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Immersive Learning Constructs for Deaf and Hard-of-Hearing Students in TVET Practical Skill

Immersive Learning Constructs for Deaf and Hard-of-Hearing S...

引用

2024 international Visualization, informatics and Technology conference, IVIT 2024

作者： Abdul Rahim, Rini Hafzah Mohd Nizam, Dinna Nina Mohd Naim, Nur Faraha Baharum, Aslina Universiti Malaysia Sabah User Experience Group Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia Sunway University Computing and Information System School of Engineering and Technology Selangor Malaysia

ISBN: (纸本)9798350354447

The advent of advanced educational technologies, and immersive learning utilizing virtual reality (VR), augmented reality (AR), and mixed reality (MR) have emerged as a powerful tool to enhance learning experiences. However, traditional approaches often lack the ability to address the unique needs of Deaf and Hard of Hearing (DHH) students, particularly in practical skill development. The usage of immersive learning for the purpose of DHH students is still limited, especially in Malaysia. This study explores critical elements of immersive learning environments designed to facilitate practical skill acquisition for DHH students. Using the systematic literature review (SLR) determines immersive practical skill learning elements from selected 34 papers to help DHH students learn more effectively. 30 constructs are highlighted in the SLR results as recommendations for creating immersive learning for DHH practical skills. It is thus intended that the highlighted features would contribute to both the process of teaching and learning as well as the enhancement of student performance. © 2024 ieee.

关键词： Contrastive Learning

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Analysis of the Applicability of Cloud computing Scaling Techniques for Real-Time Workloads of Industrial Control Systems 22

Analysis of the Applicability of Cloud Computing Scaling Tec...

引用

22nd ieee international conference on Industrial informatics, INDIN 2024

作者： Neumann, Rebekka Frick, Florian Lechler, Armin Verl, Alexander University of Stuttgart Stuttgart Germany

ISBN: (纸本)9798331527471

A key feature of cloud computing is elasticity, which enables resources to be allocated and de-allocated according to dynamic application demands. The evolution of Industrial Control Systems (ICS) is moving towards a distributed converged infrastructure that incorporates computing and communication resources as well as software, replacing dedicated hardware running control applications. While modern ICS and cloud environments share similarities, the corresponding applications differ significantly in their execution models and timing requirements. To enhance the flexibility of ICS, control applications must adapt to changing requirements throughout operation, resulting in varying workloads. The potential for dynamic scaling in ICS is considerable, but is not yet being fully exploited. The objective of this paper is to examine the extent to which state-of-the-art cloud autoscaling concepts are applicable to the scaling of real-time workloads and to propose enhancements to these concepts in order to enable the implementation of dynamic autoscaling of real-time workloads. In conclusion, the fundamental concept of cloud autoscaling can be applied, but must be extended, in particular to ensure deterministic resource provisioning and to improve task isolation in order to guarantee predictable task timing behaviour. © 2024 ieee.

关键词： Cloud platforms

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Human Resource Management of Small and Medium Enterprises Based on Cloud computing 1

Human Resource Management of Small and Medium Enterprises Ba...

引用

1st ieee international conference on Ambient Intelligence, Knowledge informatics and Industrial Electronics, AIKIIE 2023

作者： Wu, Wei Sichuan University Jinjiang College Sichuan Province Meishan City620860 China

ISBN: (纸本)9798350316469

The main contribution of this article is to design a human resource management system for small and medium-sized enterprises, which introduces salary design and performance evaluation to accurately evaluate the employees of the enterprise. Therefore, on the basis of cloud computing, this article provides convenience for human resource management of small and medium-sized enterprises, realizes innovation in human resource management models, and improves the utilization rate, efficiency, and cost savings of commodity resources. Using statistical analysis methods to study the effectiveness of cloud computing in human resource management of small and medium-sized enterprises. Based on the same evaluation criteria, cloud computing has improved efficiency and satisfaction in talent cultivation, performance management, salary management, human resource consulting services, shared services, and other aspects. Through experimental simulation, it can also be seen that when cloud computing is used, the efficiency of human resources has reached 94%, which is 4 percentage points higher than traditional human resource management. © 2023 ieee.

关键词： cloud computing Human resource management for small and medium-sized enterprises human resources small and medium-sized enterprises

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IoT-Enabled Smart Agriculture System Using Cognitive computing 3

IoT-Enabled Smart Agriculture System Using Cognitive Computi...

