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International Conference on Mobile Computing and Ubiquitous Networking (ICMU)

作者： Wei-Teng Chang Ben-Jye Chang Graduate School of Engineering Science and Technology National Yunlin University of Science and Technology Yunlin Taiwan ROC Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan ROC

New trends of extremely ultra-low delay, ultra-high reliability, long-distance high-moving, etc., are strongly required for achieving Emergency rescue, Active Safe Driving (ASD), LEO communications, etc. In 3GPP, 5G/B5G specifies flexible numerology technology providing different frequency SCS modes with different slot-times for diverse types of flows. In 5G/B5G, SDN-based flowing using different numerology SCS modes definitely requires an efficient flow scheduling. However, flow scheduling is an open issue and challenge excluded in 5G/B5G. Thus, this paper proposes an Extended Sigmoid-based Cost-based Flow Scheduling (eSCFS) approach to dynamically differentiate flow priorities to minimize delay and maximize radio RB utilization in 5G/B5G NR. Numerical results indicate that the proposed eSCFS outperforms the compared approaches in network delay, jitter, resource utilization, network net-profit. Consequently, this paper achieves obvious contributions: proposing vRB state-related dynamic flow scheduling to maximize network efficiency.

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Survey of Online Exam Proctoring Model to Detect Cheating Behavior based on Face Recognition

Survey of Online Exam Proctoring Model to Detect Cheating Be...

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International Conference on Systems and Informatics (ICSAI)

作者： Sucianna Ghadati Rabiha Iman Herwidiana Kartowisastro Reina Setiawan Widodo Budiharto Computer Science Department BINUS Graduate Program – Computer Science. Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Computer Science. Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Computer Science. Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665474498

Exams are an important component of any educational program, including online education. In any test, there is a possibility of cheating, so its detection and prevention is important. This study aims to conduct an in-depth study of the online exam monitoring model approach based on facial recognition used to detect cheating. Based on the inclusion and exclusion criteria designed, 13 selected studies were obtained. From these studies, we conducted further analysis regarding the Face Detection Method, Face Recognition Method, Initial Feature, Behavior Analysis and Evaluation Metrics used in each study so as to provide answers to research questions. the most frequently used Face detection method was Viola-Jones with a presentation of 20%, then CNN and MTCNN with a total presentation of 21%. The most widely used face recognition method in selected studies is CNN and metrics Accuracy is one of the most frequently used evaluations with a percentage of 33%. While the features that are usually used to detect cheating during online exams include facial motion and head pose which occupies the first position. The second is eye movement, then multiple faces gaze estimation and facial expression is in third place. Other features that also play a role in analyzing cheating behavior are mouth detection, facial vector, landmark location, gesture and posture.

关键词： Measurement Analytical models Face recognition Mouth Estimation Feature extraction Behavioral sciences

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Role of Fuzzy Approach towards Fault Detection for Distributed Components

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computers, Materials & Continua 2021年第5期67卷 1979-1996页

作者： Yaser Hafeez Sadia Ali Nz Jhanjhi Mamoona Humayun Anand Nayyar Mehedi Masud University Institute of Information Technology Pir Mehr Ali Shah Arid Agriculture UniversityRawalpindiPakistan School of Computer Science and Engineering SCETaylor’s UniversitySubang JayaMalaysia Department of Information systems College of Computer and Information SciencesJouf UniversitySaudi Arabia Graduate School Duy Tan UniversityDa Nang550000Viet Nam Faculty of Information Technology Duy Tan UniversityDa Nang550000Viet Nam Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Component-based software development is rapidly introducing numerous new paradigms and possibilities to deliver highly customized software in a distributed *** other communication,teamwork,and coordination problems in global software development,the detection of faults is seen as the key ***,there is a need to ensure the reliability of component-based applications *** device detection faults applied to tracked components from various sources and failed to keep track of all the large number of components from different *** this study,we propose an approach for fault detection from componentbased systems requirements using the fuzzy logic approach and historical information during acceptance *** approach identified error-prone components selection for test case extraction and for prioritization of test cases to validate components in acceptance *** the evaluation,we used empirical study,and results depicted that the proposed approach significantly outperforms in component selection and acceptance *** comparison to the conventional procedures,i.e.,requirement criteria,and communication coverage criteria without irrelevancy and redundancy successfully outperform other ***,the F-measures of the proposed approach define the accurate selection of components,and faults identification increases in components using the proposed approach were higher(i.e.,more than 80 percent)than requirement criteria,and code coverage criteria procedures(i.e.,less than 80 percent),***,the rate of fault detection in the proposed approach increases,i.e.,92.80 compared to existing methods i.e.,less than 80 *** proposed approach will provide a comprehensive guideline and roadmap for practitioners and researchers.

