• The Research Journal of the Costume Culture
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• v.20 no.5
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• pp.753-765
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• 2012

This study tested the validity of the six-factor model of fashion savvy which was modified from the consumer savvy scale developed by Macdonald and Uncles(2007) and explored the relationship between fashion savvy and consumer propensity to observe. Regarding the relationship, it was hypothesized that consumer propensity to observe antecedes fashion savvy. Data were gathered by surveying university students in Seoul metropolitan area, using convenience sampling, and 311 questionnaires were used in the statistical analysis. In analyzing data, factor analysis and regression were conducted. The findings show the validity of the six factors of fashion savvy, which are fashion sophistication, interpersonal network competency, online network competency, marketing literacy, consumer self-efficacy, and consumer expectations. Tests of the hypothesized relationship show that two factors of consumer propensity to observe influence fashion savvy. More specifically, the 'observing shoppers' factor positively influences all six factors of fashion savvy, whereas the 'following what others buy' factor negatively influences four factors of fashion savvy, fashion sophistication, interpersonal network competency, marketing literacy, and consumer self-efficacy. The implications of these findings and suggestions for future study are also discussed.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.4
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• pp.419-426
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• 2001

Concrete mix proportioning is a process of selecting the right combination of many materials such as cement, fine aggregates, coarse aggregates, water, and admixtures to make concrete satisfying for specification and cost. In determining proportioning of concrete mixes, code information, specification, and the experience of experts are needed. However, all factors regarding mix proportioning factor cannot be considered. Therefore, the final acceptance depends on concrete quality control test results. The proportioning of concrete mixes and the adjustments are somewhat complicated, time-consuming, and uncertain tasks. In this paper, as a tool to predict the factor of the proportioning of concrete mixes, an artificial neural network is used. To consider the varieties of material properties, the standard mixed table of two companies of ready mixed concrete are used. The results show that neural net works is successfully applied to the prediction of concrete mix proportioning factor.

• JSTS:Journal of Semiconductor Technology and Science
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• v.4 no.2
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• pp.83-87
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• 2004

Phase noise performance and current consumption of Radio Frequency (RF) Voltage-Controlled Oscillator (VCO) are largely dependent on the Quality (Q) factor of inductor-capacitor (LC) tank. Because the Q-factor of LC tank is determined by on-chip spiral inductor, we designed, analyzed, and modeled on-chip differential inductor to enhance differential Q-factor, reduce current consumption and save silicon area. The simulated inductance is 3.3 nH and Q-factor is 15 at 2 GHz. Self-resonance frequency is as high as 13 GHz. To verify its use to RF applications, we designed 2 GHz differential LC VCO. The measurement result of phase noise is -112 dBc/Hz at an offset frequency of 100 kHz from a 2GHz carrier frequency. Tuning range is about 500 MHz (25%), and current consumption varies from 5mA to 8.4 mA using bias control technique. Implemented in $0.35-{\mu}m$ SiGe BiCMOS technology, the VCO occupies $400\;um{\times}800\;um$ of silicon area.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.257-266
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• 2011

Over the society the trial for several systems to be connected with Network has been continued to share information and to make it various. In accordance with such a change, the concept of military warfare conduction has been changing form platform centric warfare in separate combat system based on network centric warfare in network based. We have continuously made an effort that we try to get the goal with efficient system which is linked up with network, but such a study on that one in military system analysis is still slower than the study out of military until now. So this study is searching network influence factor by using military network with application of social network analysis method which is used broadly in the society and the science as well. At this time we search co-relationships between social network and the thing that we can analyse C2 time by effectiveness measurement means. By this study it has value of network influence factor identification for the growing network composition.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.4
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• pp.95-101
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• 1990

Orthogonal decomposition technique, not using normal equation, but using observation equation directly, is accepted for adjusting the geodetic network in this paper. The results of study show that the technique is the numerically stable and powerful method in network adjustment by inner constraints or weighted position parameters. Also, it is suitable to middle sized-network and is applicable to Cholesky Factor in the normal equation system.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.23-36
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• 1997

