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On-Demand Recharge Scheduling Algorithm in Wireless Sensor Networks

On-Demand Recharge Scheduling Algorithm in Wireless Sensor N...

引用

2022 International Conference on Electronic Systems and Intelligent Computing, ICESIC 2022

作者： Dande, Bhargavi Chang, Chih-Yung Su, Ming-Yang Fan, Cheng-De Tamkang University Dept. of Computer Science and Information Engineering New Taipei City Taiwan Ming Chuan University Dept. of Computer Science and Information Engineering Taoyuan Taiwan

ISBN: (纸本)9781665483858

In recent years, energy transfer technology provides a new opportunity for recharging the sensors using the mobile charger. Most of the studies proposed recharging algorithms using a single charger but overlooked the consideration of multiple chargers and cooperation between them. Therefore, this paper proposed an On-Demand Recharge Scheduling (ODRS) algorithm for multiple mobile chargers, aiming to improve the network surveillance quality (NSQ). In this paper, the network is partitioned into many subregions. One mobile charger is employed in each subregion to recharge the sensors based on the benefit of coverage quality (BCQ) obtained. In addition, there is cooperation between neighboring mobile chargers. Experiments are evaluated to show the achieved NSQ of the proposed ODRS algorithm. © 2022 IEEE.

关键词： Wireless sensor networks

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Malaria Detection Using Neural Network

Malaria Detection Using Neural Network

引用

2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Kavitha, P. Manimala, G. Sanchana, R. Anushree, U. Rmk Engineering College Department of Computer Science and Engineering India Sri Sairam Engineering College Department of Computer Science and Engineering India Sri Sairam Institute of Technology Dept. of Information Technology India

ISBN: (纸本)9798350394580

Malaria is a serious and occasionally fatal disease brought on by a parasite that frequently infects a particular species of mosquito that feeds on people. Malaria frequently results in severe illness in its victims, including high temperatures, chills that make you shiver, and flu-like symptoms. The four different forms of malaria parasites that infect humans are most likely to result in serious infections and, if untreated, death. Malaria can be devastating, but symptoms and deaths from malaria are typically preventable. Deep Learning models, or to be extra unique,ConvolutionalNeuralNetworks(CNN)modelsarepr oposedonthistaskAcomparisonoftheproposed and contemporary algorithms exhibits that the accuracy of malaria disorder classificationprimarily based on CNN's is higher than other algorithms. If the CNN approach is supported by the addition of more feature extraction techniques and accurately classifying malaria disease in the image, it is projected that the achievement of the acquired results will increase. © 2023 IEEE.

关键词： Cnn deeplearning malariadisease TensorFlow

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Investigating the Impact of Heuristic Algorithms on Cyberthreat Detection 2

Investigating the Impact of Heuristic Algorithms on Cyberthr...

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2nd International Conference on Advances in Computation, Communication and information Technology, ICAICCIT 2024

作者： Kalla, Dinesh Mohammed, Abdul Sajid Boddapati, Venkata Nagesh Jiwani, Nasmin Kiruthiga, T. Dept. of Computer Science Colorado Technical University CharlotteNC United States Dept of School of Computer and Information Sciences University of the Cumberlands Kentucky United States Dept. of Computer Science Microsoft CharlotteNC United States Dept. of Information Technology University of The Cumberlands WilliamsburgKY United States Department of ECE Vetri Vinayaha College of Engineering and Technology Tamil Nadu Trichy India

ISBN: (纸本)9798331541217

This paper investigates the effect of heuristic algorithms on cybersecurity hazard detection and mitigation. To be able to do so, the authors analyze the performance of two heuristics-based algorithms-the simple Heuristic set of rules (SHA) and greedy Heuristic set of rules (GHA)-on 4 distinct datasets. The datasets contain malicious and non-malicious packets. Effects of the experiments show that each algorithms exhibit extraordinarily correct predictions of malicious packets while as compared to the floor-reality labels, and showcase an excessive level of detection accuracy in detecting threats. The SHA set of rules tested the strongest performance, achieving an accuracy of as much as 95 and ninety-seven percentage on datasets. The authors further take a look at that once both algorithms are utilized in aggregate, the overall performance progressed. The research findings may be generalized in further contexts and assist the notion that heuristics algorithms may be effective in threat detection and mitigation. © 2024 IEEE.

关键词： Cybersecurity

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A Sentiment Analysis Study of Twitter Users' Reactions to the COVID-19 Vaccine 14

A Sentiment Analysis Study of Twitter Users' Reactions to th...

