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A New Metaheuristic Approach to Solving Benchmark Problems: Hybrid Salp Swarm Jaya Algorithm

computers, Materials & Continua 2022年第5期71卷 2923-2941页

作者： Erkan Erdemir Adem Alpaslan Altun Department of Information Technologies Tokat Vocational and Technical Anatolian High SchoolMerkez/Tokat60030Turkey Department of Computer Engineering Faculty of TechnologyKonya Selcuk UniversitySelcuklu/Konya42130Turkey

Metaheuristic algorithms are one of the methods used to solve optimization problems and find global or close to optimal solutions at a reasonable computational *** with other types of algorithms,in metaheuristic algorithms,one of the methods used to improve performance and achieve results closer to the target result is the hybridization of *** this study,a hybrid algorithm(HSSJAYA)consisting of salp swarm algorithm(SSA)and jaya algorithm(JAYA)is *** speed of achieving the global optimum of SSA,its simplicity,easy hybridization and JAYA’s success in achieving the best solution have given us the idea of creating a powerful hybrid algorithm from these two *** hybrid algorithm is based on SSA’s leader and follower salp system and JAYA’s best and worst solution *** works according to the best and worst food source *** this way,it is thought that the leader-follower salps will find the best solution to reach the food *** hybrid algorithm has been tested in 14 unimodal and 21 multimodal benchmark *** results were compared with SSA,JAYA,cuckoo search algorithm(CS),firefly algorithm(FFA)and genetic algorithm(GA).As a result,a hybrid algorithm that provided results closer to the desired fitness value in benchmark functions was *** addition,these results were statistically compared using wilcoxon rank sum test with other *** to the statistical results obtained from the results of the benchmark functions,it was determined that HSSJAYA creates a statistically significant difference in most of the problems compared to other algorithms.

关键词： Metaheuristic optimization benchmark algorithm swarm hybrid

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Gender Identification Using Marginalised Stacked Denoising Autoencoders on Twitter Data

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Intelligent Automation & Soft Computing 2023年第6期36卷 2529-2544页

作者： Badriyya B.Al-onazi Mohamed K.Nour Hassan Alshamrani Mesfer Al Duhayyim Heba Mohsen Amgad Atta Abdelmageed Gouse Pasha Mohammed Abu Sarwar Zamani Department of Language Preparation Arabic Language Teaching InstitutePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversityMakkah24211Saudi Arabia Department of Teachers Training Arabic Linguistics InstituteKing Saud UniversityP.O.BOX 145111RiyadhZIP 4545Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj16733Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Gender analysis of Twitter could reveal significant socio-cultural differ-ences between female and male *** had been made to analyze and auto-matically infer gender formerly for more commonly spoken languages’content,but,as we now know that limited work is being undertaken for *** of the research works are done mainly for English and least amount of effort for non-English *** study for Arabic demographic inference like gen-der is relatively uncommon for social networking users,especially for ***,this study aims to design an optimal marginalized stacked denoising autoencoder for gender identification on Arabic Twitter(OMSDAE-GIAT)*** presented OMSDAE-GIAR technique mainly concentrates on the identifica-tion and classification of gender exist in the Twitter *** attain this,the OMS-DAE-GIAT model derives initial stages of data pre-processing and word ***,the MSDAE model is exploited for the identification of gender into two classes namely male and *** the final stage,the OMSDAE-GIAT technique uses enhanced bat optimization algorithm(EBOA)for parameter tuning process,showing the novelty of our *** performance validation of the OMSDAE-GIAT model is inspected against an Arabic corpus dataset and the results are measured under distinct *** comparison study reported the enhanced performance of the OMSDAE-GIAT model over other recent approaches.