In the design of telecommunication network, the network configuration using hubbing topology is useful for designing and managing the network efficiently : i. e. all of central offices (COs) are grouped into clusters. Each cluster has one hub consisting of large-scale transmission facilities like digital cross-connect systems and ATMs. In clustering process, the community of interest and geographical factor should be considered. However, there exists a tradeoff between two factors. One is to minimize total link costs for geographical factor and the other is to maximize the total intra-cluster traffics for community of interest. Hence, this can be solved by multiobjective linear programming techniques. In this paper, the problem under considerations is formulated as two p-median subproblems taking into considerations total costs and total intra-traffics, respectively. Then we propose the algorithm to solve the problem based on the concept of cost-traffic tradeoff. The algorithm enables to identify efficient cost-traffic tradeoff pairs. An illustration is also presented.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.4
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• pp.19-41
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• 2007

This research has a goal which is suggesting the way of constructing 'Cluster' which mean scheming the commencement of an enterprise in an early stage. Now it is reorganized into a IT industry structure 'Time-to market growth' is burst as a big issue. in that point, this research analyze the core success factor which is drawing from the existing IT industrial complex, and then it will be used to draw up to the 'Idealistic growth-support Cluster' on the basis of it, we pulled out various issues about the Corporate in the early stage of its growth. Therefore, this research is focused on presenting the ideal network(net) by considering the Network that organizations and business in Cluster or the network including the factors linked organizations and business in Cluster. therefore, this research carried out three big analysis. from the case investigation we pulled out the core growth factor, and then we approached the analysis of net structure for making application to Network Analysis. and then we analyzed that the characteristics of the Network after measuring by on the basis of analyzing core growth factor. and especailly, this research carried out the Core analysis for recognition of Core- support-frame by base Centrality Test on the net which is composed of growth support organizations at each Business. Judging from this, we can help to make full use of resources for the network analysis in Cluster and establish the Network Strategy by Structure comparison between the structure of industry-Cluster and ideal Business-support networks on the basis of the analysis from the Core-success-factor

• Journal of Korean Society of Water and Wastewater
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• v.13 no.2
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• pp.23-33
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• 1999

This study is to investigate the effect of C factor errors on the analysis of water distribution systems. For this purpose, an artificial distribution network and a real distribution network were selected as the study networks. Results are as follows. 1. The C factor of a pipe which has small velocity didn't give significant effect on the analysis of a water distribution system. 2. The effect of decreased value of C factors give more influence on the analysis of water distribution systems than that of the increased values. 3. For the C factor calibration, errors of the residual water heads as well as those of the head losses should be considered together. 4. In the analysis of water distribution systems, changes of C factors can give influences only on the nodes which locate behind the pipe. Therefore, this characteristics should be considered in the selection of nodes for the measurement of water heads.

• International Journal of Fluid Machinery and Systems
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• v.3 no.4
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• pp.369-378
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• 2010

The creation of the hydraulic turbine flow factor map will undoubtedly benefit its design by decreasing both the design cycle time and product cost. In this paper, the geometry and flow variables, which effectively affect the flow factor, are proposed, analyzed and determined. These flow variables are further used to create the operating condition maps by using different model approaches categorized into Response Surface Method (RSM) and Artificial Neural Network (ANN). The accuracies of models created by different approaches are compared and the performances of model approaches are analyzed. The influences of chosen variables and the combination of Principle Component Analysis (PCA) and model approaches are also studied. The comparison results between predicted and actual flow factors suggest that two-hidden-layer Feed-forward Neural Network (FFNN), and one.hidden-layer FFNN with PCA has the best performance on forming this mapping, and are accurate sufficiently for hydraulic turbine design.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.111-118
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• 1997

Adding a noise tolerance factor to the Relaxation learning algorithm in Hop-field network improves noise tolerance without effecting storage capacity. The new algorithm is called the Pseudo-Relaxation algorithm, and the convergence of the algorithm has been proved. It is also shown that the noise tolerance factor does not effect learning speed.