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Modelling and Performance Analysis of Visible Light communication System in Industrial Implementations

computers, Materials & Continua 2023年第11期77卷 2189-2204页

作者： Mohammed S.M.Gismalla Asrul I.Azmi Mohd R.Salim Farabi Iqbal Mohammad F.L.Abdullah Mosab Hamdan Muzaffar Hamzah Abu Sahmah M.Supa’at Faculty of Electrical Engineering Faculty of EngineeringUniversiti TeknologiMalaysiaSkudai81310Malaysia Lightwave Communications Research Group(LCRG) Faculty of Electrical EngineeringUniversiti TeknologiSkudaiJohorMalaysia Department of Communication Engineering Faculty of Electrical and Electronic EngineeringUniversiti Tun Hussein Onn Malaysia(UTHM)Parit RajaBatu PahatJohor86400Malaysia Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Department of Computer Science University of São PauloSão PauloBrazil

Visible light communication(VLC)has a paramount role in industrial implementations,especially for better energy efficiency,high speed-data rates,and low susceptibility to ***,since studies on VLC for industrial implementations are in scarcity,areas concerning illumination optimisation and communication performances demand further *** such,this paper presents a new modelling of light fixture distribution for a warehouse model to provide acceptable illumination and communication *** proposed model was evaluated based on various semi-angles at half power(SAAHP)and different height levels for several parameters,including received power,signal to noise ratio(SNR),and bit error rate(BER).The results revealed improvement in terms of received power and SNR with 30 Mbps data *** modulations were studied to improve the link quality,whereby better average BER values of 5.55×10^(−15) and 1.06×10^(−10) had been achieved with 4 PAM and 8 PPM,*** simulation outcomes are indeed viable for the practical warehouse model.

关键词： Visible light communication(VLC) industrial applications warehouse model light fixtures bit error rate(BER)

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Signals & Systems Imaging Real-time Facial Recognition using VLSI 11

Signals & Systems Imaging Real-time Facial Recognition using...

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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Vinay Kumar, S.B. Devaraj Verma, C. Faculty of Engineering and Technology Department of Electronics and Communication Engineering Bangalore India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9781665487320

When joint with a web cam, digitizer of image, & VLSI picture correlate chip, an IBM PC can be utilized for real-time facial identification. A semi-controlled lighting environment is used to capture a single frontal facial image, which is then preprocessed and template extracted before being correlated with a database of 173 photographs and finally post processed to yield identification. These steps use a single frontal facial image. Software development, VLSI hardware, picture preprocessing, and facial recognition are explored. The completely VLSI image corrugator can execute 340 Mop/second and increase 20 speed compared to adjusted assembly program execution on an 80486/66DX2. The algorithm recognizes a user from 173 photos of 34 persons in two to three seconds. Cross-authentication on the abstemiously variable databank yields a conservative 88% recognition rate for the system. © 2022 IEEE.

关键词： Face recognition

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Summary of Either A Report on Methodologies Can Amend Routing' Protection a Servqual 11

Summary of Either A Report on Methodologies Can Amend Routin...

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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Vanitha, K. Zabeeulla Faculty of Engineering and Technology Department of Electronics and Communication Engineering Bangalore India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9781665487320

Distant location word related advances are taking on a crucial role in the development and implementation of Vanets System (MANET). The depiction of Nodes emphasises the complexity of current protocols on illegal communication developments by emphasising geographic dynamic, limited transmission, or resource utilization. This study examines short Range radio technological devices that are in use now and in the near term. This essay also considers the advantages and disadvantages of such developments, and now it concludes with either a call for the enhancement of fair collective custom for recent and foreseeable faraway developments. The summary and connection presented in this work are thought to aid experts and project is approved in selecting the best tech for Mobile ad hoc networks enterprises. © 2022 IEEE.

关键词： Vehicular ad hoc networks

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Comparative Analysis of CNN and SVM Machine Learning Techniques for Plant Disease Detection 4th

Comparative Analysis of CNN and SVM Machine Learning Techniq...

