• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.147-161
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• 2017

Climate changes from global warming and reduction in agricultural land result in volatility of prices of agricultural products, causing a imbalance of food market in Korea. It is necessary to develop a transnational food industry cooperation system among Korea, China and Russia that directly or indirectly affect food industry in terms of the whole industrial network. This study analyzes the value chain and linkage in the agriculture, forestry and fisheries industries in three nations. The unit structure and the industrial patterns of three nations were derived using the World Input-output Table (WIOT) from 2004 to 2014 every five years. This paper is expected to contribute to develop food security cooperation in the northern part of the Korean peninsula and to promote the mutual growth of food industry through industry linkage and cooperation.

• Structural Monitoring and Maintenance
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• v.10 no.2
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• pp.175-190
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• 2023

This article aims to quantitatively predict the snowmelt in extreme cold regions, considering a combination of grayscale and neural models. The traditional non-equidistant GM(1,1) prediction model is optimized by adjusting the time-distance weight matrix, optimizing the background value of the differential equation and optimizing the initial value of the model, and using the BP neural network for the first. The adjusted ice forecast model has an accuracy of 0.984 and posterior variance and the average forecast error value is 1.46%. Compared with the GM(1,1) and BP network models, the accuracy of the prediction results has been significantly improved, and the quantitative prediction of the ice sheet is more accurate. The monitoring and maintenance of the structure by quantitative prediction model by gray models was clearly demonstrated in the model.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.301-305
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• 2021

Scientific space, one can observe the differentiation of the definition of the terms "value", "value orientations" because it does not yet have a clear standard definition. Many researchers have dealt with this topic, researched, analyzed, observed, and made conclusions. However, there is still a rich scope for research of such phenomena of personal structure as value orientations. Psychologists-researchers who, in their scientific, practical, and theoretical works, dealt with the topic of values and value orientations and came to the general conclusion that values are a structural component of a personality, with the help of which a person achieves a goal, sets this goal, and characterizes position in life. Saw the relationship between values and the basic structures of the personality, including value orientations-considered in values a system of orientation and personality attitudes.

• Asia pacific journal of information systems
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• v.28 no.1
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• pp.36-60
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• 2018

As an increasing number of people gained access to social network services (SNS), organizations started to use SNS as a channel for marketing and promotional purposes. The online advertising market has significant growth potential. Brand engagement is a key motive for online advertising, but how SNS users engage with brands, particularly in terms of the promotion of organizations, is poorly understood. This study uses customer value theory to examine brand engagement of users in terms of promoting companies in the context of Korean SNS marketing. This study identifies the antecedents of brand engagement based on customer value theory. Our findings show the significance of three factors of SNS marketing, namely, price discount, relationship support, and convenience, on brand engagement. We further show the consequences of brand engagement, namely, purchase decisions and word-of-mouth activities. These findings help advance customer value theory and offer practical insights into the use of information systems and marketing in the context of SNS.

• Convergence Security Journal
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• v.11 no.3
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• pp.55-66
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• 2011

This research focus on the value of smart phones for university students in Korea, considering on the correlations between the main causes influencing intrinsic value(price attributes, function attributes), network value(learning effects attributes, externalities attributes) user satisfaction, and intentions of repurchase of the smart phones market in Korea. Through the statistical analyses on the 8 hypotheses from a research model, we found that intrinsic value and network value gave an attentive influence on user satisfaction and repurchase intention. Call charge and Liquid crystal display and Design of smart phone have an influenced user satisfaction and repurchase intention.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.149-159
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• 1999

