• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.4
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• pp.1-17
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• 2012

This study was carried out to propose the improved method by analyzing the change of green space arrangement and planting structure of apartment complexes in Seoul. 12 survey sites, which have obvious differences, were selected by reflecting the change of floor area ratio, underground parking place, and green space ratio. We divided the survey sites into four types that high green ratio(over 40%) apartment on natural ground, low green ratio(under 40%) apartment on natural ground, low green ratio(under 40%) apartment on artificial ground, and high green ratio(over 40%) apartment on artificial ground each period based on green space ratio and ground structure, plant crown volume, planting density, and planting pattern. The main factors of change of green space arrangement were green space ratio and ground structure. The Green space ratio was changed by the floor area ratio with constructing underground parking place and floor area ratio was adjusted by government policy and economic status. Average width of front green area has been changed from 10.0m in high green ratio apartment on natural ground for 3.5m, 2.7m, and 4.5m each period. The average width of the buffer green area has been changed from 15.0m in high green ratio apartment on natural ground of 7.7m, and 2.7m by extending parking place in the low green ratio apartment of artificial ground, so buffer green areas have been reduced and disconnected. So buffer green area in apartment complexes has been extended that the average width of the buffer green area was 3.8m caused by growing recognition of green since 2001. The ratio of native plant in canopy layer was increased from 45.1 % in the case of the high green ratio apartment of natural ground in 1980~1983 to 55.6%. Average plant crown volume increased from $1.27m^3/m^2$ in high green ratio apartment on natural ground for $3.47m^3/m^2$ in a low green ratio apartment on natural ground. But average plant crown volume is $0.27m^3/m^2$ in the high green ratio apartment of the artificial ground plant density of canopy layer was changed from 5 individuals per $100m^2$ to 14.5 individuals per $100m^2$. We should construct the buffer green area with natural ground and get the function of ecological and beautiful environment regarding to garden concept in case of front green area, width 4.5m. We should get the function of increasing green volume by multi-layer planting with shade woody species and flower woody species in case of back-side green area, width over 5.0m. We should get the function of covering the wall and increasing green landscape by planting with high woody species in case of side green area. We should apply the ecological planting technique to buffer green area and connect buffer green area to inner green area in apartment complexes.

• Proceedings of the Korean DIstribution Association Conference
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• 2005.05a
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• pp.383-405
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• 2005

The traditional market is foremost a regionally positioned place, wherein the market directly represents regional and cultural centered traits while it plays an important role in the circulation of facilities through reciprocal, informative and cultural exchanges while sewing to form local communities. The traditional market in Korea is one of representative retail businesses and premodern marketing techniques by family owned business of less than five members such as product management, purchase method, and marketing patterns etc. Since the 1990s, the appearance of new circulation-type businesses and large discount convenience stores escalated the loss of traditional competitiveness, increased the living standard of customers, changed purchasing patterns, and expanded the ubiquity of the Internet. All of these changes in external circulation circumstances have led the traditional markets to lose their place in the economy. The traditional market should revive on a regional site basis through the formation of a community of regional neighbors and through knowledge-sharing that leads to the creation of wealth. For the purpose of creating a wealth in a place, the following components are necessary: 1) a facility suitable for the spatial place of the present, 2)trust built through exchanges within the changing market environment, which would simultaneously satisfy customer's desires, 3) international bench marking on cases such as regionally centered TCM (England), BID (USA), and TMO (Japan) so that the market unit of store placement transfers from a spot policy to a line policy, 4)conversion of communicative conception through a surface policy approach centered around a macro-region perspective. The budget of the traditional market funding policy was operational between 2001 and 2004, serving as a counter move to solve the problem of the old traditional market through government intervention in regional economies to promote national economic strength. This national treasury funding project was centered on environmental improvement, research corps, and business modernization through the expenditure of 3,853 hundred million won (Korean currency). However, the effectiveness of this project has yet to be to proven through investigation. Furthermore, in promoting this funding support project, a lack of professionalism among merchants in the market led to constant limitations in comprehensive striving strategies, reduced capabilities in middle-and long-term plan setup, and created reductions in voluntary merchant agreement solutions. The traditional market should go beyond mere physical place and ordinary products creative site strategies employing the communicative approach must accompany these strategies to make the market a new regional and spatial living place. Thus, regarding recent paradigm changes and the introduction of region-based site functions into the traditional market, acquiring a conversion of direction into the newly developed project is essential to reinvestigate the traditional market composed of cultural and economic meanings, for the purpose of the research. Excavating social policy demands through the comparative analysis of domestic and international cases as well as innovative and expert management leadership development for NPO or NGO civil entrepreneurs through advanced case research on present promotion methods is extremely important. Discovering the seeds of the cultural contents industry cored around regional resource usages, commercializing regionally reknowned products, and constructing complex cultural living places for regional networks are especially important. In order to accelerate these solutions, a comprehensive and systemized approach research operated within a mentor academy system is required, as research will reveal distinctive traits of the traditional market in the aging society.

