• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Korean Journal of Soil Science and Fertilizer
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• v.11 no.4
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• pp.213-233
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• 1979

It is generally agreed that the country's population will grow up to the level of 52 million by the year of 2000 and that due the active growth of industry, urbanization and road constructions, sizable portion of existing arable lands will be utilized for other purposes than agriculture in near future. From 1966 to 1977, it was estimated that, the average annual conversion of arable lands to other uses, was 12,909 ha. If this trend persists, it is predicted that from 1978 to 1991 when the 6th Five Years Economic Development Plan will terminate, approximately 181,000 ha of arable lands will be converted for other uses again. On the other hand, it is certain that the increased population (39 million in 1981, 45 million in 1991, 52 million in 2001) and the changes in food pattern along with the enhancement of living standards will bring about the phenomenal increase in demands for not only the staple food but also the livestock products such as meat, milk and eggs, vegetables and fruits. These future increased demands for various foods, naturally mean the increased needs for the expansion of arable lands at the same time. It is predicted that, if more activities than present scale are not taken for the expansion of arable lands, the national food self sufficiency level will drop from 79% in 1977 down to 62% in 1991. To meet the increased food demands in future, there are several ways and means. These will include the increased land use intensity, elevation of unit area yield levels, minimization of conversion of arable lands to other uses and expansion of arable lands through the reclamations of idle hillside lands and tidal lands. Among these, the expansion of arable lands through reclamations of idle hillside lands and tidal lands are more positive measures to cope with the increased production of foods in future. The reclamation of hillside lands demands more attention because it needs more advanced technologies in agronomical and engineering aspects, larger scale fundings and integrated socioeconomic considerations. In agromical aspects, the thechniques for early improvement of chemical and physical properties of soils, proper soil conservation measures and rational cropping systems are of particular importance. As to the financial supports to encourage the farmings in hillside land, much bold fund inputs are essential for the construction of roads, installation of irrigation and drainage facilities, soil conservation mechanisms, which will ensure the stabilized farming with reasonable incomes in the newly reclaimed lands.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.2
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• pp.278-284
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• 2011

To obtain optimum configuration method and livestock wastewater loading in small-scale livestock wastewater apparatus by natural purification method for treating livestock wastewater, the small-scale livestock wastewater apparatuses were constructed with 9 kinds of combined systems such as aerobic bed (ae)-anaerobic bed (an), ae-ae, ae-anoxic bed (ox), an-an, an-ae, an-ox, ox-ae, ox-an and ox-ox livestock wastewater treatment apparatuses. Under different configuration methods, the removal rate of COD in Ae-Ae and Ae-An livestock wastewater treatment apparatus was higher than that in other configuration methods. The removal rate of T-N in Ae-An livestock wastewater treatment apparatus was higher than that in other configuration methods. Removal rates of SS and T-P were not different regardless of configureation methods in small-scale livestock wastewater treatment apparatus. Under different livestock wastewater loading, the removal rates of pollutants were higher in the order of $50L\;m^{-2}\;day^{-1}{\fallingdotseq}100L\;m^{-2}\;day^{-1}\;>\;200L\;m^{-2}\;day^{-1}$. Therefore, optimum configuration method was Ae-An livestock wastewater treatment apparatus, and optimum livestock wastewater loding was $100L\;m^{-2}\;day^{-1}$ in small-scale livestock wastewater treatment apparatus.

• Radiation Oncology Journal
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• v.21 no.4
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• pp.291-298
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• 2003

Purpose: We report upon a web-based system for Patterns of Care Study (PCS) devised for Korean radiation oncology. This PCS was designed to establish standard tools for clinical quality assurance, to determine basic parameters for radiation oncology processes, to offer a solid system for cooperative clinical studies and a useful standard database for comparisons with other national databases. Materials and Methods: The system consisted of a main server with two back-ups in other locations. The program uses a Linux operating system and a MySQL database. Cancers with high frequencies in radiotherapy departments in Korea from 1998 to 1999 were chosen to have a developmental priority. Results: The web-based clinical PCS .system for radiotherapy in www.pcs.re.kr was developed in early 2003 for cancers of the breast, rectum, esophagus, larynx and lung, and for brain metastasis. The total number of PCS study items exceeded one thousand. Our PCS system features user-friendliness, double entry checking, data security, encryption, hard disc mirroring, double back-up, and statistical analysis. Alphanumeric data can be input as well as image data. In addition, programs were constructed for IRB submission, random sampling of data, and departmental structure. Conclusion: For the first time in the field of PCS, we have developed a web-based system and associated working programs. With this system, we can gather sample data in a short period and thus save, cost, effort and time. Data audits should be peformed to validate input data. We propose that this system should be considered as a standard method for PCS or similar types of data collection systems.

