• Annual Conference on Human and Language Technology
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• 2005.10a
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• pp.21-27
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• 2005

본 논문에서는 국가에서 추진하는 차세대신성장동력산업과 관련된 특정 분야('바이오 신약/장기' 분야 중 '면역 기능 제어')를 선택하여, 기구축된 면역학 전문용어사전을 비롯하여 의학용어사전, 표준국어대사전 등을 참조하여 핵심 용어와 관련 용어를 중심으로 면역학 시소러스(어휘 3,462개) 및 온톨로지(개념 노드 4,703개)를 구축하였다. 이것은 전문용어사전부터 온톨로지에 이르기까지 통일화된 표준 체계를 가지고 있으며, 도메인 온톨로지를 구축하여 향후 온톨로지 개발 방향을 설정할 수 있는 계기가 되었다고 할 수 있다. 또한 면역학 시소러스는 검색의 성능을 향상시킬 수 있도록 충분한 양의 데이터를 구축하였고 면역학 온톨로지는 언어처리적 관점에서의 온톨로지를 표현하였다. 이는 정보검색에서의 효율성을 비롯하여, 특정 웹 온톨로지 언어를 이용한 웹 온톨로지로의 변환성, 대규모 도메인 온톨로지라는 점에서 의미를 가진다고 할 수 있다.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.1-7
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• 2020

The demand on the underwater communications is extremely increasing in searching for underwater resources, marine expedition, or environmental researches, yet there are many problems with the wireless communications because of the characteristics of the underwater environments. Especially, with the underwater wireless networks, there happen inevitable delay time and spacial inequality due to the distances between the nodes. To solve these problems, this paper suggests a new solution based on ALOHA-Q. The suggested method use random NAV value. and Environments take reward through communications success or fail. After then, The environments setting NAV value from reward. This model minimizes usage of energy and computing resources under the underwater wireless networks, and learns and setting NAV values through intense learning. The results of the simulations show that NAV values can be environmentally adopted and select best value to the circumstances, so the problems which are unnecessary delay times and spacial inequality can be solved. Result of simulations, NAV time decreasing 17.5% compared with original NAV.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.2
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• pp.29-34
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• 2008

In this paper, we proposed a system protocol for detecting injurious insect to support energy saving transmission in wireless bio sensor networks. The main ideas and features of the system are as follows. First, the route establishment method which is based on the energy efficiency and stability by using time-division tree structure. Second, multi-hop direction-based data gatering structure. In this structure, the selected fading method is used to transmit packet via the established tree structure for supporting power saving and route lifetime efficiently. Finally, we can get the node power saving and reduce transmission delay, thus network lifetime and efficiency are improved. The performance evaluation of the proposed protocol is via OPNET(Optimized Network Engineering Tool).

• 한국HCI학회:학술대회논문집
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• 2006.02b
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• pp.377-382
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• 2006

본 연구의 주제는 정보의 관계를 사용자 중심으로 시각화하는 것이다. 생활속에서 제공되는 대부분의 정보들은 보이지 않는 연결성을 가지고 있다. 이런 정보들의 공통적인 특성 및 관계의 연구를 통해 정보의 중요도를 측정할 수 있고, 각 정보의 개체 간의 연결성이 형성되어 인접정보의 접근이 용이해진다. 특히 인간관계는 사회 연결망의 주된 관심사이며, 사회의 각 개체 간 관계를 분석하여 도식화하는 여러 방법론이 제시되어 있다. 이번 연구를 위하여 제한된 사회라고 볼 수 있는 그리스 신화를 소재로 선정하여 등장인물들 간의 관계를 파악하는데 사회연결망 이론을 적용하였다. 하지만 시각화 측면에서 볼 때 현재 제공되는 사회 연결망 분석 도구는 사용자를 고려한 디자인 부분이 배제되어 단순히 정보를 일방적으로 보여준다는 한계를 지니고 있다. 미톨로지아에서는 분석된 자료를 바탕으로 사용자가 정보를 파악하는데 좀더 효과적이고 용이한 시각적인 구성을 가질 수 있도록 시도했다. 사회 연결망 분석법으로 그리스 신화의 인물들이 가진 신분, 출현 빈도, 감정관계 등을 수치화하여 인물의 연결성을 분석하였다. 또한 정보와 사용자 간의 상호작용 기능을 제공함으로써 사용자의 이해도를 높였다. 기본 인터페이스는 인물노드에 쉽게 접근할 수 있도록 4 가지 분류에 의한 인덱스의 형태를 가지며, 인물 간의 세밀한 관계는 선택에 의한 줌-인(zoom in) 기능을 통해 볼 수 있다. 이는 기존의 필터링 기능과는 차별적인 요소로서 직접 관련된 정보 이외의 정보들은 시각적으로 제한되어 사용자가 인물 관계를 빠르고 직관적으로 파악할 수 있다. 미톨로지아는 개괄적인 관계를 보여주는 레이아웃과 부분적이며 상세한 정보를 파악하기에 적합한 인터랙션 방법을 제시한다.

