• The Korean Journal of Elementary Counseling
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• v.8 no.1
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• pp.33-50
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• 2009

The purpose of this study was to develop a PBL-based career education program and to examine its effectiveness on school children's career maturity. It's specifically meant to prepare a career education program to assist students to get an accurate grip on their aptitude, interest and personality and explore various sorts of occupations in the course of solving authentic and contextual career-related problems. After children's developmental characteristics and needs were analyzed, task analysis was implemented, and the objectives were defined. And then the core of the program, PBL problems were developed, and the validity of the problems were verified Evaluation plans and tools were prepared to assess children's problem-solving process and presentation, and an online learning space was designed. The program that consisted of 10-minute 21 sessions was provided to fifth-grade elementary schoolers for eight weeks. The findings of the study were as follows: The experimental group that participated in the PBL-based career education program showed a more significant improvement than the control group that didn't in career attitude and three career attitude subfactors involving planness, disposition and compromise. And the former made a more significant progress than the latter in career ability and its subfactors including vocational comprehension, self-understanding and decision-making skills as well. As a result of making a content analysis to make up for the survey, the students reported that they were able to get an objective understanding of themselves and acquire diverse and profound knowledge on work and the business world in the middle of solving the given PBL problems related to different areas in group and giving a presentation. In conclusion, a PBL based career education program developed by this researcher encouraged the students to have an objective self-understanding, to have a dynamic interactive discussion with their group members. Therefore the program had a positive impact on boosting the career attitude and career ability of the elementary schoolers. The findings suggested that in the field of elementary career education, autonomous learning attitude and subjecthood are the crucial factors to stimulate school children to explore and create their own future.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.191-204
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• 2010

Recently, the CO2 emission and energy consumption have become critical global issues to decide the future of nations. Especially, the spread of IT products and the increased use of internet and web applications result in the energy consumption and CO2 emission of IT industry though information technologies drive global economic growth. EU, the United States, Japan and other developed countries are using IT related environmental regulations such as WEEE(Waste Electrical and Electronic Equipment), RoHS(Restriction of the use of Certain Hazardous Substance), REACH(Registration, Evaluation, Authorization and Restriction of CHemicals) and EuP(Energy using Product), and have established systematic green business/IT strategies to enhance the competitiveness of IT industry. For example, the Japan government proposed the "Green IT initiative" for being compatible with economic growth and environmental protection. Not only energy saving technologies but energy saving systems have been developed for accomplishing sustainable development. Korea's CO2 emission and energy consumption continuously have grown at comparatively high rates. They are related to its industrial structure depending on high energy-consuming industries such as iron and steel Industry, automotive industry, shipbuilding industry, semiconductor industry, and so on. In particular, export proportion of IT manufacturing is quite high in Korea. For example, the global market share of the semiconductor such as DRAM was about 80% in 2008. Accordingly, Korea needs to establish a systematic strategy to respond to the global environmental regulations and to maintain competitiveness in the IT industry. However, green competitiveness of Korea ranked 11th among 15 major countries and R&D budget for green technology is not large enough to develop energy-saving technologies for infrastructure and value chain of low-carbon society though that grows at high rates. Moreover, there are no concrete action plans in Korea. This research aims to deduce the priorities of the Korean green business/IT strategies to use multi attribute weighted average method. We selected a panel of 19 experts who work at the green business related firms such as HP, IBM, Fujitsu and so on, and selected six assessment indices such as the urgency of the technology development, the technology gap between Korea and the developed countries, the effect of import substitution, the spillover effect of technology, the market growth, and the export potential of the package or stand-alone products by existing literature review. We submitted questionnaires at approximately weekly intervals to them for priorities of the green business/IT strategies. The strategies broadly classify as follows. The first strategy which consists of the green business/IT policy and standardization, process and performance management and IT industry and legislative alignment relates to government's role in the green economy. The second strategy relates to IT to support environment sustainability such as the travel and ways of working management, printer output and recycling, intelligent building, printer rationalization and collaboration and connectivity. The last strategy relates to green IT systems, services and usage such as the data center consolidation and energy management, hardware recycle decommission, server and storage virtualization, device power management, and service supplier management. All the questionnaires were assessed via a five-point Likert scale ranging from "very little" to "very large." Our findings show that the IT to support environment sustainability is prior to the other strategies. In detail, the green business /IT policy and standardization is the most important in the government's role. The strategies of intelligent building and the travel and ways of working management are prior to the others for supporting environment sustainability. Finally, the strategies for the data center consolidation and energy management and server and storage virtualization have the huge influence for green IT systems, services and usage This research results the following implications. The amount of energy consumption and CO2 emissions of IT equipment including electrical business equipment will need to be clearly indicated in order to manage the effect of green business/IT strategy. And it is necessary to develop tools that measure the performance of green business/IT by each step. Additionally, intelligent building could grow up in energy-saving, growth of low carbon and related industries together. It is necessary to expand the affect of virtualization though adjusting and controlling the relationship between the management teams.

