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30th Telecommunications Forum, TELFOR 2022

作者： Milutinovic, Nemanja Gajevic, Masa Krstovic, Jelena Petrovic, Aleksandar Bacanin, Nebojsa Antonijevic, Milos Singidunum University Technical Faculty Belgrade Serbia Singidunum University Faculty of Informatics and Computing Belgrade Serbia

ISBN: (数字)9781665472739

ISBN: (纸本)9781665472739

In this paper, recently proposed arithmetic optimization algorithm for adopted for extreme learning machine tuning with the goal of improving security internet of things systems. One of the greatest challenges with extreme learning machine is finding initial values of weights and biases and determining satisfying number of neurons in the hidden layer for every particular task. To tackle this challenge, which is NP-hard by nature, the arithmetic optimization algorithm was employed. The proposed method was evaluated against ToN IoT Windows 10 dataset for internet of things security for binary classification, and compared to other extreme learning structures evolved by other state-of-the-art metaheuristics under the same experimental conditions. According to experimental findings, arithmetic optimization algorithm is a promising method for tuning extreme learning machine for this particular challenge. © 2022 IEEE.

关键词： Optimization

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Review of AI Technologies for Enhancing the Lives of Visually Impaired Individuals: Applications, Outcomes, and Future Directions

Review of AI Technologies for Enhancing the Lives of Visuall...

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2024 International Conference on Information and Communication Technology for Development for Africa, ICT4DA 2024

作者： Deriba, Fitsum Gizachew Wubineh, Betelhem Zewdu Teka, Mengistu Zenebe University of Eastern Finland School of Computing Yliopistokatu 2 JoensuuFI-80100 Finland Wroclaw University of Science and Technology Faculty of Information and Communication Technology Wroclaw Poland Wachemo University School of Computing and Informatics Hosaena Ethiopia

ISBN: (纸本)9798331527792

Imagine an environment where individuals with disabilities enjoy a significantly improved quality of life, not only because of the support they receive but also due to advancements in artificial intelligence (AI). While existing studies focus on exploring specific aspects of AI technologies for visually impaired (VI) individuals, there is limited research exploring the outcomes of designed and implemented AI technologies on these individuals. This study examines the current state of AI technologies in supporting VI individuals. We systematically reviewed 263 articles published between 2008 and 2023, of which 33 met the inclusion criteria for our study. This rigorous selection process ensured that only the relevant studies conducted with AI technology for VI were included in our analysis. The results identified several applications developed for various purposes, predominantly 45% focused on AI technology for independent navigation, followed by technology that addresses daily activities issues (21%). Our findings indicate that limited AI technologies have been developed for educational purposes and use in finance and e-commerce. The outcomes of using AI technology demonstrate improvements in navigation and mobility, as well as enhanced independence and quality of life. While our study identifies gaps in existing AI technology for VI, it also contributes to various stakeholders, including developers, users, and researchers, by providing a comprehensive understanding of the current state of AI technology for individuals with VI. © 2024 IEEE.

关键词： Assistive technology

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A MLP-Mixer and mixture of expert model for remaining useful life prediction of lithium-ion batteries

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Frontiers of Computer Science 2024年第5期18卷 1-10页

作者： Lingling ZHAO Shitao SONG Pengyan WANG Chunyu WANG Junjie WANG Maozu GUO Faculty of Computing Harbin Institute of TechnologyHarbin 150001China School of Electrical Engineering Liaoning University of TechnologyJinzhou 121004China School of Computer Science Northeast Electric Power UniversityJilin 132000China Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing 211166China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China

Accurately predicting the Remaining Useful Life(RUL)of lithium-ion batteries is crucial for battery management *** learning-based methods have been shown to be effective in predicting RUL by leveraging battery capacity time series ***,the representation learning of features such as long-distance sequence dependencies and mutations in capacity time series still needs to be *** address this challenge,this paper proposes a novel deep learning model,the MLP-Mixer and Mixture of Expert(MMMe)model,for RUL *** MMMe model leverages the Gated Recurrent Unit and Multi-Head Attention mechanism to encode the sequential data of battery capacity to capture the temporal features and a re-zero MLP-Mixer model to capture the high-level ***,we devise an ensemble predictor based on a Mixture-of-Experts(MoE)architecture to generate reliable RUL *** experimental results on public datasets demonstrate that our proposed model significantly outperforms other existing methods,providing more reliable and precise RUL predictions while also accurately tracking the capacity degradation *** code and dataset are available at the website of github.

