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Novel Optimized Feature Selection Using Metaheuristics Applied to Physical Benchmark Datasets

computers, Materials & Continua 2023年第2期74卷 4027-4041页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Fadwa Alrowais Sunil Kumar Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt School of Computer Science University of Petroleum and Energy StudiesDehradun248001India Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

In data mining and machine learning,feature selection is a critical part of the process of selecting the optimal subset of features based on the target *** are 2n potential feature subsets for every n features in a dataset,making it difficult to pick the best set of features using standard ***,in this research,a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm(ASSOA)has been *** using metaheuristics to pick features,it is common for the selection of features to vary across runs,which can lead to *** of this,we used the adaptive squirrel search to balance exploration and exploitation duties more evenly in the optimization *** the selection of the best subset of features,we recommend using the binary ASSOA search strategy we developed *** to the suggested approach,the number of features picked is reduced while maximizing classification accuracy.A ten-feature dataset from the University of California,Irvine(UCI)repository was used to test the proposed method’s performance *** other state-of-the-art approaches,including binary grey wolf optimization(bGWO),binary hybrid grey wolf and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hybrid GWO and genetic algorithm 4028 CMC,2023,vol.74,no.2(bGWO-GA),binary firefly algorithm(bFA),and *** results confirm the superiority and effectiveness of the proposed algorithm for solving the problem of feature selection.

关键词： Metaheuristics adaptive squirrel search algorithm optimization methods binary optimizer

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Polymorphic Security Enhancements for Corporate Environments Utilizing Behavior Analytics

Polymorphic Security Enhancements for Corporate Environments...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Wijesinghe, W.M.A.J. Abeysinghe, Y.P.P. Rukshana, M.A.F. Adhikari, A.M.P.S. Abeywardhana, Kavinga Yapa Siriwardhana, Deemantha Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350367560

Employers should recognize that employees are the most vulnerable aspect of business environments since these cyber hazards are growing because of user neglect, lack of fundamental security discipline, and a fast-changing threat context. The theoretical approach proposed in the study bridges the difference by carefully following and handling the staff's internet presence. Overall, the study describes a comprehensive solution to govern the security of employees' internet presence by utilizing Artificial Neural Networks (ANN) for advanced intrusion detection, Natural Language Processing (NLP) for implementation and enforcement of browser-based security policies, visual and text data recognition to identify phishing attempts, and lastly analyzing and profiling users based on their online presence via a mathematical model. As a result, this study provides a comprehensive solution for mitigating risks related to human factors in corporate environments. © 2024 IEEE.

关键词： Phishing

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Enhancing Agricultural Efficiency with IoT-Enabled Precision Irrigation Management Using LoRaWAN technology 16

Enhancing Agricultural Efficiency with IoT-Enabled Precision...

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16th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Jayasinghe, J.A.S.K. Thennakoon, T.M.H.L. Ruchira, U.G.C. Wimalasena, N.G.C.L. Jayakody, J.A.D.C.A. Pandithage, Dinithi Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798331505264

The Internet of Things-empowered precision irrigation management system with LoRaWAN technology is presented given the growing food requirements across the world and pressing calls for judicious use of water in agriculture. Flow Pilot, specifically designed for chili farms, optimizes water application while enhancing crop health using precise and automated irrigation. The Flow Pilot features advanced sensors such as soil moisture, temperature, humidity, and rain sensors that collect real-time environmental data transmitted over a LoRaWAN network for analysis. Flow Pilot uses the Machine learning algorithm by analyzing sensor data to make localized irrigation recommendations based on crop needs, environmental factors, and weather forecasting. LoRaWAN gateways will support this for long-ranged communications over power-consuming agricultural fields. Besides this, it can use different network architectures. There is also an automated water tank management module that regulates the supply of water and pH levels to have optimal conditions for crop growth. A visually simple dashboard interface enables farmers to inspect and operate irrigation processes remotely, hence rendering the whole process far more efficient. Finally, over the extensive period of field tests executed by the project, Flow Pilot was able to save water, improve crop yields, and help support sustainable agriculture. For example, this testing supports the potential of IoT with LoRaWAN technologies, such as the Flow Pilot implementation, for a game change in conventional irrigation practices into a modern, scalable, and reliable solution. © 2024 IEEE.

