• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.125-132
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• 2011

Fire monitoring system detects a fire based on the values of various sensors, such as smoke, CO, temperature, or change of temperature. It detects a fire by comparing sensed values with predefined threshold values for each sensor. However, to prevent a fire it is required to predict a situation which has a possibility of fire occurrence. In this work, we propose a fire recognition system using a fuzzy inference method. The rule base is constructed as a combination of fuzzy variables derived from various sensed values. In addition, in order to solve generalization and formalization problems of rule base construction from expert knowledge, we analyze features of fire patterns. The constructed rule base results in an improvement of the recognition accuracy. A fire possibility is predicted as one of 3 levels(normal, caution, danger). The training data of each level is converted to fuzzy rules by FCM(fuzzy C-means clustering) and those rules are used in the inference engine. The performance of the proposed approach is evaluated by using forest fire data from the UCI repository.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.59-72
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• 2004

The range of Internet usage is drastically broadened and diversed from information retrieval and collection to many different functions. Contrasting to the increase of Internet use, the efficiency of finding necessary information is decreased. Therefore, the need of information system which provides customized information is emerged. Our research proposes Web Service based recommendation system which employes inference engine to find and recommend the most appropriate products for users. Web applications in present provide useful information for users while they still carry the problem of overcoming different platforms and distributed computing environment. The need of standardized and systematic approach is necessary for easier communication and coherent system development through heterogeneous environments. Web Service is programming language independent and improves interoperability by describing, deploying, and executing modularized applications through network. The paper focuses on developing Web Service based recommendation system which will provide benchmarks of Web Service realization. It is done by integrating inference engine where the dynamics of information and user preferences are taken into account.

• International Commerce and Information Review
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• v.16 no.1
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• pp.91-116
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• 2014

This study reviews the methodology for utilizing information technology by which even non-professionalists in FTAs and commodity classification area can perform the determination of commodity classification, with ease and by themselves, by means of easy utilization of the information on commodity classification and FTAs, of importing and exporting goods. This article examines the technological elements and logics, etc. which simulate the commodity classification for utilizing FTAs. To achieve this, the author has developed the technology to support the determination of commodity classification numbers by accumulating the database of examples for classification after analyzing the classification factors by each commodity item. Utilizing this Commodity Classification Determination Supporting System, users can enjoy effects of education as well as consulting. In this regards, the advantages of this system can be enumerated as followings : Firstly, self-checking on commodity classification can be performed. Secondly, time and cost for classification can be saved. Thirdly, comprehensive competitiveness will be enhanced by allowing traders to achieve the benefit of FTA preferential tariff, for they will be able to issue the Certificate of Origins on a more accurate and precise basis of commodity classification.

• Koreanishche Zeitschrift fur Deutsche Sprachwissenschaft
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• v.1
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• pp.313-348
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• 1999