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14th International Conference on information and Communication Systems, ICICS 2023

作者： Alkhushayni, Suboh Alomari, Zakaria Al-Zaleq, Du'a Yarmouk University Faculty of Information Technology and Computer Science Dept. Information Systems Irbid Jordan New York Institute of Technology Dept. Computer Science VancouverBC Canada Al-Ahliyya Amman University Dept. Robotics and Artificial Intelligence Engineering Amman Jordan

ISBN: (纸本)9798350307870

This study investigates public attitudes towards the COVID-19 vaccine through Twitter data analysis. Using the Twitter API, tweets were collected, preprocessed, and labeled. Features were extracted using the Bag of Words representation, and sentiment analysis was conducted using Text Blob and Vader. Machine learning and deep learning models were trained and tested, revealing that deep learning models achieved the highest accuracy and F1 score. The research underscores the efficacy of machine learning and deep learning in analyzing COVID-19 vaccine-related tweets, shedding light on factors influencing vaccine resistance. These insights are crucial for pharmaceutical companies and public health officials, enabling them to address barriers to vaccine acceptance and enhance the societal benefits of widespread vaccination, contributing to the pandemic's resolution. © 2023 IEEE.

关键词： COVID-19

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High-Speed Secure Vanity Address Generator for User Convenience in Blockchain Networks 5

High-Speed Secure Vanity Address Generator for User Convenie...

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5th International Conference on Blockchain Computing and Applications, BCCA 2023

作者： Islam, Md. Mainul Islam, Md. Kamrul Hammoudeh, Mohammad Texas A&M University Dept. of Computer Science and Engineering College Station United States Shahjalal University of Science and Technology Dept. of Electrical and Electronic Engineering Sylhet Bangladesh King Fahd University of Petroleum and Minerals Dept. of Information and Computer Science Dhahran Saudi Arabia

ISBN: (纸本)9798350339239

Generating a vanity address (VA) for user convenience in blockchain networks is a memoryless brute-force exercise that involves testing millions of probable private keys. It requires a high-speed processor to compute millions of public keys and corresponding addresses in a short time. In this paper, we propose a novel split-key-multiplicative online VA generator for crypto wallet that provides faster VA generation compared with the existing vanity pools. The proposed approach is capable of improving the speed (in keys per second) of conventional VA generation by 2-7 times without reconfiguring the processor. We also propose a high-speed offline VA generator that offers blockchain users the ability to create a VA with a random vanity word using a low-performance processor without reliance on a vanity pool. To the best of our knowledge, this is the first research paper on VA generation in blockchain networks. © 2023 IEEE.

关键词： Blockchain

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Power Quality Problems that Occur at a Company Producing Electrical Equipment

Power Quality Problems that Occur at a Company Producing Ele...

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2023 Power Quality and Electromagnetic Compatibility at Low-Frequency, PQEMC-LF 2023

作者： Nicolae, Petre-Marian Nicolae, Ileana-Diana Nicolae, Marian-Stefan University of Craiova Electrical Engineering Energetic and Aeronautics Dept. Craiova Romania University of Craiova Computer Science and Information Technology Dept. Craiova Romania

ISBN: (纸本)9798350341331

The paper presents the problems that arise when supplying a company producing electrical equipment from the electricity network. The distorting regimes that appear affect the operation of the electric power network, inducing new problems of functional nature. For their study, the authors designed and implemented a data acquisition system in order to acquire, record and transmit data on electrical quantities (three-phase voltages and currents) from the secondary winding of the transformer that supplies the company. Data were transferred to a PC running original software developed by authors, implementing analysis modules based on Fast Fourier Transform and Wavelet Packet Transform. Small differences were revealed between power quality indices computed with both methods. The performed analysis revealed significant distortions of the currents absorbed by the analyzed plant. The total current harmonic distortion and weights of the 5-th harmonic exceeded the limits stated by IEEE Std 519-2022 whilst the value of the power factor was lower than the neutral value, being associated to additional consumptions of power / reactive energy, with effect on the penalties to be paid by the company. © 2023 IEEE.

关键词： Fast Fourier transforms

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Advancing Low Resource Natural Language Processing: Techniques, Applications, and Future Directions 2

Advancing Low Resource Natural Language Processing: Techniqu...

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2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Middha, Parth Agarwal, Harshit Rajput, Vaibhav Thakur, Ayush Singh, Sofia Saraswat, Shipra Amity University Dept. of Computer Science & Engineering Noida India Amity Institute of Information Technology Amity University Noida India Amity University Dept. of Artificial Intelligence Noida India

ISBN: (纸本)9798331519056

This paper explores the development and application of low resource Natural Language Processing (NLP) modules, addressing the challenges of processing underrepresented languages and domains with limited linguistic resources. It discusses key methodologies such as transfer learning, unsupervised and semi-supervised learning, and data augmentation techniques that enable effective NLP in resource-constrained environments. The paper presents case studies in machine translation, named entity recognition, and sentiment analysis, demonstrating the practical impact of these approaches. Additionally, it outlines persistent challenges in the field and proposes future research directions, emphasizing the importance of enhancing data acces-sibility, model robustness, computational efficiency, and ethical considerations in advancing low resource NLP. © 2024 IEEE.