关键词： Soil moisture

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A Study of Predicting Social Networking Sites(SNS) Media Disorder Survey Data Using a Machine Learning Approach

A Study of Predicting Social Networking Sites(SNS) Media Dis...

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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Munia, Jerin Akther Tahmiduzzaman, K.B.M. Saad, Izazul Haque Islam, Md Mynul Akash, Abdul Hady Zumma, Md. Thoufiq Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh University of Technology Sydney Faculty of Engineering and Information Technology Sydney Australia University of Asia Pacific Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331509828

This study uses survey data and machine learning algorithms to forecast social media disorder in people. A total of 600 individuals answered questions on their social media usage patterns, internet habits, demographics, and signs of social media disorder. This dataset was used to train a number of machine learning models, such as Gaussian Naive Bayes (GaussianNB), Random Forest, K-Nearest Neighbors (KNN), Decision Tree, and Support Vector Machine (SVM). According to the findings, the GaussianNB model had the greatest accuracy of 97%, followed by SVM (94%), Random Forest (91%), Decision Tree (92%), and KNN (90%). These results demonstrate how well machine learning can identify those who may be at risk for social media disorder. In order to improve prediction performance, future research will concentrate on increasing feature size, diversifying datasets, and refining models. Furthermore, incorporating these models into user-friendly apps and intervention programs may offer useful resources for the early diagnosis and treatment of social media illness. © 2025 IEEE.

关键词： Adversarial machine learning

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Ferroelectrically gated two-dimensional bismuth oxyselenides for strain-invariant flexible synaptic thin-film transistors

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Science China(information Sciences) 2025年第5期68卷 396-403页

作者： Jie WEN Fei XIAO Zheng-Dong LUO Dongxin TAN Xuetao GAN Dawei ZHANG Zhufei CHU Yinshui XIA Yan LIU Genquan HAN Hangzhou Institute of Technology Xidian University State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology School of MicroelectronicsXidian University Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technology Shaanxi Key Laboratory of Optical Information Technology School of Physical Science and Technology Northwestern Polytechnical University School of Materials Science and Engineering The University of New South Wales ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET) The University of New South Wales Faculty of Electrical Engineering Computer Science Ningbo University

Two-dimensional van der Waals（2D vdW） semiconductors have proven to be of great importance for flexible thinfilm transistors（TFTs） owing to their intrinsic mechanical flexibility and superior electronic *** particular,bismuth oxyselenide（Bi2O2Se）,featuring ultrahigh electron mobility along with facile scalable thin-film growth methods,could offer a new option to deliver massively enhanced potential for flexible ***,it has remained a challenge to achieve nonvolatile flexible memory devices based on Bi2O2Se TFTs,thereby hindering the extension of Bi2O2Se TFTs to storage and emerging neuromorphic computing ***,a flexible synaptic TFT is demonstrated through the creation of a Bi2O2Se-based ferroelectric field-effect transistor（FeFET） structure on the flexible mica *** proposed device exhibits excellent nonvolatile memory characteristics,including a large memory window,excellent current modulation ratio,great retention,and strong ***,the Bi2O2Se-based FeFET can be operated as a synaptic device with analog conductance-modulating *** to the superior mechanical flexibility of the component materials and the mica substrate,the Bi2O2Se-based FeFETs can retain their performance against various bending states,showing a straininvariant electrical *** study marks the advancement of Bi2O2Se-based TFTs toward flexible nonvolatile memories and synaptic devices.

关键词： Bi$_{2}$O$_{2}$Se FeFET nonvolatile memory flexible device synaptic transistor

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Database Security: Current Challenges and Effective Protection Strategies 6

Database Security: Current Challenges and Effective Protecti...

