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Comparative Assessment of Linear Regression and Machine Learning for Analyzing the Spatial Distribution of Ground-level NO2 Concentrations: A Case Study for Seoul, Korea (서울 지역 지상 NO2 농도 공간 분포 분석을 위한 회귀 모델 및 기계학습 기법 비교)

  • Kang, Eunjin;Yoo, Cheolhee;Shin, Yeji;Cho, Dongjin;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1739-1756
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    • 2021
  • Atmospheric nitrogen dioxide (NO2) is mainly caused by anthropogenic emissions. It contributes to the formation of secondary pollutants and ozone through chemical reactions, and adversely affects human health. Although ground stations to monitor NO2 concentrations in real time are operated in Korea, they have a limitation that it is difficult to analyze the spatial distribution of NO2 concentrations, especially over the areas with no stations. Therefore, this study conducted a comparative experiment of spatial interpolation of NO2 concentrations based on two linear-regression methods(i.e., multi linear regression (MLR), and regression kriging (RK)), and two machine learning approaches (i.e., random forest (RF), and support vector regression (SVR)) for the year of 2020. Four approaches were compared using leave-one-out-cross validation (LOOCV). The daily LOOCV results showed that MLR, RK, and SVR produced the average daily index of agreement (IOA) of 0.57, which was higher than that of RF (0.50). The average daily normalized root mean square error of RK was 0.9483%, which was slightly lower than those of the other models. MLR, RK and SVR showed similar seasonal distribution patterns, and the dynamic range of the resultant NO2 concentrations from these three models was similar while that from RF was relatively small. The multivariate linear regression approaches are expected to be a promising method for spatial interpolation of ground-level NO2 concentrations and other parameters in urban areas.

The Definition of a Catastrophe as Trauma by Visual Media and the Resultant Problems: A Critical Analysis of the "Antimimetic Theory" (시각 미디어에 의한 대재앙적 사건의 트라우마 규정과 그에 따른 문제들 - "반모방 이론"에 대한 비평적인 분석을 통해서)

  • Seoh, Gil-Wan
    • Cross-Cultural Studies
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    • v.43
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    • pp.265-288
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    • 2016
  • This essay begins by discussing the issue of the definition of a catastrophe as a trauma by visual media and the problems that result. We assume a concrete approach towards these problems by examining the process through which 9/11 was defined as a "national trauma" in the exclusion of images of bodies falling from towers, which were some of the most shocking images in the media coverage of 9/11. The choice to exclude images of falling men from American visual media representations of 9/11 goes hand in hand with the tendencies of a contemporary trauma theory. This essay assumes that the representations in the U.S visual media depend on "antimimetic theory," one of the leading contemporary trauma theories, in order to validate its logic, and examines the limitations and problems of the theory. This work aims to examine the issue of the definition of a catastrophe as trauma by visual media on the basis on the "antimimetic theory" and the danger that results. Because the antimimetic theory, which the visual media in the United States uses to define 9/11 as trauma, emphasizes literal and unmediated representation of an external event, it lacks an understanding of the human aspects of the event. There is no way to intervene in the construction and interpretation of the trauma. As a result, the theory discourages active attempts to find a solution to the problems of the people directly connected with the event. Thus, it provides an opening for manipulative intervention of an external power. This essay attempts to provide a critical analysis of the "antimimetic theory" in order to help people who witness catastrophic events through various types of visual media, and to seek an alternative means of experiencing and responding to the trauma, that does not stem from the perspective of specific media outlets or external powers.

Evolution of Aviation Safety Regulations to cope with the concept of data-driven rulemaking - Safety Management System & Fatigue Risk Management System

