• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.577-590
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• 2023

This study explored types of failure encountered by elementary school students during the engineering design process and how they coped with them. To achieve this goal, we developed and taught engineering design lessons on water shortages to four fourth-grade classes, observing and interviewing seven focus groups. Our analysis revealed that student failures can be categorized into two main types: those caused by cognitive factors and those influenced by environmental factors. While cognitive failures are typically within students' control, environmental factors are beyond their reach. Our findings also showed that students tended to avoid discussing the root causes of failure and instead relied on ad hoc solutions. Additionally, some students lowered their expectations for success to avoid failure. Based on our findings, we offer practical recommendations for educators to help students learn from their failures in a constructive manner.

• Archives of design research
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• v.19 no.2 s.64
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• pp.109-120
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• 2006

Part of public arts, environmental builforms not only enhance the beauty of a building, but also serve to stabilize the citizen's psychology and as a landmark having intimate values with the city environment and symbolic meanings. Thus they do have sociocultural values as an original formative artwork. The purpose of this study was to suggest evaluation and review methods and an evaluation framework for environmental builtforms, which had legal binding under the building decoration system, to a local government to improve the quality level of urban environment. It will be such a distant goal of creating a desirable urban environment as long as environmental builtforms are merely regarded as an object to follow a vogue and a mandatory passage procedure. It's important to take a perspective of an expert to set up and suggest an evaluation system in the public aspects. In the study a consideration was made of the current systems and review criteria of environmental builtforms, which was followed by the development of a theoretical research model and of a framework for statistical evaluation by a group of experts. The questionnaire designed based on the theoretical research model was tested for validity and reliability. Its pilot test results were then analyzed to verify the hypotheses. The questionnaire collected twice were statistically analyzed in exploratory and confirmatory factor analysis with the SPSSWIN 11 program. All the analysis results were used to come up with a final evaluation framework.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.71-76
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• 2013

A computer worm is a standalone malware computer program that probes and exploits vulnerabilities of systems. It replicates and spreads itself to other computers via networks. In this paper, we study how to detect and prevent worms. First, we generated Codered II traffic on the emulated testbed called Deterlab. Then we identified dubious parts using Earlybird and wrote down Snort rules using Wireshark. Finally, by applying the Snort rules to the traffic, we could confirmed that worm detection was successfully done.

• Journal of dental hygiene science
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• v.6 no.4
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• pp.309-311
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• 2006

In order to development of new denture cleaners using natural antimicrobial agents, we have investigated various species of medicinal plants for the antimicrobial activity against Streptococcus matans and Candida albicans. Citrus extract showed significant antifungal activities in a dose-dependent manner against Candida albicans. Candidasis is also a common problem affecting older adults using full denture. We also developed liquid type denture cleaner formulation using citrus extracts.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.190-193
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• 2016

본 연구는 사행산업의 분야인 복권, 체육진흥투표권, 경마, 카지노에 대해 언론에서는 어떻게 다루어지고 있는지를 1990년부터 2015년까지의 뉴스데이터를 빅데이터 분석 방법 중 테스트의 의미연결망 분석을 통해 밝혀보고자 하는 연구이다. 이 논문은 의미망 분석을 통해 기사의 빈도와 연결성을 프레이밍과 시민관심 정도로 재조명 하여 기사에 대한 언론보도자의 의도와 시민의 인식차이를 밝혔고, 이를 통해 정책적 특성과 개혁과제를 탐색하였다. 분석결과 복권의 경우 당첨번호, 당첨금, 조작의혹 등 당첨에 대한 부분이 주제인 '사회문제' 형태였으며, 체육진흥투표권의 경우에는 사업입찰, 불법사이트, 발매대상 등 주로 사업추진과 불법사이트에 대한 '의무정보' 종류였고, 경마의 경우 사업장, 홍보, 기사 등으로 사업홍보나 광고 관련 뉴스이었고, 마지막으로 카지노의 경우에는 불법, 도박장, 외국인 등 '주요정보'에 해당하는 논문이었다. 시대에 따라 1990년대에는 카지노, 2000년대에는 복권, 2010년대에는 경마에 대한 기사보도가 많아졌으며, 이에 대한 시민의 반응도 사업비리, 당첨, 시민운동 등의 차이가 있었다. 마지막으로 기사의 빈도와 연결성이 나타내는 프레이밍 정도와 시민의 관심은 '1. 홍보광고, 2. 의무정보, 3. 사회이슈, 4. 주요정보' 네 가지로 구분되었으며 이 중 사고, 비리 등 주요기사로 구분되는 사회문제가 주요 공공의제로 형성되는 것을 확인할 수 있었다.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.321-327
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• 2004

SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of toro-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZC-BFS, which needs no additional memory when running SPIHT algorithm. It explicitly performs a breadth first search of the spatial-tree using peano-code and eliminates additional memory as it uses pre-status significant test for encoding and LSB bits of some coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in fast and simple hardware implementation and reduces the cost of production because no lists and additional memory are required.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.131-143
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• 2004

Given a path represented by a sequence of link numbers in a graph, the vine is differentiated from the loop in a sense that any link number can be visited in the path no more than once, while more than once in the loop. The vine provides a proper idea on complicated travel patterns such as U-turn and P-turn witnessed near intersections in urban transportation networks. Application of the link label method(LLM) to the shortest Path algorithms(SPA) enables to take into account these vine travel features. This study aims at expanding the LLM to a K-th path search algorithm (KPSA), which adopts the node-based-label correcting method to find a group of K number of paths. The paths including the vine type of travels are conceptualized as drivers reasonable route choice behaviors(RRCB) based on non-repetition of the same link in the paths, and the link-label-based MPSA is proposed on the basis of the RRCB. The small-scaled network test shows that the algorithm sequence works correctly producing multiple paths satisfying the RRCB. The large-scaled network study detects the solution degeneration (SD) problem in case the number of paths (K) is not sufficient enough, and the (K-1) dimension algorithm is developed to prevent the SD from the 1st path of each link, so that it may be applied as reasonable alternative route information tool, an important requirement of which is if it can generate small number of distinct alternative paths.

• Proceedings of the Korea Society of Costume Conference
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• 2001.04a
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• pp.50-51
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• 2001

