• Title/Summary/Keyword: risk analysis and evaluation

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Clinical Manifestations and Characteristics in Patients with Horseshoe Kidney (소아 및 성인 마제신 환자들의 임상적 특징과 비교)

  • Kim, Yu Kyong;Kwon, Nam Hee;Kang, Dong Il;Chung, Woo Yeong
    • Childhood Kidney Diseases
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    • v.17 no.2
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    • pp.73-78
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    • 2013
  • Purpose: We aimed to investigate the clinical characteristics and associated diseases in children with a horseshoe kidney and compared these data between children and adults. Method: We performed a retrospective analysis of the medical records and radiological findings of 43 patients diagnosed with a horseshoe kidney in the Busan Paik Hospital. The subjects were divided into the children's group (14 cases, age <18 years) and the adult group (29 cases, age ${\geq}18$ years). Results: The study group consisted of 17 males and 26 females with a median age of 34 years. In the children's group (14 cases), 5 subjects were male and 9 were female, with a mean age of $6.7{\pm}6.2$ years. Most of the subjects were asymptomatic and were incidentally diagnosed with horseshoe kidney during their evaluation for another disease. Among the associated diseases in the children's group, Turner syndrome was the most common (5 cases), whereas ureteropelvic junction (UPJ) stricture was observed in 2 cases (14.2%). None of the children exhibited abnormal renal function during the follow-up period. In the adult group (29 cases), 12 subjects were male and 17 were female, with a mean age of 48 years. Eighteen patients were incidentally diagnosed with horseshoe kidney during their evaluation for another disease, and 11 patients had hematuria or abdominal pain due to renal stones. Among the associated diseases in the adult group, Turner syndrome was the most common (5 cases), and UPJ stricture was observed in 5 cases; the other accompanying diseases included hydronephrosis and overactive bladder. Six patients exhibited decreased renal function (serum creatinine level >1.5) during the follow-up period. Conclusion: Horseshoe kidney is usually diagnosed incidentally in both children and adults. In the present study, we noted that Turner syndrome was the most common associated disease in children. In addition, most children were asymptomatic but had a high risk of urologic complications after the transition to adulthood. Therefore, children with horseshoe kidney require continuous follow-up.

Analysis of Urinary Mass Screening for Second Grade of Elemantary School Children in Paju City (파주 지역 초등학교 2학년생에게 실시된 집단 뇨검사 분석)

  • Kim Sung Kee;Kim Young Kyoun;Park Yong Won;Lee Chong Guk
    • Childhood Kidney Diseases
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    • v.5 no.2
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    • pp.156-163
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    • 2001
  • Purpose We performed urinary mass screening(UMS) program for 2,804 children of second grade elemantary school 8 years of age in Paju city with cooperation of Paju City Health Center to determine the prevalence of asymptomatic proteinuria and hematuria, and to estimate the risk of incipient renal diseases. Also we attempted to evaluate the significance of hematuria in UMS in addidtion to proteinuria. Methods : 2,804 children of the 2nd grade of elementary school who lived in Paju city were included to our UMS program in 2000. They were constituted with 1,428 boys and 1,376 girls. The screening program was carried out in 3 steps The 1st screenig test was performed at schools and then students with abnormal results were examined repeatedly at Paju City Health Center and our hospital. Those students who showed proteinuria and/or hematuria in the 1st and 2nd test were referred to our hospital to undertake the 3rd close examination including physical examination, laboratory tests and radiologic tests. Results : (I) The prevalence of urinary abnormality in the 1st screening test was $8.3\%$(233 students), comprised of $5.9\%$ of boys, $10.8\%$ of girls. (2) Among 2,804 children tested in the first screening, prevalences of asymptomatic proteinuria and isolated hematuria were 64($2.3\%$), 163($5.8\%$) respectively, and the prevalence of proteinuria with hematuria was 6($0.2\%$). (3) Among 233 students with urinary abnormalities at the 1st screening test, 102 students applied to the 2nd test. 32 children, about one third of them, were also found to have abnormal urinary findings ; isolated hematuria 30, proteinuria with hematuria 2. (4) Those findings of clinical evaluation for children with isolated hematuria at the hospital showed as follows: idiopathic isolated microscopic hematuria 21, normal 6, urinary tract infection 1, idiopathic hypercalciuria 1 and simple renal cyst 1. Those 2 students with proteinuria and hematuria seemed to have chronic glomerulonephritis. Conclusion : (1) The clinical evaluation for children who showed positive results at the 1st screening test should be done judiciously. Because of high false positive rate, almost who showed positive results was normal, only a few of them had pathologic conditions. In this study, actual incidence of incipient renal diseases in children of 8 year old was calculated to be $0.4\%$. (2) The definite conclusion whether a urinary mass screening test can alter the prognosis of incipient renal diseases could not be drawn with this study. Further study must be necessary (3) We could acknowledge the significance of hematuria in UMS, but it is necessary that one should be judicious in managing and follow-up those that show abnormal results. (J Korean Soc Pediatr Nephrol 2001;5 : 156-63)

