• Title/Summary/Keyword: grouping efficiency

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Cluster Analysis-based Approach for Manufacturing Cell Formation (제조 셀 구현을 위한 군집분석 기반 방법론)

  • Shim, Young Hak;Hwang, Jung Yoon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.36 no.1
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    • pp.24-35
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    • 2013
  • A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation, which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.

Default Prediction of Automobile Credit Based on Support Vector Machine

  • Chen, Ying;Zhang, Ruirui
    • Journal of Information Processing Systems
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    • v.17 no.1
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    • pp.75-88
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    • 2021
  • Automobile credit business has developed rapidly in recent years, and corresponding default phenomena occur frequently. Credit default will bring great losses to automobile financial institutions. Therefore, the successful prediction of automobile credit default is of great significance. Firstly, the missing values are deleted, then the random forest is used for feature selection, and then the sample data are randomly grouped. Finally, six prediction models of support vector machine (SVM), random forest and k-nearest neighbor (KNN), logistic, decision tree, and artificial neural network (ANN) are constructed. The results show that these six machine learning models can be used to predict the default of automobile credit. Among these six models, the accuracy of decision tree is 0.79, which is the highest, but the comprehensive performance of SVM is the best. And random grouping can improve the efficiency of model operation to a certain extent, especially SVM.

Practical method to improve usage efficiency of bike-sharing systems

  • Lee, Chun-Hee;Lee, Jeong-Woo;Jung, YungJoon
    • ETRI Journal
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    • v.44 no.2
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    • pp.244-259
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    • 2022
  • Bicycle- or bike-sharing systems (BSSs) have received increasing attention as a secondary transportation mode due to their advantages, for example, accessibility, prevention of air pollution, and health promotion. However, in BSSs, due to bias in bike demands, the bike rebalancing problem should be solved. Various methods have been proposed to solve this problem; however, it is difficult to apply such methods to small cities because bike demand is sparse, and there are many practical issues to solve. Thus, we propose a demand prediction model using multiple classifiers, time grouping, categorization, weather analysis, and station correlation information. In addition, we analyze real-world relocation data by relocation managers and propose a relocation algorithm based on the analytical results to solve the bike rebalancing problem. The proposed system is compared experimentally with the results obtained by the real relocation managers.

Segmentation of Airborne LIDAR Data: From Points to Patches (항공 라이다 데이터의 분할: 점에서 패치로)

  • Lee Im-Pyeong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.24 no.1
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    • pp.111-121
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    • 2006
  • Recently, many studies have been performed to apply airborne LIDAR data to extracting urban models. In order to model efficiently the man-made objects which are the main components of these urban models, it is important to extract automatically planar patches from the set of the measured three-dimensional points. Although some research has been carried out for their automatic extraction, no method published yet is sufficiently satisfied in terms of the accuracy and completeness of the segmentation results and their computational efficiency. This study thus aimed to developing an efficient approach to automatic segmentation of planar patches from the three-dimensional points acquired by an airborne LIDAR system. The proposed method consists of establishing adjacency between three-dimensional points, grouping small number of points into seed patches, and growing the seed patches into surface patches. The core features of this method are to improve the segmentation results by employing the variable threshold value repeatedly updated through a statistical analysis during the patch growing process, and to achieve high computational efficiency using priority heaps and sequential least squares adjustment. The proposed method was applied to real LIDAR data to evaluate the performance. Using the proposed method, LIDAR data composed of huge number of three dimensional points can be converted into a set of surface patches which are more explicit and robust descriptions. This intermediate converting process can be effectively used to solve object recognition problems such as building extraction.

Studies on the Nutrition Under Abnormal Environment(III) - Influence of Vibration on Growth and Metabolism - (이상환경하(異常環境下)의 영양문제연구(營養問題硏究) 제3보(第3報) - 진동(振動)이 성장(成長) 및 대사(代謝)에 미치는 영향(影響) -)

