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检索条件"任意字段=10th International Conference on Tools and Algorithms for the Construction and Analysis of Systems"

共 1703 条记录，以下是301-310 订阅

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A Visualization analysis of the Paper of Chinese Computational thinking of China in the Recent Decade 10th

A Visualization Analysis of the Paper of Chinese Computation...

引用

10th international conference on Frontier Computing, FC 2020

作者： Song, Haomin Liu, Yu Ding, Lihua Sun, Xinghua School of Information Science and Engineering Hebei North University Hebei Zhangjiakou075000 China

ISBN: (纸本)9789811601149

In this paper, the Chinese papers of computing thinking published in 2009–2019 are sorted out and analyzed, and the key words co-occurrence map and time zone map are drawn by using the visual map tools VOSviewer, CiteSpace, Gephi, and other tools, and the current situation and development trend of computing thinking research in China are analyzed according to the generated charts. the research shows that the research of computational thinking of china are mainly focuses on education reform, program design, and information technology courses of college students. there are few researches on the education of Computational thinking of K12, and many teachers of computer science also lack professional knowledge of computational thinking. the conclusion of this paper provides some reference for the future research of Computational thinking and the construction of Computational thinking Curriculum. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Curricula

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Cloud Computing for Enabling Big Data analysis 1

引用

10th international conference on Cloud Computing and Services Science (CLOSER)

作者： Belcastro, Loris Marozzo, Fabrizio Talia, Domenico Trunfio, Paolo Univ Calabria DIMES Arcavacata Di Rende Italy DtoK Lab Srl Arcavacata Di Rende CS Italy

ISBN: (数字)9783030723699

ISBN: (纸本)9783030723682;9783030723699

Every day billions of people access web sites, blogs, and social media. Often they use their mobile devices and produce huge amount of data that can be effectively exploited for extracting valuable information concerning human dynamics and behaviors. Such data, commonly referred as Big Data, contains rich information about user activities, interests, and behaviors, which makes it intrinsically suited to a very large set of applications. For getting valuable information and knowledge from such data in a reasonable time, novel scalable frameworks and data analysis techniques on Cloud systems have been developed. this paper aims at describing some recent Cloud-based frameworks and methodologies for Big Data processing that can be used for developing and executing several data analysis applications, including trajectory mining and sentiment analysis. the paper is organized in two main parts. the first part focuses on tools for developing and executing scalable data analysis applications on Clouds. the second part presents data analysis methodologies for extracting knowledge from large datasets.

关键词： Cloud computing Big data analysis Sentiment analysis Trajectory mining Social data analysis

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Intelligent System for Socialization of Individual’s with Shared Interests based on NLP, Machine Learning and SEO Technologies 6

Intelligent System for Socialization of Individual’s with S...

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6th international conference on Computational Linguistics and Intelligent systems, COLINS 2022 - Volume I: Main

作者： Batiuk, Taras Vysotska, Victoria Holoshchuk, Roman Holoshchuk, Svitlana Lviv Polytechnic National University S. Bandera Street 12 Lviv79013 Ukraine Osnabrück University Friedrich-Janssen-Str. 1 Osnabrück49076 Germany

the main objective of this work is to create an intelligent system for socialization by personal interests based on SEO technologies and methods of machine learning. the primary purpose of this intelligent system is to identify the user within the system using neural networks and to select similar users by analyzing the user's current information. An intelligent system is created that, through Identity and JWT tokens, provides optimized and secure authorization, logging, and support functions for the current system user session. Finding a face in a user's photo and checking the presence of a similar user in the database are implemented using convolutional and Siamese neural networks. the analysis and formation of similar user beeps are implemented using fuzzy search algorithms, the Levenshtein algorithm, and the Noisy Channel model, which made it possible to maximize the user selection process's automation and optimize the time spent in this process. tools have also been created to view other user’s profiles, preferences and private correspondence. All personal mail and information about it are stored in the current database. Each user of the system can view all the information about sent and received messages. the created intelligent system meets the original goal, as it fully implements user identification, analysis, selection and further socialization of users of the system. the algorithm of sampling of users of similar interests implemented in the IS is 25-30% more efficient and accurate than usual Levenshtein algorithm. At the same time, the implemented algorithm performs sampling 10 times faster than Levenshtein algorithm. © 2022 Copyright for this paper by its authors.