  • Lee, Gun-Young
    • The Korean Journal of Air & Space Law and Policy
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    • v.33 no.2
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    • pp.345-366
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    • 2018
  • Article 37 of the International Convention on Civil Aviation requires that rules should be adopted to keep in compliance with international standards and recommended practices established by ICAO. As SARPs are revised annually, each ICAO Member State needs to reflect the new content in its national aviation Acts in a timely manner. In recent years, data-driven international standards have been developed because of the important roles of aviation safety data and information-based legislation in accident prevention based on human factors. The Safety Management System and crew Fatigue Risk Management Systems were reviewed as examples of the result of data-driven rulemaking. The safety management system was adopted in 2013 with the introduction of Annex 19 and Chapter 5 of the relevant manual describes safety data collection and analysis systems. Through analysis of safety data and information, decision makers can make informed data-driven decisions. The Republic of Korea introduced Safety Management System in accordance with Article 58 of the Aviation Safety Act for all airlines, maintenance companies, and airport corporations. To support the SMS, both mandatory reporting and voluntary safety reporting systems need to be in place. Up until now, the standard of administrative penal dispensation for violations of the safety management system has been very weak. Various regulations have been developed and implemented in the United States and Europe for the proper legislation of the safety management system. In the wake of the crash of the Colgan aircraft, the US Aviation Safety Committee recommended the US Federal Aviation Administration to establish a system that can identify and manage pilot fatigue hazards. In 2010, a notice of proposed rulemaking was issued by the Federal Aviation Administration and in 2011, the final rule was passed. The legislation was applied to help differentiate risk based on flight according to factors such as the pilot's duty starting time, the availability of the auxiliary crew, and the class of the rest facility. Numerous amounts data and information were analyzed during the rulemaking process, and reflected in the resultant regulations. A cost-benefit analysis, based on the data of the previous 10 year period, was conducted before the final legislation was reached and it was concluded that the cost benefits are positive. The Republic of Korea also currently has a clause on aviation safety legislation related to crew fatigue risk, where an airline can choose either to conform to the traditional flight time limitation standard or fatigue risk management system. In the United States, specifically for the purpose of data-driven rulemaking, the Airline Rulemaking Committee was formed, and operates in this capacity. Considering the advantageous results of the ARC in the US, and the D4S in Europe, this is a system that should definitely be introduced in Korea as well. A cost-benefit analysis is necessary, and can serve to strengthen the resulting legislation. In order to improve the effectiveness of data-based legislation, it is necessary to have reinforcement of experts and through them prepare a more detailed checklist of relevant variables.

A Study on the Decisive Factors Influencing the Career Preparation Activities of North Korean Adolescent Defector (탈북 청소년 진로준비행동에 영향을 미치는 결정요인에 관한 연구)

  • Cho, Hyun-Seob;Chae, Kyung-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.6
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    • pp.501-513
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    • 2019
  • In this study, which is based on the findings of the preceding studies, the researchers determined social support and Career Decision Self-efficacy as the key influencing variables for the successful Career Preparation Activities, to analyze the relationship between Career Preparation Activities and these variables, while identifying the mediating effect of Career Decision Self-efficacy in the relationship between social support and Career Preparation Activities. In addition, there is an objective to provide effective career counseling materials. For this study, a total of 174 North Korean adolescent defectors, who were in their middle and high schools, were interviewed and the resultant data were analyzed the data based on the questionnaire data of 204 copies from March 12 to 19, 2019. For the analysis of the data, SPSS and AMOS statistical suites were used to verify the hypothesis. The result of the analysis showed that, first, in the relationship between the social support, Career Decision Self-efficacy, and Career Preparation Activities of the North Korean adolescent defectors social support, Career Decision Self-efficacy, and Career Preparation Activities were all positively related. Especially, Career Decision Self-efficacy has been identified as the variable that is highly related to Career Preparation Activities. Second, rather than social support(${\beta}=.107$), Career Decision Self-efficacy(${\beta}=.388$) turned out to have more profound direct influence on Career Preparation Activities. Third, social support did not influence Career Preparation Activities directly(${\beta}=.107$, p>.05) but completely intermediated Career Decision Self-efficacy to influence Career Preparation Activities(Indirect effect=.307, p<.05, Z-value=2.924, p<.01). The findings of this study show that, in order to enhance the Career Preparation Activities of the North Korean adolescent defectors, it is necessary to examine how they perceive the emotional, informational, material, and evaluative supports from the surrounding environment are perceived and identify the abilities, values, and career desires of themselves through a behavioral planning that can establish a professional and value system in accordance with them.

Performance of Waste-air Treating System Composed of Two Alternatively-operating UV/photocatalytic Reactors and Evaluation of Its Characteristics (교대로 운전되는 두 개의 UV/광촉매반응기로 구성된 폐가스 처리시스템의 성능 및 특성 평가)

  • Lee, Eun Ju;Lim, Kwang-Hee
    • Korean Chemical Engineering Research
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    • v.59 no.4
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    • pp.574-583
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    • 2021
  • Waste air containing ethanol (100 ppmv) and hydrogen sulfide (10 ppmv) was continuously treated by waste air-treating system composed of two annular photocatalytic reactors (effective volume: 1.5 L) packed with porous SiO2 media carrying TiO2-anatase photocatalyst, one of which was alternately operated for 32 d/run while the other was regenerated by 100 ℃ hot air with 15 W UV(-A)-light on. As its elimination-behavior of ethanol, the removal efficiencies of ethanol at 1st, 2nd and 3rd operation of the photocatalytic reactor system(A), turned out to be ca. 60, 55 and 54%, respectively, at their steady state condition. Unlike the elimination-behavior of ethanol, its hydrogen sulfide-elimination behavior showed repeated decrease of hydrogen sulfide removal efficiency by its resultant arrival at a lower level of steady state condition. Nevertheless, the removal efficiencies of hydrogen sulfide at 1st, 2nd and 3rd operation of the photocatalytic reactor system, turned out to be ca. 80, 75 and 73%, respectively, at their final steady state condition, higher by ca. 20, 20 and 19% than those of ethanol, respectively. Therefore, assuming that adsorption on porous SiO2-photocatalyst carrier was regarded to belong to a reversible deactivation and that decreased % of removal efficiency due to the reversible deactivation of photocatalyst including the adsorption was independent of the number of its use upon regeneration, the increments of the decreased % of removal efficiency of ethanol and hydrogen sulfide, due to an irreversible deactivation of photocatalyst, for the 3rd use of regenerated photocatalyst, compared with the 2nd use of regenerated photocatalyst, were ca. 1 and 2%, respectively, which was insignificant or the less than those of ca. 5 and 5%, respectively, for the 2nd use of regenerated photocatalyst compared with the 1st use of virgin photocatalyst. This trend of the photocatalytic reactor system was observed to be similar to that of the other alternately-operating photocatalytic reactor system.

