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Enhancing Organizational Performance: Synergy of Cyber-Physical Systems, Cloud Services, and Crowdsensing

International Journal of Crowd science 2025年第1期9卷 44-55页

作者： Al-Qerem, Ahmad Ali, Ali Mohd Nabot, Ahmad Jebreen, Issam Alauthman, Mohammad Alangari, Someah Aburub, Faisal Aldweesh, Amjad Computer Science Department Faculty of Information Technology Zarqa University Zarqa13110 Jordan Communications and Computer Engineering Department Faculty of Engineering Al-Ahliyya Amman University Amman19328 Jordan Department of Information Security University of Petra Amman11196 Jordan Department of Computer Science College of Science and Humanities Dawadmi Shaqra University Shaqra11911 Saudi Arabia Department of Business Intelligence and Data Analytics University of Petra Amman11196 Jordan College of Computing and Information Technology Shaqra University Shaqra11911 Saudi Arabia

In the contemporary business landscape, software has evolved into a strategic asset crucial for organizations seeking sustainable competitive advantage. The imperative of ensuring software quality becomes evident as low-quality software systems pose formidable challenges to organizational performance. This study delves into the profound impact of three key dimensions of information system quality on organizational performance—information quality (IQ), quality of service (QoS), and software quality (SQ). Anchored in the DeLone and McLean information system (IS) success model, a quantitative questionnaire was administered to 360 industry experts and academics. Rigorous data analysis, employing exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM), revealed significant positive effects of all three quality dimensions on organizational performance. Among these dimensions, software quality emerged as the most influential, showcasing substantial total effects, closely followed by information and service qualities. The study underscores the tangible value derived from strategic investments in enhancing software, information, and service quality. Elevating these facets manifests as a catalyst for improved organizational performance, empowering decision-makers with accurate and timely information while enhancing user satisfaction with the system. This research contributes significantly to the IS success literature by empirically validating the synergistic relationship between information quality, service quality, software quality, and organizational outcomes. The systematic analysis offered in this study goes beyond theoretical validation, providing actionable insights for managers. The findings guide the prioritization of quality initiatives and resource allocation, enabling organizations to maximize competitive advantage. As a future research direction, investigating moderator influences and exploring alternate qualit

关键词： data quality

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Arabic Pilgrim Services dataset: Creating and Analysis 1

Arabic Pilgrim Services Dataset: Creating and Analysis

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

作者： Al-Barhamtoshy, Hassanin M. Himdi, Hanen T. Alyahya, Mohamad King Abdulaziz University Faculty of Computer & Information Technology IT Department Jeddah Saudi Arabia University of Jeddah Faculty of Computer and Engineering Computer Science & Artificial Intelligence Department Jeddah Saudi Arabia

ISBN: (纸本)9781665472753

With Countless Arabic news articles published daily;users have become increasingly concerned about obtaining news from credible sources. Nonetheless, to individuals, credible news sources are associated with certain countries where users have faith. Therefore, detecting the source of a news article is imperative to fake news detection and enables users a better trust in their consuming news. This paper introduces to create, filter, analyze, and evaluate a domain services-specific Arabic dataset for pilgrims. The Arabic Pilgrim Services (ArPiS) dataset is a collection of approximately 30,000 news, collected across three different Arabic countries and regions. The paper presents a creation for pilgrims' opinions measurement services dataset for text mining, text classification, clustering, and text summarization. The default basic search methods start with 124 web sites of Arabic news. Then, many of filtering features have been done to limit the dataset by pilgrim subjected services. A lot of topics are addressed, and a lot of filter with a discussion group have been made with many opinions| and extra comments. The huge of the collected data need some kind of additional effort and more analysis to produce valuable dataset. Balanced dataset is one of this extra effort, we are going to create. Therefore, the collected and annotated dataset represents real news for pilgrims' services. So, we need to build additional quantity of these data to be fake news. Accordingly, a precondition procedure invoked as a methodology to create and then annotate such dataset. © 2023 IEEE.

