• Journal of Climate Change Research
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• v.4 no.4
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• pp.409-416
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• 2013

Recently, the property damage has been increasing due to climate change in South Korea. While the general public has become more aware of the environmental issues, but the environmental education system has not been able to meet up with the demands of the public. The purpose of this study is to suggest preliminary data which is needed for developing a environmental textbook. A survey was conducted to meet the following requirements. Respondent's level of interest in problems or situations concerning the following eight themes: fundamental science, health and medicine, aerospace engineering, life science, electrical electronics, telecommunication, mineral and energy resources, environment. The data was collected from 139 students in Seoul and Gyeonggi province. The results showed that health and medicine issues interest students the most (49.6%), followed by environment (46.8%). We asked the respondents who were very interested in each question for their reasons, and they answered that environmental issue is related to the improvement of their life quality (53.8%) than their curiosity (38.5%). Students were very interested in the other issues because of just curiosity. Most students (90.6%) said seasonal change was not same each year. 18.0% of respondents replied that they and their friends had experienced climate change. The majority of students (94.2%) thought that they will experience natural disaster blamed on climate change during their life. In other words, climate change is already the day-to-day events of their lives. The majority of their opinions, more then three than ten students(30.9%) said the South Korean government should conduct an energy saving campaign to climate change problems followed by expanding new renewable energy (24.5%), conducting adaptation policies of climate change(22.3 %), introducing of a system as like $CO_2$ emissions trading(20.9%) and so on. There are more Stu- dents (69.1%) who know of new renewable energy than students who don't know it; however, respondents who know the meaning very well were just 18.7% showing that most students dimly know the meaning of new renewable energy.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.5
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• pp.41-48
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• 2019

Our daily lives are changing at a rapid pace and the concept of smart city is spreading, as the information communication technologies apply to various fields. However, efforts to prepare for changes in society due to technological evolution are insufficient in the field of landscape architecture. The purposes of this study are to explore the concept of smart parks, to investigate how smart technology has been applied to parks, and to identify the users' perception and satisfaction on smart park services. To this end, we conducted literature review, focus group interviews with experts, and a questionnaire survey with 180 users of the IoT See pilot smart park in Daegu. Smart parks can, as a result, be defined as sustainable parks that improve users' experience in parks and solve social and environmental problems faced by utilizing various high technology. Smart technologies introduced at the park so far have been mostly focused on safety and environmental areas, including AI CCTV, smart street lamp, and fine dust warning devices. The results of survey showed that not many users were aware of the smart services the park provided due to the lack of public communication as well as the nature of maintenance-oriented smart services. The survey also found that AR services for the education of historic parks were the least utilized, while solar power benches and WiFi service were most preferred by the park users. In conclusion, smart technologies need to be integrated with diverse park contents more centered user needs, providing services to enhance safety and environmental management in order to develop user-oriented smart parks.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.261-268
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• 2021

Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.

• Applied Chemistry for Engineering
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• v.32 no.3
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• pp.268-276
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• 2021

As wireless communication devices become more common, interests in how to control the electromagnetic waves generated from the devices are increasing. One of the most commonly used electromagnetic wave control materials is magnetic one, but due to the features that make the product heavy and thick when applied to the product, it is difficult to use them in curved electronic devices. Therefore, a polymer flexible meta electronic device has been presented to sort out the problem, which is thin and can have various curvatures. However, it requires an additional evaluation of curvature reliability. In this study, we developed a method to predict electromagnetic wave control characteristics through the resistance/length of the conductive ink line patterns of polymer flexible meta electronic devices, which is inversely proportional to the electromagnetic wave control characteristics. As the radius of curvature decreased, the resistance/length increased, and there was little variations with the duration times of curvature. We also found that both permanent and recoverable changes along with the removal of curvature were occurred when the curvature was applied, and that the cause of these changes was newly created vertical cracks in the conductive ink line pattern due to the tensile stress applied by applying curvature.

