• 한국산업정보학회논문지
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• 제19권6호
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• pp.97-106
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• 2014

기업은 조직내에서 공유되고 사용되는 지식을 경쟁우위와 직결된 지적자본으로 인식하고 있다. 이에 따라 많은 선행연구에서 지식근로자 사이에 공유되는 지식을 파악하고자 노력하였다. 선행 연구의 한 가지 접근법은 정보기술을 이용하여 자동화되고 효율적으로 명시적인 지식을 공유하는 기술적인 방법을 강조하는 접근법이며 다른 접근법은 지식근로자간 휴먼 네트워크를 이용하여 암묵적인 지식의 흐름을 파악하고자 하는 연구이다. 두 번째 접근법의 경우 지식공유를 위해 실행공동체의 역할이 강조되고 있으나 자발적인 참여가 아닌 경우 실행공동체를 파악하기 힘들다는 단점이 있다. 본 연구에서는 휴먼 네트워크를 사회연결망 관점에서 파악하여 지식의 전파를 분석하고 실행공동체에 참여할 수 있는 지식근로자를 찾아내는 방법을 제안하고자 한다. 이를 위해 두 가지 사회연결망 관련 지표를 이용하여 지식 근로자를 분류하는 프레임워크를 제시하고 실무적용 가능성을 확인한 결과를 제시하고자 한다.

• 한국경영정보학회:학술대회논문집
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• 한국경영정보학회 2008년도 춘계학술대회
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• pp.270-275
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• 2008

The various research on Communities of practices (CoP) for propagation of softer type knowledge in new Knowledge Management (KM) strategy having been performed for past couple of years. CoP is one of effective process innovation tool for diffusion of knowledge. Based on CoP's voluntary and spontaneous characteristic, it performs a function of delivering softer type knowledge of workers to the other colleagues of organization. But one step further to CoP's function of propagation of internal knowledge, research on function of CoP's contribution in enterprise strategy are insufficient yet. This paper presents enterprise CoP should be managed and aligned to strategic objectives of enterprise, and also, suggests the methodology for CoPs to maintain a lifecycle as a tool to contribute in strategic goal attainment. Although CoPs are voluntary and spontaneous informal organization, it can display a contribution as tool for KM strategy when it is aligned to strategy properly and form efficient lifecycle.

• 전자공학회논문지B
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• 제31B권7호
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• pp.119-128
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• 1994

In this paper, we propose a method for facial feature extraction and recognition algorithm using neural networks. First we extract a face part from the background image based on the knowledge that it is located in the center of an input image and that the background is homogeneous. Then using vertical and horizontal projections. We extract features from the separated face image using knowledge base of human faces. In the recognition step we use the back propagation algorithm of the neural networks and in the learning step to reduce the computation time we vary learning and momentum rates. Our technique recognizes 6 women and 14 men correctly.

• International Journal of Reliability and Applications
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• 제10권1호
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• pp.1-15
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• 2009

Even though the impact of manufacturing quality to reliability is not considered much as well as that of design area, a major cause of an early failure of the product is known as manufacturing problem. This research applies two different types of neural network algorithms, the Back propagation (BP) algorithm and Learning Vector Quantization (LVQ) algorithm, to identify and classify the nonrandom variation pattern on the control chart based on knowledge-based diagnosis of dimensional variation. The performance and efficiency of both algorithms are evaluated to choose the better pattern recognition system for auto body assembly process. To analyze hundred percent of the data obtained by Optical Coordinate Measurement Machine (OCMM), this research considers an application in which individual observations rather than subsample means are used. A case study for analysis of OCMM data in underbody assembly process is presented to demonstrate the proposed knowledge-based pattern recognition system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4405-4418
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• 2016

Automatic image completion techniques have difficulty processing images in which the target region has multiple planes or is non-facade. Here, we propose a new image completion method that uses belief propagation based on planar priorities. We first calculate planar information, which includes planar projection parameters, plane segments, and repetitive regularity extractions within the plane. Next, we convert this planar information into planar guide knowledge using the prior probabilities of patch transforms and offsets. Using the energy of the discrete Markov Random Field (MRF), we then define an objective function for image completion that uses the planar guide knowledge. Finally, in order to effectively optimize the MRF, we propose a new optimization scheme, termed Planar Priority-belief propagation that includes message-scheduling-based planar priority and dynamic label cropping. The results of experiment show that our approach exhibits advanced performance compared with existing approaches.

