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Self-Service Framework for Hospital Management System 8th

Self-Service Framework for Hospital Management System

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8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024

作者： Lubis, Muharman Lubis, Bastian Naufal, Fadhil Izzati, Berlian Maulidya Lubis, Arif Ridho Ramadhani, Rafian Fakhrurroja, Hanif Telkom University Industrial Engineering West Java Bandung Indonesia Department of Anesthesiology and Reanimation Universitas Sumatra Utara Sumatra Utara Indonesia Department of Computer Engineering and Informatics Politeknik Negri Medan Medan Indonesia

ISBN: (纸本)9789819795581

Self-service technology framework was developed for implementation at Tarakan Hospital, Jakarta, an institution under the administration of the DKI Jakarta provincial government that previously lacked such autonomous services. Leveraging the Healthcare Innovation Framework, which is dedicated to fostering innovations within the healthcare sector, this research proposes the introduction of a Tele-Assistance application mock-up at Tarakan Hospital Jakarta. This application is designed to offer Tele-Assistance for outpatients and Tele-Inpatient services for those admitted to the hospital. The adoption of this service model is anticipated to eliminate the need for physical queues and registration form fill-outs, facilitated by the integration of patients’ National Identification Numbers (NIK) with the Tele-Assistance application. Furthermore, the application will enable patients to check room availability, thereby reducing face-to-face interactions. Consequently, the creation of a service blueprint is essential for visualizing the interactions between patients and the self-service system, ensuring a seamless integration of this innovative solution into the hospital's operational framework. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Healthcare innovation Patient engagement Self-service technology Service blueprint Tele-assistance

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Evaluating ChatGPT-driven Automated Test Generation for Personalized Programming Education

Evaluating ChatGPT-driven Automated Test Generation for Pers...

引用

Foundation and Large Language Models (FLLM), International Conference on

作者： Christos Troussas Christos Papakostas Akrivi Krouska Phivos Mylonas Cleo Sgouropoulou Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (数字)9798350354799

ISBN: (纸本)9798350354805

Large Language Models (LLMs), such as ChatGPT, hold immense potential to irrevocably influence the dimension of educational technology by providing empowerment for personalized learning experiences. This paper covers the integration of ChatGPT into existing eLearning platforms toward supporting Java programming education. Using artificial intelligence-based capabilities of ChatGPT in natural language processing, our software enables instructors to generate individual module assessments tailored to a student's profile with unprecedented ease. Evaluation of the effectiveness and efficiency of the system was performed by a comprehensive review of the system, obtaining feedback from instructors and students, and analyzing test performance metrics. The evaluation showed that most teachers found the system very user friendly, with significant savings in time for test creation. Satisfaction related to personalized tests designed by ChatGPT was also adequate, and the average scores achieved on test cases set by ChatGPT were relatively high compared to those manually curated. Results underline the potential of ChatGPT-driven automated test generation for enhancing personalized programming education on eLearning platforms, making available tailored assessment, by consideration of individual needs of students, and increased learning outcomes and efficiency.

关键词： Java Electronic learning Accuracy Large language models Chatbots Question generation Software Test pattern generators Programming profession Testing

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Improving Prediction of Need for Mechanical Ventilation using Cross-Attention 46

Improving Prediction of Need for Mechanical Ventilation usin...

引用

46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Mohanty, Anwesh Shashikumar, Supreeth P. Lam, Jonathan Y. Nemati, Shamim University of California San Diego Department of Computer Science and Engineering La Jolla United States University of California San Diego Division of Biomedical Informatics La Jolla United States

ISBN: (纸本)9798350371499

In the intensive care unit, the capability to predict the need for mechanical ventilation (MV) facilitates more timely interventions to improve patient outcomes. Recent works have demonstrated good performance in this task utilizing machine learning models. This paper explores the novel application of a deep learning model with multi-head attention (FFNN-MHA) to make more accurate MV predictions and reduce false positives by learning personalized contextual information of individual patients. Utilizing the publicly available MIMIC-IV dataset, FFNN-MHA demonstrates an improvement of 0.0379 in AUC and a 17.8% decrease in false positives compared to baseline models such as feed-forward neural networks. Our results highlight the potential of the FFNN-MHA model as an effective tool for accurate prediction of the need for mechanical ventilation in critical care settings. © 2024 IEEE.

关键词： Contrastive Learning

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Personalized Hint Delivery in Multimedia Learning Environments Using Learning Styles: An Integrated Approach with Artificial Neural Networks and Weighted Sum Model

Personalized Hint Delivery in Multimedia Learning Environmen...

