• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.87-93
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• 2012

This paper discusses a new weighting method for text analyzing from the view point of supervised learning. The term frequency and inverse term frequency measure (tf-idf measure) is famous weighting method for information retrieval, and this method can be used for text analyzing either. However, it is an experimental weighting method for information retrieval whose effectiveness is not clarified from the theoretical viewpoints. Therefore, other effective weighting measure may be obtained for document classification problems. In this study, we propose the optimal weighting method for document classification problems from the view point of supervised learning. The proposed measure is more suitable for the text classification problem as used training data than the tf-idf measure. The effectiveness of our proposal is clarified by simulation experiments for the text classification problems of newspaper article and the customer review which is posted on the web site.

• Nuclear Engineering and Technology
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• v.1 no.2
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• pp.79-85
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• 1969

Determination of a two-point boundary value problem is the key of finding the control function u(f) with the application of the fundamental idea of Minimum principle. The late development shows the discovery of the initial testate vector for the solution of a two-point value problem. As a new technique of determining the optimal control function, Newton's sequential method is examined in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.10
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• pp.121-129
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• 1995

The objective of this research is to develop an effective inspection planning strategy for sculptured surfaces by using 3-dimensional Coordinate Measuring Machine (CMM). First, the CAD/CAM database is generated by using the Bezier surface patch mathod and variable cutter step size approach for design and machining of the workpiece model. Then, optimum measuring point locations are determained based on the mean curvature analysis to obtain more effective inspection results for the given sample numbers. An optimal probe sequence generation method is proposed by implementing the Traveling Salesperson (TSP) algorithm and new guide point selection methods are suggested based on the concepts of the variable distance between the first and second guide points. Finally, simulation study and experimental work show the effectiveness of the proposed strategy.

• Journal of the Korean Institute of Gas
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• v.4 no.2 s.10
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• pp.7-14
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• 2000

LNG (Liquified Natural Gas) carried by LNG ship is unloaded into the LNG storage tanks at the very low temperature (a little lower than the boiling point of LNG). Because LNG is unloaded through the pipeline, two phase flow appears in the pipeline. In this study, we have studied the pressure-drop mechanisms of the two-phase flow in the pipeline, and the calculation method of BOG (Boil-off Gas) amount based on the heat transfer mechanism through the insulation and the surface of the pipeline. We have developed a computer program for thermal-hydraulic analysis on the LNG pipeline system. We have also developed the optimal design program to find the optimal thickness of insulation and the pipeline size. The program searches the optimal design with the minimum capital cost of pipelines and insulation on the operating conditions of maximum allowance pressure-drop and BOG amount, etc.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1202-1211
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• 2018

In this paper, induction machine operation efficiency and torque is improved using Machine Learning based Gene Optimization (ML-GO) Technique is introduced. Optimized Genetic Algorithm (OGA) is used to select the optimal induction machine data. In OGA, selection, crossover and mutation process is carried out to find the optimal electrical machine data for induction machine design. Initially, many number of induction machine data are given as input for OGA. Then, fitness value is calculated for all induction machine data to find whether the criterion is satisfied or not through fitness function (i.e., objective function such as starting to full load torque ratio, rotor current, power factor and maximum flux density of stator and rotor teeth). When the criterion is not satisfied, annealed selection approach in OGA is used to move the selection criteria from exploration to exploitation to attain the optimal solution (i.e., efficient machine data). After the selection process, two point crossovers is carried out to select two crossover points within a chromosomes (i.e., design variables) and then swaps two parent's chromosomes for producing two new offspring. Finally, Adaptive Levy Mutation is used in OGA to select any value in random manner and gets mutated to obtain the optimal value. This process gets iterated till finding the optimal value for induction machine design. Experimental evaluation of ML-GO technique is carried out with performance metrics such as torque, rotor current, induction machine operation efficiency and rotor power factor compared to the state-of-the-art works.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.45-66
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• 2008

Refuse collection, one of important elements in reverse logistics, is an activity rendering recyclables or wastes and moving them to some points where further treatment is required. Among various decisions in the collection activity, we focus on network design, which is the problem of locating collection points as well as allocating refuses at demand points to collection points while satisfying the capacity restriction at each collection point. Here, the collection point is the place where recyclables or wastes near the point are gathered, and locating the collection points is done by selecting them from a given set of potential sites. The objective is to minimize the sum of fixed costs to open collection points and transportation costs to move refuses from demand points to collection points. An integer programming model is developed to represent the problem mathematically and due to the complexity of the problem, two types of heuristics, one with simultaneous and the others with separate location and allocation, are suggested. Computational experiments were done on test problems up to 500 potential sites, and the results are reported. In particular, some heuristics gave near optimal solutions for small-size test problems, i.e., 2% gaps in average from the optimal solution values.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.53-63
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• 2017

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.15-25
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• 2010

The objective of this study is to investigate the optimal arrangement of cameras used for the robot's vision control scheme. The used robot's vision control scheme involves two estimation models, which are the parameter estimation and robot's joint angle estimation models. In order to perform this study, robot's working region is divided into three work spaces such as left, central and right spaces. Also, cameras are positioned on circular arcs with radius of 1.5m, 2.0m and 2.5m. Seven cameras are placed on each circular arc. For the experiment, nine cases of camera arrangement are selected in each robot's work space, and each case uses three cameras. Six parameters are estimated for each camera using the developed parameter estimation model in order to show the suitability of the vision system model in nine cases of each robot's work space. Finally, the robot's joint angles are estimated using the joint angle estimation model according to the arrangement of cameras for robot's point-position control. Thus, the effect of camera arrangement used for the robot's vision control scheme is shown for robot's point-position control experimentally.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1009-1013
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• 2007

To do a HRTF customization, researchers used a spherical head model for modeling the head block of structural modeling of HRTF, which is the one of the technique for HRTF customization, because of its simplicity. In this paper, an analytic spheroidal HRTF caused by an incident point source will be introduced. Using proposed spheroidal HRTF, near-field HRTF customization can be applicable through a structural modeling of HRTF. To see the necessity of sheroidal head model, comparison of two analytic solutions, which are classical spherical HRTF and proposed spheroidal HRTF, will be shown. On the view point of ITD, optimal head model which matches with the measured ITD of KEMAR HRTF can be obtained. ITD results show that there are only slight differences between spherical and spheroidal head model. Magnitude comparison is made by constructing head model using measured head size. Although magnitude comparison is not studied between optimal models, the results of 24 of 36 subjects are shown that spheroidal head model matches notch frequency pattern of measured HRTF better than those of spherical one, where the sound source is at contralateral position.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2211-2220
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• 2015

This paper analyzes multiple active management (AM) techniques of active distribution network (ADN), and proposes an optimal coordination model of intermittent distributed generation (IDG) accommodation considering the timing characteristic of load and IDG. The objective of the model is to maximize the daily amount of IDG accommodation under the uncertainties of IDG and load. Various active management techniques such as IDG curtailment, on-load tap changer (OLTC) tap adjusting, voltage regulator (VR) tap adjusting, shunt capacitors compensation and so on are fully considered. Genetic algorithm and Primal-Dual Interior Point Method (PDIPM) is used for the model solving. Point estimate method is used to simulate the uncertainties. Different scenarios are selected for the IDG accommodation capability investigation under different active management schemes. Finally a modified IEEE 123 case is used to testify the proposed accommodation model, the results show that the active management can largely increase the IDG accommodation and penetration.