• Tribology and Lubricants
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• v.4 no.2
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• pp.28-35
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• 1988

A general and efficient algorithm is proposed for the analysis of the frictionless elastic contact problems. It utilizes a simplex-type algorithm with a modified entry rule and incoporates finite element method to obtain flexibility matrices. The algorithmic solution is compared with the Hertzian solution for the contact problem between two cylinders to prove its accuracy and the contact problem between pin and piston rod is solved and compared with the numerical results of Frankavilla and Zienkiewicz to demonstrate the generality and effectiveness of the suggested algorithm. The contact problem between mating involute gear teeth at the worst load position is considered. The computed contact stress is smaller than the result of Hertz's theory applied to the contact between two kinematically equivalent discs and the contact area is larger than that of Hertz's theory.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.9
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• pp.101-110
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• 1998

In process planning for 3D pocket machining, the critical issues for the optimal process planning are the generation of cutting layers and the tool selection for each cutting layers as well as the other factors such as the determination of machining types, tool path, etc. This paper describes the optimal tool selection on a single cutting layer for 2D pocket machining, the generation of cutting layers for 3D pocket machining, the determination of the thickness of each cutting layers, the determination of the tool combinations for each cutting layers and also the development of an algorithm for determining the machining sequence which reduces the number of tool exchanges, which are based on the backward approach. The branch and bound method is applied to select the optimal tools for each cutting layer, and an algorithmic procedure is developed to determine the machining sequence consisting of the pairs of the cutting layers and cutting tools to be used in the same operation.

• The Mathematical Education
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• v.52 no.1
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• pp.111-128
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• 2013

The purpose of this study was to examine and analyze the cognitive demand of the mathematical tasks suggested in the middle school textbooks. In particular, it aimed to reveal the overall picture of the level of cognitive demand of the mathematical tasks in the strand of geometry in the textbooks. We adopted the framework for mathematical task analysis suggested by Stein & Smith(1998) and analyzed the mathematical tasks accordingly. The findings from the analysis showed that 95 percent of the mathematical tasks were at high level and the rest at low level in terms of cognitive demand. Most of the mathematical tasks in the textbooks were algorithmic and focused on producing correct answers by using procedures. In particular, the high level tasks were presented at the end of each chapter or unit for wrap up rather than as key resources.

• Journal of Information Technology Services
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• v.8 no.3
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• pp.223-232
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• 2009

The most popular convergent services are being made mostly out of IT related services and devices. To help understand the underlying principles making convergent services the paper suggests a logical view of converging process. A service is assumed to consist of unit services that can be used in algorithmic operations to form a new convergent service. Convergence operations for a couple of unit services are typed according to whether the unit services are modified. Internal convergence leads to a new service from a combination of sub units of the two unit services. External convergences do not alter original unit services but simply combine them to form a new service. The paper also suggests several measurements to evaluate the convergent services with respect to the existing services used to create the new convergent service.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.25 no.3
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• pp.107-116
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• 2021

We introduce optimization algorithms using Bregman Divergence for solving non-negative matrix factorization (NMF) problems. Bregman divergence is known a generalization of some divergences such as Frobenius norm and KL divergence and etc. Some algorithms can be applicable to not only NMF with Frobenius norm but also NMF with more general Bregman divergence. Matrix Factorization is a popular non-convex optimization problem, for which alternating minimization schemes are mostly used. We develop the Bregman proximal gradient method applicable for all NMF formulated in any Bregman divergences. In the derivation of NMF algorithm for Bregman divergence, we need to use majorization/minimization(MM) for a proper auxiliary function. We present algorithmic aspects of NMF for Bregman divergence by using MM of auxiliary function.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.25-26
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• 2019

