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HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Subandi Subandi Aulia Akhrian Syahidi Siti Zakiah Kiyoshi Kiyokawa Ahmad Riyadi M. Helmy Noor Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin Indonesia Informatics Engineering Undergraduate Program Faculty of Computer Science Universitas Brawijaya Malang Indonesia Cybernetics and Reality Engineering Laboratory Nara Institute of Science and Technology Ikoma Japan Informatics Engineering Diploma Program Politeknik Negeri Banjarmasin Banjarmasin Indonesia

ISBN: (纸本)9781665476652

Sasirangan cloth is one of the traditional cloths owned by Indonesia and is a typical cloth originating from the province of South Kalimantan. This Sasirangan cloth has many motifs and is unique. Sasirangan cloth is also one of the potentials that can attract local and foreign tourists to visit South Kalimantan. However, in recent years, tourist visits to South Kalimantan have decreased due to the impact of the COVID-19 pandemic. Then it also has an impact on the delay in the implementation of the Banjarmasin Sasirangan Festival which is usually held annually. The next impact is a decrease in turnover and interest in shopping for Sasirangan cloth, so that employees who work for Sasirangan cloth craftsmen are dismissed and reduce people's income. So the purpose of this study is to report the results of the development of a Virtual Reality Game application called VR-SasiranganKu by integrating the interaction of Non-Player Character (NPC) behavior with the type of narrative in the simulation genre game. VR-SasiranganKu is recommended to introduce and at the same time promote Sasirangan cloth to users, then justify the reaction to knowledge and shopping experience, and evaluate user experience using the UX Honeycomb method. Respondents involved as many as 100 people who are local and national tourists. The results show that the interaction of NPC behavior can provide good direction to users regarding the introduction of Sasirangan cloth by presenting an appropriate interaction design based on the narrative and the theme of the NPC that has been adopted, the results of justification using VR-SasiranganKu can provide knowledge reaction and very good shopping experience, and based on user experience evaluation that VR-SasiranganKu has adopted a very good UX with an average score of 4.91.

关键词： Human computer interaction COVID-19 Solid modeling Pandemics Games Virtual reality User experience

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Learner Action Patterns in the Problem-Solving Process Related to program Code Composition Based on Tracking System Activities 7

Learner Action Patterns in the Problem-Solving Process Relat...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Syahidi, Aulia Akhrian Supianto, Ahmad Afif Hirashima, Tsukasa Watanobe, Yutaka Politeknik Negeri Banjarmasin Smart City Information System Applied Undergraduate Program Banjarmasin City Indonesia Research Center for Data and Information Sciences Bandung City Indonesia Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Learning Engineering Laboratory Higashihiroshima Japan University of Aizu Division of Information Systems Department of Computer Science and Engineering Fukushima AizuWakamatsu Japan

ISBN: (纸本)9798350345711

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the 'if-then' rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process. © 2022 IEEE.

关键词： Data mining

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An algorithm for conditional-fault local diagnosis of multiprocessor systems under the MM⁎ model

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Theoretical computer Science 2024年 987卷

作者： Lv, Yali Lin, Cheng-Kuan Hsu, D. Frank Fan, Jianxi School of Information Technology Henan University of Chinese Medicine Zhengzhou China Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Undergraduate Degree Program of Systems Engineering and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Computer Science and Information Engineering Chung Cheng Institute of Technology NDU Taoyuan Taiwan Department of Computer and Information Science Fordham University New York United States School of Computer Science and Technology Soochow University Suzhou China

Diagnosis is a crucial subject for maintaining the reliability of multiprocessor systems. Under the MM⁎ diagnosis model, Sengupta and Dahbura proposed a polynomial-time algorithm with time complexity O(N5) to diagnose a system with N processors. In this paper, we propose a (α,β)-trees combination S(u,X,α,β) and give an algorithm to identify the fault or fault-free status of each processor for conditional local diagnosis under the MM⁎ model. According to our results, a connected network with a (α,β)-trees combination S(u,X,α,β) for a node u is conditionally locally (α+2β−3)-diagnosable at node u and the time complexity of our algorithm to diagnose u is O(α2β+αβ2). As an application, we show that our algorithm can identify the status of each node of n-dimensional star graph Sn if the faulty node number does not exceed 3n−8. Compared with existing algorithms, our algorithm allows more faulty nodes in a multiprocessor system. © 2024 Elsevier B.V.

