• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.321-331
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• 2021

This study sought to analyze factors influencing high-risk drinking in single-person households. For this, data from the 2018 community health survey were used. Subjects were 32,389 adults above the age of 19 in single-person households. For the data analysis, high-risk drinking groups were extracted according to the high-risk drinking rate index of the survey to arrive at influencing factors and differences in health-related and sociodemographic characteristics. The IBM SPSS 25.0 software was used for analysis and a complex sampling design was applied. The results showed that the high-risk drinking rate of Korea's single-person households was 15.0% (male: 25.8%, female: 5.8%) and age, education under high school level, service-industry employees, smokers, people with depression, high blood pressure, and irregular breakfast eaters appeared as common elements for both genders. Stress appeared to only affect males while being diabetic only affected females. High-risk drinking was higher for males in their 30~40s and women in their 20~30s. The younger generation showed the highest numbers in high-risk drinking and factors like stress or depression appeared to be influencing factors for high-risk drinking. Hence, mental health programs along with customized health policies through health forms and lifestyle changes will be required to lower the high-risk drinking rates of single-person households.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.102-116
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• 2021

For the safe operation of autonomous vehicles, the representative technology of the 4^th industrial revolution era, a combination of various technologies such as sensor technology, software technology and car technology is required. An autonomous vehicle is a vehicle that recognizes current location and situation by using the various sensors, and makes its own decisions without depending on the driver. Perfect recognition technology is required for fully autonomous driving. Since the precise road maps provide various road information including lanes, stop lines, traffic lights and crosswalks, it is possible to minimize the cognitive errors that occur in autonomous vehicles by using the precise road maps with location information of the road facilities. In this study, the definition, necessity and technical trends of the precise road map have been analyzed, and the HD(High Definition) map prototype based on the web GIS has been built in the autonomous driving-specialized areas of Daegu Metropolitan City(Suseong Medical District, about 24km), the Happy City of Sejong Special Self-Governing City(about 33km), and the FMTC(Future Mobility Technical Center) PG(Proving Ground) of Seoul National University Siheung Campus using the MMS(Mobile Mapping System) surveying results given by the National Geographic Information Institute. In future research, the built-in precise road map service will be installed in the autonomous vehicles and control systems to verify the real-time locations and its location correction algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1331-1340
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• 2020

Object detection in maritime means that the captain detects floating objects that has a risk of colliding with the ship using the computer automatically and as accurately as human eyes. In conventional ships, the presence and distance of objects are determined through radar waves. However, it cannot identify the shape and type. In contrast, with the development of AI, cameras help accurately identify obstacles on the sea route with excellent performance in detecting or recognizing objects. The computer must calculate high-volume pixels to analyze digital images. However, the CPU is specialized for sequential processing; the processing speed is very slow, and smooth service support or security is not guaranteed. Accordingly, this study developed maritime object detection software and implemented it with FPGA to accelerate the processing of large-scale computations. Additionally, the system implementation was improved through embedded boards and FPGA interface, achieving 30 times faster performance than the existing algorithm and a three-times faster entire system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.354-360
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• 2021

People hope to live a healthy and happy life achieving satisfaction by striking a good work-life balance. Therefore, there is a growing interest in well-aging which means living happily to a healthy old age without worry. This study identified important factors related to well-aging by analyzing news articles published in Korea. Using Python-based web crawling, 1,199 articles were collected on the news service of portal site Daum till November 2020, and 374 articles were selected which matched the subject of the study. The frequency analysis results of text mining showed keywords such as 'elderly', 'health', 'skin', 'well-aging', 'product', 'person', 'aging', 'female', 'domestic' and 'retirement' as important keywords. Besides, a social network analysis with 45 important keywords revealed strong connections in the order of 'skin-wrinkle', 'skin-aging' and 'old-health'. The result of the CONCOR analysis showed that 45 main keywords were composed of eight clusters of 'life and happiness', 'disease and death', 'nutrition and exercise', 'healing', 'health', and 'elderly services'.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.23-36
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• 2022

