• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.681-688
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• 2022

According to a recent study, most construction companies in Korea do not manage risk effectively, and it is judged that the risk management system needs to be improved. In addition, most risk-related studies deal with risks from a macroscopic perspective, and there are few studies dealing with process risks at the project construction stage. Therefore, this study tried to suggest a risk response plan through analysis and classification of risk factors that may occur in retaining work among process risks. To this end, a workshop was held for risk experts to identify and analyze risks that may occur during the construction of retaining work for apartments. As a result of the study, it was expected that savings of KRW 4.97 billion would be possible in the 95 % confidence interval, and the maximum possible cost was reduced from KRW 15 billion to about KRW 10 billion. Based on the risk reduction ratio, it was found that risks that can be reduced without any special input cost, risks with large effects in response to risks, and risks with insignificant effects were found. Therefore, using the types and risk factors presented in this study as guides, it is expected that it will be helpful in successfully operating the project if an appropriate response strategy is prepared and systematically responded to the site conditions.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• Journal of Marine Life Science
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• v.4 no.2
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• pp.96-105
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• 2019

The mugilidae fishes are common euryhaline species that live in coastal marine waters to freshwater areas. The taxonomy and nomenclature of the mugilidae fishes still remain unresolved because of their morphological similarities. Among the mugilidae fishes, most commonly consumed in Korea, are grey mullet (Mugil cephalus) and red lip mullet (Chelon haematocheilus). It is generally called 'mullet' without distinguishing between two mullets. Therefore, the aim of this study is to examine the scientific names and common names of mullet species used in Korea from the domestic journals and Korean old documents. The scientific name of grey mullet is M. cephalus, but that of redlip mullet is C. haematocheilus. But the genus of redlip mullet is still mixed with Chelon, Mugil, and Liza. The standard name of two mullet is not distinguished in the Korean dictionary, but they were clearly distinguished in the Japanese, English, and Chinese dictionaries. In the ancient Korean references, the mullet was called 'Chieo' or 'Sueo'. In most of the old literature, the distinction between grey mullet and redlip mullet is not clear. However, in Jasaneobo, it was written separately from grey mullet and redlip mullet, and attaching "ga" was different from now. The Korean standard name of redlip mullet is 'gasungeo', however, the fishermen in Jeollado and Gyoungsangdo call it 'chamsungeo'. Considering the negative perception of 'ga' character, it is proposed to change 'cham(眞)' instead of 'ga(假)' to improve economic value of red lip mullet.

• Korean small business review
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• v.42 no.3
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• pp.27-42
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• 2020

The purposes of this study are to summarize the past studies on human resource management (HRM) published in Asia Pacific Journal of Small Business and to propose the future research directions. This study selected 33 HRM papers (3.1 % of all published papers) and classified them depending three yardsticks. First, this study investigated the frequency and the trend of each year and, as a result, it demonstrated the variations in published papers depending on the publication year. Next, on the basis of the research theme, this study divided 33 papers into two parts; a general HRM vs. a specific HRM practice. The result showed that most studies focused on the specific HRM practice. Lastly, with regard to methodology, this study classified them into a conceptual paper, a case-study, and empirical research, and the result showed that most studies are empirical-based papers. Based on the trends, this study proposed three issues in terms of the number of research, research theme, and methodology, and suggested future research directions for HRM in small-medium enterprises.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.203-232
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• 2022

