detected N-V–center dynamics not only provides a platform for studying magnetically induced nonlinearities but also promises novel functionalities in quantum control and quantum sensing.

关键词： Coherent control Electromagnetically induced transparency Magneto-optics Nonlinear optics Quantum sensing Nitrogen vacancy centers in diamond Microwave techniques Optically detected magnetic resonance

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Comprehensive analysis for assessing the renewable energy integration on a research ship vessel in India

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International Journal of Ambient Energy 2024年第1期45卷

作者： Roselyn, J. Preetha Ravi, Anirudhh Baran, Mesut E. Muthukaruppan, Valliappan Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Chennai India Electrical and Computer Engineering Department NC State University RaleighNC United States

Using onboard renewable energy resources, marine fuel consumption can be optimised to yield emission reduction and fuel cost savings. This paper proposes a methodology for accurate assessment of integrating PV and energy storage to a marine Indian TARA research vessel. This Indian vessel has only diesel generation and batteries to meet propeller demands, lighting and communication loads. In this paper, the net system is estimated with solar PV for minimising carbon emissions. The installation of solar PV in maximum available space in research vessel is estimated considering the panel dimensions and actual demand profile of vessel is analysed for integrating solar PV and battery systems. A novel method is adopted for estimating annual vessel-demand and PV-power generation. Using demand and generation data, the onboard fuel consumption is optimised using PV and battery by an optimal dispatch scheme that includes a Minimum Generator Operation with N-1 safety constraint. The fuel savings after integration of solar PV and battery in vessel are analysed, and net present value and cost to emission savings after renewable energy integration are studied considering real-time load profile and vessel movement. Finally, based on optimal dispatch results, factors that affect fuel savings are examined and overall investigation findings are summarised. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Economic analysis

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