Earticle

The market for commercial open source software (OSS) has been rapidly growing with the proliferation of OSS. One way to commercialize OSS is the support model, which has been adopted by leading OSS firms such as Red Hat and JBoss. Despite the growing interest in OSS commercialization, little research has provided OSS support providers with a pricing guideline. In this paper, we examine the optimal pricing strategies for OSS support providers. Our benchmark is a monopoly case in which we investigate a startup software vendor’s incentive to choose the OSS support regime over the proprietary one. Then we extend the model to a duopoly case in which OSS under the support regime competes against proprietary software. We characterize the conditions under which the OSS support model is viable under competition. We believe that our results offer insights to the OSS vendors who consider commercializing their OSS with a support model.

In the default prediction problem, the cost from the failure of forecasting defaults is much bigger than that of forecasting non-defaults. The cost asymmetry is deeper in the corporate default prediction than the retail as corporate loan portfolios are not granular. However, the two types of costs are treated equally in general as default prediction models are usually estimated to minimize prediction errors or maximize statistical performance. This practice might not fulfill the goal of risk management to minimize economic losses. To mitigate this issue, this study apply cost-sensitive learning approach to default prediction, which minimizes economic costs instead of statistical errors. We define economic costs and test them for various levels of the cost asymmetry by employing Logistic regression, XGBoost, and LightGBM. As a result of empirical experiments with Taiwanese and Polish corporate default data, we first find that the proposed cost-sensitive models are superior to the cost-insensitive counterparts in terms of economic cost, mostly regardless of the cost asymmetry scenarios. Secondly, nevertheless, the decreases in the statistical performance are relatively small – economic costs decrease 24.6% at the expense of the decrease in AUC of 4.6% on average. This suggests that financial firms can adopt the proposed default prediction models without violating the regulatory requirement on model quality. Lastly, we find that the features of high prediction power in the cost-sensitive and insensitive models are different, which has an important implication for credit monitoring.

In the default prediction problem, thecost from thefailure of forecasting defaults is much biggerthan that of forecastingnon-defaults. Thecost asymmetryis deeperin the corporatedefaultpredictionthan theretailas corporateloan portfolios arenot granular. However, thetwo typesof costs aretreatedequallyin generalas defaultpredictionmodels areusually estimatedto minimizepredictionerrorsor maximizestatistical performance. This practicemight not fulfill thegoal of risk managementto minimizeeconomiclosses. To mitigatethis issue, this study apply cost-sensitivelearningapproach to defaultprediction, which minimizeseconomiccosts insteadof statistical errors. Wedefineeconomic costs and testthemfor various levelsof thecost asymmetryby employingLogistic regression, XGBoost, and LightGBM. As a resultof empiricalexperimentswith Taiwaneseand Polish corporate default data, we first find that the proposed cost-sensitivemodels are superiorto thecost-insensitivecounterpartsin termsof economiccost, mostly regardless of thecost asymmetryscenarios. Secondly, neverthele,ssthedecreasesin thestatistical performanceare relativelysmall – economic costs decrease24.6% at theexpenseof the decrease in AUC of 4.6% on average. This suggests that financial firms can adopt the proposed default prediction models without violating the regulatory requirement on model quality. Lastly, we find that the features of high prediction power in the cost-sensitive and insensitive models are different, which has an important implication for credit monitoring.