• Informatization Policy
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• v.29 no.1
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• pp.24-37
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• 2022

Amid rapid changes in the ICT environment attributed to the 4th Industrial Revolution, the development of information & communication technology, and COVID-19, the existing internet developed without considering security, mobility, manageability, QoS, etc. As a result, the structure of the internet has become complicated, and problems such as security, stability, and reliability vulnerabilities continue to occur. In addition, there is a demand for a new concept of the internet that can provide stability and reliability resulting from digital transformation-geared advanced technologies such as artificial intelligence and IoT. Therefore, in order to suggest a way of implementing the Korean future internet that can strengthen cybersecurity, this study suggests the direction and strategy for promoting the future internet that is suitable for the Korean cyber environment through analyzing important key factors in the implementation of the future internet and evaluating the trend and suitability of domestic & foreign research related to future internet. The importance of key factors in the implementation of the future internet proceeds in the order of security, integrity, availability, stability, and confidentiality. Currently, future internet projects are being studied in various ways around the world. Among numerous projects, Bright Internet most adequately satisfies the key elements of future internet implementation and was evaluated as the most suitable technology for Korea's cyber environment. Technical issues as well as strategic and legal issues must be considered in order to promote the Bright Internet as the frontrunner Korean future internet. As for technical issues, it is necessary to adopt SAVA IPv6-NID in selecting the Bright Internet as the standard of Korean future internet and integrated data management at the data center level, and then establish a cooperative system between different countries. As for strategic issues, a secure management system and establishment of institution are needed. Lastly, in the case of legal issues, the requirement of GDPR, which includes compliance with domestic laws such as Korea's revised Data 3 Act, must be fulfilled.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.246-262
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• 2023

This study analyzed policy implementation factors focusing on how Donuimun, a demolished cultural heritage, was digitally restored and the policy implementation process of Donuimun Gate restoration. Through this, the characteristics of the implementation process of the digital Donuimun Gate restoration policy promoted by public-private multilateral collaboration were examined and implications were sought for how institutions with different interests solved problems and collaborated in the implementation process. The research method was focused on policy implementation factors including policy executive factors, policy content factors, policy resource factors, and policy environment factors, and the process was analyzed for each detailed component. Along with literature analysis, in-depth interviews were conducted with participants in policy implementation. As a result of the study, first, it was found in the policy executive factor that the quick decision-making leadership of the policy manager and the flexible attitude of the person in charge of the government agency had a positive effect on preventing conflicts between different interest groups. Second, in terms of policy content, establishing a common goal that everyone can accept and moving forward consistently gave trust and created synergy. Third, in the policy implementation resource factor, the importance of the budget was emphasized. Finally, as an environmental factor for policy implementation, the opening of 5G mobile communication for the first time along with the emergence of the Fourth Industrial Revolution at the time of policy implementation acted as a timely factor. The digital Donuimun Gate was the first case of restoring a lost cultural heritage with AR and VR, and received attention and support from the mass media and the public. This also shows that digital restoration can be a model case that can be a solution without conflicts with local residents where cultural heritages are located or conflicts between stakeholders in the preservation and restoration of real objects.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.171-180
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• 2023

The three major sleep disorders in Korea are snoring, sleep apnea, and insomnia. Lack of sleep is the root of all diseases. Some of the most serious potential problems associated with sleep deprivation are cardiovascular problems, cognitive impairment, obesity, diabetes, colitis, prostate cancer, etc. To solve these problems, the Korean government provided low-cost national health insurance benefits for polysomnography tests in July 2018. However, insomnia patients still have problems getting treated in terms of time, space, and economic perspectives. Therefore, it would be better for insomnia patients to be allowed to test at home. The measuring device can measure six biosignals (eye movement, tossing and turning, body temperature, oxygen saturation, heart rate, and audio). A gyroscope sensor (MPU9250, InvenSense, USA) was used for eye movement, tossing, and turning. The input range of the sensor was in 258°/sec to 460°/sec, and the data range was in the input range. Body temperature, oxygen saturation range, and heart rate were measured by a sensor (MAX30102, Analog Devices, USA). The body temperature was measured in 30 ℃ to 45 ℃, and the oxygen saturation range was 0% for the unused state and 20 % to 90 % for the used state. The heart rate measurement range was in 40 bpm to 180 bpm. The measurement of audio signal was performed by an audio sensor (AMM2742-T-R, PUIaudio, USA). The was -42 dB ±1 dB frequency range was 20 Hz to 20 kHz. The measured data was successfully received in wireless network conditions. The system configuration was consisted of a PC and a mobile app for bio-signal measurement and data collection. The measured data was collected by mobile phones and desktops. The data collected can be used as preliminary data to determine the stage of sleep and perform the screening function for sleep induction and sleep disturbances. In the future, this convenient sleep measurement device could be beneficial for treating insomnia.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.