• Journal of the korean Society of Automotive Engineers
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• 제12권5호
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• pp.97-106
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• 1990

A method of weight evaluation of the load-bearing structural elements of cars is presented and the weight ratio of the analysis model is investigated. Replacing the materials of floor elements of the car into the high-strength steel, a considerable weight-reduction of the model has been obtained. The 1500cc model is selected for the present study and the stick model analysis is employed for the structural analysis. The torsional stiffness of the weight-reduced model is also evaluated and it is shown it has a reasonable rigidity. The ratio of the weight of the load-bearing structural elements to the unladen vehicle weight of cars is about 0.12for the 1500cc model and the weight-reduction of this study can be obtained around 17% of the weight of the load-bearing structural elements.

• Nutrition Research and Practice
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• 제16권2호
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• pp.205-216
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• 2022

BACKGROUND/OBJECTIVES: While many obesity studies have pointed out the importance of meal regularity, few have conducted empirical analyses using data from food diaries. We examined the association between meal regularity (i.e., meal time regularity [MTR] and calorie intake regularity [CIR]) and weight loss. SUBJECTS/METHODS: We collected food diary data from 637 women who had participated in commercial weight loss programs for 28-168 days (4-24 weeks). This study defined "meal regularity" in terms of two concepts: MTR and CIR. MTR refers to how regularly people eat their meals (i.e., at certain times each day), whereas CIR refers to how regularly people consume a certain amount of calories at each meal. We conducted multiple regression analyses. RESULTS: MTR (model 1: β = -2,576.526, P < 0.001; model 2: β = -1511.447, P < 0.05; model 3: β = -1,721.428, P < 0.05) and CIR (model 1: β = -1,231.551, P < 0.01; model 2: β = -2,082.353, P < 0.001; model 3: β = -1,343.490, P < 0.01) turned out to be significant determinants of the amount of weight loss in breakfast, lunch, and dinner contexts. While meal regularity (i.e., MTR and CIR) was significantly associated with weight loss, daily calorie intake from meals was not significantly associated with the amount of weight loss (model 1: β = 0.13, P > 0.05; model 2: β = 0.11, P > 0.05; model 3: β = 0.14, P > 0.05). Subjects who consumed an equal amount of calories per meal throughout the day lost more weight than those who did not (model 4: β = -3,675.51, P < 0.001). CONCLUSIONS: Eating each meal (i.e., breakfast, lunch, and dinner) at a certain time every day may increase weight loss success. Also, consuming the same amount of calories at each meal may help weight loss success.

• Journal of Animal Science and Technology
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• 제48권1호
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• pp.29-38
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• 2006

The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were －0.47 and －0.67 using modelⅠand －0.56 and －0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were －0.26 and 0.01 using modelⅠand －0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were －0.49 and －0.67 suing model Ⅰ and －0.57 and －0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were －0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were －0.43 and －0.67 using model Ⅰ and －0.50 and －0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were －0.09 and 0.02 using model Ⅰ and －0.02 and 0.13 using model Ⅱ.

• Korean Journal of Computational Design and Engineering
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• 제19권1호
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• pp.1-11
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• 2014

In the initial design stage, the technology for estimating and managing the weight of a floating offshore structure, such as a FPSO (Floating, Production, Storage, and Off-loading unit) and an offshore wind turbine, has a close relationship with the basic performance and the price of the structure. In this study, using the genetic programming (GP), being used a lot in the approximate estimating model and etc., the weight estimation model of the floating offshore structure was studied. For this purpose, various data for estimating the weight of the floating offshore structure were collected through the literature survey, and then the genetic programming method for developing the weight estimation model was studied and implemented. Finally, to examine the applicability of the developed model, it was applied to examples of the weight estimation of a FPSO topsides and an offshore wind turbine. As a result, it was shown that the developed model can be applied the weight estimation process of the floating offshore structure at the early design stage.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제45권4호
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• pp.118-126
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• 2022

