• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.542-558
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• 2023

A digital focus index (DFI) is a value used to determine image focus in scientific apparatus and smart devices. Automatic focus (AF) is an iterative and time-consuming procedure; however, its processing time can be reduced using a general processing unit (GPU) and a multi-core processor (MCP). In this study, parallel architectures of a minimax search algorithm (MSA) are applied to two DFIs: range algorithm (RA) and image contrast (CT). The DFIs are based on a histogram; however, the parallel computation of the histogram is conventionally inefficient because of the bank conflict in shared memory. The parallel architectures of RA and CT are constructed using parallel reduction for MSA, which is performed through parallel relative rating of the image pixel pairs and halved the rating in every step. The array size is then decreased to one, and the minimax is determined at the final reduction. Kernels for the architectures are constructed using open source software to make it relatively platform independent. The kernels are tested in a hexa-core PC and an embedded device using Lenna images of various sizes based on the resolutions of industrial cameras. The performance of the kernels for the DFIs was investigated in terms of processing speed and computational acceleration; the maximum acceleration was 32.6× in the best case and the MCP exhibited a higher performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.63-70
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• 2023

Due to the spread of high-definition black boxes and the introduction of mobile applications such as 'Smart Citizens Report' and 'Safety Report', the number of public interest reports for violations of Traffic Law has increased rapidly, resulting in shortage of police personnel to handle them. In this paper, we describe the development of a system that can automatically detect lane violations which account for the largest proportion of public interest reporting videos for violations of traffic laws, using deep learning algorithms. In this study, a method for recognizing a vehicle and a solid line object using a YOLO model and a Lanenet model, a method for tracking an object individually using a deep sort algorithm, and a method for detecting lane change violations by recognizing the overlapping range of a vehicle object's bounding box and a solid line object are described. Using this system, it is expected that the shortage of police personnel in charge will be resolved.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.203-209
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• 2023

The paper brings across data that is utilized in the Bring Your Own Device (BYOD) status collected between February and April of 2021 across Saudi Arabia. The data set was collected using questionnaires established through online mechanisms for the respondents. In the questionnaire, personal details included five questions while seven questions addressed the working model of personal mobile devices. Six questions addressed the awareness of employees bring your own device awareness for employees comprised seven questions and two questions addressed the benefits of business achievements. In the identification of suitable respondents for the research, two approaches were applied. The research demanded that the respondents be Saudi Arabian nationals and have attained 18 years. Snowball and purposive techniques were applied in the collection of information from a wide area of Saudi Arabia while employing social media approaches that include the use of WhatsApp and emails in the collection of data. The approach ensured the collection of data from 857 respondents used in the identification of the status as well as issues across the BYOD environment and accompanying solutions. The data was also used in the provision of awareness in the community through short-term courses, cyber security training and awareness programs. The results of the research are therefore applicable to the context of the Saudi Arabian country that is currently facing issues in dealing with the application of personal devices in the work environment.

• Journal of Korean Academy of Nursing
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• v.53 no.1
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• pp.69-86
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• 2023

Purpose: This study aimed to evaluate the effects of digital health interventions on the psychotic symptoms among people with severe mental illness in the community. Methods: A systematic review and meta-analysis were conducted in accordance with the Cochrane Intervention Research Systematic Review Manual and PRISMA. A literature search was conducted of published randomized controlled trials (RCTs) for digital health interventions from January 2022 to April 2022. RevMan software 5.3 was used for quality assessment and meta-analysis. Results: A total 14 studies out of 9,864 studies were included in the review, and 13 were included in meta-analysis. The overall effect size of digital health interventions on psychotic symptoms was - 0.21 (95% CI = - 0.32 to - 0.10). Sub-analysis showed that the reduction of the psychotic symptoms was effective in the schizophrenia spectrum group (SMD = - 0.22; 95% CI = - 0.36 to - 0.09), web (SMD = - 0.41; 95% CI = - 0.82 to 0.01), virtual reality (SMD = - 0.33; 95% CI = - 0.56 to - 0.10), mobile (SMD = - 0.15; 95% CI = - 0.28 to - 0.03), intervention period of less than 3 months (SMD = - 0.23; 95% CI = - 0.35 to - 0.11), and non-treatment group (SMD = - 0.23; 95% CI = - 0.36 to - 0.11). Conclusion: These findings suggest that digital health interventions alleviate psychotic symptoms in patients with severe mental illnesses. However, well-designed digital health studies should be conducted in the future.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.663-668
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• 2023