  • Yu, Jong-Yull;Lee, Sung-Dong
    • Journal of Nutrition and Health
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    • v.9 no.4
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    • pp.11-18
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    • 1976
  • In this third report influence of vibration on growth and on some metabolism of young growing rats fed on varying levels of protein was investigated. Forty eight (48) young growing male rats weighing about 60 grams were used, grouping to four (4) groups, twelve (12) rats each group. They were fed on 8%, 13%, 19%, and 26% casein diet respectively (See the table 1) for the period of 10 weeks experiment. During the experimental period the half number of the rats of each group were subjected to a given degree of vibration for two (2) hours daily. Observations for growth rate, food and protein efficiency ratios, organs development, cholesterol levels in aorta, total nitrogen, urea nitrogen and creatinine levels in urine may be summarized as follows 1. Growth was impaired by the vibration in all groups including 26% easein diet. 2. There is tendeney that in higher protein diets, the organs (See table 3) developed more well. And also the impairment of the organs development by the vibration revealed less in higher protein diets. 3. Food and protein efficiency ratios were generally decreased under vibration and the food efficiency was improved by increasing the protein level in diet. 4. Total and free cholesteral levels in aorta were increased by the vibration. Ester from/tatal ratio was 17.7% and 17.3% respectively at 8% and 13% protein diets and 54.8% and 54.2% at 19% and 26% protein diets. These show that, in higher protein diets, the vibration doesn't influence the cholesterol ratio. 5. Total nitrogen, urea nirogen and creatinine levels in urine were increased by increasing the protion level in diet and also increased by the vibration. 6. It seems that, according to the above observations, the vibration used in this experiment influenced, in certain extent, on physical development, physiological availability of nutrients, and on body metabolism. And it is also thought that higher protein diets act some good role in protecting body from suffering from vibration.

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Optimal Clustering of Energy Storage System for Frequency Regulation Service Considering Life Degradation (수명감소를 고려한 주파수 조정용 에너지저장장치의 최적 클러스터링)

  • Kim, Wook-Won;Kim, Jin-O
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.4
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    • pp.555-560
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    • 2016
  • Recently, many countries have placed great attention on energy security and climate changes. Governments are promoting the construction of renewable energy projects with regulatory support in Korea. Despite an increasing penetration of renewable resources, however, the photovoltaic and wind power are underutilized due to the endemic problems such as difficulties of output control and intermittent output. The Energy Storage System (ESS) is proposed as a good solution for solving the problems and has been studied in both the private business and the government. However, because of inefficient aspects, the research has been carried out for improving high costs and a small capacity. In addition, the ESS is currently installed for using only one purpose which is frequency regulation or transmission congestion relief such that has an economic limitation. Therefore, methods which are becoming economically justifiable to increase the penetration of the ESS is required. Thus, this paper presents in terms of operation efficiency to improve economic feasibility of the ESS currently used. mainly, there are two aspects for the operation efficiency. Firstly, it is intended to improve the utilization rate through a process that can utilize the ESS for various purposes. It is necessary to be able to use for other purposes by classifying and clustering for increasing the efficiency of availability. The clustering method is proposed to conduct the grouping the ESS. Especially, it is proposed to utilize ESS for frequency regulation service which is the one of ancillary services in the power system. Through case studies, it is confirmed to secure the necessary resources by clustering small size ESS.

Group Management Structure of Segments for P2P-based On Demand Streaming Services (P2P 기반의 사용자 주문형 스트리밍 서비스를 위한 세그먼트 그룹 관리 구조)

  • Lee, Chong-Deuk;Jeong, Taeg-Won
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.7
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    • pp.1621-1630
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    • 2009
  • There is a lot of recent research to provide services of dynamic distributed contents in P2P-based distributed environment. Distributed services of contents objects, however, have problems in QoS and dynamic management of segments. This paper proposed a new segment management method for the service of P2P-based distributed contents. The proposed method manages groups by the SGM(Segment Group Manager). The SGM manages streaming efficiently by the grouping of segments to be served in P2P environment. The segments in the same group cooperate for improved QoS using the management structure based on the distance and relationship. The distance-based management structure is for the improvement of retrieval efficiency while the relationship-based management structure is for the improvement of service ratio. The simulation results of the proposed method showed improvements in average transmission efficiency and average service rate. The improvement is 8% - 30% in average transmission efficiency and 10% - 30% in average service rate.

R&D Strategy Development for Nanotechnology Areas based on Efficiency Comparisons (효율성 비교를 통한 나노기술 분야별 R&D 전략 수립)