본 연구는 금융투자소득세(금투세)라는 경제정책에 대한 유튜브 콘텐츠와 댓글 분석을 통해 정책 논의 및 여론 형성 과정에서 유튜브가 수행하는 역할을 탐색하 고자 하였다. 최근 개인 투자자들이 금융시장에서 차지하는 비중이 커지면서, 이들의 의견 파악 및 정책으로의 수용이 정책 결정 과정에 중요한 요소가 되었다. 특 히 젊은 투자자들은 유튜브와 같은 소셜 미디어에서 활발히 의견을 공유하고 정보를 교환하는 경향이 높아, 본 연구는 이들의 의견 형성 메커니즘에 주목하였다. 연구 대상으로는 경제 분야에서 영향력 있는 유튜브 채널인 ‘슈카월드’의 금투세 관련 콘텐츠를 선정하여 대본과 댓글 데이터를 수집하고, 잠재 디리클레 할당 (LDA) 토픽 모델링 분석 기법을 활용하여 분석하였다. 연구 결과, 콘텐츠 대본은 정책에 대한 구조적이고 객관적인 정보 제공과 설명에 중점을 두고 있었으나, 댓 글은 개인 투자자들의 실제적인 우려와 감정적 반응이 활발히 나타났다. 또한 댓글은 콘텐츠의 정보를 단순히 수용하는 데 그치지 않고, 불공정성, 차별과 같은 현 실적인 문제점에 대해 적극적이고 비판적인 상호작용을 보이는 공론장으로 기능하였다. 본 연구는 유튜브가 경제 정책 논의에서 정보 전달을 넘어 정책 평가와 여 론 형성을 위한 중요한 소통 플랫폼임을 실증적으로 확인하였으며, 정책 입안자들이 소셜미디어 댓글을 통해 대중의 실제 목소리를 적극적으로 수렴할 필요가 있 음을 확인하였다. 이를 바탕으로 정책 커뮤니케이션 전략에 대한 이론적 및 실무적 시사점을 제안하였다.

This study explores the role of YouTube in the discussion and public opinion formation surrounding economic policy by analyzing content and user comments related to the Financial Investment Tax (FIT). As individual investors have become increasingly prominent in the financial market, understanding their perspectives and incorporating their voices into policy decisions has become a critical factor. In particular, younger investors are highly active in sharing opinions and exchanging information on social media platforms such as YouTube. Focusing on these mechanisms of opinion formation, this study selected a highly influential economic YouTube channel, “Shuka World,” and analyzed both the video script and user comments using LDA topic modeling and N-gram analysis. The results show that while the video script primarily provided structural and objective explanations of the policy, the comments reflected investors’ practical concerns and emotional reactions. Furthermore, the comments did not merely absorb the content passively, but actively engaged with the perceived unfairness and systemic inequalities, functioning as a critical and participatory public sphere. The study confirms that YouTube serves not only as a channel for information delivery in economic policy communication but also as a platform that facilitates policy evaluation and public discourse. These findings highlight the importance of integrating user feedback from social media into policy-making processes and offer both theoretical and practical implications for future policy communication strategies.

이 글의 주요 목적은 GDP와 같은 국가 거시경제 펀더멘털, 은행시장발전과 주식시장발전과 같은 제도적 요인, 경제불확실성과 같은 기업 경영환경 요인 등이 은행 성과와 지역혁신에 미치는 영향을 고찰하는데 있다. 일련의 모델을 고찰하기 위해 2011~2024년 기간을 연구 시기로 프랑스, 독일, 이탈리아, 스페인, 영국 등 유럽 5개국 132개 일반 상업은행 재무 데이터와 각국별 자료를 Stata 통계패키지를 활용한 실증분석 에 사용하였다. 실증분석 결과 발견된 주요 사실은 다음과 같다. 우선 첫째, 국가 거시경제 펀더멘털 요소로 GDP는 은행의 성과에는 영향을 주 지 않지만 지역혁신 성과에는 긍정적 영향을 미친다. 둘째, 은행시장발전 및 주식시장발전과 같은 제도적 요인 역시 은행의 성과에 미치는 영 향력은 부재하지만 은행의 성과 개선은 지역혁신 수준을 개선시키는 긍정적 관계를 갖는다. 한편 은행시장발전과 금융시장발전은 지역혁신을 개선시키는 직접효과도 있지만 경제불확실성과 지역혁신 간 부정적 관계를 개선시키는 긍정적 조절요인으로 작용한다. 마지막으로, 경제불확 실성과 같은 기업 경영환경요인은 은행의 성과에 부정적 영향을 미치며 지역혁신을 저해하는 요소로 작용한다. 반면 지역혁신 지수는 은행의 성과를 개선시키고 경제불확실성과 은행 성과 간 부정적 관계를 긍정적 관계로 전환시키는 조절기능을 수행한다.