이 논문은 독일어의 겹자음회피현상을 설명함에 있어 어휘음운론에서의 분석이 보이는 문제들을 지적하고, 이 문제들이 제약에 바탕을 둔 이론에서는 어떻게 해결될 수 있는가를 보인다. 제약들간의 상호작용에서 특히 중요한 역할을 하는 것이 단일형태실현제약 (Uniform Exponence)으로서, 이 제약을 통해 독일어 동사의 현재시제, 단수, 2인칭 형태와 3인칭형태에서 나타나는 겹자음회피현상이 동사의 어형변화표 (Verbparadigma)와 밀접한 관련이 있음을 알 수 있다. 이는 규칙들을 통해 2인칭과 3인칭의 올바른 형태를 각각 개별적으로 찾아내는 어휘음운론의 분석과는 근본적으로 다르다. 왜냐하면 어휘음운론의 분석에 따를 때, 예를 들어 3인칭 동사 arbeitet에서 Schwa 모음의 삽입은 겹자음회피를 위해 일어난다고 설명되지만 겹자음이 없음에도 불구하고 Schwa 모음이 마찬가지로 삽입되는 2인칭동사 arbeitest는 설명되지 않기 때문이다. 이런 분석에서는 2인칭 형태와 3인칭 형태가 서로 아무런 관련 없이 각기 따로 존재하게된다. 이에 반해 단일형태제약은 이 두개의 형태를 동시에 비교하므로, 동사 굴절형태에서 마치 불필요한 것으로 보이는 모음삽입이나 자음탈락의 원인에 대해 이론적인 근거를 제시할 수 있다. 즉 2인칭 형태와 3인칭 형태는 보다 상위의 제약들이 막지 않는 한 서로 최대한 비슷한 형태를 가지려고 한다. 이 논문은 겹자음 회피를 위한 수단으로서 모음삽입이나 자음탈락은 오로지 이를 통해 동사의 어형변화표가 좋아질 때만 가능하다는 것을 보여줌으로써 규칙이론이 포착하지 못하고 있는 중요한 일반화를 제시하고 있다. 단일형태 실현제약의 중요성은 접두사 in- 과 un- 이 어간과 결합할 때 보이는 대조를 통해서도 확인된다. 여기서도 어휘음운론의 다층어휘부 구조에 의한 설명이 갖는 문제점이 제약들간의 상호작용을 통해 해결될 수 있음을 알 수 있다.VII-1 및 VII-2공의 3600 m 하부층은 건성 가스 생성 단계에까지 도달한 것으로 나타났다. JDZ VII-1, VII-2 시추공의 3500 m 하위 구간의 올리고세 퇴적층에서 유기물 함량 및 수소 지수가 급격히 감소하는 것은 매몰 심도가 깊어지면서 유기물이 열 분해되어 이미 탄화수소를 생성한 것으로 해석된다. JDZ VII-1 및 VII-2 시추공의 가스징후 및 길소나이트 (gilsonite)는 탄화수소가 생성되어 이동한 흔적을 시사한다.을 해석할 수 있음을 보여주는 것으로 평가된다. 다만 PLAYMAKER2가 보다 신뢰할 만한 퇴적환경 해석을 위한 전문가 시스템으로 구축되기 위해서는 향후 많은 퇴적학 전문가들이 추가로 참여하여 기존 규칙들을 재검증하고 새로운 규칙들을 첨가함으로써 보디 세련된 지식베이스를 개발하여야 할 것으로 판단된다.이며 세 개의 산소가 이루는 평면에서 $1.68{\AA}$ 소다라이트내로 이동하여 위치한다. 32개의 $Tl^{+}$ 이온은 결정학적 자리 II에 존재하고 있으며 산소와의 결합거리를 $2.70(1){\AA}$을 유지하면서 큰 동공속으로 $1.48{\AA}$ 이동하여 위치한다. 약 18개의 $Tl^+$ 이온은 결정학적 자리III에, 또 다른 10개의 $Tl^+$ 이온은 결정학적 자리III'에 존재하고 골조 산소와 각각 $2.86(2){\AA},\;2.96(4){\AA}$의 결합거리를 이룬다.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.247-260
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• 2003

To share and standardize information, especially in the database environments, MDR (Metadata Registry) can be used to integrate various heterogeneous databases within a particular domain. But due to the discrepancies of data element representation between organizations, global information integration is not so easy. And users who are searching integrated information on the Web have limitation to obtain schema information for the underlying source databases. To solve those problems, in this paper, we present a 3-layered Information Integration System (LI2S) based on MDRs and Ontology. The purpose of proposed architecture is to define information integration model, which combine both of the nature of MDRs standard specification and functionality of ontology for the concept and relation. Adopting agent technology to the proposed model plays a key role to support the hierarchical and independent information integration architecture. Ontology is used as for a role of semantic network from which it extracts concept from the user query and the establishment of relationship between MDRs for the data element. (MDR and Knowledge Base are used as for the solution of discrepancies of data element representation between MDRs. Based on this architectural concept, LI2S was designed and implemented.