关键词： lithium-ion battery remaining useful life deep learning MLP-Mixer mixture-of-experts

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Early Detection of Alzheimer’s Disease Based on Laplacian Re-Decomposition and XGBoosting

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Computer Systems Science & Engineering 2023年第9期46卷 2773-2795页

作者： Hala Ahmed Hassan Soliman Shaker El-Sappagh Tamer Abuhmed Mohammed Elmogy Information Technology Department Faculty of Computers and InformationMansoura UniversityMansoura35511Egypt Faculty of Computer Science and Engineering Galala UniversitySuez435611Egypt Faculty of Computers and Artificial Intelligence Benha UniversityBanha13518Egypt College of Computing and Informatics Sungkyunkwan UniversitySuwonKorea

The precise diagnosis of Alzheimer’s disease is critical for patient treatment,especially at the early stage,because awareness of the severity and progression risks lets patients take preventative actions before irreversible brain damage *** is possible to gain a holistic view of Alzheimer’s disease staging by combining multiple data modalities,known as image *** this paper,the study proposes the early detection of Alzheimer’s disease using different modalities of Alzheimer’s disease brain ***,the preprocessing was performed on the ***,the data augmentation techniques are used to handle ***,the skull is removed to lead to good *** the second phase,two fusion stages are used:pixel level(early fusion)and feature level(late fusion).We fused magnetic resonance imaging and positron emission tomography images using early fusion(Laplacian Re-Decomposition)and late fusion(Canonical Correlation Analysis).The proposed system used magnetic resonance imaging and positron emission tomography to take advantage of *** resonance imaging system’s primary benefits are providing images with excellent spatial resolution and structural information for specific *** emission tomography images can provide functional information and the metabolisms of particular *** characteristic helps clinicians detect diseases and tumor progression at an early ***,the feature extraction of fused images is extracted using a convolutional neural *** the case of late fusion,the features are extracted first and then ***,the proposed system performs XGB to classify Alzheimer’s *** system’s performance was evaluated using accuracy,specificity,and *** medical data were retrieved in the 2D format of 256×256 *** classifiers were optimized to achieve the final results:for the decision tree,the maximum depth of a tree was *** best number of trees for the random forest was 60;for

关键词： Alzheimer’s disease(AD) machine learning(ML) image fusion Laplacian Re-decomposition(LRD) XGBoosting

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Extreme learning machine tuning by original sine cosine algorithm

Extreme learning machine tuning by original sine cosine algo...

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2022 IEEE World Conference on Applied Intelligence and computing, AIC 2022

作者： Salb, Mohamed Bacanin, Nebojsa Zivkovic, Miodrag Antonijevic, Milos Marjanovic, Marina Strumberger, Ivana Singidunum University Faculty of Informatics and Computing Belgrade Serbia Singidunum University Technical Faculty Belgrade Serbia

ISBN: (数字)9781665479882

ISBN: (纸本)9781509050017

Extreme learning machine (ELM) is a revolutionary approach for training single-hidden layer feedforward neural networks that combines both high performance and rapid learning speed. Because the input weights and hidden neurons biases are randomly initialized and stay fixed during the process of learning, and the output weights are analytically calculated. ELM produces high generalization capability with a huge number of hidden neurons. The sine cosine method was presented in this study for tuning the input weights and hidden biases. The suggested method is named SCA-ELM, and it selects the input weights and hidden biases using SCA while determining the output weights using the Moore-Penrose (MP) generalized inverse, The aim is to improve the original extreme learning machine *** suggested methodologies were evaluated on several benchmark classification data sets, and compared with other recent state-of-art algorithms. Simulations reveal that the suggested method outperforms the other alternatives in the comparative analysis. © 2022 IEEE.