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4th International Conference on Data, engineering, and Applications, IDEA 2022

作者： Adeniyi, Abidemi Emmanuel Madamidola, Olugbenga Ayomide Awotunde, Joseph Bamidele Misra, Sanjay Agrawal, Akshat Department of Computer Science College of Computing and Communication Studies Bowen University Iwo Nigeria Department of Information Technology Federal University of Technology Akure Nigeria Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Ilorin Nigeria Department of Applied Data Science Institute for Energy Technology Halden Norway Department of Computer Science & Engineering Amity University Haryana Gurugram122412 India

ISBN: (纸本)9789819700363

The growing advancement of different jobs, skills and businesses has stimulated the spread of diseases. Most of the time, these diseases can cross countries’ borders and spread at a very rapid rate. Avoiding and detecting these infections have proved to be a major problem for our public health and one that must be treated with great importance. Crop disease has haunted, farmers have been victimized for several decades, and a remedy must be offered to halt this damage. As a result, a system should be developed to detect plant disease. Untreated plant diseases ultimately result in a loss to the farmer. Traditional methods of detecting plant disease have become less efficient and inaccurate;thus there is need to improve on the techniques of plant disease detection, as a reliable detection of plant diseases will greatly improve the quality of food crops produced and decrease the threat plant diseases pose to food security. Therefore, this study is aimed at analyzing comparatively, two machine learning language techniques convolutional neural network (CNN) and support vector machine (SVM) in terms of their respective accuracy in detecting plant diseases through their leaves in which both algorithms are used for the automatic diagnosis of plant disease. From the experimental test conducted on various plants using CNN and SVM algorithms, CNN had an accuracy of 98%, while SVM had an accuracy of 62% on various plant leaves used. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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Human Action Recognition Using Difference of Gaussian and Difference of Wavelet

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Big Data Mining and Analytics 2023年第3期6卷 336-346页

作者： Gopampallikar Vinoda Reddy Kongara Deepika Lakshmanan Malliga Duraivelu Hemanand Chinnadurai Senthilkumar Subburayalu Gopalakrishnan Yousef Farhaoui Department of Computer Science and Engineering(AI&ML) CMR Technical CampusHyderabad 501401India. Department of Information Technology Kakatiya Institute of Technology and ScienceWarangal 506015India. Department of Electronics and Communication Engineering Malla Reddy Engineering College for Women(Autonomous)Hyderabad 500100India. Department of Computer Science and Engineering S.A.Engineering College(Autonomous)Thiruverkadu 600077India. Department of Electronics and Communication Engineering Saveetha Institute of Medical and Technical Sciences(SIMATS)Chennai 602105India. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600062India. IDMS Team STI LaboratoryFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsErrachidia 25003Morocco.

Human Action Recognition(HAR)attempts to recognize the human action from images and *** major challenge in HAR is the design of an action descriptor that makes the HAR system robust for different environments.A novel action descriptor is proposed in this study,based on two independent spatial and spectral *** proposed descriptor uses a Difference of Gaussian(DoG)filter to extract scale-invariant features and a Difference of Wavelet(DoW)filter to extract spectral *** create a composite feature vector for a particular test action picture,the Discriminant of Guassian(DoG)and Difference of Wavelet(DoW)features are *** Discriminant Analysis(LDA),a widely used dimensionality reduction technique,is also used to eliminate duplicate ***,a closest neighbor method is used to classify the *** and UCF 11 datasets were used to run extensive simulations of the suggested strategy,and the accuracy assessed after the simulations were run on Weizmann datasets for five-fold cross validation is shown to perform *** average accuracy of DoG+DoW is observed as 83.6635%while the average accuracy of Discrinanat of Guassian(DoG)and Difference of Wavelet(DoW)is observed as 80.2312%and 77.4215%,*** average accuracy measured after the simulation of proposed methods over UCF 11 action dataset for five-fold cross validation DoG+DoW is observed as 62.5231%while the average accuracy of Difference of Guassian(DoG)and Difference of Wavelet(DoW)is observed as 60.3214%and 58.1247%,*** the above accuracy observations,the accuracy of Weizmann is high compared to the accuracy of UCF 11,hence verifying the effectiveness in the improvisation of recognition accuracy.

