• Title/Summary/Keyword: Usability Evaluation

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An Empirical Study on the Intention to Continue Using Generative AI in Engaged Learning: Focusing on the ChatGPT Case (참여형 학습에서 생성형 AI 지속 사용 의도에 대한 실증적 연구: ChatGPT 사례 중심으로)

  • Kyungsoon Kim;Nacil Kim;Myoungsoo Kim;Yongtae Shin
    • Journal of Information Technology Services
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    • v.22 no.6
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    • pp.17-35
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    • 2023
  • This study investigated how helpful the use of generative AI such as ChatGPT is in conducting engaged learning at each university. In this study, based on the experiences of users using generative AI technology, we analyzed the relationship between usability and ease in consideration of the characteristics of learners, and examined whether there is an intention to continue using generative AI technology in the future. In this study, in order to verify the factors affecting the intention to use ChatGPT technology in order to solve the problems given in the participating classes, we examined previous papers based on the Technology Acceptance Model (TAM) and the Information System Success Model (IS), extracted the factors affecting the intention of ChatGPT technology, and presented the research model and hypothesis. Empirical research on the continuous use of generative AI in participatory learning using ChatGPT was conducted to determine whether it is suitable for long-term and continuous use in the educational environment, and whether it is sustainable by examining the intention of learners to continue using it. First, user satisfaction was positively related to the intention to continue using generative AI technology. Second, if the user experience has a great influence on the intention to continue using ChatGPT technology, and users gain experiences such as usefulness, interest, and effective response in the process of using the technology, the evaluation of the technology is positively formed and the intention to continue using it is high. Third, the ease of use of the technology also showed that it was intended to be used continuously when an environment was provided in which users could easily and conveniently utilize generative AI technology.

Performance Improvement of Facial Gesture-based User Interface Using MediaPipe Face Mesh (MediaPipe Face Mesh를 이용한 얼굴 제스처 기반의 사용자 인터페이스의 성능 개선)

  • Jinwang Mok;Noyoon Kwak
    • Journal of Internet of Things and Convergence
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    • v.9 no.6
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    • pp.125-134
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    • 2023
  • The purpose of this paper is to propose a method to improve the performance of the previous research is characterized by recognizing facial gestures from the 3D coordinates of seven landmarks selected from the MediaPipe Face Mesh model, generating corresponding user events, and executing corresponding commands. The proposed method applied adaptive moving average processing to the cursor positions in the process to stabilize the cursor by alleviating microtremor, and improved performance by blocking temporary opening/closing discrepancies between both eyes when opening and closing both eyes simultaneously. As a result of the usability evaluation of the proposed facial gesture interface, it was confirmed that the average recognition rate of facial gestures was increased to 98.7% compared to 95.8% in the previous research.

Metaverse Artifact Analysis through the Roblox Platform Forensics (메타버스 플랫폼 Roblox 포렌식을 통한 아티팩트 분석)

  • Yiseul Choi;Jeongeun Cho;Eunbeen Lee;Hakkyong Kim;Seongmin Kim
    • Convergence Security Journal
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    • v.23 no.3
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    • pp.37-47
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    • 2023
  • The growth of the metaverse has been accelerated by the increased demand for non-face-to-face interactions due to COVID-19 and advancements in technologies such as blockchain and NFTs. However, with the emergence of various metaverse platforms and the corresponding rise in users, criminal cases such as ransomware attacks, copyright infringements, and sexual offenses have occurred within the metaverse. Consequently, the need for artifacts that can be utilized as digital evidence within metaverse systems has increased. However, there is a lack of information about artifacts that can be used as digital evidence. Furthermore, metaverse security evaluation and forensic analysis are also insufficient, and the absence of attack scenarios and related guidelines makes forensics challenging. To address these issues, this paper presents artifacts that can be used for user behavior analysis and timeline analysis through dynamic analysis of Roblox, a representative metaverse gaming solution. Based on analyzing interrelationship between identified artifacts through memory forensics and log file analysis, this paper suggests the potential usability of artifacts in metaverse crime scenarios. Moreover, it proposes improvements by analyzing the current legal and regulatory aspects to address institutional deficiencies.