• The Journal of Korean Society for School & Community Health Education
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• v.5
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• pp.25-42
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• 2004

This study set out to investigate the relations between middle school students' perception of body image and their allowance for plastic surgery, to understand their perception of body image and desire for plastic surgery, and provide some data needed to warn against reckless plastic surgery and guide the students effectively. For those purposes, an examination was conducted of the relationships between the individual characteristics and perception levels of body image, the individual characteristics and allowance for plastic surgery, and perception levels of body image and allowance for plastic surgery. The subjects were drawn from sour middle schools located in two regions of Gyeonggi Province. Total 922 boys and girls were surveyed on a questionnaire, which was developed based on the pretest of previous literature, reviewed for appropriateness, and tested for reliability and reasonableness. The body image on the five scale was greater as the perception level was higher. The allowance for plastic surgery was also greater as the scores were more. The findings were as follows: First, the relationships between individual characteristics and perception levels of body image were examined. The third graders showed the highest perception level, being followed by the first and second graders. The girls were more perceptive than the boys, and those who were extrovert were more perceptive than those who were introvert. Those students whose parents earned 2 million won or more a month and who adapted themselves to the environmental changes had a higher perception level. In a word, the girls from the middle class that were well adapted, felt happy, and were extrovert had a higher perception level of body image. Second, the connections between individual characteristics and allowance for plastic surgery were investigated. The third graders were the most admissive of plastic surgery, followed by the second and first graders. That is, the upper graders were more admissive of plastic surgery. In addition, the girls were more admissive than the boys, and those who were extrovert were more than those who were introvert. There were no significant differences according to the monthly income of the parents, grades, adaptability to surroundings, and happiness, which results almost resembled the findings of a study conducted on adults. Third, there were negative correlations found between the perception levels of body image and the allowance for plastic surgery. To elaborate, the higher the perception levels were, the lower the allowance was, and vice versa. As for the items, the subjects showed more allowance for plastic surgery when they scored less in the item of caring about appearance, importance of looking pretty to others, and efforts to improve appearance. When they had a low value of body and easily felt tired, they were highly acceptive of plastic surgery. The allowance for plastic surgery was also great when their perception was much of how healthy they felt, how important they felt about their bodies, how they were satisfied with their current appearances, how they evaluated the appearance of others, how much they were satisfied physically, and how much demanding they were for physical changes. Meanwhile, there were no correlations between the allowance and physical attraction, the degree for one's activities to be hindered, and sickness. In short, the demand for plastic surgery was 41% for the girls and 20.2% for the boys. Just as the study on adults reported, those who had a low or negative perception of body image were more acceptive of plastic surgery. The middle school students were generally positive about their bodies with the lowest perception level at 2.91 and the highest at 3.21. Their individual allowance for plastic surgery was related to their individual body images, which were in turn affected by the mass communication, surrounding environments, and social values. Thus it's necessary for the entire society to try to improve or change the overall perception. Helping measures should be taken so that the students can form right sense of values about their bodies, avoid the obsession with appearance and appearance-based evaluation, and exercise righteous criteria against humans beings and things. In conclusions, the following suggestions were made: they need to develop such questionnaires or tools as can measure the body image of teens and fit the reality. Moreover, body image improvement programs should be more diverse and more applicable to teens. Despite the consistent reports that prove the correlations between body image and plastic surgery, there has been little effort to apply such factors as experience of the life of the disabled, volunteer activities for the disabled and at the hospitals, and others that can induce changes to body image to the body image improvement programs. In the future, comparative research should be carried out on body image and plastic surgery.

