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Cyberbullying Sexism Harassment Identification by Metaheurustics-Tuned eXtreme Gradient Boosting

computers, Materials & Continua 2024年第9期80卷 4997-5027页

作者： Milos Dobrojevic Luka Jovanovic Lepa Babic Miroslav Cajic Tamara Zivkovic Miodrag Zivkovic Suresh Muthusamy Milos Antonijevic Nebojsa Bacanin Technical Faculty Singidunum UniversityBelgrade11000Serbia Informatics and Computing Singidunum UniversityBelgrade11000Serbia Business Economics Singidunum UniversityBelgrade11000Serbia Computing and Informatics Sinergija UniversityBijeljina76300Bosnia and Herzegovina Department for Information Systems and Technologies University“Union Nikola Tesla”Cara DusanaBelgrade11080Serbia Department for Computer Science and Informatics School of Electrical EngineeringUniversity of BelgradeBelgrade11000Serbia Department of Electrical and Electronics Engineering Kongu Engineering College(Autonomous)PerunduraiErode638060India Department of Mathematics Saveetha School of Engineering(Deemed to be University)SIMATS ThandalamChennai602105India MEU Research Unit Middle East UniversityAmman11831Jordan

Cyberbullying is a form of harassment or bullying that takes place online or through digital devices like smartphones,computers,or *** can occur through various channels,such as social media,text messages,online forums,or gaming *** involves using technology to intentionally harm,harass,or intimidate others and may take different forms,including exclusion,doxing,impersonation,harassment,and ***,due to the rapid growth of malicious internet users,this social phenomenon is becoming more frequent,and there is a huge need to address this ***,the main goal of the research proposed in this manuscript is to tackle this emerging challenge.A dataset of sexist harassment on Twitter,containing tweets about the harassment of people on a sexual basis,for natural language processing(NLP),is used for this *** algorithms are used to transform the text into a meaningful representation of numbers for machine learning(ML)input:Term frequency inverse document frequency(TF-IDF)and Bidirectional encoder representations from transformers(BERT).The well-known eXtreme gradient boosting(XGBoost)ML model is employed to classify whether certain tweets fall into the category of sexual-based harassment or ***,with the goal of reaching better performance,several XGBoost models were devised conducting hyperparameter tuning by *** this purpose,the recently emerging Coyote optimization algorithm(COA)was modified and adjusted to optimize the XGBoost ***,other cutting-edge metaheuristics approach for this challenge were also implemented,and rigid comparative analysis of the captured classification metrics(accuracy,Cohen kappa score,precision,recall,and F1-score)was ***,the best-generated model was interpreted by Shapley additive explanations(SHAP),and useful insights were gained about the behavioral patterns of people who perform social harassment.

关键词： Coyote optimization algorithm NLP TF-IDF BERT XGBoost online harassment and cyberbullying metaheuristics

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An Implementation of the NOAA Satellite Data Reception Ground Station for Weather and Climate Enthusiasts

An Implementation of the NOAA Satellite Data Reception Groun...

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Geoinformatics for Spatial-Infrastructure Development in Earth and Allied Sciences (GIS-IDEAS)

作者： Wichapol Utumporn Suwabhat Somboonsub Watchara Amasiri Dahmmaet Bunnjaweht Warinthorn Kiadtikornthaweeyot Evans Pirapat Waritkraikul Electrical and Computer Engineering Dept. Faculty of Engineering Thammasat School of Engineering Thammasat University Pathumthani Thailand Industrial Engineering Dept. Faculty of Engineering Thammasat School of Engineering Thammasat University Pathumthani Thailand

ISBN: (数字)9798331504243

ISBN: (纸本)9798331504250

During the dry season in Thailand, the risk of forest fires increases significantly, posing a serious threat to both the environment and public health. There is a pressing need for weather and climate enthusiasts to access comprehensive data on forest fires, climate patterns, and environmental conditions. This work aimed at implementing a satellite ground station to exemplify enthusiasts' alternative data access other than published data on governmental websites. The goal was to achieve good results with low-cost software-defined radio (SDR) hardware, specifically the RTL-SDR, commercial-off-the-shelf components, and open-source software. Raspberry-NOAA-V2 program suite offers a powerful solution for individuals with minimal or no coding experience, enabling hobbyists to easily set up an automatic satellite imagery reception. With the free reverse proxy functionality from ngrok, the station owner could establish and manage access to the image archive without needing any network knowledge, while their peer enthusiasts could access it from anywhere. Such an approach was considered to offer hobbyists with inquisitive interest to apply technology to build an operational ground station to obtain real-time meteorological data. While the ground station employed inexpensive components, the weather image reconstruction results were relatively satisfactory. The implemented station was a good hands-on activity for weather and climate enthusiasts. By combining the strengths of technology, real-time data, and community awareness, a municipality can create more resilient ecosystems with local engagement that are better prepared to face the challenges of climate variability.

