• Journal of the Korean School Mathematics Society
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• v.16 no.4
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• pp.745-770
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• 2013

In the knowledge-based society today, most knowledge is the integrated one which is difficult to be classified into subjects rather than the knowledge of a single subject. Thus, integrated thinking, which integrated knowledge is preferentially acquired first and then can be also associated with imagination and artistic sensitivity, is simultaneously required in order that we have a problem-solving capability in our daily life. STEAM education(science, technology, engineering, arts and mathematics) is one of the educational methods to improve this problem-solving capability as well as integrated thinking. This research developed materials for STEAM education which can be applied to the 6th grade curriculum of elementary school mathematics, then input it, and analyzed how it impacts with students' attitudes toward mathematics. Unit 3 'Prism' and Pyramid' were restructured and replaced by classes such as 'Spaghetti Project' or 'Paper Craft'. Unit 4 'Several Solid Figure' was taught as a class of 'EDUCUBE'. Unit 6 'Proportional Graph' was taught as a class of 'Creating my own bracelet'. After having this class, we found that mathematics class applied STEAM also has a positive effect on the mathematical attitude of students. Many students said that math is fun and gets more interesting after having math class applied STEAM and we come to know that they have positive awareness of mathematics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2781-2800
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• 2016

Emerging attacks aim to access proprietary assets and steal data for business or political motives, such as Operation Aurora and Operation Shady RAT. Skilled Intruders would likely remove their traces on targeted hosts, but their network movements, which are continuously recorded by network devices, cannot be easily eliminated by themselves. However, without complete knowledge about both inbound/outbound and internal traffic, it is difficult for security team to unveil hidden traces of intruders. In this paper, we propose an autonomous anomaly detection system based on behavior profiling and relation mining. The single-hop access profiling model employ a novel linear grouping algorithm PSOLGA to create behavior profiles for each individual server application discovered automatically in historical flow analysis. Besides that, the double-hop access relation model utilizes in-memory graph to mine time-sequenced access relations between different server applications. Using the behavior profiles and relation rules, this approach is able to detect possible anomalies and violations in real-time detection. Finally, the experimental results demonstrate that the designed models are promising in terms of accuracy and computational efficiency.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.425-429
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• 2018

지식 그래프는 많은 수의 개채와 이들 사이의 관계를 저장하고 있기 때문에 많은 연구에서 중요한 자원으로 활용된다. 최근에는 챗봇과 질의응답과 같은 연구에서 자연어 생성을 위한 연구에 활용되고 있다. 특히 자연어 생성에서 최근 발전 된 심층 신경망이 사용되고 있는데, 이러한 방식은 모델 학습을 위한 많은 양의 데이터가 필요하다. 즉, 심층신경망을 기반으로 지식 그래프에서 문장을 생성하기 위해서는 많은 트리플과 문장 쌍 데이터가 필요하지만 학습을 위해 사용하기엔 데이터가 부족하다는 문제가 있다. 따라서 본 논문에서는 데이터 부족 문제를 해결하기 위해 핵심어 시퀀스를 추출하여 학습하는 방법을 제안하고, 학습된 모델을 통해 트리플을 입력으로 하여 자연어 문장을 생성한다. 부족한 트리플과 문장 쌍 데이터를 대체하기 위해 핵심어 시퀀스를 추출하는 모듈을 사용해 핵심어 시퀀스와 문장 쌍 데이터를 생성하였고, 순환 신경망 기반의 인코더 - 디코더 모델을 사용해 자연어 문장을 생성하였다. 실험 결과, 핵심어 시퀀스와 문장 쌍 데이터를 이용해 학습된 모델을 이용해 트리플에서 자연어 문장 생성이 원활히 가능하며, 부족한 트리플과 문장 쌍 데이터를 대체하는데 효과적임을 밝혔다.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.1-6
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• 2006

The prediction of protein function basically make use of a protein-protein interaction map based on the concept of guilt-by-association. The method however cannot determine the functions of proteins in case that the target protein does not interact with proteins with known functions directly. This paper studies protein function prediction considering the given problem as a K-class classification problem and proposes a predictive approach utilizing a modular neural network. The proposed method uses interaction data and protein related attributes as well. The experimental results demonstrate that the proposed approach can predict the functional roles of Yeast proteins whose interaction knowledge is not known and shows better performance than the graph-based models that use protein interaction data.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.144-147
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• 2015