Drug addiction or substance use disorder is continuously observed worldwide for its risks and prevalence. In this context, numerous studies have been conducted regarding this issue. However, bibliometric analysis related to drug addiction is insufficient. In particular, it is difficult to find research that utilizes a macro-level bibliographic approach that comprehensively reflects various characteristics related to drug addiction. In this study, to reflect the multidimensional features of drug addiction, research trends in drug addiction in social science, natural science, and multidisciplinary studies were compared and analyzed. This study collected drug addiction research articles from 2002 to 2021 by searching from the Web of Science, and classified academic disciplines based on SCI(E) and SSCI information. Author keyword co-occurrence analysis was also conducted, which provided confirmation that natural science mainly studied psychoactive substances and the reward system in the brain, while drug addiction studies reflecting demographic characteristics were conducted in the domain of social science. In the multidisciplinary field, all of the above topics were covered. Author co-citation analysis was also employed, which showed that there are superstars (i.e., authors who receive a rigorous amount of citation) in the field of natural science, while in the social science domain, authors were highly cited not only at the individual level but also at the institutional level.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.1013-1022
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• 2022

Recently, with the worldwide development of the fourth industry, the development of technologies for smart and eco-friendly ships is accelerating. With the emergence of autonomous vessels with complete unmanned or minimum personnel on board and eco-friendly fuel (methane, ammonia, electricity, etc.), the role of existing seafarers on board is expected to change significantly. To improve the competitiveness of seafarers in the future, predicting future seafarer occupation groups, improving the educational curriculum, and creating an educational system are necessary. In this study, eight occupational groups that seafarers may have in the future were derived through a review of earlier studies and brainstorming of maritime university students, incumbent seafarers and expert groups. A survey was conducted on the eight occupational groups using the Likert scale, and based on the results, a leading occupational group related to future seafarer was derived. The most likely occupational groups with high scores were remote control centre operators and cargo remote manager. In addition, essential educational elements to be educated first for these occupational groups were derived and presented.

• 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 Intelligence and Information Systems
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• v.28 no.3
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• pp.81-103
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• 2022

It recognizes the importance of mental health and well-being worldwide and consistently records public happiness figures through the World Happiness Report. COVID-19, which occurred in China in 2019, has changed people's daily lives a lot. The accumulation of stress caused by the prolonged epidemic is affecting people's happiness. The present research has revealed negative mental health effects such as "depression" and "anxiety" after the pandemic. In this regard, it was revealed that the happiness index was also lowered numerically. It is insufficient to analyze specific issues about changes in the issue of happiness felt by the public in Korean society after the epidemic. Therefore, this study aims to identify changes in the happiness issue of Koreans after COVID-19 and find ways to improve happiness. Data were collected from various aspects by searching 32 sub keywords based on ERG theory by dividing the period before and after COVID-19. The results of topic modeling before and after COVID-19 were classified into seven areas of happiness index 2.0 published by the National Assembly Future Research Institute and compared and analyzed. Based on the results of comparing the results of the before and after topic from the perspective of each area, a plan to improve happiness was presented. The academic implications of this paper are that the research on psychological changes caused by COVID-19 was expanded by mining the opinions of the actual public on 'happiness'. In addition, it has practical implications in that it specifically presented measures to promote happiness by utilizing the area of objective happiness indicators based on the existing research on ways to reduce happiness promotion unhappiness.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.365-385
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• 2022

The easy payment service is a payment and remittance service that uses a simple authentication method. As online transactions have increased due to COVID-19, the use of an easy payment service is increasing. At the same time, electronic financial industries such as Naver Pay, Kakao Pay, and Toss are diversifying the competition structure of the easy payment market; meanwhile overseas fintech companies PayPal and Alibaba have a unique market share in their own countries, while competition is intensifying in the domestic easy payment market, as there is no unique market share. In this study, the participants in the easy payment market were classified as electronic financial companies, mobile phone manufacturers, and financial companies, and a SWOT analysis was conducted on the representative services in each industry. The analysis examined the user reviews of Google Play Store via a topic modeling analysis, and it employed positive topics as strengths and negative topics as weaknesses. In addition, topic modeling was conducted by dividing news articles into political, economic, social, and technology (PEST) articles to derive the opportunities and threats to easy payment services. Through this research, we intend to confirm the service capabilities of easy payment companies and propose a service activation strategy that allows gaining the upper hand in the market.