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Biological Toxicity Assessment of Sediment at an Ocean Dumping Site in Korea (폐기물 배출해역 퇴적물의 생물학적 독성평가 연구)

  • Seok, Hyeong Ju;Kim, Young Ryun;Kim, Tae Won;Hwang, Choul-Hee;Son, Min Ho;Choi, Ki-young;Kim, Chang-joon
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.1
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    • pp.1-9
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    • 2022
  • The effect of sediments in a waste dumping area on marine organisms was evaluated using sediment toxicity tests with a benthic amphipod (Monocorophium acherusicum) and bioluminescent bacterium (Vibrio fischeri) in accordance with the Korean Standard Method for Marine Wastes (KSMMW). Nine sites in the East Sea-Byeong, East Sea-Jeong, and Yellow Sea-Byeong areas were sampled from 2016 to 2019. The test results showed that the relative average survival rate (benthic amphipods) and relative luminescence inhibition rate (luminescent bacteria) were below 30%, which were judged to be "non-toxic." However, in the t-test, a total of 12 benthic amphipod samples (6, 1, 1, and 4 in 2016, 2017, 2018, and 2019, respectively) were significantly different (p<0.05) from the control samples. To identify the source of toxicity on benthic amphipods, a simple linear regression analysis was performed between the levels of eight heavy metals (Cr, As, Ni, Cd, Cu, Pb, Zn, and Hg) in sediments and the relative average survival rate. The results indicated that Cr had the highest contribution to the toxicity of benthic amphipods (p = 0.000, R2 = 0.355). In addition, Cr was detected at the highest concentration at the DB-85 station and exceeded the Marine Environment Standards every year. Although the sediments were determined as "not toxic" according to the ecotoxicity criteria of the KSMMW, the results of the statistical significance tests and toxicity identification evaluation indicated that the toxic effect was not acceptable. Therefore, revising the criteria for determining the toxic effect by deriving a reference value through quantitative risk assessment using species sensitivity distribution curves is necessary in the future.

A basic study on explosion pressure of hydrogen tank for hydrogen fueled vehicles in road tunnels (도로터널에서 수소 연료차 수소탱크 폭발시 폭발압력에 대한 기초적 연구)

  • Ryu, Ji-Oh;Ahn, Sang-Ho;Lee, Hu-Yeong
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.23 no.6
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    • pp.517-534
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    • 2021
  • Hydrogen fuel is emerging as an new energy source to replace fossil fuels in that it can solve environmental pollution problems and reduce energy imbalance and cost. Since hydrogen is eco-friendly but highly explosive, there is a high concern about fire and explosion accidents of hydrogen fueled vehicles. In particular, in semi-enclosed spaces such as tunnels, the risk is predicted to increase. Therefore, this study was conducted on the applicability of the equivalent TNT model and the numerical analysis method to evaluate the hydrogen explosion pressure in the tunnel. In comparison and review of the explosion pressure of 6 equivalent TNT models and Weyandt's experimental results, the Henrych equation was found to be the closest with a deviation of 13.6%. As a result of examining the effect of hydrogen tank capacity (52, 72, 156 L) and tunnel cross-section (40.5, 54, 72, 95 m2) on the explosion pressure using numerical analysis, the explosion pressure wave in the tunnel initially it propagates in a hemispherical shape as in open space. Furthermore, when it passes the certain distance it is transformed a plane wave and propagates at a very gradual decay rate. The Henrych equation agrees well with the numerical analysis results in the section where the explosion pressure is rapidly decreasing, but it is significantly underestimated after the explosion pressure wave is transformed into a plane wave. In case of same hydrogen tank capacity, an explosion pressure decreases as the tunnel cross-sectional area increases, and in case of the same cross-sectional area, the explosion pressure increases by about 2.5 times if the hydrogen tank capacity increases from 52 L to 156 L. As a result of the evaluation of the limiting distance affecting the human body, when a 52 L hydrogen tank explodes, the limiting distance to death was estimated to be about 3 m, and the limiting distance to serious injury was estimated to be 28.5~35.8 m.

