• The Journal of Society for e-Business Studies
• /
• v.22 no.2
• /
• pp.137-152
• /
• 2017

The decline in the price of IT devices and the development of the Internet have created a new field called Internet of Things (IoT). IoT, which creates new services by connecting all the objects that are in everyday life to the Internet, is pioneering new forms of business that have not been seen before in combination with Big Data. The prospect of IoT can be said to be unlimited in its utilization. In addition, studies of standardization organizations for smooth connection of these IoT devices are also active. However, there is a part of this study that we overlook. In order to control IoT equipment or acquire information, it is necessary to separately develop interworking issues (IP address, Wi-Fi, Bluetooth, NFC, etc.) and related application software or apps. In order to solve these problems, existing research methods have been conducted on augmented reality using GPS or markers. However, there is a disadvantage in that a separate marker is required and the marker is recognized only in the vicinity. In addition, in the case of a study using a GPS address using a 2D-based camera, it was difficult to implement an active interface because the distance to the target device could not be recognized. In this study, we use 3D Depth recognition camera to be installed on smartphone and calculate the space coordinates automatically by linking the distance measurement and the sensor information of the mobile phone without a separate marker. Coordination inquiry finds equipment of IoT and enables information acquisition and control of corresponding IoT equipment. Therefore, from the user's point of view, it is possible to reduce the burden on the problem of interworking of the IoT equipment and the installation of the app. Furthermore, if this technology is used in the field of public services and smart glasses, it will reduce duplication of investment in software development and increase in public services.

• Journal of Intelligence and Information Systems
• /
• v.22 no.4
• /
• pp.19-43
• /
• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Journal of Intelligence and Information Systems
• /
• v.21 no.3
• /
• pp.79-99
• /
• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2003.11a
• /
• pp.348-351
• /
• 2003

산소 과전압이 낮은 $MnO_2$를 촉매로 사용하여 반도체 산화물계의 산소선택성 전극을 제조하고 산화물 coating층의 미세구조와 전기화학적 특성을 분석하였다. Ti 기판에 열분해 법을 이용하여 $MnO_2$ 피막을 형성하였고, 또한 PVDF : $MnO_2$의 함량비를 1 : 1에서 1 : 40까지 정량적으로 변화시키고 DMF의 함량을 각각의 고정된 PVDF : $MnO_2$의 함량비에서 변화시켜 Pb전극에 1.5 mm/sec의 속도로 5회 dipping하여 $MnO_2$ 피막층을 형성 하였다. $450^{\circ}C$에서 1시간 열분해하여 약 $1\;{\mu}m$의 $MnO_2$ 피막층이 형성되었으나 Ti 기판과의 접착력이 약하여 피막자체에 대한 전기화학적 특성을 관찰할 수 없었다. PVDF : DMF = 4 : 96인 경우 pb 전극의 피막층이 얇기 때문에 박리현상이 일어났으며 이는 산화물 용제의 낮은 점도 때문인 것으로 판단된다. 또한 PVDF : DMF = 10 : 90의 경우는 5회 dipping 하여 약 $150\;{\mu}m$의 피막층을 형성하였다. PVDF : $MnO_2$의 함량비가 1:1에서 1:6 까지는 DMF의 함량에 무관하게 전극 특성이 나타나지 않았지만 $MnO_2$의 양이 상대적으로 증가하면 cycle이 증가하더라도 거의 일정한 전류 값을 갖고 $MnO_2$와 PVDF의 비가 20:1 이상의 조성에서는 균일한 CV 특성을 나타냈다. 이는 $MnO_2$가 효과적으로 촉매 작용을 한 것으로 판단되며 anodic polarization에 의한 산소 발생 과전압도 약 1.4V 정도로 감소되었다.동등한 MSIL 코드를 생성하도록 시스템을 컴파일러 기법을 이용하여 모듈별로 구성하였다.적용하였다.n rate compared with conventional face recognition algorithms. 아니라 실내에서도 발생하고 있었다. 정량한 8개 화합물 각각과 총 휘발성 유기화합물의 스피어만 상관계수는 벤젠을 제외하고는 모두 유의하였다. 이중 톨루엔과 크실렌은 총 휘발성 유기화합물과 좋은 상관성 (톨루엔 0.76, 크실렌, 0.87)을 나타내었다. 이 연구는 톨루엔과 크실렌이 총 휘발성 유기화합물의 좋은 지표를 사용될 있고, 톨루엔, 에틸벤젠, 크실렌 등 많은 휘발성 유기화합물의 발생원은 실외뿐 아니라 실내에도 있음을 나타내고 있다.>10)의 $[^{18}F]F_2$를 얻었다. 결론: $^{18}O(p,n)^{18}F$ 핵반응을 이용하여 친전자성 방사성동위원소 $[^{18}F]F_2$를 생산하였다. 표적 챔버는 알루미늄으로 제작하였으며 본 연구에서 연구된 $[^{18}F]F_2$가스는 친핵성 치환반응으로 방사성동위원소를 도입하기 어려운 다양한 방사성의 약품개발에 유용하게 이용될 수 있을 것이다.었으나 움직임 보정 후 영상을 이용하여 비교한 경우, 결합능 변화가 선조체 영역에서 국한되어 나타나며 그 유의성이 움직임 보정 전에 비하여 낮음을 알 수 있었다. 결론: 뇌활성화 과제 수행시에 동반되는 피험자의 머리 움직임에 의하여 도파민 유리가 과대평가되었으며 이는 이 연구에서 제안한 영상정합을 이용한 움직임 보정기법에 의해서 개선되었다. 답이 없는 문제, 문제 만들기, 일반화가 가능한 문제 등으로 보고, 수학적 창의성 중 특히 확산적 사고에 초점을 맞추어 개방형 문제가 확산적 사고의 요소인 유창성, 독창성, 유연성 등에 각각 어떤 영향을 미치는지 20주의 프로그램을 개발, 진행하여 그 효과를 검증하고자

