• Structural Engineering and Mechanics
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• v.63 no.2
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• pp.237-249
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• 2017

The Self-Organization Feature Map as an unsupervised network is very widely used these days in engineering science. The applied network in this paper is the Self Organization Feature Map with constant weights which includes Kohonen Network. In this research, Reinforced Concrete Shear Wall buildings with different stories and heights are analyzed and a database consisting of measured fundamental periods and characteristics of 78 RC SW buildings is created. The input parameters of these buildings include number of stories, height, length, width, whereas the output parameter is the fundamental period. In addition, using Genetic Algorithm, the structure of the Self-Organization Feature Map algorithm is optimized with respect to the numbers of layers, numbers of nodes in hidden layers, type of transfer function and learning. Evaluation of the SOFM model was performed by comparing the obtained values to the measured values and values calculated by expressions given in building codes. Results show that the Self-Organization Feature Map, which is optimized by using Genetic Algorithm, has a higher capacity, flexibility and accuracy in predicting the fundamental period.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.129-134
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• 2003

This paper describes an application level composition mechanism called Generic Modeling Environment(GME) for web caching on an Application Level Active Network(ALAN). Web caching on an ALAN requires the application level composition mechanism and a service composition to support adaptability for self-organization. ALAN was developed to solve the problems of the network level Active Network(AN) ALAN has the features of both AN as well as mobile agents. The efficient composition mechanism for the existing AN Projects has been supported primarily for the network level AN. Conversely, ALAN lacks support for the application level AN The existing web caching technology is inter-connected in a manually configured hierarchical tree. Since a self-organization system is intended to be adaptive, web caching for self-organization does not involve a manual configuration or any low-level tuning of the individual nodes of the entire system but requires service composition to support adapting intelligence and fault-tolerance to enable self-organization.

• Journal of IKEEE
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• v.23 no.3
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• pp.941-946
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• 2019

In this paper, the author analyzed the PCI (Physical Cell Identification) allocation methods in the LTE (Long Term Evolution) SON (Self Organization Network) environment. A variety of techniques have been proposed for how to allocate PCI, and the LTE standard fundamentally explained that collision between a cell and neighbor cells arise while a cell assign the PCI. Therefore, in this paper, the author examined the scenarios of PCI collision, weak collision, and confusion proposed by LTE specification. In addition, the cell central approach and the distributed approach were discussed as solutions for each scenario. In this paper, the author reviewed the approach of graphic coloring technique which was studied recently and explained the strategy of central approach.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1025-1030
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• 2019

This paper describes SON(: Self Organization Network) technology in LTE networks. The SON is a unique feature of LTE compared to previous cellular systems such as UMTS and GSM, and it is a tool that effectively derives the best performance in the time-varying wireless radio environment. Also, the SON has the ability for the operator to automate the setting of the network, allowing for centralized planning and reducing the need for manual work. The SON is largely divided into three categories: Self-Configuration, Self-Optimization, and Self-Healing. Each large categories has a detailed description of technology, and the technologies in each categories are gathered to complete the technology called the SON. In this paper, we focus on MRO which is one of the Self-Optimization technique in each of the three categories.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.196-201
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• 2018

Recently, various infrastructure-less IoT networking schemes have been studied to construct local IoT networks based on self-organization. This is, because RPL protocol, which is to support infrastructure based network construction is used to construct local IoT networks. Thus, a self-organization networking and ad hoc path between client and server in local IoT networks is not supported in basis RPL protocol. In this paper, we propose a self-organization networking scheme which support infrastructure-less based IoT network construction in low-power and lossy network based IoT environments consisting of IoT devices with the constrained feature, such as low power, the limited transmission rate and low computing capacity. Through simulation, we show that the proposed self-organization networking scheme improves the performance, in terms of the number of packets generated for end-to end data transmission and the end-to-end delay, compared to basis RPL protocol.

• Knowledge Management Research
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• v.16 no.2
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• pp.67-89
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• 2015

Improving productivity of knowledge workers is an important issue in the 21st century referred as knowledge-based society. The core key word is knowledge sharing among constituents of an organization. The purpose of this study is to combine the social network position factors with attitude and behavior factors, and develop an integrated research model for the knowledge sharing among members of an organization. This study adopted the integrated theoretical framework based on social capital, self-efficacy, transactive memory, and knowledge sharing. Surveys were conducted to 42 organizational members from a department in a leading IT outsourcing company to empirically test the proposed research model. In order to validate the proposed research model, social network analysis tool, UCINET, a structural equation modeling tool, SmartPLS, were utilized. The empirical result showed that, first of all, organizational members' familiarity network position had significant influence on knowledge self-efficacy and transactive memory capability. Second, knowledge self-efficacy and transactive memory capability affected knowledge sharing intention. Third, knowledge sharing intention also had an impact on the job performance. However, organizational members' expertise network position had no significant influence on knowledge self-efficacy and transactive memory capability. This finding reveals the importance of the emotional approach rather than the rational approach in knowledge management. The theoretical and practical implications on the research findings were discussed along with limitations.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.893-900
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• 2019

This paper deals with the analysis of SON (Self Organization Network) technology in LTE networks. SON is a unique LTE feature compared to previous cellular systems UMTS and GSM, and is a cost-effective tool for achieving the best performance in a changing environment. In addition, SON has the function of automating the settings of the network, enabling centralized planning and reducing the need for manual tasks. SON is largely divided into three categories: Self-Configuration, Self-Optimization, and Self-Healing. Each large category has a detailed description, and all the technologies in each category come together to complete the technology called SON. In this paper, we analyzed intensively about ANR among the techniques of Self-Configuration in each of the three categories.

• The Journal of Information Technology
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• v.8 no.1
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• pp.119-124
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• 2005

Learning procedure in the neural network is updating of weights between neurons. Unadequate initial learning coefficient causes excessive iterations of learning process or incorrect learning results and degrades learning efficiency. In this paper, adaptive learning algorithm is proposed to increase the efficient in the learning algorithms of Kohonens Self-Organization Neural networks. The algorithm updates the weights adaptively when learning procedure runs. To prove the efficiency the algorithm is experimented to clustering of the random weight. The result shows improved learning rate about 42~55% ; less iteration counts with correct answer.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.368-368
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• 2000

In this paper, we present forecasting ozone concentration with decision support system. Since the mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, modeling of ozone prediction system has many problems and results of prediction are not good performance so far. Forecasting ozone concentration with decision support system is acquired to information from human knowledge and experiment data. Fuzzy clustering method uses the acquisition and dynamic polynomial neural network gives us a good performance for ozone prediction with ability of superior data approximation and self-organization.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.602-603
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• 2018

최근 사물인터넷 환경에서는 다양한 서비스가 공존하고 있다. 특히 동일 지역 내에 다양한 서비스가 제공되고 있으며 서비스 별로 사물인터넷 디바이스가 구성되어 있다. 이런 네트워크 환경은 서비스 제공에 있어 비효율적이다. 따라서 본 논문에서는 서비스 중심의 사물인터넷 네트워크 구축을 위한 네트워킹 기법을 제안한다. 제안하는 기법은 사물인터넷 환경에서 Self-Organization IoT Network (S-IoTN) 기법을 활용한 서비스 중심 사물인터넷 네트워킹 기법이다. 제안하는 기법은 사물인터넷 서비스 제공에 필요한 제어메시지를 최소활 할 수 있는 기법으로 활용 가능하다.