• Journal of Korean Academy of Nursing
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• v.28 no.4
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• pp.1047-1059
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• 1998

Senile Dementia is one of the dispositional mental disorder which has been known to the world since Hippocratic age. It has become a wide-spread social problem all over the world because of chronic disease processes and the demands of dependent care for several years as well as improbability of treatment of it at the causal level. Essentially, life styles of the older generation differ from those of the younger generation. While the fomer is used to the patriarchal system and the spirit of filial piet and respect, the latter is pragmatized and individualized under the effects of the Western material civilization. These differences between the two generations cause conflict between family members. In particular, the pain and conflict of care-givers who take care of a totally dependent dementia patient not only is inciting to the collapse of the family union, but is expanding into a serious social problem. According to this practical difficulty, this study has tried to compare dementia care-givers' experiences inter-culturally and to help set up more proper nursing interventions, describing and explaining them through ethnographies by participant observation and in-depth interviews that enable seeing them in a more close, honest and certain way. It also tries to provide a theoetical model of nusing care for dementia patients which is proper to Korean culture. This study is composed of 12 participants (4 males, 8 females) whose ages range from 37-71 years. The relations of patients are 5 spouses(3 husbands, 2 wives), 4 daughters-in-law, 2 daughters, and 1 son-in-law. The following are the care-givers' meaning of experiences that results of the study shows. The first is "psychological conflict". It contains the minds of getting angry, reproaching, being driven to dispair, blaming oneself, giving up lives, and being afraid, hopeless, and resigned. The second is "physical, social and psychological pressure" . At this stage, care-givers are shown to be under stress of both body and soul for the lack of freedom and tiredness. They also feel constraint because they hardly cope with the care and live through others' eyes. The third is "isolation". It makes the relationship of patient care-giver to be estranged, without understanding each other. They, also, experience indifference such as being upset and left alone. The forth is "acceptance" They gradually have compassion, bear up and then adapt themselves to the circumstances they are in. The fifth is "love". Now they learn to reward the other with love. It is also shown that this stage contains the process of winning others' recognition. The final is "hope". In this stage they really want situations to go smoothly and hope everything will be O.K. These consequences enable us to summarize the principles of cue experience such as, in the early stage, negative response such as physical·psychological confusion, pain and conflict are primary. Then the stage of acceptance emerges. It is an initial positive response phase when care-givers may admit their situations. As time passes by a positive response stage emerges. At last they have love and hope. Three stages we noted above : however, there are never consistent situations. Rather it gradually comes into the stage of acceptance, repeating continuous conflict, pressure and isolation. If any interest and understanding of families or the support of surrounding society lack, it will again be converted to negative responses sooner or later. Otherwise, positive responses like hope and love can be encouraged if the family and the surroundings give active aids and understanding. After all, the principles of dementia care experiences neither stay at any stage, nor develop from negative stages to positive stages steadily. They are cycling systems in which negative responses and positive responses are constantly being converted. I would like to suggest the following based on the above conclusions : First, the systematic and planned education of dementia should be performed in order to enhance public relations. Second, a special medical treatment center which deals with dementia, under government's charge, should be managed. Third, the various studies approaching dementia care experiences result in the development of more reasonable and useful nursing guidelines.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.176-188
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• 2018

Modern urban problems are increasingly becoming a market mix that can not be solved by the power of a single department and the necessity of establishing a cooperation system based on data communication between departments is increasing. Therefore, this study analyzed Busan metropolitan city's IT projects from 2014 to 2018 in order to understand the utilization and sharing status of departmental data from the viewpoint that cooperation between departments can start from the sharing of data with high common utilization. In addition, based on the results of the FGI(Focus Group Interview) conducted for the officials of the department responsible for the informatization project, we verified the results of data status analysis. At the same time, we figured out the necessity of data link between departments through SNA(Social Network Analysis) and presented data that should be shared first in the future. As a result, most of the information systems currently use limited data only within the department that produced the data. Most of the linked data was concentrated in the information department. Therefore, this study suggested the following solutions. First, in order to prevent overlapping investments caused by the operation of individual departments and share information, it is necessary to build a small platform to tie the departments, which have high connectivity with each other, into small blocks. Second, a local level process is needed to develop data standards as an extension of national standards in order to expand the information to be used in various fields. Third, as another solution, we proposed a system that can integrate various types of information based on address and location information through application of cloud-based GIS platform. The results of this study are expected to contribute to build a cooperation system between departments through expansion of information sharing with cost reduction.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.122-130
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• 2013