关键词： Component-based software selection acceptance testing fault detection

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Apache Spark Powered: Enhancing Network Intrusion Detection System Using Random Forest

Apache Spark Powered: Enhancing Network Intrusion Detection ...

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Novel Intelligent and Leading Emerging sciences Conference (NILES)

作者： Hesham Mamdouh Mohamed Tarek Abdelrahman Radwan Adel Saeed Ahmed Abdeen Monier Ashraf Khaled M. Fouad Ibrahim Abdelbaky School of Engineering and Applied Science (EAS) Nile University Giza Egypt CS program School of Information Technology and Computer Science (ITCS) Nile University Giza Egypt Faculty of Computer Science and Engineering New Mansoura University Artificial Intelligence Department Faculty of Computers and Artificial Intelligence Benha University Banha Egypt

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378528

The increasing sophistication of cyber attacks necessitates effective intrusion detection systems. We propose a novel intrusion detection method integrating deep learning with big data management using Apache Spark. Leveraging the comprehensive CSE-CIC-IDS2018 dataset, we apply extensive data preprocessing, including handling missing and unreliable values, duplicates, and redundant columns. In addition, implementation of a Random Forest based feature importance approach is derived to prioritize the most impactful Features. Furthermore, stratified k-fold cross-validation is used for a model selection process on a class-imbalanced dataset. Our weighted Random Forest classifier achieves a remarkable weighted average F1-score of 0.999 and a test inference time of 0.673 seconds using only the top 34 features, outperforming previous studies without sampling techniques. The proposed architecture offers a scalable and accurate solution for intrusion detection in cloud architectures, demonstrating the effectiveness of combining deep learning and big data technologies for cybersecurity.

关键词： Deep learning Cloud computing Data preprocessing Network intrusion detection Cluster computing Forestry Big Data Random forests Cyberattack Testing

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Mobile Application as Community Social Media

Mobile Application as Community Social Media

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International Conference on Inventive Computation Technologies (ICICT)

作者： Teuku Ryan Pahlevi Johannes Haryanto Rahmat Adha Bayu Alfian Harco Leslie Hendric Spits Warnars Rahayu Widiono Computer Science Department School of Computer Science. Bina Nusantara University Jakarta Indonesia Information Systems department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Binus Online Learning Bina Nusantara University Jakarta Indonesia

To day's society is different from the past, where the speed of the internet is getting more sophisticated, and the existing gadget technology is getting faster, and of course, this is also changing the lifestyle of today's people, which of course almost half of their daily life is spent in front of gadgets. On the one hand, this is undoubtedly very good and supports humans in carrying out their daily life activities, but on the other hand, this raises new problems where humans start to lack time to communicate and socialize with each other and often making them stressed and anxious because they are already tired and do not know how to socialize anymore. This paper begins with a model and implementation of a very simple mobile application that behaves as a social media inspired by *** as a social media for academics. The design of this mobile application is done by using use case diagrams to describe existing processes and class diagrams to describe class relationships.

