• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.653-655
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• 2011

EPCglobal proposed a Q-algorithm, which is used for selecting a slot-count in the next query round. However, it is impossible to allocate an optimized slot-count because the original Q-algorithm did not define an optimized weight C value. In this paper, we propose an adaptive Q-algorithm, in which we differentiate the weight values with respect to collision and empty slots. The weight values are defined with the identification time as well as the collision probability.

• Proceedings of the Korea Association of Information Systems Conference
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• 2002.11a
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• pp.289-312
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• 2002

This study suggests the Link weight analysis approach to choose input variables and an integrated model to make more accurate bankruptcy prediction model. the Link weight analysis approach is a method to choose input variables to analyze each input node's link weight which is the absolute value of link weight between an input nodes and a hidden layer. There are the weak-linked neurons elimination method, the strong-linked neurons selection method in the link weight analysis approach. The Integrated Model is a combined type adapting Bagging method that uses the average value of the four models, the optimal weak-linked-neurons elimination method, optimal strong-linked neurons selection method, decision-making tree model, and MDA. As a result, the methods suggested in this study - the optimal strong-linked neurons selection method, the optimal weak-linked neurons elimination method, and the integrated model - show much higher accuracy than MDA and decision making tree model. Especially the integrated model shows much higher accuracy than MDA and decision making tree model and shows slightly higher accuracy than the optimal weak-linked neurons elimination method and the optimal strong-linked neurons selection method.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.172-176
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• 2011

In the Gen-2 Q-algorithm, the values of weight C, which is the parameter for incrementing or decrementing the slot-count size, are not optimized in the standard. However, the standard suggests that the reader uses small values of C when the slot-count is large and larger values of C when the slot-count is small. In this case, if the reader selects an inappropriate weight, there are a lot of empty or collided slots. As a result, the performance will be declined because the frame size does not converge to the optimal point quickly during the query round. In this paper, we propose a scheme to select the weight based on the slot-count size of current query round. Through various computer simulations, it is demonstrated that the proposed scheme achieves more stable performances than Gen-2 Q-algorithm.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.228-232
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• 2002

This paper is reporting the whole process of developing a weight measuring scaler of truck and trailer system for static and dynamic condition. The sensors attached on the top of springs each wheels. Acquisition and data processing performs accurate data extraction from noise environment, filtering and estimation. Weight information was highly distorted with noise and perturbation. Hence the perturbation was classified several categories and evaluated for accurate signal extract. The final products supply accurate and easy readable data of load weight for truck. It supplies total weight as well as loading condition of each axle. It is expected that it give the information to the truck operator of proper amount loading and safe condition to drive with it.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.53-61
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• 2014

In this paper, we proposed covariance weight matrix using SPT matrix in order to accurate target estimation. We have estimated a target using modified covariance matrix and beam steering error method. We have minimized beam steering error in order to estimation desired a target. This method obtain optimum covariance weight using modified SPT matrix. This paper of proposal method is showed good performance than general method. We updated a weight of covariance matrix using modified SPT matrix. We obtain optimum covariance matrix weight to application beam steering error method in order to beam steering toward desired target. Through simulation, we showed that compare proposal method with general method. It have improved resolution of estimation target to good performance more proposed method than general method.

• The Korean Journal of Community Living Science
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• v.25 no.2
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• pp.175-192
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• 2014

This study explores the effects of various factors on the use of nutrition information on food away from home (FAFH). Consumer groups were classified into groups according to their perception of being overweight and obese (correctly perceiving, underestimating and overestimating weight). For this, frequency analysis, a chi-square test, and an ANOVA were conducted to determine any differences between factors, and a logit analysis (SPSS 18.0) was conducted to identify those factors influencing the use of information. Information recognition, intentions to use information and the use on FAFH showed significant differences across the groups. In addition, health inspection, the perception of the intrinsic quality of restaurants, labeling, FAFH expenditure, and some individual characteristics showed significant differences between groups. The information recognition of FAFH had a significant positive effect on information use in all groups. In all groups, labeling had a significant positive effect on information use, and family health concerns had a significant positive effect on information use in the group correctly perceiving weight. The price of domestic food items, household head and household income had significant positive effects on information use in the group overestimating weight.