Knowledge graph-based knowledge map for efficient expression and inference of associated knowledge (연관지식의 효율적인 표현 및 추론이 가능한 지식그래프 기반 지식지도)

  • Yoo, Keedong
    • Journal of Intelligence and Information Systems
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    • v.27 no.4
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    • pp.49-71
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    • 2021
  • Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.

Mineral Phase Transitions of Jarosite Substituted by Oxyanions during the Reductive Dissolution Using Oxalate Solution (옥살레이트 용액을 이용한 환원성 용해 시 산화음이온으로 치환된 자로사이트의 광물 상변화)

  • Lee, Myoungsin;Lee, Dongho;Chun, Herin;Kim, Yeongkyoo;Baek, YoungDoo
    • Korean Journal of Mineralogy and Petrology
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    • v.34 no.2
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    • pp.95-106
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    • 2021
  • The SO4 in the jarosite structure can be substituted by other oxyanions, and therefore, the transition of jarosite to goethite plays a very important role in controlling the behavior of oxyanions. In this study, the phase change according to the species of the oxyanion in jarosite and the related behavior of the oxyanion was studied by mineralogical and geochemical methods when jarosite, which is coprecipitated with various oxynions, undergoes a phase change by a reductive dissolution. Jarosite substituted by five oxyanions by 5 mol% was used in this study. The mineral phase change induced by reductive dissolution using ammonium oxalate was investigated, and the order of phase transition rate of jarosite to goethite was MoO4-jarosite ≥ SeO4-jarosite ≥ CrO4-jarosite > pure jarosite > SeO3-jarosite > AsO4-jarosite, showing that the transition rates vary depending on the substituted oxyanion. The resultant concentration of the leached Fe was slightly different depending on the type of oxyanion and time but did not show a noticeable difference. The concentration of each oxyanion leached according to the change of the mineral phase showed that the order of concentration of oxyanions was Mo > Se(SeO3) > As > Se(SeO4) > Cr in general, and showed a slight increase with time. This trend was related to the species of oxyanions rather than mineral phase change. The results of this study showed that the phase transition of jarosite to goethite was affected by the species of oxyanions, but this tendency did not affect the concentrations leached oxyanions.

Quality characteristics of kombucha made with saccharified rice solution (쌀당화액을 이용한 콤부차의 품질 특성)

  • Lee, Dae-Hyoung;Seo, Jae-Soon;Shin, Bok-Eum;Lee, Yong Seon;Cho, Chang Hui
    • Korean Journal of Food Science and Technology
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    • v.54 no.4
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    • pp.455-461
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    • 2022
  • In this study, kombucha was prepared using saccharified rice solution to assess this possible means of increasing rice consumption. Chucheong rice yielded the highest starch content (80.40±1.33%) when used to produce saccharified rice solution. The resultant saccharified rice solution showed the highest 10.42 °Brix at 90 min of saccharification. Chamdream rice yielded the highest acidity at 0.38%, and Kawaji No.1 yielded the lowest at 0.24%. Organic acid analysis on the 15th day of fermenting kombucha made with different rice varieties indicated an acetic acid content of 111.70±1.09 ppm in Chamdream, and 46.86±1.00 ppm in Dongjinchal. Comparison of enzymes used in saccharified rice kombucha fermentation revealed that α-amylase resulted in the highest acidity (1.06%), and β-amylase yielded the lowest acidity (0.58%). Kombucha with green tea yielded the highest acidity (1.09%), and kombucha with rooibos tea yielded the lowest (0.37%). Polyphenol analysis indicated that the amount of polyphenol increased the most (1,623.75 ppm to 3,989.00 ppm) on day 0 of fermentation with green tea. Organic acid analysis revealed that the acetic acid content of kombucha supplemented with green tea increased from 172.89 ppm on day 0 of fermentation to 2,649.11 ppm on day 15. Kombucha with 2.0% added alcohol had the highest acidity (1.32%), and kombucha with 0.5% alcohol had the lowest (0.97%). Taken together, these results confirm that it is possible to make kombucha using saccharified rice solutions.