• Knowledge Management Research
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• v.22 no.2
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• pp.1-17
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• 2021

In this study, we predicted the bitcoin prices of Bithum and Coinbase, a leading exchange in Korea and USA, using ARIMA and Recurrent Neural Networks(RNNs). And we used news articles from each country to suggest a separated RNN model. The suggested model identifies the datasets based on the changing trend of prices in the training data, and then applies time series prediction technique(RNNs) to create multiple models. Then we used daily news data to create a term-based dictionary for each trend change point. We explored trend change points in the test data using the daily news keyword data of testset and term-based dictionary, and apply a matching model to produce prediction results. With this approach we obtained higher accuracy than the model which predicted price by applying just time series prediction technique. This study presents that the limitations of the time series prediction techniques could be overcome by exploring trend change points using news data and various time series prediction techniques with text mining techniques could be applied to improve the performance of the model in the further research.

• The KIPS Transactions:PartA
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• v.10A no.5
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• pp.469-478
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• 2003

Internet information search engines using web robots visit servers conneted to the Internet periodically or non-periodically. They extract and classify data collected according to their own method and construct their database, which are the basis of web information search engines. There procedure are repeated very frequently on the Web. Many search engine sites operate this processing strategically to become popular interneet portal sites which provede users ways how to information on the web. Web search engine contacts to thousands of thousands web servers and maintains its existed databases and navigates to get data about newly connected web servers. But these jobs are decided and conducted by search engines. They run web robots to collect data from web servers without knowledge on the states of web servers. Each search engine issues lots of requests and receives responses from web servers. This is one cause to increase internet traffic on the web. If each web server notify web robots about summary on its public documents and then each web robot runs collecting operations using this summary to the corresponding documents on the web servers, the unnecessary internet traffic is eliminated and also the accuracy of data on search engines will become higher. And the processing overhead concerned with web related jobs on web servers and search engines will become lower. In this paper, a monitoring system on the web server is designed and implemented, which monitors states of documents on the web server and summarizes changes of modified documents and sends the summary information to web robots which want to get documents from the web server. And an efficient web robot on the web search engine is also designed and implemented, which uses the notified summary and gets corresponding documents from the web servers and extracts index and updates its databases.

• Journal of the Korean association of regional geographers
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• v.6 no.3
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• pp.117-138
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• 2000

This study is, from the view point of constructive social studies which is the foundation of the 7th curriculum, to explore whether there is any viable program and to investigate it by which students, using photo resources in social studies, can organize their knowledge in the way of self-directed thinking. The main results are as follows: If it is a principle of knowledge construction process of constructive social studies that individual construction (cognitive construction) develops into communal construction(social construction) and yet communal construction develops itself, interacting with individual construction, it will be meet the objectives of social studies. In social studies, photos are a powerful communication tool. communicating with photos enables to invoke not only the visual aspects but also invisible aspects of social phenomena from photos. It, therefore, can help develop thinking power through inquiry learning, which is one of the emphasis of the 7th curriculum. Having analyzed photo resources appeared on the regional textbooks in elementary social studies, they have been appeared that even though the importance and amount of space photo resources occupy per page is big with regard to total resources, most of the photos failed to lad to self-directed thinking but just assistant material in stead. Besides, there appeared some problems with the title, variety, size, position, tone of color, visibility of the photos, and further with the combination of the photos. Developing of photo resources for constructive social studies is to overcome some problems inherent in current text books and to reflect the theoretical background of the 7th curriculum. To develop the sort of photo that can realize the point just mentioned, it would be highly preferable to provide photo database to facilitate study with homepage through web-based interaction. To take advantage of constructive photo resources, the instruction is strategized in four stages, intuition, conflict, accommodation, and equilibration stage. With the advancement of the era of image culture, curriculum developers are required to develop dynamic, multidimensional digital photos rather than static photos when develop text books.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.