Purpose: The purpose of this study was to evaluate cervical lymph node metastasis of oral squamous cell carcinoma patients by MRI film and neural network system. Materials and Methods: The oral squamous cell carcinoma patients(21 patients. 59 lymph nodes) who have visited SNU hospital and been taken by MRI. were included in this study. Neck dissection operations were done and all of the cervical lymph nodes were confirmed with biopsy. In MR images. each lymph node were evaluated by using 6 MR imaging criteria(size. roundness. heterogeneity. rim enhancement. central necrosis, grouping) respectively. Positive predictive value. negative predictive value. and accuracy of each MR imaging criteria were calculated. At neural network system. the layers of neural network system consisted of 10 input layer units. 10 hidden layer units and 1 output layer unit. 6 MR imaging criteria previously described and 4 MR imaging criteria (site I-node level II and submandibular area. site II-other node level. shape I-oval. shape II-bean) were included for input layer units. The training files were made of 39 lymph nodes(24 metastatic lymph nodes. 10 non-metastatic lymph nodes) and the testing files were made of other 20 lymph nodes(10 metastatic lymph nodes. 10 non-metastatic lymph nodes). The neural network system was trained with training files and the output level (metastatic index) of testing files were acquired. Diagnosis was decided according to 4 different standard metastatic index-68. 78. 88. 98 respectively and positive predictive values. negative predictive values and accuracy of each standard metastatic index were calculated. Results: In the diagnosis of using single MR imaging criteria. the rim enhancement criteria had highest positive predictive value (0.95) and the size criteria had highest negative predictive value (0.77). In the diagnosis of using single MR imaging criteria. the highest accurate criteria was heterogeneity (accuracy: 0.81) and the lowest one was central necrosis (accuracy: 0.59). In the diagnosis of using neural network systems. the highest accurate standard metastatic index was 78. and that time. the accuracy was 0.90. Neural network system was more accurate than any other single MR imaging criteria in evaluating cervical lymph node metastasis. Conclusion: Neural network system has been shown to be more useful than any other single MR imaging criteria. In future. Neural network system will be powerful aiding tool in evaluating cervical node metastasis.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.238-243
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• 2007

The TAM(Topographic Attentive Mapping) network neural network model is an especially effective one for pattern analysis. It is composed of of Input layer, category layer, and output layer. Fuzzy rule, lot input and output data are acquired from it. The TAM network with three pruning rules for reducing links and nodes at the layer is called fuzzy TAM network. In this paper, we apply fuzzy TAM network to pattern analysis of leadership type for organizational leader and show its usefulness. Here, criteria of input layer and target value of output layer are the value and leadership related personality type variables of the Egogram and Enneagram, respectively.

• The Journal of Information Technology
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• v.7 no.2
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• pp.43-54
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• 2004

Since Dr. John J. Hopfield has proposed the HOpfield network, it has been widely applied to the pattern recognition and the routing optimization. The method of Jian-Hua Li improved efficiency of Hopfield network which input pattern's weights are regenerated by SVD(singluar value decomposition). This paper deals with Li's Hopfield Network by linear pre-processing. Linear pre-processing is used for increasing orthogonality of input pattern set. Two methods of pre-processing are used, Hadamard method and random method. In manner of success rate, radom method improves maximum 30 percent than the original and hadamard method improves maximum 15 percent. In manner of success time, random method decreases maximum 5 iterations and hadamard method decreases maximum 2.5 iterations.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2468-2478
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• 2018

We propose the Sparse Feature Convolutional Neural Network (SFCNN) to reduce the volume of convolutional neural networks (CNNs). Despite the superior classification performance of CNNs, their enormous network volume requires high computational cost and long processing time, making real-time applications such as online-training difficult. We propose an advanced network that reduces the volume of conventional CNNs by producing a region-based sparse feature map. To produce the sparse feature map, two complementary region-based value extraction methods, cluster max extraction and local value extraction, are proposed. Cluster max is selected as the main function based on experimental results. To evaluate SFCNN, we conduct an experiment with two conventional CNNs. The network trains 59 times faster and tests 81 times faster than the VGG network, with a 1.2% loss of accuracy in multi-class classification using the Caltech101 dataset. In vehicle classification using the GTI Vehicle Image Database, the network trains 88 times faster and tests 94 times faster than the conventional CNNs, with a 0.1% loss of accuracy.

• Asian Journal of Business Environment
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• v.11 no.1
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• pp.27-37
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• 2021

Purpose: This article aims to provide a balanced understanding of the structural conditions and social processes involved in the creation and diffusion of innovation. Research design, data and methodology: Drawing on organizational and economic sociology and strategic management literature, this article offers a conceptual framework that highlights the two dimensions of network structures: the vertical dimension focusing on power and legitimacy vs. the horizontal dimension highlighting information value. By organizing the literature on the functions and consequences of network, this paper advances a theoretical perspective in understanding the vast array of empirical studies on innovation involving network analysis. Results: Using the proposed framework, this article explains how the mechanisms of power, legitimacy, and information value work together with social structural factors, thus enriching our understanding of innovation. This study reveals that the information mechanism (horizontal dimension) has been most important in innovation creation and diffusion, and that trust, credibility, and legitimacy are operative in innovation diffusion. Conclusions: This paper contributes to the literature by responding to calls to extend existing frameworks to better account for the dynamics between innovation and network. In addition, this article highlights how conceptualizing innovation within the horizontal-vertical dimensions of network structures, creates new opportunities for future research.