• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.108-117
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• 1997

To prove the stability and the effectiveness of the robust non-linear friction control suggested and proved analytically in the previous paper, the describing function analysis is introduced. The instability of the Southward's nonlinear friction compensation for a digital position control and the improvement of phase margin of the robust nonlinear friction compensation are verified qualitatively through the describing function analysis. Those controls are applied to a single-axis digital servo driving experimental setup which has inherent stick-slip friction and experimental results confirm the results obtained in and the effectiveness of the robust nonlinear friction compensation for a digital position control.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.22-27
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• 1989

In this paper influences of disturbances and Modeling errors are qualitatively for the linear approximation model of turret servo system, and then LQG/LTR Control theory is applied to linear approximation model in order to design a controller which satisfies robustneas/stability for the modeling errors. Finally the performance and robustness of designed controller for the given plant are verified through the simulation.

• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.113-132
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• 1998

In this paper, we consider a minimum distance (M.D.) estimation based on kernels for U-statistics. We use Cramer-von Mises type distance function which measures the discrepancy between U-empirical distribution function(d.f.) and modeled d.f. of kernel. In the distance function, we allow various integrating measures, which can be finite, $\sigma$-finite or discrete. Then we derive the asymptotic normality and study the qualitative robustness of M. D. estimates.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.131-134
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• 1996

Application of machine learning to scheduling problems has focused on improving system performance based on opportunistic selection among multitudes of simple rules. This study proposes a new method of learning scheduling rules, which first establishes qualitatively meaningful criteria and quantitatively optimizes the use of them, a similar way as human scheduler accumulate their expertise. The weighting of these criteria is trained in response to the system states through simulation. To mimic human quantitative feelings, distributed fuzzy sets are used for assessing the system state. The proposed method was applied to job dispatching in a simulated FMS environment. The job-dispatching criteria used were the length of the processing time of a job and the situation of the next workstation. The results show that the proposed method can develop efficient and robust scheduling strategies, which can also provide understandable and usable know-hows to the human scheduler.

• Journal of the Korea Institute of Building Construction
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• v.13 no.2
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• pp.159-168
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• 2013

Construction projects have become increasingly complex in recent years, resulting in substantial safety hazards and frequent fall accidents. In an attempt to prevent fall accidents, various safety management systems have been developed. These systems have mainly been evaluated qualitatively and subjectively by practitioners or supervisors, and there are few tools that can be used to quantitatively evaluate the performance of safety management systems. We propose an expertise-based safety performance evaluation model (EXSPEM), which integrates a fuzzy approach-based analytic hierarchy process and a regression approach. The proposed model uses S-shaped curves to represent the degree of contribution by subjective expertise and is verified by a genetic algorithm. To illustrate its practical application, EXSPEM was applied to evaluate the safety performance of a newly developed real-time mobile detector monitoring system. It is expected that this model will be a helpful tool for systematically evaluating the application of a robust safety control and management system in a complex construction environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1191-1202
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• 1999

We propose an efficient vehicle detection and classification algorithm for an electronic toll collection using the feature which is robust to abrupt intensity change between consecutive frames. The local correlation coefficient between wavelet transformed input and reference images is used as such a feature, which takes advantage of textural similarity. The usefulness of the proposed feature is analyzed qualitatively by comparing the feature with the local variance of a difference image, and is verified by measuring the improvements in the separability of vehicle from shadowy or shadowless road for a real test image. Experimental results from field tests show that the proposed vehicle detection and classification algorithm performs well even under abrupt intensity change due to the characteristics of sensor and occurrence of shadow.

• Nuclear Engineering and Technology
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• v.47 no.3
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• pp.362-379
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• 2015

In this study, Nuclear Power Plant (NPP) construction schedule delay risk assessment methodology is developed and the construction delay risk is assessed for turnkey international NPP projects. Three levels of delay factors were selected through literature review and discussions with nuclear industry experts. A questionnaire survey was conducted on the basis of an analytic hierarchy process (AHP) and Relative Importance Index (RII) methods and the schedule delay risk is assessed qualitatively and quantitatively by severity and frequency of occurrence of delay factors. This study assigns four main delay factors to the first level: main contractor, utility, regulatory authority, and financial and country factor. The second and the third levels are designed with 12 sub-factors and 32 sub-sub-factors, respectively. This study finds the top five most important sub-sub-factors, which are as follows: policy changes, political instability and public intervention; uncompromising regulatory criteria and licensing documents conflicting with existing regulations; robust design document review procedures; redesign due to errors in design and design changes; and worldwide shortage of qualified and experienced nuclear specific equipment manufacturers. The proposed combined AHP-RII methodology is capable of assessing delay risk effectively and efficiently. Decision makers can apply risk informed decision making to avoid unexpected construction delays of NPPs.

