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2020 International Conference on Computing and Information Technology, ICCIT 2020

作者： Manikandan, V. Mavaluru, DInesh Gobinathan, K. Rajanarayanan, S. Jenifer, M. Rohini, R. Lebanese French University Department of Computer Networking Erbil Kurdistan Region Iraq Saudi Electronic University College of Computing and Informatics Department of Information Technology Saudi Arabia Gnanamani Collge of Technology Department of CSE Namakkal India Arba Minch University Dept. of Business Administration and Information System Ethiopia Arba Minch University Arba Minch Institute of Technology Faculty of Computing and Software Engineering Ethiopia Vivekanandha College of Engineering for Women Department of CSE Namakkal India

ISBN: (纸本)9781728126807

In recent times, Wireless Sensor Networks (WSNs) are broadly utilized in targeted monitoring applications. Traditional target coverage techniques usually consider that environment is known completely and every target is covered by single sensor. However those algorithms are inflexible when the sensor is about to die, that is, lack of energy and therefore target has to be covered with more than a sensor which is termed as n coverage crisis. In general, n coverage problem is energy and time consuming process, as well sensor organization is needed all the time. To resolve this crisis, this work anticipates a n coverage model with VCH-PSO (Virtual Cluster Head based Particle Swarm Optimization and EFLM (Energy management based Fuzzy logic Model) to enlarge the lifetime of WSN. During the search of optimal area coverage, diverse factors like node position, energy consumption, and coverage range of sensors are considered significantly. Simulation was carried out in MATLAB environment and compared with prevailing techniques. The proposed model shows better trade off in terms of network lifetime and time needed for switching between various coverage regions. © 2020 IEEE.

关键词： Fuzzy logic

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Open IE-Triples Inference– Corpora Development and DNN Architectures

Open IE-Triples Inference– Corpora Development and DNN Arch...

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Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Martin Víta Petr škoda NLP Centre Faculty of Informatics Masaryk University Botanická 68a Brno Czech Republic Department of Software Engineering Charles University Malostranské nám. 2/25 Prague Czech Republic

ISBN: (数字)9788395541674

ISBN: (纸本)9781728141473

Natural language inference (NLI) is a well established part of natural language understanding (NLU). This task is usually stated as a 3-way classification of sentence pairs with respect to entailment relation (entailment, neutral, contradiction). In this work, we focus on a derived task of relation inference: we propose a method of transforming a general NLI corpus to an annotated corpus for relation inference that utilizes existing NLI annotations. We subsequently introduce a novel relation inference corpus obtained from a well known SNLI corpus and provide its brief characterization. We investigate several DNN siamese architectures for this task and this particular corresponding corpus. We set several baselines including hypothesis only baseline. Our best architecture achieved 96.92% accuracy.

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Integrating educational theories with virtual reality: Enhancing engineering education and VR laboratories

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Social Sciences and Humanities Open 2024年 10卷

作者： Abbas Shah, Syed Faisal Mazhar, Tehseen Shahzad, Tariq khan, Muhammad Amir Ghadi, Yazeed Yasin Hamam, Habib Department of Computer Science & Information Technology Virtual University of Pakistan Lahore 54000 Pakistan Department of Computer Science and information Technology School Education Department Government of Punjab Layyah 31200 Pakistan Department of Computer Science COMSATS University Islamabad Sahiwal Campus Sahiwal 57000 Pakistan School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Shah Alam 40450 Malaysia Department of Computer Science and Software Engineering Al Ain University Abu Dhabi 12555 United Arab Emirates Faculty of Engineering University de Moncton Moncton E1A3E9 NB Canada Department of Electrical and Electronic Engineering Sciences University of Johannesburg Johannesburg 2006 South Africa International Institute of Technology and Management (IITG) Av. Grandes Ecoles BP Libreville 1989 Gabon Bridges for Academic Excellence - Spectrum Tunis Tunisia

Immersive technologies, including virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (XR), create realistic digital experiences by overlaying digital elements. This study aims to highlight the benefits of utilizing VR technology in education, particularly in universities and higher education institutions, by integrating VR with educational theories to create engaging and interactive learning experiences that enhance understanding and retention. This review includes a comprehensive analysis of 103 works, synthesizing existing literature to evaluate the suitability of various educational approaches and theories for implementation in VR-based educational applications. The findings emphasize VR's potential to transform learning by providing immersive experiences that bridge different domains and encourage engagement. By integrating learning theory into VR development, meaningful learning environments can be created, improving student understanding and retention across diverse learning settings. The study concludes that the combination of technology and educational theories provides a novel approach to motivate students and foster deep learning in VR laboratories. © 2024 The Authors

关键词： Augmented reality Educational theories engineering education Immersive technology Interactive learning VR laboratories

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Drama patterns: Seeing the patterns from within: Focus group report 19

Drama patterns: Seeing the patterns from within: Focus group...

