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Designing and Simulating a Smart Water Harvesting System Using PLC Techniques

Designing and Simulating a Smart Water Harvesting System Usi...

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2023 International Conference on Innovation and Intelligence for informatics, Computing, and Technologies, 3ICT 2023

作者： Thabet, Hassaan Th. H. Al-Hilali, Aqeel A. Qasim, Haitham B. Thabit, Thabit H. Mahmood, Firas M. Al-Hadba University College Techniques Engineering Dept. of Medical Instruments Mosul Iraq Al-Farahidi University Dept. of Medical Instruments Engineering Techniques Baghdad Iraq Al-Esraa University College Dept. of Computer Science Baghdad Iraq Ninevah University Dept. of Computer Engineering and Information Mosul Iraq Cihan University-Erbil Dept. of Informatics and Software Engineering Iraq

ISBN: (纸本)9798350307771

The presence of water in human life is crucial, and God has blessed humans much with its availability. This paper tries to reduce the amount of water that people use for washing in all aspects of daily life and instead utilize it to irrigate gardens and maintain hygienic facilities. The importance of water as a fundamental ingredient and the range of social and age groups that regularly take advantage of the washing process made it an ideal location for water waste during the washing process. This is why the authors choose this region to conduct their research. The monitoring and management of water usage during the washing process are simulated using PLC techniques. © 2023 IEEE.

关键词： Washing

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Deep Learning for Channel Prediction in Non-Stationary Wireless Fading Environments

Deep Learning for Channel Prediction in Non-Stationary Wirel...

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2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Data Science and Quantum Computing ABV Indian Institute of Information Technology and Management Gwalior India

ISBN: (纸本)9798350379525

In non-stationary wireless fading channels deep learning models are effective in predicting channel states as indicated by this study. This work compared the LSTM and GRU models with autoregressive methods or Kalman filter, implying that deep learning is indeed able to capture temporal dependence between variables and was likely more adapted than linear method when dealing with many changes in dynamics. From the perspective of pre-processing data, keys like attention mechanism and transfer learning were decisive elements in helping them to improve prediction scores and make models more robust. These results showed that these enhanced procedures allow the models to generalise over a wide range of non-stationary situations, generating consistent performance in various diverse environments. This study indicates the promise of deep learning for enhancing wireless network operation, which could lead to greater self-awareness and utilization features in emerging future-generation wireless systems. © 2024 IEEE.

关键词： Prediction models

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Deep Learning-Based Decision Prediction in Turkish Legal Texts 11

Deep Learning-Based Decision Prediction in Turkish Legal Tex...

引用

11th International Conference on Electrical and electronics engineering, ICEEE 2024

作者： Solmaz, Seher Dursun, Mahir Graduate School Of Informatics Gazi University Dept of Information Systems Ankara Turkey Gazi University Faculty of Technology Dept. of Electrical and Electronics Engineering Ankara Turkey

ISBN: (纸本)9798350362541

Since text recognition studies in the literature are generally carried out in English, tokenization processes of Turkish legal texts in the Ural-Altaic language family cannot be used much. In this study, we tokenize Turkish legal texts and perform decision prediction using a deep learning Convolutional Neural Network (CNN) model. Artificial intelligence (AI), which is developing at a rapid pace, has become applicable to almost all fields of study and has started to be used effectively. Developments in AI have affected the field of law as well as other fields of study. The use and spread of AI in the field of law has increased significantly in recent years. One of the most important factors in this increase is that there is a huge amount of data in the field of law. It has become a need to analyze this data and transform it into meaningful and usable information. This paper aims to make decision prediction using artificial intelligence in judicial applications. In the study, using CNN, a neural network-based deep learning model, decision prediction was made with the data published by the Ombudsman's Office on the institution's website, which is free from publicly accessible personal data. The model was trained on the applicant information and the type of decision in the decision text. An F1 score of 0.63 was achieved for decision prediction. © 2024 IEEE.

关键词： Convolutional neural networks

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A Simple Approach to Analyze and Evaluate Image Segmentation Methods Based on Image Quality Metrics 3

A Simple Approach to Analyze and Evaluate Image Segmentation...