Gesture Control Gaming for Motoric Post-Stroke Rehabilitation

  • Andi Bese Firdausiah Mansur
    • International Journal of Computer Science & Network Security
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    • v.23 no.10
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    • pp.37-43
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    • 2023
  • The hospital situation, timing, and patient restrictions have become obstacles to an optimum therapy session. The crowdedness of the hospital might lead to a tight schedule and a shorter period of therapy. This condition might strike a post-stroke patient in a dilemma where they need regular treatment to recover their nervous system. In this work, we propose an in-house and uncomplex serious game system that can be used for physical therapy. The Kinect camera is used to capture the depth image stream of a human skeleton. Afterwards, the user might use their hand gesture to control the game. Voice recognition is deployed to ease them with play. Users must complete the given challenge to obtain a more significant outcome from this therapy system. Subjects will use their upper limb and hands to capture the 3D objects with different speeds and positions. The more substantial challenge, speed, and location will be increased and random. Each delegated entity will raise the scores. Afterwards, the scores will be further evaluated to correlate with therapy progress. Users are delighted with the system and eager to use it as their daily exercise. The experimental studies show a comparison between score and difficulty that represent characteristics of user and game. Users tend to quickly adapt to easy and medium levels, while high level requires better focus and proper synchronization between hand and eye to capture the 3D objects. The statistical analysis with a confidence rate(α:0.05) of the usability test shows that the proposed gaming is accessible, even without specialized training. It is not only for therapy but also for fitness because it can be used for body exercise. The result of the experiment is very satisfying. Most users enjoy and familiarize themselves quickly. The evaluation study demonstrates user satisfaction and perception during testing. Future work of the proposed serious game might involve haptic devices to stimulate their physical sensation.

App Development and Usability Evaluation for Caregivers (돌봄 제공자를 위한 디지털 돌봄 앱 개발 및 사용성 평가)

  • Jongchan, Park;Jaegook Kim;Euijae Chung;Changsun Ahn;Bongsu Jung;Youngjoo Kim
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.11
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    • pp.337-346
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    • 2023
  • There is a need to develop an app for a caregiver health management that can provide continuous management in response to changes over time, because elderly people have low digital utilization capabilities, difficulty maintaining regular and continuous self-management. Based on this need, this study designed an app with a user-friendly UI and simple structure for the elderly. The app developed in this study supports regular management of health data such as blood pressure, blood sugar, and heart rate, as well as specific information on physical, disease, cognitive, communication, and environment in the care field. The app developed in this study supports care services by automatically entering data through integration with health management devices, automatically analyzing and visually representing recorded data to understand trends and volatility, and adding scalability to connect with various health management and medical support platforms. The effectiveness and satisfaction of the developed app were confirmed to be significant in the field verification results.

Privacy-Preserving Cloud Data Security: Integrating the Novel Opacus Encryption and Blockchain Key Management

  • S. Poorani;R. Anitha
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.11
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    • pp.3182-3203
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    • 2023
  • With the growing adoption of cloud-based technologies, maintaining the privacy and security of cloud data has become a pressing issue. Privacy-preserving encryption schemes are a promising approach for achieving cloud data security, but they require careful design and implementation to be effective. The integrated approach to cloud data security that we suggest in this work uses CogniGate: the orchestrated permissions protocol, index trees, blockchain key management, and unique Opacus encryption. Opacus encryption is a novel homomorphic encryption scheme that enables computation on encrypted data, making it a powerful tool for cloud data security. CogniGate Protocol enables more flexibility and control over access to cloud data by allowing for fine-grained limitations on access depending on user parameters. Index trees provide an efficient data structure for storing and retrieving encrypted data, while blockchain key management ensures the secure and decentralized storage of encryption keys. Performance evaluation focuses on key aspects, including computation cost for the data owner, computation cost for data sharers, the average time cost of index construction, query consumption for data providers, and time cost in key generation. The results highlight that the integrated approach safeguards cloud data while preserving privacy, maintaining usability, and demonstrating high performance. In addition, we explore the role of differential privacy in our integrated approach, showing how it can be used to further enhance privacy protection without compromising performance. We also discuss the key management challenges associated with our approach and propose a novel blockchain-based key management system that leverages smart contracts and consensus mechanisms to ensure the secure and decentralized storage of encryption keys.

Utilization of Generative Artificial Intelligence Chatbot for Training in Suicide Risk Assessment of Depressed Patients: Focusing on Students at a College of Korean Medicine (우울증 환자의 자살 위험 평가의 훈련을 위한 생성형 인공지능 챗봇의 의학적 교육 활용 사례: 일개 한의과대학 학생을 중심으로)

  • Chan-Young Kwon
    • Journal of Oriental Neuropsychiatry
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    • v.35 no.2
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    • pp.153-162
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    • 2024
  • Objectives: Among OECD countries, South Korea has been having the highest suicide rate since 2018, with 24.1 deaths per 100,000 people reported in 2020. The objectie of this study was to examine the use of generative artificial intellicence (AI) chatbots to train third-year Korean medicine (KM) students in conducting suicide risk assessments for patients with depressive disorders to train students for their clinical practice skills. Methods: The Claude 3 Sonnet model was utilized for chatbot simulations. Students performed mock consultations using standardized suicide risk assessment tools including Ask Suicide-Screening Questions (ASQ) tool and ASQ Brief Suicide Safety Assessment. Experiences and attitudes were collected through an anonymous online survey. Responses were rated on a 1~5 Likert scale. Results: Thirty-six students aged 22~30 years participated in this study. Their scores for interest and appropriateness (4.66±0.57), usefulness (4.60±0.61), and overall experience (4.63±0.60) were high. Their evaluation of the usability of artificial intelligence chatbot was also high at 4.58±0.70 points. However, their trust in chatbot responses (Q12) was lower (3.86±0.99). Common issues related to dissatisfaction included conversation disruptions due to token limits and inadequate chatbot responses. Conclusions: This is the first study investigating generative AI chatbots for suicide risk assessment training in KM education. Students reported high satisfaction, although their trust in chatbot accuracy was moderate. Technical limitations affected their experience. These preliminary findings suggest that generative AI chatbots hold promise for clinical training, particularly for education in psychiatry. However, improvements in response accuracy and conversation continuity are needed.