Results of Postoperative Irradiation in Patients with Carcinoma of Uterine Cervix Stage IB and IIA (자궁경부암 IB와 IIA 환자의 수술후 방사선치료 결과)

  • Ahn Sung Ja;Nam Taek Keun;Chung Woong Ki;Nah Byung Sik;Choi Ho Sun;Byun Ji Soo
    • Radiation Oncology Journal
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    • v.13 no.1
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    • pp.41-48
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    • 1995
  • Purpose : The adjuvant postoperative radiotherapy has been usually applied to the patients with unfavorable prognostic factors after radical operation in early cervical cancer. We focused on the evaluation of the survival status and failure patterns of the patients with postoperative radiotherapy. Materials and Methods : We retrospectively analyzed ninety patients with FIGO stage IB and IIA cervix cancer who received postoperative pelvic irradiation at Chonnam University Hospital between August 1985 and December 1988, Seventy-eight patients had adequate follow-up information for survival analysis. Median follow-up time of these patients was 64 months. Results : The 5 year overall and disease free survival rate of ninety patients was $80.0\%$ and $80.2\%$, respectively. The prognostic significance to the survival was determined by multivariate analysis. Adequacy of resection margin(p=0.005) and lymph node status(p=0.005) appeared to be independent prognostic factors. Recurrence occurred in 13 patients, 5 in the pelvis and 8 at distant sites. The median time to recurrence was 19 months(range:3-39 months). The pelvic recurrence was more prevalent in the group of patients with adenocarcinoma, depth of stromal invasion more than 10mm and use of chemotherapy. The distant failure was more prevalent in the group of positive resection margin or positive lymph node with statistical significance. Conclusion : Patients with pelvic lymph node or surgical margin involvement clearly constitute a high risk group in this analysis and should be considered as candidates for some form of adjuvant therapy.

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Usefulness of Data Mining in Criminal Investigation (데이터 마이닝의 범죄수사 적용 가능성)

  • Kim, Joon-Woo;Sohn, Joong-Kweon;Lee, Sang-Han
    • Journal of forensic and investigative science
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    • v.1 no.2
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    • pp.5-19
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    • 2006
  • Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

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Recent Progress in Air-Conditioning and Refrigeration Research : A Review of Papers Published in the Korean Journal of Air-Conditioning and Refrigeration Engineering in 2013 (설비공학 분야의 최근 연구 동향 : 2013년 학회지 논문에 대한 종합적 고찰)

  • Lee, Dae-Young;Kim, Sa Ryang;Kim, Hyun-Jung;Kim, Dong-Seon;Park, Jun-Seok;Ihm, Pyeong Chan
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.26 no.12
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    • pp.605-619
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    • 2014
  • This article reviews the papers published in the Korean Journal of Air-Conditioning and Refrigeration Engineering during 2013. It is intended to understand the status of current research in the areas of heating, cooling, ventilation, sanitation, and indoor environments of buildings and plant facilities. Conclusions are as follows. (1) The research works on the thermal and fluid engineering have been reviewed as groups of fluid machinery, pipes and relative parts including orifices, dampers and ducts, fuel cells and power plants, cooling and air-conditioning, heat and mass transfer, two phase flow, and the flow around buildings and structures. Research issues dealing with home appliances, flows around buildings, nuclear power plant, and manufacturing processes are newly added in thermal and fluid engineering research area. (2) Research works on heat transfer area have been reviewed in the categories of heat transfer characteristics, pool boiling and condensing heat transfer and industrial heat exchangers. Researches on heat transfer characteristics included the results for general analytical model for desiccant wheels, the effects of water absorption on the thermal conductivity of insulation materials, thermal properties of Octadecane/xGnP shape-stabilized phase change materials and $CO_2$ and $CO_2$-Hydrate mixture, effect of ground source heat pump system, the heat flux meter location for the performance test of a refrigerator vacuum insulation panel, a parallel flow evaporator for a heat pump dryer, the condensation risk assessment of vacuum multi-layer glass and triple glass, optimization of a forced convection type PCM refrigeration module, surface temperature sensor using fluorescent nanoporous thin film. In the area of pool boiling and condensing heat transfer, researches on ammonia inside horizontal smooth small tube, R1234yf on various enhanced surfaces, HFC32/HFC152a on a plain surface, spray cooling up to critical heat flux on a low-fin enhanced surface were actively carried out. In the area of industrial heat exchangers, researches on a fin tube type adsorber, the mass-transfer kinetics of a fin-tube-type adsorption bed, fin-and-tube heat exchangers having sine wave fins and oval tubes, louvered fin heat exchanger were performed. (3) In the field of refrigeration, studies are categorized into three groups namely refrigeration cycle, refrigerant and modeling and control. In the category of refrigeration cycle, studies were focused on the enhancement or optimization of experimental or commercial systems including a R410a VRF(Various Refrigerant Flow) heat pump, a R134a 2-stage screw heat pump and a R134a double-heat source automotive air-conditioner system. In the category of refrigerant, studies were carried out for the application of alternative refrigerants or refrigeration technologies including $CO_2$ water heaters, a R1234yf automotive air-conditioner, a R436b water cooler and a thermoelectric refrigerator. In the category of modeling and control, theoretical and experimental studies were carried out to predict the performance of various thermal and control systems including the long-term energy analysis of a geo-thermal heat pump system coupled to cast-in-place energy piles, the dynamic simulation of a water heater-coupled hybrid heat pump and the numerical simulation of an integral optimum regulating controller for a system heat pump. (4) In building mechanical system research fields, twenty one studies were conducted to achieve effective design of the mechanical systems, and also to maximize the energy efficiency of buildings. The topics of the studies included heating and cooling, HVAC system, ventilation, and renewable energies in the buildings. Proposed designs, performance tests using numerical methods and experiments provide useful information and key data which can improve the energy efficiency of the buildings. (5) The field of architectural environment is mostly focused on indoor environment and building energy. The main researches of indoor environment are related to infiltration, ventilation, leak flow and airtightness performance in residential building. The subjects of building energy are worked on energy saving, operation method and optimum operation of building energy systems. The remained studies are related to the special facility such as cleanroom, internet data center and biosafety laboratory. water supply and drain system, defining standard input variables of BIM (Building Information Modeling) for facility management system, estimating capability and providing operation guidelines of subway station as shelter for refuge and evaluation of pollutant emissions from furniture-like products.