The main purpose of this article is to examine the impact of national macroeconomic fundamentals such as GDP, institutional factors such as banking market development and stock market development, and business management environment factors such as economic uncertainty on bank performance and regional innovation. To examine a series of models, the study period from 2011 to 2024 was used to conduct an empirical analysis using the Stata statistical package using the financial data of 132 general commercial banks in five European countries and data for each country. The main facts discovered as a result of the empirical analysis are as follows. First, as a national macroeconomic fundamental factor, GDP does not affect bank performance, but has a positive effect on regional innovation performance. Second, institutional factors such as banking market development and stock market development also have no influence on bank performance, but improvement in bank performance has a positive relationship with improving regional innovation. Meanwhile, banking market development and financial market development have a direct effect on improving regional innovation, but they also act as positive regulating factors that improve the negative relationship between economic uncertainty and regional innovation. Lastly, corporate business environment factors such as economic uncertainty have a negative impact on banks' performance and act as factors that hinder regional innovation. On the other hand, the regional innovation index improves the performance of banks and performs a regulating function by converting the negative relationship between economic uncertainty and bank performance into a positive relationship.

"Olive-style" Integration Strategy(OIS) is a new strategy model, We borrow deeply familiar western sports term "grab type football" to intuitive, vividly described the top-level design of regional economic development strategy. OIS of the mechanical effect of single tower cable-stayed bridge, for the regional government based on the existing resources conditions, regional geographic features, economy, technology, environment, investment environment, the local social and cultural environment, carefully cultivate and develop the new succeeded alternative industries, which is scientific and effective to achieve the optimal allocation of limited resources area and the strategic reorganization of industrial structure(Including primary industry, secondary industry and tertiary industry), industry value chain smile curve, Which should play a positive guiding role to speed up regional industrial economic development.

2013년 사쿠라지마 화산 폭발을 비롯하여 세계적으로 화산분화가 잦아짐에 따라 백두산 화산분화에 대한 우려가 증가하고 있다. 화산분화 시 상황에 따라 화산재, 화쇄류 및 화산이류와 같은 화산재해가 발생하며, 이 중 화산재는 기상상황에 따라 한반도에 직접적인 피해를 줄 수 있는 것으로 보고되었다. 그러나 지금까지의 연구는 대부분 기상 및 지구과학적 측면에서 화산재 확산자체에 대한 모델 적용 또는 경제적 측면에서 재해에 따른 경제적 취약성 계산과 같은 어느 하나의 학문분야에 초점을 두고 수행되었다. 본 연구에서는 화산재모델링의 결과 값을 공간적으로 표출하는 과정과 이를 근거로 하여 피해 산정 모델링 식에 적용을 하여, 상호작용을 통한 경제적 피해산정이 모델링 결과에 이어 바로 수행할 수 있도록 설계 및 프로그램 구현을 진행하였다. 즉, 피해지도는 모델링의 결과와 경제적 피해산정의 결과가 모두 지역단위로 표출될 수 있도록 연결한 것으로, 보통 피해액 산정에 있어 전체 값만을 도출하는 기존 연구와 차이를 보여준다. 실제 이러한 모듈은 화산분화 발생 시 효과적인 대응시스템 적용으로 연결될 것이며, 피해지도(damage map)의 표출 관련 이론적 틀을 마련하는 데 기여할 것으로 사료된다. 지역단위의 상세한 공간정보 설계와 지도학적 표현을 가능하게 하는 프로그래밍은 화산학, 기상학, 토목공학 및 경제학의 영역의 일부를 모두 포함하여, 우리에게 주어진 질문 “백두산의 화산분화가 우리의 삶과 경제에 얼마나 영향을 미칠 것인가?” 에 답할 수 있도록 구현되었으며 그 답은 본 연구의 결과에 분화 당시의 파라미터 값에 따라 동적으로 다양한 결과를 얻게 된다고 할 수 있다.