关键词： Self-supervised learning

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Computing and Analysing PQ Indices for a Consumer with Various Sources of Harmonics and Non-symmetries

Computing and Analysing PQ Indices for a Consumer with Vario...

引用

2023 Power Quality and Electromagnetic Compatibility at Low-Frequency, PQEMC-LF 2023

作者： Nicolae, Ileana - Diana Nicolae, Petre - Marian Cirstea, Daniel-Nicolae University of Craiova Computer Science and Information Technology Dept. Craiova Romania University of Craiova Electrical Engineering Energetic and Aeronautics Dept. Craiova Romania

ISBN: (纸本)9798350341331

The paper presents a detailed analysis of certain operating regimes that appear for a consumer with various sources of harmonics and non-symmetries. The analyzed waveforms were acquired with a portable dedicated data acquisition system and transferred to a laptop for processing with Fast Fourier Transform (FFT) and Wavelet Packed Transform (WPT). Small differences (FFT vs WPT) were noticed between the computed values of the power quality indices, due to the non-sinusoidal and sometimes non-symmetric nature of the studied regimes and discrete nature of the processed data respectively. The FFT analysis revealed significant non-symmetrical regimes, as great weights for harmonic orders multiple of 3 were found in the three-phase currents waveforms. Reversed flow of active and reactive powers were noticed. A comparative study of the energies produced by current harmonics was made and discussed. A non-symmetry of the consumer as a whole was detected as well. © 2023 IEEE.

关键词： Fast Fourier transforms

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About Measurement System in Stations and Substations using Original Data Acquisition Systems

About Measurement System in Stations and Substations using O...

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2023 Power Quality and Electromagnetic Compatibility at Low-Frequency, PQEMC-LF 2023

作者： Nicolae, Ileana-Diana Nicolae, Petre n Marian Nicolae, Marian-Stefan University of Craiova Computer Science and Information Technology Dept. Craiova Romania University of Craiova Electrical Engineering Energetic and Aeronautics Dept. Craiova Romania

ISBN: (纸本)9798350341331

The paper deals with a method and measurement system designed for the simultaneous monitoring and recording of time variations of electric quantities with no inter-correlation requirements. The method and measurement system were obtained by realizing a multi-unit data acquisition system (MUDAS), relying on at most 3 independent data acquisition systems which operate jointly, in a synchronous way, by means of a synchronizer. Because each of the individual data acquisition system can acquire data for at most 8 electrical quantities (4 voltages and 4 currents), the maximum total number of electrical quantities to be monitored, acquired, and transferred simultaneously to a central control unit is equal to 24. The sampling rate allows for the determination of power quality parameters according to existing standards. MUDAS can also be used in a structure with only 2 individual data acquisition system, in order to simultaneously acquire and display at most 16 electrical quantities. Two examples of utilization of MUDAS are presented. © 2023 IEEE.

关键词： Data acquisition

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Energy Efficient Coverage Optimization in Mobile Wireless Sensor Network Using Grey Wolf Algorithm 14

Energy Efficient Coverage Optimization in Mobile Wireless Se...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Gupta, Ankit Mamatha, K.M. Kiran, M. National Institute of Technology Karnataka Dept. of Information Technology Surathkal India Viseveshvaraya Technological University Dept. of Computer Science and Engineering Belgaum India

ISBN: (纸本)9798350335095

The issue of decreased coverage rate in Mobile Wireless Sensor Networks (MWSNs), caused by mobile sensor nodes being randomly placed inside a monitoring area. Additionally, it becomes extremely important to utilise a sensor node's energy very effectively due to the finite energy of sensor nodes. Hence, to provide optimised positions for the sensor nodes while using the energy of sensor nodes adept.y authors propose an energy efficient coverage algorithm. Initially, article focus on optimal placement of the sensor nodes within a area to achieve the maximum coverage and later authors have focused on improvising the network lifetime. Article presents a combination of Grey Wolf Optimization and Virtual Force algorithm for optimization of coverage in MWSN. Further, to improve the network lifetime, a GWO-based clustering algorithm is presented using distance and energy as a parameter. The algorithms are implemented and simulated on Matlab. The efficiency of the presented algorithm is observed comparing with other Swarm Intelligence (SI) based optimization algorithms, like GWO, VFA, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Ant-lion Optimization (ALO) and the results of the GWO-based clustering is compared with the traditional LEACH algorithm and energy-balanced clustering based on PSO. Simulation results demonstrate that the presented algorithms outperform the considered algorithms. © 2023 IEEE.

关键词： Sensor nodes

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