• 대한약학회:학술대회논문집
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• 대한약학회 2003년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.1
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• pp.77-77
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• 2003

p43 is a protein with complex biological activities. It is first found as a protein associated with macromolecular tRNA synthetase complex. Within this complex, p43 specifically interacts with arginyl-tRNA synthetase to help the substrate tRNA binding to the enzyme. It is also necessary for the cellular stability of arginyl-tRNA synthetase and the molecular association of a few complex-forming tRNA synthetases. (omitted)

• 한국지능시스템학회논문지
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• 제14권1호
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• pp.9-14
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• 2004

감정은 지능을 지닌 존재의 이성판단에 영향을 준다. 그래서 주변 환경정보에 의해 평가된 기본적이고 보편적인 감정을 로봇에 가미하면 더욱 인간과 가까운 지능 로봇이 될 것이다. 그러나 인간의 감정을 학습하기 위해서는 다양한 감각정보의 학습과 패턴 분류가 선행되어야 하고 이를 위해서 적합한 네트워크 구조가 요구된다. 신경망은 시스템의 특징을 추출하는데 매우 우수한 능력을 발휘하고 있다. 그러나 임시적 혼선현상과 지역 최소치에 수렴하는 단점이 있다. 그래서 복잡한 문제를 단순한 여러 개의 부분적인 문제로 나누어 해결하는 모듈라 설계방법이 관심의 대상이 되고 있다. 본 논문에서는 수많은 감정평가와 학습 데이터 패턴들을 학습하기 위해서 재결합과 재구성에 탁월한 성능을 지닌 Jacobs와 Jordan이 제안한 모듈라 네트워크와 상황의 재 표현이 가능하고 예측값과 모델링에 적합한 특징을 지닌 궤환 신경망을 결합하였다. 구성된 구조는 기존의 모듈라 네트워크의 학습결과와 비교 검토하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권8호
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• pp.2030-2052
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• 2023

Analysis of a bipartite (two-mode) network is a significant research area to understand the formation of social communities, economic systems, drug side effect topology, etc. in complex information systems. Most of the previous works talk about a projection-based model or latent feature model, which predicts the link based on singular similarity. The projection-based models suffer from the loss of structural information in the projected network and the latent feature is hardly present. This work proposes a novel method for link prediction in the bipartite network based on an ensemble of composite similarities, overcoming the issues of model-based and latent feature models. The proposed method analyzes the structure, neighborhood nodes as well as latent attributes between the nodes to predict the link in the network. To illustrate the proposed method, experiments are performed with five real-world data sets and compared with various state-of-art link prediction methods and it is inferred that this method outperforms with ~3% to ~9% higher using area under the precision-recall curve (AUC-PR) measure. This work holds great significance in the study of biological networks, e-commerce networks, complex web-based systems, networks of drug binding, enzyme protein, and other related networks in understanding the formation of such complex networks. Further, this study helps in link prediction and its usability for different purposes ranging from building intelligent systems to providing services in big data and web-based systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1437-1459
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• 2020

Wireless Sensor Networks (WSN) is a distributed Sensor network whose terminals are sensors that can sense and check the environment. Sensors are typically battery-powered and deployed in where the batteries are difficult to replace. Therefore, maximize the consumption of node energy and extend the network's life cycle are the problems that must to face. Low-energy adaptive clustering hierarchy (LEACH) protocol is an adaptive clustering topology algorithm, which can make the nodes in the network consume energy in a relatively balanced way and prolong the network lifetime. In this paper, the novel multi-objective LEACH protocol is proposed, in order to solve the proposed protocol, we design a multi-objective coupling algorithm based on bat algorithm (BA), glowworm swarm optimization algorithm (GSO) and bacterial foraging optimization algorithm (BFO). The advantages of BA, GSO and BFO are inherited in the multi-objective coupling algorithm (MBGF), which is tested on ZDT and SCH benchmarks, the results are shown the MBGF is superior. Then the multi-objective coupling algorithm is applied in the multi-objective LEACH protocol, experimental results show that the multi-objective LEACH protocol can greatly reduce the energy consumption of the node and prolong the network life cycle.

• Journal of the Korean Physical Society
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• 제73권10호
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• pp.1589-1595
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• 2018

Similarity index measures the topological proximity of node pairs in a complex network. Numerous similarity indices have been defined and investigated, but the dependency of structure on the performance of similarity indices has not been sufficiently investigated. In this study, we investigated the relationship between the performance of similarity indices and structural properties of a network by employing a two-state random network. A node in a two-state network has binary types that are initially given, and a connection probability is determined from the state of the node pair. The performances of similarity indices are affected by the number of links and the ratio of intra-connections to inter-connections. Similarity indices have different characteristics depending on their type. Local indices perform well in small-size networks and do not depend on whether the structure is intra-dominant or inter-dominant. In contrast, global indices perform better in large-size networks, and some such indices do not perform well in an inter-dominant structure. We also found that link prediction performance and the performance of similarity are correlated in both model networks and empirical networks. This relationship implies that link prediction performance can be used as an approximation for the performance of the similarity index when information about node type is unavailable. This relationship may help to find the appropriate index for given networks.