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24th European Conference on Pattern Languages of Programs, EuroPLoP 2019

作者： Vranic, Aleksandra Vranic, Valentino Vranic, Branislava Súkromná Základná Umelecká Škola Private Elementary Art School Ružová dolina c. 29 Bratislava82109 Slovakia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9781450362061

This report summarizes a focus group on drama patterns we organized at EuroPLoP 2019. Apart from the organizers, the focus group attracted eight participants, who together built a short drama play entitled The Real Red Riding Hood (created by Aleksandra Vranic). The play went through three settings with the final setting involving three drama patterns and one fundamental property (as defined by Alexander): Thoughts Reflecting Environment, Reversed Advantage, Disbelieved Identity, and Echoes. In addition, the participants tried out a name learning game based on the Thoughts Reflecting Environment pattern. The final setting was performed at the conference banquet without any further rehearsals (the focus group took only 75 minutes), followed by numerous informal discussions and reflections on how drama patterns could be beneficial for achieving a better understanding of the concept of a pattern, pattern composition, and pattern language, and for education in general. The focus group once more confirmed the effectiveness and efficiency of drama patterns that has been observed so far. © 2019 Association for Computing Machinery.

关键词： drama

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Classification and Self-Supervised Regression of Arrhythmic ECG Signals Using Convolutional Neural Networks

arXiv

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arXiv 2022年

作者： Grabowski, Bartosz Glomb, Przemyslaw Masarczyk, Wojciech Plawiak, Pawel Yıldırım, Özal Acharya, U. Rajendra Tan, Ru-San Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44-100 Poland Warsaw University of Technology Pl. Politechniki 1 Warsaw00-661 Poland Department of Computer Science Faculty of Computer Science and Telecommunications Cracow University of Technology Warszawska 24 Krakow31-155 Poland Department of Software Engineering Firat University Elazig Turkey School of Science and Technology Singapore University of Social Sciences Singapore Faculty of Business Education Law and Arts University of Southern Queensland Australia School of Engineering Ngee Ann Polytechnic 535 Clementi Road 599489 Singapore Department of Bioinformatics and Medical Engineering Asia University Taiwan Kumamoto University Kumamoto Japan Department of Cardiology National Heart Centre Singapore169609 Singapore Duke-NUS Medical School 169857 Singapore

Interpretation of electrocardiography (ECG) signals is required for diagnosing cardiac arrhythmia. Recently, machine learning techniques have been applied for automated computer-aided diagnosis. Machine learning tasks can be divided into regression and classification. Regression can be used for noise and artifacts removal as well as resolve issues of missing data from low sampling frequency. Classification task concerns the prediction of output diagnostic classes according to expert-labeled input classes. In this work, we propose a deep neural network model capable of solving regression and classification tasks. Moreover, we combined the two approaches, using unlabeled and labeled data, to train the model. We tested the model on the MIT-BIH Arrhythmia database. Our method showed high effectiveness in detecting cardiac arrhythmia based on modified Lead II ECG records, as well as achieved high quality of ECG signal approximation. For the former, our method attained overall accuracy of 87.33% and balanced accuracy of 80.54%, on par with reference approaches. For the latter, application of self-supervised learning allowed for training without the need for expert labels. The regression model yielded satisfactory performance with fairly accurate prediction of QRS complexes. Transferring knowledge from regression to the classification task, our method attained higher overall accuracy of 87.78%. © 2022, CC BY.

关键词： Electrocardiography

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Managing MyGRANTS Fragmented Database Using Binary Vote Assignment Grid Quorum with Association Rule (BVAGQ-AR) Replication Model 2nd

Managing MyGRANTS Fragmented Database Using Binary Vote Assi...