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international conference on Advances in computing, Communication and Applied informatics (ACCAI)

作者： Rajababu, Durgam Boddepalli, Eswararao Survase, Rajesh Bhaskar Pal, Arunabha Dandagala, Sreenivasulu Chakravarthi, M. Kalyan SR Univ Dept EEE Sch Engn Warangal Telangana India Virginia Tech Bradley Dept ECE Blacksburg VA USA Savitribai Phule Pune Univ ES Divekar Coll Varvand Dept Geog Pune Maharashtra India Centurion Univ Technol & Management MS Swaminathan Sch Agr Dept Soil Sci Parlakhemundi 761211 Odisha India Annamacharya Univ Annamacharya Inst Technol & Sci Dept Civil Engn Rajampet 516126 Andhra Pradesh India VIT AP Univ Sch Elect Engn Amaravathi 522237 Andhra Pradesh India

ISBN: (纸本)9798350389432;9798350389449;9798350389456

Together, the Internet of Things (IoT) and cognitive computing have revolutionized the agricultural industry by enabling the implementation of intelligent husbandry systems. Investigating the creation and use of an Internet of Things-enabled smart husbandry system that leverages cognitive computing techniques is the aim of this study. The system includes detectors to gather data on environmental factors like crop health, soil temperature, and humidity in real-time. After that, a centralized platform receives these data. This data is processed by algorithms used in cognitive computing to give growers useful insights like optimal irrigation timing and early detection of crop issues. The application of this method raises agricultural operations' productivity and enhances decision-making processes' effectiveness. This study covers the following topics: the system's armature;the choice and incorporation of Internet of Things bias;the use of cognitive computing models;and the assessment of system performance in actual agricultural scripts. The results show how cognitive computing and the Internet of Things (IoT) may revolutionize traditional husbandry methods into data-driven, intelligent husbandry systems.

关键词： IoT smart agriculture cognitive computing sensor networks data analytics precision farming

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Exploring Non-Functional Requirements in Requirements Engineering: A Systematic Review

Exploring Non-Functional Requirements in Requirements Engine...

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2024 ieee international conference on computing, ICOCO 2024

作者： Ramasamy, Rosaan Lim, Tek Yong Antdragon Sdn Bhd Negeri Sembilan Malaysia Faculty of Computing and Informatics Multimedia University Cyberjaya Malaysia

ISBN: (纸本)9798331530303

Non-functional requirements (NFRs) are often poorly documented and inadequately integrated into the software development process resulting in discrepancies between expected and actual system quality. This gap leads to a number of issues like requirement ambiguity, ineffective stakeholder communication and inadequate validation which severely impact project outcomes. This systematic review addresses these challenges by investigating the state of NFRs management in requirements engineering. The review identifies predominant techniques such as automated tools and document analysis for eliciting NFRs while also highlighting current challenges and effective validation practices, including inspections, reviews and user feedback. Future research should develop comprehensive frameworks combining technology with human-centered approaches to address these challenges. ©2024 ieee.

关键词： I. INTRODUCTION non-functional requirement requirements engineering systematic review

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Cognitive computing in Intelligent Traffic Management Systems 3

Cognitive Computing in Intelligent Traffic Management System...

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international conference on Advances in computing, Communication and Applied informatics (ACCAI)

作者： Sudhakar, A. V. V. Tyagi, Anuj Patil, Pallavi Sachin Kumar, K. Suresh Sathe, Manoj Geetha, B. T. SR Univ Sch Engn Dept EEE Warangal Telangana India Northeastern Univ Boston MA 02115 USA Savitribai Phule Pune Univ Genba Sopanrao Moze Coll Engn Dept Artificial Intelligence & Machine Learning Pune 45 Maharashtra India Panimalar Engn Coll Chennai 600123 Tamil Nadu India PES Modern Inst Business StudiesPune Comp Sci Pune Maharashtra India Saveetha Univ SIMATS Saveetha Sch Engn Dept ECE Chennai Tamil Nadu India

ISBN: (纸本)9798350389432;9798350389449;9798350389456

Intelligent business operation systems are undergoing a revolution as a result of cognitive computing, which is boosting their capacity to analyze large amounts of data and produce well-informed conclusions in real-time. The purpose of this investigation is to investigate the possibility of incorporating cognitive computing technologies, such as machine literacy, natural language processing, and big data analytics, into business operation systems to address the issue of civic traffic, improve the flow of business, and enhance safety. The development of adaptive business control mechanisms that can respond robustly to changing business situations is made possible by cognitive computing. This is accomplished through the use of sophisticated algorithms and predictive analytics. The purpose of this article is to investigate case studies and real-world implementations, to highlight the major improvements in company efficiency and decrease in travel times that may be realized using cognitive computing. The findings provide evidence that cognitive computing has the potential to transform conventional business operation systems into intelligent, responsive networks that are capable of tone-optimization. This would result in the creation of civic environments that are more intelligent and more environmentally sustainable.

关键词： Cognitive computing intelligent traffic management urban congestion adaptive traffic control predictive analytics

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A Data-driven Truck Dispatching Algorithm for a Sequence-constrained Less-than-truckload Container Transshipment Problem 22

A Data-driven Truck Dispatching Algorithm for a Sequence-con...