关键词： Satellite broadcasting Radio transmitters Forestry Satellite ground stations Real-time systems Satellite images Public healthcare Meteorology National Oceanic and Atmospheric Administration Software radio

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Cyber Security Posterior Distribution 13

Cyber Security Posterior Distribution

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13th IEEE International Conference on Communication systems and Network Technologies, CSNT 2024

作者： Andrews, Leo John Baptist Venkatachary, Sampath Kumar Sarathkumar, D. Alagappan, Annamalai Fathima, M. Raj, Raymon Antony Rajeshkanna, R. Botho University Faculty of Engineering and Technology Department of Information Technology Gaborone Botswana Kongu Engineering College Department of Electrical and Electronics Engineering Erode district Tamilnadu 638 060 India Grant Thornton Gaborone Botswana Botho University Faculty of Engineering and Technology Department of Network and Infrastructure Management Gaborone Botswana Thamirabarani Engineering College Department of Eee Tamil Nadu Tirunelveli627 358 India Sri Krishna College of Engineering and Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India

ISBN: (纸本)9798350305463

Currently, the vast majority of international interactions and activities related to trade, government, culture, social interaction, and economics take place online. These interactions involve people, non-governmental organizations, governments, and government agencies at all levels. Recently, a sizeable number of commercial firms and government organizations all over the world have been presented with the challenge offered by cyberattacks as well as the danger represented by wireless communication technologies. A very little amount of time has passed since this had place. We were able to develop a model for the risk of cyber security by making use of Bayesian Networks. This model has the capability of locating the point of cyber security that is weak and merging two different cyber analysis models. Among these is the activityquality model, which shows how individuals and/or groups adhere to the legal requirements for cyber security. Evidence describing the critical component of cyber security for a research reactor's RPS may be produced via the cyber security risk model. An further model that shows the probability of a cyberattack against RPS architecture is the cyber security risk model. © 2024 IEEE.

关键词： Bayesian networks

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Synergistic Swarm Optimization Algorithm

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computer Modeling in engineering & Sciences 2024年第6期139卷 2557-2604页

作者： Sharaf Alzoubi Laith Abualigah Mohamed Sharaf Mohammad Sh.Daoud Nima Khodadadi Heming Jia Faculty of Computer Sciences and Informatics Amman Arab UniversityAmman11953Jordan Computer Science Department Al Al-Bayt UniversityMafraq25113Jordan Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia College of Engineering Al Ain UniversityAbu Dhabi112612United Arab Emirates Department of Civil and Architectural Engineering University of MiamiCoral Gables1251USA School of Information Engineering Sanming UniversitySanming365004China

This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm(SSOA).The SSOA combines the principles of swarmintelligence and synergistic cooperation to search for optimal solutions efficiently.A synergistic cooperation mechanism is employed,where particles exchange information and learn from each other to improve their search *** cooperation enhances the exploitation of promising regions in the search space while maintaining exploration ***,adaptive mechanisms,such as dynamic parameter adjustment and diversification strategies,are incorporated to balance exploration and *** leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation,the SSOAmethod aims to achieve superior convergence speed and solution quality performance compared to other optimization *** effectiveness of the proposed SSOA is investigated in solving the 23 benchmark functions and various engineering design *** experimental results highlight the effectiveness and potential of the SSOA method in addressing challenging optimization problems,making it a promising tool for a wide range of applications in engineering and *** codes of SSOA are available at:https://***/matlabcentral/fileexchange/153466-synergistic-swarm-optimization-algorithm.

关键词： Synergistic swarm optimization algorithm optimization algorithm metaheuristic engineering problems benchmark functions

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Public Healthcare Informatics for COVID-19 from Social Media Data

Public Healthcare Informatics for COVID-19 from Social Media...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Vishwa V. Kumar Avimanyu Sahoo Ritika Kumar Nicholas Loyd Industrial & Systems Engineering and Engineering Management Department of Electrical and Computer Engineering The University of Alabama in Huntsville USA North Alabama Medical Center Florence AL USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The COVID-19 pandemic has profoundly affected various facets of society. This research explores the discourse on social media, specifically "X" (Twitter), to understand public sentiment and needs regarding healthcare supply chain challenges, such as the availability of testing kits, oxygen supplies, and hospital beds, during the pandemic. By identifying pertinent opinionated keyphrases and employing advanced natural language processing (NLP) techniques, we sifted through over 3.9 million tweets to collect health informatics. The content of these tweets is analyzed to investigate the word trends and sentiments. The extracted sentiments were then organized into ten distinct categories using the K-means clustering method that pointed out top-ten healthcare supply needs. The findings underscore the value of social media as a tool for gathering timely and actionable insights on healthcare supply chain logistics, offering critical data for effective response strategies during health crises.

