• Title/Summary/Keyword: 데이터모델

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A Study of Information Communication Technology's impact on Culture and Management: Focusing on Hofstede's Cultural Dimension (정보통신기술이 문화와 경영에 미치는 영향에 관한 연구 : 홉스테드 모델을 중심으로)

  • Kim, Hak-Cho;Lee, Ji-Seok
    • Korea Trade Review
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    • v.41 no.1
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    • pp.91-116
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    • 2016
  • This study proposes a research model to investigate the effect of ICT on national culture and values. Why should we research the relationship between ICT and culture? We do this to shed light on the cultural framework and find areas for further research. This research has found that the development of Information Communication Technology(ICT) has proved to have a positive effect on the quality of individualism (B0.603), there is a decrease in power distance index(B-0.331)and a correlation between individualism and wealth. Also, the development of Information Communication Technology(ICT) has proved to have a positive effect on the quality of Long Term Orientation. As for adoption and use of ICT, the role of culture is important for many reasons. First of all, we can recognize the importance of national culture and organizational culture in establishing the ability of the overall culture to adapt, efficiently merging with different cultures and overcoming potential obstacles of these tasks. This is the evidence supporting the current theory. Our research shows that development of technology highly influences deep human values. Furthermore, the data points used in this research are from World Economic Forum, World Development Indicator and International Telecommunication Union. In order to understand and develop social evolution and progress, we tried to use data that is fair and verifiable.

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Factor Analysis Affecting on the Charterage of Capesize Bulk Carriers (케이프사이즈 용선료에 미치는 영향 요인분석)

  • Ahn, Young-Gyun;Lee, Min-Kyu
    • Korea Trade Review
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    • v.43 no.3
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    • pp.125-145
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    • 2018
  • The Baltic Shipping Exchange is reporting the Baltic Dry Index (BDI) which represents the average charter rate for bulk carriers transporting major cargoes such as iron ore, coal, grain, and so on. And the current BDI index is reflected in the proportion of capesize 40%, panamax 30% and spramax 30%. Like mentioned above, the capesize plays a major role among the various sizes of bulk carriers and this study is to analyze the influence of the factors influencing on charter rate of capesize carriers which transport iron ore and coal as the major cargoes. For this purpose, this study verified causality between variables using Vector Error Correction Model (VECM) and tried to derive a long-run equilibrium model between the dependent variable and independent variables. Regression analysis showed that every six independent variable has a significant effect on the capesize charter rate, even at the 1% level of significance. Charter rate decreases by 0.08% when capesize total fleet increases by 1%, charter rate increases by 0.04% when bunker oil price increases by 1%, and charter rate decreases by 0.01% when Yen/Dollar rate increases by 1%. And charter rate increases by 0.02% when global GDP increases by one unit (1%). In addition, the increase in cargo volume of iron ore and coal which are major transportation items of capesize carriers has also been shown to increase charter rates. Charter rate increases by 0.11% in case of 1% increase in iron ore cargo volume, and 0.09% in case of 1% increase in coal cargo volume. Although there have been some studies to analyze the influence of factors affecting the charterage of bulk carriers in the past, there have been few studies on the analysis of specific size vessels. At present moment when ship size is getting bigger, this study carried out research on capesize vessels, which are biggest among bulk carriers, and whose utilization is continuously increasing. This study is also expected to contribute to the establishment of trade policies for specific cargoes such as iron ore and coal.

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Contrast Media Side Effects Prediction Study using Artificial Intelligence Technique (인공지능 기법을 이용한 조영제 부작용 예측 연구)

  • Sang-Hyun Kim
    • Journal of the Korean Society of Radiology
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    • v.17 no.3
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    • pp.423-431
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    • 2023
  • The purpose of this study is to analyze the factors affecting the classification of the severity of contrast media side effects based on the patient's body information using artificial intelligence techniques to be used as basic data to reduce the degree of contrast medium side effects. The data used in this study were 606 examiners who had no contrast medium side effects in the past history survey among 1,235 cases of contrast medium side effects among 58,000 CT scans performed at a general hospital in Seoul. The total data is 606, of which 70% was used as a training set and the remaining 30% was used as a test set for validation. Age, BMI(Body Mass Index), GFR(Glomerular Filtration Rate), BUN(Blood Urea Nitrogen), GGT(Gamma Glutamyl Transgerase), AST(Aspartate Amino Transferase,), and ALT(Alanine Amiono Transferase) features were used as independent variables, and contrast media severity was used as a target variable. AUC(Area under curve), CA(Classification Accuracy), F1, Precision, and Recall were identified through AdaBoost, Tree, Neural network, SVM, and Random foest algorithm. AdaBoost and Random Forest show the highest evaluation index in the classification prediction algorithm. The largest factors in the predictions of all models were GFR, BMI, and GGT. It was found that the difference in the amount of contrast media injected according to renal filtration function and obesity, and the presence or absence of metabolic syndrome affected the severity of contrast medium side effects.