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A Data Analysis Method Using Orthogonal Transformation in a Reproducing Kernel Hilbert Space

A Data Analysis Method Using Orthogonal Transformation in a ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Lingxiao Qu Yan Pei Jianqiang Li Graduate School of Computer Science and Engineering University of Aizu Aizuwakamatsu Fukushima Japan Faculty of Information Technology Beijing University of Technology Beijing China

We propose a data analysis method that combines the objectives of nonlinear principal component analysis and nonlinear discriminant analysis with the kernel method in a reproducing kernel Hilbert space. This method addresses nonlinear data analysis problems in high-dimensional spaces, specifically the reproducing kernel Hilbert space, through the use of the kernel trick. Our proposed method can be considered as a semi-supervised data analysis approach. We evaluate our proposed method using various kernel functions and datasets, both visually and quantitatively. The evaluation results demonstrate that our proposal outperforms kernel principal component analysis and generalized discriminant analysis in terms of classification performance. This indicates the advantages and originality of our proposed method. Furthermore, we analyze and discuss our findings based on the evaluation results, and highlight potential areas for further research and future work related to our proposal.

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Machine Learning Implementations in Childhood Stunting Research: A Systematic Literature Review

Machine Learning Implementations in Childhood Stunting Resea...

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International Conference on information Management and Technology (ICIMTech)

作者： Reza Rahutomo Gregorius Natanael Elwirehardja Mahmud Isnan Faisal Asadi Bens Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Childhood stunting is a condition anticipated to affect the growth potential of children under the age of five. With numerous stunting researches that have been conducted, stunting datasets are now widely available to facilitate stunting research. This provides an opportunity to implement machine learning (ML) principles to produce a broader insight or a novel technique in stunting prediction. A systematic literature review is necessary to discover the landscape of machine learning implementation in the application domain as a preliminary study for creating an effective research roadmap. This paper presents a systematic literature review (SLR) of 22 curated manuscripts that focuses on identifying the ML models applied in stunting research, as well as the datasets used in such studies that were published during 2017–2022. The SLR process found that ML principles have been applied in stunting research since 2017, and the diversity of ML implementation has become more varied in 2021–2022. In terms of ML models, XGBoost and Random Forest are recognized as the two most utilized models, and stunting prediction is the most common ML implementation. The majority of stunting research utilizing ML has been conducted in Indonesia. Although national survey data has been the most commonly utilized dataset in stunting research, researchers in Indonesia have shown a preference for utilizing data from regional or independent surveys. This study will be followed by developing a classifier model for stunted children using XGBoost and Random Forest algorithms. The model will be trained on a dataset generated from StuntingDB.

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Azimuthally and radially polarized beams generated in a helical fiber grating 22

Azimuthally and radially polarized beams generated in a heli...

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Optical Components and Materials XXII 2025

作者： Meng, Zhang Wang, Peng Zhao, Hua Li, Hongpu Graduate School of Science and Technology Shizuoka University Johoku 3-5-1 Chuo-Ku Hamamatsu 432-8561 Japan School of the Electronic Engineering Nanjing Xiaozhuang University Nanjing 211171 China School of the Computer and Electronic Information Nanjing Normal University Nanjing 210023 China Faculty of the Engineering Shizuoka University Johoku 3-5-1 Chuo-Ku Hamamatsu 432-8561 Japan

ISBN: (纸本)9781510684720

Azimuthally polarized (AP) and radially polarized (RP) beams are the two common types of cylindrical vector beam that has a spatially varying polarization distribution. In this study, an efficient method allowing the flexible generation of the azimuthally and radially polarized beams has been proposed and experimentally demonstrated, which is realized by using a helical fiber grating with an intermediate-period (HFG). To the best of our knowledge, this is the first time that such two kinds of cylindrical vector beams can be flexibly generated by using only one fiber component, i.e., the HFG. The proposed method provides the potential application of the HFG to not only the laser processing but also the optical tweezer, and the optical manipulator as well. © 2025 SPIE.

