• Proceedings of the Technology Innovation Conference
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• 2006.02a
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• pp.5-20
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• 2006

An efficient and productive R&D operation is a major source of competitive advantage in today's economy, and a lot of efforts are made to raise R&D productivity. A prerequisite for making R&D more efficient and productive is to be able to measure it. Hence, a number of studies have attempted to measure R&D productivity. R&D productivity, in the previous studies, was measured with patents at the firm or industry level. However, most previous studies considered only a quantitative aspect, not a quantitative aspect of patents. In this study, various dimensions of patent quality as well as patent quantity were considered for the measurement of R&D performance. The differences in R&D performance across sectors were examined, and it was found that electrical/electronic industry shows higher R&D performance than mechanic and chemical industries. Discriminant analysis based on inputs and outputs for R&D shows' that there exist a strong discriminatory power across industries. The results of this research can provide the directions 'for the firm's R&D policy.

• Speech Sciences
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• v.15 no.4
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• pp.85-96
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• 2008

Automatic speech recognition has severe performance degradation under noisy environments. To cope with the noise problem, many methods have been proposed. Most of them focused on noise-robust features or model adaptation. However, researchers have overlooked utterance verification (UV) under noisy environments. In this paper we discuss UV problems based on the normalized confidence measure. First, we show that UV performance is also degraded in noisy environments with the experiments of an isolated word recognition. Then we observe how the degradation of UV performances is suffered. Based on the UV experiments we propose a modeling method of the statistics of phone confidences using sigmoid functions. For obtaining the parameters of the sigmoidal models, the particle swarm optimization (PSO) is adopted. The proposed method improves 20% rejection performance. Our experimental results show that the PSO-NCM can apply noise speech recognition successfully.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.3
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• pp.189-198
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• 1998

This study explored the effects of expectatioin, performance, and disconfirmatoni on satisfaction of theme park users. Everland was chosen as the study area, and 260 users were selected by the nonprobability sampling. In expectation disconfirmation paradigm, expectation should be measured before purchase, and performance, disconfirmation and satisfaction should be measured after purchase. An entrance survey was done to measure expectation, and an exit survey to measure performance, disconfirmation, and satisfaction. Maximum likelihood method was used to estimate structural equation model by the LISREL 7.2. Performance had the most significant effect on satisfaction among three variables. The satisfaction of theme park users depends largely on it, therefore, the consideration of visitors' performance should e essential for managers.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.148-151
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• 2009

We consider the problem of optimizing the performance of a system with resources shared by non-cooperative users. The worst-cast ratio between the cost of a Nash equilibrium and the optimal cost, called Price of Anarchy, is investigated. It measures the performance degradation due to the users' selfish behavior. As the objective function of the optimization problem, we are concerned in a load balancing measure, which is different from that used in the previous works. Also we consider the Stackelberg scheduling which can assign a fraction of the users to resources while the remaining users are free to act in a selfish manner.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2004-2007
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• 2003

This paper describes a method of performance enhancement using Flatness Mesure(FM) for the Gaussian Mixture Model(GMM) face recognition systems. Using this measure we discard the frames having low information before training and test. As the result, the performance increases about 9％ in the lower mixtures and calculation burden is decreased. As well, the recognition error rate is decreased under the illumination change surroundings. We use the 2D DCT coefficients lot face feature vectors and experiments are carried out on the Olivetti Research Laboratory (ORL) face database.

• ETRI Journal
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• v.29 no.5
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• pp.697-699
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• 2007

Spatiograms are histograms augmented with spatial means and covariances to capture a richer description of the target. We present a particle filtering framework for region-based tracking using spatiograms. Unlike mean shift, the framework allows for non-differentiable similarity measures to compare two spatiograms; we present one such similarity measure, a combination of a recent weighting scheme and histogram intersection. Experimental results show improved performance with the new measure as well as the importance of global spatial information for tracking. The performance of spatiograms is compared with color histograms and several texture histogram methods.