关键词： Intelligent systems

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A Modified Usefulness, Satisfaction, and Ease-of-Use Questionnaire for Pre-Elderly Users)

A Modified Usefulness, Satisfaction, and Ease-of-Use Questio...

引用

HCI and UX conference in Indonesia (CHIuXiD), international

作者： Annisa Nuritsna Ardyani P. Insap Santosa Azkario Rizky Pratama Department of Electrical and Information Engineering Universitas Gadjah Mada D.I.Yogyakarta Indonesia

ISBN: (数字)9798350380439

ISBN: (纸本)9798350380446

Interactive system design and development always involves testing and evaluation to ensure that user needs and expectations are met, including the pre-elderly (aged 45–59) population who have unique emotional and functional requirements compared to other categories of users. However, the existing evaluation methods still fall short in addressing this demographic’s needs and preferences. In order to properly address the challenges faced by pre-elderly users, this study proposes a modified method of evaluating the usability aspects of application of the existing USE (Usefulness, Satisfaction, and Ease-of-Use) questionnaire. the questionnaire was modified by paraphrasing and removing certain questions, while also incorporating user interface as a new specific key factor. the modification resulted in 18 items within five factors. A sample of 62 pre-elderly users participated in completing the modified questionnaire after finishing structured mobile news app scenario testing. the factor analysis results demonstrate that the modified questionnaire effectively captures both functional and non-functional requirements specific to pre-elderly users. While all 18 items were retained, they were categorized into two distinct factors: Ease of Use and Learning, and User Interface and Satisfaction. the findings of this study are anticipated to contribute to future research on user experience evaluation tools that are more tailored to the specific needs of pre-elderly users. Furthermore, these findings offer invaluable insights for enhancing the usability and user experience of mobile news applications, thereby improving user satisfaction and engagement.

关键词： Interactive systems User interfaces Aging User experience Mobile applications Usability Finishing Testing

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Dezyne: Paving the Way to Practical Formal Software Engineering 6

Dezyne: Paving the Way to Practical Formal Software Engineer...

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19th international conference on tools and algorithms for the construction and analysis of systems (TACAS)

作者： van Beusekom, Rutger de Jonge, Bert Hoogendijk, Paul Nieuwenhuizen, Jan Verum Software Tools BV Eindhoven Netherlands

Designing software that controls industrial equipment is challenging, especially due to its inherent concurrent nature. Testing this kind of event driven control software is difficult and, due to the large number of possible execution scenarios only a low dynamic test coverage is achieved in practice. this in turn is undesirable due to the high cost of software failure for this type of equipment. In this paper we describe the Dezyne language and tooling;Dezyne is a programming language aimed at software engineers designing large industrial control software. We discuss its underlying two layered and compositional approach that enables reaping the benefits of Formal Methods, hereby strongly supporting guiding principles of software engineering. the core of Dezyne uses the mCRL2 language and model-checker (Jan Friso Groote et al.) to verify the correctness and completeness of all possible execution scenarios. the IDE of Dezyne is based on the Language Server Protocol allowing a smooth integration with e.g., Visual Studio Code, and Emacs, extended with several automatically generated interactive graphical views. We report on the introduction of Dezyne and its predecessor at several large high-tech equipment manufacturers resulting in a decrease of software developing time and a major decrease of reported field defects.

关键词： Concurrency control

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10th international conference in Methodologies and Intelligent systems for Technology Enhanced Learning, MIS4TEL 2020

10th International Conference in Methodologies and Intellige...