• 한국콘텐츠학회논문지
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• 제12권4호
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• pp.476-484
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• 2012

조선 역대 왕의 가계에 등장하는 인물로 구성된 네트워크를 구축하고 분석한 결과, 일반적인 사회 네트워크와 같은 척도 없는 네트워크를 보여주고 있다. 조선왕조 가계 인물 네트워크가 비록 척도 없는 네트워크이지만 네트워크의 지름이 다른 사회 네트워크에 비해 비교적 큰데, 왕조 가계 인물 네트워크는 한 왕에서 다음 왕으로 이어지는 연속적인 특성이 반영된 것이다. K-코어 알고리즘을 도입하여 복잡한 네트워크를 단순화시킬 경우, 복잡한 네트워크에서는 발견하지 못하는 숨겨진 정보를 얻을 수 있는데, 왕조 가계 네트워크에서는 특별한 정보를 얻지 못하였다. 비교적 네트워크의 지름이 크고 길게 이어지는 네트워크에는 k-코어 알고리즘이 적합하지 못함을 의미한다. 단순한 네트워크 구축을 위해 가계 인물 네트워크를 구성하고 있는 소단위 네트워크 즉, 황후, 후궁, 공주나 옹주, 대군이나 군 중심의 네트워크를 구축하여 단순화시키고 그로부터 유용한 정보를 얻고자 하였다. 본 연구에서 복잡한 네트워크의 경우, 데이터베이스에서 분류 가능한 소단위 네트워크를 구축하여 유용한 정보를 도출하는 것도 복잡한 네트워크를 단순화하여 유용한 정보를 도출하는 방법이 될 수 있음을 제시한다. 동시에 역사적인 사실의 정보를 네트워크 관점에서 얻을 수 있음을 본 연구는 제시하고 있다.

• 한국시뮬레이션학회논문지
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• 제3권1호
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• pp.75-88
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• 1994

Discrete event modeling is finding ever more application to anlysis and design of complex manufacturing, communication, computer systems, etc. This paper shows how packet network systems may be advantageously represented as DEVS (Discrete Event System Specification) models by employing System Entity structure / Model base (SES/MB) framework developed by Zeigler. DEVS models and network structure representations support a strong basis for performance analysis of packet network systems. This approach is illustated in a typical packet network example with several routing strategies.

• 대한전기학회논문지
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• 제37권9호
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• pp.663-670
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• 1988

Advances in VLSI technology have made it possible to have a larger number of processing elements to be included in highly parallel processor system. A system with a large number of processing elements and memory requires a complex data path. Multistage Interconnection networks(MINS) are useful in providing programmable data path between processing elements and memory modules in multiprocessor system. In this thesis, the performance of MINS for the star network has been analyzed and compared with other networks, such as generalized shuffle network, delta network, and referenced crossbar network.

• 한국국방경영분석학회지
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• 제27권1호
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• pp.1-9
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• 2001

In this paper, "a conceptual model of Reconnaissance-Strike-Logistics Complex(RSLC) in future warfare" is proposed. Basic idea of the RSLC model is to combine logistics and the pre-existing Reconnaissance-Strike Complex(RSC) through a C4 network system. That is, the RSLC model consists of reconnaissance, strike, logistics, and C4 network systems. The C4 network system creates new combat power by integrating all the other systems. The RSLC model generates three conceptual complex circles; the RSC, the SLC(Strke-Logistics Complex), and the RSLC circles. The RSC circles describes direct combat behaviors in the battlefield. On the other hand, the SLC circle indicates combat sustainment capabilities. The RSLC circle including the RSC and the SLC circles, can present a more complete combat process. There are two key advantages of the RSLC model. First of all, logistics is considered one of key combat components to form IDA(Information-Decision-Action) cycle for combat decision-making process more completely. Secondly, the capabilities of battlefield awareness which reconnaissance and war-net systems provide, can be applied not only to the strike system in the RSC circle, but also to the logistics system in the SLC circle. Thus, the RSLC model can maximize combat synergy effects by integrating the RSC and the SLC. With a similar logic, this paper develops "A Revised System of Systems with Logistics (RSSL)" which combines "A New system of Systems" and logistics. These tow models proposed here help explain several issues such as logistics environment in future warfare, MOE(Measure of Effectiveness( on logistics performance, and COA(Course of Actions) for decreasing mass and increasing velocity. In particular, velocity in logistics is emphasized.

• 한국통신학회논문지
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• 제25권3A호
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• pp.375-382
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• 2000

Equalization of satellite communication using Complex-Bilinear Recurrent Neural Network(C-BLRNN) is proposed in this pater. Since the BLRNN is based on the bilinear polynomial and it has been more effectively used in modeling highly nonlinear systems with time-series characteristics than multi-layer perception type neural networks(MLPNN) , it can be applied to satellite equalizer. the proposed C-BLRNN based equalizer for M-PSK with a channel model is compared with Volterra filter Equalizer, DFE, and conventional Complex MLPNN Equlizer. The results show that the proposed C-BLRNN based equalizer gives very favorable results in both of MSE and BER criteria over other equalizers.