• Journal of agricultural medicine and community health
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• v.16 no.1
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• pp.48-60
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• 1991

In a seroepidemiological study in several areas of Korea, the ELISA technique was performed to determine prevalence of some important helminthic diseases in our nation during March $15^{th}$ to June $30^{th}$. 1991. In this survey the serum antibody positive rates of anisakiasis, toxocariasis, clonorchiasis, paragonimiasis, cysticercosis, and sparganosis were measured. Among, 6,704 cases examined, 19.7% showed positive antibody titer at least one of the six items studied. Overall positive antibody rate was 8.1% in anisakiasis, 5.6% in toxocariasis, 3.6% in clonorchiasis, 1.7% in paragonimiasis, 4.5% in cysticercosis, and 2.6% in sparganosis respectively. In Pusan port southeastern part of Korea, antibody positive rate of anisakiasis was 2.9%, and clonorchiasis was 2.8% among 450 examine. In TaeJ$\check{o}$n city, central part of Korea. toxocariasis(6.7%) and anisakiasis(3.7%) showed high serologic positive rate. Of the 875 persons in Chunche$\check{o}$n gun(=province), northern central rural area of South Korea, anisakiasis was revealed as 3.4% seropositivity. In Tonghae port, eastern coast of South Korea. 9.9% of population examined showed positive antibody titer in anisakiasis. Of the 1,122 persons examined in Southern part of Cholla-Namdo(Southwestern coastal area of Korea), anisakiasis was 16.9%, cysticerocosis was 12.7% and the paragonimiasis was 3.3% respectively. In some localized area of Cholla-Pukdo, anisakiasis was 9.3% and cysticekosis was 4.3% among 702 cases examined. In some localized area of Kyungsang-Pukdo, anisakiasis was 10.6%. and toxocariasis was 16.1% among 900 cases examined. And finally, in Cheju-do, southern island of Korea, anisakiasis showed high positive rate(6.7%). Because cross reactions between related helminth group may disturb the analysis of these data, use of further developed techniques such as EITB(enzyme-linked immunoelectrotransfer blot) was considered as a essential tools for the study. We thought that probably most of the positive cases of cysticerosis were taeniasis cases. We can't rule out taeniasis even though EITB was employed as far as crude worm extract or cystic fluid of cysticercus was used as antigen. It was well Known that toxocariasis and anisakiasis also showed cross reactivity. However, the data presented here focus on seropositive rate of several helminthic diseases in Korea, not true prevalence rate of helminthiases, and to wait for more expensive purified antigen in sufficient amount for epidemiologic use is not necessary because increased immunologic sensitivity had little effect on epidemiologic sensitivity. We, here, suggest that ELISA should be applied as soon as possible to the evaluation of prevalence of tissue invading parasitic diseases, and a review of the antibody positive rate obtained in this study would be a basic data for controlling program of parasitic diseases in Korea.

• 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.

• 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.

• Journal of Nutrition and Health
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• v.42 no.2
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• pp.119-127
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• 2009

Malnutrition of hospitalized patients can adversely affect clinical outcomes and cost. Several nutritional screening tools have been developed to identify patients with malnutrition risk. However, many of those possess practical pitfalls of requiring much time and labor to administer and may not be highly applicable to a Korean population. This study sought to develop and evaluate a Nutrition Risk Screening Tool (NRST) which is simple and quick to administer and widely applicable to Korean hospitalized patients with various diseases. The study was also designed to generate a screening tool predictable of various clinical outcomes and to validate it against the Nutritional Risk Screening 2002 (NRS 2002). Electronic medical records of 424 patients hospitalized at a general hospital in Seoul during a 14-month period were abstracted for anthropometric, medical, biochemical, and clinical outcome variables. The study employed a 4-step process consisting of selecting NRST components, searching a scoring scheme, validating against a reference tool, and confirming clinical outcome predictability. NRST components were selected by stepwise multiple regression analysis of each clinical outcome (i.e., hospitalization period, complication, disease progress, and death) on several readily available patient characteristics. Age and serum levels of albumin, hematocrit (Hct), and total lymphocyte count (TLC) remained in the last model for any of 4 dependent variables were decided as NRST components. Odds ratios of malnutrition risk based on NRS 2002 according to levels of the selected components were utilized to frame a scoring scheme of NRST. A NRST score higher than 3.5 was set as a cut-off score for malnutrition risk based on sensitivity and specificity levels against NRS 2002. Lastly differences in clinical outcomes by patients' NRST results were examined. The results showed that the NRST can significantly predict the in-hospital clinical outcomes. It is concluded that the NRST can be useful to simply and quickly screen patients at high-nutritional risk in relation to prospective clinical outcomes.