Objectives : This study aimed to provide basic data on intervention strategies that occupational therapists can access by systematically analyzing the intervention and effectiveness for youth with disabilities. Methods : The RISS, PubMed, and Web of Science databases were used to search for papers published between 2006 and 2021. The keywords were "Disability AND Adolescents OR Young adult AND Transition education OR Transition program". Seven papers were selected for analysis, and the full text was reviewed. The keywords and national relations were analyzed and visualized using the WoS (Web of Science) and VOSviewer programs. Results : The participants were classified into five types (ASD or ADHD, ID, DD, and physical disability). The areas used for the intervention were mixed into three categories: occupation (academic), self-management (time), and interaction (personal relations and communication). Sociality and adaptation, quality of life, and at least one of the three categories of daily life activities showed significant improvement. Conclusions : This study can be used as basic data to expand the area where only OTs can contribute while grasping the research trend of the conversion program and presenting the direction of exchange with various experts by organizing the application and its effects.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.189-196
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• 2022

Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.259-266
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• 2023

It is very difficult to measure the performance of the machine learning model in the business service stage. Therefore, managing the performance of the model through the operational department is not done effectively. Academically, various studies have been conducted on the concept drift detection method to determine whether the model status is appropriate. The operational department wants to know quantitatively the performance of the operating model, but concept drift can only detect the state of the model in relation to the data, it cannot estimate the quantitative performance of the model. In this study, we propose a performance prediction model (PPM) that quantitatively estimates precision through the statistics of concept drift. The proposed model induces artificial drift in the sampling data extracted from the training data, measures the precision of the sampling data, creates a dataset of drift and precision, and learns it. Then, the difference between the actual precision and the predicted precision is compared through the test data to correct the error of the performance prediction model. The proposed PPM was applied to two models, a loan underwriting model and a credit card fraud detection model that can be used in real business. It was confirmed that the precision was effectively predicted.

• Therapeutic Science for Rehabilitation
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• v.12 no.1
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• pp.65-78
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• 2023

Objective : The typical decline in function due to aging includes limitations in vision, hearing, cognitive function, and activities of daily living. Therefore, this study evaluated the mediating effect of cognitive function on the relationship between vision and hearing and activities of daily living. Methods : The participants in this study were 36,767 persons from the long-term care database on older adults provided by the National Health Insurance Sharing Service. The extracted variables were: (i) independent variables: visual and hearing; (ii) dependent variables: basic and instrumental daily living activities; and (iii) mediator variables: cognitive function. Regression analysis was performed evaluate the mediating effects of the extracted variables. Results : Cognitive function showed a mediating effect of 30% on the relationship between vision and basic daily life activities and 42% in the relationship with instrumental daily life activities. The mediating effect was 50% in the relationship between hearing and basic activities of daily living, and 53% in the relationship with instrumental activities of daily living. Conclusion : Prevention programs for functional decline due to aging are in progress in Korea. Based on the results of this study, establishing a prevention program would help promote successful aging.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

• Knowledge Management Research
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• v.24 no.1
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• pp.31-49
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• 2023

TikTok, as a leading short video platform, has attracted many users, and the resulting attention generates immense business value as a platform to diffuse knowledge. As a qualitative and explorative approach, this study reviews the knowledge payment industry and discusses the influential factors of users' payment decisions regarding knowledge products on TikTok. By conducting in-depth interviews with ten participants and observing 95 knowledge providers' videos, we find that TikTok has significant business potential in the knowledge payment industry. By using the ATLAS. ti software to code the data collected from these interviews, this study finds that demander characteristics (personal needs), product characteristics (product quality), provider characteristics (the key opinion leader effect), and platform characteristics (platform management) are the four core categories that influence users' payment decisions regarding knowledge products on TikTok. A theoretical model consisting of the ten variables of emotional needs, professional needs, quality, price, helpfulness, value, charisma, user trust, service guarantee, and scarcity is proposed based on the grounded theory. The theoretical and practical implications of the study findings are also discussed.