• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.1
• /
• pp.117-128
• /
• 2023

Due to the full revision of the Digital Signature Act (enforcement on December 10, 2020), various certificates are being released and competing in the market. Under fierce competition, the certificate market share of large IT platform companies is increasing, and it is predicted that they will eventually monopolize the market. Therefore, identifying the consumer's certificate choice factors and understanding the difference in importance between the choice factors are essential elements for establishing a company's strategy for the certificate market and product positioning, and are key points in setting the government's certificate policy direction. In this study, consumers' certificate choice factors were extracted based on the details of preceding papers and surveys, and based on the extracted choice factors, 4 choice factors (reliability of issuer, program installation, certificate usage method(how to use), versatility(where to use)) were identified through a Delphi survey. As a result of conjoint analysis by conducting a consumer survey with selected choice factors, the reliability of the issuer was found to be the most important utility value. In order of importance, the certificate usage method(how to use), program installation, and versatility(where to use) appeared.

• Journal of the Korean Society for Library and Information Science
• /
• v.56 no.1
• /
• pp.405-423
• /
• 2022

The purpose of this study was to establish a national R&D lifecycle and to propose a research support service plan. In particular, in terms of providing research support services, a plan to provide services in connection with IRIS and NTIS, which are national research support systems, was proposed. To this end, the current status of IRIS and NTIS was analyzed, a linkage plan according to the role of each system was proposed, and an R&D lifecycle was established by analyzing previous studies and cases at home and abroad. Through current status analysis and case analysis, research support services that can be provided at each stage on the entire R&D lifecycle were proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.469-472
• /
• 2022

With the recent development of intelligent transportation systems, various technologies applying deep learning technology are being used. To crackdown on illegal vehicles and criminal vehicles driving on the road, a vehicle type classification system capable of accurately determining the type of vehicle is required. This study proposes a vehicle type classification system optimized for mobile traffic control systems using YOLO(You Only Look Once). The system uses a one-stage object detection algorithm YOLOv5 to detect vehicles into six classes: passenger cars, subcompact, compact, and midsize vans, full-size vans, trucks, motorcycles, special vehicles, and construction machinery. About 5,000 pieces of domestic vehicle image data built by the Korea Institute of Science and Technology for the development of artificial intelligence technology were used as learning data. It proposes a lane designation control system that applies a vehicle type classification algorithm capable of recognizing both front and side angles with one camera.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.12
• /
• pp.347-356
• /
• 2023

In the recent war between Ukraine and Russia, low-orbit satellite communication played a major role, and Korea laid a foothold for low-orbit satellite communication services with the successful launch of Nuri in May 2023 and entered a full-scale civilian space age competition. In order to create an ecosystem for ICT digital transformation and data convergence in the field of low-orbit satellite communication, this paper conducts user sentiment analysis by importing posts from Reddit, one of the world's SNS, and extracts need-related sentences through need mining to identify user needs, performs topic modeling to classify topics, and prepares an action plan according to these topics. We hope that this study will be used as a policy resource for the development and innovation of new business models in the field of low-orbit satellite communication, bridging the digital information gap and solving social problems, contributing to sustainable digital transformation and enhancing soft power.

• Journal of Information Science Theory and Practice
• /
• v.12 no.1
• /
• pp.60-76
• /
• 2024

Broadband Internet has proven to be vital for economic growth in developed countries. Developing countries have implemented several initiatives to increase their broadband access. However, its full potential can only be realized through adoption and use. With lower-middle-income countries accounting for the majority of the world's unconnected population, this study employs the theory of planned behavior (TPB) to investigate users' intentions to adopt broadband. Rural Tanzania was chosen as a case study. A cross-sectional study was conducted over three weeks, using 155 people from seven villages with the lowest broadband adoption rates. Non-probability voluntary response sampling was used to recruit the participants. Using the TPB constructs: attitude toward behavior (ATB), subjective norms (SN), and perceived behavioral control (PBC), ordinal regression analysis was employed to predict intention. Descriptive statistical analysis yielded mean scores (standard deviation) as 3.59 (0.46) for ATB, 3.34 (0.40) for SN, 3.75 (0.29) for PBC, and 4.12 (0.66) for intention. The model adequately described the data based on a comparison of the model with predictors and the null model, which revealed a substantial improvement in fit (p<0.05). Moreover, the predictors accounted for 50.3% of the variation in the intention to use broadband Internet, demonstrating the predictive power of the TPB constructs. Furthermore, the TPB constructs were all significant positive predictors of intention: ATB (β=1.938, p<0.05), SN (β=2.144, p<0.05), and PBC (β=1.437, p=0.013). The findings of this study provide insight into how behavioral factors influence the likelihood of individuals adopting broadband Internet and could guide interventions through policies meant to promote broadband adoption.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.26 no.1
• /
• pp.45-60
• /
• 2024

This study analyzes the athleisure wear purchase status, wearing conditions, and design preferences of men in their 20s and 30s and provides basic data for the development of men's athleisure wear that reflects consumer preferences. An online survey was conducted on 200 men from August 23 to August 27, 2023. The questionnaire consisted of a total of 48 questions, including 8 questions about the respondent's general information, 19 questions about the purchase status of athleisure wear, 6 questions about the status of wearing athleisure wear, and 15 questions about athleisure wear design preferences. The survey results are as follows. The most common motive for exercise participation was 'maintaining health.' 'Nike' was the most preferred and purchased brand among athleisure wear brands, and the main place of purchase of athleisure wear was 'Internet and mobile shopping malls', reflecting the recent purchasing trend of the MZ generation. When purchasing athleisure wear, the most common selection criterion was 'design', followed by 'fitting comfort', 'possibility to use as daily wear', and 'price'. The most common route to obtain purchase information was 'Internet search', and the 'overall satisfaction' with athleisure wear was found to be satisfactory with an average of 3.83. The most common reason for wearing athleisure wear was 'because it is comfortable to do activities', followed by 'because it can be used as everyday wear'. Lastly, 'black', 'short-sleeved t-shirt', 'short length' sleeve, 'round neckline', 'waist length', and 'relaxed loose fit' were preferred for the top design, and 'black', 'shorts', 'full elastic type' waistband, 'regular fit that fits the body well' were preferred for the bottom design.