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2nd International Conference on Advanced Data and Information engineering, DaEng 2015

作者： Noraziah, Ahmad Fauzi, Ainul Azila Che Mohd, Wan Maseri Wan Herawan, Tutut Abdullah, Zailani Faculty of Computer Systems & Software Engineering University of Malaysia Pahang Gambang KuantanPahang26300 Malaysia Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia School of Informatics & Applied Mathematics Universiti Malaysia Terengganu Terengganu Malaysia

ISBN: (纸本)9789811317972

Replication is one of the mechanisms managing data since it improves data access and reliability. However, in recent years, with widely available, low-cost technology, the amount of various data grows rapidly. The problem is although we are packed with data, but we have lacked of knowledge. Nevertheless, if the impractical data is used in database replication, this will cause waste of data storage and the time taken for a replication process will be delayed. This paper propose a new algorithm namely Binary Vote Assignment on Grid Quorum with Association Rule (BVAGQ-AR) in order to handle fragmented database replication. BVAGQ-AR algorithm is capable of partitioning the database into disjoint fragments. Fragmentation in distributed database is very useful in terms of usage, reliability and efficiency. Handling fragmented database replication becomes challenging issue to administrator since the distributed database is scattered into split replica partitions or fragments. We address how to build reliable system by using the proposed BVAGQ-AR algorithm for distributed database fragmentation by using Malaysian Greater Research Network (MyGRANTS) data as a case study. The result shows that managing fragmented database replication through proposed BVAGQ-AR algorithm able to preserve MyGRANTS data consistency. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Association rules

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Increasing K-Means Clustering Algorithm Effectivity for Using in Source Code Plagiarism Detection 1st

Increasing K-Means Clustering Algorithm Effectivity for Usin...

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1st International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2019

作者： Hrkút, Patrik Ďuračík, Michal Mikušová, Miroslava Callejas-Cuervo, Mauro Zukowska, Joanna Department of Software Technologies Faculty of Management Science and Informatics University of Žilina Univerzitná 1 Zilina010 26 Slovakia Department of Road and Urban Transport Faculty of Operation and Economics of Transport University of Žilina Univerzitná 1 Zilina010 26 Slovakia Centro de Investigación y Extensión de la Facultad de Ingeniería Universidad Pedagógica y Tecnológica de Colombia UPTC TunjaBoyacá Colombia Faculty of Civil and Environmental Engineering Gdansk University of Technology 11/12 Gabriela Narutowicza Street Gdansk80-233 Poland

ISBN: (纸本)9783030467845

The problem of plagiarism is becoming increasingly more significant with the growth of Internet technologies and the availability of information resources. Many tools have been successfully developed to detect plagiarisms in textual documents, but the situation is more complicated in the field of plagiarism of source codes, where the problem is equally serious. At present, there are no complex tools available to detect plagiarism in a large number of software projects, such as student projects, which are created hundreds per year at each faculty of informatics. Our project aim is to create such a system for finding plagiarism in a large dataset of source codes. The whole system consists of several parts. A classification of source code is an essential part of the whole system because it makes it much more efficient to manipulate source code and divide data into individual clusters so that searching in large volumes of source code is as efficient as possible. The paper discusses how to optimize the implementation of clustering, so the whole system would deliver results in a reasonable time because allocating the different parts of the source code into suitable clusters will allow faster and more memory-efficient search for similar parts of the code. © Springer Nature Switzerland AG 2020.

关键词： Large dataset

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Kurdish Handwritten Character Recognition using Deep Learning Techniques

arXiv

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arXiv 2022年

作者： Ahmed, Rebin M. Rashid, Tarik A. Fattah, Polla Alsadoon, Abeer Bacanin, Nebojsa Mirjalili, Seyedali Vimal, S. Chhabra, Amit IT Department Faculty of Applied Science Tishk International University Erbil Iraq Computer Science and Engineering Department University of Kurdistan Hewler Erbil Iraq Software and Informatics Engineering Salahaddin University-Erbil- Erbil Iraq School of Computing and Mathematics Charles Sturt University Sydney Australia Sydney Australia Singidunum University Belgrade Serbia Centre for Artificial Intelligence Research and Optimisation Torrens University Australia Yonsei Frontier Lab Yonsei University Seoul Korea Republic of Department of Artificial Intelligence and Data Science Ramco Institute of Technology North Venganallur Village Virudhunagar District Tamilnadu Rajapalayam626 117 India Department of Computer Engineering and Technology Guru Nanak Dev University Amritsar India

