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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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Web Scraping Fire Incidents and Assessment of Fire Impact - A Case Study of Split and Dalmatia County Fires 1

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1st International Conference on Digital Transformation in Education and Artificial Intelligence Applications, MoStart 2023

作者： Knežić Buhovac, Selena Šerić, Ljiljana Ivanda, Antonia Krstinić, Damir Faculty of Mechanical Engineering Computing and Electrical Engineering University of Mostar Mostar Bosnia and Herzegovina Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture University of Split Split Croatia

ISBN: (数字)9783031368332

ISBN: (纸本)9783031368325

This paper presents a framework for initiating a fire incidents database using web scraping and impact assessment techniques. The methodology used for correct space, time, and impact association is described. The dataset used in this study was collected from media reports published daily by the Croatian Fire Association during a specific period. Each incident in the collected data was assigned an estimated time of occurrence and evaluated for its impact level. The study includes a comparison of the obtained results with the official reports of fire impact. In this context, impact refers to the extent of damage caused by the fire incident. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fires

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Development of Adaptive Fuzzy PID Controller Integrated with Slide Mode Control for Brushless Direct Current Motors 6

Development of Adaptive Fuzzy PID Controller Integrated with...

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6th IEEE Conference on Energy Conversion, CENCON 2023

作者： Xinyue, Dai Nordin, Norjulia Binti Mohamad Afrouzi, Hadi Nabipour Geach, Chen Rui Xingye, Wang Tavalaei, Jalal Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor Bahru Malaysia Swinburne University of Technology Faculty of Engineering Computing and Science Kuching Malaysia

ISBN: (纸本)9798350325096

The relationship between magnetic flux and speed in a BLDC motor is complex and will show different trends under different control methods. Add the gap, other research has been done but still this issue is there. This study focuses on analyzing the relationship between magnetic flux and speed in a BLDC motor, using a proportional-integral-derivative (PID) control system with the inner loop acting as the current outer loop, investigating the performance of the fuzzy controller, and using three control methods, the traditional PID control, fuzzy PID control and adaptive PID control. The simulation uses the BLDC to simulate at 30%, 50%, and 100% of the rated speed, and verifies that the system can adjust the PID parameters in different situations and different control modes. At the same time, since harmonic distortion will be generated in the circuit, an adaptive filter is introduced, which acts as an integral filter at the operating frequency while suppressing other frequency components to balance control performance and stability. The experimental results show that the adaptive fuzzy control can reach a desired output state faster in only 0.665s, while the fuzzy PID control needs 0.693s, and the traditional fuzzy PID needs 0.696s. It can be proved that the traditional PID parameters are difficult to adjust, and it is difficult to achieve the best effect of magnetic flux and speed. On top of that, the optimized adaptive fuzzy PID controller has faster response speed, smaller overshoot, higher control precision, and can control the motor speed output more effectively. © 2023 IEEE.

关键词： Three term control systems

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Energy Coverage Analysis of Millimeter Wave Wireless Power Transfer 6

Energy Coverage Analysis of Millimeter Wave Wireless Power T...

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6th IEEE International Symposium on Telecommunication Technologies, ISTT 2022

作者： Azali, Nur Atikah Muhammad, Nor Aishah Apandi, Nur Ilyana Anwar Sunar, Noorhazirah Wahab, Nur Haliza Abdul School of Electrical Engineering Faculty of Engineering Malaysia Faculty of Electrical Engineering Malaysia School of Computing Faculty of Engineering Malaysia

ISBN: (数字)9781665489423

ISBN: (纸本)9781665489423

The millimeter wave (MMW) region received great interest in wireless communication applications as it provides large bandwidth ranging from 30 GHz to 300 GHz. MMW communication is a new feature of fifth-generation (5G) and beyond 5G cellular networks. The large antenna arrays that will be implemented in the MMW system potentially increase user performance. Since the MMW system performance closely depends on the antenna gain, a suitable antenna pattern model is crucial to predict the MMW system performance before the real base station implementation. This paper presents a simplified antenna model known as a modified sectored (M-sectored) antenna that incorporates the number of antenna elements. Leveraging the concept of stochastic geometry, this paper analyze the energy coverage probability of MMW wireless power transfer. The locations of base station and users are modeled following Poisson point processes (PPP), and then the effect of the antenna model is investigated. This study had demonstrated that the energy coverage probability (ECP) of the proposed antenna model matches the actual antenna gain pattern. In addition, the effects of the base station density and blockage parameter are also observed. © 2022 IEEE.

