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Cloud computing Adoption by Small and Medium Enterprises Based on DOI and TOE Theory 9

Cloud Computing Adoption by Small and Medium Enterprises Bas...

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9th international conference on Cloud computing and Big Data Analytics, ICCCBDA 2024

作者： Xie, Shuyi Zuo, Yuxin Deng, Guohua School of Business Jianghan University Wuhan China Institute of Intelligent Decision-Making Jianghan University Wuhan China Manufacturing Industry Development Research Centre on Wuhan City Circle Wuhan China

ISBN: (纸本)9798350373554

In order to identify the key factors influencing small and medium enterprises (SMEs) adoption of cloud computing, a cloud computing adoption model for SMEs was constructed based on the diffusion of innovation (DOI) theory and the technology-organization-environment (TOE) framework. A questionnaire-based survey was used to collect data from 136 firms (SMEs) in central China. The results showed that top management support, technology readies and regulatory support have a significant influence on the adoption of cloud computing and external pressure has an indirect effect on it, however relative advantages, complexity, perceived risk, firm size and sensitivity & criticality of business have no significant influence on it. The research help firms consider their evaluation and investment for cloud computing project and also offer service providers with a better understanding of what effects cloud computing adoption, with relevant insight on current designs and promotions. © 2024 ieee.

关键词： Cloud computing

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Data-Enhanced Prediction with Decomposition and Amplitude-Aware Permutation Entropy in Distributed computing Systems

Data-Enhanced Prediction with Decomposition and Amplitude-Aw...

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2024 ieee international conference on Systems, Man, and Cybernetics, SMC 2024

作者： Yuan, Haitao Hu, Qinglong Bi, Jing Zhang, Wei Zhang, Jia Zhou, MengChu School of Automation Science and Electrical Engineering Beihang University Beijing100191 China City University of Hong Kong Dept. of Computer Science 999077 Hong Kong College of Computer Beijing University of Technology Beijing100124 China University of Connecticut Dept. of Computer Science and Engineering StorrsCT06269 United States Southern Methodist University Dept. of Computer Science DallasTX75275 United States New Jersey Institute of Technology Dept. of Electrical and Computer Engineering NewarkNJ07102 United States

ISBN: (纸本)9781665410205

In recent years, distributed computing has wit-nessed widespread applications across numerous organizations. Predicting workload and computing resource data can facilitate proactive service operation management, leading to substantial improvements in quality of service and cost efficiency. However, these data often exhibit non-linearity, high volatility, and inter-dependencies across different categories, presenting challenges for accurate forecasting. Consequently, there is a critical need to develop a method that thoroughly and comprehensively analyzes all available data to forecast future trends effectively. This work proposes a novel integrated data-enhanced prediction model named SVI for achieving high-accuracy workload prediction in distributed computing systems. SVI employs the Savitzky-Golay filter and variational mode decomposition for feature processing, whose features are subsequently utilized by Informer for multivariate joint analysis of the enhanced data, achieving high-precision prediction. Ablation and comparative experiments with advanced prediction models are conducted on the Google cluster trace and other typical datasets. Realistic data-driven results indicate that SVI improves the prediction accuracy by 35.4% compared to the original Informer, with each module contributing to the performance enhancement. Furthermore, compared with Autoformer, SVI enhances the prediction accuracy of workload, CPU, and memory by 62.5%, 65.6%, and 69.1 %, respectively. © 2024 ieee.

关键词： Quality of service

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Knowledge Management Process and Innovation Capabilities in the Software Engineering Sector in Sri Lanka 4

Knowledge Management Process and Innovation Capabilities in ...

引用

4th international conference on advanced Research in computing, ICARC 2024

作者： Wickramasinghe, Samanthi Thilakarathne, Chathuni Hettiarachchi, Sunesh School of Computing Esoft Metro Campus Colombo Sri Lanka Faculty of It Horizon Campus Malabe Sri Lanka Tech Computers Pepiliyana Sri Lanka

ISBN: (纸本)9798350384864

A number of technological developments, including those in the areas of artificial intelligence, machine learning, and the internet of things, have contributed to the fast expansion of software engineering. It is essential for businesses to have this sector since it makes it possible to automate processes, reduces expenses, and enhances customer satisfaction by connecting different capabilities. There will be 28.7 million software engineers working around the globe by the year 2024. By the year 2027, it is anticipated that the market would have reached a total value of 1039 million. On the other hand, the imbalance between supply and demand in the sector is the primary factor that is driving the need for outsourcing solutions. The sector is currently confronted with significant challenges that are associated with capacity, information sharing, and priority problems. Software engineers in Sri Lanka have difficulties in locating developers with the necessary skills and in adjusting to the quickly changing technical environment. It is vital that the industry shift its focus from providing services to manufacturing tangible items in order to achieve growth and generate positive cash flows. An empirical investigation was undertaken to examine the correlation between knowledge management and innovation capabilities in the software engineering industry of Sri Lanka. The findings demonstrated a robust and affirmative association between the capacity for innovation and the processes of generating, disseminating, and implementing knowledge. The regression model showed that knowledge creation, transfer, and application are influenced by innovation capabilities, with 86% of the variance of innovation capabilities being attributed to these factors. © 2024 ieee.