AI Security Plan for Public Safety Network App Store (재난안전통신망 앱스토어를 위한 AI 보안 방안 마련)

  • Jung, Jae-eun;Ahn, Jung-hyun;Baik, Nam-kyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.458-460
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    • 2021
  • The provision and application of public safety network in Korea is still insufficient for security response to the mobile app of public safety network in the stages of development, initial construction, demonstration, and initial service. The available terminals on the Disaster Safety Network (PS-LTE) are open, Android-based, dedicated terminals that potentially have vulnerabilities that can be used for a variety of mobile malware, requiring preemptive responses similar to FirstNet Certified in U.S and Google's Google Play Protect. In this paper, before listing the application service app on the public safety network mobile app store, we construct a data set for malicious and normal apps, extract features, select the most effective AI model, perform static and dynamic analysis, and analyze Based on the result, if it is not a malicious app, it is suggested to list it in the App Store. As it becomes essential to provide a service that blocks malicious behavior app listing in advance, it is essential to provide authorized authentication to minimize the security blind spot of the public safety network, and to provide certified apps for disaster safety and application service support. The safety of the public safety network can be secured.

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Optimal Capacity Determination of Hydrogen Fuel Cell Technology Based Trigeneration System And Prediction of Semi-closed Greenhouse Dynamic Energy Loads Using Building Energy Simulation (건물 에너지 시뮬레이션을 이용한 반밀폐형 온실의 동적 에너지 부하 예측 및 수소연료전지 3중 열병합 시스템 적정 용량 산정)

  • Seung-Hun Lee;Rack-Woo Kim;Chan-Min Kim;Hee-Woong Seok;Sungwook Yoon
    • Journal of Bio-Environment Control
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    • v.32 no.3
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    • pp.181-189
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    • 2023
  • Hydrogen has gained attention as an environmentally friendly energy source among various renewable options, however, its application in agriculture remains limited. This study aims to apply the hydrogen fuel cell triple heat-combining system, originally not designed for greenhouses, to greenhouses in order to save energy and reduce greenhouse gas emissions. This system can produce heating, cooling, and electricity from hydrogen while recovering waste heat. To implement a hydrogen fuel cell triple heat-combining system in a greenhouse, it is crucial to evaluate the greenhouse's heating and cooling load. Accurate analysis of these loads requires considering factors such as greenhouse configuration, existing heating and cooling systems, and specific crop types being cultivated. Consequently, this study aimed to estimate the cooling and heating load using building energy simulation (BES). This study collected and analyzed meteorological data from 2012 to 2021 for semi-enclosed greenhouses cultivating tomatoes in Jeonju City. The covering material and framework were modeled based on the greenhouse design, and crop energy and soil energy were taken into account. To verify the effectiveness of the building energy simulation, we conducted analyses with and without crops, as well as static and dynamic energy analyses. Furthermore, we calculated the average maximum heating capacity of 449,578 kJ·h-1 and the average cooling capacity of 431,187 kJ·h-1 from the monthly maximum cooling and heating load analyses.

Analyzing the Determinants and Estimate cost against Resettlement on New Town Project Using Ordinal Logit Model (순서형로짓모형을 이용한 재정비촉진지구의 재정착비용추정 및 결정요인 분석)

  • Choi, Yeol;Park, Sung Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2D
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    • pp.287-293
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    • 2009
  • The aim of this paper is to analyze resettlement cost and decision factors of resettlement since Redevelopment Promotion Projects. Range of resettlement cost was averagely increased 204% by using actual data. Consequently, the research is operated for aboriginal people in these areas by a questionnaire. The questionnaire ask a payment range of the resettlement cost with 4 stages; 150% and less, 180% and less, 200% and less, excess of 200%. Research scope is consist of Seo-kumsa, Civil Park, Chung-mu and Young-do. These areas are redevelopment of Busan metropolitan city. Resettlement is come under the influence of the resettlement cost and many factors by each specific character. In many alternatives for resettlement, understanding the reason why aboriginal peoples select a certain alternative and if we actualize the proper alternative, aboriginal peoples' resettlement ratio will be increased. Moreover it ask housing characteristic, housing life pattern for understanding aboriginal peoples' characteristic. Also data analysis model is ordinal logistic model'. In analysis result, resettlement cost is 150% of aboriginal assets. and significance parameter is sex, job, income, region, affection, attachment, housing possession type, size and others have influence on aboriginal peoples' resettlement.

