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4th International Conference on computer Information Science and Artificial Intelligence, CISAI 2021

作者： Han, Jiazheng Wei, Zhengang Ocean University of China Dept. of Computer Application Technology Qingdao China Ocean University of China Dept. of Software Engineering Qingdao China

ISBN: (纸本)9781665406925

with the effective practical application of data mining technology in other fields, many researchers have used data mining technology to analyze the learning process data in the field of education and teaching, and explore the hidden and potentially valuable information and knowledge. This paper mainly mines the association in students' learning behavior data through lag sequence analysis algorithm (LSA), and shows learners' learning trajectory, willingness and cognitive process in the learning process. Help to grasp the potential behavior mode of students' learning and effectively guide the development and implementation of follow-up teaching work. © 2021 IEEE.

关键词： Data mining

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Task and Process Capturing Toolkit using GUI Automation 4

Task and Process Capturing Toolkit using GUI Automation

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4th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2022

作者： Perera, Ravindu Lakshan Bellanthudawa, Hiruni Piyumika Hevavitharana, Nipun Dimantha Ariyasinghe, Kavindu Malshan Wickramarathne, Jagath Perera, Jeewaka Sri Lanka Institute of Information Technology Dept.Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781665468350

Automation is one of the best ways to make easier everyone's day-to-day life. When considering the industry, if someone could be able to automate the mechanism of solving computer software issues, that will be helpful to every company. Because most companies are facing difficulties when it comes to giving IT support. Some companies are suffering from a lack of IT supporters because they have to solve the same problem on different computers at the same time. This most likely reduces the efficiency of the company and affects its performance as well. Without the proper knowledge of technology, employees tend to get a lot of technical issues while working with the technology. Here comes the opportunity to automate the IT-related problem-solving mechanism. That will save a lot of time and increase the company's efficiency as well. While carrying out the background research we thought, by automating the IT-related problem it will reduce the allocation of human power and that will directly affect company efficiency. The research team came up with the idea of creating a software product that can export an executable file by capturing selected tasks of the user's screen and its' relevant processes. Task and process capturing toolkit is a software product called the 'ClickMe toolkit'. It can capture relevant processes that are happening in any computer which runs on Windows 10 platform, then make a script called 'ClickMe script', and convert it into an executable file. It can be run on any Windows 10 Platform. © 2022 IEEE.

关键词： Graphical user interfaces

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Towards An Automatic Construction Of Simulation Scenarios: A Systematic Review

Towards An Automatic Construction Of Simulation Scenarios: A...

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Simulation Winter Conference

作者： Christopher W.H. Davis Antonie J. Jetter Philippe J. Giabbanelli Microsoft Portland OR USA Dept. of Engineering & Technology Management Portland State University Portland OR USA Dept. of Computer Science & Software Engineering Miami University Oxford OH USA

A predictive simulation is built on a conceptual model (e.g., to identify relevant constructs and relationships) and serves to estimate the potential effects of ‘what-if’ scenarios. Developing the conceptual model and plausible scenarios has long been a time-consuming activity, often involving the manual processes of identifying and engaging with experts, then performing desk research, and finally crafting a compelling narrative about the potential futures captured as scenarios. Automation could speed-up these activities, particularly through text mining. We performed the first review on automation for simulation scenario building. Starting with 420 articles published between 1995 and 2022, we reduced them to 11 relevant works. We examined them through four research questions concerning data collection, extraction of individual elements, connecting elements of insight and (degree of automation of) scenario generation. Our review identifies opportunities to guide this growing research area by emphasizing consistency and transparency in the choice of datasets or methods.

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Proceedings of the 14th International Conference on Education Technology and computers

作者： Veronica Segarra-Faggioni Sylvie Ratté Frank De Jong Dept. Software and IT Engineering École de technologie supérieure Canada and Dept. Computer Science and Electronics Universidad Tecnica Particular de Loja Ecuador Dept. Software and IT Engineering École de technologie supérieure Canada Dept. Learning and Innovation Aeres Wageningen Applied University Netherlands

ISBN: (纸本)9781450397766

Knowledge Building as a pedagogy supports collaborative work between students to improve ideas. The result of knowledge-building discourse in student communities is the development of academic artifacts. Student reports are academic artifacts that can result from a knowledge-building process during their learning. However, the automatic analysis of student reports is quite challenging due to the documents’ length and written language. Given this context, our goal is to analyze the semantic similarity between student reports and curriculum literature using the information coverage measure based on the Skip-gram word2vec model. Word2vec is a well-known set of techniques that provides a way to create a representation of words to predict the nearby words between every word and its context to capture the internal semantic and syntactic information. In this work, through the experimental comparison between the vocabulary list, the best similarity value is 0.90 using word2vec. The results show that each student report was aligned with each document in the curriculum literature using the information coverage measure based on word2vec.

