• Korean small business review
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• v.42 no.4
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• pp.251-283
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• 2020

The purpose of this study is to provide assistance to the establishment of related policies to improve the level of acceptance and use of smart factories for SMEs in Korea. To this end, the Unified Technology Acceptance Model (UTAUT) was extended to select additional factors that could affect the intention to accept technology, and to demonstrate this. To achieve the research objective, a questionnaire composed of 7-point Likert scales was prepared, and a survey was conducted for manufacturing-related companies. A total of 136 questionnaires were used for statistical processing. As a result of the hypothesis test, performance expectation and social influence had a positive (+) positive effect on voluntary use, but effort expectation and promotion conditions did not have a significant effect. As an extension factor, the network effect and organizational characteristics had a positive (+) effect, and the innovation resistance had a negative effect (-), but the perceived risk had no significant effect. When the size of the company is large, the perceived risk and innovation resistance are low, and the level of influencing factors for veterinary intentions, veterinary intentions, and veterinary behaviors are excluded. Through this study, factors that could have a positive and negative effect on the adoption (reduction) of smart factory-related technologies were identified and factors to be improved and factors to be reduced were suggested. As a result, this study suggests that smart factory-related technologies should be accepted.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.83-106
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• 2021

Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.79-86
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• 2022

This study aims to analyze the research trends on the civic participation in a smart city and to present implications to policy makers, industry professionals and researchers. As rapid urbanization is defining development trend of modern city, urban problems such as transportation, environment, and energy are spreading and intensifying around the city. Countries around the world are introducing smart cities to solve these urban problems and to achieve sustainable development. Recently, many countries are modifying urban planning from top-down to down-up by actively engaging citizens to participate in the urban construction process directly and indirectly. Although the construction of smart cities is being promoted in Korea to solve urban problems, awareness of smart cities and civic participation are low. In order to overcome this situation, discussions on ideas and methods that can increase civic participation in smart cities are continuously being conducted. Therefore, in this study, by collecting publication containing both 'Smart Cities' and 'Participation (Engagement)' in Scopus DB, the topics of related studies were categorized and research trends were analyzed using topic modeling. Through this study, it is expected that it can be used as evidence to understand the direction of civic participation research in smart cities and to present the direction of related research in the future.

• Journal of the Korean Society of Food Culture
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• v.25 no.1
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• pp.100-107
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• 2010

This study was performed to compare the dietary intake and food sources of zinc (Zn), using a database of Zn composition developed in this study, between elementary schoolchildren in a remote rural area (RA, n=58, $9.9{\pm}1.7\;yrs$) and those in an urban area (UA, n=60, $9.4{\pm}1.8\;yrs$) in Chungnam province in Korea. A dietary survey for three days by food record method was performed. All kinds of foods (n=273) consumed by subjects were collected by aliquot sampling method, and the Zn content of these foods were analyzed by wet technique. The results showed that the daily mean intakes of energy, calcium, iron, and vitamin C from diet in the RA were in the range of 49-88% of the Korean DRI (KDRI), while those in the UA were similar to or greater than the KDRI, except for calcium and iron. The daily mean intake of Zn from the RA diet was $7.0{\pm}0.5\;mg/d$ ($114.1{\pm}8.4%$ of the KDRI), and $16.0{\pm}1.0\;mg/d$ ($258.3{\pm}16.3%$ of the KDRI) in that of the UA (p<0.001). The percentage of dietary intake of Zn less than 2/3 of the KDRI was 19.0% in the RA, in comparison to 1.7% in the UA. Those in the RA consumed Zn from plant foods more often than did those in the UA (p<0.001). Beef rib stew was the food source with highest Zn amount for the total subjects, followed by beef rib meat, roasted; and beef soup w/seasoned red pepper sauce. These results showed that some children in the RA had poor Zn nutrition based upon low intakes and poor food sources of Zn, while overall, children in the UA had good Zn nutrition. Therefore, those in RAs should have their Zn nutrition improved through government policy and nutrition education.

• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1075-1084
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• 2023

Satellite-derived data is collected by observing the Earth and is used in various fields such as national defense, natural disasters, location-based services, infrastructure, environment, energy, marine, and insurance. This study aims to present the virtuous cycle structure of the satellite information data industry and the business ecosystem model of the industry. As a research method, cases were collected and categorized from the following areas: literature, online, application, and content. The results show that the ecosystem model of the satellite information data industry provides an approach to content services in public and commercial areas, and develops various algorithmic technologies to facilitate content production and services at the level of complex general-purpose technologies. Second, in terms of content typology, satellite information data can be subdivided into monitoring content, urban space monitoring content, and satellite information content. Third, the consumption value of satellite content could be subdivided into informational value, environmental, social and governance (ESG) value, educational value, and content value. In order to expand the global content market, Korea will need to focus on creating an ecosystem for the satellite information industry and discovering differentiated content. It will also need to increase the popularization and accessibility of data to the general public and promote the Korean K-Satellite Information Data Industry ecosystem through government support, policy efforts, and policies such as establishing legal systems, increasing investment, and training human resources.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.159-164
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• 2024

The domestic petroleum market is highly sensitive to changes in international oil prices. So, it is important to identify and respond to those changes. In particular, it is necessary to clearly understand the factors causing the price fluctuations of gasoline, which exhibits high consumption. International gasoline prices are influenced by global factors such as gasoline supplies, geopolitical events, and fluctuations in the U.S. dollar. However, previous studies have only focused on gasoline supplies. In this study, we explore the causal relationship between economic indicators and international gasoline prices using various machine learning-based regression models. First, we collect data on various global economic indicators. Second, we perform data preprocessing. Third, we model using Multiple linear regression, Ridge regression, and Lasso(Least Absolute Shrinkage and Selection Operator) regression. The multiple linear regression model showed the highest accuracy at 96.73% in test sets. As a result, Our Multiple linear regression model showed the highest accuracy at 96.73% in test sets. We will expect that our proposed model will be helpful for domestic economic stability and energy policy decisions.

• Information Systems Review
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• v.26 no.1
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• pp.93-117
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• 2024

In February 2022, the EU announced a draft of the EU Corporate Sustainability Due Diligence Directive requiring due diligence and disclosure of information on environmental and human rights risks in corporate supply chains. This study evaluated the ability of 13 Korean pharmaceutical/bio companies to respond to the EU's demand for due diligence in the supply chain and compared it to 13 globally leading pharmaceutical/bio companies which are considered good in environmental and human rights risk management. For comparative analysis, text mining analysis was performed using R. Basic word frequency and concurrent words were analyzed and topic modeling was performed by applying Latent Dirichlet Allocation. As a result of the analysis, it was found that compared to advanced companies, domestic pharmaceutical and bio companies lack negative issue reporting and identification systems and supply chain due diligence implementation processes, and require advancement of data management for environmental and human rights information disclosure. Accordingly, domestic pharmaceutical and bio companies need to prepare differentiated support measures to systematically identify and reduce risks in the supply chain of small and medium-sized businesses beyond simply providing financial support. It is also desirable for the government to provide policy support by mandating Korea's own supply chain environment and human rights due diligence system, along with support for strengthening the ability to respond to due diligence of domestic pharmaceutical and bio companies, such as expert consulting and financial support.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.8
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• pp.367-376
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• 2007

In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.

• Journal of the Korean Society for Marine Environment & Energy
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• v.14 no.4
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• pp.213-223
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• 2011

The status and changes of water quality of national fishing harbors and designated ports in East Coast of Korea were analyzed to support establishment effective water environmental management. COD (Chemical Oxygen Demand) concentration was satisfied to designated water quality criteria in most areas, but TN (Total Nitrogen) and TP (Total Phosphorus) exceeded the criteria frequently. Also, peak concentration was summer in COD and SS (Suspended Solid), but winter in TP. Eutrophication index of Ganggu and Pohang (old) area were the highest. Pollution index by function of COD, TN, and TP of Ganggu, Pohang, Jumunjin, and Guryongpo was high with gradual increasing recently, on the contrary, that of Samcheok, Imwon, and Chuksan was decreased. Pollution index involving multi-indictors relation to organics and inorganics was necessary for water quality assessment. Designated water quality criteria needed to be improved because the criteria of Jukbyun and Chuksan was applied more strictly compared to the other regions although without difference of environmental characteristics. Furthermore, the criteria notified lately needed to be related to management pollutants from land-based sources. The continuous diagnosis and monitoring on sediment quality within the study area were necessary for prevention of water pollution and eco-friendly disposal of dredged sediment. Especially, monitoring of Designated Ports was implemented partially, however monitoring ratio of National Fishing Har-bors was 7% to whole part. Therefore, systematic and integrated environmental monitoring for ports and harbors with charge of national management was reestablished by strengthening and securing a legal basis.