• Journal of Korean Association for Spatial Structures
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• v.17 no.2
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• pp.53-62
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• 2017

This study aims to establish a seismic resistance performance evaluation method that makes sure to secure the seismic resistance performance of the existing mid-low story reinforced concrete structures. This study focuses on the development of the seismic resistance performance evaluation method for the overall seismic resistance performance evaluation on the buildings by applying fuzzy theory. This seismic resistance performance evaluation method considers the mutual relations among the type of force, the type of member, the type of story, and the states of deterioration of the buildings. The total seismic resistance performance index from this method was calculated by the intensity weight of each evaluation item, fuzzy measure, fuzzy integration. Moreover, the evaluation methodology was established in this study to identify the performance level of the Immediate Occupancy, Life Safe, Collapse Prevention by applying the fuzzy theory.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.260-270
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• 2013

This paper proposes a strategic portfolio model for managing performance of online games. The portfolio matrix is composed of two dimensions: financial performance and non-financial performance. Financial performance is measured by the conventional measure, average revenue per user (ARPU). In terms of non-financial performance, five non-financial key performance indicators (KPIs) that have been widely used in the online game industry are utilized: RU (Register User), VU (Visiting User), TS (Time Spent), ACU (Average Current User), MCU (Maximum Current User). Data envelopment analysis (DEA) is then employed to produce a single performance measure aggregating the five KPIs. DEA is a linear programming model for measuring the relative efficiency of decision making unit (DMUs) with multiple inputs and outputs. This study employs DEA as a tool for multiple criteria decision making (MCDM), in particular, the pure output model without inputs. Combining the two types of performance produces the online game portfolio matrix with four quadrants: Dark Horse, Stop Loss, Jack Pot, Luxury Goods. A case study of 39 online games provided by company 'N' is provided. The proposed portfolio model is expected to be fruitfully used for strategic decision making of online game companies.

• International Journal of Quality Innovation
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• v.8 no.1
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• pp.40-75
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• 2007

In the early industrial age which with high intensity of machine and labor, using financial measurement index was good enough to tie in company's mechanization and philosophy of management and been in efficiency. But being comply with "New Economic age," a new economic environment is full of knowledge and information, the enterprise competition had changed from tangible assets, plants to intangible innovation ability of knowledge. As recognizing the new tendency by enterprise, they value gradually the growth and influence from learning. Practice of organization learning not only needs firm structure and be in coordination with both hardware and software, but also needs an affect measurement model to offer enterprise to estimate learning performance. It's a good instrument of financial performance measure mold in the past years, But it's for measuring the past, couldn't formulate enterprise trend to future, hard to estimate investment for future, such as development of products, organization learning, knowledge management etc, as which intangible assets and knowledge ability just the key factors of being win around competition environment in the future. In 1992, Kaplan and Norton brought up Balance Scorecard (BSC) on Harvard Business Review, as an instrument helping enterprise to measure performance, which is being considered to be a most influence management instrument. It added non-financial index such as customer, internal process and learning growth besides traditional financial index, as offering enterprise an index to measure and manage intangible assets and intellectual property. As being aware of organization learning is hard to be ignored in the new economic age, this research is based on learning and growth of BSC, and citing one national material company try to let the most difficult measurement performance of organization learning, to be estimate through BSC, analyze of factor and individual case, to discuss the company how to make the related strategy and vision of organization learning to develop learning and growth of the structure of BSC, subject the matter of out put factors to be discussed, and measure the outcomes as a result of research. The research affect offers (1) the base implement procedure of carrying out BSC; (2) the reference of formulating measurement index while enterprise using BSC to estimate performance of organization learning; (3) the possibility bottleneck maybe forcing while carrying out BSC, to be an improvement or preventive for enterprise.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.426-429
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• 2004

To reconstruct the 3-D information of a irregular object, this paper proposes a new method applying the composition focus measure to time-series image. A focus measure function is carefully selected because a focus measure is apt to be affected by the working environment and the characteristics of an object. The proposed focus measure function combines the variance measure which is robust to noise and the Laplacian measure which, regardless of an object shape, has a good performance in calculating the focus measure. And the time-series image, which considers the object shape, is proposed in order to efficiently applying the interesting window. This method, first, divides the image frame by the window. Second, the composition focus measure function be applied to the windows, and the time-series image is constructed. Finally, the 3-D information of an object is reconstructed from the time-series images considering the object shape. The experimental results have shown that the proposed method is suitable algorithm to 3-D reconstruction of an irregular object.