关键词： Classification (of information)

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Vision transformer for detecting traffic congestion using image mapping

Advances in Transportation Studies

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Advances in Transportation Studies 2025年 66卷 19-38页

作者： Khalfi, A. Guerroumi, M. Haid, T. Laradji, N. Faculty of Computer Science Artificial Intelligence and Data Science Department University of Science and Technology Houari Boumediene Algiers Algeria Matter Sciences and Computer Science Faculty Department of Computer Science University of Djilali Bounaama Khemis Miliana Algeria

Leveraging advanced computer vision techniques, we present a novel method for analyzing and categorizing traffic videos by utilizing an image mapping technique combined with a UniVit (Unit Vision Transformer) model. First, video data is transformed into an image dataset, where each frame undergoes a mapping process based on vehicle detection using the YOLOv8s algorithm. These mapped images are then input into a vision transformer, which utilizes attention mechanisms to identify and analyze complex patterns across frames. The approach is evaluated on the UCSD (University of California San Diego) dataset, which features diverse weather conditions such as clear, overcast, and rainy scenarios, enabling a rigorous assessment under varied environments. Our method achieves a notable accuracy score of 99.89%, surpassing previous approaches on the UCSD benchmark. This improvement underscores the effectiveness of combining image mapping with advanced vision transformers, suggesting promising applications for intelligent traffic management systems aimed at mitigating traffic issues. © 2025, Aracne Editrice. All rights reserved.

关键词： Photomapping

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Assessment of Musculoskeletal Loads in Three Types of Body Posture According to Dolphens 21st

Assessment of Musculoskeletal Loads in Three Types of Body ...

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21st Scientific Conference on Medical and Sport Technologies, 2024

作者： Nowakowska-Lipiec, Katarzyna Sośniak, Paulina Zadoń, Hanna Jochymczyk-Woźniak, Katarzyna Bibrowicz, Karol Szurmik, Tomasz Mitas, Andrzej W. Michnik, Robert Department of Biomechatronics Faculty of Biomedical Engineering Silesian University of Technology Roosevelta 40 Zabrze41-800 Poland Faculty of Biomedical Engineering Students Scientific Circle "Biokreatywni" Silesian University of Technology Zabrze Poland Science and Research Center of Body Posture College of Education and Therapy in Poznań Poznań Poland Faculty of Arts and Educational Science University of Silesia Cieszyn Poland Department of Medical Informatics and Artificial Intelligence Faculty of Biomedical Engineering Silesian University of Technology Zabrze Poland

ISBN: (纸本)9783031821424

This study aimed to evaluate the effect of body posture type according to the Dolphens on musculoskeletal loads. There are three types of posture: neutral, swayback and lordotic according to Dolphens classification. The study involved a group of 29 subjects. Assessment of body posture was carried out using the Posture Photographic Assessment System. The following parameters were measured for each subject: pelvic tilt angle, lumbosacral and thoracolumbar tilt, upper kyphosis tilt angle. The position of the joints and individual body segments in relation to the vertical axis, the position of the centre of mass of the body and the values of the ground reaction forces were determined. The results obtained provided the input for the modelling of the posture of each person in the AnyBody Modelling System. A full-body Standing Model was used. The model was scaled to the weight and height of each subject. The highest values of lumbar loads were observed in subjects with a kyphotic posture. For those with a kyphotic posture, the average resultant force at the L5-S1 level was 0.97 ± 0.31 BW (BW - body weight). For those with a lordotic posture it was 0.87 ± 0.27 BW and for those with a neutral posture it was 0.86 ± 0.15 BW. Subjects with a kyphotic posture had the highest values for the compressive component of the force at the L5-S1 joint (0.96 ± 0.31 BW). The highest shear force values were obtained for the lordotic posture (0.1 ± 0.04 BW). The study also assessed the force values of the abdominal and dorsal muscles. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Physiological models

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The Quest for Fairness: A Comparative Study of Accuracy in AI Hiring Systems 3

The Quest for Fairness: A Comparative Study of Accuracy in A...