Design of a designated lane enforcement system based on deep learning (딥러닝 기반 지정차로제 단속 시스템 설계)

  • Bae, Ga-hyeong;Jang, Jong-wook;Jang, Sung-jin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.236-238
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    • 2022
  • According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.

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The Roles of Learning Orientation and Market Orientation in Driving Marketing Capabilities and Firm Performance (학습지향성과 시장지향성이 마케팅역량과 기업성과에 미치는 영향)

  • Shin, Sohyoun Synthia;Lee, Sungho;Chaiy, Seoil
    • Asia Marketing Journal
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    • v.13 no.3
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    • pp.1-23
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    • 2011
  • The previous studies found the importance of market orientation (MO), learning orientation (LO), and marketing capabilities (MC) in driving firm performance (FP), but respectively. This research attempted to integrate the rather separate research streams of MO, LO, and MC in explaining FP. How MO and LO, as two critical constructs of organizations' cultural values, affect FP was examined with the mediating role of MC (composed of marketing planning capability (MPC) and marketing implementation capability (MIC)). Specifically, we derived specific conceptualizations on the effects of LO on FP through MO, MPC, and MIC as well as the effect of MO on FP through MPC. Accordingly, we empirically tested a process of how LO, MO, and MC translate into FP, using survey data of 146 respondents from Korean companies. The results successfully supported our model. It is worth noting not only that LO and MO are found to have synergistic effects on FP through MC but also that LO fosters MO. The relevant implications of our findings are presented with limitations and further research directions.

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A Study on Variation of Economic Value of Overseas Carbon Reduction Projects with Risk Factors (해외 탄소저감 사업의 위험요소를 고려한 사업 경제성 변동 분석)

  • Park, Jongyul;Choa, Sunghoon
    • Korean Journal of Construction Engineering and Management
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    • v.24 no.6
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    • pp.45-52
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    • 2023
  • Recently, as climate change caused by greenhouse gases is intensifying, the international community has committed to reduce greenhouse gas emissions. The purpose of this study is to present the methodology and major considerations for investment judgment. Two actual cases of overseas projects were selected as study subjects. As an analysis method, the major risk factors were defined as a probability distribution, and the NPV was stochastically estimated using the Monte Carlo simulation method. In addition, assuming a policy change, the range of NPV change was analyzed. As a result, the average NPV of project A was lowered by 19%, and the probability of showing a negative NPV was 12.2%. The average value of project B was lowered by 12.5%. Considering the policy change, project A can obtain economic benefits only when it obtains 72.9% or more of the total amount of carbon credits generated, and project B is economically feasible when it acquires 49.5% or more. As a result, the average value of project A is lower than the net present value under basic assumptions, so caution is needed in investment decisions depending on changes in major risk factors. Additionally, considering policy changes, the carbon credit distribution ratio should be differentially applied depending on the project size, and this was presented as a specific figure.

Analysis of the Abstract Structure in Scientific Papers by Gifted Students and Exploring the Possibilities of Artificial Intelligence Applied to the Educational Setting (과학 영재의 논문 초록 구조 분석 및 이에 대한 인공지능의 활용 가능성 탐색)

  • Bongwoo Lee;Hunkoog Jho
    • Journal of The Korean Association For Science Education
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    • v.43 no.6
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    • pp.573-582
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    • 2023
  • This study aimed to explore the potential use of artificial intelligence in science education for gifted students by analyzing the structure of abstracts written by students at a gifted science academy and comparing the performance of various elements extracted using AI. The study involved an analysis of 263 graduation theses from S Science High School over five years (2017-2021), focusing on the frequency and types of background, objectives, methods, results, and discussions included in their abstracts. This was followed by an evaluation of their accuracy using AI classification methods with fine-tuning and prompts. The results revealed that the frequency of elements in the abstracts written by gifted students followed the order of objectives, methods, results, background, and discussions. However, only 57.4% of the abstracts contained all the essential elements, such as objectives, methods, and results. Among these elements, fine-tuned AI classification showed the highest accuracy, with background, objectives, and results demonstrating relatively high performance, while methods and discussions were often inaccurately classified. These findings suggest the need for a more effective use of AI, through providing a better distribution of elements or appropriate datasets for training. Educational implications of these findings were also discussed.