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6th International Conference on Computing and Informatics, ICCI 2024

作者： Naguib, Ahmed Fouad, Khaled M. Faculty of Information Technology and Computer Science Nile University Egypt Faculty of Computers and Artificial Intelligence Benha University Egypt Faculty of Computer Science and Engineering New Mansoura University Egypt

ISBN: (纸本)9798350373875

Database security has grown to a necessary level of importance today, characterized by the escalating demand for data storage. The surge in data storage requirements, propelled by technological advancements, has led to increased attacks targeting database security vulnerabilities. While multiple storage and protection methods have emerged in tandem with evolving technologies, the discovery of security vulnerabilities has led to new attack vectors. This study aims to repair this gap by securing and fortifying the security of stored data within databases. Fundamental to information security, the study highlights integrity, confidentiality, and accessibility in addressing database security concerns. The study aims to spotlight these issues and increase awareness about security problems and potential solutions. An analysis of the most common security problems in databases forms a central part of the study, accompanied by a discussion of viable solutions for these challenges. Moreover, the study delves into international security standards and secure models to counteract cyber-attacks targeting databases. © 2024 IEEE.

关键词： Cryptography

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An Improved Multi-Objective Particle Swarm Optimization Routing on MANET

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computer Systems Science & engineering 2023年第2期44卷 1187-1200页

作者： G.Rajeshkumar M.Vinoth Kumar K.Sailaja Kumar Surbhi Bhatia Arwa Mashat Pankaj Dadheech Department of Computer Science and Engineering Erode Sengunthar Engineering CollegePerunduraiErode638057Tamil NaduIndia Department of Information Science and Engineering Dayananda Sagar Academy of Technology and ManagementBangalore560082India Department of Master of Computer Applications M.S.Ramaiah Institute of TechnologyBangalore560054India Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversityRiyadh11533Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityRabigh21911Saudi Arabia Department of Computer Science and Engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipur302017RajasthanIndia

A Mobile Ad hoc Network(MANET)is a group of low-power con-sumption of wireless mobile nodes that conﬁgure a wireless network without the assistance of any existing infrastructure/centralized *** primary aim of MANETs is to extendﬂexibility into the self-directed,mobile,and wireless domain,in which a cluster of autonomous nodes forms a MANET routing *** Intrusion Detection System(IDS)is a tool that examines a network for mal-icious behavior/policy violations.A network monitoring system is often used to report/gather any suspicious attacks/*** IDS is a software program or hardware system that monitors network/security trafﬁc for malicious attacks,sending out alerts whenever it detects malicious *** impact of Dynamic Source Routing(DSR)in MANETs challenging blackhole attack is investigated in this research *** Cluster Trust Adaptive Acknowledgement(CTAA)method is used to identify unauthorised and malfunctioning nodes in a MANET *** system is active and provides successful delivery of a data packet,which implements Kalman Filters(KF)to anticipate node ***,KF is used to eliminate synchronisation errors that arise during the sending and receiving *** order to provide an energy-efﬁcient solution and to minimize network trafﬁc,route optimization in MANET by using Multi-Objective Particle Swarm Optimization(MOPSO)technique to determine the optimal num-ber of clustered MANET along with energy dissipation in *** to the researchﬁndings,the proposed CTAA-MPSO achieves a Packet Delivery Ratio(PDR)of 3.3%.In MANET,the PDR of CTAA-MPSO improves CTAA-PSO by 3.5%at 30%malware.

关键词： MANET intrusion detection system cluster kalmanﬁlter dynamic source routing multi-objective particle swarm optimization packet delivery ratio

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MQTT based monitoring and control system for remote stations in automotive industry

MQTT based monitoring and control system for remote stations...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Ivanovic, Denis Job, Josip Puntaric, Marko Herceg, Marijan TTTech-Auto CX Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Department of Software Engineering Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Department of Communications Osijek Croatia

ISBN: (纸本)9798350347722

In this paper is presented implementation of a lightweight supervisory control and data acquisition system for remote test stations as a part of a larger test house in the automotive industry. It is necessary to allow remote set up and monitoring of the test stations, which means defining the structure of a system with numerous test stations as endpoints. The test stations are meant to be virtual machines but can be both virtual and physical machines. A communication protocol must be used that enables this within the organization's network, regardless of actual distance and location. The parameters of the test stations to be monitored can be defined according to the needs and purpose. Even when creating your own tool, this function is not unique, i.e. on one test station parameters of operating system resources such as memory usage can be monitored, while on another test station logged-in users or running programs, reported system errors and others must be monitored. Data storage is one of the mandatory functions of this system. This process allows viewing data throughout history and more detailed analysis of events. There are numerous benefits that can be drawn and used from the data stored in the database. It is necessary to pay attention to the data stored as well as the scope and retention throughout history. The correct and secure setup of a database is one of the prerequisites for any serious system that processes data. Appropriate views should be created for users involved in the data monitoring process using all the elements mentioned so far. Creating a visually acceptable and easy-To-use interface that serves the main purpose is the final presentation of the entire system to users. A complete system leads to higher productivity, profitability and better organization of the company. It also allows project managers to better plan the use and occupancy of test stations. At any time, they have insight into the status of individual test stations, their activitie