Question Answering (QA) services can provide exact answers to user questions written in natural language form. This research focuses on how to build a QA system for a specific domain area. Online and offline QA system architecture of targeted domain such as domain detection, question analysis, reasoning, information retrieval, filtering, answer extraction, re-ranking, and answer generation, as well as data preparation are presented herein. Test results with an official Frequently Asked Question (FAQ) set showed 68% accuracy of the top 1 and 77% accuracy of the top 5. The contribution of each part such as question analysis system, document search engine, knowledge graph engine and re-ranking module for achieving the final answer are also presented.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.147-158
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• 1996

This paper proposed a concurrency control structure based on specialized data flow graphs that was analysed a run-time concurrency control activity to be integrated with the task scheduler Data were viewed as flowing on the arcs from one node to another in a stream of discrete to tokens. The network that Is based upon the Entity-Relationship model, can be viewed a fixed problems used query tokens as a data flow graph. The performance was measured used in the various expriments compared the overall performance of the different concurrency control methods, DBFG (DataBase Flow graphs) scheduling had the knowledge to obtain better performance than 2PL in a distributed environment.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.1
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• pp.17-23
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• 2004

This paper proposes to determine word senses in Korean language processing by corpus-based ontology learning. Our approach is a hybrid method. First, we apply the previously-secured dictionary information to select the correct senses of some ambiguous words with high precision, and then use the ontology to disambiguate the remaining ambiguous words. The mutual information between concepts in the ontology was calculated before using the ontology as knowledge for disambiguating word senses. If mutual information is regarded as a weight between ontology concepts, the ontology can be treated as a graph with weighted edges, and then we locate the least weighted path from one concept to the other concept. In our practical machine translation system, our word sense disambiguation method achieved a 9％ improvement over methods which do not use ontology for Korean translation.

• Education of Primary School Mathematics
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• v.16 no.3
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• pp.193-209
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• 2013

This study was designed to identify how teachers and students solve problems and communicate with each other during the course of study through application of PBL questions that can be utilized in math ratio and graph sections of the 6th-grade elementary school curriculum in class. Therefore we haved figure it out that through pbl class student acquired a propound knowledge in math and showed self-directed learning through various communication activities, and that they finally showed positive attitude and confidence in this subject.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3211-3230
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• 2014

Recently, sparse coding has achieved remarkable success in image representation tasks. In practice, the performance of clustering can be significantly improved if limited label information is incorporated into sparse coding. To this end, in this paper, a novel semi-supervised algorithm, called constrained sparse concept coding (CSCC), is proposed for image representation. CSCC considers limited label information into graph embedding as additional hard constraints, and hence obtains embedding results that are consistent with label information and manifold structure information of the original data. Therefore, CSCC can provide a sparse representation which explicitly utilizes the prior knowledge of the data to improve the discriminative power in clustering. Besides, a kernelized version of our proposed CSCC, namely kernel constrained sparse concept coding (KCSCC), is developed to deal with nonlinear data, which leads to more effective clustering performance. The experimental evaluations on the MNIST, PIE and Yale image sets show the effectiveness of our proposed algorithms.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.27-38
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• 2019

Sensors collect information for Internet of Things (IoT)-based services. However, indoor construction sites have a poor communication environment and many interfering elements that make it difficult to collect sensor information. In this study, a network was constructed between a Bluetooth Low Energy (BLE)-based IoT device based on a serverless IoT framework and a router. This experimental environment was applied to large- and small-scale indoor construction sites. Experiments were performed to test the communication performance of BLE-based IoT devices and routers at indoor construction sites. An analysis of the received signal strength indication (RSSI) graph patterns collected from the communication between the BLE-based IoT devices and routers for different testbed site situation revealed areas with good communication performance and poor communication performance due to interfering factors. The results confirmed that structural components of the building as well as the materials, equipment, and temporary facilities used in indoor construction interfere with the communication performance. Construction project managers will require improved technical knowledge of IoT, such as optimizing the router placement and matching communication between the router and workers, to improve the communication performance for large-scale indoor construction.