关键词： Arabic twitter gender identification bat algorithm hybrid deep learning social media arabic corpus

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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm

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computers, Materials & Continua 2022年第8期72卷 2175-2190页

作者： Mustafa Musa Jaber Salman Yussof Amer S.Elameer Leong Yeng Weng Sura Khalil Abd Anand Nayyar Institute of Informatics and Computing in Energy Universiti Tenaga NasionalMalaysia Department of Computer Science Dijlah University CollageBaghdad10021Iraq Biomedical Informatics College University of Information Technology and CommunicationsBaghdadIraq Faculty of Information Technology Duy Tan UniversityDa Nang550000Viet Nam Graduate School Duy Tan UniversityDa Nang550000Viet Nam Department of Computer Science Al-turath University CollegeBaghdadIraq

Artificial intelligence plays an essential role in the medical and health *** convolution networks offer valuable services and help create automated systems to perform medical image ***,convolution networks examine medical images effectively;such systems require high computational complexity when recognizing the same disease-affected ***,an optimized deep convolution network is utilized for analyzing disease-affected regions in this *** disease-relatedmedical images are selected and examined pixel by pixel;this analysis uses the gray wolf optimized deep learning *** method identifies affected pixels by the gray wolf hunting *** convolution network uses an automatic learning function that predicts the disease affected by previous imaging *** optimized algorithm-based selected regions are further examined using the distribution pattern-matching *** pattern-matching process recognizes the disease effectively,and the system’s efficiency is evaluated using theMATLAB implementation *** process ensures high accuracy of up to 99.02%to 99.37%and reduces computational complexity.

关键词： Artificial intelligence medical field gray wolf-optimized deep convolution networks distribution pattern-matching rule

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Analyzing Land Cover and Land Use Changes Using Remote Sensing Techniques: A Temporal Analysis of Climate Change Detection with Google Earth Engine 22

Analyzing Land Cover and Land Use Changes Using Remote Sensi...

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22nd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2023

作者： Afzal, Mozina Ali, Kamran Kasi, Mumraiz Khan Ur Rehman, Masood Khoshkholgh, Mohammad Ali Haq, Bushra Shah, Syed Ahmed Balochistan University of Information Technology Engineering and Management Sciences Quetta Pakistan Middlesex University Faculty of Science and Technology London United Kingdom Balochistan University of Information Technology Engineering and Management Sciences Department of Computer Science Quetta Pakistan University of Glasgow Department of Electronic Engineering Glasgow United Kingdom Lahore University of Management Sciences Lahore Pakistan

ISBN: (纸本)9798350381993

The detection of changes in land cover and land use (LCLU) is crucial for various geospatial applications, including urban development and environmental management. One vital aspect of LCLU research involves identifying modifications in impervious surface cover, which has significantly increased due to global economic growth and the rising urban population in many parts of the world. This investigation employs Landsat 9 OLI- 2/TIRS-2 imagery with a 30m spatial resolution to map structures in the Ziarat District of Pakistan, encompassing forests, water bodies, and barren land. It aims to detect changes in tree cover and canopy height. A time series of Landsat 9 OLI-2/TIRS-2 images were utilized to create change detection and land cover maps. The Analysis of Land Cover and Land Use (LCLU) for the Ziarat District was conducted using the GEE platform. The satellite images were classified into broad land cover classes, which include impervious surfaces, forest/tree cover, grassland/cropland, and water. The generated change detection map facilitates the identification of locations that have undergone modifications due to new constructions, offering valuable insights for the implementation of urban development policies and disaster management on a global scale. © 2023 IEEE.

关键词： Land use

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Enhanced Broad Siamese Network for Facial Emotion Recognition in Human-Robot Interaction

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2021年第5期2卷 413-423页

作者： Li, Yikai Zhang, Tong Philip Chen, C.L. The School of Computer Sciences and Engineering South China University of Technology Guangzhou510006 China The Pazhou Lab Guangzhou510335 China The Department of Computer and Information Science Faculty of Science and Technology University of Macau China

Robotics is one important domain of artificial intelligence applications. Proliferation of robotics makes our lives more convenient and colorful. Emotion recognition is one important task for a robot to communicate with human beings. Although different works have been proposed to complete the task of emotion recognition, conventional methods often require a lot of time and memory resources. Since a robot is often required to react timely and equipped with limited resources, we propose an enhanced Siamese network algorithm to resolve such a problem. We combine Siamese network with broad learning system while further improving mechanism of similarity metric. Experiment results show that our method can achieve a comparable performance to conventional deep learning method while reducing consumption of computing time and memory resources. © 2021 IEEE.