• Journal of the East Asian Society of Dietary Life
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• v.10 no.6
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• pp.522-529
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• 2000

This study was carried out to find the factors which are related to the weight gain during pregnancy of women and infant birth weight. The information of the general characteristics and pregnancy outcomes of the 506 women who had a delivery during Jan to Dec, 1997 in a hospital at Taegu area were collected from the medical records. The results are as follows. The mean age of the subjects was 29 years old and the average prepregnancy weight was 52.75kg. They gained 13.51kg of weight during the pregnancy. The weight gain during pregnancy was higher in prepregnancy BMI<20kg/m$^2$, the infant weight was heavier in groups that had over 14kg of weight gain during the pregnancy than other groups. The prepregnancy BMI was negatively correlated to weight gain during pregnancy(r=0.2825), and positively correlated to number of pregnancy(r=0.2146), number of living delivery(r=0.1409), and infant weight(r=0.1250). The baby weight was Positively correlated to weight gain during pregnancy(r=0.1392) and Apgar score(r=0.1627). The results showed that the prepregnancy BMI and weight gain during pregnancy may be the influential factors on the infant weight, thus we need to develop the specific nutritional management program according to the status of prepregnancy weight.

• Journal of Korean Medicine for Obesity Research
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• v.19 no.1
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• pp.12-23
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• 2019

Objectives: Obesity is associated with a high mortality risk and impairment in health-related quality of life (HRQOL). The aim of this article is to examine the impact of weight loss on HRQOL and which questionnaires sensitively reflect weight loss effects on HRQOL. Methods: PubMed, Scopus, Research Information Sharing Service, and Korean Studies Information Service System were searched for the studies related to weight loss and HRQOL, published from 2009 to 2018. A total of 28 studies were eligible for inclusion. HRQOL results after weight loss from selected studies were classified and reported according to questionnaires. Results: Twenty-two studies reported statistically significant HRQOL improvements after weight loss and especially, all of studies with weight loss of more than 5% reported HRQOL improvements. HRQOL questionnaires were classified as generic, obesity-related and depression questionnaires. The most commonly used questionnaires were Short-Form health survey 36 (SF-36), Impact of Weight on Quality Life-Lite (IWQOL-Lite) and Beck Depression Inventory (BDI) respectively. SF-36 had a tendency to reflect physical health. IWQOL-Lite score was tended to be changed sensitively according to weight change. Depression questionnaires including BDI reported improvement of depression while mental aspects of SF-36 not changed in same studies. Conclusions: Improvements of HRQOL were noted in studies with weight loss of more than 5%. The main questionnaires for evaluating HRQOL were SF-36, IWQOL-Lite and BDI. It is suggested to use these questionnaires together for evaluating multiple aspects of impact of weight loss on HRQOL.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.1-10
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• 2001

Neural networks we increasingly being seen as an addition to the statistics toolkit which should be considered alongside both classical and modern statistical methods. Neural networks are usually useful for classification and function estimation. In this paper we concentrate on function estimation using neural networks with weight decay factor The use of weight decay seems both to help the optimization process and to avoid overfitting. In this type of neural networks, the problem to decide the number of hidden nodes, weight decay parameter and iteration number of learning is very important. It is called the optimization of weight decay neural networks. In this paper we propose a automatic optimization based on genetic algorithms. Moreover, we compare the weight decay neural network automatically learned according to automatic optimization with ordinary neural network, projection pursuit regression and support vector machines.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.97-105
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• 2017

This study is the realization study recognizing the Korean gothic printing letter. This study defined the new grapheme by using the connection ingredient and had the graphemes recognized by means of the feature dots of the isolated dot, end dot, 2-line gathering dots, more than 3 lines gathering dots, and classified the characters by means of the arrangement information of the graphemes and the layers that the graphemes form within the characters, and made the character database for the recognition by using them. The layers and the arrangement information of the graphemes consisting in the characters were presumed by using the weight center position information of the graphemes extracted from the characters to recognize and the information of the graphemes obtained by vertically exploring from the weight center of each grapheme, and it recognized the characters by judging and comparing the character groups of the database by means of the information which was secured this way. 350 characters were used for the character recognition test and about 97% recognition result was obtained by recognizing 338 characters.