• Journal of the Korean Institute of Gas
• /
• v.8 no.2 s.23
• /
• pp.15-27
• /
• 2004

The purpose of this paper is to improve the performance of Polymer electrolyte fuel cell(PEMFC) by studying the channel dimension of bipolar plates using commercial CFD program 'Fluent'. Simulations are done ranging from 0.5 to 3.0mm for different size in order to find the channel size which shoves the highst hydrogen consumption. The results showed that the smaller channel width, land width, channel depth, the higher hydrogen consumption in anode. When channel width is increased, the pressure drop in channel is decreased because total channel length Is decreased, and when land width is increased, the net hydrogen consumption is decreased because hydrogen is diffused under the land width. It is also found that the influence of hydrogen consumption is larger at different channel width than it at different land width. The change of hydrogen consumption with different channel depth isn't as large as it with different channel width, but channel depth has to be small as can as it does because it has influence on the volume of bipolar plates. however the hydrogen utilization among the channel sizes more than 1.0mm which can be machined in reality is the most at channel width 1.0, land width 1.0, channel depth 0.5mm and considered as optimum channel size. The fuel cell combined with 2cm${\times}$2cm diagonal or serpentine type flow field and MEA(Membrane Electrode Assembly) is tested using 100W PEMFC test station to confirm that the channel size studied in simulation. The results showed that diagonal and serpentine flow field have similarly high OCV and current density of diagonal (low field is higher($2-40mA/m^2$) than that of serpentine flow field under 0.6 voltage, but the current density of serpentine type has higher performance($5-10mA/m^2$) than that of diagonal flow field under 0.7-0.8 voltage.

• Journal of Science and Technology Studies
• /
• v.4 no.2 s.8
• /
• pp.67-101
• /
• 2004

Although the study of citation patterns is an important theme within the sociology of science, due to the fact that it is intimately related to the production, reproduction, and evaluation of knowledge, only sustained theoretical research outlining the differences of citation patterns between the hard and soft sciences has been conducted, and empirical studies nevertheless remain few and far between. The perspectives of institutionalism and constructivism have to attempted to explain different citation patterns between the hard and soft sciences as a contrast between 'what one says' and 'who one is'. Therefore, against this background this study examines the 'theoretical' controversy empirically by comparing the contrasting citation patterns of physics, as a representative of hard science, and sociology, as a representative of soft science. The results, in brief, are as follows: the citaton patterns in physics, as in sociology, vary according to the author's status within the hierarchical employment structure, i. e. whether s/he is a full-time lecturer or not, but diversity of citation patterns according to Ph. D. diploma area is unique to sociology. These results would suggest that the explanation of constructivism is more relevant in explaining variance according to the author's status in the employment hierarchy, but the approach of institutionalism is more appropriate to understanding variance due to Ph. D. diploma area. Furthermore, this implies the complex diversity of the citation patterns between the hard and soft sciences, pointing us to the more qualified conclusion that rather than having to choose between institutionalism and constructivism according to a mutually exclusive either/or logic, these two approaches can in fact be mutually complementary, and these approaches should also be applied piecemeal to different levels of phenomena. In conclusion, this comparative research enables us to assert the following two claims: firstly that physics, as a 'science in society', produces knowledge dependent on social context, and secondly that it also possesses a characteristic that transcends locality from the view of a sociology of knowledge.

