• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.65-76
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• 2023

This paper identifies the aspects of living environment elements (PM^2.5, PM¹⁰, Noise) throughout Seoul and the urban characteristics that affect them by utilizing the big data of the S-Dot sensors in Seoul, which has recently become a hot topic. In other words, it proposes a big data based urban computing research methodology and research direction to confirm the relationship between urban characteristics and living environments that directly affect citizens. The temporal range is from 2020 to 2021, which is the available range of time series data for S-Dot sensors, and the spatial range is throughout Seoul by 500mX500m GRID. First of all, as part of analyzing specific living environment patterns, simple trends through EDA are identified, and cluster analysis is conducted based on the trends. After that, in order to derive specific urban planning factors of each cluster, basic statistical analysis such as ANOVA, OLS and MNL analysis were conducted to confirm more specific characteristics. As a result of this study, cluster patterns of environment elements(PM^2.5, PM¹⁰, Noise) and urban factors that affect them are identified, and there are areas with relatively high or low long-term living environment values compared to other regions. The results of this study are believed to be a reference for urban planning management measures for vulnerable areas of living environment, and it is expected to be an exploratory study that can provide directions to urban computing field, especially related to environmental data in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.71-92
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• 2023

Globally, under the leadership of advanced ICT countries, the private sector is promoting various policies to promote the digital transformation of public services. Looking at the research trend, design of public service indicators, development of evaluation system, and empirical research are being carried out steadily, but there are insufficient research cases on models in which the private sector participates in the planning, development, and operation of public services. In this study, Private-centric digital public service suitability evaluation indicators were discovered through interviews with experts in various fields, and weights for each indicator were analyzed through AHP evaluation. In addition, by applying the analysis results to 18 digital public services on a trial basis, the importance and priority of evaluation indicators for each service were derived, and at the same time, the evaluation framework was designed and applied to diagnose implications. As a result of the study, 'social utility', 'corporate acceptability', and 'public acceptability' were selected as the top three indicators of suitability evaluation. At this time, it was analyzed that the weight of the 'company acceptability' index, which includes sub-indices such as 'service profitability', 'service scalability', and 'private initiative possibility', was the highest among the three top indicators. As a result of the demonstration for public services, "IoT facility unmanned remote monitoring service", "blockchain real estate transaction service", and "digital twin disaster prediction service" were evaluated as the most suitable public services for the transition to the private sector.

• Journal of Korean Public Health Nursing
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• v.37 no.1
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• pp.5-24
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• 2023

Purpose: The objective of this review was to identify the research trends in Information and Communication Technology (ICT)-based health-related intervention studies for children and adolescents published in South Korea over the past 10 years. Methods: A scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) and the system classification framework for digital health intervention 1.0 of the World Health Organization (WHO) was applied to analyze how technology was being used to support the needs of the health system. Results: A total of 18 studies were included in the final analysis. The participants were mainly children with a variety of diseases. No studies had used innovative technology platforms such as artificial intelligence (AI), the Internet of Things (IoT), and robotics. In addition, the scope of application of the WHO classification criteria was quite limited. Finally, no intervention study considered technical operational indicators, such as the number of website visits and streaming as outcome measurements. Conclusions: Researchers should introduce advanced technology-based strategies to provide customized and professional healthcare services to children and adolescents in South Korea and continue efforts to integrate innovative ICT for various research purposes, subjects, and environments.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.827-837
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• 2017

Since the area of smart home has been attracting attention, researches have been conducted to control syntagmatically various electronic products with a single remote controller. Previous researches have developed a dedicated controller or an application that acts as a remote controller and controls electronic products by configuring control screen for each product. However, these approaches are not suitable for controlling various electronic products that should be controlled by configuring separate control screens for each product. In this paper, we propose a web-based remote control platform. We define universal user interfaces applicable to various devices by categorizing user interactions of electronic goods and implement them as APIs. By applying the APIs to IPTV and car navigation devices we show that it is possible to control them through only a web browser. We also propose a method to group multiple control requests in order to efficiently handle consecutive control requests and show the improved response time and data usage.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.9
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• pp.27-35
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• 2016

Today, with the advance of Information and communication technology, 'Smart, connected' toys, which apply technologies related to IoT (Internet of Things) to traditional toys, are emerging and rapidly growing. This research aims to analyze the tendencies and limitations of smart, connected toys through exploring the representative cases of smart, connected toys based on characteristics of ICBM (Internet of Things, Cloud, Big-data, and Mobile) technology. For this study, we begin by understanding literature research about smart, connected toys and ICBM technology. Then, we extracted the characteristics of ICBM technology for connecting physical and digital environments through investigating cases to which ICBM technologies are applied. Based on the extracted characteristics, the case studies of smart, connected toys were conducted. In this research, we explore the level of ICBM technology application and limitation to smart, connected toys. We expect this research will contribute to providing guidelines for developing smart, connected toys based on the characteristics of the latest technology.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.51-51
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• 2020

