• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.159-165
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• 1994

In this paper, we propose a multi-layer associative neural network structure suitable for hardware implementaion with the function of performance refinement and improved robutst capability. Unlike other methods which reduce network complexity by putting restrictions on synaptic weithts, we are imposing a requirement of hidden layer neurons for the function. The proposed network has synaptic weights obtainted by Hebbian rule between adjacent layer's memory patterns such as Kosko's BAM. This network can be extended to arbitary multi-layer network trainable with Genetic algorithm for getting hidden layer memory patterns starting with initial random binary patterns. Learning is done to minimize newly defined network error. The newly defined error is composed of the errors at input, hidden, and output layers. After learning, we have bidirectional recall process for performance improvement of the network with one-shot recall. Experimental results carried out on pattern recognition problems demonstrate its performace according to the parameter which represets relative significance of the hidden layer error over the sum of input and output layer errors, show that the proposed model has much better performance than that of Kosko's bidirectional associative memory (BAM), and show the performance increment due to the bidirectionality in recall process.

• Journal of Ship and Ocean Technology
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• v.12 no.4
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• pp.1-6
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• 2008

Nowadays, the computational capability and graphical power based on PCs increase very rapidly every year. As a result, the complicated engineering or scientific problems that could have only been handled by supercomputers a couple of decades ago can now be routinely run on PCs. Besides, the PCs can be assembled in parallel to increase its computational capability theoretically without limitation. The Web-based interface and communication tools are also being enhanced very rapidly and the real-time distance learning (E-Learning) and project cooperation on web get increasing attention. Using the-state-of-the-art computational method, a number of complicated and computationally intensive problems are being solved by PCs. The results can be well demonstrated on screen by graphics and animation tools. Those examples include the simulations of fully nonlinear waves, their interactions with floating bodies, global-motion analysis of multi-unit floating production system including complicated mooring lines and risers. Several examples will be presented in this regard. Also, Web and java-applet based educational tools have been developed at Texas A&M University for better understanding of waves and wave-body interactions. The background and examples of such Web-based educational tools published in Kim et al. (2003) are briefly introduced here.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.1
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• pp.149-158
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• 2019

Due to the rapid development of IT (information technology) and internet, products become smart and able to collect, process and produce information and can think of themselves to provide better service to consumers. However, research on the characteristics of smart product is still sparse. In this paper, we report the systemic development of a scale to measure the perceived product smartness associated with smart product. To develop product smartness scale, this study follows systemic scale development processes of item generation, item reduction, scale validation, reliability and validity test consequently. And, after acquiring a large amount of qualitative interview data asking the definition of smart product, we add a unique process to reduce the initial items using both a text mining method using 'r' s/w and traditional reliability and validity tests including factor analysis. Based on an initial qualitative inquiry and subsequent quantitative survey, an eight-factor scale of product smartness is developed. The eight factors are multi-functionality, human-like touch, ability to cooperate, autonomy, situatedness, network connectivity, integrity, and learning capability consequently. Results from Korean samples support the proposed measures of product smartness in terms of reliability, validity, and dimensionality. Implications and directions for further study are discussed. The developed scale offers important theoretical and pragmatic implications for researchers and practitioners.

• Journal of Agricultural Extension & Community Development
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• v.29 no.1
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• pp.19-31
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• 2022

This study aims to examine the moderating effect of regional agricultural leader's capacity between the sense of community of female farmers and the resident participation. A survey was conducted on 312 female farmers from October 20 to November 19, 2020. The main results of the analysis are as follows. First, it showed that the higher the sense of community, the higher the awareness of resident participation. Second, it was found that the sense of community had a positive effect on resident participation as self-directed learning capability was higher, and that self-directed learning capability had a moderating effect on the relationship between the sense of community and the resident participation. Third, regional agricultural leadership capacity was found to have a moderating effect in the relationship between the sense of community and the resident participation.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.425-436
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• 2006

The e-learning system in which the learning is carried out by predefined procedures cannot offer proper learning suitable to the capability of individual learner. To solve this problem, SCORM sequencing can be used to define various learning procedures according to the capabilities of learners. Currently the sequencing is designed by teachers or learning contents producers to regularize the learning program. However, the predefined sequencing may not reflect the characteristics of the learning group. If inappropriate sequencing is designed it may cause the unnecessary repetition of learning. In this paper, we propose an automated evaluation system in which dynamic sequencing is applied. The dynamic sequencing reflects the evaluation results to the standard scores used by sequencing. By changing the standard scores, the sequencing changes dynamically according to the evaluation results of a learning group. Through several experiments, we verified that the proposed learning system that uses the dynamic sequencing is effective for providing the proper learning procedures suitable to the capabilities of learners.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.185-195
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• 2020

This study is intended to determine that there is a casual relationship between technological innovation capability and new product development performance in small and mid-sized venture companies, and that the introduction of collaboration as a means to step up technological innovation capability will improve new product development performance. To achieve this, a survey was carried out to employees who are engaged in R&D work for small and mid-sized venture companies based in Korea, and the results were analyzed by regression analysis. The findings showed that technology strategy, technology learning and open innovation belonging to technological innovation capability in small and mid-sized venture companies had an effect on new product development performance. In other words, the selection of collaboration as a wider array of core strategies on new product development performance showed that collaboration was a strategy affecting new product development performance. In addition, the moderating role of technological innovation capability in boosting new product development performance through the introduction of collaboration showed that common collaboration had a positive effect on stepping up technology strategy, and collaboration as a core strategy had a positive effect on the size of new product development performance by strengthening technology strategy and open innovation.

• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.31-41
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• 2019

The purpose of this study is to investigate the participation of vocational training program of construction engineers and the impact of workplace learning (formal learning and informal learning) on human resource performances of construction engineers. The data of 306 construction engineers were extracted from 10,069 workers in various industries those were collected by 6th human resource company panel survey done by Korea Research Institute of Vocational Education & Training. This study found that, compared with workers in other industries, participation rate of construction engineers in workplace learning (formal learning, informal learning) was relatively low, and especially the participation rate of informal learning was significantly low. Regression analysis showed that participation in formal learning did not affect positive job performance and job satisfaction. On the other hand, informal learning has a positive effect on job capability, job satisfaction, and organizational commitment.

• Journal of Digital Contents Society
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• v.7 no.4
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• pp.257-261
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• 2006

In this paper, learning oriented puzzle game which based on combination of consonant and vowel of Korean alphabet is implemented. Firstly, consonants and vowels of Korean alphabet are classified separately, and then reconstructed a word in real time. Word combinator is utilized by API based edit window and, in order to effective retrieve, initial combined syllable consonant based method is involved. Implemented Korean puzzle game can be used for improving the words learning capability for children.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.8
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• pp.495-497
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• 2005

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a neural network used for identification of the process dynamics of s signal input and signal output system and it was shown that this method offered superior capability over the conventional back propagation algorithm. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal estimate input signal about controller using neural networks.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.18-20
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• 2005

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a neural network used for identification of the process dynamics of s signal input and signal output system and it was shown that this method offered superior capability over the conventional back propagation algorithm. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident. This paper goal estimate input signal about controller using neural networks.