• Journal of The Korean Association For Science Education
• /
• v.40 no.3
• /
• pp.347-358
• /
• 2020

He purpose of this study is to design and apply a pilot assessment tools for scientifically gifted and talented elementary school students with lower grades. The assessment tool consists of three parts: homeroom teachers' recommendation, paper and pencil test and performance tests. The tools are verified whether they are suitable for unique characteristics of young children and enable to attract active participation. For suitability check, students' performance tests were inductively analyzed and 30 behavioral patterns were shown which were included and partially exceeded the level of lower elementary students' performance expectation in NGSS. As a result, we concluded that assessment tool developed in this study will be effective in discriminating young pupils' scientific talents. Then for participation check, we compared the number of coding references as an indicator of participation. Two cases were found that students with high interest participated passively in performance tests. We found these 'passive participants' had excessive scientific experiences and extremely narrow region of interest, during the process of complex interpretation between the results of this assessment tool and in-depth interviews with homeroom teachers. We found out in this study that newly developed tools can be used in school scene after modifying and elaboration through accumulation of more case studies.

• Journal of the Economic Geographical Society of Korea
• /
• v.6 no.1
• /
• pp.1-20
• /
• 2003

This paper aims to examine the contribution that the ERVET System, composed of ERVET and real service centers, has made to both governing and enhancing regional innovation system in Emilia Romagna, Italy. ERVET and real service centers both establish and perform plans for regional development and innovation. But they also try to provide varieties of real services for local firms, mostly small and medium-sized firms. Attempting to promote innovation networks between industries, universities and administrative bodies, the ERVET System has become a core intermediary agency of Emilia Romagna in both governing regional innovation system and enhancing regional innovation capabilities. Based on the case of the ERVET System, we propose a policy recommendation. As local governments in Korea have still been less autonomous but hierarchical, it would be difficult for them to make the decision effectively on regional innovation and development initiatives. In this context, we suggest that regional development agencies need to be established on the basis of benchmarking advanced cases in Europe and North America such as the ERVET System.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.41 no.3
• /
• pp.200-209
• /
• 2013

In this paper, the types of B-dot controller and the review results of B-dot controller stability are summarized. Also, it is confirmed that B-dot controller is very useful and essential tool when a dawn-dusk low earth orbit(LEO) large satellite has especially to capture the Sun for a required power supply in a reliable way after anomaly and that its algorithm is very simple for on-board implementation. New physical interpretation of B-dot controller is presented as a result of extensive theoretical investigation introducing the concept of transient control torque and steady state control torque. Also, the failure effect analysis results of magnetic torquers as well as a simulation verification are included. And the design recommendation for optimal design is provided to cope with the failure of magnetic torquer. Nonlinear simulation results are included to justify its capability as well as its performance for an application to a dawn-dusk LEO large satellite.

• Journal of Intelligence and Information Systems
• /
• v.13 no.3
• /
• pp.119-140
• /
• 2007

Recommender systems enable a user to decide which information is interesting and valuable in our world of information overload. As the recent studies of distributed computing environment have been progressing actively, recommender systems, most of which were centralized, have changed toward a peer-to-peer approach. Collaborative Filtering (CF), one of the most successful technologies in recommender systems, presents several limitations, namely sparsity, scalability, cold start, and the shilling problem, in spite of its popularity. The move from centralized systems to distributed approaches can partially improve the issues; distrust of recommendation and abuses of personal information. However, distributed systems can be vulnerable to attackers, who may inject biased profiles to force systems to adapt their objectives. In this paper, we consider both effective CF in P2P environment in order to improve overall performance of system and efficient solution of the problems related to abuses of personal data and attacks of malicious users. To deal with these issues, we propose a multi-agent framework for a distributed CF focusing on the trust relationships between individuals, i.e. web of trust. We employ an agent-based approach to improve the efficiency of distributed computing and propagate trust information among users with effect. The experimental evaluation shows that the proposed method brings significant improvement in terms of the distributed computing of similarity model building and the robustness of system against malicious attacks. Finally, we are planning to study trust propagation mechanisms by taking trust decay problem into consideration.

• Journal of KIISE:Software and Applications
• /
• v.35 no.10
• /
• pp.608-615
• /
• 2008

In Knowledge Q&A services where information is created by unspecified users, document quality is an important factor of user satisfaction with search results. Previous work on quality prediction of Knowledge Q&A documents evaluate the quality of documents by using non-textual information, such as click counts and recommendation counts, and focus on enhancing retrieval performance by incorporating the quality measure into retrieval model. Although the non-textual information used in previous work was proven to be useful by experiments, data sparseness problem may occur when predicting the quality of newly created documents with such information. To solve data sparseness problem of non-textual features, this paper proposes new features for document quality prediction, namely text-confidence features, which indicate how trustworthy the content of a document is. The proposed features, extracted directly from the document content, are stable against data sparseness problem, compared to non-textual features that indirectly require participation of service users in order to be collected. Experiments conducted on real world Knowledge Q&A documents suggests that text-confidence features show performance comparable to the non-textual features. We believe the proposed features can be utilized as effective features for document quality prediction and improve the performance of Knowledge Q&A services in the future.