Long-term Usability Evaluation of Low Fish Meal Extruded Pellet Diet for Juvenile Olive Flounder Paralichthys olivaceus at Jeju Fish Farm (제주도 양식장 내 치어기 넙치(Paralichthys olivaceus)의 저어분 EP (Extruded Pellet) 사료 장기간 이용성 평가)

  • Hyunwoon Lim;Jaesik Kim;Daehyun Ko;Jin-Woo Song;Seunghan Lee;Sang-Woo Hur;Kang-Woong Kim;Kyeong-Jun Lee
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.57 no.1
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    • pp.23-31
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    • 2024
  • This study evaluated the utilization of a low fish meal (LFM) diet and black soldier fly (BSF) Hermetia illucens meal and oil as a fish meal (FM) substitute or functional additive for juvenile olive flounder Paralichthys olivaceus at the Jeju fish farm. Two experimental diets replaced FM using animal (tankage, poultry byproduct and tuna byproduct meal) and plant (wheat gluten and soy protein concentrate) protein sources, containing 45% (FM45) and 35% (FM35) of FM, respectively. One experimental diet replaced FM with animal, plant, and BSF meal, fish oil using insect meal and oil (FM35+). After the feeding trial ended, no differences in growth performance, feed utilization, survival and biological indices were observed among all experimental groups. Aspartate aminotransferase and cholesterol levels in the FM35 and FM35+ groups were significantly higher than that in the FM70 group. The linoleic acid level in the muscle was significantly higher in the fish fed with the FM70 diet than in those fed with the FM45, FM35, and FM35+ diets. Thus, the LFM diet is suitable for juvenile olive flounder farming during six months.

EDF: An Interactive Tool for Event Log Generation for Enabling Process Mining in Small and Medium-sized Enterprises

  • Frans Prathama;Seokrae Won;Iq Reviessay Pulshashi;Riska Asriana Sutrisnowati
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.6
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    • pp.101-112
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    • 2024
  • In this paper, we present EDF (Event Data Factory), an interactive tool designed to assist event log generation for process mining. EDF integrates various data connectors to improve its capability to assist users in connecting to diverse data sources. Our tool employs low-code/no-code technology, along with graph-based visualization, to help non-expert users understand process flow and enhance the user experience. By utilizing metadata information, EDF allows users to efficiently generate an event log containing case, activity, and timestamp attributes. Through log quality metrics, our tool enables users to assess the generated event log quality. We implement EDF under a cloud-based architecture and run a performance evaluation. Our case study and results demonstrate the usability and applicability of EDF. Finally, an observational study confirms that EDF is easy to use and beneficial, expanding small and medium-sized enterprises' (SMEs) access to process mining applications.

A Study on the Design of Sustainable App Services for Medication Management and Disposal of Waste Drugs (약 복용 관리와 폐의약품 처리를 위한 지속 가능한 앱 서비스 디자인 연구)

  • Lee, Ri-Na;Hwang, Jeong-Un;Shin, Ji-Yoon;Hwang, Jin-Do
    • Journal of Service Research and Studies
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    • v.14 no.2
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    • pp.48-68
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    • 2024
  • Due to the global pandemic aftermath of the coronavirus, the importance of health care is being emphasized more socially. Due to the influence of these changes, domestic pharmaceutical companies have introduced regular drug delivery services, that is, drug and health functional food subscription services. Currently, this market is continuously growing. However, these regular services are causing new environmental problems in which the number of waste drugs increases due to the presence of unused drugs. Therefore, this study proposes a service that not only promotes health management through regular medication adherence to reduce the amount of pharmaceutical waste but also aims to improve awareness and practices regarding proper medication disposal. As a preliminary survey for service design, a preliminary survey was conducted on 51 adults to confirm their perception of drug use habits and waste drug collection. Based on the Honey Comb model, a guideline for service design was created, and a prototype was produced by specifying the service using the preliminary survey results and service design methodology. In order to verify the effectiveness of the prototype, a first user task survey was conducted to identify the problems of the prototype, and after improving this, a second usability test was conducted on 49 adults to confirm the versatility of the service. Usability verification was conducted using SPSS Mac version 29.0. For the evaluation results of the questionnaire, Spearmann Correlation Analysis was conducted to confirm the relationship between frequency analysis and evaluation items. This study presents specific solutions to the problem of waste drugs due to the spread of drug subscription services.