Handwriting recognition is one of the active and challenging areas of research in the field of image processing and pattern recognition. It has many applications that include: a reading aid for visual impairment, automated reading and processing for bank checks, making any handwritten document searchable, and converting them into structural text form, etc. Moreover, high accuracy rates have been recorded by handwriting recognition systems for English, Chinese Arabic, Persian, and many other languages. Yet there is no such system available for offline Kurdish handwriting recognition. In this paper, an attempt is made to design and develop a model that can recognize handwritten characters for Kurdish alphabets using deep learning techniques. Kurdish (Sorani) contains 34 characters and mainly employs an Arabic\Persian based script with modified alphabets. In this work, a Deep Convolutional Neural Network model is employed that has shown exemplary performance in handwriting recognition systems. Then, a comprehensive dataset was created for handwritten Kurdish characters, which contains more than 40 thousand images. The created dataset has been used for training the Deep Convolutional Neural Network model for classification and recognition tasks. In the proposed system, the experimental results show an acceptable recognition level. The testing results reported a 96% accuracy rate, and training accuracy reported a 97% accuracy rate. From the experimental results, it is clear that the proposed deep learning model is performing well and is comparable to the similar model of other languages' handwriting recognition systems. © 2022, CC BY.

关键词： Convolutional neural networks

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Design, monitoring, and testing of microservices systems: The Practitioners’ perspective

arXiv

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arXiv 2021年

作者： Waseem, Muhammad Liang, Peng Shahin, Mojtaba Salle, Amleto Di Márquez, Gastón School of Computer Science Wuhan University Wuhan430072 China Department of Software Systems and Cybersecurity Faculty of Information Technology Monash University Melbourne3800 Australia Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’AquilaI-67100 Italy Department of Electronics and Informatics Federico Santa María Technical University Concepción4030000 Chile

Context: Microservices Architecture (MSA) has received significant attention in the software industry. However, little empirical evidence exists on design, monitoring, and testing of microservices systems. Objective: This research aims to gain a deep understanding of how microservices systems are designed, monitored, and tested in the industry. Method: A mixed-methods study was conducted with 106 survey responses and 6 interviews from microservices practitioners. Results: The main findings are: (1) a combination of domain-driven design and business capability is the most used strategy to decompose an application into microservices, (2) over half of the participants used architecture evaluation and architecture implementation when designing microservices systems, (3) API gateway and Backend for frontend patterns are the most used MSA patterns, (4) resource usage and load balancing as monitoring metrics, log management and exception tracking as monitoring practices are widely used, (5) unit and end-to-end testing are the most used testing strategies, and (6) the complexity of microservices systems poses challenges for their design, monitoring, and testing, for which there are no dedicated solutions. Conclusions: Our findings reveal that more research is needed to (1) deal with microservices complexity at the design level, (2) handle security in microservices systems, and (3) address the monitoring and testing challenges through dedicated solutions. © 2021, CC BY.

关键词： Surveys

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Designing a Pseudo-Haptics Study for Virtual Anesthesia Skills Development

Designing a Pseudo-Haptics Study for Virtual Anesthesia Skil...

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IEEE Games Media Entertainment (GEM)

作者： Bill Kapralos Alvaro Quevedo KC Collins Celina Da Silva Eva Peisachovich Kamen Kanev Michael Jenkin Adam Dubrowski Fahad Alam maxSIMhealth. Ontario Tech University Oshawa Ontario Canada Software and Informatics Research Centre. Ontario Tech University Oshawa Ontario Canada Collaborative Human Immersive Interaction Lab Toronto Canada School of Information Technology Carleton University Ottawa Ontario Canada Department of Health York University Toronto Ontario Canada Research Institute of Electronics Shizuoka University Hamamatsu Japan Department of Electrical Engineering and Computer Science Lassonde School of Engineering York University Canada Faculty of Health Sciences Ontario Tech University Oshawa Ontario Canada Department of Anesthesia Sunnybrook Health Science Centre Toronto Ontario Canada

ISBN: (纸本)9781665461399

Pseudo-haptics refers to the simulation of haptic sensations without the use of haptic interfaces, using, for example, audiovisual feedback and kinesthetic cues. Given the COVID-19 pandemic and the shift to online learning, there has been a recent interest in pseudo-haptics as it can help facilitate psychomotor skills development away from simulation centers and laboratories. Here we present work-in-progress that describes the study design of a pseudo-haptics for virtual anesthesia skills development. We anticipate this work will provide greater insight to pseudo-haptics and its application to anesthesia-based training.

关键词： Training COVID-19 Pandemics Laboratories Entertainment industry Games Media

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