• Korean Journal of Fisheries and Aquatic Sciences
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• v.52 no.6
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• pp.719-724
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• 2019

This study is an extension of our previous model for a size-based fish stock assessment. In the previous model, we applied an allometric length-weight relationship (W=α·L^β) to convert lengths of fish to weights, and estimated those parameters α and β, using data about lengths and weights aggregated over years. In this study, we focused on whether consideration of temporal (e.g., year-to-year) variability in those estimates (i.e., ${\hat{\alpha}}$ and ${\hat{\beta}}$) would contributive. After calculating year-specific estimates (i.e., year-specific pairs of ${\hat{\alpha}}$ and ${\hat{\beta}}$) by applying data about lengths and weights separated by year, we evaluated the contribution of those year-specific pairs of ${\hat{\alpha}}$ and ${\hat{\beta}}$ to the performance of the size-based stock assessment model. The model with such year-to-year variability being considered (lower AIC) outperformed that with the variability being ignored (higher AIC). We illustrated this study using data on Korean chub mackerel Scomber japonicus from 2005-2017.

• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.327-332
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• 2010

In this paper we presents an approach to assessing the efficiency of freight railroad stations reflecting freight item importance weights with multiple performance indicators and multiple operational condition indicators. We evaluate 187 freight railroad stations using data envelopment analysis with assurance region. Each freight item's loading/unloading volume is used as a performance indicator. Freight labor and yard capacity are used as operational condition indicators. Freight item importance weights are reflected to the data envelopment analysis as assurance region. The evaluation results facilitates the organization's decision making by providing valuable information.

• Journal of the Korean Society for Railway
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• v.16 no.2
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• pp.117-121
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• 2013

Railway line segment deterioration can be affected by rail tracks, subgrades, bridges, tunnels, and line shapes. In this paper, an evaluation method is presented for the railway line segment deterioration using the analytic hierarchy process (AHP) and data envelopment analysis (DEA). The importance weights can be assessed systematically for component facilities from numerous experts using AHP. The importance weights provided by experts may differ according to each expert; however, the DEA enables the evaluation of railway line segment deterioration that reflects the variety of expert opinions using these importance weights.

• Design & Manufacturing
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• v.13 no.3
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• pp.53-58
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• 2019

This paper presents Artificial Neural Network(ANN) method to predict maximum injection pressure of injection molding machine and weights of injection molding products. 5 hidden layers with 10 neurons is used in the ANN. The ANN was conducted with 5 Input parameters and 2 response data. The input parameters, i.e., melt temperature, mold temperature, fill time, packing pressure, and packing time were selected. The combination of the orthogonal array L27 data set and 23 randomly generated data set were applied in order to train and test for ANN. According to the experimental result, error of the ANN for weights was $0.49{\pm}0.23%$. In case of maximum injection pressure, error of the ANN was $1.40{\pm}1.19%$. This value showed that ANN can be successfully predict the injection pressure and the weights of injection molding products.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.1
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• pp.80-89
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• 2021

In Korea, marine fish landed at ports are randomly sampled on a periodic basis (e.g., daily or weekly), and body sizes (e.g., lengths and weights) of those sampled fish are measured. The motivation for our study is whether or not such measurements reflect the size distribution, especially the length distribution of fish landed (= a population), because such length measurements are key data for a length-based assessment model. The current sampling method is to sample fish landed at ports by body size group (e.g., very small, small, medium, large, very large), using the sampling weights as the number of boxes by body size group. In this study, we showed that length composition data about fish sampled by the current method did not represent the length frequency distribution of the fish landed, and suggested that an alternative sampling method should be applied of using the sampling weights as the number of fish landed by body size group. We also introduced a method for determining an appropriate sample size.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.6
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• pp.729-732
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• 2000