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3rd IEEE Asian Conference on Innovation in technology, ASIANCON 2023

作者： D'Souza, Jason Kadam, Vedant Shinde, Pranali Saxena, Kumkum Thadomal Shahani Engineering College Information Technology Department Mumbai India Thadomal Shahani Engineering College Artificial Intelligence and Data Science Department Mumbai India Thadomal Shahani Engineering College Computer Engineering Department Mumbai India

ISBN: (纸本)9798350302288

artificial intelligence and Machine Learning based models are increasingly being used in developing models for automating recruitment systems in various Multinational Companies as well as small-scale and developing companies and industries. With the advent of Generative artificial intelligence models, many companies are turning towards automatic and AI-based hiring software. J.P. Morgan uses HireVue, Deloitte incorporates Hiretual for talent sourcing and engagement, IBM incorporates *** for automated interview scheduling and many more. But in all these systems a major factor to consider is the biasness in the models and how to detect them and efficiently mitigate them. Some models unwillingly sometimes amplify the biases in the models and results in faulty and biased predictions which can lead to the inaccurate matching of profiles to the job description and result in wayward hiring processes. The biasness can be based on the parameters such as gender, address, etc., or biasness transferred from the programmer into the model while creating the model which is called unconscious bias. The models implemented in the research are Random Forest, Decision Tree, KNN Tree, AdaBoost, and XGBoost. The accuracies for the models Random Forest, Decision Tree, KNN Tree, AdaBoost, and XGBoost were 0.80, 0.81, 0.81, 0.78, and 0.84 respectively. © 2023 IEEE.

关键词： Decision trees

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Self Defence and Safety Monitoring System 4

Self Defence and Safety Monitoring System

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4th International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022

作者： Suhas, M.L. Kashyap, Akshat Devadiga, Dhanush Ghoshal, Manish Roopashree, S. Deemed-to-be University Artificial Intelligence and Machine Learning Faculty of Engineering and Technology Jain Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9781665474368

In the modern world, the safety of women has been compromised. Domestic violence, sexual assault, and murder against women are more common than they are supposed to be. Women's safety is a major concern in India and there are many laws and measures in place to stop them, but the number of such incidents is only increasing by the day. This is not just limited to women as men face a lot of harassment too. In response to these problems, we aim to create a smart safety device that provides some security to the user. Many such smart devices are already available in the market but are not proven to be effective and often provide serious damage to the attacker. We aim to create a safety device that is capable of alerting the user or taking actions automatically without or with very little involvement from the user to activate it. This helps when there is a situation where the user doesn't get enough time to react. Different models available are analysed and the proposed solution is explained in detail. The drawbacks and future works are also included in the article. © 2022 IEEE.

关键词： Emotion Recognition

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Dynamic Key Generationfor Secure File Sharing System Using Time Stamp

Dynamic Key Generationfor Secure File Sharing System Using T...

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2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Annie Silviya, S.H. Hilda Jerlin, C.M. Mohana Suganthi, N. Helen Sathiya, V. Jayashree, R. Oviya, N. Rajalakshmi Institute of Technology Chennai India Artificial Intelligence and Data Science Panimalar Engineering College Chennai India School of Computing Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Chennai India Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai India

ISBN: (纸本)9798331543617

Dynamic key generation for secure file sharing system using timestamp is a novel approach to military-based secure file sharing, which adds an additional layer of security to AES-2S6 which is prominently considered as the military-grade encryption. It is designed to enhance the confidentiality and integrity of transmitted files. When a Sender uploads a file, the system prompts for a character, converts it to its ASCII value, adds the current system time value to it and utilizes this aggregated value as a unique code to secure the uploaded file. To retrieve a file, the user must possess either the file key or initiate the retrieval process during the exact time of the original upload or in the next precise clock cycle. The combination of these factors provides an extra layer of security, making unauthorized access significantly more challenging. © 2024 IEEE.