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3rd IEEE International Conference on Applied Electromagnetics, Signal Processing, and Communication, AESPC 2023

作者： Ganesan, P. Ravichandran, M. Joseph, L.M.I. Leo Sathish, B.S. Prasad, M. Raiendra Sajiv, G. Vidya Jyothi Institute of Technology Dept. of Electronics and Communication Engineering Hyderabad India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept. of Computer Science Engineering Chennai India Sr University Dept. of Electronics and Communication Engineering Telangana Warangal India Sri Venkateshwara College of Engineering Dept. of Computer Science Engineering Ai Bengaluru India Saveetha School of Engineering Simats Chennai India

ISBN: (纸本)9798350358742

The role of image segmentation is inevitable in image analysis. There are many algorithms and methods for image segmentation. However it is tricky to choose best possible clustering procedure. The proper selection of clustering method leads to the successful outcome in image analysis. In segmentation process, data is fragmented into some reasonable regions (clusters). Elements (image pixels) in a particular cluster should be very analogous w.r.t some attributes like lightness, texture or color. In the proposed method, test image is clustered based on chrominance (color) using four segmentation methods, viz., FCM, PCM, PFCM and MFCM. The outcome of segmentation methods are transformed into binary image using otsu threshold method. The binary image of FCM is taken as a reference image because it is standard and fundamental one. The binary images of other methods are compared with reference image. The comparison is done using some image quality metrics such as dice, jaccard. The optimal segmentation method is decided based on the analysis of these image quality metrics. © 2023 IEEE.

关键词： Binary images

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Real-time Monitoring Using AWS Cloud Platform For Agriculture Soil 1

Real-time Monitoring Using AWS Cloud Platform For Agricultur...

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1st IEEE International Symposium on Consumer Technology, ISCT 2024

作者： Tirtakusuma, Danar Ikram Sukaridhoto, Sritrusta Nourma Budiarti, Rizqi Putri Mulyo, Dwi Alfarezi, Fitratama Aminputra, Bima Briliandhika Hakim, Oktafian Sultan Politeknik Elektronika Negeri Surabaya Dept. of Creative Multimedia Technology Indonesia Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Indonesia Universitas Nahdlatul Ulama Surabaya Indonesia

ISBN: (纸本)9798350365191

In the era of modern agriculture, real-time monitoring of soil conditions is crucial for increasing productivity and efficiency. This research proposes an agricultural soil monitoring system that utilizes the AWS Cloud platform to capture, analyze, and present real-time soil data. This system is designed to integrate various sensors that can measure humidity, pH, temperature and soil nutrients, all connected via the Internet of Things (IoT). The data collected by these sensors is sent to the AWS Cloud, where it is processed using cloud computing services such as AWS Lambda and Amazon EC2. The use of the AWS Cloud enables high scalability, reliability, and data security, and facilitates big data analysis using Amazon S3 and Amazon RDS. By using an intuitive dashboard, farmers can see soil analysis results in real-time and make informed decisions based on the data. Additionally, this system is equipped with machine learning algorithms that run on the AWS Cloud to predict soil needs and provide optimal fertilizer recommendations. This research shows how implementing AWS Cloud in agriculture can bring digital transformation to agriculture, enabling farmers to increase crop yields while reducing waste and operational costs. © 2024 IEEE.

关键词： Cloud platforms

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Delta-γ Modeling of Wireless System Resilience in Multipath Fading and Interference Environments 7

Delta-γ Modeling of Wireless System Resilience in Multipath...

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7th International Conference on Contemporary Computing and informatics, IC3I 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Sharma, Kunj Bihari Gupta, Mridul Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Madhav Institute of Technology & Science Deemed University Centre for Internet of Things Gwalior India

ISBN: (纸本)9798350350067

In this paper, we pursue the resilience of wireless communication systems in multipath fading and interference environments utilizing Delta- γ modelling. Furthermore, fading phenomena such as Rayleigh/Rician/Nakagami channels can be simulated to examine the impact on important performance metrics like SNR, BER and throughput. Different types of interference scenarios, covering co-channel and adjacent channel interferences are also studied to understand impact on system capacity as well as reliability. This article investigates the use of adaptive modulation techniques, multiple-input multiple-output (MIMO) strategies and advanced interference management schemes by extensive *** results illustrate the importance of adaptive strategies in overcoming fading and interference which leads to an increase in system resilience as well as a robust communication link. Metrics for the outage probability and mean time to failure (MTTF) can inform how reliable systems are across operational scenarios. This work reconciles theory with practice to provide a systematic way of controlling the operational parameters in wireless networks under varying conditions. These lessons will be crucial in steering the design of forthcoming wireless systems that must more reliably satisfy a broader set of application requirements. © 2024 IEEE.

关键词： Multipath fading

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Optimal Resource Allocation in Dynamic Fading Channels via Meta-Learning Techniques 2

Optimal Resource Allocation in Dynamic Fading Channels via M...