This work proposes a 12b 100MS/s 45nm CMOS four-step pipeline ADC for high-speed digital communication systems requiring high resolution, low power, and small size. The input SHA employs a gate-bootstrapping circuit to sample wide-band input signals with an accuracy of 12 bits or more. The input SHA and MDACs adopt two-stage op-amps with a gain-boosting technique to achieve the required DC gain and high signal swing range. In addition, cascode and Miller frequency-compensation techniques are selectively used for wide bandwidth and stable signal settling. The cascode current mirror minimizes current mismatch by channel length modulation and supply variation. The finger width of current mirrors and amplifiers is laid out in the same size to reduce device mismatch. The proposed supply- and temperature-insensitive current and voltage references are implemented on chip with optional off-chip reference voltages for various system applications. The prototype ADC in a 45nm CMOS demonstrates the measured DNL and INL within 0.88LSB and 1.46LSB, respectively. The ADC shows a maximum SNDR of 61.0dB and a maximum SFDR of 74.9dB at 100MS/s, respectively. The ADC with an active die area of $0.43mm^2$ consumes 29.8mW at 100MS/s and a 1.1V supply.

• Proceedings of the Korean Environmental Health Society Conference
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• 2003.06a
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• pp.24-25
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• 2003

Lead is ubiquitous in the human environment as a result of industrialization. China's rapid industrialization and traffic growth have increased the potential for lead emissions. Lead poisoning in children is one of the most common public health problems today, and it is entirely preventable. Children are more vulnerable to lead pollution and lead in their bodies can affect their nervous, circulatory, and digestive systems. Children are exposed to lead from different sources (such as paint, gasoline, and solder) and through different pathways (such as air, food, water, dust, and soil). Although all children are exposed to some lead from food, air, dust, and soil, some children are exposed to high dose sources of lead. Significant sources of lead for China's children include industrial emissions (often close to housing and schools), leaded gasoline, and occupational exposure that occurs when parents wear lead-contaminated clothing home from work, burning of coal for home heat and cooking, contaminated food, and some traditional medicines. To assess the blood lead level in children in China, a large-scale study was conducted in 19 cities among 9 provinces during 1997 to 2000. There were 6502 children, aged 3-5 years, were recruited in the study The result indicates that the mean blood lead level was 8.83ug/dl 3-5 year old living in city area. The mean blood lead level of boys was higher than that of girls (9.1l ug/dl vs 8.73ug/dl). Almost 30 percent childrens blood lead level exceeded 10ug/dl. The average blood lead level was higher than that of in 1985 (8.83ug/dl vs 8.lug/dl). An epidemiological study was carried on the children living around the cottage industries recycling the lead from battery. Nine hundreds fifty nine children, aged 5-12 years, living in lead polluted villages where the lead smelters located near the residential area and 207 control children live in unpolluted area were recruited in the study. The lead levels in air, soil, drinking water and crops were measured. The blood lead and ZnPP level were tested for all subjects. The results show that the local environment was polluted. The lead levels both in the air and crops were much higher than that of in control area. In the polluted area, the average blood level was 49.6ug/dl (rang 19.5-89.3ug/dl). Whereas, in the unpolluted area, the average blood level was 12.4ug/dl (rang 4.6-24.8ug/dl). This study indicates that in some countryside area, some cottage industries induce seriously lead pollution and cause children health problem. For the introducing of unleaded gasoline in some large cities, such as Beijing and Shanghai, the blood lead level showed a declined trend since 1997. By 2000, the use of leaded gasoline in motor vehicles has been prohibited in China. The most recent data available show that levels of lead in blood among children in Shanghai decreased from 8.3ug/dl in 1997 to 7.6ug/dl in 1999. The prevalence rate of children lead poisoning (blood lead >10ug/dl) was also decreased from 37.8% to 24.8%. In children living in downtown area, the blood lead level reduced dramatically. To explore the relationship between gene polymorphisms and individual susceptibility of lead poisoning, a molecular epidemiological study was conducted among children living in lead polluted environment. The result showed that the subjects with ALAD2 allele has higher ZPP level, and the subjects with VDR B allele has larger head circumference than only with b allele. In the present study, we demonstrated that ALAD genotypes modify lead effects on heme metabolism and VDR gene variants influence the skull development in highly exposed children. The polymorphism of ALAD and VDR genes might be the molecular inherited factor modifying the susceptibility of lead poisoning. Recently, Chinese government pays more attention to lead pollution and lead poisoning in children problem. The leaded gasoline was prohibited used in motor vehicles since 2000. The government has decided to have a clampdown on the high-polluted lead smelters for recycling the lead from battery in countryside. It is hopeful that the risk of lead poisoning in children will be decreased in the further

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.