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10th international conference in Methodologies and Intelligent systems for Technology Enhanced Learning, MIS4TEL 2020

ISBN: (纸本)9783030522865

the proceedings contain 26 papers. the special focus in this conference is on Methodologies and Intelligent systems for Technology Enhanced Learning. the topics include: Evaluating statistical and informatics competencies in medical students in a blended learning course;a serious game and negotiation skills in nursing students: A pilot study;preface;construction of fuzzy-classification expert system in cerebral palsy for learning performance facilitation;interprofessional high-fidelity simulation on nursing students’ collaborative attitudes: A quasi-experimental study using a mixed-methods approach;from high-fidelity patient simulators to robotics and artificial intelligence: A discussion paper on new challenges to enhance learning in nursing education;the concept of high-fidelity simulation and related factors in nursing education: A scoping review;the use of simulation for teaching therapy management: An observational descriptive study on 2nd and 3rd year students of the nursing degree course of Reggio Emilia;computer laboratory: the key to access the electronic databases in learning evidence-based practice;perspectives in nursing education: From paper standardized taxonomies to electronic records applied in nursing practice;the perceived usefulness of a problem-solving incorporated into blended learning in nursing education: A descriptive study;Authoring interactive-video exercises with ELEVATE: the NLS procedure case study;extending and evaluating a collaborative note-taking application: A pilot study;Enhancing learning opportunities for CS: Experiences from two learning systems;security in multimedia information systems: analysis and prediction;a dynamic recommender system for online judges based on autoencoder neural networks;lessons learned from implementing blended learning for classes of different size;smart object design by children as protagonists.

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Implicit and Explicit Proof Management in KeYmaera X 6

Implicit and Explicit Proof Management in KeYmaera X

引用

19th international conference on tools and algorithms for the construction and analysis of systems (TACAS)

作者： Mitsch, Stefan Carnegie Mellon Univ Comp Sci Dept Pittsburgh PA 15213 USA

Hybrid systems theorem proving provides strong correctness guarantees about the interacting discrete and continuous dynamics of cyber-physical systems. the trustworthiness of proofs rests on the soundness of the proof calculus and its correct implementation in a theorem prover. Correctness is easier to achieve with a soundness-critical core that is stripped to the bare minimum, but, as a consequence, proof convenience has to be regained outside the soundness-critical core with proof management techniques. We present modeling and proof management techniques that are built on top of the soundness-critical core of KeYmaera X to enable expanding definitions, parametric proofs, lemmas, and other useful proof techniques in hybrid systems proofs. Our techniques steer the uniform substitution implementation of the differential dynamic logic proof calculus in KeYmaera X to allow users choose when and how in a proof abstract formulas, terms, or programs become expanded to their concrete definitions, and when and how lemmas and sub-proofs are combined to a full proof. the same techniques are exploited in implicit sub-proofs (without making such sub-proofs explicit to the user) to provide proof features, such as temporarily hiding formulas, which are notoriously difficult to get right when implemented in the prover core, but become trustworthy as proof management techniques outside the core. We illustrate our approach with several useful proof techniques and discuss their presentation on the KeYmaera X user interface.

关键词： Hybrid systems

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Design and Implementation of a Deep Learning-Based Distributed Photovoltaic Power Forecasting System

Design and Implementation of a Deep Learning-Based Distribut...

引用

international conference on Computer and Communications (ICCC)

作者： Bo Han Zhengyun Han Hongyan Fan Sifang Feng University of Chinese Academy of Sciences Shenyang institute of computing technology Shenyang China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

With the global shift towards renewable energy and the pursuit of “dual-carbon” targets [1], the integration of distributed photovoltaic (PV) power generation into the grid poses significant challenges to power system stability and economic viability. Addressing the limitations of existing forecasting methods, which often focus on individual PV stations and lack a comprehensive approach to regional-scale integration, this study introduces a novel power forecasting system. We systematically investigate the impacts of distributed PV on grid stability and develop an advanced forecasting approach that enhances both prediction accuracy and operational efficiency. Our approach begins with an analysis of spatial correlations between centralized and distributed PV stations within the same region. By identifying and aggregating groups of distributed stations that exhibit significant correlations with centralized ones [2], we create virtual centralized stations. this innovative strategy refines the forecasting model and significantly boosts its accuracy. We then propose a combined LSTM- Transformer model for power output forecasting of these virtual stations. this model capitalizes on the sequence prediction capabilities of LSTM and the long-range dependency capturing efficiency of the Transformer, thereby enhancing forecast precision [3]. through empirical analysis using real data from PV stations in Northeast China, we confirm the effectiveness of our model. It provides accurate forecasts essential for power system scheduling and aids in decision-making for PV station planning, construction, and operation. this study not only advances the field of distributed PV power generation but also optimizes electrical resource allocation and promotes the green transformation of energy structures.