• Journal of Chest Surgery
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• v.37 no.1
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• pp.27-34
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• 2004

Background: Infective endocarditis shows higher operative morbidity and mortality rates than other cardiac diseases. The vast majority of studies on infective endocarditis have been made on aortic endocarditis, with little attention having been paid to infective endocarditis on the mitral valve. This study attempts to investigate the clinical aspects and operative results of infective endocarditis on the mitral valve. Meterial and Method: The subjects of this study consist of 23 patients who underwent operations for infective endocariditis on the mitral valve from June 1995 to May 2003. Among them, 2 patients suffered from prosthetic valvular endocarditis and the other 21 from native valvular endocarditis. The subjects were evenly distributed age-wise with an average age of 44.8$\pm$15.7 (11∼66) years. Emergency operations were performed on seventeen patients (73.9%) due to large vegetation or instable hemodynamic status. In preoperative examinations, twelve patients exhibited congestive heart failure, four patients renal failure, two patients spleen and renal infarction, and two patients temporary neurological defects, while one patient had a brain abscess. Based on the NYHA functional classification, seven patients were determined to be at Grade II, 9 patients at Grade III, and 6 patients at Grade IV. Vegetations were detected in 20 patients while mitral regurgitation was dominant in 19 patients with 4 patients showing up as mitral stenosis dominant on the preoperative echocardiogram. Blood cultures for causative organisms were performed on all patients, and positive results were obtained from ten patients, with five cases of Streptococcus viridance, two cases of methicillin-sensitive Staphylococcus aureus, and one case each of Corynebacteriurn, Haemophillis, and Gernella. Operations were decided according to the AA/AHA guidelines (1988). The mean follow-up period was 27.6 $\pm$23.3 (1 ∼ 97) months. Result: Mitral valve replacements were performed on 43 patients, with mechanical valves being used on 9 patients and tissue valves on the other 4. Several kinds of mitral valve repair or mitral valvuloplasty were carried out on the remaining 10 patients. Associated procedures included six aortic valve replacements, two tricuspid annuloplasty, one modified Maze operation, and one direct closure of a ventricular septal defect. Postoperative complications included two cases of bleeding and one case each of mediastinitis, low cardiac output syndrome, and pneumonia. There were no cases of early deaths, or death within 30 days following the operation. No patient died in the hospital or experienced valve related complications. One patient, however, underwent mitral valvuloplasty 3 months after the operation. Another patient died from intra-cranial hemorrhage in the 31st month after the operation. Therefore, the valve-related death rate was 4.3%, and the valve-related complication rate 8.6% on mid-term follow-up. 1, 3-, and 5-year valve- related event free rates were 90.8%, 79.5%, and 79.5%, respectively, while 1, follow-up. 1, 3-, and 5-year valve- related event free rates were 90.8%, 79.5%, and 79.5%, respectively, while 1, 3-, and 5-year survival rates were 100%, 88.8%, and 88.8%, respectively. Conclusion: The findings suggest that a complete removal of infected tissues is essential in the operative treatment of infectious endocarditis of the mitral valve. It is also suggested that when infected tissues are completely removed, neither type of material nor method of operation has a significant effect on the operation result. The postoperative results also suggest the need for a close follow-up observation of the patients suspected of having brain damage, which is caused by preoperative blood contamination or emboli from vegetation, for a possible cerebral vascular injury such as mycotic aneurysm.

• Journal of Chest Surgery
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• v.40 no.8
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• pp.536-545
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• 2007

Background: Compared to adult patients, mitral regurgitation in pediatric patients is uncommon and it shows a wide spectrum of morphologic abnormalities. We retrospectively evaluated the midterm results of mitral valve repair in pediatric patients. Material and Method: Between December 1993 and August 2006, mitral valve repair was performed in 35 patients who were aged less than 18 years, The mean age was $5.3{\pm}5.3$ years and the mean body weight was $20,0{\pm}16.3\;kg$. 18 patients had associated cardiac anomalies. The most common pathologic finding was leaflet prolapse (n=17). The most common method of repair was the double orifice technique (n=15). Result: There was no early mortality. Eight patients underwent reoperation (24.2%), and five of them required mitral valve replacement. Among the four ring annuloplasty cases, two have developed mitral stenosis. Four out of the 14 double orifice cases required reoperation. One case of early mortality and one case of late mortality occurred in the reoperation cases. The 5-year survival rate and the freedom from reoperation rate were $93.3{\pm}4.6%$ and $76.1{\pm}8.2%$, respectively. The 5-year freedom from mitral valve replacement rate was $83.6{\pm}6.7%$. There was no significant risk factor for reoperation. Conclusion: The midterm results of mitral valve repair are very acceptable in pediatric patients compared to the adult cases, although the reoperation rate is slightly higher.