关键词： human action recognition difference of Gaussian difference of wavelet linear discriminant analysis Weizmann UCF 11 accuracy

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Navigating Energy: Unveiling Power Consumption Patterns in Autonomous Vehicles 1

Navigating Energy: Unveiling Power Consumption Patterns in A...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Saif, Abdu Shah, Nor Shahida Mohd Ameen, Ali Alnoamani, Aiman Al-Qatf, Majjed Alsamhi, Saeed Hamood Department of Communication and Computer Engineering Faculty of Engineering and IT Taiz University P.O. Box 6803 Taiz Yemen Faculty of Engineering Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia Faculty of Computer Science Lincoln University College Kuala Lumpur Malaysia Insight Center for Data Analytics University of Galway Galway Ireland

ISBN: (纸本)9798331533557

Energy consumption is critical in self-driving cars and is set to change how transportation works. In this paper, we address the challenges of vehicle energy consumption by examining how the location of self-driving cars affects their energy use over time, looking at two- and three-dimensional aspects. Using models and real-world data, we examine the energy usage patterns of vehicle systems within MATLAB to reveal insights into their design and operation. In this paper, the power dynamics of cars that significantly contribute to the discussions of practical and sustainable self-driving transportation are introduced. The main goal is to demonstrate how power management may be revolutionized for self-driving car systems, ensuring maximum performance and dependability in today’s dynamic mobility scene. The findings show that enhancing autonomous vehicles’ design and operational strategies ensures their reliability and optimizes performance in today’s rapidly evolving transportation landscape. © 2024 IEEE.

关键词： Autonomous vehicles

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Comprehensive analysis of multiple machine learning techniques for rock slope failure prediction

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Journal of Rock Mechanics and Geotechnical engineering 2024年第11期16卷 4386-4398页

作者： Arsalan Mahmoodzadeh Abed Alanazi Adil Hussein Mohammed Hawkar Hashim Ibrahim Abdullah Alqahtani Shtwai Alsubai Ahmed Babeker Elhag Department of Civil Engineering University of HalabjaHalabjaKurdistan Region46018Iraq Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Department of Communication and Computer Engineering Faculty of EngineeringCihan University-ErbilKurdistan RegionIraq Department of Civil Engineering College of EngineeringSalahaddin University-Erbil44002ErbilKurdistan RegionIraq Software Engineering Department College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Department of Civil Engineering College of EngineeringKing Khalid UniversityAbha61413Saudi Arabia

In this study,twelve machine learning(ML)techniques are used to accurately estimate the safety factor of rock slopes(SFRS).The dataset used for developing these models consists of 344 rock slopes from various open-pit mines around Iran,evenly distributed between the training(80%)and testing(20%)*** models are evaluated for accuracy using Janbu's limit equilibrium method(LEM)and commercial tool GeoStudio *** assessment metrics show that the random forest model is the most accurate in estimating the SFRS(MSE=0.0182,R2=0.8319)and shows high agreement with the results from the LEM *** results from the long-short-term memory(LSTM)model are the least accurate(MSE=0.037,R2=0.6618)of all the models ***,only the null space support vector regression(NuSVR)model performs accurately compared to the practice mode by altering the value of one parameter while maintaining the other parameters *** is suggested that this model would be the best one to use to calculate the SFRS.A graphical user interface for the proposed models is developed to further assist in the calculation of the SFRS for engineering *** this study,we attempt to bridge the gap between modern slope stability evaluation techniques and more conventional analysis methods.

关键词： Rock slope stability Open-pit mines Machine learning(ML) Limit equilibrium method(LEM)

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The Role of ERNIE Model in Analyzing Hotel Reviews using Chinese Sentiment Analysis

The Role of ERNIE Model in Analyzing Hotel Reviews using Chi...

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2023 International Conference on computer communication and Informatics, ICCCI 2023

作者： Jie, Lee Hao Ayyasamy, Ramesh Kumar Sangodiah, Anbuselvan Jalil, Norazira Binti A Krishnan, Kesavan Chinnasamy, P. University Tunku Abdul RahmanKampar Faculty of Information and Communication Technology Malaysia Faculty of Computing and Engineering Quest International University Ipoh Malaysia Universiti Malaya Faculty of Computer Science and Information Technology Kuala Lumpur Malaysia MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350348217

This research aims to find the best deep learning model to do Chinese sentimental analysis. BERT's model may work well in the English language but not work in the Chinese language. English is easier to encode in embedding space, and words are separated by space characters, unlike Chinese words, which do not exist separate by the area. BERT Chinese model work on character level encoding is not enough to make the BERT model adapt to Chinese NLP tasks. The BERT Model and ERNIE models are the current state of art pre-training language models. Word level embeddings and input is needed to improve the BERT model to perform in Chinese Sentiment Analysis. With the motivation to improve the Chinese Sentiment Analysis, this study will explore the role of different models to propose a better version of the ERNIE model. This study will limit the scope to improve Chinese sentiment analysis among different NLP tasks. © 2023 IEEE.