关键词： Software engineering

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Prefabricated Buildings for Smart Cities: A Literature Survey 12

Prefabricated Buildings for Smart Cities: A Literature Surve...

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12th international conference on advanced Cloud and Big Data, CBD 2024

作者： Hu, Xingchen Shen, Jun Ma, Zhenjun School of Computing and Information Technology University of Wollongong Wollongong Australia University of Wollongong Wollongong Australia

ISBN: (纸本)9798331511074

Prefabricated buildings are becoming a focal point in smart city development indebted to their many advantages. To assess the current research status of prefabricated buildings and understand their suitability for smart cities, this paper surveyed papers from the Web of Science and conducted bibliometric analysis to identify the main research themes of prefabricated buildings. Then, a comprehensive review of smart city-oriented prefabricated buildings is undertaken from the perspective of each phase of their life cycle. The result indicates that underlying data collection, modeling or analysis methods such as the Internet of Things (IoT), digital twin, machine learning, and artificial intelligence (AI) are the main interests in recent literature. On the other hand, the current research on prefabricated buildings is recently shifting toward a higher degree of intelligence and digitalization. Facilitated by information and communication technology (ICT) and big data techniques, prefabricated buildings make integration into smart cities more feasible. Additionally, this paper highlights the shortcomings in the current research on prefabricated buildings and suggests directions for future work. © 2024 ieee.

关键词： Smart homes

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A Methodical Approach to Healthcare Cybersecurity: Handling current Risks and Advancements 6

A Methodical Approach to Healthcare Cybersecurity: Handling ...

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6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Husain Bathushaw, M. Nagasundaram, S. Department of Computer Applications VELS Institute of Science Technology and Advanced Studies Pallavaram Chennai600117 India

ISBN: (纸本)9798331522667

The methods were evaluated using machine learning-driven interruption detection, blockchain-enhanced access control for inconsistency localization, and structured threat insight data in a simulated healthcare environment. With an accuracy range of 0.88-0.94 and lift specified between 0.75 and 1, knowledge values ranging from.86 to.92, and F1 scores between and above, the test results demonstrated that all computations were possible. BACA strengthened access control with blockchain;ADA surpassed expectations in identifying discrepancies;TIAA succeeded in risk insights management;and ML-IDS achieved outstanding results in intrusion detection. A comparison with related research highlights the significance of these algorithms in tackling specific cybersecurity issues in the healthcare sector. Because the proposed algorithms provide a holistic approach to safeguard confidential health information, ensure the validity of assessment models, and strengthen organizations against a range of dynamic cyberthreats, they are pertinent to the expanding discussion about cybersecurity in the healthcare industry. © 2025 ieee.

关键词： Electronic health record

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EduGuard - Mobile Application for Sex Education and Sexual Harassment Reporting for Sri Lanka 6

EduGuard - Mobile Application for Sex Education and Sexual H...

引用

6th international conference on Advancements in computing, ICAC 2024

作者： Udapolawatta, Sithmi Perera, Nimesha Perera, Kalya Henarath, Sajith Samarakoon, Uthpala Pandithage, Dinithi Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9798331517878

The lack of comprehensive sex education for Sri Lankans and inadequate systems for reporting sexual harassment are significant problems in the current society. These issues lead to limited awareness, compromised safety, and poor health outcomes. Many individuals lack access to accurate information and resources, exacerbating the risks associated with sexual health and safety. Addressing these gaps is crucial for fostering a well-informed and secure community. In this research, we introduce Eduguard, a mobile application aimed at improving sex education and sexual harassment reporting in Sri Lanka. This comprehensive approach addresses significant gaps in education and safety, promoting awareness and health through advanced technology. Eduguard features four key components: an age-appropriate sex education platform using face recognition, a sexual harassment reporting system utilizing voice recognition for discreet reporting, a blog and questionnaire platform with Natural Language Processing (NLP) for content filtering, and a sexually transmitted disease detection module employing image processing for early diagnosis. In conclusion, Eduguard represents a pioneering solution that combines education, safety, and health through the use of advanced technology. Its impact is substantial, offering a replicable model for regions facing similar challenges. © 2024 ieee.

关键词： Face recognition

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Enhanced Detection and Classification of PCB Defects Utilizing advanced YOLO Architectures 3

Enhanced Detection and Classification of PCB Defects Utilizi...