• Steel and Composite Structures
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• v.2 no.1
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• pp.67-84
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• 2002

Traffic decks of steel or composite motorway bridges sometimes provide the opportunity of using the composite action between an existing steel deck and a reinforced concrete plate (RC plate) in the process of rehabilitation, i.e., to increase the load-carrying capacity of the deck for concentrated traffic loads. The steel decks may be orthotropic decks or also unstiffened steel plates, which during the rehabilitation are connected with the RC plate by shear studs, such developing an improved local load distribution by the joint behaviour of the two plate elements. Investigations carried out, both experimentally and numerically, were performed in order to quantitatively assess the combined static behaviour and to qualitatively verify the usability of the structure for dynamic loading. The paper reports on the testing, the numerical simulation as well as the comparison of the results. Conclusions drawn for practical design indicated that the static behaviour of these structures may be very efficient and can also be analysed numerically. Further, the results gave evidence of a highly robust behaviour under fatigue equivalent cyclic traffic loading.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1181-1196
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• 2011

Image fusion is the process of combining information from two or more source images of a scene into a single composite image with application to many fields, such as remote sensing, computer vision, robotics, medical imaging and defense. The most common wavelet-based fusion is discrete wavelet transform fusion in which the high frequency sub-bands and low frequency sub-bands are combined on activity measures of local windows such standard deviation and mean, respectively. However, discrete wavelet transform is not translation-invariant and it often yields block artifacts in a fused image. In this paper, we propose a robust image fusion based on the stationary wavelet transform to overcome the drawback of discrete wavelet transform. We use the activity measure of interquartile range as the robust estimator of variance in high frequency sub-bands and combine the low frequency sub-band based on the interquartile range information present in the high frequency sub-bands. We evaluate our proposed method quantitatively and qualitatively for image fusion, and compare it to some existing fusion methods. Experimental results indicate that the proposed method is more effective and can provide satisfactory fusion results.

• International Journal of Industrial Entomology and Biomaterials
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• v.5 no.2
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• pp.153-162
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• 2002

Earlier breeding experiments undertaken at Central Sericultural Research and Training Institute, Mysore, India since a decade had resulted in the development of many productive and qualitatively superior bivoltine hybrids. However, the hot climatic conditions of tropics prevailing particularly in summer are not conducive to rear these high yielding bivoltine hybrids. This has necessitated breeding of compatible bivoltine hybrids for year-round rearing. Accordingly, the Japanese hybrid, B2Ol ${\times}$ BCS12 which was found to be tolerant to high temperature was used as breeding resource material. Following hybridization and selection rearing of silkworms was taken up in SERICATRON (Environmental chamber with precise and automatic control facilities for uniform maintenance of temperature and humidity) at high temperature of $36{\times}1^{\circ}C$ and 85${\times}$5% RH in fifth instar and the control batches at $25{\times}1^{\circ}C$ and 65{\times}$5% RH. Directional selection was resorted to the batches reared at 36$\pm$1$^{\circ}C$ till F$_{5}$ keeping pupation rate as important selection criteria. From $F_{2}% onwards the experiment was modified in such a way as to conduct normal rearing every alternate generation to regain the lost vitality due to continuous exposure to high temperature and high humidity stress. At $F_{2}$ , Oval and dumb-bell cocoons were separated out and designated as CSR18 and CSR19, respectively. By utilizing these lines at $F_{12}$, the hybrid CSR18$\times$CSR19 was prepared and studied for the thermotolerance by subjecting to stress condition at high temperature of 36$\pm$1$^{\circ}C$ and 85$\pm$5% RH in fifth instar and the control batches at $25{\times}1^{\circ}C$ and 65${\times}$5% RH. The better performance of CSR18${\times}$CSR19 (survival > 88%) at $36{\times}1^{\circ}C$ clearly indicates the general superiority of CSR18${\times}$CSR19 with regard to high temperature tolerance over the productive hybrids and CSR18$\times$CSR19 can perform well in varied agro-climatic conditions of the tropics with optimum qualitative and quantitative characteristics.s.