• Journal of Korean Society of Steel Construction
• /
• v.15 no.1
• /
• pp.1-8
• /
• 2003

In locations where the cost of concrete is relatively high or in situations where the weight of concrete members has to be kept to a minimum, it may be more economical to use hollow reinforced concrete vertic al members. Hollow reinforced concrete colun-ms with a low axial load, a moderate longitudinal steel percentage and a reasonably thick wall were found to perform in a ductile manner at the flexural strength, similar to solid columns. Hollow reinforced concrete columns with a high axial load, a high longitudinal steel percentage, and a thin wall were found, however, to behave in a brittle manner at the flexural strength, since the neutral axis is forced to occur away from the inside face of the tube towards the section centroid and, as a result, crushing of concrete occurs near the unconfined inside face of the section. If, however, a steel tube is placed near the inside face of a circular hollow column, the column can be expected not to fail in a brittle manner through the disintegration of the concrete in the compression zone. A design recommendation and example through the moment-curvature analysis program for curvature ductility are herein presented. A theoretical moment-curvature analysis for reinforced concrete columns, indicating the available flexural strength and ductility, can be conducted, providing that the stress-strain relation for the concrete and steel are known. In this paper, a unified stress-stain model for confined concrete by Mander is developed foi members with circular sections.

• Journal of KIISE:Databases
• /
• v.37 no.6
• /
• pp.343-350
• /
• 2010

We can get answers we want to know via questioning in Knowledge Search Service (KSS) based on Q&A Community. However, it is getting more difficult to find credible documents in enormous documents, since many anonymous users regardless of credibility are participate in answering on the question. In previous works in KSS, researchers evaluated the quality of documents based on textual information, e.g. recommendation count, click count and non-textual information, e.g. answer length, attached data, conjunction count. Then, the evaluation results are used for enhancing search performance. However, the non-textual information has a problem that it is difficult to get enough information by users in the early stage of Q&A. The textual information also has a limitation for evaluating quality because of judgement by partial factors such as answer length, conjunction counts. In this paper, we propose the QualityRank algorithm to improve the problem by textual and non-textual information. This algorithm ranks the relevant and credible answers by considering textual/non-textual information and user centrality based on Social Network Analysis(SNA). Based on experimental validation we can confirm that the results by our algorithm is improved than those of textual/non-textual in terms of ranking performance.

• KIISE Transactions on Computing Practices
• /
• v.23 no.3
• /
• pp.183-187
• /
• 2017

Smart phone users prefer fast reading and texting. Hence, users frequently use abbreviated sequences of words and phrases. Nowadays, abbreviations are widely used from chat terms to technical terms. Therefore, gathering abbreviations would be helpful to many services, including information retrieval, recommendation system, and so on. However, manually gathering abbreviations needs to much effort and cost. This is because new abbreviations are continuously generated whenever a new material such as a TV program or a phenomenon is made. Thus it is required to generate of abbreviations automatically. To generate Korean abbreviations, the existing methods use the rule-based approach. The rule-based approach has limitations, in that it is unable to generate irregular abbreviations. Another problem is to decide the correct abbreviation among candidate abbreviations generated rules. To address the limitations, we propose a method of generating Korean abbreviations automatically using sequence-to-sequence learning in this paper. The sequence-to-sequence learning can generate irregular abbreviation and does not lead to the problem of deciding correct abbreviation among candidate abbreviations. Accordingly, it is suitable for generating Korean abbreviations. To evaluate the proposed method, we use dataset of two type. As experimental results, we prove that our method is effective for irregular abbreviations.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.1-23
• /
• 2011

The contextual subjective well-being (SWB) of context-aware system users can be very helpful in recommending relevant mental health services, especially for those who struggle with mental illness due to a metabolic syndrome or melancholia. Self-surveying measuring or auto-sensing methods have been suggested to monitor users' SWB. However, self-surveying measuring method is not inappropriate for a context-aware service due to requesting personal data in a manual and hence obtrusive manner. Moreover, auto-sensing methods still suffer from accuracy problem to be applied in mental health services. Hence, the purpose of this paper is to propose a contextual SWB estimation method to estimate the user's mental health in unobtrusive and accurate manners. This method is timely in that it acquires context data from the user's literal responses, which expose their temporal feeling. In particular, we developed a measuring method based on exposed feeling verbs and degree adverbs in chat and other text-based communications which show anger or negative feelings. Based on the proposed contextual SWB degree estimation method, we developed an idea of well-being life care recommendation. From the experiment with actual drivers, we demonstrated that the proposed method accurately estimate the user's degree of negative feelings even though it does not require a self-survey.

• Journal of KIISE:Software and Applications
• /
• v.35 no.12
• /
• pp.764-773
• /
• 2008

The web ontology language(OWL) has become a W3C recommendation to publish and share ontologies on the semantic web. In order to check the satisfiablity of concepts in OWL ontology, OWL reasoners have been introduced. But most reasoners simply report check results without providing a justification for any arbitrary entailment of unsatisfiable concept in OWL ontologies. In this paper, we propose dependency label based causing inconsistency axiom (CIA) detection for debugging unsatisfiable concepts in ontology. CIA is a set of axioms to occur unsatisfiable concepts. In order to detect CIA, we need to find axiom to cause inconsistency in ontology. If precise CIA is gave to ontology building tools, these ontology tools display CIA to debug unsatisfiable concepts as suitable presentation format. Our work focuses on two key aspects. First, when a inconsistency ontology is given, it detect axioms to occur unsatisfiable and identify the root of them. Second, when particular unsatisfiable concepts in an ontology are detected, it extracts them and presents to ontology designers. Therefore we introduce a tableau-based decision procedure and propose an improved method which is dependency label based causing inconsistency axiom detection. Our results are applicable to the very expressive logic SHOIN that is the basis of the Web Ontology Language.