关键词： Base stations

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Enhancing intrusion detection in IIoT: optimized CNN model with multi-class SMOTE balancing

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Neural computing and Applications 2024年第24期36卷 14643-14659页

作者： Eid, Abdulrahman Mahmoud Soudan, Bassel Nassif, Ali Bou Injadat, MohammadNoor Department of Computer Engineering College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Data Science and AI Faculty of Information Technology Zarqa University Zarqa Jordan

This work introduces an intrusion detection system (IDS) tailored for industrial internet of things (IIoT) environments based on an optimized convolutional neural network (CNN) model. The model is trained on a dataset that was balanced using a novel multi-class implementation of synthetic minority over-sampling technique (SMOTE) that ensures equal representation of all classes. Additionally, systematic optimization will be used to fine tune the hyperparameters of the CNN model and mitigate the effects of the increased size of the training dataset. Evaluation results will demonstrate substantial improvement in performance when the optimized CNN model is trained on the balanced dataset. The proposed IDS will be evaluated using the IIoT-specific WUSTL-IIOT-2021 dataset, and then its generalization capability will be verified using the non-domain specific UNSW_NB15 dataset. The model’s performance will be evaluated using accuracy, precision, recall, and F1-score metrics. The results will demonstrate that the proposed IDS is highly effective with performance exceeding 99.9% on all performance metrics. The IDS is also highly effective in detecting intrusion for generic IT networks achieving improvements in excess of 30% compared to the default baseline model. The results emphasize the versatility and effectiveness of the proposed IDS model, making it a reliable and adaptable solution for enhancing network security across diverse network environments. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Neural network models

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Comparative Analysis of News Articles Summarization using LLMs

Comparative Analysis of News Articles Summarization using LL...

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2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Archanaa, N. Shivanesh, B. Suwin Kumar, J.D.T. Bharathi Mohan, G. Doss, Srinath Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India Botho University Faculty of Engineering and Technology Botswana

ISBN: (纸本)9798350361537

In the rapidly evolving domain of Natural Language Processing (NLP), the efficiency of Large Language Models (LLMs) in generating abstractive text summaries plays a pivotal role in information synthesis. This study advances the understanding of LLM performance by conducting a comprehensive evaluation of seven cutting-edge models on four distinct datasets. The models selected for comparison include Distilbart-cnn-12-6, Led-base-16384, Google's Bigbird, Microsoft's ProphetNet, Facebook's BART, T5 fine-tuned, and Google's PEGASUS. Each model's summarization prowess is rigorously assessed using a battery of metrics: ROUGE, METEOR, BERTScore, Cosine Similarity, and BLEU. The goal is to discern the intricate relationship between dataset characteristics and model efficacy, delivering insights into the inherent advantages and limitations of each model in handling specific data contexts. The results contribute to a refined understanding of LLM applicability, offering empirical evidence to aid in the selection of the most suitable model for varied summarization needs. © 2024 IEEE.

关键词： Natural language processing systems

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Divergent Approaches to Antimicrobial Peptide Classification: A Comparative Evaluation of AI Techniques 7

Divergent Approaches to Antimicrobial Peptide Classification...

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7th International Conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Rajagopal, Sushma Bharathi Mohan, G. Doss, Srinath Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India Botho University Faculty of Engineering and Technology Botswana

ISBN: (纸本)9798350372816

Given the global rise in antibiotic resistance, antimicrobial peptides (AMPs) provide a viable substitute for traditional antibiotics. Through a comparison of transformer-based, deep learning (DL), and machine learning (ML) techniques, this work seeks to classify AMPs. AMP sequences from curated databases were compared with non-AMP sequences obtained from UniProtKB/Swiss-Prot. The study compares performance across many assessment variables to assess how well various algorithms separate AMPs from non-AMPs. Significantly, RoBERTa outperformed DistilBERT (84.43%) in accuracy (86.53%). To provide a thorough knowledge of the algorithms' performance, the research also included a variety of other assessment criteria, including area under the receiver operating characteristic curve (AUC-ROC), recall, F1 score, and accuracy. The performance of the LSTM and GRU models was notable, despite their significantly lower accuracies. Furthermore, conventional machine learning methods such as Naive Bayes and Logistic Regression demonstrated competitive accuracy. This thorough analysis clarifies the benefits and drawbacks of various AMP classification techniques, providing insightful information for next studies on antimicrobial peptides and their potential to fight antibiotic resistance. © 2024 IEEE.

