• Tuberculosis and Respiratory Diseases
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• v.40 no.5
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• pp.575-583
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• 1993

Background: Mediastinal masses are not uncommon, and an overall incidence of one case per 100,000 population per year in individuals of all ages and with no difference in sex incidence may be a reasonable estimation. At least half of all mediastinal masses are asymptomatic and this proportion has increased in recent decades with wider use of screening chest roentgenography. Symptoms in patients with mediastinal mass lesions are usually due to compression or invasion of nearby intrathoracic structures. Most mediastinal mass lesions have characteristic predilectional locations. The basic focus of diagnostic evaluation is an orderly preparation for obtaining a tissue diagnosis but even lesions discovered to be benign must generally be removed. Seldom is this status known for certain preoperatively. In additaion, benign tumors may continue to enlarge, thus compromising vital organs; they may rupture, hemorrhage, become infected or have the possibility of various malignant degeneration. Therefore, all mediastinal masses must be surgically removed whether they are malignant or benign. Methods: We reviewed the medical records of 344 cases previously confirmed as mediastinal tumors or cysts from January, 1960 to August, 1992 and investigated the clinical findings. Results: Neurogenic tumors were the most common(24.7%) and thymomas were distinctively increased recently. Overall ratio between males and females was 1.1:1 and age distribution was relatively even among all age groups. Predilectional sites were posterior for neurogenic tumors, and anterior for teratodermoid tumors, thymomas and lymphomas. Dyspnea was the most common symptom in the patients of the mediastinal tumors and asymptomatic patients were 19.5%, Benign mediastinal mass lesions were 66.0% and malignant, 34.0%, Complete or partial resection was done in 42.4%. Conclusion: We could find the increasing incidence and the tendency of aggressive resection as possible in the mediastinal tumors. We expect the discovery of more mediastinal tumors with wider use of regular check-up and development of diagnostic methods.

• Journal of the Korea Concrete Institute
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• v.25 no.5
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• pp.485-496
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• 2013

In recent years, frequent terror or military attacks by explosion or impact accidents have occurred. Examplary case of these attacks were World Trade Center collapse and US Department of Defense Pentagon attack on Sept. 11 of 2001. These attacks of the civil infrastructure have induced numerous casualties and property damage, which raised public concerns and anxiety of potential terrorist attacks. However, a existing design procedure for civil infrastructures do not consider a protective design for extreme loading scenario. Also, the extreme loading researches of prestressed concrete (PSC) member, which widely used for nuclear containment vessel, gas tank, bridges, and tunnel, are insufficient due to experimental limitations of loading characteristics. To protect concrete structures against extreme loading such as explosion and impact with high strain rate, understanding of the effect, characteristic, and propagation mechanism of extreme loadings on structures is needed. Therefore, in this paper, to evaluate the impact resistance capacity and its protective performance of bi-directional unbonded prestressed concrete member, impact tests were carried out on $1400mm{\times}1000mm{\times}300mm$ for reinforced concrete (RC), prestressed concrete without rebar (PS), prestressed concrete with rebar (PSR, general PSC) specimens. According to test site conditions, impact tests were performed with 14 kN impactor with drop height of 10 m, 5 m, 4 m for preliminary tests and 3.5 m for main tests. Also, in this study, the procedure, layout, and measurement system of impact tests were established. The impact resistance capacity was measured using crack patterns, damage rates, measuring value such as displacement, acceleration, and residual structural strength. The results can be used as basic research references for related research areas, which include protective design and impact numerical simulation under impact loading.

• 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.

• The Journal of Korean Academy of Prosthodontics
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• v.43 no.4
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• pp.528-543
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• 2005