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2nd IEEE International Conference on Advancements and Key Challenges in Green Energy and Computing, AKGEC 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Madhav Institute of Technology & Science Deemed University Centre for Internet of Things Gwalior India

ISBN: (纸本)9798350390179

In this paper, we address the optimally dynamical resource allocation problem for fading channels utilizing meta-learning methods with an application to improve efficiency and performance in wireless communication systems. Extensive experiments are conducted and our meta-learning model has demonstrated the ability to adapt itself dynamically in various channel conditions, leading to improvement of Signal-to-Noise Ratio (SNR), reduction of Bit Error Rate (BER) and enhancement on throughput when compared with traditional methods. Visualizations like performance analysis comparisons, heatmaps or 3D plots are used to show how the model can be leverage as effectively manager of resources where they are and when they suit best. The performance improvements demonstrated here are statistically significant testifying for the scalability of our work. The findings of this study demonstrate the major benefits that can be achieved by meta-learning to overcome immanent issues in fast-changing wireless conditions and its potential to propel future communication technologies forward. © 2024 IEEE.

关键词： Contrastive Learning

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Computational Overhead Analysis for Mitigation of Content Poisoning Attack in NDN-based IoT Body Area Networks 3

Computational Overhead Analysis for Mitigation of Content Po...

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3rd International Conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

作者： Priya, M. Castro, S. Kumar, Sathesh K. Kalaivani, N. Dept. of Computer Science and Engineering E. G. S. Pillay Engineering College Nagapattinam611002 India Dept. of Information Technology Karpagam College of Engineering Coimbatore641032 India Dept. of Electronics and Communication Engineering Vivekanandha College of Engineering for Women Tiruchengode637205 India Dept. of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Coimbatore641041 India

The Body Sensors Network has developed into a significant element of the Medical IoT. Massive data gathering from a resource-constrained network represents a laborious procedure in IoT equipped BSN/WBAN, creating a number of difficult problems. Conventional communication protocols may be used on IoT platforms without any alterations and provide impractical techniques for large-scale networks. The new architecture known as ICN has the potential to overcome these difficulties in huge data collection. According to this perspective, the proposed work indicates a CPA mitigation strategy for information centric WBANs. © 2023 Elsevier B.V.. All rights reserved.

关键词： Internet of things

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Dynamic Resource Allocation and Security Strategies in Cooperative Relaying Systems with Eavesdropping Threats 27

Dynamic Resource Allocation and Security Strategies in Coope...

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27th International Symposium on Wireless Personal Multimedia Communications, WPMC 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Upadhyay, Abhay Gupta, Mridul Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Deemed University Centre for Internet of Things Madhav Institute of Technology and Science Gwalior India

ISBN: (纸本)9798350392319

The dynamic resource allocation and security strategies for cooperative relaying systems proposed here provide significant performance improvements along with robust security features over traditional methods. The method improves throughput, energy efficiency and secrecy capacity by dynamically provisioning resources according to real-time network conditions in conjunction with its interference-suppression techniques such adaptive beamforming and artificial noise. The system is quite good at preventing eavesdropping, and it has such high signal-to-noise ratios that there is a very low error rate. The use case results show that the integrated framework optimizes resource consumption while mitigating security threats, thereby offering a trade-off between existing solutions thus solving some of their shortcomings. Our work demonstrates the opportunity for efficient and secure communication in dynamic environments. © 2024 IEEE.

关键词： Energy efficiency

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An Effectual Methodology to Objective Quality Assessment for Noisy and Compressed Images Using Full and Blind Reference Quality Metrics 3

An Effectual Methodology to Objective Quality Assessment for...

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3rd IEEE International Conference on Applied Electromagnetics, Signal Processing, and Communication, AESPC 2023

作者： Ravichandran, M. Alexander, T. Jerry Sathish, B.S. Joseph, L.M.I. Leo Ganesan, P. Sajiv, G. Vel Tech Rangarajan Dr. Sagunthala R &d Institute of Science and Technology Dept. of Computer Science Engineering Chennai India Swarnandhra College of Engineering and Technology Dept. of Ece AP Narsapur India Sri Venkateshwara College of Engineering Dept. of Computer Science Engineering Ai Bengaluru India Sr University Dept. of Electronics and Communication Engineering Telangana Warangal India Vidya Jyothi Institute of Technology Dept. of Electronics and Communication Engineering Hyderabad India Saveetha School of Engineering Simats Chennai India

ISBN: (纸本)9798350358742

The proposed work elucidates the role of metrics to decide the superiority of noisy and compressed images. The metrics approximate the superiority of degraded image (noisy or compressed) with or without the reference images. The computed numerical value based on this comparison finalizes the excellence of the image under test. The degradation in any stage of image processing (acquisition, transmission and reception) deteriorates the eminence of an image. It is challenging to understand the source and reason for low quality of the image. The suggested work analyzes the quality of salt and pepper noisy image and compressed image using blind and complete reference metrics. The analysis using full reference metrics is an unpretentious process. However, they do not related to human perception. In contrast, blind quality metrics demonstrated its hegemony in this facet. © 2023 IEEE.

关键词： Salt and pepper noise

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