• Computers and Concrete
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• 제14권6호
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• pp.727-743
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• 2014

The management of existing concrete bridges has become a major social concern in many developed countries due to the large number of bridges exhibiting signs of significant deterioration. This problem has increased the demand for effective maintenance and renewal planning. In order to implement an appropriate management procedure for a structure, a wide array of corrective strategies must be evaluated with respect to not only the condition state of each defect but also safety, economy and sustainability. This paper describes a new performance evaluation system for existing concrete bridges. The system evaluates performance based on load carrying capability and durability from the results of a visual inspection and specification data, and describes the necessity of maintenance. It categorizes all girders and slabs as either unsafe, severe deterioration, moderate deterioration, mild deterioration, or safe. The technique employs an expert system with an appropriate knowledge base in the evaluation. A characteristic feature of the system is the use of neural networks to evaluate the performance and facilitate refinement of the knowledge base. The neural network proposed in the present study has the capability to prevent an inference process and knowledge base from becoming a black box. It is very important that the system is capable of detailing how the performance is calculated since the road network represents a huge investment. The effectiveness of the neural network and machine learning method is verified by comparing diagnostic results by bridge experts.

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1998년도 제13회 하계학술발표회 논문집
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• pp.57-90
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• 1998

This study attempts to explore the evolution paths of Korean SMEs'strategies and their technological teaming processes. Several different evolution paths are identified based on a dynamic strategic group analysis of 115 SMEs'strategy in the Korean electronic component industry for the period of 1990-1995. Further, inadept case analyses on technological learning processes in 5 firms are undertaken. Major findings of this study can be summarized as follows : 1) There are three dominant evolution paths in SMEs'strategy. First path indicates the evolution from a subcontractor or petty imitator group(a strategic group with the narrow product/market domain and the low level of accumulated resource/capabilities) into an innovator group(a strategic group with the narrow domain but high level of technological capability) by accumulating technological capabilities. Second, some firms move from a subcontractor group into a generalizer group(a strategic group with broad product/market domain but relatively low level of technological capability) by simply adding product lines. Third path involves firms which evolve from a subcontractor group into a production focus group(a strategic group with high level of production capability) by investing in production capabilities. 2) An in-depth case analysis shows those who succeeded in technological learning are managed by CEOs, who have technological expertise and strategic vision, and have made an effort to establish management practices to support innovation, such employee educational program, performance-based reward system, etc. The successful firms also aggressively pursue diverse external linkages with outside technology sources to learn product and process technologies. Fiendly, this study discusses several implications of the findings for the theoretical development and strategic management of small firms in Korea.

• 기술혁신연구
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• 제12권2호
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• pp.151-183
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• 2004

This paper investigates the evolution of 'inter-firm' technology transfer in the Thai automobile industry, which has gradually been integrated into global production network of some specific automotive models(one-ton pickups). This paper discusses the linkage between the role of automobile assemblers in transferring technology and the way their strategic changes bring about heightened demands on the technological capacity of suppliers and the contents of technology transfer. With higher competition at the global level, local suppliers are required to improve their technical and managerial skills, especially in the area of 'product engineering' capability. The authors examine the ways local firms have adapted to these changes in their environments, as well as the ways they utilize inter-firm relationship with automobile assemblers as a means to improve their own technological capabilities. The dynamic process of capability formation in local parts firms, through intensive efforts and learning inducements brought about by inter-firm relationships, are also discussed.

• 경영과학
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• 제18권2호
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• pp.25-38
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• 2001

The well-known back-propagation algorithm for multi-layered neural network has successfully been applied to pattern c1assification problems with remarkable flexibility. Recently. the multi-layered neural network is used as a powerful data mining tool. Nevertheless, in many cases with complex boundary of classification, the successful learning is not guaranteed and the problems of long learning time and local minimum attraction restrict the field application. In this paper, an Improved learning procedure of multi-layered neural network is proposed. The procedure is based on the generalized delta rule but it is particular in the point that the architecture of network is not fixed but enlarged during learning. That is, the number of hidden nodes or hidden layers are increased to help finding the classification boundary and such procedure is controlled by entropy evaluation. The learning speed and the pattern classification performance are analyzed and compared with the back-propagation algorithm.