Statement of problem: Repeated delivery and removal of abutment cause some changes such as wear, scratch or defect of hexagonal structure. It may increase the value of rotational freedom(RF) between hexagonal structures. Purpose: The purpose of this study was to evaluate surface changes and rotational freedom between the external hexagon of the implant fixture and internal hexagon of abutment after repeated delivery and removal under SEM and toolmaker's microscope. Materials and methods: Implant systems used for this study were 3i and Avana. Seven pail's of implant fixture, abutment and abutment screws for each system were selected and all fixtures were perpendicularly mounted in liquid unsaturated polyesther with dental surveyor. Each one was embedded beneath the platform of fixture. Surfaces of hexagonal structure before repeated closing and opening of abutment were observed using SEM and rotational freedom was measured by using toolmaker's microscope. Each abutment was secured to the implant future by each abutment screw with recommended torque value using a digital torque controller and was repeatedly delivered and removed by 20 times respectively. After experiment, evaluation for the change of hexagonal structures and measurement of rotational freedom were performed. Result : The results were as follows; 1. Wear of contact area between implant fixture and abutment was considerable in both 3i and Avana system. Scratches and defects were frequently observed at the line-angle of hexagonal structures of implant fixture and abutment. 2. In the SEM view of the external hexagon of implant fixture, the point-angle areas at the corner edge of hexagon were severely worn out in both systems. It was more notable in the case of 3i systems than in that of Avana systems. 3. In the SEM view of the internal hexagon of abutment, Gingi-Hue abutment of 3i systems showed severe wear in micro-stop contacts that were machined into the corners to prevent rotation and cemented abutment of Avana systems showed wear in both surface area adjacent to the corner mating with external hexagon of implant fixture. 4 The mean values of rotational freedom between the external hexagon of the implant fixture and internal hexagon of abutment were 0.48$\pm$0.04$^{\circ}$ in pre-tested 3i systems and 1.18$\pm$0.25$^{\circ}$ after test, and 1.80$\pm$0.04$^{\circ}$ in pre-tested Avana systems and 2.61$\pm$0.16$^{\circ}$ after test. 5. Changes of rotational freedom after test shouted statistical)y a significant increase in both 3i and Avana systems(P<0.05, paired t-test). 6. Statistically, there was no significant difference between amount of increase in the rotational freedom of 3i systems and amount of increase in that of Avana ones(P>0.05, unpaired t-test). Conclusion: Conclusively, it was considered that repeated delivery and remove of abutment by 20 times would not have influence on screw joint stability. However, it caused statistically the significant change of rotational freedom in tested systems. Therefore, it is suggested that repeated delivery and remove of abutment should be minimal as possible as it could be and be done carefully Additionally, it is suggested that the means or treatment to prevent the wear of mating components should be devised.

• Sleep Medicine and Psychophysiology
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• v.18 no.1
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• pp.40-44
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• 2011

Narcolepsy is a sleep disorder, which is characterized by excessive daytime sleepiness (EDS) that is typically associated with cataplexy, sleep fragmentation and other REM sleep-related phenomenon such as sleep paralysis and hypnagogic hallucination. Narcoleptic symptoms can be developed from various medical or neurological disorders. A 17-year-old male patient admitted for the evaluation of EDS which started three-month ago. He slept more than 18 hours a day with cataplexy and hypnagogic hallucination. He was obese with body mass index (BMI) of 30.4 kg/$m^2$. After admission he was newly diagnosed to the thyrotoxicosis. T3 391.2 ng/dL (60-181), free T4 4.38 ng/dL (0.89-1.76), TSH <0.01 ${\mu}IU$/mL (0.35-5.5) were measured. His pulse rate ranged 70-90 beats per minute and blood pressure ranged 150/100-120/70 mmHg. Polysomnography revealed many fragmentations in sleep with many positional changes (81 times/h). Sleep onset latency was 33.5 min, sleep efficiency was 47.9%, and REM latency from sleep onset was delayed to 153.6 min. REM sleep percent was increased to 27.1%. Periodic limb movement index was 13.4/h. In the multiple sleep latency test (MSLT), average sleep latency was 0.4 min and there were noted 3 SOREMPs (Sleep Onset REM sleep period) on 5 trials. We couldn't discriminate the obvious sleep-wake pattern in the actigraph and his HLA DQB1 $^*0602$ type was negative. His thyroid function improved following treatment with methimazole and propranolol. Vital sign maintained within normal range. Cataplexy was controlled with venlafaxine 75 mg. Subjective night sleep continuity and PLMS were improved with clonazepam 0.5 mg, but the EDS were partially improved with modafinil 200-400 mg. Thyrotoxicosis might give confounding role when we were evaluating the EDS, though sleep fragmentation was one of the major symptoms of narcolepsy, but enormous amount of it made us think of the influence of thyroid hormone. The loss of sleep-wake cycle, limited improvement of EDS to the stimulant treatmen, and the cataplexy not supported by HLA DQB1 $^*0602$ should be answered further. We still should rule out idiopathic hypersomnia and measuring CSF hypocretin level would be helpful.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.6
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• pp.943-954
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• 2014