关键词： Computational complexity

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Location Analysis Probing Rockets in Ground with Telemetry Data

Location Analysis Probing Rockets in Ground with Telemetry D...

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International Symposium on Instrumentation Systems, Circuits and Transducers (INSCIT)

作者： Nilton Rodrigues Cantanhede Ewaldo Eder Carvalho Santana Paulo Fernandes da Silva Júnior Raimundo Carlos Silvério Freire Tiago Pereira Santana Lúcio Flávio de Albuquerque Campos Gabrielle Muniz Fernandes Maria Tereza Cunha de Albuquerque Sophia Viana Macedo Graduate Program in Electrical Engineering Federal University of Maranhão São Luís Brazil Graduate Program in Computer and System Engineering State University of Maranhão São Luís Brazil Graduate Program in Electrical Engineering Federal University of Campina Grande Campina Grande Brazil Graduate Program in Computational Engineering and Systems State University of Maranhão São Luís Brazil Undergraduate Program in Computational Engineering State University of Maranhão São Luís Brazil Graduate Program in Electrical Engineering Federal University of Paraiba João Pessoa Brazil

ISBN: (数字)9798350350869

ISBN: (纸本)9798350350876

Rocket launch centers are crucial in technological development across various fields, including meteorology, long-distance real-time communications, geoprocessing, and satellite operations. However, one of the challenges in tracking probing rockets is accurately identifying their position from the moment of launch until the initial seconds, due to ground noise that interferes with traditional radar location systems. In this study is proposed an innovative method to precisely determine the distance between the rocket and the ground telemetry station. We utilize onboard telemetry signals processed by the Acquisition and Processing Data Trajectory (APDtraj) system, developed by Delsis Aerospace for the Launch Center. This system enables the identification of the rocket's position both on the ground and during the early stages of flight, using telemetry data processed by APDtraj. This monitoring equipment alone calculated the distance between the Telemetry Station and the rocket just moments before launch lift-off with an error of only 16.844 meters from the actual position of origin. Based on our studies, we were able to measure the radial distance and location between the rocket and the telemetry station just four seconds after launch, even without reliable radar information, which is often disrupted by ground noise. This technological advancement not only enhances the efficiency of rocket launch operations but also expands overall tracking capabilities.

关键词： Rockets Transducers Satellites Radar measurements Spaceborne radar Noise Radar tracking Real-time systems Trajectory Telemetry

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Innovations in Social Informatic: A Patent Landscape Review

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Procedia computer Science 2024年 234卷 1228-1235页

作者： Nur Afia Agung Purnomo Fairuz Iqbal Maulana Yogi Tri Prasetyo Ma. Janice J. Gumasing Elsa Rosyidah Satria Fadil Persada Institute for Research and Community Services Universitas Nahdlatul Ulama Sidoarjo Sidoarjo 61234 Indonesia English Language Education Universitas Nahdlatul Ulama Sidoarjo Sidoarjo 61234 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department Bina Nusantara University Jakarta 11480 Indonesia School of Industrial Engineering and Engineering Management Mapúa University Manila 1002 Philippines International Bachelor Program in Engineering Yuan Ze University Taoyuan 32003 Taiwan

Patent intellectual property in social informatics with entrepreneurship support creates greater opportunities to improve human life. It has the potential to open enormous innovation opportunities in various fields, such as technology, health, services, and society. This research was conducted to review the patent landscape and the main trends of patents on social informatics in all countries. Researchers applied a patent landscape analysis using data on 487 patent documents over 16 years from the *** database. The study results show yearly patented development patterns related to social informatics. There is a royalty-free opportunity by using 15 patent discontinued. Patent related to social informatics was dominated by company ownership and inventors from the United States. The patent physics (G) section overwhelmed patents related to social informatics. There were 334 simple family patents on social informatics in nine jurisdictions; the United States was the highest.