引用

International Workshop on Semantic Media Adaptation and Personalization (SMAP)

作者： Christos Troussas Akrivi Krouska Christos Papakostas Phivos Mylonas Cleo Sgouropoulou Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (数字)9798331504502

ISBN: (纸本)9798331504519

This paper introduces a novel multimedia learning environment designed to support holistic learning of web development. ANNs and the WSM model have been adopted to implement the framework of the VARK learning style model in order to dynamically provide personalized educational hints that assist learners to overcome difficulties and deepen their understanding, thus acquiring a higher level of knowledge in a more general and effective way. In our approach, hints are not an adjunct but a core feature of the learning process, dynamically tailored to each learner in their time of need. An ANN combined with a WSM collaborates to achieve optimal delivery of these hints, ensuring they are timely and context-aware according to the learning styles of individual students defined by the VARK model. Students receive the best possible guidance to make learning much more effective. A structured questionnaire-based evaluation followed by statistical hypothesis testing showed promising results for the efficacy of this multimedia learning environment.

关键词： Adaptation models Computational modeling Learning (artificial intelligence) Artificial neural networks Educational technology Weighted sum model Testing Context modeling

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A Preprocessor for Creation of Large-Scale Computational Applications 25

A Preprocessor for Creation of Large-Scale Computational App...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Simonov, Victor S. Khairetdinov, Marat S. Dept. Computer Engineering Novosibirsk State Technical University Novosibirsk Russia Dept. Geophysical Informatics Institute of Computational Mathematics and Mathematical Geophysics SB RAS Novosibirsk Russia

ISBN: (纸本)9798350389234

The emergence of large-scale computing paradigms required the evolution of software development methods, moreover, the need to effectively transform traditionally sequential applications into parallelizable and scalable architectures. This transformation is key in harnessing the computing power of modern multicore and distributed systems. Python, with its vast ecosystem and simplicity, is becoming a powerful language that facilitates this transition. This article discusses the methodologies and development of a Python preprocessor tool aimed at converting sequential applications into forms suitable for large-scale computing environments. Through detailed analysis and implementation, we demonstrate the use of Spark functions and third-party libraries to automate this transition, making large-scale computing more accessible to a wider range of applications and developers. The tool includes a set of rules that identify different patterns of code input (for example, list-sequential looping) and transform consistent code. This article introduces a Python preprocessor designed to automate the transformation of sequential Python applications into ones that harness the power of large-scale computing environments. © 2024 IEEE.

关键词： Python

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Affective Computing in Intelligent Tutoring Systems: Exploring Insights and Innovations

Affective Computing in Intelligent Tutoring Systems: Explori...

引用

South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Theofanis Tasoulas Christos Troussas Phivos Mylonas Cleo Sgouropoulou Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

Integrating intelligent tutoring systems (ITS) into education has significantly enriched personalized learning experiences for students and educators alike. However, these systems often neglect the critical role of emotions in the learning process. By integrating affective computing, which empowers computers to recognize and respond to emotions, ITS can foster more engaging and impactful learning environments. This paper explores the utilization of affective computing techniques, such as facial expression analysis and voice modulation, to enhance ITS functionality. Case studies and existing systems have been scrutinized to comprehend design decisions, outcomes, and guidelines for effective integration, thereby enhancing learning outcomes and user engagement. Furthermore, this study underscores the necessity of considering emotional aspects in the development and deployment of educational technology to optimize its influence on student learning and well-being. A major conclusion of this research is that integration of affective computing into ITS empowers educators to customize learning experiences to students' emotional states, thereby enhancing educational effectiveness. To achieve this, it is crucial for such systems to make informed design decisions and adhere to established guidelines. These design decisions may involve selecting appropriate emotion recognition algorithms and integrating them seamlessly into the ITS interface, while guidelines can offer practical insights into effectively implementing affective computing techniques in ITS, such as ensuring data privacy and security measures are in place and providing adequate training for educators on interpreting emotional data.

关键词： computers Training Affective computing Sentiment analysis Emotion recognition Technological innovation Text analysis Feature extraction Classification algorithms Guidelines

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AVIG: A Real-Time Visual Inspection for Guava Grading System Using computer Vision and XGBoost 23

AVIG: A Real-Time Visual Inspection for Guava Grading System...

引用

8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Setyawan, Raden Arief Perdana, Rizal Setya Harilegawa, Made Wena Balantimuhe, Alan Stevrie Basuki, Achmad Department of Electrical Engineering Faculty of Engineering Brawijaya University Malang Indonesia Department of Informatics Engineering Faculty of Computer Science Brawijaya University Malang Indonesia Directorate of Information Technology Brawijaya University Malang Indonesia

ISBN: (纸本)9798400708503

The conventional approach to manual inspection can be described by its considerable time and labor demands and the unavoidable occurrence of human error when faced with the inspection of a large number of products. Therefore, the application of an automated visual inspection system is frequently employed. The camera(s) can easily capture visual features for automatic visual inspection. However, it is essential to note that there are limitations when using this method to estimate the size-based grading system. The volume measurement is an essential feature in the field of automatic image analysis for fruit and vegetable grading, specifically guava. In this study, we propose a novel image analysis approach that utilizes a dual-view camera system to enhance the accuracy of volume approximation, particularly in scenarios involving non-perfect spherical objects. Hence, this research presents the training process of a comprehensive model for estimating the volume of objects with irregular shapes, named AVIG (Automatic Visual Inspection for Grading). The model utilizes the ellipsoid approximation technique, a dual-view camera, and XGBoost algorithm. The results from the accuracy comparison demonstrate that XGBoost shows the highest degree of accuracy, specifically 86%, thereby outperforming the performance of other algorithms. The comprehensive experiment conducted in this study has shown that the proposed architecture, AVIG, exhibits superior performance compared to previous research in terms of automatic evaluation of moving objects. © 2023 ACM.