The purpose of this study was to gather basic data and measure job satisfaction and job engagement of dietitians and nutrition teachers in Chungbuk area. This study was conducted on 20 August, 2010. Out of 336 questionnaires, 266 were completed and made available for the purpose of statistical evaluation. As the main results, job satisfaction was classified into eight categories: task, wage, policies related to tasks, professional growth, promotion, relationships with colleagues, working environment, and supervision. In the case of wage, promotion, and policies related to tasks, the average scores of job satisfaction were around 2 points out of 5. Dietitians' job satisfaction levels according to employment type and school type significantly differed. In terms of job involvement and organizational commitment, average scores were 3.53 points and 3.12 points respectively. The survey showed significantly different results for job involvement and organizational commitment, depending on employment type, school type, and status as chef in charge or trainee. Dietitians working in elementary schools, as chef in charge, or with permanent employment showed higher job involvement and organizational commitment. Furthermore, there was a significantly positive correlation between factors such as task, wage, promotion, relationships with colleagues, supervision, work environment, policies related to tasks, professional growth, and job satisfaction.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.6
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• pp.13-24
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• 2017

The purpose of this study is to examine the effect of the management of receivables on the management performance of micro manufacturing industries. The results of the survey are as follows. First, among the factors of management of pre- and post-trade receivables in the micro manufacturing industries, management organization and regulations, contract execution management, bad debt control, which are the subordinate factors of credit control, are positive (+) significant effect on stability. In terms of profitability, management organizations and regulations, which are subordinate factors of credit control management, have a positive (+) significant effect on profitability. The recovery management, which is a factor of management of post - receivable receivables, did not have a significant effect on the stability and profitability of financial management performance. Second, the effect of financial performance on organizational satisfaction is positively related to stability, while profitability has no significant effect on organizational satisfaction. The implication of this study is that pre - trade receivables management is more important than post - trade receivables management in the management of accounts receivables of micro manufacturing industries. Proactive credit management refers to the procedure of establishing and managing personal guarantees and physical guarantees in order to smooth the execution of the obligations at the same time as the contract is concluded through processes such as credit investigation, analysis and evaluation, and sales decision before the contract is concluded. Post receivables management based on the assumption of default is a receivables management procedure from receipt of receivables that are already defaulted to bad debts to bad debt processing. If the collection of receivables is delayed or bad debt is increased, Furthermore, a corporation may be subject to bankruptcy risk (insolvency by paper profits). Therefore, it is meaningful that this study suggests direction to induce change of contract type in advance by understanding the possibility of settlement of accounts receivable and recovery of bad debts within the day of transition in case of contract of micro manufacturing industries.

• 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.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Progress in Medical Physics
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• v.24 no.3
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• pp.198-203
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• 2013

Generally, to evaluate gated radiation therapy, moving phantoms are used to simulate organ motion. Since the target moves in every direction, we need to take into account motion in each direction. This study proposes methods to evaluate gated radiation therapy using gamma index analysis and to visualize adequate gating window sizes according to motion ranges. The moving phantom was fabricated to simulate motion in the craniocaudal direction. This phantom consisted of a moving platform, the I'm MatriXX, and solid water phantoms. A 6 MV photon filed with a field size of $4{\times}4cm^2$ was delivered to the phantom using the gating system, while the phantom moved in the 1-, 2-, 3-, 4-, and 5-cm motion ranges. The gating windows were set at 40~60%, 30~40%, and 0~90%, respectively. The I'm MatriXX acquired the dose distributions for each scenario and the dose distributions were compared with a $4{\times}4cm^2$ static filed. The tolerance of the gamma index was set at 3%/3 mm. The greater the gating window, the lower the pass rate, and the greater the motion range, the lower the pass rate in this study. In case treatment without gated radiation therapy for the target with motion of 2 cm, the pass rate was less than 96%. But it was greater than 99% when gated radiation therapy was used. However gated radiation therapy was used for the target with motion greater than 4 cm, the pass rate could not be greater than 97% when gating window was set as 30~70%. But when the gating window set as 40~60%, the pass rate was greater than 99%.