• 대한인간공학회지
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• 제24권2호
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• pp.1-8
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• 2005

A new design of shoulder straps and frame of backpack is proposed for reducing compression and fatigue of shoulder. The stress reduction effects of a backpack equipped with the newly designed shoulder straps and frame have been analyzed statistically through various experiments. We show that the newly designed shoulder straps(wider than the conventional ones) is superior to existing shoulder straps in respect of RPE, task performance measure and physiological measure. The new frame is also proven to be superior to existing frame in respect of RPE and task performance measure. In conclusion, the proposed shoulder straps and frame are shown to enhance the task performance of soldiers.

• 품질경영학회지
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• 제33권4호
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• pp.96-102
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• 2005

Cusum control chart is an efficient method to detect the change of process status. Many variants of cusum have considered, and the effects of design parameters have reviewed. To find the best cusum out of variants and to decide the best values of the design parameters, we need a criterion measuring the performance of the cusum control chart. People used and suggested several criterions which appear to be similar, but those have quite different properties. In this paper we review the properties of performance measure of cusum and its variants. Our goal is to provide fair and impartial criterion for comparison of cusums when the decision boundaries of the cusums are much different each other. We comparatively tested newly suggested measure and traditional measure with the examples of cumulative scored chart as a special case of cusum chart.

• 품질경영학회지
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• 제37권1호
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• pp.56-68
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• 2009

A measure for service quality of university dormitory is developed to gain a better understanding of the quality issues that impact on students' experiences and to improve service quality. Literature survey, thorough discussion with staff members and a pilot test are utilized to elicit attributes of service quality. Factor analysis is used to group the service quality attributes into dimensions. The resulting measure is consisted of 6 dimensions; competence, attitude, facility, amenity, security and discipline. Importance-performance analysis is utilized to verify which factors to be focused on with high Priority to improve dormitory service.

• 한국정보과학회논문지:소프트웨어및응용
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• 제26권1호
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• pp.130-130
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• 1999

In this paper, we propose a novel design method for improving performance of existing FCM-type clustering algorithms. First, we define the performance measure which focuses on bothcompactness and separation of clusters. Next, we optimize this measure using evolution program.Especially the proposed method has following merits: ① using evolution program, it solves suchproblems as initialization, number of clusters, and convergence to local optimum ② it reduces searchspace and improves convergence speed of algorithm since it represents chromosome with possiblepotential centers which are selected possible candidates of centers by density measure ③ it improvesperformance of clustering algorithm with the performance index which embedded both compactnessand separation Properties ④ it is robust to noise data since it minimizes its effect on center search.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.191-196
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• 1998

A new Fuzzy Logic Controller(FLC) called a Gradient-Descent Based Self-Organizing Controller is presented. The Self-Organizing Controller(SOC) has two inputs such as error and change of error, and updates control rules with monitoring a performance measure. There are many works in the SOC which concentrate on the self-organizing ability in control rule base, but have a few research on the performance measure which is akin to sliding mode control. With this procedure, we can get a robust performance measure on the SOC. To verify the perfomance of proposed controller, we have performed for the cart-pole system which is one of the well-known benchmark problem in the control literature.

• International Journal of Quality Innovation
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• 제8권1호
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• pp.1-14
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• 2007

The Six Sigma and Lean Production methodologies suggest that creating value for customers is the objective of a production process or an organisation. In the production context, "added value" dominates the discussion about the creation of value to customers. However, "added value" is often only defined conceptually or discussed at a strategic level, and the link between added value and customer value has not yet been well conceptualised. Therefore, the purpose of the paper is to develop a methodology to measure added value in order to complement the existing performance measures in Six Sigma and Lean Production by conceptualising the link between customer value and added value. The conceptual link "confirms" that quality, time, and costs are the elements of added value, which are transformed into a metric to express customer value. The implementation of the metric recommends the adoption of Lean (Six) Sigma and Lean Accounting (Activity Based Costing), which thus implies that "leanness" is an important "feature" of added value.

• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.77-82
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• 2019

Collaborative filtering is a popular technique for recommender systems and used in many practical commercial systems. Its basic principle is select similar neighbors of a current user and from their past preference information on items the system makes recommendations for the current user. One of the major problems inherent in this type of system is data sparsity of ratings. This is mainly caused from the underlying similarity measures which produce neighbors based on the ratings records. This paper handles this problem and suggests a new similarity measure. The proposed method takes users rating patterns into account for computing similarity, without just relying on the commonly rated items as in previous measures. Performance experiments of various existing measures are conducted and their performance is compared in terms of major performance metrics. As a result, the proposed measure reveals better or comparable achievements in all the metrics considered.

• ETRI Journal
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• 제44권5호
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• pp.769-779
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• 2022

Spectral clustering has become a typical and efficient clustering method used in a variety of applications. The critical step of spectral clustering is the similarity measurement, which largely determines the performance of the spectral clustering method. In this paper, we propose a novel spectral clustering algorithm based on the local similarity measure of shared neighbors. This similarity measurement exploits the local density information between data points based on the weight of the shared neighbors in a directed k-nearest neighbor graph with only one parameter k, that is, the number of nearest neighbors. Numerical experiments on synthetic and real-world datasets demonstrate that our proposed algorithm outperforms other existing spectral clustering algorithms in terms of the clustering performance measured via the normalized mutual information, clustering accuracy, and F-measure. As an example, the proposed method can provide an improvement of 15.82% in the clustering performance for the Soybean dataset.

• 한국컴퓨터정보학회논문지
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• 제23권12호
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• pp.219-226
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• 2018

Collaborative filtering has been most popular approach to recommend items in online recommender systems. However, collaborative filtering is known to suffer from data sparsity problem. As a simple way to overcome this problem in literature, Jaccard index has been adopted to combine with the existing similarity measures. We analyze performance of such combination in various data environments. We also find optimal weights of factors in the combination using a genetic algorithm to formulate a similarity measure. Furthermore, optimal weights are searched for each user independently, in order to reflect each user's different rating behavior. Performance of the resulting personalized similarity measure is examined using two datasets with different data characteristics. It presents overall superiority to previous measures in terms of recommendation and prediction qualities regardless of the characteristics of the data environment.

• 한국시스템다이내믹스연구
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• 제8권1호
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• pp.211-227
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• 2007

Like the saying "You can't manage what you can't measure," performance measurement is considered as one of the most important management activities for the organizations in either private or public sector. Performance measurement, however, has thus far relied too much on financial statements. Realizing the importance of a more scientific and comprehensive performance measurement, many organizations have adopted several different systems in order to objectively estimate their balanced performance results. The Balanced Scorecard (BSC) has become a popular means to measure performance. But the BSC has also received some criticisms. In this paper four limitations in the use of the BSC are discussed : BSCs focus on unidirectional causality, are unable to distinguish delays between actions and their impacts on performance, integrate insufficiently strategy with operational measures, and lead to internal biases. We propose a system dynamics approach with causal loop diagram(CLD) to develop a Dynamic BSC in order to overcome these limitations. The results suggest that developing a BSC with system dynamics is a promising approach to supplement existing BSC frameworks.