• Korean Security Journal
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• no.9
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• pp.69-98
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• 2005

The security industry for civilians (Private Security), was first introduced to Korea via the US army's security system in the early 1960's. Shortly after then, official police laws were enforced in 1973, and private security finally started to develop with the passing of the 'service security industry' law in 1976. Korea's Private Security industry grew rapidly in the 1980's with the support of foreign funds and products, and now there are thought to be approximately 2000 private security enterprises currently running in Korea. However, nowadays the majority of these enterprises are experiencing difficulties such as lack of funds, insufficient management, and lack of control over employees, as a result, it seems difficult for some enterprises to avoid the low production output and bankruptcy. As a result of this these enterprises often settle these matters illegally, such as excessive dumping or avoiding problems by hiring inappropriate employees who don't have the right skills or qualifications for the jobs. The main problem with the establishment of this kind of security service is that it is so easy to make inroads into this private service market. All these hindering factors inhibit the market growth and impede qualitative development. Based on these main reasons, I researched this area, and will analyze and criticize the present condition of Korea's private security. I will present a possible development plan for the private security of Korea by referring to cases from the US and Japan. My method of researching was to investigate any related documentary records and articles and to interview people for necessary evidence. The theoretical study, involves investigation books and dissertations which are published from inside and outside of the country, and studying the complete collection of laws and regulations, internet data, various study reports, and the documentary records and the statistical data of many institutions such as the National Police Office, judicial training institute, and the enterprises of private security. Also, in addition, the contents of professionals who are in charge of practical affairs on the spot in order to overcomes the critical points of documentary records when investigating dissertation. I tried to get a firm grasp of the problems and difficulties which people in these work enterprises experience, this I thought would be most effective by interviewing the workers, for example: how they feel in the work places and what are the elements which inpede development? And I also interviewed policemen who are in charge of supervising the private escort enterprises, in an effort to figure out the problems and differences in opinion between domestic private security service and the police. From this investigation and research I will try to pin point the major problems of the private security and present a developmental plan. Firstly-Companies should unify the private police law and private security service law. Secondly-It is essential to introduce the 'specialty certificate' system for the quality improvement of private security service. Thirdly-must open up a new private security market by improving old system. Fourth-must build up the competitive power of the security service enterprises which is based on an efficient management. Fifth-needs special marketing strategy to hold customers Sixth-needs positive research based on theoretical studies. Seventh-needs the consistent and even training according to effective market demand. Eighth-Must maintain interrelationship with the police department. Ninth-must reinforce the system of Korean private security service association. Tenth-must establish private security laboratory. Based on these suggestions there should be improvement of private security service.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.15 no.2
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• pp.160-167
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• 2004

Objectives : There have been very few studies on the compliance of methylphenidate-immediate releasing form(MPH-IR), which is the most frequently used drug in Korea, in Attention Deficit Hyperactivity Disorder(ADHD). This study was conducted to investigate the compliance rate and the related factors in the one year pharmacotherapy process via OPD for children with ADHD. Method : Total 100 ADHD patients were selected randomly among patients who have been treated with MPH-IR from September in 2002 to December in 2002. All the selected patients were diagnosed with DSM-IV-ADHD criteria and fulfilled the inclusion criteria. In March, 2003(at the time of 6 month treatment), all the patients and parents received the questionnaire for the compliance and satisfaction for MPH-IR treatment. In October 2003(at time of 1 year treatment), we, investigators evaluated the socio-demographic variables, developmental data, medical data, family data, comorbid disorders, treatment variables, and compliance rate. Through these very comprehensive data, The compliance rate at the time of mean 1 year treatment and the related factors were investigated. Result : 1) In the questionnaire for compliance and satisfaction for MPND treatment, the 60% of respondents(parents) reported more than moderate degree of satisfaction in the effectiveness of MPND. Their compliance rate for the morning prescription was 81%, but the rate of afternoon prescription was 43%. 2) In the evaluation at the time of 1 year treatment(October 2003), the 38% of parents were dropped out from the OPD treatment. The mean compliance rate for the 1 year treatment was 62%. the 38% of parents were dropped out from the OPD treatment. The mean compliance rate for the 1year treatment was 62%. 3) Compared with the noncompliant group(drop-out group), compliant group showed higher total, verbal and performance IQ scores. In the treatment variables, higher reposponder rate(clinician rating), higher medication dosage and more compliance rate in afternoon prescription were found in the compliant group compared with the noncompliant group. There were no statistical differences in the demographic variables(age, sex, SES, parental education level), medical data, developmental profiles and academic function. Conclusion : To our knowledge, this is the first report about the compliance rate of the MPH-IR treatment for the children with ADHD. The compliance rate at the time of mean 1year treatment was 62%, which was comparable with other studies performed in foreign countries, especially States. In this study, the compliance related factors were IQ score, clinical treatment response, dosage of MPH-IR, and early compliance for the afternoon prescription. These results suggest that clinician plan the strategies for the promotion of the early compliance for the after prescription and enhancement of overall treatment response.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.1-22
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• 2021

Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.