많은 소비자들이 가치지향적인 의사결정을 할 때 제품의 품질을 매우 중요한 요소로 생각하며, 제품구매시 불완전한 정보 상황에서 빈번히 제품품질의 지표로서 가격을 이용한다고 한다(Peterson & Wilson. 1985). 이와 관련하여 시장에서의 실제 가격과 객관적 품질과의 관계를 분석하여 소비자의 효율성을 파악한 연구가 각국에서 이루어져 왔으나, 패션제품에 관한 가격과 객관적 품질과의 관계에 관한 연구는 국내 외적으로 매우 미흡한 실정이다. 따라서 본 연구의 목적은 1990년대 한국과 미국 패션시장의 가격과 객관적 품질간의 상관관계를 비교 분석함으로써 양국 패션제품의 품질수준을 비교해 보 는데 있다. 본 연구의 결과를 통해 가격이 제품품질의 지표가 될 수 있는가를 파악할 수 있을 것이다. 이를 위해 본 연구에서는 다음과 같은 연구문제를 설정하였다. 첫째, 한국과 미국 패션제품 시장의 가격과 품질의 상관관계는 전체적으로 어떠한 차이가 있는가\ulcorner 둘째, 한국과 미국 패션제품의 가격과 객관 적 품질의 상관관계가 패션산업범주에 따라 어떠한 차이가 있는가\ulcorner 마지막으로, 본 연구의 결과와 같은 제품의 품질에 대한 정보탐색으로부터 얻을 수 있는 한국과 미국 소비자의 구매이득은 어느 정도인가\ulcorner 본 연구를 위한 내용분석에 이용된 자료는 양국의 소비자의 권익보호를 위한 중립적 정보원에서 발간하고 있는, 한국의 <소비자 시대>와 미국의 에 개 재 된 1990년부터 1999년까지 의 상품비교테스트 정보중에서 패션제품군에 관련된 자료를 토대로 하였다. 수집된 자료는 한국의 36개 패션제품군, 470개 제품과, 미국의 40개 패션제품군. 692개의 패션 제품이었으며, 패션산업범주는 여성복, 남성복, 유니 섹스 의류, 스포츠 의류, 유.아동복, 언더웨어. 잡화. 제화류, 침장류, 섬유직물, 화장품. 학생복 등 11 가지 산업범주로 분류하였다. 본 연구의 결과를 요약하면 다음과 같다. 첫째, 한국과 미국 패션제품의 지난 십년간의 가격 과 품질의 상관관계는 매우 약한 정(+)의 상관을 가지고 있었다. 한국패션제품의 전체 서열상관계수의 평균은 0.091이었고, 미국의 상관계수 평균은 0.192였 다. 상관계수의 수치만으로 볼 때 한국보다는 미국 패션제품의 가격과 품질간의 상관관계가 조금 높게 나타났으나, 양국간 통계적인 차이는 없었다. 또한, 한국 패션제품의 경우에는 제품군의 가격대별 상관관계를 살펴보았는데, 그 결과 1만원 미만의 저가 제품군과 330만원이상의 고가의 제품군의 경우 부(-)의 상관계수를 나타냈다. 둘째. 1990년대 한국과 미국 패션시장의 가격과 품질간의 상관계수의 범위는 제품군별. 산업범주별 로 상이한 분포를 보이고 있었다. 패션제품군별로 보 면, 한국의 경우는 가장 높은 '여행용가방(r = 0.707)' 에서 가장 낮은 '자외선 차단화장품(r = -0.58)'까지, 그리고 미국 패션제품군의 상관계수의 범위는 '팬티 스타킹'의 0.820에서 '남성용 런닝슈즈'의 -0.472까지의 분포를 나타냈다. 마지막으로, 제품의 가격과 품질에 대한 정보를 소비자가 알 경우 얻을 수 있는 소비자의 구매이득 을 추산한 결과 패션제품시장에서 완전한 품질정보를 가지고 있다고 가정한 '현명한 사람'은, 최고가격의 제품만을 구입한다고 가정한 '부유한 사람들'의 구입방식에 비해 최고 좋은 품질의 상품을 총 지불액의 비율로 보아, 한국의 소비자는 약 50% 정도를, 미국의 소비자는 약 91%나 되는 액수를 절약하여 구매할 수 있는 것으로 나타났다. 이상의 본 연구의 결과를 종합하여 볼 때 한국과 미국 모두 제품군별, 그리고 산업범주별로 상관관계가 차이를 보이고 있어, 양국의 소비자들이 패션제품 의 품질을 평가함에 있어 오로지 가격에 대한 정보만을 이용하는 것은 위험하고 비합리적인 구매의사 결정이라고 볼 수 있다. 따라서 소비자가 좀 더 합리적인 구매의사결정을 하여 재정적 손실을 막기 위해서는 가격과 품질에 관한 신뢰있는 정보의 탐색이 반드시 필요하다고 본다.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.649-658
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• 2003

We propose a hierarchical architecture of ART2 Network for performance improvement and fast pattern classification model using fitness selection. This hierarchical network creates coarse clusters as first ART2 network layer by unsupervised learning, then creates fine clusters of the each first layer as second network layer by supervised learning. First, it compares input pattern with each clusters of first layer and select candidate clusters by fitness measure. We design a optimized fitness function for pruning clusters by measuring relative distance ratio between a input pattern and clusters. This makes it possible to improve speed and accuracy. Next, it compares input pattern with each clusters connected with selected clusters and finds winner cluster. Finally it classifies the pattern by a label of the winner cluster. Results of our experiments show that the proposed method is more accurate and fast than other approaches.