关键词： Swarm intelligence

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A Review of Machine Learning Botnet Detection Techniques based on Network Traffic Log

A Review of Machine Learning Botnet Detection Techniques bas...

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2022 IEEE International Conference on computing, ICOCO 2022

作者： Ibrahim, Zul-Azri Razali, Rina Azlin Ismail, Saiful Adli Azhar, Iman Hakimi Khairil Rahim, Fiza Abdul Azilan, Ahmad Muzafaraidil Ahmad Institute of Informatics and Computing in Energy College of Computing and Informatics Universiti Tenaga Nasional Selangor Kajang Malaysia Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia Wilayah Persekutuan Kuala Lumpur Kuala Lumpur Malaysia Universiti Tenaga Nasional Department of Computing College of Computing and Informatics Selangor Kajang Malaysia

ISBN: (纸本)9781665489966

Cyber-attacks are a common issue in this modern era because of the introduction of high-speed networks and the use of new technologies like Internet of Things (IoT) devices, which fuel the rapid expansion of cyber-attack. One of the common cyber-attacks is botnet attacks. Hackers use botnet attacks to exploit newly discovered vulnerabilities in order to conduct intensive scraping, distributed denial of service (DDoS) attacks, and other large-scale cybercrime. With their adaptable and dynamic character, botnets work with a botmaster to plan their activities, modify their codes, and update the bots regularly to avoid detection. Researchers use numerous techniques to detect the botnet. However, botmasters nowadays have improved due to avoiding security in detection. As the communication can leave traces that allow researchers to detect the botnet's existence, this paper will review 15 related works on botnet detection that utilize machine learning to predict the botnet communication with the command-and-control (C&C or C2) center based on the network traffic log. This paper summarizes the related works based on the dataset, environment, botnet type, features employed, and machine learning techniques. © 2022 IEEE.

关键词： Botnet

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Authentication Methods that use Haptic and Audio: A Review 8

Authentication Methods that use Haptic and Audio: A Review

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8th International Cryptology and Information Security Conference 2022, CRYPTOLOGY2022

作者： Kam, Yvonne Hwei-Syn Chin, Ji-Jian Faculty of Engineering Multimedia University Selangor Malaysia Faculty of Computing & Informatics Multimedia University Selangor Malaysia

Authentication is an important step for many applications eg. banking, communications etc. Identity theft can happen because the systems that we use are vulnerable to observation attacks both by a person (shoulder surfing) and also video recordings. Thus authentication methods that rely on the visual channel alone, which are displayed onscreen are more susceptible to shoulder surfing. In this paper, a review of haptic and audio authentication methods is presented where we describe and analyse various methods that utilise non-visual channels, namely haptic and audio, for authentication. We categorise the methods into the categories of recall, recognition and challenge-response. We focus on the security aspects of the methods, comparing the susceptibility of the methods to various attacks. The review indicates that most haptic and audio methods are less susceptible to observation attacks and intersection attacks. © 2022 Institute for Mathematical Research (INSPEM). All rights reserved.

关键词： Authentication

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B2A, A Straight-Through Approach from Basics to Advanced Level: Case Study for Python Course 11

B2A, A Straight-Through Approach from Basics to Advanced Lev...

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11th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2024

作者： Shazmeen, Abbasi Dakić, Pavle Zoltan, Alwahab Dhulfiqar Department of Programming Languages and Compilers Faculty of Informatics Eötvös Loránd University 1/C Pázmány Péter st. BudapestH-1117 Hungary Faculty of Informatics and Computing Singidunum University Danijelova 32 Belgrade Serbia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava842 16 Slovakia

In this study, we present a straightforward teaching strategy for teaching the Python programming language. Our method emphasizes a clear progression from fundamental to sophisticated concepts. Beginning with a thorough explanation of core Python ideas, we show a beginner-level script that dissects each line of code and displays the results. One distinguishing feature of our system is that students use ChatGPT to optimize code, which encourages them to improve the core program with fewer lines. After getting the updated solutions, students carefully compare the original and optimized programs to discover improvements and potential flaws. This study underlines the effectiveness of the Straight-Through Approach, which focuses on improving Python understanding while also developing critical thinking and code optimization skills. Our findings show that this strategy is a simple and effective way for teachers to assist students in growing from basic to advanced Python abilities, resulting in a dynamic and successful learning environment. The proposed technique will teach students how to use AI-driven modules correctly, such as ChatGPT. © 2024 Copyright for this paper by its authors.