The effects of Allomyrina dichotoma larval extract on palmitate-induced insulin resistance in skeletal muscle cells (장수풍뎅이 유충 추출물이 고지방산 처리 골격근세포의 인슐린 저항성에 미치는 영향)

  • Kim, Kyong;Sim, Mi-Seong;Kwak, Min-Kyu;Jang, Se-Eun;Oh, Yoon Sin
    • Journal of Nutrition and Health
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    • v.55 no.4
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    • pp.462-475
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    • 2022
  • Purpose: Allomyrina dichotoma larvae are one of the approved edible insects with nutritional value and various functional and medicinal properties. Previously we have demonstrated that the Allomyrina dichotoma larval extract (ADLE) ameliorates hepatic insulin resistance in high-fat diet (HFD)-induced diabetic mice through the activation of adenosine monophosphate-activated protein kinase (AMPK). This study investigated the effects of ADLE on insulin resistance in the skeletal muscle and explored mechanisms for enhancing the glucose uptake in palmitate (PAL)-treated C2C12 myotubes. Methods: To induce insulin resistance, the differentiated C2C12 myotubes were treated with PAL (0.5 mM) for 24 hours, and then treated with a 0.5 mg/ml concentration of ADLE, and the resultant effects were measured. The expression levels of glucose transporter-4 (GLUT4), AMPK, and the mitochondrial metabolism-related proteins were analyzed by western blotting. The mRNA expression levels of lipogenesis- related genes were determined by quantitative reverse-transcriptase PCR. Results: The exposure of C2C12 myotubes to 0.5 mg/ml of ADLE increased cell viability significantly compared to PAL-treated cells. ADLE upregulated the protein expression of GLUT4 and enhanced glucose uptake in the PAL-treated cells. ADLE increased the phosphorylated AMPK in both the PAL-treated C2C12 myotubes and HFD-treated skeletal muscle. The reduced expression levels of peroxisome-proliferator-activated receptor gamma co-activator-1 alpha (PGC1α) and uncoupling protein 3 (UCP3) due to the PAL and HFD treatment were reversed by the ADLE treatment. The citrate synthase activity was also significantly increased with the PAL and ADLE co-treatment. Moreover, the mRNA and protein expressions of fatty acid synthesis-related factors were reduced in the PAL and HFD-treated muscle cells, and this effect was significantly attenuated by the ADLE treatment. Conclusion: ADLE activates AMPK, which in turn induces mitochondrial metabolism and reduces fatty acid synthesis in C2C12 myotubes. Therefore, ADLE could be useful for preventing or treating insulin resistance of skeletal muscles in diabetes.

Estimation of the Korean Yield Curve via Bayesian Variable Selection (베이지안 변수선택을 이용한 한국 수익률곡선 추정)

  • Koo, Byungsoo
    • Economic Analysis
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    • v.26 no.1
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    • pp.84-132
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    • 2020
  • A central bank infers market expectations of future yields based on yield curves. The central bank needs to precisely understand the changes in market expectations of future yields in order to have a more effective monetary policy. This need explains why a range of models have attempted to produce yield curves and market expectations that are as accurate as possible. Alongside the development of bond markets, the interconnectedness between them and macroeconomic factors has deepened, and this has rendered understanding of what macroeconomic variables affect yield curves even more important. However, the existence of various theories about determinants of yields inevitably means that previous studies have applied different macroeconomics variables when estimating yield curves. This indicates model uncertainties and naturally poses a question: Which model better estimates yield curves? Put differently, which variables should be applied to better estimate yield curves? This study employs the Dynamic Nelson-Siegel Model and takes the Bayesian approach to variable selection in order to ensure precision in estimating yield curves and market expectations of future yields. Bayesian variable selection may be an effective estimation method because it is expected to alleviate problems arising from a priori selection of the key variables comprising a model, and because it is a comprehensive approach that efficiently reflects model uncertainties in estimations. A comparison of Bayesian variable selection with the models of previous studies finds that the question of which macroeconomic variables are applied to a model has considerable impact on market expectations of future yields. This shows that model uncertainties exert great influence on the resultant estimates, and that it is reasonable to reflect model uncertainties in the estimation. Those implications are underscored by the superior forecasting performance of Bayesian variable selection models over those models used in previous studies. Therefore, the use of a Bayesian variable selection model is advisable in estimating yield curves and market expectations of yield curves with greater exactitude in consideration of the impact of model uncertainties on the estimation.