Weight records from birth to calving and calving scores of 407 two-year old heifers and weights of their offspring from birth to one year of age were used to study the effects of sire birth weight on maternal traits of their female progeny. The heifers (G1) were the progeny of 81 sires (G0) and were classified into three classes based on their sires' birth weights (High, Medium and Low). The heifers were from three distinct breed-groups and were mated to bulls with medium birth weights within each breed-group to produce the second generation (G2). The data were analyzed using a covariance model. The female progeny of high birth-weight sires were heavier from birth to calving than those sired by medium and low birth-weight bulls. The effect of sire birth weight on calving difficulty scores of their female progeny was not significant. Grand progeny (G2) of low birth-weight sires were lighter at birth than those from high birth-weight sires (p<0.05) but they did not differ significantly in weaning and yearling weights with the other two Grand progeny groups. The results indicated that using low birth weight sires would not result in an increase in the incidence of dystocia among their female progeny calving at two-year of age and would not have an adverse effect on weaning and yearling weights of their grand progeny.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.3-8
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• 2013

In CDMA-based systems, recently, researches on chip-level equalization have been studied in order to improve receiving performance when supporting high-rate data services. In this paper, we consider a chip-level LMMSE (linear minimum mean-squared error) receiver for D-TxAA (dual stream transmit antenna array) based single stream HSDPA MIMO systems using precoding weights. First, we will derive precoding weights for maximizing the total instantaneous received power. We will also analyze the effects of both transmit delay of precoding weights and mobile velocity on chip-level LMMSE receivers, which is verified through computer simulations in various mobile channel environments.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.309-326
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• 2011

Most metadata quality measurement employ simple techniques by counting error records. This study presents a new quantitative measurement of metadata quality using advanced weighting schemes in order to overcome the limitations of exiting measurement techniques. Entropy, user tasks, and usage statistics were used to calculate the weights. Integrated weights were presented by combining these weights and were applied to actual journal article metadata. Entropy weights were found to reflect the characteristics of the data itself. User tasks presented the required metadata elements to solve user's information need. Integrated weights showed balanced measures without being affected by the influence of error elements, This finding indicates the new method being suitable for quantitative measurement of metadata quality.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3472-3482
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• 2024

This study proposes a modified extended cognitive reliability and error analysis method (CREAM) for achieving a more accurate human error probability (HEP) in advanced control rooms. The traditional approach lacks failure data and does not consider the common performance condition (CPC) weights in different cognitive functions. The modified extended CREAM decomposes tasks using a method that combines structured information analysis (SIA) and the extended CREAM. The modified extended CREAM performs the weight analysis of CPCs in different cognitive functions, and the weights include cognitive, correlative, and important weights. We used the extended CREAM to obtain the cognitive weight. We determined the correlative weights of the CPCs for different cognitive functions using the triangular fuzzy decision-making trial and evaluation laboratory (TF-DEMATEL), and evaluated the importance weight of CPCs based on the interval 2-tuple linguistic approach and ensured the value of the importance weight using the entropy method in the different cognitive functions. Finally, we obtained the comprehensive weights of the different cognitive functions and calculated the HEPs. The accuracy and sensitivity of the modified extended CREAM were compared with those of the basic CREAM. The results demonstrate that the modified extended CREAM calculates the HEP more effectively in advanced control rooms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.1-6
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• 2006

This study proposes a new approach which combines Data Envelopment Analysis(DEA) and the Analytic Hierarchy Process(AHP) techniques to effectively evaluate Decision Making Units(DMUs). While DEA evaluates a quantitative data set, employs linear programming to obtain input and output weights and ranks the performance of DMUs, AHP evaluates the qualitative data retrieved from expert opinions and other managerial information in specifying weights. The objective of this research is to design a decision support process for managers to incorporate positive aspects of DEA's absolute numerical evaluations and AHP's human preference structure values. It is believed that a pragmatic manager will be more receptive to the results that include subjective opinions incorporated into the evaluation of the efficiency of each DMU efficiency. The WPDEA method provides better discrimination than the DEA method by reducing the number of efficient units.