关键词： Automotive industry

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Phasmatodea Population Evolution Algorithm Based on Spiral Mechanism and Its Application to Data Clustering

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computers, Materials & Continua 2025年第4期83卷 475-496页

作者： Jeng-Shyang Pan Mengfei Zhang Shu-Chuan Chu Xingsi Xue Václav Snášel College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao266590China School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing210044China Department of Information Management Chaoyang University of TechnologyTaichung41349TaiwanChina Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou350118China Faculty of Electrical Engineering and Computer Science VŠB-Technical University of OstravaOstrava70833Czech Republic

Data clustering is an essential technique for analyzing complex datasets and continues to be a central research topic in data *** clustering algorithms,such as K-means,are widely used due to their simplicity and *** paper proposes a novel Spiral Mechanism-Optimized Phasmatodea Population Evolution Algorithm(SPPE)to improve clustering *** SPPE algorithm introduces several enhancements to the standard Phasmatodea Population Evolution(PPE)***,a Variable Neighborhood Search(VNS)factor is incorporated to strengthen the local search capability and foster population ***,a position update model,incorporating a spiral mechanism,is designed to improve the algorithm’s global exploration and convergence ***,a dynamic balancing factor,guided by fitness values,adjusts the search process to balance exploration and exploitation *** performance of SPPE is first validated on CEC2013 benchmark functions,where it demonstrates excellent convergence speed and superior optimization results compared to several state-of-the-art metaheuristic *** further verify its practical applicability,SPPE is combined with the K-means algorithm for data clustering and tested on seven *** results show that SPPE-K-means improves clustering accuracy,reduces dependency on initialization,and outperforms other clustering *** study highlights SPPE’s robustness and efficiency in solving both optimization and clustering challenges,making it a promising tool for complex data analysis tasks.

关键词： Phasmatodea population evolution algorithm data clustering meta-heuristic algorithm

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Predict of the Hidden Drug Interactions Based on Similarity Utilizing the Knowledge Graph

Predict of the Hidden Drug Interactions Based on Similarity ...

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2024 International Conference on computer and Applications, ICCA 2024

作者： Elfiky, Mariam Gamal Ghoniemy, Samy Eldin, Ahmed Sharaf University of Hertfordshire hosted by Gaf Dept. of Information Technology Management for Business Cairo Egypt Galala University Faculty of Computer Science and Engineering Cairo Egypt Sinai University Faculty of Information Technology and Computer Science Cairo Egypt

ISBN: (纸本)9798350367560

Drug-drug interactions (DDIs) can significantly impact treatment outcomes by causing adverse effects or reducing therapeutic efficacy. Whereas many DDIs are already known, there are numerous hidden interactions. Therefore, this study tries to predict unknown interactions based on drug structure and target information from the Drug Bank dataset. This paper trains the random forest model integrated with a knowledge graph on a dataset containing 922 unique drugs and 731,196 drug interactions. To illustrate the complex interactions between these drugs, we created a knowledge graph with Neo4j. This graph integrates information gathered from the dataset and extracts relevant data using Cypher queries. The inference engine was created according to the model's predictions on unknown DDIs. The random forest model, with an F1-score of 0.82, achieved a recall of 0.99 and a precision of 0.70. Also, 34,580 potential DDIs were extracted from the sample dataset of drugs. By embedding the knowledge network, our inference engine significantly enhanced predicting the hidden interactions and was found strong in the balance of precision and recall. Our research is applicable to the enhancement of drug safety and effectiveness via mitigating potential DDIs by identifying them. © 2024 IEEE.

关键词： Knowledge graph

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