• Tuberculosis and Respiratory Diseases
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• v.45 no.4
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• pp.813-822
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• 1998

Background: Extubation is recommended to be performed at minimum pressure support (PSmin) during the pressure support ventilation (PSV). In field, physicians sometimes perform additional 1 hr T-piece trial to the patient at PSmin to reduce re-intubation risk. Although it provides confirmation of patient's breathing reserve, weaning could be delayed due to increased airway resistance by endotracheal tube. Methods: To investigate the effect of additional 1 hr T-piece trial on weaning outcome, a prospective study was done in consecutive 44 patients who had received mechanical ventilation more than 3 days. Respiratory mechanics, hemodymic, and gas exchange measurements were done and the level of PSmin was calculated using the equation (PSmin=peak inspiratory flow rate $\times$ total ventilatory system resistance) at the 15cm $H_2O$ of pressure support. At PSmin, the patients were randomized into intervention (additional 1 hr T-piece trial) and control (extubation at PSmin). The measurements were repeated at PSmm, during weaning process (in cases of intervention), and after extubation. The weaning success was defined as spontaneous breathing more than 48hr after extubation. In intervention group, failure to continue weaning process was also considered as weaning failure. Results: Thirty-six patients with 42 times weaning trial were satisfied to the protocol. Mean PSmin level was 7.6 (${\pm}1.9$)cm $H_2O$. There were no differences in total ventilation times (TVT), APACHE III score, nutritional indices, and respiratory mechanics at PSmin between 2 groups. The weaning success rate and re-intubation rate were not different between intervention group (55% and 18% in each) and control group (70% and 20% in each) at first weaning trial. Work of breathing, pressure time product, and tidal volume were aggravated during 1 hr T-piece trial compared to those of PSmin in intervention group ($10.4{\pm}1.25$ and $1.66{\pm}1.08$ J/L in work of breathing) ($191{\pm}232$ and $287{\pm}217$cm $H_2O$ s/m in pressure time product) ($0.33{\pm}0.09$ and $0.29{\pm}0.09$ L in tidal volume) (P<0.05 in each). As in whole, TVT, and tidal volume at PSmin were significantly different between the patients with weaning success ($246{\pm}195$ hr, $0.43{\pm}0.11$ L) and the those with weaning failure ($407{\pm}248$ hr, $0.35{\pm}0.10$L) (P<0.05 in each). Conclusion : There were no advantage to weaning outcome by addition of 1 hr T-piece trial compared to prompt extubation to the patient at PS min.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.137-152
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• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.2
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• pp.101-127
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• 2017

Even with the most advanced aviation technology benefits, aircraft accidents are constantly occurring while air passenger transportation volume is expected to double in the next 15 years. Since it is not possible to secure aviation safety only by the post aircraft accident safety action of accident investigations, it has been recognized and consensus has been formed that proactive and predictive prevention measures are necessary. In this sense, the aviation safety management system (SMS) was introduced in 2008 and has been carried out in earnest since 2011. SMS is a proactive and predictive aircraft accident preventive measure, which is a mechanism to eliminate the fundamental risk factors by approaching organizational factors beyond technological factors and human factors related to aviation safety. The methodology is to collect hazards in all the sites required for aircraft operations, to build a database, to analyze the risks, and through managing risks, to keep the risks acceptable or below. Therefore, the improper implementation of SMS indicates that the aircraft accident prevention is insufficient and it is to be directly connected with the aircraft accident. Reports of duty performance related hazards including their own errors are essential and most important in SMS. Under the policy of just culture for voluntary reporting, the guarantee of information providers' anonymity, non-punishment and non-blame should be basically secured, but to this end, under-reporting is stagnant due to lack of trust in their own organizations. It is necessary for the accountable executive(CEO) and senior management to take a leading role to foster the safety culture initiating from just culture with the safety consciousness, balancing between safety and profit for the organization. Though a Ministry of Land, Infrastructure and Transport's order, "Guidance on SMS Implementation" states the training required for the accountable executive(CEO) and senior management, it is not legally binding. Thus it is suggested that the SMS training completion certificates of accountable executive(CEO) and senior management be included in SMS approval application form that is legally required by "Korea Aviation Safety Program" in addition to other required documents such as a copy of SMS manual. Also, SMS related items are missing in the aircraft accident investigation, so that organizational factors in association with safety culture and risk management are not being investigated. This hinders from preventing future accidents, as the root cause cannot be identified. The Aircraft Accident Investigation Manuals issued by ICAO contain the SMS investigation wheres it is not included in the final report form of Annex 13 to the Convention on International Civil Aviation. In addition, the US National Transportation Safety Board(NTSB) that has been a substantial example of the aircraft accident investigation for the other accident investigation agencies worldwide does not appear to expand the scope of investigation activities further to SMS. For these reasons, it is believed that investigation agencies conducting their investigations under Annex 13 do not include SMS in the investigation items, and the aircraft accident investigators are hardly exposed to SMS investigation methods or techniques. In this respect, it is necessary to include the SMS investigation in the organization and management information of the final report format of Annex 13. In Korea as well, in the same manner, SMS item should be added to the final report format of the Operating Regulation of the Aircraft and Railway Accident Investigation Board. If such legal and institutional improvement methods are complemented, SMS will serve the purpose of aircraft accident prevention effectively and contribute to the improvement of aviation safety in the future.

• 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.