关键词： Contrastive Learning

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State of charge estimation for electric vehicles using random forest

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Green Energy and Intelligent Transportation 2024年第5期3卷 42-51页

作者： Mohd Herwan Sulaiman Zuriani Mustaffa Faculty of Electrical&Electronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)26600 Pekan PahangMalaysia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)26600 Pekan PahangMalaysia

This paper introduces an innovative approach to addressing a critical challenge in the electric vehicle(EV)industry—the accurate estimation of the state of charge(SOC)of EV batteries under real-world operating *** electric mobility landscape is rapidly evolving,demanding more precise SOC estimation methods to improve range prediction accuracy and battery *** study applies a Random Forest(RF)machine learning algorithm to improve SOC ***,SOC estimation has posed a formidable challenge,particularly in capturing the complex dependencies between various parameters and SOC values during dynamic driving *** methods,including the Extreme Learning Machine(ELM),have exhibited limitations in providing the accuracy and robustness required for practical EV *** contrast,this research introduces the RF model,for SOC estimation approach that excels in real-world *** leveraging decision trees and ensemble learning,the RF model forms resilient relationships between input parameters,such as voltage,current,ambient temperature,and battery temperatures,and SOC *** unique approach empowers the model to deliver precise and consistent SOC estimates across diverse driving *** comparative analyses showcase the superiority of the RF over *** RF model not only outperforms in accuracy but also demonstrates exceptional robustness and reliability,addressing the pressing needs of the EV *** results of this study not only underscore the potential of RF in advancing electric mobility but also suggest a promising integration of the SOC estimation approach into the battery management system of BMW *** integration holds the key to more efficient and dependable electric vehicle operations,marking a significant milestone in the ongoing evolution of EV ***,the RF model demonstrates a lower Root Mean Squared Error(RMSE)of 5.902,8%compared to 6.312,7%for ELM,and a

关键词： Electric vehicles Extreme learning machine Machine learning Random Forest State of charge of battery

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Community Involvement in Fire reporting: Time Series Examination of Official Reports and Social Media Posts in Split and Dalmatia County 8

Community Involvement in Fire reporting: Time Series Examina...

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8th International Conference on Smart and Sustainable Technologies, SpliTech 2023

作者： Buhovac, Selena Knežić Šerić, Ljiljana Ivanda, Antonia University of Mostar Faculty of Mechanical Engineering Computing and Electrical Engineering Mostar Bosnia and Herzegovina University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia

ISBN: (纸本)9789532901283

In this paper, we examine the value of social media posts in comparison with official records on a case study of wildfires that occurred on the territory of Split and Dalmatia County in 2021 and 2022. Three sources of data were used. Unofficial data from the Facebook social network fun page, official daily media reports posted by Croatian Fire Association and official data from the firefighting interventions database. Appropriate measures for event description based on word counts and number of intervention participants was utilized to create timeseries of data from three sources. To obtain insights into data correlation, time series analysis metrics and Pearson's and R2, coefficient of determination were employed. While the plots reveal similarity among the data, the metrics did show evident correlation with traditional measures. However, this paper highlights the significance and value of unofficial crowdsourced data when compared to official data and the significance of community involvement in crisis management. © 2023 University of Split, FESB.

关键词： Time series analysis

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Refractive Index Measurement Based on Fibre Optics with Multiparameter Sensing Capabilities 19

Refractive Index Measurement Based on Fibre Optics with Mult...

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19th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2023

作者： Bong, Paul Cornelius Tan, Alfred Jia Yee Chua, Hong Siang Swinburne University of Technology Sarawak Campus Faculty of Engineering Computing and Science Kuching Malaysia

ISBN: (纸本)9781665476928

Quality control and assurance plays a core in chemical, agrifood, F B and pharmaceutical industries due to quality regulations. Refractometry plays an indispensable part in determining the composition or purity of a sample and conventional solutions can be intrusive and very expensive. In this paper we aim to determine the Refractive Index (RI) sensing and multiparameter sensing capabilities of a triple U-shaped side + center polished macrobent fibre optic sensor prototype. This prototype was tested on controlled glycerol samples ranging from (1.34-1.39) Refractive Index Unit (RIU) and showed a linear trend in RI sensing. It boasts an average percentage error of 0.1318% in refractive index measurements when subjected to 12 randomly prepared test data within the range of(1.33 to 1.40) RIU. Individually, the percentage error is higher for each probe but did not exceed 0.4% when used in tandem. This proves improved performance when using multiple probes with different configurations. The sensor was also able to extrapolate further for 1. 40RIU which was not within the range of the training data thus it is highly scalable. Its temperature sensing (30°C to 45°C) capabilities was also tested. Despite the great performance in RI sensing, the center polished probe was found unsuitable. The 500\mum diagonal polished probe showed great sensitivity and linearity while the 300\mum diagonal polished probe showed low sensitivity and high linearity, thus allowing the system to determine the RIU of the solution at room temperature. This project shows great promise in the field of multiparameter RI sensing. © 2023 IEEE.

关键词： Probes

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