• Progress in Medical Physics
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• v.12 no.1
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• pp.41-50
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• 2001

The quantification analysis of renal scintigraphy is strongly affected by the location, shape and size of region of interest(ROI). When ROIs are drawn manually, these ROIs are not reproducible due to the operators' subjective point of view, and may lead to inconsistent results even if the same data were analyzed. In this study, the effect of the ROI variation on the analysis of renal scintigraphy when the ROIs are drawn manually was investigated, and in order to obtain more consistent results, methods for automated ROI definition were developed and the results from the application of the developed methods were analyzed. Relative renal function, glomerular filtration rate and mean transit time were selected as clinical parameters for the analysis of the effect of ROI and the analysis tools were designed with the programming language of IDL5.2. To obtain renal scintigraphy, $^{99m}$Tc-DTPA was injected to the 11 adults of normal condition and to study the inter-operator variability, 9 researchers executed the analyses. The calculation of threshold using the gradient value of pixels and border tracing technique were used to define renal ROI and then the background ROI and aorta ROI were defined automatically considering anatomical information and pixel value. The automatic methods to define renal ROI were classified to 4 groups according to the exclusion of operator's subjectiveness. These automatic methods reduced the inter-operator variability remarkably in comparison with manual method and proved the effective tool to obtain reasonable and consistent results in analyzing the renal scintigraphy quantitatively.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.187-197
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• 2010

Carbon dioxide Capture and Storage(CCS) is regarded as one of the most promising options to response climate change. CCS is a three-stage process consisting of the capture of carbon dioxide($CO_2$), the transport of $CO_2$ to a storage location, and the long term isolation of $CO_2$ from the atmosphere for the purpose of carbon emission mitigation. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the $CO_2$ mixture captured from the power plants and steel making plants contains many impurities such as $N_2$, $O_2$, Ar, $H_2O$, $SO_2$, $H_2S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification, transport and injection processes. In order to design a reliable $CO_2$ marine geological storage system, it is necessary to analyze the impact of these impurities on the whole CCS process at initial design stage. The purpose of the present paper is to compare and analyse the relevant physical property models including BWRS, PR, PRBM, RKS and SRK equations of state, and NRTL-RK model which are crucial numerical process simulation tools. To evaluate the predictive accuracy of the equation of the state for $CO_2-SO_2$ mixture, we compared numerical calculation results with reference experimental data. In addition, optimum binary parameter to consider the interaction of $CO_2$ and $SO_2$ molecules was suggested based on the mean absolute percent error. In conclusion, we suggest the most reliable physical property model with optimized binary parameter in designing the $CO_2-SO_2$ mixture marine geological storage process.

• Journal of Hospice and Palliative Care
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• v.7 no.2
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• pp.189-199
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• 2004

Purpose: Despite the small incidence, head and neck cancer may cause a wide range of physical transformation by surgical operation, damage to active functions such as eating and speaking. It may provoke hopelessness, change self-esteem and self-concept after its operation, influencing the quality life of head and neck cancer patients. Thus nursing intervention should be developed to provide supportive nursing for head and neck cancer patients and play roles as competent supporters. Methods: This study was a nonequivalent, control group, pretest-posttest, non-synchronized quasi-experimental research designed to determine how supportive nursing intervention effects on hopelessness, self-esteem and self-concept of head and neck cancer patients. Subjects of the study included 40 adult inpatients of K University hospital in Pusan who were diagnosed as having head and neck cancer and operated. They were divided into experimental and comparison groups, each consisting of 20 members. The data were collected during the period from December 1, 1999 to April 11, 2000. Tools of the study included the protocol of supportive nursing intervention which was developed by researcher by means of reference, literal review and expert's advice. The measurement tool of hopelessness was translated by Won was the device of hopelessness self-evaluation from Beck, the tool for self-esteem measurement was developed by Rosenberg and translated by Kim, and the device of self-concept used by Lee et al, modified by Lee were used respectively. Data were analyzed using the SPSS/PC 9.0 program. The homogeneity of the subjects were tested using $x^2-test$ and t-test. 3 hypotheses were tested using t-test. Results: The results of the study can be summarized as follows. 1. The third hypothesis that the experimental group receiving supportive nursing intervention showed a little hopelessness than the control group not receiving supportive nursing intervention was supported (t=4.550, P=.000). 2. The third hypothesis that the experimental group receiving supportive nursing intervention showed more self-esteem than the control group not receiving supportive nursing intervention was supported (t=-6.40, p=.000). 3. The third hypothesis that the experimental group receiving supportive nursing intervention showed more self-concept than the control group not receiving supportive nursing intervention was supported (t=-6.065, P=.000). Conclusion: Supportive nursing intervention was effective nursing intervention strategy for reducing hopelessness and increasing self-esteem and self-concept of head and neck cancer patients. Then the quality of life of head and neck cancer patients can be enhanced by providing supportive nursing intervention in nursing practice.