• Journal of Information Processing Systems
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• 제16권5호
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• pp.1015-1033
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• 2020

With promising results and enormous capability, deep learning technology has attracted more and more attention to both theoretical research and applications for a variety of image processing and computer vision tasks. In this paper, we investigate 32 research contributions that apply deep learning techniques to the agriculture domain. Different types of deep neural network architectures in agriculture are surveyed and the current state-of-the-art methods are summarized. This paper ends with a discussion of the advantages and disadvantages of deep learning and future research topics. The survey shows that deep learning-based research has superior performance in terms of accuracy, which is beyond the standard machine learning techniques nowadays.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.223-228
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• 2021

As a consequence of sudden outbreak of COVID-19 pandemic worldwide, educational institutes around the globe are forced to switch from traditional learning systems to e-learning systems. This has led to a variety of technology-driven pedagogies in e-teaching as well as e-learning. In order to take the best advantage, an appropriate understanding of the cognitive capability is of prime importance. This paper presents an intelligent cognitive maturity recognition system for confidence-based e-learning. We gather the data from actual test environment by involving a number of students and academicians to act as experts. Then a Genetic Programming based simulation and modeling is applied to generate a generalized classifier in the form of a mathematical expression. The simulation is derived towards an optimal space by carefully designed fitness function and assigning a range to each of the class labels. Experimental results validate that the proposed method yields comparative and superior results which makes it feasible to be used in real world scenarios.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1570-1575
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• 1991

The feasibility of using an adaptive resonance network (ART2) with unsupervised learning capability for too] wear detection in turning operations is investigated. Specifically, acoustic emission (AE) and cutting force signals were measured during machining, the multichannel AR coefficients of the two signals were calculated and then presented to the network to make a decision on tool wear. If the presented features are significantly different from previously learned patterns associated with a fresh tool, the network will recognize the difference and form a new category m worn tool. The experimental results show that tool wear can be effectively detected with or without minimum prior training using the self-organization property of the ART2 network.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.143-146
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• 1990

The human brain has the most powerful capabilities in thinking, interpreting, remembering, and problem-solving. Artificial neural network is appeared by scientists who have tried to simulate such a human brain. The artificial neural network has the capability of learning, massive parallelism capability and robustness for disturbance which are necessary for power system application. In this paper, We reviewed the typical topologies and learning algorithms of artifical neural networks which can be used for pattern classification. And we surveyed for the applications of artifical neural network to the power system.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.1081-1091
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• 2020

The objective of this study is to disclose the effect of socio-demographic characteristics such as, age and ethnicity which is comprised of Malay, Chinese, Indian and Others on four financial capability domains namely planning ahead, managing money, choosing products and staying informed. A closed ended self-administered questionnaire was disseminated to a total of 2000 respondents among four types of groups which consist of FELDA or rural area residents, private sector employees, government sector employees and youth in institutions of higher learning in Malaysia. Those four groups were selected to cover a wide range of Malaysian population. 500 respondents were involved in this study for each types of groups through purposive sampling technique. Analysis of Variance (ANOVA) and analysis via Statistical Package for Social Science (SPSS) was utilized in this study. The results revealed that age has significant effect on planning ahead, managing money, choosing products and staying informed. Whereas, ethnicities were found to have no effect on financial capability except planning ahead domain. It is suggested that more devotion should be placed on research and professional training in building respondents' financial capability. Furthermore, government and non-government organizations should develop a comprehensive approach to intensify their financial capability and upgrade their standards of living especially of financially vulnerable households.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.247-251
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• 2014

스마트교육의 시행과 함께 새로운 교수 학습 방법의 필요성이 증대되고 있고 이에 따라 교원 양성 대학에서도 예비 교사들을 위한 스마트교육 교수 학습 방법을 체계화할 필요가 있다. 본 연구는 국내외 초 중 고등학교 스마트교육 교수 학습 유형 분석과 CTLA(Creation Teaching Learning Assessment) 모델 분석을 통해 예비 교사에게 적용할 수 있는 스마트교육 교수 학습 모형을 설계하였다. 스마트교육의 목적은 학습자의 역량 강화에 있다. 예비 교사들의 Smart Literacy 역량 강화에 도움을 줄 수 있도록 설계된 스마트교육 교수 학습 모형은 앞으로 스마트교육을 받을 예비 학습자의 역량 강화에 적합하도록 설계되었다. 본 연구의 스마트교육 교수 학습 모형 설계는 교원양성 대학의 예비 교사에게 적용할 수 있도록 15주차로 지도안을 작성하였다. 교수 학습 모형은 문제중심학습(PBL: Problem Based Learning), 상황학습(Situated Learning)모형, 협동학습 모형 등을 주차별 수업에 맞게 적용하였다. 향후에는 제안된 교수 학습 모형의 점진적 개선을 통해 예비교사들의 Smart Literacy 역량 강화의 효과성을 입증하고 지속적인 스마트교육 교수 학습 모형 개발 및 검증연구가 지속되어야 할 것이다.