Frequently reported volcanic eruption events such as Sakurajima volcano in 2013 have made people worried about the time of the Baekdusan volcanic eruption and the extent of it. Volcanic eruption may bring volcanic disasters including ash, pyroclastic flow, lahar and earthquake, of which, especially, volcanic ash of Baekdusan has assumed and reported to have an influence on Republic of Korea based on the wind direction. Previous researches have focused on the geological and atmospheric modeling and economic damage assessment in separate field. This study aims to integrate FALL3D volcanic ash modeling and economic damage assessment by designing and programming based on GIS data. The amount of ash deposition can be calculated by FALL3D model with controlling parameters and expressed in hazard map. The detailed information on the agricultural activities in the regional unit has been merged with economic damage assessment model, then we are able to draw volcanic ash damage map. This module will be a part of a volcanic ash response system and give an intuition of the dynamic concept of damage map. GeoSpatial information design and cartographical expression will cover the different fields such as volcanology, atmospheric science, civil engineering and economics to response the question “How much will Baekdusan volcano eruption affect our life and economy? The answer will depends on the input parameters of the integrated GIS model during the event.

Background/Aims: Dual priming oligonucleotide-based multiplex polymerase chain reaction (DPO-based PCR) can detect the presence of clarithromycin resistance without culture. The aim of this study was to investigate the costeffectiveness of DPO-based PCR for Helicobacter pylori eradication. Methods: From 2015 to 2016, medical records of patients who received H. pylori eradication therapy were analyzed. Patients were divided into two groups: tailored group patients who were treated based on DPO-based PCR and empirical group patients. Eradication rate and medical cost, including diagnostic tests, eradication regimens, and 13C-urea breath tests, were compared between the two groups. Cost for one successful eradication was calculated in each group. The expected cost of eradication for empirical treatment was investigated by varying the treatment duration and eradication rate. Results: A total of 527 patients were analyzed (tailored group 208, empirical group 319). The eradication success rate of the first-line therapy was higher in the tailored group compared to that in the empirical group (91.8% vs 72.1%, p<0.01). The total medical cost for each group was 114.8±14.1 U.S. dollars (USD) and 85.8±24.4 USD, respectively (p<0.01). The total medical costs for each ultimately successful eradication in the tailored group and in the empirical group were 120.0 USD and 92.4 USD, respectively. The economic modeling expected cost of a successful eradication after a 7- or 14-day empirical treatment was 93.8 to 111.4 USD and 126.3 to 149.9 USD, respectively. Conclusions: Based on economic modeling, the cost for a successful eradication using DPO-based PCR would be similar or superior to the expected cost of a successful eradication with a 14-day empirical treatment when the first-line eradication rate is ≤80%.

본 논문은 Crandall의 탑승자 사망에 관한 모형에 Directed Graph를 응용한 것으로써 데이터는 Crandall이 사용한 미국의 1947-1981 기간의 탑승자 사망 데이터를 1993년까지 확장한 것을 사용하였다. Directed Graph Algorithm방법은 최근에 컴퓨터과학 분야에서 발전된 것을 원용한 것이다. 먼저 1947-1981 기간의 데이터를 기초로 하여 회귀분석을 통한 분석 대신에 Directed Graph Algorithm을 이용한 결과, 회귀분석을 이용했던 Crandall의 결과와는 달리 탑승자 사망은 소득수준, 자동차의 운행거리, 자동차의 안전장치 수준에 의하여 직접적으로 결정이 되는 것으로 나타났다. 자동차의 운행거리는 수득수준과 시내주행에 대한 교외주행 의 비 에 의해서 결정되는 것으로 나타났다. 이런 결과에 근거하여 3SLS(three stage least squares regression)를 이용하여 추정하고, 이러한 추정에 근거하여 1982-1993 기간을 예측했으며, Crandall의 원래의 모형의 예측력과 비교를 하여？. 예측 결과 본 모형이 MSE(mean squared error)를 기준으로한 예측력에서 훨씬 뛰어난 결과를 보였다. 더욱 중요한 것은 본고에서는 Crandall이 사용한 변수간에 기존의 계량적 방법으로는 색출이 불가능했던 잠재변수 (Latent variable)가 존재함을 구체적으로 보임으로써 회귀분석을 통한 모형화는 진정한 변수간의 관계를 반영치 못함을 보인 것이다.

Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

From the past until now, political and economic relations among countries have been one of the most important issues among analysts and numerous studies have tried to analyze these relations from different theoretical perspectives. The dynamic system of games has introduced a new modeling method in the game theory. In this study, we use behavioral models (level- k) along with the dynamic system in games to model rational agent behavior. As an application, we study Russia- Norway economic and political relations (1970-2019). The dynamic system in games along with behavioral games theory can be used to predict the players behavior in the future.

Purpose: In this paper we propose modified Notz designs which are useful to experimenters who want to adopt the sequential experimentation strategy and to estimate second-order regression model with as few experimental points as possible. Methods: We first present the design matrices and design points in two or three dimensional spaces for such small sized second-order designs as small composite, hybrid, and Notz designs. Modified Notz designs are proposed and compared with some response surface designs in terms of the total number of experimental points, the estimation capability criteria such as D- and A-optimality. Results: When sequential experimentation is necessary, the modified Notz designs are recommendable. Conclusion: The result of this paper will be beneficial to experimenters who need to do experiments more efficiently, especially for those who want to reduce the time of experimentation as much as possible to develop cutting-edge products.

A series of tests dedicated to station blackout (SBO) accident scenarios have been recently performed at the $Prim{\ddot{a}}rkreislauf-Versuchsanlage$ (primary coolant loop test facility; PKL) facility in the framework of the OECD/NEA PKL-3 project. These investigations address current safety issues related to beyond design basis accident transients with significant core heat up. This work presents a detailed analysis using the best estimate thermal-hydraulic code TRACE (v5.0 Patch4) of different SBO scenarios conducted at the PKL facility; failures of high- and low-pressure safety injection systems together with steam generator (SG) feedwater supply are considered, thus calling for adequate accident management actions and timely implementation of alternative emergency cooling procedures to prevent core meltdown. The presented analysis evaluates the capability of the applied TRACE model of the PKL facility to correctly capture the sequences of events in the different SBO scenarios, namely the SBO tests H2.1, H2.2 run 1 and H2.2 run 2, including symmetric or asymmetric secondary side depressurization, primary side depressurization, accumulator (ACC) injection in the cold legs and secondary side feeding with mobile pump and/or primary side emergency core coolant injection from the fuel pool cooling pump. This study is focused specifically on the prediction of the core exit temperature, which drives the execution of the most relevant accident management actions. This work presents, in particular, the key improvements made to the TRACE model that helped to improve the code predictions, including the modeling of dynamical heat losses, the nodalization of SGs' heat exchanger tubes and the ACCs. Another relevant aspect of this work is to evaluate how well the model simulations of the three different scenarios qualitatively and quantitatively capture the trends and results exhibited by the actual experiments. For instance, how the number of SGs considered for secondary side depressurization affects the heat transfer from primary side; how the discharge capacity of the pressurizer relief valve affects the dynamics of the transient; how ACC initial pressure and nitrogen release affect the grace time between ACC injection and subsequent core heat up; and how well the alternative feeding modes of the secondary and/or primary side with mobile injection pumps affect core quenching and ensure stable long-term core cooling under controlled boiling conditions.

This study discusses an effort to build a model to link normalized difference vegetation indices (NDVI) and socio-economic indicators derived from village survey (1990, 1993, 1996, and 2000) statistical data in Bekasi, West Java, Indonesia. Socio-economics indicators of sub-district level, in this study the number of agricultural households (AH), are aggregated from village level data. NDVI from Landsat-TM resolution data (1989 and 1997) are computed to detect land use/land cover (LULC) dynamics in the sub-district areas. Attention is mainly paid on the examination of agricultural land cover changing in the sub-district level. NDVI measurements might be used to predict AH dynamics as showed by computed linear regression models.