关键词： Azimuthally polarized beam cylindrical vector modes helical fiber grating radially polarized beam

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IoT-Based Warehouse Management System

IoT-Based Warehouse Management System

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2022 International Conference on Cyber Resilience, ICCR 2022

作者： Hasan, Mohammad Kamrul Junjie, Ma Ahasan Habib, A.K.M. Al Mamun, Abdullah Ghazal, Taher M. Saeed, Rashid A. Faculty of Information Science and Technology Selango Bangi43600 Malaysia UKM-Graduate School of Business Universiti Kebangsaan Malaysia Malaysia School of Information Technology Skyline University College Sharjah1797 United Arab Emirates College of Computers and Information Technology Taif University Department of Computer Engineering Taif21944 Saudi Arabia

ISBN: (纸本)9781665461221

Warehouse management system is important for the daily production and storage of materials. The traditional manual counting and operation methods are still used;it is inefficient and prone to errors. This article mainly studies the warehouse management system based on the Internet of Things (IoT). The system's design is web-based and uses radio frequency identification (RFID) technology to build a complete warehouse management system. Hypertext Preprocessor (PHP) and MySQL are mainly used and connected with web page RFID readers. The methodology used is the incremental model. This system can improve warehouse management efficiency, reduce data loss, and reduce labor costs. © 2022 IEEE.

关键词： Websites

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Pilot study of using transcranial temporal interfering theta-burst stimulation for modulating motor excitability in rat

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Journal of Neuroengineering and Rehabilitation 2024年第1期21卷 147页

作者： Wu, Chun-Wei Lin, Bor-Shing Zhang, Zhao Hsieh, Tsung-Hsun Liou, Jian-Chiun Lo, Wei-Lun Li, Yu-Ting Chiu, Shao-Chu Peng, Chih-Wei School of Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei 11031 Taiwan Department of Computer Science and Information Engineering National Taipei University New Taipei City 237303 Taiwan School of Mechanical and Electrical Engineering Wuyi University Fujian Province Wuyishan City China School of Physical Therapy and Graduate Institute of Rehabilitation Science College of Medicine Chang Gung University Taoyuan Taiwan Neuroscience Research Center Chang Gung Memorial Hospital Linkou Taiwan Department of Surgery Division of Neurosurgery Shuang Ho Hospital Taipei Medical University New Taipei City Taiwan Department of Surgery School of Medicine College of Medicine Taipei Medical University Taipei Taiwan Taiwan Instrument Research Institute National Applied Research Laboratories Hsinchu Taiwan School of Gerontology and Long-Term Care College of Nursing Taipei Medical University Taipei Taiwan Graduate Institute of Biomedical Optomechatronics College of Biomedical Engineering Taipei Medical University Taipei 11031 Taiwan

Transcranial temporal interference stimulation (tTIS) is a promising brain stimulation method that can target deep brain regions by delivering an interfering current from surface electrodes. Most instances of tTIS stimulate the brain with a single-frequency sinusoidal waveform generated by wave interference. Theta burst stimulation is an effective stimulation scheme that can modulate neuroplasticity by generating long-term potentiation- or depression-like effects. To broaden tTIS application, we developed a theta burst protocol using tTIS technique to modulate neuroplasticity in rats. Two cannula electrodes were unilaterally implanted into the intact skull over the primary motor cortex. Electrical field of temporal interference envelopes generated by tTIS through cannula electrodes were recorded from primary motor cortex. Theta burst schemes were characterized, and motor activation induced by the stimulation was also evaluated simultaneously by observing electromyographic signals from the corresponding brachioradialis muscle. After validating the stimulation scheme, we further tested the modulatory effects of theta burst stimulation delivered by tTIS and by conventional transcranial electrical stimulation on primary motor cortex excitability. Changes in the amplitude of motor evoked potentials, elicited when the primary motor cortex was activated by electrical pulses, were measured before and after theta burst stimulation by both techniques. Significant potentiation and suppression were found at 15 to 30 min after the intermittent and continuous theta burst stimulation delivered using tTIS, respectively. However, comparing to theta burst stimulations delivered using conventional form of transcranial electrical stimulation, using tTIS expressed no significant difference in modulating motor evoked potential amplitudes. Sham treatment from both methods had no effect on changing the motor evoked potential amplitude. The present study demonstrated the feasibility of usin

关键词： Brain stimulation Motor evoked potential Neuroplasticity Theta burst stimulation Transcranial electrical stimulation Transcranial temporal interference stimulation

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