关键词： Sentiment analysis

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An Enhanced Product Recommendation System Using Decision Tree Algorithm 7th

An Enhanced Product Recommendation System Using Decision Tre...

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7th International Conference on communication, Device and Networking, ICCDN 2024

作者： Awotunde, Joseph Bamidele Sur, Samarendra Nath Imoize, Agbotiname Lucky Akinyoola, Oluwatimilehin Moses Department of Computer Science Faculty of Information and Communication Sciences University of Ilorin Kwara State Ilorin240003 Nigeria Department of Electronics and Communication Engineering Sikkim Manipal Institute of Technology Sikkim Manipal University Sikkim India Department of Electrical and Electronics Engineering Faculty of Engineering University of Lagos Akoka Lagos 100213 Nigeria Department of Electrical Engineering and Information Technology Institute of Digital Communication Ruhr University Bochum44801 Germany

ISBN: (纸本)9789819764648

Product recommendation systems are a critical element of e-commerce platforms, as they enable customers to identify the items that best meet their needs. Product recommendation systems are important tools used by organizations to increase customer engagement, satisfaction, and loyalty. Existing product recommendation systems have several weaknesses, such as an inability to incorporate features outside of customer preferences. Therefore, this paper proposes an enhanced product recommendation system using a decision tree algorithm. The main objectives of this system are to improve the accuracy and efficiency of the existing product recommendation systems. To accomplish this, a framework includes a data preprocessing phase, a feature selection phase, and a model training phase. The data preprocessing phase is used to clean the data and eliminate any noise. The feature selection phase is used to identify the most informative features, which are then used to train the decision tree model. The model is trained using CART, a supervised learning algorithm, and is evaluated using various metrics such as accuracy, precision, recall, and F1-score. Finally, the model is tested on a test dataset to compare with existing solutions. The results show that the proposed system outperforms existing recommender systems in terms of all the evaluation metrics discussed. Furthermore, the improved system also provides useful insights into the product recommendation process for future studies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sales

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Design and Analysis of High-Speed communication Systems for 5G and Beyond 9

Design and Analysis of High-Speed Communication Systems for ...

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9th International Conference on science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Jegadeesan, R. Srinivas, Dava Deivakani, M. Joshi, Sunita Dinesh, P.M. Kumar, M. Jogendra Jyothishmathi Institute of Technology And Science Department of Computer Science And Engineering Telangana Karimnagar505481 India Psna College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Dindigul624622 India Manav Rachna International Institute of Research And Studies Department of Faculty of Computer Applications Haryana Faridabad121004 India Sona College of Technology Department of Electronics And Communication Engineering Tamil Nadu Salem636005 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram522302 India

ISBN: (纸本)9798350365092

Fifth Era Innovation (5G) is the late portable network in wireless communications. This article presents an assessment of the advancements in portable communications. The different issues that arise at each stage are reported in our guide to state-of-the-art wearable networks. The fifth era (5G) of portable networks offers everybody admittance to high-speed web at whatever point they need, any place they are. Since to its inventive qualities, such connecting individuals and controlling contraptions, machines, and items, 5G is somewhat unique. Various levels of execution and capacities presented by the 5G versatile innovation will make new client encounters and connection new organizations. It is pivotal to comprehend where the business can utilize5G's benefits. This work examines and models a microstrip fix antenna working at 29 GHz for impending 5G communication innovation. The result of this reproduction is better than past work that was finished. It can then be used as a significant source of strength for 5G wireless technologies. The ongoing logic diary demonstrates that the proposed antenna performs better than those currently in use. This antenna may therefore be adequate for his 5G wireless connection architecture. © 2024 IEEE.

关键词： 5G mobile communication systems

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