引用

3rd international conference on trends in Electrical, Electronics and Computer Engineering, TEECCON 2024

作者： Roshan, Vidhun Bardia, Viksith Prabu, M. Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Tamil Nadu Chennai India

ISBN: (纸本)9798331505714

In rapidly growing industries, speed and accuracy in manufacturing products has become paramount. In electronics production, particularly in Printed Circuit Boards (PCBs), detecting and classifying defects is crucial to ensuring product reliability and quality. PCBs are highly sophisticated, and defects are often imperceptible to the naked eye. To address this challenge, various data augmentation techniques were applied to the dataset to enhance model training. These techniques enabled the model to learn essential features, facilitating faster defect localization and classification into different categories. This research presents an advanced methodology for PCB defect detection using the latest version of YOLO (You Only Look Once) integrated with specialized enhancements. These enhancements include the Convolutional Block Attention Module (CBAM), an attention mechanism, and an Intersection over Union (IoU) based loss function. These additions significantly improve the model's ability to accurately detect defects by minimizing false negatives. Experimental evaluations were conducted with YOLO versions 8, 9, and 10, demonstrating that integrating CBAM and the IoU loss function yields promising results compared to traditional YOLO models. This paper provides manufacturing companies with a powerful mechanism to enhance efficiency and product quality through automated PCB defect detection techniques. © 2024 ieee.

关键词： Deep learning

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A Deep and Systematic Review of the Intrusion Detection Systems Based on Machine Learning and Deep Learning Techniques 10

A Deep and Systematic Review of the Intrusion Detection Syst...

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10th international conference on advanced computing and Communication Systems, ICACCS 2024

作者： Guhan, N.K. Ravindran, Sindhu Ramachandran, M. Vijean, Vikneswaran Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Universiti Malaysia Perlis Kampus Alam UniMAP Faculty of Electronic Engineering & Technology Arau Pauh Putra Perlis Malaysia

ISBN: (纸本)9798350384369

Intrusion detection systems are the primitive elements in safeguarding vital infrastructures, which are able to identify malicious activity on hosts or networks. The efficient IDS must be able to handle a variety of threats is a difficult security cum threat related problems. Numerous strategies have been put out in the literature as of right now to increase intrusion detection efficiency while taking into account some of these restrictions, like mobility and resource limitations. This review paper discusses about the early research works on performed on IDS using Deep Learning and Machine Learning techniques. This paper provides a qualitative assessment of these methods and deeper insights about the analysis as well as a summary of the field's current themes and the methods used to train and implement IDSs. We address the overall limitations of these solutions, namely the types of attacks that these approaches are unable to identify and the setup limitations that are specific to each of these works, even though they offer insightful information and solutions for certain aspects of these constraints. © 2024 ieee.

关键词： Network intrusion

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current and Emerging trends in Python Programming Learning 9

Current and Emerging Trends in Python Programming Learning

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9th international STEM Education conference (ISTEM-Ed)

作者： Ahmad, Amir Ray, Santosh Nawaz, Ali United Arab Emirates Univ Coll Informat Technol Abu Dhabi U Arab Emirates Liwa Coll Fac Informat Technol Abu Dhabi U Arab Emirates

ISBN: (纸本)9798350365986;9798350365979

Programming skills are very important in the rapidly changing technological landscape of the modern world. Due to its versatile features, Python has been widely used in developing applications for modern computing devices. However, learners face challenges in finding appropriate learning paths and content among the frequently disorganized and varied contents available for learning Python. This article aims to help such learners find courses that best fit their unique requirements and learning goals by offering a clear and simple roadmap. The research presented in this article examines pedagogical approaches used by some of the popular institutions offering courses in Python. It also emphasizes the importance of websites as helpful resources for prospective Python learners. The article aims to provide a set of organized resources for those starting their Python programming adventure while keeping up with emerging trends in Python education by carefully analyzing various resources. The ultimate goal of the article is to provide students with the information and knowledge required to successfully traverse the evolving world of Python programming.

关键词： Python Digital education Pedagogy Teaching

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IoT-based automatic road accident detection systems: A review 4

IoT-based automatic road accident detection systems: A revie...

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4th international conference on Soft computing for Security Applications, ICSCSA 2024

作者： Prabu, C.R. Namitha, Kalakunnath Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798331515720

With the increasing number of vehicles on roads, the occurrence of road accidents has become a major concern globally. Automatic road accident detection systems based on Internet of Things (IoT) technologies have emerged as a promising solution to improve emergency response times and reduce the severity of accidents. The review encompasses various aspects including the underlying technologies, sensor networks, data processing algorithms, communication protocols, and system architectures used in these systems. Furthermore, the paper discusses the challenges and limitations of current approaches such as sensor accuracy, system scalability, and real-Time data processing. It also identifies future research directions including the integration of advanced sensor technologies, machine learning algorithms for accident prediction, and the development of standardized communication protocols for interoperability among different systems. To improve road safety, researchers and practitioners can use the ideas to help build IoT-based autonomous road accident detection systems that are more effective and efficient. © 2024 ieee.

关键词： Interoperability

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