특허제도가 활성화되자 ‘특허괴물’로 논의되는 부작용이 드러나면서 저명 경제학자, 특허소송전문 판사, 그리고 미국·유럽 시민단체들까지 합류하여 공공정책관점에서 특허제도 폐지나 전면 개정을 주장하기에 이르렀다. 이들의 견해는 특허체제가 혁신과 발명을 방해하고 시장과 소상인에게 부정적 독점 형성, 기술특허 소송의 장기화, 거대화로 인해 막심한 사회적 낭비가 발생한다는 것이다. 이것은 특허가 개인의 독점과 배타적 권리 전제로 제도적 취지와는 달리 ‘특허부자’를 목표로 하는 과다경쟁 결과라 할 수 있다. 왜냐하면 특허는 연구 개발비와 투자 대비 영업실적이 큰, 즉 구매력이 높은 소비자들을 대상으로 하는 기술 집약 부분에 과다집중 되어있기 때문이다. 본 연구의 목적은 최근 특허가 제도의 본래 취지와 달리 기형적으로 발달하고 있고, 국가별로 검토하고 있는 정부차원에서의 특허권한 취소·박탈이라는 과잉 조처에 대해 장기적이고도 긍정적인 특허제도 균형발전 안을 탐색하는 데 있다. 연구방법으로 특허제도에 관한 문헌과 선행연구, 사례와 제도운영 시스템들을 양적·질적으로 검토하였다. 이를 근거로 통합적 win-win 구도 형성을 위한 특허제도 발달 모델링 프레임웍을 개발하여 제시하고, 그 각 구성개념과 요소들이 장기적 경제시스템 속에 선순환하며 긍정적 특허 활성화를 위한 기틀 형성에 기여하고자 한 것이다. 이론적 접목은 인간의 보편적 욕구에 기초한 동기부여이론(Maslow, 1943), Six-Sigma DMAIC 모델 (Harry and Schroeder, 2000)과 Strategy Maps(Kaplan and Norton, 2004)를 토대로 하였다. 본 연구의 차별점은 다양한 관점에서의 자료 검토와 특허전문가 FGI(focus group interview) 결과를 접목하고 이론·사례·FGI 방법론을 모두 활용하여 특허의 종단적 발전과정을 탐색하여 기업, 개인, 특허행정, 소비자, 산업구조, 경제적 관점에서의 문제점과 개선방향을 간결하게요약 제시함과 동시에, 경영학 관점에서의 융·복합적 특허발전 전략모델을 제시한다는 것이다. 이것은 특허관련 최초의 연구가 될 것으로 판단되어 후속연구가 기대된다. 긍정적 특허 활성화를 위해서는 향후 융·복합시대에 기술발달에 대한 인문·사회학적 고찰과 기술전문인의 경영학적 마인드, 그리고 지역사회에서의 경제시스템과 체제를 통합적으로 고려하는 인재 양성 프로그램 운영이 요구된다. 그리고 특허정책수립과 의사결정자들이 세계 시장구도를 미리 예측하여 전략적 주력 산업분야를 발굴, 대비하는 세계적, 국가적, 사회적 전략시스템 제시가 개인적 특허기술 개발에 선행되어야 할 것이다. 긍정적 특허활성화 결과는 장기적으로 인재와 자본투자의 분산, 산업별 균형발전, 그리고 지역특화에도 기여할 것이다.

In the framework of OECD/NEA Working Group on Fuel Safety, a RIA fuel-rod-code Benchmark Phase I was organized in 2010-2013. It consisted of four experiments on highly irradiated fuel rodlets tested under different experimental conditions. This benchmark revealed the need to better understand the basic models incorporated in each code for realistic simulation of the complicated integral RIA tests with high burnup fuel rods. A second phase of the benchmark (Phase II) was thus launched early in 2014, which has been organized in two complementary activities: (1) comparison of the results of different simulations on simplified cases in order to provide additional bases for understanding the differences in modelling of the concerned phenomena; (2) assessment of the uncertainty of the results. The present paper provides a summary and conclusions of the second activity of the Benchmark Phase II, which is based on the input uncertainty propagation methodology. The main conclusion is that uncertainties cannot fully explain the difference between the code predictions. Finally, based on the RIA benchmark Phase-I and Phase-II conclusions, some recommendations are made.