关键词： COVID-19 Social networking (online) Pandemics Hospitals Supply chains Training data Medical services Natural language processing Real-time systems Testing

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Shape Recognition of GPR Images using Hough Transform and PCA plus LDA 2

Shape Recognition of GPR Images using Hough Transform and PC...

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2nd International Conference on Electronic and electrical engineering and Intelligent System, ICE3IS 2022

作者： Ali, H. Bahari, N.I. Elshaikh, M. Kanafiah, S.N.A. Mohd Amran, T.S. Tengku Jusman, Yessi Universiti Malaysia Perlis Centre of Excellence Unmanned Aerial Systems Faculty of Electrical Engineering and Technology Arau Malaysia Universiti Malaysia Perlis Faculty of Electrical Engineering and Technology Arau Malaysia Non-Destructive Testing Group Nuclear Agency Malaysia Industrial Technology Division Kajang Malaysia Universitas Muhammadiyah Yogyakarta Faculty of Electrical Engineering Department of Electrical Engineering Yogyakarta Indonesia

ISBN: (纸本)9781665465410

Ground penetrating radar (GPR) is a nondestructive test used for shallow subsurface investigation such as land mine detection, mapping and locating buried utilities. In practical applications, GPR images could be noisy due to system noise, the heterogeneity of the medium, and mutual wave interactions. Hence, it is a complex task to recognize the hyperbolic pattern from GPR B-scan images. Thus, this project proposes combined shape recognition of buried objects using Hough Transform (HT) and PCA plus LDA in GPR images. The use of HT is justified because it has the property of transforming global curve detection into efficient peak detection in the Hough parameter space. Whereas PCA plus LDA tries to maximize between-class scatter while minimizing within-class scatter. In this framework, the preprocessed GPR images were extracted using HT. The extracted HT features were subjected to PCA plus LDA to map them from high into lower dimensional features. Then, the reduced PCA+LDA features were used as input to the k-NN classifier to recognize four geometrical shapes cubic, disc, and spherical of the buried objects. Based on the results obtained, the average recognition rate of reduced HT features using PCA plus LDA was achieved 85.30% thus shows a promising result. © 2022 IEEE.

关键词： Hough transforms

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Optimizing Maximum Profit for Electric Vehicle Users in a Bipolar DC Distribution Grid with Probabilistic EV Load Demand and V2G Integration

Optimizing Maximum Profit for Electric Vehicle Users in a Bi...

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International electrical engineering Congress (iEECON)

作者： Guntinan Sakulphaisan Sirirat Son-in Nitikorn Junhuathon Industrial technology and innovation management Faculty of science and technology Pathumwan institute of technology Bangkok Thailand Electrical Engineering and Automation Control Systems Faculty of engineering and industrial technology Bansomdejchaopraya Rajabhat University Bangkok Thailand Department of Electrical Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathumthani Thailand

ISBN: (数字)9798350383591

ISBN: (纸本)9798350383607

This article delves into the synergistic potential of integrating Bipolar DC distribution grids, Probabilistic EV load demand forecasting, and Vehicle-to-Grid (V2G) technology. It offers a blueprint for electric vehicle (EV) users to smartly improve their financial results. Through the amalgamation of these components, individuals who possess electric vehicles have the potential to mitigate their energy expenditures while concurrently generating additional income. The study reveals that the integration of EV into the distribution system can lead to a substantial increase in daily energy loss, reaching up to 25.91%. However, when V2G technology is employed within the distribution grid, it has the remarkable capability to mitigate this increase in daily energy loss significantly, achieving a reduction of up to 64.12%.

关键词： electrical engineering Vehicle-to-grid Energy loss Electric potential Demand forecasting Probabilistic logic Resilience

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Simulation of the Floating Photovoltaic System in the Napique Lagoon to Evaluate the Supply of Electricity Demand in the District of Castilla, Piura

Simulation of the Floating Photovoltaic System in the Napiqu...

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electrical engineering and Green Energy (CEEGE), International Conference on

作者： Santiago Linder Rubiños Jimenez Juan Herber Grados Gamarra Eduardo Nelson Chavez Gallegos Yesmi Katia Ortega Rojas Niko Alain Alarcon Cueva Adan Almircar Tejada Cabanillas Faculty of Electrical and Electronic Engineering Universidad Nacional del Callao Callao perú Faculty of Industrial and Systems Engineering Universidad Nacional del Callao Callao perú

ISBN: (数字)9798350350623

ISBN: (纸本)9798350350630

Currently, there has been a significant increase in the installation of photovoltaic (PV) modules on water surfaces, due to the natural capacity of water to cool and keep the modules fresh, generating a reduction in the loss of thermal energy and avoiding the loss of efficiency due to overheating. However, in Peru the application of photovoltaic systems on floating surfaces is null and the studies published regarding their applications are limited so far. The objective of this research is to carry out a realistic simulation of a floating photovoltaic system driven by climate and based on energy demand in the district of Castilla. PVsystem and Global Solar atlas were used as calculation and simulation tools in this study. The results show that 1GWh is necessary to cover the electricity demand and that with the FPV around 76.28 MWh is produced, less than what is necessary per year with an average PR of 83.88%. The Ñapique lagoon is an ideal location for the implementation and installation of the FPV system because it covers 92.37% of the energy demand of the district of Castilla, which can be complemented with low requirements for a diesel generator.