关键词： Python

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Towards Optimizing the Logistic Transportation Selection in Hajj 1

Towards Optimizing the Logistic Transportation Selection in ...

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1st International Conference on Logistics, ICL 2024

作者： Mohamed, Marwa F. Elsherif, Samiha M. Eltoukhy, Mohamed Meselhy Suez Canal University Faculty of Computers and Informatics Computer Sciences Department Ismailia Egypt Suez Canal University Faculty of Computers and Informatics Information Systems Department Ismailia Egypt College of Computing and Information Technology at Khulais University of Jeddah Department of Information Technology Jeddah Saudi Arabia

ISBN: (纸本)9798331518844

The Hajj is an international Islamic event that takes place in Mecca, Saudi Arabia, annually and attracts millions of pilgrims. One of the most important services during the Hajj period is pilgrims' transportation services, they transport pilgrims between the holy sites (e.g., walking facilities, traditional buses, shuttle buses, and the holy sites train). The shuttle bus, among these services, is the busiest for Hajj. It operates during the Hajj and transports most of the pilgrims. For example, during the first Muzdalifah holiday, when on the ninth-day pilgrims move from Arafat to Muzdalifah, the transportation serves more than one million pilgrims. Therefore, there are many transportation companies, and choosing an appropriate company is one of the most important challenges facing Hajj organizers. There are many criteria for selecting transportation companies, such as cost and service quality;therefore, this paper presents a framework that uses the NSGA-III optimization algorithm to choose the best companies based on two objectives (e.g., costs and quality of service). The results of NSGA-III have been compared with heuristic algorithms (e.g., best fit and first fit), and NSGA-III outperformed these algorithms. © 2024 IEEE.

关键词： Bus transportation

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Model of Visualization and Analytics for Open Data (Case: Election Voters & Kids Disability Category) 1

Model of Visualization and Analytics for Open Data (Case: El...

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1st International Conference in Advanced Innovation on Smart City, ICAISC 2023

作者： Wibowo, Ripto Mukti Fakieh, Bahjat Ramzan, Muhammad Sher Alzahrani, Ahmed Saeed Siddiqui, Muazzam Alzahrani, Bander King Abdulaziz University Faculty of Computing and Information Technology Department of Information Systems Saudi Arabia King Abdulaziz University Faculty of Computing and Information Technology Department of Computer Science Saudi Arabia Indiana University Luddy School of Informatics Computing and Engineering Bloomington United States

ISBN: (纸本)9781665472753

Several regional head elections had to be postponed due to the pandemic, including in Indonesia because of the COVID-19 pandemic. Several big cities in Indonesia are of concern because of their large population and GDP. This study conducts analysis and testing of datasets taken from Open Data in a city in Indonesia. In addition to conducting research on regional head elections, we also present information on voters from the category of kids with disabilities. The steps used in this research are using regional mapping data of the city of Surabaya in the Election of the Regional Head. Download the data or dataset for the Regional Head Election ampersand Categories of kids with disabilities. Based on the dataset voters from the category of children with disabilities are more than 5 *** this research, we use Python to process our datasets & Big Data technology. Data cleaning or cleansing, Exploratory Data Analysis, and Empirical Cumulative Distribution Functions (ECDF) in python are also needed. Result from ECDF chart with steady increase (increment of 0.1). The highest variance value is in Electoral District 5 = 6.090 and the lowest value is in Electoral District 4 = 0.90. The result of Open Data is graphical data visualization and candidate scores to help as an alternative for the 2024 Regional Head Election and the Category of kids with disabilities. © 2023 IEEE.

关键词： Open Data

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