关键词： Emotion Recognition

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Security Analysis of Industrial Control S7 Protocol based on Peach 23

Security Analysis of Industrial Control S7 Protocol based on...

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9th International Conference on Computing and Data Engineering, ICCDE 2023

作者： Shen, Quanjiang Wang, Liangliang Zhang, Lei Wang, Binbin Liu, Chang Sha, Junyi Department of Information Technology State Grid Shanghai Electric Power Research Institute Shanghai China College of Computer Science and Technology Shanghai University of Electric Power Shanghai China

ISBN: (纸本)9781450398022

The normal operation of industrial control system (ICS) is the fundamental to ensure the stable production of industry. However, the existence of loopholes in ICS seriously threatens the normal operation of ICS. Fuzzy testing technology is one of the important technical means to find undisclosed vulnerabilities. This paper is based on the peach framework. Firstly, this paper excavates the vulnerabilities of HTTP protocol, and then this method is applied to the 0xf0 function code of industrial control S7 protocol. The results show that this method is effective in the vulnerability discovery of industrial control protocol. © 2023 ACM.

关键词： Hypertext systems

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Reduction of Microarray Data Dimensions to Enhance Performance of Naïve Bayes in Classification

Reduction of Microarray Data Dimensions to Enhance Performan...

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science and information technology in Smart Administration (ICSINTESA), International Conference of

作者： Putri Tsatsabila Ramadhani Erna Budhiarti Nababan Syahril Efendi Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

ISBN: (数字)9798350376111

ISBN: (纸本)9798350376128

According to data Global Burden of Cancer Survey (Globocan) by World Health Organization (WHO) in 2018 there were 18.1 million new cases with a death rate of 9.6 million deaths, where 1 in 8 men and 1 in 11 women died of cancer. The death rate could be prevented with a comprehensive management system that starts with early detection, prevention, and treatment [2]. In the study of microarray data for cancer early detection, the properties of high-dimensional data, small sample sizes, and noise, must be treated seriously because they can affect the classifier’s performance. This is critical for dealing with the curse of dimensionality and the inability to identify important information hidden in microarray data. Therefore, we propose PCA method for dimensionality reduction of microarray data to support Naive Bayes algorithm to complish classification tasks. Based on the studies we conducted, we discovered an increases of performance classification where the accuracy achieved is $\mathbf{9 2. 1 1 \%}$, precision $\mathbf{9 0. 2 0 \%}$ and the $\mathbf{f 1}$-score is $\mathbf{9 3. 8 8 \%}$ for ovarian cancer and prostate cancer had the accuracy is 93.55%, precision and $\mathbf{f 1 -}$ score reached $\mathbf{9 2. 8 6 \%}$.

关键词： Surveys Obituaries Accuracy Prevention and mitigation Noise Organizations Naive Bayes methods Prostate cancer Principal component analysis Ovarian cancer

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IoT-Based Water Quality Monitoring and Detection system 1

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2nd International Conference on Emerging Trends in Expert Applications and Security, ICETEAS 2023

作者： Kanchana, M. Gopirajan, P.V. Sureshkumar, K. Sudharsanan, R. Suganthi, N. Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai603203 India Department of Computational Intelligence School of Computing SRM Institute of Science and Technology Kattankulathur Campus Chennai603203 India Department of Information Technology Saveetha Engineering College Chennai602105 India Department of Information Technology SRM Institute of Science and Technology Ramapuram Chennai600089 India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai600089 India