关键词： Photovoltaic systems Green energy electrical engineering Economics Energy consumption Electricity Production Generators Thermal energy Meteorology

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Research on the 'Electric Vehicles and Automotive Electronics' Curriculum Aimed at Modernization within the DIGITRANS Project 65

Research on the 'Electric Vehicles and Automotive Electronic...

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65th IEEE Annual International Scientific Conference on Power and electrical engineering of Riga Technical University, RTUCON 2024

作者： Arhun, Shchasiana Hnatov, Andrii Kunicina, Nadezhda Kharkiv National Automobile and Highway University Automobile Faculty Vehicle Electronics Department Kharkiv Ukraine Riga Technical University Riga Latvia Institute of Industrial Electronics Electrical Engineering and Energy Riga Technical University Faculty of Computer Science Information Technology and Energy Riga Latvia

ISBN: (纸本)9798350365771

The rapid evolution of the automotive industry, driven by technological innovations and the shift towards sustainability, necessitates a corresponding transformation in educational curricula. This paper presents a detailed examination of the 'Electric Vehicles and Automotive Electronics' curriculum at Kharkiv National Automobile and Highway University, which has been targeted for modernization under the DIGITRANS project. The project's primary objective is to align the curriculum with the latest industry demands and technological advances, particularly focusing on electric vehicles (EVs) and automotive electronics. This research utilizes a mixed-methods approach, combining quantitative data from industry surveys with qualitative feedback from academic experts and industry stakeholders. The findings highlight significant gaps in the current educational offerings, particularly in areas such as advanced diagnostics, battery management systems, and integration of smart automotive technologies. The paper discusses the development and integration of new course materials that include hands-on laboratory exercises, industry placements, and enhanced e-learning modules. The modernized curriculum aims to equip students with the skills necessary to excel in the fast-evolving automotive sector, emphasizing critical thinking, technical expertise, and practical experience. The outcomes of this research underscore the importance of continuous industry-academia collaboration to keep educational programs relevant and forward-thinking. This initiative not only enhances the employability of graduates but also contributes to the broader goal of advancing electric vehicle technology and sustainability in automotive engineering. © 2024 IEEE.

关键词： Automotive industry

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A 1D Residual CNN with SMOTE-Tomek and Cosine Annealing for Enhanced ECG Arrhythmia Classification 16

A 1D Residual CNN with SMOTE-Tomek and Cosine Annealing for ...

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16th IEEE Latin American Symposium on Circuits and systems, LASCAS 2025

作者： Jiang, Feng Lim, Yang Wei Ahmad, Siti Anom Ahmad, Faisul Arif Ismail, Luthffi Idzhar Hussein, Ahmed Faeq Rokhani, Fakhrul Zaman Universiti Putra Malaysia Department of Computer and Communication Systems Engineering Faculty of Engineering Malaysia Universiti Putra Malaysia Department of Electrical and Electronics Engineering Faculty of Engineering Malaysia Al-Nahrain University Department of Biomedical Engineering Faculty of Engineering Baghdad Iraq

ISBN: (纸本)9798331522124

This paper proposes a 1D residual convolutional neural network (CNN) for classifying arrhythmias based on electrocardiogram (ECG) signals. The additional residual blocks and skip connections effectively alleviate the gradient problem in deep neural networks by providing a direct path for gradient propagation and enhancing the feature information propagation. In addition, the SMOTE-Tomek technique was demonstrated in this work to mitigate the effects of class imbalance caused by a large amount of data during model training and effectively increase the SNR of the training set. The robustness of the model is increased by adding the cosine annealing technique and L 2 regularization. The proposed model was evaluated with various performance metrics, resulting in an accuracy of 9 8. 7 4 %, sensitivity of 9 8. 3 5 %, specificity of 9 1. 8 6 %, precision of 9 7. 9 5 %, and F1 score of 9 8. 1 4 % on the MIT-BIH Arrhythmia Database. The result shows better performance for classifying previously unseen data for the proposed approach as compared to the state-of-the-art works. © 2025 IEEE.

关键词： Convolutional neural networks

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