关键词： Machine learning natural language processing word2vec

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Intelligent Model for Optimizing Gantt Chart in the Planning Stage

Intelligent Model for Optimizing Gantt Chart in the Planning...

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International Conference on Information Technology (ICIT)

作者： Noor Bdair Wael Alzyadat Shadi AlZubi Dept of Software engineering Faculty of Science and IT Alzaytoonh University of Jordan Dept. of of Computer Science Faculty of Science and IT Alzaytoonh University of Jordan

Scheduling tasks under resource constraints is essential for project success, and this research focuses on scheduling tasks efficiently to minimize completion time. To tackle this problem, two optimization techniques are employed: Linear programming (LP) and particle swarm optimization (PSO). PSO significantly reduces the duration, leading to a reduction in project duration. But the LP algorithm does not improve the project duration. Using suitable algorithms to maximize project efficiency and success is essential for successful project management. This research provides valuable information for project managers and decision makers, highlighting the importance of utilizing suitable algorithms to maximize project efficiency and success.

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Kubernetes Cluster Disaster Recovery Using AWS

Kubernetes Cluster Disaster Recovery Using AWS

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International Conference on Computing Communication Control and Automation (ICCUBEA)

作者： Simran Bhavsar Apoorva Agrawal Tanvi Ropalkar Pranjali Kamdi Aparna Hajare Shilpa Deshpande Rahul Rathi Devendra Garg Dept. of Computer Engineering Cummins College of Engineering for Women Pune India Veritas Software Technologies India Private Limited Pune India

As applications in IT have been spanning multiple containers across servers, kubernetes is being used extensively for automating software deployment, scaling and management. Kubernetes eases the container tasks and also other activities like horizontal scaling and canary development. To run cloud-native applications, kubernetes has become the de facto standard for container orchestration, regardless of the underlying platform. This makes it very crucial to have a disaster recovery plan for kubernetes environments. This paper proposes a system for backup and restore of a kubernetes cluster using the snapshot method along with the Public Key Infrastructure (PKI) certificates of a cluster. It also focuses on automating the backup and restore operations using microservices. Furthermore, it makes use of Amazon Web Services (AWS) tools for the reliability, scalability and the automation of backup and restore operations. The user can run the proposed microservices to backup and restore the cluster from any specific timestamp before the disaster. The experimental results demonstrate the effective performance of the proposed method in terms of efficiently restoring the kubernetes cluster in optimal time.

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A New Configurable SC-based Dual Source Inverter Topology with Improved Reliability

A New Configurable SC-based Dual Source Inverter Topology wi...

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Energy Technologies for Future Grids (ETFG), IEEE International Conference on

作者： Mohammad Anas Anees Marif Daula Siddique Saad Mekhilef Marizan Binti Mubin Mehdi Seyedmahmoudian Alex Stojcevski Dept. of Electrical Engineering University of Malaya Malaysia Dept. of Electrical and Computer Engineering National University of Singapore Singapore School of Software and Electrical Engineering. Swinburne University of Tech. Australia

This paper presents a novel fifteen-level two-source inverter topology that is reliable against source outages. The topology has two DC sources, a total of ten switches, and four DC-link capacitors. Level-shifted PWM is used to generate the required number of levels. Simulations are performed for normal operation as well as for the source outage conditions. The proposed topology is able to generate multi-level output waveform satisfactorily even at the advent of source outages. The simulation results for the source outages are presented for both static and dynamic conditions along with the THD measurements.

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Joint Energy and Computation Workload Management for Geo-distributed Data Centers

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2025年

作者： Wang, Ran Wu, Rixin Liu, Linfeng Yi, Changyan Zhu, Kun Wang, Ping Niyato, Dusit Nanjing University of Aeronautics and Astronautics Collaborative Innovation Center of Novel Software Technology and Industrialization College of Computer Science and Technology Nanjing China Nanjing University of Posts and Telecommunications School of Computer Science and Technology Nanjing China York University Dept. of Electrical Engineering and Computer Science Lassonde School of Engineering Canada Nanyang Technological University School of Computer Science and Engineering Singapore