• Korean Journal of Mineralogy and Petrology
• /
• v.34 no.3
• /
• pp.157-167
• /
• 2021

Lead (Pb) is one of the key trace elements, exhibiting a peculiar partitioning behavior into silicate melts in contact with minerals. Partitioning behaviors of Pb between silicate mineral and melt have been known to depend on melt composition and thus, the atomic structures of corresponding silicate liquids. Despite the importance, detailed structural studies of Pb-bearing silicate melts are still lacking due to experimental difficulties. Here, we explored the effect of lead content on the atomic structures, particularly the evolution of silicate networks in Pb-bearing sodium metasilicate ([(PbO)_x(Na₂O)_1-x]·SiO₂) glasses as a model system for trace metal bearing natural silicate melts, using ²⁹Si solid-state nuclear magnetic resonance (NMR) spectroscopy. As the PbO content increases, the ²⁹Si peak widths increase, and the maximum peak positions shift from -76.2, -77.8, -80.3, -81.5, -84.6, to -87.7 ppm with increasing PbO contents of 0, 0.25, 0.5, 0.67, 0.86, and 1, respectively. The ²⁹Si MAS NMR spectra for the glasses were simulated with Gaussian functions for Qⁿ species (SiO₄ tetrahedra with n BOs) for providing quantitative resolution. The simulation results reveal the evolution of each Qⁿ species with varying PbO content. Na-endmember Na₂SiO₃ glass consists of predominant Q² species together with equal proportions of Q¹ and Q³. As Pb replaces Na, the fraction of Q² species tends to decrease, while those for Q¹ and Q³ species increase indicating an increase in disproportionation among Qⁿ species. Simulation results on the ²⁹Si NMR spectrum showed increases in structural disorder and chemical disorder as evidenced by an increase in disproportionation factor with an increase in average cation field strengths of the network modifying cations. Changes in the topological and configurational disorder of the model silicate melt by Pb imply an intrinsic origin of macroscopic properties such as element partitioning behavior.

• Korean Journal of Heritage: History & Science
• /
• v.54 no.1
• /
• pp.100-119
• /
• 2021

This paper has been written to verify the existing theory that districts occurred independently in various parts of the world, including the Korean Peninsula. Song Giho (2006) claims that the origin of the Gudle, is an example of polygenism that occurred in various areas in the world, including the Korean peninsula. This argument has been corroborated by a large number of researchers. However, it is difficult to understand the lineage of Gudle and its process of development, if a theory of polygenism is continued to be taken into account. The place which is targetet by this theory is the North-West area of the Korean peninsula, south of Primorsky Krai, and in the northern area of Zabaikal-Mongolia. This means that these areas developed independently because they were far from each other and had no direct cultural relationship. However, the structure of Gudle, shape, and assemblages of earthenware it cannot be explained by polygenism, as they are the same in every place. Furthermore, it is also questionable as to the timing and region of emergence of the culture in East Asia over a limited time frame of 3-2 BC. Gudle are formed by furnaces with roofs and walls, Gorae, which saves heat, and it has smoke ventilation that draws smoke out. Therefore, the Gudle is not a structure that anyone can make without advanced technical understanding. So far, the only facility with furnaces and smoke ventilation that appear before the Gudle is Buttumak. Thus, the Gudle is likely to have been invented in the place where Buttumak were used. The area as known for the origin of Gudle was observed to verify the existence of the Buttumak's structure, but none of these facilities were found. The Gudle suddenly appeared within a new culture that had never existed before. That means that none of the three places had the conditions under which the Gudle could be invented, so it must have been introduced from outside. In conclusion, the three places that I mentioned above are not the origin of Gudle. So, the origin of Gudle has to be found elsewhere.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.251-267
• /
• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.

• Journal of Food Hygiene and Safety
• /
• v.37 no.2
• /
• pp.46-54
• /
• 2022

Known for its effectiveness in weight loss and diabetes prevention, Gymnema sylvestre products can be found in the US, Japanese, and Indian markets. However, the recommended dosage or safety of these products has not yet been proven. Therefore, development of an analytical method for detecting the content of Gymnema sylvestre in food products is required. Accordingly, this study proposes an analysis method that can examine Gymnema sylvestre in food using LC-ESI-MS/MS and KASP (Kompetitive Allele-Specific PCR) markers. In LC-ESI-MS/MS, a simultaneous analysis method for gymnemic acid and deacylgymnemic acid was optimized using negative ionization mode, and its validation test was completed for solid and liquid samples. In addition, KASP markers were prepared by finding the specific SNP of G. sylvestre in ITS2 and matK through DNA barcodes. The two KASP markers returned positive FAM fluorescence result when combined with G. sylvestre, and this aspect was confirmed in raw G. sylvestre as well. The applicability of the method was tested on 21 different food and healthy functional products containing G. sylvestre purchased on the internet. As a result, although there was a difference in the ratios of gymnemic acid and deacylgymnemic acid in LC-ESI-MS/MS, the index component was detected in all 21 products samples. In the KASP analysis, 9 products returned positive FAM result, and the rest of the products were found to be containing G. sylvestre extract. This study is the first study to use the dual system of LC-ESI-MS/MS and KASP for the analysis of G. sylvestre. The study has confirmed that these two methods are applicable to the examine G. sylvestre content in food products.