关键词： Cryptography Encryption File Sharing System Timestamp

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A Modified White Shark Optimizer for Gene Selection Optimization Problem

A Modified White Shark Optimizer for Gene Selection Optimiza...

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Cyber Resilience (ICCR), International Conference on

作者： Sharif Naser Makhadmeh Hussam N. Fakhouri Mohammed Azmi Al-Betar Data Science and Artificial Intelligence Department University of Petra Amman Jordan Data Science and Artificial Intelligence Department Faculty of Information Technology University of Petra Amman Jordan Artificial Intelligence Research Center (AIRC) Ajman University Ajman United Arab Emirates

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

This paper investigates the application of the White Shark Optimizer (WSO) to gene selection, a fundamental task in machine learning to analyze complex, high-dimensional data such as gene expressions derived from DNA microarray studies. The problem of gene selection is complicated by the presence of redundant and misleading genes that can reduce the effectiveness of machine learning models. We divided gene selection techniques into two categories: candidate-based and envelope-based, focusing on prominent methods such as Kullback-Leibler and Chi-square to measure the difference between the probability distributions. We focus on the novel WSO, which draws inspiration from the predatory strategies of white sharks, famous for their adaptability and efficiency in complex scenarios. The paper presents a modified version of WSO, tailored to the binary nature of gene selection, and evaluates its effectiveness against particle swarm optimization. The results highlight the superior accuracy and robustness of WSO, where the proposed WSO outperformed the compared method in obtaining the accuracy and fitness values of the three datasets.

关键词： High-dimensional data Sharks Machine learning Robustness Probability distribution Gene expression Particle swarm optimization

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Security Enhancement using Image verification method to Secure Docker Containers 4

Security Enhancement using Image verification method to Secu...

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4th International Conference on Information Management and Machine intelligence, ICIMMI 2022

作者： Saxena, Vivek Saxena, Deepika Singh, Uday Pratap Department of Computer Engineering Poornima Institute of Engineering and Technology India Department of Computer Science Engineering Poornima University India Department of Artificial Intelligence and Data Science Poornima Institute of Engineering and Technology India

ISBN: (纸本)9781450399937

Now with the dawn of the internet, cloud computing has been reformed by opening new horizons at an inclusive level with auspicious opportunities. With the rise of opportunities, popularity, and public connectivity by the internet, it is the next foremost edge for Trojans, worms, viruses, hackers and cyber-attacks will broaden because a hacker would see this as a new edge to try to steal confidential interrupt, information, services and route damage to the originality cloud computing Docker system. Security in Docker container over the cloud is of great anxiety hence care needs to be taken to provide secure Docker containers and secure cloud services. Docker is usual within the software development community due to the portability, versatility, and scalability of containers. In this paper, we analyze the Docker storage-based security and by applying the methods of Docker image verification, checking capabilities, and storage selection, improve the security in Docker containers. © 2022 ACM.

关键词： Containers

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MPFFNet:Semantic Segmentation of Remote Sensing Image Buildings Based on Multipath Feature Fusion 8

MPFFNet:Semantic Segmentation of Remote Sensing Image Buildi...

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8th International Conference on Communication, Image and Signal Processing, CCISP 2023

作者： Dong, Jie Mao, Jingkun Liu, Kun Cheng, Liangyong School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China Interplanetary Space Technology Development Co. LTD Tianjin China

ISBN: (纸本)9798350305838

The buildings with variable scales and complex background information in remote sensing images often result in missed and misclassified segmentation of buildings. To address this issue, this paper designs an multipath feature fusion network (MPFFNet). MPFFNet has an overall encoding and decoding structure, embedded with an residual depth Inception block(RDI) module to extract multi-scale features. At the same time, MPFFNet uses the multipath residual channel attention (MPRCA) module to expand the Receptive field of the feature map to obtain rich multi-scale context information. The validity of the proposed algorithm is proved on the WHU Buildings data set, with F1 reaching 94.70%, IOU reaching 89.93%, and Recall reaching 94.98%. © 2023 IEEE.

关键词： Buildings

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