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22nd ieee international conference on Industrial informatics, INDIN 2024

作者： Gong, Jiahui Chen, Jianjun Qi, Jun Zhang, Haiyang Department of Computing Xi’an Jiaotong-Liverpool University Jiangsu China

ISBN: (纸本)9798331527471

Container handling optimization in ports significantly influences logistics chain efficiency and cost control, vital for economic benefits. Traditional research prioritizes quay crane (QC) scheduling, while truck dynamic scheduling often ties directly to specific QCs, prolonging QC operation times and affecting port throughput and efficiency. To tackle this, the paper introduces a dynamic truck dispatching algorithm with two task allocation strategies. Experimental results reveal our algorithm reduces total QC makespan by 10.8% in general when compared to traditional methods and has increased effectiveness in large-scale problems. © 2024 ieee.

关键词： Heuristic algorithms

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Detecting Singular Value Decomposition-based WatermarkEmbedded Medical Images using ResNet Neural Network 2

Detecting Singular Value Decomposition-based WatermarkEmbedd...

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2nd ieee international conference on Advances in computing, Communication and Applied informatics, ACCAI 2023

作者： Abirami, R. Malathy, C. Srm Institute of Science and Technology School of Computing Department of Networking and Communications Kattankulathur603 203 India

ISBN: (纸本)9798350315905

Digital products copyright protection is a severe issue in the growth of network technology. The security of data, especially medical data, is of utmost importance. The growth of the internet gives easy access to transactional medical data. It causes image distortion and a high risk of misclassification among medical experts. Watermarking aims to protect information and provide authentication for data during transmission. Instead of the conventional method, the deep learning-based watermarking method gained benefits in information security. In this paper, Singular Value Decomposition transformation is applied for embedding watermark, and Resnet a deep-learning model is modified for detecting watermarked images. Watermarking algorithm ensures robust watermarking for medical images to detect changes even after some manipulations like cropping, compression, filtering rotation, and more. MSE, SSIM, and PSNR are some metrics for assessing image quality. © 2023 ieee.

关键词： Singular value decomposition

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Distributed Brute-Force Password Recovery with a Partitioned Quantum Grover’s Algorithm 2

Distributed Brute-Force Password Recovery with a Partitioned...

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2nd international conference on Computational Intelligence and Network Systems, CINS 2024

作者： Bounceur, Ahcene University of Sharjah College of Computing and Informatics Sharjah United Arab Emirates

ISBN: (纸本)9798331504106

In the booming field of quantum computing, Grover’s Algorithm emerges as a pivotal quantum search algorithm, theoretically capable of outperforming classical brute-force search methods by exploiting the principles of superposition and quantum parallelism. However, the practical application of Grover’s Algorithm to crack complex passwords is limited by the nascent stage of quantum technology, which is currently challenged by limitations in qubit count and coherence times. This paper proposes a novel distributed quantum computing framework that aims to circumvent these limitations by partitioning the search space for a complex password among an array of quantum processors. Each processor executes Grover’s Algorithm on a fraction of the total search space, thereby reducing the complexity and quantum resource requirements for each individual computation. The partial results are then transmitted to a central classical computer, which synthesizes them into the final password. This distributed approach not only makes the task feasible for (with) present-day quantum systems but also presents a scalable model that could adapt to the rapid advancements in quantum technologies. By dissecting the complexity of the quantum brute-force problem into smaller, more manageable units, this method holds the potential to significantly reduce the time complexity of password recovery processes and thus presents a profound progress (implications) for the fields of cryptography and cybersecurity. ©2024 ieee.

关键词： Quantum computers

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Energy-Efficient and Intelligent Lighting Solutions: A Prototype for Smart Cities 6

Energy-Efficient and Intelligent Lighting Solutions: A Proto...

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

作者： Ariff, Mohamed Imran Mohamed Razally, Batrisyia Qistina Azizan, Azilawati Ahmad, Samsiah Zulkifli, Zalikha Arshad, Noreen Izza College of Computing Informatics and Mathematics Universiti Teknologi MARA Perak Branch Tapah Campus Malaysia EMI Solutions Sdn Bhd C-43-2 Block C Jaya One 72A Jalan Universiti Section 13 Selangor Petaling Jaya46200 Malaysia Department of Computer and Information Sciences Universiti Teknologi PETRONAS Seri Iskandar Malaysia

ISBN: (纸本)9798331522667

This paper presents a Smart Street Lighting System (SSLS) aimed at improving energy efficiency and providing enhanced convenience for urban areas, with a particular focus on parking facilities. By employing light, rain, and motion sensors, the SSLS ensures precise control over lighting levels, optimizing energy use while enhancing safety and visibility. The system’s light sensors adjust illumination according to ambient conditions, minimizing energy waste during daylight hours. During rain, brightness levels are automatically elevated for better visibility, while motion sensors activate full brightness when movement is detected to guarantee safety. A dedicated mobile application offers users real-time control and monitoring of energy usage and lighting settings. Among its notable contributions are the implementation of an IoT-based adaptive lighting framework and a scalable design that has demonstrated up to 35% energy savings in varied urban environments. This innovative solution addresses key challenges in urban lighting, ensuring sustainability and reducing operational expenses. © 2025 ieee.

关键词： Rain

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