The increasing demands of data computation and storage for cloud-based services motivate the development and deployment of large-scale data centers (DCs). The energy demand of these devices is rising rapidly and becoming a noticeable challenge for current power networks. The smart grid (SG) is deemed as the future power system paradigm enabling more affordable and sustainable energy supply, which can effectively relieve the load pressure from DCs. Moreover, with growing concerns regarding harmful emissions due to combustion of fossil fuels, the exploitation of renewable energy sources (RES) has attracted extensive attention, which can benefit SGs and DCs, as well as society at large. However, the geo-distributed property of DCs and SGs and the uncertain nature of RES production pose severe challenges to the optimal management of computation and energy resources in such a tripartite coupling system. Focusing on these issues, a joint energy and computation workload management framework is proposed for enabling a sustainable DC paradigm with distributed RES. Specifically, a three-layer game is formulated to model the iterations among entities including the energy market, data center operators (DCOs), and SGs. The market includes a certain amount of RES that must be dispatched. The SG offers the DCO an electricity selling price while simultaneously importing RES from the market at a buying price in order to maximize the benefit. The DCO allocates the workload to different DCs, aiming to minimize the costs of energy consumption and carbon emissions. The interactive processes between different entities are further decomposed into two coupling Stackelberg games. We obtain the equilibrium state of the game and prove its uniqueness and optimality. Simulation experiments are conducted to evaluate the performance of the joint energy and computation workload management scheme and show its superiority over counterparts in utilizing renewable energy and reducing emissions. Furthe

关键词： Smart power grids

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Machine Learning in Agriculture and Crop Management: A Comprehensive Review

Machine Learning in Agriculture and Crop Management: A Compr...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Rachna Rathore Archana Ganesh Said Preeti Jnagra Haritha Murari Saloni Bansal Harshita Singh Dept. of Mathematics Jiwaji University Gwalior India Dept. of Computer Engineering AISSMS’s Institute Of Information Technology Pune India Dept. of Biotechnology Lingayas Vidyapeeth Haryana India Dept. of Software Engineer Spark Infotech Inc Phoenix Arizona USA Dept. of Computer Eng. & Applications GLA University Mathura India Dept. of CSE (AIML) CSE-APEX Chandigarh University Chandigarh India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

Machine learning (ML) has transformed agriculture and crop management, revolutionizing modern farming techniques. By leveraging ML, farmers can accurately monitor and analyze agricultural data, gaining valuable insights into crop health, soil conditions, weather patterns, and pest infestations. Through the analysis of satellite imagery, sensor data, and historical records, ML models can predict optimal planting times, forecast yields, and identify potential disease outbreaks, enabling more efficient resource management. These innovations promote precision agriculture, reduce waste, and support sustainability. This paper explores the latest developments in ML applications for agriculture, emphasizing their potential to enhance food security, minimize environmental impact, and boost farm profitability through data-driven decision-making.

关键词： Technological innovation Systematics Reviews Weather forecasting Machine learning Predictive models Soil Satellite images Sustainable development Crop yield

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Self-Reported Learning Strategies and Preferences in Health Informatics

Self-Reported Learning Strategies and Preferences in Health ...

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34th Medical Informatics Europe Conference, MIE 2024

作者： Rohani, Narjes Gallagher, Michael Gal, Kobi Banas, Kasia Manataki, Areti Usher institute University of Edinburgh United Kingdom Moray House School of Education and Sport University of Edinburgh United Kingdom School of Informatics University of Edinburgh United Kingdom Dept. of Software and Information Systems Engineering Ben-Gurion University Israel School of Computer Science University of St Andrews United Kingdom

ISBN: (纸本)9781643685335

Despite the proliferation of educational programmes in Health Informatics (HI) worldwide, there is limited knowledge regarding students' preferences and learning strategies in HI courses. To address this gap, we conducted a study to gather and analyse data from three HI courses. Employing the Motivated Strategies for Learning Questionnaire (MSLQ) and theories of deep and surface learning, we designed a questionnaire to collect data. The analysis of students' responses indicates that machine learning emerges as one of the most interesting topics, while certain topics such as data wrangling of genomics data were more challenging for students. Students expressed a preference for sequential learning. They exhibited multimodal tendencies regarding the type of learning resources, with tendency to prefer learning resources that have more visual contents. In all three courses, learners reported using deep learning strategy rather than surface learning, yet they appear to struggle with employing organisation, elaboration, and peer learning tactics. This study provides valuable insights into HI education, offering recommendations for educators, learners, and researchers to enhance HI education. © 2024 The Authors.

关键词： Contrastive Learning

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