关键词： computer vision

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Circumstance Evaluation Using Extreme Value Analysis on Charging Station Data: The Case of DEI Blue in Greece 14th

Circumstance Evaluation Using Extreme Value Analysis on Cha...

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14th International Conference on Information, Intelligence, Systems, and Applications, IISA 2023

作者： Panagoulias, Dimitrios P. Sarmas, Elissaios Marinakis, Vangelis Tsihrintzis, George A. Department of Informatics University of Piraeus Piraeus18534 Greece Decision Support Systems Lab School of Electrical and Computer Engineering National Technical University of Athens Zografou-Athens15773 Greece

ISBN: (纸本)9783031674259

We apply Extreme Value Analysis on sets of Electric Vehicle (EV) charging data with the goal to extract indications in the data of future trends in the demand for EV charging. The datasets have been provided by DEI blue, a service designed to provide integrated e-mobility solutions to individuals, companies and public administration throughout Greece. Eventhough the data are limited as they have been collected during a period of only twelve months, our analysis still reveals trends in the data highlighting a probable seasonality. The seasonality is observed during periods of extreme heat, regional population mobility and incoming visitors. These occurrences impact technical aspects of battery efficiency, grid capacity and a shift of behavioural usage patterns. Our findings cannot be ignored by policy makers as they are expected to intensify in the years to come due to the fast-rising number of EVs in use. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Electrification

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Investigating the Role of Digital Escape Rooms in Enhancing Educational Outcomes through Game-Based Learning

Investigating the Role of Digital Escape Rooms in Enhancing ...

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South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Panagiota Zachari Christos Papakostas Christos Troussas Akrivi Krouska Phivos Mylonas Cleo Sgouropoulou Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

This research investigates the integration of a Digital Educational Escape Room in teaching fifth-grade history. The study explores how the Digital Educational Escape Room can enhance student engagement, collaboration, and learning outcomes. The game is designed to improve students’ understanding specifically of Justinian’s reign. It aligns with the Bloom’s taxonomy and involves six interactive puzzles that cater to various learning styles, including visual, auditory, and kinesthetic. The adapted evaluation framework assesses four critical dimensions: learning and training, system, user experience, and affective dimension. Forty-four fifth-grade students participated, engaging in the activities designed to improve their understanding of the history topic of Justinian’s reign. Results indicated significant improvements in students’ historical knowledge, critical thinking, and teamwork. Students reported high satisfaction levels and positive emotional engagement, despite encountering some technical issues. By integrating game-based learning with digital technology, digital escape rooms offer a promising alternative to traditional teaching methods, potentially transforming the educational experience for primary school students.

关键词： Training Visualization Social networking (online) Taxonomy Transforms Games User experience Teamwork History Noise level

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Modeling Educational Strategies in Augmented Reality Learning Using Fuzzy Weights

Modeling Educational Strategies in Augmented Reality Learnin...

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South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Christos Papakostas Christos Troussas Akrivi Krouska Phivos Mylonas Cleo Sgouropoulou Department of Informatics and Computer Engineering University of West Attica Egaleo Greece

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

This paper shows the development and application of a fuzzy weight model methodology for the optimization of educational environments in augmented reality. A technology-based learning process in an augmented reality learning environment, notoriously able to improve spatial abilities and increase user engagement with the material learned as well as knowledge retention, has revolutionary potential in education. However, its effectiveness varies greatly. In this, we collaborated with 13 experts in augmented reality and education to deeply evaluate the following six key in-depth strategies: interactive feedback, gamified leaderboards, challenges, personalized learning path, AR-based simulations, and badges. Thus, strategies were rated upon the impact on the learners' outcome, and the ratings were agreed upon as a fuzzy set, because it is a subjective matter of evaluation. Normalization was done to get a balanced measurement that gave weights on which strategies are to be given higher priority. Such a model has been developed and implemented in a case study of AR-based spatial ability training application, focusing on AR-based simulations supplemented with interactive feedback. Pre- and post-tests among 30 respondents have shown significant improvements in the experimental group using the AR application over the control group using traditional means of spatial ability training. The results strongly support the potential of the model for later implementation in AR educational applications that focus on individual specifics and effective learning.

关键词： Training Weight measurement Fuzzy sets Three-dimensional displays Social networking (online) Focusing Machine learning Market research Augmented reality Optimization

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