• Journal of Internet Computing and Services
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• v.3 no.2
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• pp.79-85
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• 2002

In open communication architecture, application systems consist of objects distributed in lots of computing nodes. To reduce complexity of development. and management of distributed software, to manage efficiently distributed objects and to provide realtime service, the mechanisms for object group management and communication are needed in distributed environment. In this paper we compose object groups and provide reliable group communication mechanism based on CORBA which can adopt a new service without lots of changes on existing system. Group consist of some subgroups that subgroup manager manages for improving the efficiency of group management and message ordering is kept by using sequencer, Communication method among groups uses multicast based on paint to point communication as well as IP multicast and we provide high performance by using selective retransmission of message through message history, We analyze the performance of the proposed mechanism through simulation in distributed environment.

• Journal of Information Management
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• v.19 no.1
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• pp.1-29
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• 1988

The purpose of this study is to investigate a decision making support system for the effective information management. Decision making theory is reviewed and problems are discussed. A model is suggested through the computing of expected monetary value in decision tree technique. The expected monetary value is computed by 1 inking the probability theory with chance node. The selection of right expected monetary value and expected value of perfect information will make great advance the present system. It is concluded that expected monetary value and expected value of perfect information in decision tree techniques will make great aids to advance information management system.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.9
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• pp.1-10
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• 1998

This paper is to propose an algorithm named as DYSAC to find the critical path(the longest sensitizable path) in a large digital circuit, whose purpose is to reduce the time to find critical path and to find critical paths of the circuits for which the previous methods could not find one. Also a set of path sensitization criteria named as DYPSEC is proposed, which is used to select a path from input to the output inside the DYSAC. The DYSAC consists of two sub-algorithms; the level assignment algorithm to assign a level to each node and the critical path selection algorithm to select the sensitizable path. The proposed algorithm was implemented with C-language on SUN Sparc and applied to the ISCAS'85 benchmark circuits to make sure if it works correctly and finds the correct critical path. Also, the results from the experiments were compared to the results from the previous works. The comparison items were the ability to find the critical path and the speed, in both of which the proposed algorithm in this paper shows better results than others.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1275-1282
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• 2014

Too much information exists in ubiquitous environment, and therefore it is not easy to obtain the appropriately classified information from the available data set. Decision tree algorithm is useful in the field of data mining or machine learning system, as it is fast and deduces good result on the problem of classification. Sometimes, however, a decision tree may have leaf nodes which consist of only a few or noise data. The decisions made by those weak leaves will not be effective and therefore should be excluded in the decision process. This paper proposes a method using a classifier, UChoo, for solving a classification problem, and suggests an effective method of decision process involving only the important leaves and thereby excluding the noisy leaves. The experiment shows that this method is effective and reduces the erroneous decisions and can be applied when only important decisions should be made.

• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.137-140
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• 2003

Recently, CG (Conjugate Gradient) scheme for the optimization of the Rayleigh quotient has been proven a very attractive and promising technique for interior eigenvalues for the following eigenvalue problem, Ax＝λx (1) The given matrix A is assummed to be large and sparse, and symmetric. Also, the method is very amenable to parallel computations. A proper choice of the preconditioner significantly improves the convergence of the CG scheme. We compare the parallel preconditioners for the computation of the interior eigenvalues of a symmetric matrix by CG-type method. The considered preconditioners are Point-SSOR, ILU (0) in the multi-coloring order, and Multi-Color Block SSOR (Symmetric Succesive OverRelaxation). We conducted our experiments on the CRAY­T3E with 128 nodes. The MPI (Message Passing Interface) library was adopted for the interprocessor communications. The test matrices are up to $512{\times}512$ in dimensions and were created from the discretizations of the elliptic PDE. All things considered the MC-BSSOR seems to be most robust preconditioner.