• Transactions of Materials Processing
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• v.24 no.6
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• pp.437-442
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• 2015

The development of polishing technology has enabled the production of injection molds with high quality surfaces and shapes. For products such as mobile phones which require high quality performance the use of plastic materials has many constraints such as shrinkage and deflection. The purpose of the current research is to use reverse engineering in order to find and analyze the data of a selected aspherical lens and then creating a process to design an improved lens. Additionally, the improved lenses are subject to molding analysis. In order to solve this problem, the lens construction program, Zemax, was used to analyze and optimize performance. In the case of optimization, the object was to eliminate spherical aberration and to find good MTF data. The result of the optimization data was similar to the MTF data found from a random lens. Specific resin and analysis conditions were selected and CAD modeling was done to enhance the injection molding analysis.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1355-1364
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• 1996

A complex object model is one of the value based data model which extends the existing relational data model for supporting complex structured data. This paper studies a method for designing algebra for the complex object model. For this some others' algebra supporting complex objects are compared and analysed in terms of the applicability of a algebraic optimization strategics. The complex object algebra is designed, based on four principles, simple and clear definitions, no restriction on input data, single specification system. The central nature of this paper is to keep the basis of algebraic optimization method through simplicity, safety and the applicability of algebraic optimization strategy. Finally, it shown that the designed algebra has the equivalent or enhanced expressability with other's algebra.

• The Journal of the Acoustical Society of Korea
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• v.34 no.1
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• pp.82-91
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• 2015

In this paper, a novel codebook design method for data modem over voice channel is presented. Proposed method searches the symbols which have the maximum probability distribution overlap in the symbol space and minimizes the overlap to improve the symbol error rate via minimax optimization. We present numerical simulations and an example implementation. We also give the results of the experiment tests.

• Transactions of the Society of Information Storage Systems
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• v.9 no.1
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• pp.5-9
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• 2013

Page-oriented holographic data storage (HDS) is very sensitive to the disturbances. However, vibration effect by disc imbalance can be ignored because data pages are recorded and retrieved with stop-go rotation. Therefore, just estimating de-track due to eccentricity of disc is enough to construct stable track servo system. In this paper, propose the spacing of track servo patterns optimization method using Least Mean Square (LMS) estimation algorithm. Through the patterns spacing optimization, storage density maximize can be achieved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1877-1891
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• 2022

As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.

• Genomics & Informatics
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• v.9 no.3
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• pp.134-135
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• 2011

DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.377-384
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• 2023

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.383-392
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• 2014

The research for coatings is one of the most popular and active research in the polymer industry. For the coatings, electronics industry, medical and optical fields are growing more important. In particular, the trend is the increasing of the technical requirements for the performance and accuracy of the coatings by the development of automotive and electronic parts. In addition, the industry has a need of more intelligent and automated system in the industry is increasing by introduction of the IoT and big data analysis based on the environmental information and the context information. In this paper, we propose an optimization model for the design of experiments based coating formulation data objects using the Internet technologies and big data analytics. In this paper, the coating formulation was calculated based on the best data analysis is based on the experimental design, modify the operator with respect to the error caused based on the coating formulation used in the actual production site data and the corrected result data. Further optimization model to correct the reference value by leveraging big data analysis and Internet of things technology only existing coating formulation is applied as the reference data using a manufacturing environment and context information retrieval in color and quality, the most important factor in maintaining and was derived. Based on data obtained from an experiment and analysis is improving the accuracy of the combination data and making it possible to give a LOT shorter working hours per data. Also the data shortens the production time due to the reduction in the delivery time per treatment and It can contribute to cost reduction or the like defect rate reduced. Further, it is possible to obtain a standard data in the manufacturing process for the various models.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.5 s.236
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• pp.625-632
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• 2005

This paper describes the shape optimization of a stator blade in a single-stage transonic axial compressor. The blade optimization has been performed using response surface method and three-dimensional Navier-Stokes analysis. Two shape variables of the stator blade, which are used to define a stacking line, are introduced to increase an adiabatic efficiency. Data points for response evaluations have been selected by D-optimal design, and linear programming method has been used for an optimization on a response surface. Throughout the shape optimization of a stator blade, the adiabatic efficiency is increased to 5.8 percent compared to that of the reference shape of the stator. The increase of the efficiency is mainly caused by the pressure enhancement in the stator blade. Flow separation on the blade suction surface of the stator is also improved by optimizing the stator blade. It is noted that the optimization of the stator blade is also useful method to increase the adiabatic efficiency in the axial compressor as well as the optimization of a rotor blade, which is widely used now.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.204-206
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• 2007

In this study, we introduce the optimization method of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation, The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods. Particularly, in parameter identification, we use the UNDX operator which uses multiple parents and generate offsprings around the geographic center off mass of these parents.