Performance of Investment Strategy using Investor-specific Transaction Information and Machine Learning (투자자별 거래정보와 머신러닝을 활용한 투자전략의 성과)

  • Kim, Kyung Mock;Kim, Sun Woong;Choi, Heung Sik
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.65-82
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    • 2021
  • Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

Victims of Bullying among Korean Adolescents: Prevalence and Association with Psychopathology Evaluated Using the Adolescent Mental Health and Problem Behavior Screening Questionnaire-II Standardization Study Data (청소년정서행동발달검사 표준화연구 자료를 활용한 학교폭력 피해 전국유병률 및 관련요인 조사)

  • Bhang, Soo-Young;Yoo, Han-Ik K.;Kim, Ji-Hoon;Kim, Bong-Seog;Lee, Young-Sik;Ahn, Dong-Hyun;Suh, Dong-Su;Cho, Soo-Churl;Hwang, Jun-Won;Bahn, Geon-Ho
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.23 no.1
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    • pp.23-30
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    • 2012
  • Objectives : This study was conducted to investigate the prevalence of victims of bullying and the demographic characteristics of victims, and their related psychopathology, in a Korean nationwide sample of youths in middle and high school over a one month period. Methods : During the autumn of 2009, students in the 7th to 12th grades at 23 secondary schools participated in a nationwide, cross-sectional study. The study subjects completed the Adolescent Mental Health and Problem Behavior Screening Questionnaire-II (AMPQ-II) and Symptom Checklist-90-Revision (SCL-90-R). Based on the data acquired, descriptive statistics, correlation coefficients and multiple logistic regression analysis were performed. Results : Among the 3364 participants, 2272 (67.54%) completed the questionnaire. The prevalence of victimization was 28.9%. Male gender was positively associated with victimization, and grade level was negatively related to victimization. The AMPQ-II bullying score (Factor 4) was significantly (p<.001) and positively correlated to the AMPQ-II student total score (r= 0.50), Worry and thought (Factor 1 ; r=0.38), Mood and suicide (Factor 2 ; r=0.31), Academic and Internet-related problems (Factor 3 ; r=0.24), Rule violations (Factor 5 ; r=0.23), and AMPQ-II teacher total score (r=0.11). Somatization (r=0.23), Obsessive-compulsive behavior (r=0.24), Interpersonal sensitivity (r=0.30), Depression (r=0.33), Anxiety (r=0.26), Hostility (r=0.30), Phobic anxiety (r=0.22), Paranoid ideation (r=0.36), and Psychoticism (r=0.31) results from the SCL-90-R were also found to be positively related to the AMPQ-II bullying score, and remained significant after adjusting for age and gender. A total of 26% of the victims reported suicidal ideations as compared to 9% of non-victims over the month prior to the evaluation ($x^2$=119.595, df=1, p<.001). The multiple logistic regression analysis indicated that the AMPQ-II bullying score significantly increased the risk of suicidal ideation [Exp(b)=1.55, df=1, p<.001] after adjusting for age and gender. Conclusion : School bullying was highly prevalent among Korean middle and high school students. This study provided strong evidence that suicidal ideation and psychopathology were serious problems among the victims of bullying.

The Prediction of DEA based Efficiency Rating for Venture Business Using Multi-class SVM (다분류 SVM을 이용한 DEA기반 벤처기업 효율성등급 예측모형)

  • Park, Ji-Young;Hong, Tae-Ho
    • Asia pacific journal of information systems
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    • v.19 no.2
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    • pp.139-155
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    • 2009
  • For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.