소셜 미디어(social media)가 급속히 발달하고 대중화되면서, 뮤지엄(museum)의 관람객은 시 공간의 제약 없이 뮤지엄의 콘텐츠를 향유하는 동시에, 전통적인 관람객의 역할을 넘어 매개자(mediator), 프로슈머(prosumer), 그리고 크리에이터(creator)로 활동하고 있다. 또한, 뮤지엄도 고유의 업무 수행에 다수 관람객의 참여를 유도하며 관람객과 적극적으로 소통하고 있다. 이러한 흐름 속에, 이화여자대학교박물관에서는 소셜 미디어를 기반으로 사전 설문조사를 진행하여 작품에 대한 설문 참여자의 반응을 수집한 후 이를 바탕으로 큐레이션에 대중의 선호도를 반영하는 '관람객 참여전시'를 개최하였다. 더 나아가 알고리즘 기반 전시 큐레이션 모델도 개발하였는데, 이 모델은 앞의 관람객 참여전시에서 얻은 데이터를 활용하여 컴퓨터가 일반 관람객의 개인적 취향에 부합하는 작품을 자동으로 추천하고, 이를 바탕으로 개별 관람객에게 '개인적으로 최적화된' 전시를 구성할 수 있는 기반을 제공한다. 본 논문은 이러한 이화여자대학교박물관의 최신 전시활동을 소개하며, 초연결, 초지능화의 시대에 관람객들이 뮤지엄에 다양하게 참여하고 함께 소통할 수 있는 방법을 모색하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5287-5303
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• 2018

Handling vast amount of data found in large transactional datasets is an obvious challenge for the conventional data mining algorithms. Addressing this challenge, our paper proposes a parallel approach for proper decomposition of mining problem into sub-problems in order to find frequent patterns from these datasets. The proposed, Pattern Mining for Large Distributed Dataset (PMLDD) approach, ensures minimum dependencies as well as minimum communications among sub-problems. It establishes a linear aggregation of the intermediate results so that it can be adapted to large-scale programming models like MapReduce. In this context, an algorithmic structure for MapReduce programming model is presented. PMLDD guarantees an efficient load balancing among the sub-problems by a specific selection criterion. Further, it optimizes the number of required iterations over the dataset for mining frequent patterns as compared to the existing approaches. Finally, we believe that our approach is scalable enough to handle larger datasets in terms of performance evaluation, and the result analysis justifies all these mentioned concerns.

• Advances in aircraft and spacecraft science
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• v.8 no.1
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• pp.69-85
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• 2021

A modified fuzzy mechanical control of large-scale multiple time delayed dynamic systems in states is considered in this paper. To do this, at the first level, a two-step strategy is proposed to divide a large system into several interconnected subsystems. As a modified fuzzy control command, the next was received as feedback theory based on the energetic function and the LMI optimal stability criteria which allow researchers to solve this problem and have the whole system in asymptotically stability. Modeling the Fisher equation and the temperature gauge for high-speed aircraft and spacecraft shows that the calculation method is efficient.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.203-211
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• 2022

Multi-objective optimization problems (MOPs) arise in many real-world applications. MOPs involve two or more objectives with the aim to be optimized. With these problems improvement of one objective may led to deterioration of another. The primary goal of most multi-objective evolutionary algorithms (MOEA) is to generate a set of solutions for approximating the whole or part of the Pareto optimal front, which could provide decision makers a good insight to the problem. Over the last decades or so, several different and remarkable multi-objective evolutionary algorithms, have been developed with successful applications. However, MOEAs are still in their infancy. The objective of this research is to study how to use and apply machine learning (ML) to improve evolutionary multi-objective optimization (EMO). The EMO method is the multi-objective evolutionary algorithm based on decomposition (MOEA/D). The MOEA/D has become one of the most widely used algorithmic frameworks in the area of multi-objective evolutionary computation and won has won an international algorithm contest.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.109.2-109
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• 2001

In the PCB assembly lines, as components become more complex and smaller, the conventional inspection method using traditional ICT and function test show their limitations in application. The automatic optical inspection(AOI) gradually becomes the alternative in the PCB assembly line. In Particular, the PCB inspection machines need more reliable and flexible object recognition algorithms for high inspection accuracy. The conventional AOI machines use the algorithmic approaches such as template matching, Fourier analysis, edge analysis, geometric feature recognition or optical character recognition (OCR), which mostly require much of teaching time and expertise of human operators. To solve this problem, in this paper, a statistical learning based part recognition method is proposed. The performance of the ...