• Journal of Ecology and Environment
• /
• v.47 no.4
• /
• pp.219-227
• /
• 2023

The US National Science Foundation's National Ecological Observatory Network (NEON) is a continental-scale program intended to provide open data, samples, and infrastructure to understand changing ecosystems for a period of 30 years. NEON collects co-located measurements of drivers of environmental change and biological responses, using standardized methods at 81 field sites to systematically sample variability and trends to enable inferences at regional to continental scales. Alongside key atmospheric and environmental variables, NEON measures the biodiversity of many taxa, including microbes, plants, and animals, and collects samples from these organisms for long-term archiving and research use. Here we review the composition and use of NEON resources to date as a whole and specific to biodiversity as an exemplar of the potential of national research infrastructure to contribute to globally relevant outcomes. Since NEON initiated full operations in 2019, NEON has produced, on average, 1.4 M records and over 32 TB of data per year across more than 180 data products, with 85 products that include taxonomic or other organismal information relevant to biodiversity science. NEON has also collected and curated more than 503,000 samples and specimens spanning all taxonomic domains of life, with up to 100,000 more to be added annually. Various metrics of use, including web portal visitation, data download and sample use requests, and scientific publications, reveal substantial interest from the global community in NEON. More than 47,000 unique IP addresses from around the world visit NEON's web portals each month, requesting on average 1.8 TB of data, and over 200 researchers have engaged in sample use requests from the NEON Biorepository. Through its many global partnerships, particularly with the Global Biodiversity Information Facility, NEON resources have been used in more than 900 scientific publications to date, with many using biodiversity data and samples. These outcomes demonstrate that the data and samples provided by NEON, situated in a broader network of national research infrastructures, are critical to scientists, conservation practitioners, and policy makers. They enable effective approaches to meeting global targets, such as those captured in the Kunming-Montreal Global Biodiversity Framework.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.1
• /
• pp.25-30
• /
• 2024

The modern society has become full-fledged entry into the information age since spread of Internet. In the information age, internet was developed from the wired access to the wireless Internet access. When a surge in demand for wireless Internet access, efficiency and performance of 2.4GHz band which leads to saturation of the communication was significantly fall. Accordingly, the communication of the 5GHz band came to be interested. In this paper, we studied the design and fabrication of u-slot microstrip patch antenna to be used in wireless communication systems operating at around 5GHz band. To obtain antenna parameters such as patch size, inter patch space, antenna was simulated by HFSS(High Frequency Structure Simulator). From these parameters, u-slot microstrip antenna is fabricated using FR-4 substrate of dielectric constant 4.4. The characteristics of fabricated antenna were analyzed by network analyzer.

• Physical Therapy Korea
• /
• v.31 no.2
• /
• pp.174-181
• /
• 2024

Background: Effective management of clinical assessment tools is critical in stroke and brain injury rehabilitation research. Managing rehabilitation outcome measures (ROMs) scores and training therapists in multicenter randomized clinical trials (RCTs) is challenging. Objects: The aim of this study was to develop a web-based platform, the Korean Rehabilitation Outcome Measurement (KoROM), to address these limitations and improve both therapist training and patient involvement in the rehabilitation process. Methods: The development of the KoROM spanned from June 2021 to July 2022, and included literature and web-based searches to identify relevant ROMs and design a user-friendly platform. Feedback from six physical therapy and informatics experts during pilot testing refined the platform. Results: Several clinical assessment tools categorized under the International Classification of Functioning, Disability, and Health (ICF) model are categorized in the KoROM. The therapist version includes patient management, assessment tool information, and data downloads, while the patient version provides a simplified interface for viewing scores and printing summaries. The master version provides full access to user information and clinical assessment scores. Therapists enter clinical assessment scores into the KoROM and learn ROMs through instructional videos and self-checklists as part of the therapist standardization process. Conclusion: The KoROM is a specialized online platform that improves the management of ROMs, facilitates therapist education, and promotes patient involvement in the rehabilitation process. The KoROM can be used not only in multi-site RCTs, but also in community rehabilitation exercise centers.

• The Transactions of the Korea Information Processing Society
• /
• v.13 no.10
• /
• pp.497-504
• /
• 2024

Generative Adversarial Networks (GANs) are typically described as a two-player game between a generator and a discriminator, where the generator aims to produce realistic data, and the discriminator tries to distinguish between real and generated data. However, this setup often leads to mode collapse, where the generator produces limited variations in the data, failing to capture the full range of the target data distribution. This paper proposes a new training system to mitigate the mode collapse problem. Specifically, it extends the traditional two-player game of GANs into a multi-player game and introduces a peer-evaluation method to effectively train multiple GANs. In the peer-evaluation process, the generated samples from each GANs are evaluated by the other players. This provides external feedback, serving as an additional standard that helps GANs recognize mode failure. This cooperative yet competitive training method encourages the generators to explore and capture a broader range of the data distribution, mitigating mode collapse problem. This paper explains the detailed algorithm for peer-evaluation based multi-GANs training and validates the performance through experiments.