• Journal of Communications and Networks
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• 제15권6호
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• pp.547-558
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• 2013

Ultra broadband communication systems operated at THz frequencies will require the thorough knowledge of the propagation channel. Therefore, an extensive measurement campaign of 50 GHz wide indoor radio channels is presented for the frequencies between 275 and 325 GHz. Individual ray paths are resolved spatially according to angle of arrival and departure. A MIMO channel is recorded in a $2{\times}2$ configuration. An advanced frequency domain ray tracing approach is used to deterministically simulate the THz indoor propagation channel. The ray tracing results are validated with the measurement data. Moreover, the measurements are utilized for the calibration of the ray tracing algorithm. Resulting ray tracing accuracies are discussed.

• Steel and Composite Structures
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• 제31권6호
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• pp.641-653
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• 2019

In this paper, wave propagation is studied and analyzed in double-layered nanotubes systems via the nonlocal strain gradient theory. To the author's knowledge, the present paper is the first to investigate the wave propagation characteristics of double-layered porous nanotubes systems. It is generally considered that the material properties of nanotubes are related to the porosity and hygro-thermal effects. The governing equations of the double-layered nanotubes systems are derived by using the Hamilton principle. The dispersion relations and displacement fields of wave propagation in the double nanotubes systems which experience three different types of motion are obtained and discussed. The results show that the phase velocities of the double nanotubes systems depend on porosity, humidity change, temperature change, material composition, non-local parameter, strain gradient parameter, interlayer spring, and wave number.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 1997년도 International Symposium on Fire Science and Technology
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• pp.252-259
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• 1997

A method to automate hazard analysis of chemical plants is proposed in this paper. The proposed system is composed of three knowledge bases - unit knowledge base, organizational knowledge base and material knowledge base, and three hazard analysis algorithms - deviation, malfunction and accident analysis algorithm. Hazard analysis inference procedure is developed based on the actual hazard analysis procedures and accident development sequence. The proposed algorithm can perform hazard analysis in two methods and represent all conceivable types of accidents using accident analysis algorithm. In addition, it provides intermediate steps in the accident propagation, and enables the analysis result to give a useful information to hazard assessment. The proposed method is successfully demonstrated by being applied to diammonium phosphate manufacturing process. A system to automate hazard analysis is developed by using the suggested method. The developed system is expected to be useful in finding the propagation path of a fault or the cause of a malfunction as it is capable to approach causes of faults and malfunctions simultaneously.

• 한국공작기계학회논문집
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• 제16권1호
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• pp.60-68
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• 2007

It has been conducted by laser vision sensor for weldability estimation of front-bead after doing high speed butt laser welding of any condition. It has been developed a real time GUI(Graphic User Interface) system for weldability application in the basis of texts and field qualify levels. In the reference of bead imperfections, defects absolute position and defects intensity index of front-bead in the basis of formability reference, it has been produced a weldability estimation and defects intensity index of back-bead by back propagation neural network. In the result of by comparing measuring data by laser vision sensor of back-bead and data by back propagation neural network of one, it has been shown the similar results. Finally, under knowledge of welding condition in production line, it has been conducted a weldability estimation of back-bead only in knowledge of informations of front-bead data without using laser vision sensor or welding inspection experts and furthermore it can be used data for final inspection results of back-bead.

• 제어로봇시스템학회논문지
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• 제9권7호
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• pp.527-535
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• 2003

A behavior-based control and learning architecture is proposed, where reinforcement learning is applied to learn proper associations between stimulus and response by using two types of memory called as short Term Memory and Long Term Memory. In particular, to solve delayed-reward problem, a knowledge-propagation (KP) method is proposed, where well-designed or well-trained S-R(stimulus-response) associations for low-level sensors are utilized to learn new S-R associations for high-level sensors, in case that those S-R associations require the same objective such as obstacle avoidance. To show the validity of our proposed KP method, comparative experiments are performed for the cases that (ⅰ) only a delayed reward is used, (ⅱ) some of S-R pairs are preprogrammed, (ⅲ) immediate reward is possible, and (ⅳ) the proposed KP method is applied.