关键词： entrepreneurship, patent, social informatics innovation

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Towards More Robust Natural Language Understanding

arXiv

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arXiv 2021年

作者： Zhang, Xinliang Undergraduate Program in Computer Science and Engineering The Ohio State University United States

Natural Language Understanding (NLU) is a branch of Natural Language Processing (NLP) that uses intelligent computer software to understand texts that encode human knowledge. Recent years have witnessed notable progress across various NLU tasks with deep learning techniques, especially with pretrained language models. Besides proposing more advanced model architectures, constructing more reliable and trustworthy datasets also plays a huge role in improving NLU systems, without which it would be impossible to train a decent NLU model. It’s worth noting that the human ability of understanding natural language is flexible and robust. On the contrary, most of existing NLU systems fail to achieve desirable performance on out-of-domain data or struggle on handling challenging items (e.g., inherently ambiguous items, adversarial items) in the real world. Therefore, in order to have NLU models understand human language more effectively, it is expected to prioritize the study on robust natural language understanding. In this thesis, we deem that NLU systems are consisting of two components: NLU models and NLU datasets. As such, we argue that, to achieve robust NLU, the model architecture/training and the dataset are equally important. Specifically, we will focus on three NLU tasks to illustrate the robustness problem in different NLU tasks and our contributions (i.e., novel models and new datasets) to help achieve more robust natural language understanding. The major technical contributions of this thesis are: 1. We study how to utilize diversity boosters (e.g., beam search & QPP) to help neural question generator synthesize diverse QA pairs, upon which a Question Answering (QA) system is trained to improve the generalization on the unseen target domain. It’s worth mentioning that our proposed QPP (question phrase prediction) module, which predicts a set of valid question phrases given an answer evidence, plays an important role in improving the cross-domain generalizability

关键词： Natural language processing systems

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AI Recommendations: Friend or Foe? Unraveling the Impact on Consumer Benefits and Privacy

AI Recommendations: Friend or Foe? Unraveling the Impact on ...

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International Conference on ICT For Smart Society (ICISS)

作者： Desyra Sukma Dewanthi Hari Kristopo Nunung Nurul Qomariyah Muhammad Axel Management Department Business Management & Marketing Program BINUS Business School International Undergraduate Program Bina Nusantara University Jakarta Indonesia Food Technology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computing and Creative Arts Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Artificial Intelligence (AI) and marketing have transformed consumer behavior and shopping experiences, especially through Recommender Systems (RSs) in e-commerce. RSs use algorithms to provide personalized recommendations, enhancing shopping convenience. However, this raises data privacy and ethical concerns, as RSs rely on user data. This research explores the quality determinants of RSs and their impact on consumer behavior, focusing on privacy awareness and its effect on repurchase intentions. Using a qualitative approach with semi-structured interviews, the study targets Indonesian respondents aged 18–40 with e-commerce experience. Findings reveal that recommendation quality, especially self-reference and vividness, significantly influences purchasing decisions. Respondents prefer recommendations that match their preferences and are visually appealing. Positive shopping experiences are linked to efficient and accurate RSs, but there's a need for improvements in transparency, novelty, diversity, and advanced technologies like AR. Respondents are aware of digital data storage but have limited understanding of privacy concerns. They trust e-commerce platforms with basic personal details but are hesitant to share sensitive information. Despite privacy issues, e-commerce remains vital, with respondents emphasizing the need for transparency, robust security, and clear explanations for data use to maintain trust. Addressing these issues not only enhances customer experience but also demonstrates that consumer trust directly impacts the sustainability and success of the business.

关键词： Data privacy Privacy Consumer behavior Focusing Electronic commerce Security Artificial intelligence Sustainable development Interviews Recommender systems

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A Comparison Diagnosis Algorithm for Conditional Fault Local Diagnosis of Multiprocessor Systems 25th

A Comparison Diagnosis Algorithm for Conditional Fault Loca...

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25th International computer Symposium on New Trends in computer Technologies and Applications, ICS 2022

作者： Lv, Yali Lin, Cheng-Kuan Hsu, D. Frank Fan, Jianxi School of Information Technology Henan University of Chinese Medicine Zhengzhou China Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan Undergraduate Degree Program of Systems Engineering and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Computer Science and Information Engineering Chung Cheng Institute of Technology NDU Taoyuan City Taiwan Department of Computer and Information Science Fordham University New York United States School of Computer Science and Technology Soochow University Suzhou China

ISBN: (纸本)9789811995811

An efficient diagnosis is very important for a multiprocessor system. In this paper, we present a (α, β) -trees combination S(u, X, α, β) and give some conclusions about the local diagnosis. Based on the (α, β) -trees combination, we give a conditional fault local diagnosis algorithm to identify the fault or fault-free status of each processor correctly under the MM ∗ model when the number of faulty nodes does not exceed α+ 2 β- 3 and every node has at least one fault-free neighboring node. According to our results, a connected network with a (α, β) -trees combination S(u, X, α, β) for a node u is conditionally locally (α+ 2 β- 3 ) -diagnosable at node u and the time complexity of our algorithm to diagnose u is O(α2β+ αβ2). As an application, we show that our algorithm can identify all the faulty nodes of n-dimensional star graph Sn if the faulty node number does not exceed 3 n- 8. Compared with existing algorithms, our algorithm allows more faulty node in a multiprocessor system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computational complexity

