• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.549-556
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• 2022

The aim of this study was to evaluate the genetic parameters of growth traits for improvement breeding in olive flounder Paralichthys olivaceus at the 8^th generation of selective breeding in April 2021. Growth traits such as total length, body weight and condition factor at 11 months of age were measured for 7,508 individuals with confirmed paternity. Data were analyzed using the restricted maximum likelihood method applied to a multiple traits animal model. The effects of sex and family were significantly different across traits (P<0.05). The heritability values of total length, body weight and condition factor were estimated to be high as 0.479, 0.457, and 0.466, respectively. Correlation analysis between phenotypic and breeding values, indicated that the selection accuracy was 75.9-85.2% for all traits. To increase the selection accuracy for parent fish selection, the sex and pedigree characteristics that affect each trait should be considered. Moreover, further improvement of multiple traits can be achieved if the correlation between each trait is appropriately considered.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1332-1335
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• 2008

In order to various service types of real time and non-real time traffic with varying requirements are transmitted over the IEEE 802.16 standard is expected to provide quality of service(QoS) researchers have explored to provide a queue management scheme with differentiated loss guarantees for the future Internet. The sides of a packet drop rate, an each class to differential drop probability on achieving a low delay and high traffic intensity. Improved a queue management scheme to be enhanced to offer a drop probability is desired necessarily. This paper considers multiple random early detection with differential drop probability which is a slightly modified version of the Multiple-RED(Random Early Detection) model, to get the performance of the best suited, we analyzes its main control parameters (max_th, min_th, max_p) for achieving the proportional loss differentiation (PLD) model, and gives their setting guidance from the analytic approach. we propose Dynamic-multiple queue management scheme based on differential drop probability, called Dynamic-VQSDDP(Variable Queue State Differential Drop Probability)T, is proposed to overcome M-RED's shortcoming as well as supports static max_p parameter setting values for relative and each class proportional loss differentiation. M-RED is static according to the situation of the network traffic, Network environment is very dynamic situation. Therefore max_p parameter values needs to modify too to the constantly and dynamic. The verification of the guidance is shown with figuring out loss probability using a proposed algorithm under dynamic offered load and is also selection problem of optimal values of parameters for high traffic intensity and show that Dynamic-VQSDDP has the better performance in terms of packet drop rate. We also demonstrated using an ns-2 network simulation.

• Fibers and Polymers
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• v.7 no.4
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• pp.404-413
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• 2006

This study examines multiple quality optimization of the injection molding for Polyether Ether Ketone (PEEK). It also looks into the dimensional deviation and strength of screws that are reduced and improved for the molding quality, respectively. This study applies the Taguchi method to cut down on the number of experiments and combines grey relational analysis to determine the optimal processing parameters for multiple quality characteristics. The quality characteristics of this experiment are the screws' outer diameter, tensile strength and twisting strength. First, one should determine the processing parameters that may affect the injection molding with the $L_{18}(2^1{\times}3^7)$ orthogonal, including mold temperature, pre-plasticity amount, injection pressure, injection speed, screw speed, packing pressure, packing time and cooling time. Then, the grey relational analysis, whose response table and response graph indicate the optimum processing parameters for multiple quality characteristics, is applied to resolve this drawback. The Taguchi method only takes a single quality characteristic into consideration. Finally, a processing parameter prediction system is established by using the back-propagation neural network. The percentage errors all fall within 2%, between the predicted values and the target values. This reveals that the prediction system established in this study produces excellent results.

• The Journal of Korea Robotics Society
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• v.7 no.1
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• pp.9-19
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• 2012

This paper proposes a performance index for the multiple shape object handling of dual arm manipulator to determine whether a robot is good or not. When the dual-arm manipulator grasps a fixed object and is posed, the dual-arm manipulator should procure a space to freely control the manipulator. As a performance evaluation parameter, each joint torque from current sensor signal is utilized. From the current information, torque and energy for each joint are estimated. In this paper an performance index for an unstructured object is defined by an energy-cost function, and stability analysis for each motion is derived by the maximum force to the object. The maximum force to the object is computed by the inertia of object and acceleration information of end-effector. The acceleration data are derived by the double derivation of each encoder signal. Manipulability measure which implies how efficiently the dual-arm manipulator can move with the grasped object, can be represented by the intersection of the two manipulability ellipsoids for the left and right arms. Effectiveness of the proposed algorithm has been verified through the practical simulations and real experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5616-5630
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• 2019

Fully homomorphic encryption allows a third-party to perform arbitrary computation over encrypted data and is especially suitable for secure outsourced computation. This paper investigates secure outsourced computation of multiple matrix multiplication based on fully homomorphic encryption. Our work significantly improves the latest Mishra et al.'s work. We improve Mishra et al.'s matrix encoding method by introducing a column-order matrix encoding method which requires smaller parameter. This enables us to develop a binary multiplication method for multiple matrix multiplication, which multiplies pairwise two adjacent matrices in the tree structure instead of Mishra et al.'s sequential matrix multiplication from left to right. The binary multiplication method results in a logarithmic-depth circuit, thus is much more efficient than the sequential matrix multiplication method with linear-depth circuit. Experimental results show that for the product of ten 32×32 (64×64) square matrices our method takes only several thousand seconds while Mishra et al.'s method will take about tens of thousands of years which is astonishingly impractical. In addition, we further generalize our result from square matrix to non-square matrix. Experimental results show that the binary multiplication method and the classical dynamic programming method have a similar performance for ten non-square matrices multiplication.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.79-84
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• 2017