This study presents a robust thermoeconomic framework for marine nuclear propulsion, utilizing the Nuclear Ship Savannah as a case study. To overcome data limitations, creative solutions are applied, including the application of artificial neural network approach to solve nonlinear coupled exergoeconomic equations and determine the thermodynamic properties of the flow within the Savannah's Nuclear Propulsion (SNP). Upon validating the proposed model, the study introduces innovative design modifications to enhance the thermal efficiencies of the SNP. Furthermore, single-objective optimization (SOO) and multi-objective optimization (MOO) are incorporated into the improved SNP (ISNP) to optimize system performance criteria, such as exergy efficiency (η_II), total capital cost rate (Ċ^I&O&M_tot), and total product exergy cost rate (Ċ_P). Afterwards, the ISNP optimization is executed using Henry Gas Solubility Optimization (HGSO) to determine the optimal non-dominated solutions, allowing for the evaluation of trade-offs in system performance. The final optimal design of the optimized ISNP (OISNP) is then selected through a multi-criteria decision-making process. Subsequently, a comprehensive comparative analysis is conducted on the SNP, ISNP, and OISNP models, considering energy, exergy, exergoeconomic, and environmental economics (4-E) viewpoints. The 4-E analysis reveals that the SNP exhibits an energy efficiency of 26.18 % and an exergy efficiency of 51.8 %, whereas the ISNP demonstrates enhanced performance with an energy efficiency of 28.42 % and an exergy efficiency of 55.50 %. The improvement lead to a 1.31 MW boost in propulsion power compared to the SNP, bringing it to 16.4 MW. This comparative evaluation underscores the significant improvements achieved through the modifications implemented in the SNP. Also, the OISNP demonstrates further advancements, achieving an exergy efficiency of 55.01 %, representing a 3.2 % improvement over the SNP, while its energy efficiency is recorded at 28.4 %, a 2.22 % increase compared to the SNP. Additionally, the propulsion power reaches 16 MW, marking a 1 MW increase over the SNP. Notably, the Ċ^I&O&M_tot,OISNP and Ċ_P,OISNP are reduced to $282.3/hour and $4290/hour, respectively, indicating substantial cost savings relative to both the ISNP and SNP models. Besides, the environmental analysis indicates that transitioning from a fossil fuel-powered MSP to an OISNP annually cuts fossil fuel consumption by 61,320 tons, generating $30.66 million in potential export revenue. This change reduces emissions by 193 kilotons (kt) of CO₂, 4.3 kt of NO_x, 3 kt of SO₂, and 0.92 kt of PM, while decreasing external costs by $6.132 million and potentially avoiding $9.65 million in annual carbon tax liabilities for the shipping industry. Furthermore, to evaluate the comparative statistical performance of the competing algorithms, a Wilcoxon rank sum test is conducted. The comparative results show that the HGSO algorithm outperforms the others, delivering both competitive and superior outcomes in solving complex optimization problems.

본 연구에서는 충주시의 음식물바이오에너지센터로부터 음식물류페기물의 혐기발효 처리 후 발생되는 바이오 가스를 전처리 및 고질화공정을 통해 이산화탄소 및 불순물을 제거한 바이오메탄을 원료로 그린수소를 생산하는 수소추출시스템 공정을 모델링하고 경제성 분석을 수행하였다. 고질화된 바이오메탄은 개질 및 정제공정을 통해 하루 약 500 kg의 고순도 수소가 생산되며, 공정모델의 수소생산량 결과를 토대로 현재 실증을 위해 구축하고 있는 그린수소충전소 수소추출시스템의 경제성 분석을 수행하였다. 경제성 분석 결과, 수소추출시스템의 구축년도를 제외한 15년의 사업운영 후 순현재가치는 38억3천1백만 원, 수익성지수법 1.42 및 내부수익률 20.25%로 사회적 할인율 4.5%를 상회하므로 타당성 확보가 가능하다 판단된다.