This paper describes a mobile application that can recognize and identify cats residing on a university campus using the Google's machine learning platform, 'Teachable Machine'. Machine learning, one of the core technologies of the Fourth Industrial Revolution, performs an efficient task of finding optimal results through data learning. Therefore, the model is learned and generated using the platform based on machine learning, and then implemented as an application for smartphones, so that cats can be identified simply and efficiently. In this application, if you take a picture of a cat directly on the spot or call it from the gallery, the cat is identified and information about the cat is provided. Though this system was developed for a specific university campus, it is expected that it can be extended to other campuses and other species of animals.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.465-467
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• 2022

Mobile phones have become an essential item nowadays since it provides access to online platform and service fast and easy. Coming to these platforms such as Social Network Service (SNS) for shopping have been a go-to option for many people. However, searching for a specific fashion item in the picture is challenging, where users need to try multiple searches by combining appropriate search keywords. To tackle this problem, we propose a system that could provide immediate access to websites related to fashion items. In the framework, we also propose a deep learning model for an automatic analysis of image contexts using instance segmentation. We use transfer learning by utilizing Deep fashion 2 to maximize our model accuracy. After segmenting all the fashion item objects in the image, the related search information is retrieved when the object is clicked. Furthermore, we successfully deploy our system so that it could be assessable using any web browser. We prove that deep learning could be a promising tool not only for scientific purpose but also applicable to commercial shopping.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.591-596
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• 2023

This study developed a program that can produce videos easily and conveniently, focusing on teenage media producers. Through user research, we identified the needs and problems of teenage producers, and implemented a character customization function desired by users and an emotion and action recommendation system using GPT. In the rendering process, the final image was created by combining audio and video using OpenCV and FFmpeg. Teenage users who do not have expertise in video production can customize web drama characters through a simple interface and receive recommendations for emotions and actions with the help of GPT. The program of this study is expected to be a tool that can help teenage users who do not have expertise in editing and directing to produce high-quality videos, lower the entry barrier to video production, and contribute to the development of the one-person media industry. do. In the future, we plan to provide a video production environment considering mobile or vertical resolution versions.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.34 no.4
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• pp.192-203
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• 2023

Digital therapeutics based on software, such as artificial intelligence, virtual reality, games, and smartphone applications, are in the spotlight as new therapeutic alternatives in child and adolescent psychiatry. It draws attention to overcoming conventional therapeutics' limitations, such as toxicity, cost, and accessibility, and encourages patients to participate in the treatment attractively. The growth potential of the digital therapeutics market for psychiatric disorders in children and adolescents in Korea and abroad has been highlighted. Clinical studies and Food and Drug Administration approvals for digital therapeutics have increased, and cases approved by the Ministry of Food and Drug Safety have emerged in Korea. As seen above, digital transformation in child and adolescent psychiatry will change treatment paradigms significantly. Therefore, as this new field has just begun to emerge, it is necessary to verify the effectiveness and scope of the application of digital therapeutics and consider preparing a compensation system and institutional arrangements. Accordingly, this study analyzed the development trends and application status of digital therapeutics in children and adolescents and presented limitations and development directions from the perspective of application in healthcare. Further, the study is expected to identify the utility and limitations of digital therapeutics for children and adolescents and establish effective application measures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.126-146
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• 2024

Caladium bicolor is one of the most popular plants in Thailand. The original species of Caladium bicolor was found a hundred years ago. Until now, there are more than 500 species through multiplication. The classification of Caladium bicolor can be done by using its color and shape. This study aims to develop a model to classify Caladium bicolor using a transfer learning technique. This work also presents a proof of concept, GUI design, and web application deployment using the user-design-center method. We also evaluated the performance of the following pre-trained models in this work, and the results are as follow: 87.29% for AlexNet, 90.68% for GoogleNet, 93.59% for XceptionNet, 93.22% for MobileNetV2, 89.83% for RestNet18, 88.98% for RestNet50, 97.46% for RestNet101, and 94.92% for InceptionResNetV2. This work was implemented using MATLAB R2023a.

• Information Systems Review
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• v.21 no.3
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• pp.87-110
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• 2019

The Fintech services provide innovation to financial services users using various mobile devices and computers in wired and wireless communication environments. In this study, we develope a theoretical research framework to explain the psychology of Fintech services users based on a cognitive, affective, and conative framework. Using this framework, this study analyzes the relationships between the cognitive characteristics (i.e., innovation, relative advantage, ease of use, and usefulness), emotional characteristic (i.e., attitude), and behavioral characteristic (i.e., actual use) toward Fintech services users. This study conducted an online survey of people who have experienced using Fintech services. And the data of the collected Fintech services users was analyzed using structural equation model software (i.e., SMART PLS 2.0 M3). The results of the empirical analysis show the relationships between innovation, relative advantage, perceived usefulness, perceived ease of use, attitude, and actual use of Fintech service users. The results of this study provide useful information to improve the practical use of Fintech services users in the Internet of Things (IoT) environment.