This paper is a multi-input multi-path (Multiple-input multiple-output: MIMO) using a space-alternating generalized expectation maximization(SAGE) algorithm in the parameter channel and determine the channel estimation performance. Estimated by the algorithm, SAGE time-varying channel environment, the channel parameters estimated from the parameters of the channel measured in the island region 781 of the band in order to compare the performance and compares the original data. This allows you to check the performance of the algorithm SAGE and is highly stable to delay spread (Delay Spread), the diffusion angle of arrival (Arrive of Angular Spread) performance in terms of accuracy down through the SAGE algorithm for estimating a more general calculation parameters.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.173-180
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• 2009

It is difficult to predict non-stationary or chaotic time series which includes the drift and/or the non-linearity as well as uncertainty. To solve it, we propose an effective prediction method which adopts data preprocessing and multiple model TS fuzzy predictors combined with model selection mechanism. In data preprocessing procedure, the candidates of the optimal difference interval are determined based on the correlation analysis, and corresponding difference data sets are generated in order to use them as predictor input instead of the original ones because the difference data can stabilize the statistical characteristics of those time series and better reveals their implicit properties. Then, TS fuzzy predictors are constructed for multiple model bank, where k-means clustering algorithm is used for fuzzy partition of input space, and the least squares method is applied to parameter identification of fuzzy rules. Among the predictors in the model bank, the one which best minimizes the performance index is selected, and it is used for prediction thereafter. Finally, the error compensation procedure based on correlation analysis is added to improve the prediction accuracy. Some computer simulations are performed to verify the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.9
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• pp.854-862
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• 2012

The optimal design of batch-storage network by using periodic square wave model provides analytical lot sizing equations for a complex supply chain network characterized as multi-supplier, multi-product, multi-stage, non-serial, multi-customer, cyclic system including recycling and/or remanufacturing. The network structure includes multiple currency flows as well as material flows. The processes are represented by multiple feedstock/product materials with fixed composition which are very suitable for production processes. In this study, transportation processes that carry multiple materials with unknown composition are added and the time frame is changed from single period into multiple periods in order to represent nonperiodic parameter variations. The objective function of the optimization involves minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders in the numeraire currency. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a multiperiod subproblem for average flow rates and analytical lot-sizing equations. The multiperiod lot sizing equations are different from single period ones. The effects of corporate income taxes, interest rates and exchange rates are incorporated.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.1
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• pp.97-105
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• 2009

In this paper, the performance of AP(Alternating Projection) and EM(Expectation Maximization) algorithms is investigated in terms of detection of multiple signals, resolvability of coherent signals and the efficiency of sensor array processing. The basic idea of these algorithms is utilization of relaxation technique of successive 1D maximization to solve a direction finding problem by maximizing the multidimensional likelihood function. It means that the function is maximized over only for a single parameter while the other parameters are fixed at each step of the iteration. According to simulation results, the algorithms showed good performance for both incoherent and coherent multiple signals. Moreover, some advantages are identified for direction finding with very small samples and fast convergence. The performance of AP algorithm is compared with that of EM using multiple criteria such as the number of sensor, SNR, the number of samples, and convergence speed over uniform circular array. It is resulted AP algorithm is superior to EM overally except for one criterion, convergence speed. Especially, for EM algorithm there is no performance difference between incoherent and coherent case. In conclusion, AP and EM are viable and practical alternatives, which can be applied to a direction under due to the resolvability of multi-path signals, reliable performance and no troublesome eigen-decomposition of the sample-covariance matrix.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.3
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• pp.15-28
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• 2023

The compaction properties of the soil change depending on the physical properties, and are also affected by crushing of the particles. Since the particle size distribution of soil affects the engineering properties of the soil, it is necessary to analyze the material properties to understand the compaction characteristics. In this study, the size of each sieve was classified into four in the particle size analysis as a material property, and the compaction characteristics were evaluated by multiple regression and maximum dry unit weight. As a result of maximum dry unit weight prediction, multiple regression analysis showed R² of 0.70 or more, and DNN analysis showed R² of 0.80 or more. The reliability of the prediction result analyzed by DNN was evaluated higher than that of multiple regression, and the analysis result of DNN-T showed improved prediction results by 1.87% than DNN. The prediction of maximum dry unit weight using particle size distribution seems to be applied to evaluate the compacting state by identifying the material characteristics of roads and embankments. In addition, the particle size distribution can be used as a parameter for predicting maximum dry unit weight, and it is expected to be of great help in terms of time and cost of applying it to the compaction state evaluation.