본 연구에서는 기수역에서의 GPS 전자부자를 활용한 계측 데이터와 염분측정 데이터를 비교분석하여 GPS 전자부자의 거동 특성이 담수의 실제 거동특성과 같이 일치하게 나타나는지 확인하고, GPS 전자부자에 대한 활용성을 증명하고자 하였다. 기수역에서의 담수와 해수의 분포를 확인하기 위해서는 많은 인력과 장비를 소모하며 수리량과 염분도에 대한 측정을 통해 분석을 할 수 있는데, 대표적인 수리량 측정장비인 ADCP 또는 ADV는 각종 측정 한계들이 존재한다. 따라서 이러한 기수역에서의 수체 구간별 흐름 특성이 어떻게 나타나는지 확인하기 위해서 GPS 전자부자를 활용하고자 하였으며. GPS 전자부자의 데이터와 수직방향으로 측정한 염분도 데이터와 비교하고자 하였다. 수영강 좌수영교 상류 1km지점에서 주입하였으며 간조 시와 만조 시에 유하시켜 수영강에 위치한 좌수영교와 수영교에서 각각 좌측, 중간, 우측에서 수심방향으로 측정한 염분도를 상층 중층 하층으로 평균하여 비교하였다. 본 연구에서 사용한 GPS 전자부자는 표면부자이기 때문에 만조 시 하류방향으로 더 뻗어 나가는것으로 확인하였고, 간조 시에는 흐름이 더디거나 정체하는 것으로 나타났다. 이러한 계측 결과는 담수의 흐름 특성과 일치하게 나타나는 것을 확인하였고 이러한 GPS Floater를 활용한다면 굳이 각종 수질을 측정하지 않아도 흐름 상황으로 간조인지 만조인지에 대한 상황과 염분 분포를 대략적으로 알 수 있다. 이러한 GPS 전자부자의 위치데이터와 시간을 잘 이용한다면 ADCP의 유속 측정에 대한 단점을 보완할 수 있는 Lagrangian 타입의 유속을 측정 할 수 있다. 이러한 GPS 전자부자를 하천에서 선주입으로 활용한다면 각 구간별로 수체에 대한 흐름과 유속들을 분석할 수 있을 것으로 사료된다. 또한 GPS 전자부자를 좀더 활용하여 IoT 기반 수질센서 등과 같은 각종 센서가 GPS Floater에 결합이 된다면, 흘러가면서 각종 데이터 정보취득을 통해 수체내 흐름을 분석하는 것뿐만 아니라 수환경 유출오염사고들에 대한 초기대응에 많은 도움이 될 것으로 사료 된다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.699-706
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• 2023

Recently, the 4 generation industry revolution is developed with advanced and combined with a variety of new technologies. Conventional healthcare system is applied with IoT application. It provides many advantages with mobility and swift data transfers to patient and doctor. In despite of these kinds of advantages, it occurred security issues between basic devices and protocols in their applications. Especially, internet of things have restricted and limited resources such as small memory capacity, low capability of computing power, etc. Therefore, we can not utilize conventional mechanism. In this paper, we analyzed attacks and vulnerability in terms of security issues. To analyze security structure, features, demands and requirements, we solve the methods to be reduced security issues.

• Smart Structures and Systems
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• v.31 no.1
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• pp.1-11
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• 2023

Assessment of the compressive strength of concrete plays a major role during formwork removal and in the prestressing process. In concrete, temperature changes occur due to hydration which is an influencing factor that decides the compressive strength of concrete. Many methods are available to find the compressive strength of concrete, but the maturity method has the advantage of prognosticating strength without destruction. The temperature-time factor is found using a LM35 temperature sensor through the IoT technique. An experimental investigation was carried out with 56 concrete cubes, where 35 cubes were for obtaining the compressive strength of concrete using a universal testing machine while 21 concrete cubes monitored concrete's temperature by embedding a temperature sensor in each grade of M25, M30, M35, and M40 concrete. The mathematical prediction model equation was developed based on the temperature-time factor during the early age compressive strength on the 1^st, 2^nd, 3^rd and 7^th days in the M25, M30, M35, and M40 grades of concrete with their temperature. The 14^th, 21^st and 28^th day's compressive strength was predicted with the mathematical predicted equation and compared with conventional results which fall within a 2% difference. The compressive strength of concrete at any desired age (day) before reaching 28 days results in the discovery of the prediction coefficient. Comparative analysis of the results found by the predicted mathematical model show that, it was very close to the results of the conventional method.

• Journal of Environmental Health Sciences
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• v.49 no.6
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• pp.295-304
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• 2023

Background: Adolescents are relatively more sensitive than adults to exposure to indoor pollutants. The indoor air quality in classrooms where students spend time together must therefore be managed at a safe level because it can affect the health of students. Objectives: In this study, three types of green-wall models were applied to classrooms where students spend a long time in a limited space, and the resulting effects on reducing PM were evaluated. Methods: In the middle school classrooms which were selected as the experimental subjects, IoT-based indoor air quality monitoring equipment was installed for real-time monitoring. Three types of plant models (passive, active, and active+light) were installed in each classroom to evaluate the effects on improving indoor air quality. Results: The concentration of PM in the classroom is influenced by outdoor air quality, but repeated increases and decreases in concentration were observed due to the influence of students' activities. There was a PM reduction effect by applying the green-wall model. There was a difference in PM reduction efficiency depending on the type of green-wall model, and the reduction efficiency of the active model was higher than the passive model. Conclusions: The active green-wall model can be used as an efficient method of improving indoor air quality. Additionally, more research is needed to increase the efficiency of improving indoor air quality by setting conditions that can stimulate the growth of each type of plant.