ISBN: (数字)9789819919093

ISBN: (纸本)9789819919086

This paper suggests Internet of things (IoT) and Arduino-based tele-water quality monitoring systems integrated with the web application. The most critical component of the Wireless Sensor Network includes a microcontroller for processing the circuit's sensor data, a communication system between and within node communication, and a few other sensors such as pH, Microbial Fuel Cell (MFC), humidity, and temperature. All data is collected at the Arduino (data which is sensed by the sensors) by using remote monitoring and Internet of things technology (ESP8622MOD). The real-time data is transmitted, and that data is displayed by sending through the cloud in a human interface format on a server device (pc/mobile) by the web or mobile applications. The main objective is to get a water monitoring system with high mobility (the ability to check water more freely, the ability to check wherever required), high frequency, and low power (as it is compatible, we can take and check quickly). Therefore, our main objective is that our system will immensely help people with small water reservoirs, water mines, and villagers/ framers with fields to become conscious/aware of polluted water and stop contaminating the water. The deciding parameters of water, whether toxic or drinkable, are decided by the potential level of hydrogen value. If the hydrogen value is less than five, it is acidic, and if the hydrogen value is above 7.5, then it is primary. The MFC sensor, if the analogy sensor, senses any electricity from the cathode and anode ends (0–200 indicates acidic water, 200–300 is normal water, and above 300 is essential to water);by this water, we decide whether water toxic in nature and temperature and humidity also plays a role in determining the quality, it can result in an effect on the level of O2. Also, the capacity of organisms to resist certain pollutants, so different conditions should have different water temperatures. © 2023, The Author(s), under exclusive license to Spr

关键词： Internet of things

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Analysis Implementation of Chatbots to Increase Knowledge of Stunting Prevention in Indonesian Society with Bibliometric 9

Analysis Implementation of Chatbots to Increase Knowledge of...

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9th International Conference on information Management and technology, ICIMTech 2024

作者： Sutedja, Indrajani Handayani, Lutfi Maryuni Hendry Faisal, Mohammad Reza School of Information Sytems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Midwifery Study Program Binawan University Faculty of Nursing and Midwifery Jakarta13630 Indonesia Satya Wacana Christian University Faculty of Information Technology Salatiga50711 Indonesia FMIPA Lambung Mangkurat University Department of Computer Science Banjarmasin70123 Indonesia

ISBN: (纸本)9798350390025

The healthcare industry uses AI, because it is more efficient. In Indonesia, the accuracy of measurements and transmission of children's growth and development is often wrong. Many small hospitals usually don't have length measuring equipment, so the results are inaccurate. This research aims to determine the effectiveness of the stunting prevention program in Indonesia using an information system. The methodology used is a qualitative method, to conduct subjective research and analysis. The results of the research are to improve the website/mobile application information system which can display a child's growth and development history and simple educational information related to nutrition. Digital recording methods can speed up the process of updating data with a central database in real time. The value of this research is to reach the public to utilize technology and obtain personalized and interactive information directly to individuals. The theoretical implications of this research focus on information dissemination and understanding how chatbots influence knowledge acquisition and behavior change in the context of stunting prevention can contribute to advancing these theories in the field of public health. Managerial implications can provide cost effectiveness as Chatbots offer potentially cost-effective solutions and data-driven insights where managers can leverage chatbot analytics. © 2024 IEEE.

关键词： Artificial Intelligent Indonesian information system Stunting stunting stunting chatbot and bibliometric stunting prevention VOS Viewer

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Visual Programming Concept for Infineon XMC Series Microcontrollers

Visual Programming Concept for Infineon XMC Series Microcont...

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Proceedings of the International Convention MIPRO

作者： Lukrecia Vulić Luka Kaučić Ivan Aleksi Tomislav Matić Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9798350382501

ISBN: (纸本)9798350382518

In today’s modern world, efficient programming is a necessity. To speed up code generation nowadays, programming code is generated using different graphical tools. Although efficient, this technology is scarcely used in embedded system development. In this paper, we present a procedure for block-based visual programming with applications in embedded systems development. We present several examples of blocks using the Blockly open-source visual programming tool and test the implementation on selected Infineon XMC-based boards. The presented programming solution shows successful implementation of block-based visual programming in embedded systems development.

关键词： Visualization Embedded systems Codes Microcontrollers Programming

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