In this paper, we carried out the process modelling and economical analysis of the 500 kg-H₂/d-class green hydrogen production system process based on biomethane from the Food Bio Energy Center in Chungju. As a result of economic analysis, the NPV(Net present value) after 15 years of operation is 3.831 billion won, the PI(Profitability index method) is 1.42. It was found that the project of 500 kg-H₂/d-class green hydrogen production system has a 20.25% of IRR, which is higher than social discount rate of 4.5% and feasibility is ensured.

Aujeszky's disease (AD) is a respiratory, infectious viral illness associated with high mortality, especially in neonatal piglets and has frequently been considered an economically important disease in many endemic countries. Although AD is still occurring in a geographically defined region in Korea, little attention has been paid to the economics of AD. In this study, partial budget technique was used to develop a simulation model to measure financial losses following the disease epidemic in a swine operation utilizing stochastic or deterministic parameters from the literatures and the index case herd of AD occurred in 2005, where available and applicable. For the infected case herd with a 12500-pig, the total economic loss for this operation was estimated to be about 199 million Korean won (95% confidence interval [CI] 148,645,000-250,741,000). Given net loss due to death of a pig at sow level was 119,000 won, total loss for the case herd with 1200 sows accounted for 143 million won (95% CI 92,599,000-193,729,000). The net loss of the death of one pig at growing and fattening level resulted in loss of 46,000 won (95% CI 40,000-53,000) and 126,000 won (95% CI 122,000-131,000), respectively. Taking into account for the number of pigs raised in the case herd, total loss amounted to 8 million won (95% CI 7,167,000-9,347,000) and 12 million won (95% CI 11,959,000-12,891,000), for growers and fatteners, respectively, assuming 63% of saved feed intake when a pig dies halfway through the respective period. Under the model's assumptions, suckling pig mortality was the major factors of loss in estimating the economic consequences (approximately 71.8% of the total loss). The high economic losses of a herd infected with AD suggest that the effective and region-specific control measures should be implemented in disease endemic foci.

본 연구는 정보화 역기능을 대표하는 '1·25 인터넷 침해사고'와 같이 인터넷이 정지되어서 발생하는 실제 피해액을 산출할 수 있는 모델을 구축하는 것이다. 인터넷 정지에 따른 피해는 직접적인 피해와 간접적인 피해로 구분할 수 있다. 그러나 현재까지 한국에서는 간접적인 피해가 인정되고 있지 않으므로 직접적인 피해만 모델에 포함시킨다. 모델은 직접적 피해를 온라인 매출이익 감소분, 효율성 저하에 따른 생산 감소분, 인터넷 복구부분으로 나뉘어 구성된다. 각 구성항목은 인터넷 정지시간, 온라인 매출액, 생산 감소분 등의 실제적인 변수를 사용하고 있으므로 피해액도 구체적으로 특정할 수 있다. 한편, 본 연구에서 제시하는 모델은 기존의 해외 선행모델과 달리 인터넷 정지의 원인에 기초한 피해가 아니라 현재화된 실제적 결과를 분석대상으로 하고 있다.

On this study, we establish a model for accessing the actual economic damages caused by the internet incidents such as the infamous '1.25 internet incident'. The damages from internet incidents can be classified into two parts, 'direct damages' and 'indirect damages'. But in the model developed on this paper, only the 'direct damage' part is counted, as the 'indirect damages' are not usually accepted in Korea. The 'direct damage' part consists of 'loss of profit on online sales', 'reduction of production due to loss of work efficiency', and 'recovery costs'. Since each component is measured in the actual statistic such as the 'internet down time', 'online sales', and 'reduced production', the economic damage can be specified concretely. But, unlike the previously avaliable foreign models, the model proposed in the paper considers the net results of the incidents, not the causes of the incidents.