This study attempts a comparison between AHP(Analytic Hierarchy Process) in which the importance weight is structured by individual subjective values and regression model with importance weight based on statistical theory in determining the importance weight of casual model. The casual model is designed by for students' satisfaction with university, and SERVQUAL modeling methodology is applied to derive factors affecting students' satisfaction with university. By comparison of importance weights for regression model and AHP, the following characteristics are observed. 1) the lower the degree of satisfaction of the factor, the higher the importance weight of AHP, 2) the importance weight of AHP has tendency to decrease as the standard deviation(or p-value) increases. degree of decreases. the second sampling is conducted to double-check the above observations. This study empirically checks that the importance weight of AHP has a relationship with the mean and standard deviation(or p-value) of independence variables, but can not reveal how exactly the relationship is. Further research is needed to clarify the relationship with long-term perspective.

• Proceedings of the Korea Association of Information Systems Conference
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• 한국정보시스템학회 2002년도 추계학술대회
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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 Ocean Engineering and Technology
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• 제23권3호
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• pp.14-19
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• 2009

The present study developed a model to estimate the light weight of an ultra-large container ship. The weight estimation model utilized container ship data obtained from shipyards and the subdivided this weight data into appropriate weight groups. Parameters potentially affecting the group weight were selected and expanded based on experience for weight estimation, and a correlation analysis was performed by the SPSS program to determine the key parameters characterizing the group weight. A weight estimation model applying the multi-regression analysis was proposed to assess the weight of an ultra-large container ship at the preliminary design stage, and the results obtained by the suggested method showed good agreement with the shipyard data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.405-423
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• 2022

The distance vector-hop (DV-Hop) is one of the emblematic algorithms that use node connectivity for locating, which often accompanies by a large positioning error. To reduce positioning error, the bio-inspired algorithm and weight optimization model are introduced to address positioning. Most scholars argue that the weight value decreases as the hop counts increases. However, this point of view ignores the intrinsic relationship between the error and weight. To address this issue, this paper constructs the relationship model between error and hop counts based on actual communication characteristics of sensor nodes in wireless sensor network. Additionally, we prove that the error converges to 1/6CR when the hop count increase and tendency to infinity. Finally, this paper presents a modified error-oriented weight positioning model, and implements it with genetic algorithm. The experimental results demonstrate excellent robustness and error removal.

• Journal of the Society of Naval Architects of Korea
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• 제50권6호
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• pp.373-382
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• 2013

The weight of floating offshore plant, such as an FPSO(Floating, Production, Storage, and Off-loading unit) and an offshore wind turbine, is important for estimating the amount of production material and for determining the production method. Furthermore, the weight is a factor which affects in the building cost and production time of the floating offshore plant. Although the importance of the weight has long been recognized, the weight has been roughly estimated by using the existing design and production data, and designer's experience. To solve this problem, a simplified model for the weight estimation of the floating offshore plant using the statistical method was proposed in this study. To do this, various data for estimating the weight of the floating offshore plant were collected through the literature survey, and then the correlation analysis and the multiple regression analysis were performed to generate the simplified model for the weight estimation. Finally, to examine the applicability of the developed model, it was applied to examples of the weight estimation of an FPSO topsides and an offshore wind turbine. As a result, it was shown that the developed model can be applied the weight estimation process of the floating offshore plant at the early design stage.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 한국항해항만학회 1998년도 추계학술대회논문집:21세기에 대비한 지능형 통합항만관리
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• pp.175-180
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• 1998

In container crane system, the variation of cargo weight have effect on the travelling and sway control of load. For precise travelling and/or anti-sway control of crane system, the cargo weight should be measured and considered with control algorithm. But, and added attachment for measuring the cargo weight put restraint upon the control freedom for travelling and anti-sway. In this paper, we propose an estimation method for cargo weight in container crane system by using observation technique. First of all, we model the container crane system as a bilinear system and transform this model into linear system with external disturbance model. Second, we propose a generalized type - disturbance estimation observer and set a disturbance model, where, the cargo weight is related with the sway of load, and the sway is represented as a periodic external disturbance. Lastly, by using simulation we verify that the proposed algorithm of disturbance estimation observer is effective to estimate the cargo weight, and it will be used with anti-sway control algorithm.