• 산업경영시스템학회지
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• 제8권12호
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• pp.7-12
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• 1985

Line balancing algorithm can be classified by two class, the analytical method and the heuristic method. In this thesis the study was focused on the determinstic line balancing model of the single model production assembly line balancing which is one of the heuristic method. The algorithm of Tonge, Kilbridge & Wester, Helgeson & Birnie which is using the analytical method was examined with one example. And then the algorithms were compared with using line balancing-efficiency, number of work station, standard deviation and range. The result showed that Helgeson & Birnie algorithm is the most convenient in use. A computer program was run in order to use Helgeson & algorithm more conveniently.

• Computational Structural Engineering : An International Journal
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• 제1권1호
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• pp.39-48
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• 2001

An analytical compressive stress-strain relationship model for circular and rectangular concrete specimens confined with laminated carbon fiber sheets (CFS) is studied. Tsai-Hill and Tsai-Wu failure criteria were used to implement orthotropic behavior of laminated composite materials. By using these criteria, an algorithm which analyzes the confinement effect of CFS on concrete was developed. The proposed analytical model was verified through the comparison with experimental data. Various parameters such as concrete strength, ply angle, laminate thickness, section shape, and ply stacking sequences were investigated. Numerical results by the proposed model effectively simulate the experimental compressive stress-strain behavior of CFS confined concrete specimens. Also, the pro-posed model estimates the compressive strength of the specimen to a high degree of accuracy.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.

• 대한기계학회논문집A
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• 제20권6호
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• pp.1773-1783
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• 1996

Finite element method(FEM) is one of the most popularly used method analyzing the dynamic behaviors of structures. But unless number of finite elements is large enough, the results from FEM some what different from exact analytical solutions, especially at high frequency range. On the other hand, as the spectral analysis method(SAM) deals directly with the governing equations of a structure, the results from this melthod cannot but be exact regardless of any frequency range. However, the SAM can be applied only to the case where a structure is subjected to the concentrated loads, despite a structure could be unddergone distributed loads more generally. In this paper, therefore, new spectral analysis algorithm is introduced through the spectral element method(SEM), so that it can be applied to anlystructures whether they are subjected to the concentrated loads or to the distributed loads. The results from this new SEM are compared with both the results from FEM and the exact analytical solutions. As expected, the results from new SEM algorithm are found to be almost identical to the exact analytical solutions while those from FEM are not agreed well with the exact analytical solutions as the mode number increases.

• 전기전자학회논문지
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• 제13권1호
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• pp.1-10
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• 2009

최근 블라인드 적응등화기의 주요 알고리듬 중에 하나인 CMA (Constant Modulus Algorithm) 의 주파수 영역의 고속 알고리듬들이 소개되고 있다 [1,2]. 이중에서 [1] 에서는 입력신호를 블록 단위로 처리하는 비용함수를 사용하고, 보다 최근에 제시된 [2] 에서는 매 입력신호마다 목적함수를 최소한 하는 새로운 알고리듬이 소개되고 있다. 모두다 기존의 알고리듬의 계산량을 줄일 수 있으나, 수렴성에서는 기존의 CMA와 차이가 보여질 것으로 판단된다. 따라서, 본 논문에서는 이러한 주파수 영역 CMA 의 오차평면과 목적함수에 대한 해석적 분석을 통하여, 최근에 제안된 블라인드 등화 알고리듬 [2]가 [1] 보다 국소 최소 값에 빠질 확률이 적어서 수렴성이 개선됨을 보인다. 모의실험결과 이전의 고속 알고리듬 보다 50% 이상의 수렴성 개선결과를 보인다. 또한, 동일조건하에 최신 고속 알고리듬이 기존의 CMA 와 동일한 수렴특성을 나타내는 것을 보인다.

• Journal of Communications and Networks
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• 제18권5호
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• pp.857-869
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• 2016

This paper proposes an X-MAC/BEB protocol that runs a binary exponential backoff (BEB) algorithm on top of an X-MAC protocol to save more energy by reducing collision, especially in densely populated wireless sensor networks (WSNs). X-MAC, a lightweight asynchronous duty cycle medium access control (MAC) protocol, was introduced for spending less energy than its predecessor, B-MAC. One of X-MAC 's conspicuous technique is a mechanism to allow senders to promptly send their data when their receivers wake up. X-MAC, however, has no mechanism to deal with sudden traffic fluctuations that often occur whenever closely located nodes simultaneously diffuse their sense data. To precisely evaluate the impact of the BEB algorithm on X-MAC, this paper builds an analytical model of X-MAC/BEB that integrates the BEB model with the X-MAC model. The analytical and simulation results confirmed that X-MAC/BEB outperformed X-MAC in terms of throughput, delay, and energy consumption, especially in congested WSNs.

• 디지털산업정보학회논문지
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• 제13권4호
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• pp.153-162
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• 2017

Advances in communication technologies and the decreasing cost of computers have made distributed computer systems an attractive alternative for satisfying the information needs of large organizations. This paper presents a distributed algorithm for performance improvement through load balancing and file migration in distributed systems. We employed a sender initiated strategy for task migration and used learning automata with several internal states for file migration. A task can be migrated according to the load information of a computer. A file is migrated to the destination processor when it is in the right boundary state. We also described an analytical model for load balancing with file migration to verify the proposed algorithm. Analytical and simulation results show that our algorithm is very well-suited for distributed system environments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.377-382
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• 2005

This paper presents a new method for the attitude control of planar space robots. In order to control highly constrained non-linear system such as a 3D space robot, the analytical formulation for the system with complex dynamics and effective control methodology based on the formulation, are not always obtainable. In the proposed method, correspondingly, a non-analytical but effective self-organizing modeling method for controlling a highly constrained system is proposed based on a polynomial data mining algorithm. In order to control the attitude of a planar space robot, it is well known to require inputs characterized by a special pattern in time series with a non-deterministic length. In order to correspond to this type of control paradigm, we adopt the Model Predictive Control (MPC) scheme where the length of the non-deterministic horizon is determined based on implementation cost and control performance. The optimal solution to finding the size of the input pattern is found by a solving two-stage programming problem.

• 한국공간구조학회논문집
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• 제3권3호
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• pp.75-83
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• 2003

The purpose of this study is to obtain the optimum shape of cable domes by using the real coding genetic algorithm. Generally, the structural performance of the cable domes is influenced very sensitively by pre-stress, geometry and length of the mast because of flexible system. So, it is very important to decide the optimum shape to get maximum stiffness of cable domes. We use the analytical model to verify the usefulness of this algorithm for shape optimization and analyze the roof system of Seoul olympic gymnastic arena as analytical model of a practical structures. It is confirmed lastly that the optimum shape domes have more stiffness than initial shape ones.

• 한국CDE학회지
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• 제21권2호
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• pp.39-49
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• 2015

This paper presents the single objective design optimization of plate-fin heat sink equipped with fan cooling system using Genetic Algorithm. The proper heat sink and fan model are selected based on the previous studies. And the thermal resistance of heat sinks and fan efficiency during operation are calculated according to specific design parameters. The objective function is combination of thermal resistance and fan efficiency which have been taken to measure the performance of the heat sink. And Decision making procedure is suggested considering life time of semiconductor and Fan Operating cost. And also Analytical Model used for optimization is validated by Fluent, Ansys 13.0 and this model give a quite reasonable and reliable design.