关键词： Photovoltaic systems Renewable energy sources Adaptation models Accuracy Correlation Predictive models Power system stability Transformers Data models Forecasting

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A Bibliometric analysis and Research Landscape of Artificial Intelligence in Education

A Bibliometric Analysis and Research Landscape of Artificial...

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IEEE international conference on Control System, Computing and Engineering (ICCSCE)

作者： Samuel-Soma M. Ajibade Bayan Issa Muhammed Basheer Jasser Farrukh Hassan Ghassan Saleh ALDharhani Ismail Ahmed Al-Qasem Al-Hadi Kayode Akinlekan Akintoye Almighty Cortezo Tabuena Department of Computing and Information Systems School of Engineering and Technology Sunway University No. 5 Jalan Universiti Bandar Sunway Selangor Darul Ehsan Malaysia Department of Computer Engineering Istanbul Ticaret University Istanbul Turkiye Faculty of Informatics Engineering University of Aleppo Syria Institute of Computer Science and Digital Innovation UCSI University Kuala Lumpur Malaysia Faculty of Information Science and Technology UKM University Bangi Selangor Malaysia Department of Computer Science The Federal Polytechnic Ado Ekiti Ekiti State Nigeria College of Arts and Sciences University of the City of Valenzuela Philippines

ISBN: (数字)9798350364507

ISBN: (纸本)9798350364514

this study examines the academic field of Artificial Intelligence in Education (AI-ED) by examining the publications and indexed documents in Scopus from 2010 to 2023. Consequently, we examined the publishing trends, exemplary articles, and the most engaged participants and funding institutions in the domain of AI-ED research. A bibliometric analysis was performed to examine the network of co-authorships, keywords, and citations in the domain of AIED research. the Scopus search resulted in the discovery of 10,474 published documents on AI-ED. Additionally, trends analysis indicated a significant increase of over 3,000% in publications between 2010 and 2023. conference papers are the most often utilized document type, including 6757 publications or $64.5 \%$ of the overall amount. the ACM international conference Proceeding Series is the primary source for published materials, accounting for 675 publications or $6.44 \%$ of the total publications on the topic. the most prolific researchers in the field of AI-ED are Breazeal, C and Chai C.S, each having published 18 documents. Additionally, the two institutions that have produced the highest number of published documents are Carnegie Mellon University (CMU) and the University of NC State University (NCSU). the output of the affiliations active in the topic is primarily attributed to the funders, specifically the National Science Foundation, which is the leading funding institution based in the United States and has contributed to 354 publications. An analysis of keyword co-occurrence revealed 6 main study areas that cover the essential tools, theories, methodologies, and socioeconomic and financial aspects of artificial intelligence in education (AIED). Future research in the field of artificial intelligence in education will focus on employing sophisticated deep learning, machine learning, and neural network algorithms to precisely predict students’ learning patterns.

关键词： Deep learning Education Bibliometrics Neural networks Market research Prediction algorithms Stakeholders Artificial intelligence Socioeconomics Meteorology

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Describing and Simulating Concurrent Quantum systems 26th

Describing and Simulating Concurrent Quantum Systems

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26th international conference on tools and algorithms for construction and analysis of systems (TACAS)

作者： Bornat, Richard Boender, Jaap Kammueller, Florian Poly, Guillaume Nagarajan, Rajagopal Middlesex Univ Dept Comp Sci London England Hensoldt Cyber GmbH Taufkirchen Germany Widmee Nouvelle Region De Borde France

We present a programming language for describing and analysing concurrent quantum systems. We have an interpreter for programs in the language, using a symbolic rather than a numeric calculator, and we give its perfor... 详细信息

ISBN: (纸本)9783030452360;9783030452377

关键词： Quantum communication

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