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Cross-system biological image quality enhancement based on the generative adversarial network as a foundation for establishing a multi-institute microscopy cooperative network

arXiv

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arXiv 2024年

作者： Panek, Dominik Rząca, Carina Szczypior, Maksymilian Sorysz, Joanna Misztal, Krzysztof Baster, Zbigniew Rajfur, Zenon Doctoral School of Exact and Natural Sciences Jagiellonian University ul. Lojasiewicza 11 Kraków30-348 Poland Department of Molecular and Interfacial Biophysics Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University ul. Lojasiewicza 11 Kraków30‑348 Poland Undergraduate Program in Biophysics Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University ul. Lojasiewicza 11 Kraków30‑348 Poland Undergraduate program in Biomedical Engineering Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Al. A. Mickiewicza 30 Building B-1 Kraków30-059 Poland Division of Computational Mathematics Faculty of Mathematics and Computer Science Jagiellonian University 6 Lojasiewicza St. Kraków Poland

High-quality fluorescence imaging of biological systems is limited by processes like photobleaching and phototoxicity, and also in many cases, by limited access to the latest generations of microscopes. Moreover, low temporal resolution can lead to a motion blur effect in living systems. Our work presents a deep learning (DL) generative-adversarial approach to the problem of obtaining high-quality (HQ) images based on their low-quality (LQ) equivalents. We propose a generative-adversarial network (GAN) for contrast transfer between two different separate microscopy systems: a confocal microscope (producing HQ images) and a wide-field fluorescence microscope (producing LQ images). Our model proves that such transfer is possible, allowing us to receive HQ-generated images characterized by low mean squared error (MSE) values, high structural similarity index (SSIM), and high peak signal-to-noise ratio (PSNR) values. For our best model in the case of comparing HQ-generated images and HQ-ground truth images, the median values of the metrics are 6·10-4, 0.9413, and 31.87, for MSE, SSIM, and PSNR, respectively. In contrast, in the case of comparison between LQ and HQ ground truth median values of the metrics are equal to 0.0071, 0.8304, and 21.48 for MSE, SSIM, and PSNR respectively. Therefore, we observe a significant increase ranging from 14% to 49% for SSIM and PSNR respectively. These results, together with other single-system cross-modality studies, provide proof of concept for further implementation of a cross-system biological image quality enhancement. © 2024, CC BY-SA.

关键词： Fluorescence imaging

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Detecting Face Masks Through Embedded Machine Learning Algorithms: A Transfer Learning Approach for Affordable Microcontrollers

SSRN

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SSRN 2023年

作者： Azevedo, Mariana B. de Medeiros, Thaís de A. Medeiros, Morsinaldo de A. Silva, Ivanovitch Costa, Daniel G. Undergraduate Program in Computer Engineering Federal University of Rio Grande do Norte RN Natal59078-970 Brazil Federal Univesity of Rio Grande do Norte RN Natal59078-970 Brazil State University of Feira de Santana Brazil

The adoption of face masks to halt the spread of airborne diseases has been recognized as an effective measure, being a significant resource to reduce new infections of different types of virus that affect the respiratory system. In this sense, the enforcement of the use of masks in crowded areas has been a recurrent concern of governments, which has fostered the development of camera-based approaches to automatically detect people without face masks. In order to tackle this problem, this article proposes a low-cost approach based on the use of affordable and energy-efficient microcontrollers to quickly process images and detect when people are not wearing face masks, performing local decisions. For this on-the-edge processing, reduced Machine Learning models were created and evaluated through different techniques. As a result, a complete processing pipeline was designed to perform a transfer learning process taking as reference the MobileNet model supported by the Edge Impulse platform, achieving an innovative TinyML solution for quick decisions on resource-constrained Internet of Things units. Additionally, we performed a series of experiments on the Arduino Nano 33 board attached to an OV7675 camera module, evaluating the practical application of the proposed solution after proper training using public image datasets. Working as a soft-sensor unit that is reproducible and ready to be used, the defined trainable model and the performed evaluation results represent a significant contribution towards real-world deployment of face masks detection systems. © 2023, The Authors. All rights reserved.

关键词： Machine learning

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