  • Bae, Seoung-Hun;Kim, Jun-Hyun;Jung, Yeon-Ju;Kang, Sang-Kyu;Kim, Jae-Sin;Kim, Heung-Kyu
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.40 no.2
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    • pp.31-40
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    • 2017
  • In this paper, we compared the efficiencies of national R&D investments between NT (Nanotechnology) areas in terms of papers, patents, and commercializations, and found ways to improve the efficiencies of national R&D investments for each NT area. This is in response to huge R&D investments government has made recently in NT areas. Here, we collected data on investments, papers, patents, and commercializations for the R&D projects in NT areas through National Science & Technology Information Service. Based on the data, we analyzed the investment and performances (papers, patents, and commercializations) for each NT area, calculated the efficiency for each NT area, and compared the efficiencies between NT areas. Next, using cluster analysis, we identified several NT areas with similar characteristics in terms of paper efficiency, patent efficiency and commercialization efficiency. Finally, we derived implications for the efficiency enhancement for each grouping. The cluster analysis showed that there could be two groups, one being low in terms of technological outcome (papers and patents) efficiencies and high in terms of commercialization efficiencies, while the other being high in terms of technological outcome (papers and patents) efficiencies and low in terms of commercialization efficiencies. Therefore, the strategy for one group calls for support for technology transfer or technology introduction from other R&D performers and grant of guidance for improving R&D performers' commercialization ability to other R&D performers while the strategy for the other group calls for R&D support for transfer of technology to other R&D performers, activation of technology transfer and support for commercialization of R&D performers.

A Study on the Economic Efficiency of Capital Market (자본시장(資本市場)의 경제적(經濟的) 효율성(效率性)에 관한 연구(硏究))

  • Nam, Soo-Hyun
    • The Korean Journal of Financial Management
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    • v.2 no.1
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    • pp.55-75
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    • 1986
  • This article is to analyse the economic efficiency of capital market, which plays a role of resource allocation in terms of financial claims such as stock and bond. It provides various contributions to the welfare theoretical aspects of modern capital market theory. The key feature that distinguishes the theory described here from traditional welfare theory is the presence of uncertainty. Securities has time dimensions and the state and outcome of the future are really uncertain. This problem resulting from this uncertainty can be solved by complete market, but it has a weak power to explain real stock market. Capital Market is faced with the uncertainity because it is a kind of incomplete market. Individuals and firms in capital market made their consumption-investment decision by their own criteria, i. e. the maximization of expected utility form intertemporal consumption and the maximization of the market value of firm. We noted that allocative decisions that had to be made in the economy could be naturally subdivided into two groups. One set of decisions concerned the allocation of first-period resources among consumption $C_i$, investment in risky firms $I_j$, and riskless investment M. The other decisions concern the distribution among individuals of income available in the second period $Y_i(\theta)$. Corresponing to this grouping, the theoretical analysis of efficiency has also been dichotomized. The optimality of the distribution of output in the second period is distributive efficiency" and the optimality of the allocation of first-period resources is 'the efficiency of investment'. We have found in the distributive efficiency that the conditions for attainability is the same as the conditions for market optimality. The necessary and sufficient conditions for attainability or market optimality is that (1) all utility functions are such that -$\frac{{U_i}^'(Y_i)}{{U_i}^"(Y_i)}={\mu}_i+{\lambda}Y_i$-linear risk tolerance function where the coefficients ${\mu}_i$ and $\lambda$ are independent of $Y_i$, and (2) there are homogeneous expectations, i. e. ${\Large f}_i(\theta)={\Large f}(\theta)$ for every i. On the other hand, the efficiency of investment has disagreement about optimal investment level. The investment level for market rule will not generally lead to Pareto-optimal allocation of investment. This suboptimality is caused by (1)the difference of Diamond's decomposable production function and mean-variance valuation model and (2) the selection of exelusive investment or competitive investment. In conclusion, this article has made an analysis of conditions and processes of Pareto-optimal allocation of resources in capital marker and tried to connect with significant issues in modern finance.

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A hybrid algorithm based on EEMD and EMD for multi-mode signal processing

  • Lin, Jeng-Wen
    • Structural Engineering and Mechanics
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    • v.39 no.6
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    • pp.813-831
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    • 2011
  • This paper presents an efficient version of Hilbert-Huang transform for nonlinear non-stationary systems analyses. An ensemble empirical mode decomposition (EEMD) is introduced to alleviate the problem of mode mixing between intrinsic mode functions (IMFs) decomposed by EMD. Yet the problem has not been fully resolved when a signal of a similar scale resides in different IMF components. Instead of using a trial and error method to select the "best" outcome generated by EEMD, a hybrid algorithm based on EEMD and EMD is proposed for multi-mode signal processing. The developed approach comprises the steps from a bandpass filter design for regrouping modes of the IMFs obtained from EEMD, to the mode extraction using EMD, and to the assessment of each mode in the marginal spectrum. A simulated two-mode signal is tested to demonstrate the efficiency and robustness of the approach, showing average relative errors all equal to 1.46% for various noise levels added to the signal. The developed approach is also applied to a real bridge structure, showing more reliable results than the pure EMD. Discussions on the mode determination are offered to explain the connection between modegrouping form on the one hand, and mode-grouping performance on the other.