• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.812-816
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• 1987

A quadratic regulator problem for a class of nonlinear system, in which a small parameter multiplies the control cost, is considered. In the analysis of the problem, we utilize the method of multiple time-scale decomposition which has been devised for analyzing complex linear cheap control problems. In so doing, we extend the class of nonlinear systems, considerably, for which the minimum cost becomes zero as the small parameter goes to zero.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.375-378
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• 2011

Measurement of network traffic have shown that the self-similarity is a ubiquitous phenomenon spanning across diverse network environments. In previous work, we have explored the feasibility of exploiting the long-range correlation structure in a self-similar traffic for the congestion control. We have advanced the framework of the multiple time scale congestion control and showed its effectiveness at enhancing performance for the rate-based feedback control.

• The Journal of Internal Korean Medicine
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• v.38 no.2
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• pp.246-251
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• 2017

In this study, a 54-year-old female woman diagnosed as Multiple System Atrophy (MSA) presented diplopia with other symptoms - gait disturbance, ataxia, sleep apnea, dysuria. She had been cared with Korean medical treatment - Herbal medicine, acupuncture, bee venom acupuncture, electroacupuncture, cupping, moxa. Notable improvement was observed in diplopia expressing time and Unified Multiple System Atrophy Rating Scale (UMSARS). For MSA patient with no typical treatment indispensable, Korean medical treatment may be effective.

• Journal of Korean Academy of Nursing
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• v.34 no.6
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• pp.964-973
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• 2004

Purpose: This study was aimed to identify the major factors affecting performance in health promoting behaviors in women workers at small-scale industries. Method: This study was based on the Pender's Health Promotion Model. The subjects for this study were 251 women workers at 23 small-scale industries in Busan city. The data for this study was collected from July 15th to August 15th 2003 by structured questionaries, and were analyzed with ANOVA, t-test, Pearson' correlation coefficient, and multiple Regression in the SPSS/WIN 10.0. Result: The mean performance of the health promoting behavior was 2.56. The factors related to the performance of the health promoting behaviors were social support, marital status, status of owning a house, perceived barriers to action, working time, and self-efficacy, and they explained 58.4% of the variance of the health promoting behaviors. Conclusion: The mean performance of the health promoting behavior seemed to be low, and the most important variable related to health promoting behaviorsof women working at a small-scale industry was social support. Therefore, intervention programs to increase the social support for women worker need to be developed.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1083-1094
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• 2020

Recognizing plant species based on leaf images is challenging because of the large inter-class variation and inter-class similarities among different plant species. The effective extraction of leaf descriptors constitutes the most important problem in plant leaf recognition. In this paper, a multi-scale angular description method is proposed for fast and accurate leaf recognition and retrieval tasks. The proposed method uses a novel scale-generation rule to develop an angular description of leaf contours. It is parameter-free and can capture leaf features from coarse to fine at multiple scales. A fast Fourier transform is used to make the descriptor compact and is effective in matching samples. Both support vector machine and k-nearest neighbors are used to classify leaves. Leaf recognition and retrieval experiments were conducted on three challenging datasets, namely Swedish leaf, Flavia leaf, and ImageCLEF2012 leaf. The results are evaluated with the widely used standard metrics and compared with several state-of-the-art methods. The results and comparisons show that the proposed method not only requires a low computational time, but also achieves good recognition and retrieval accuracies on challenging datasets.

• Research in Community and Public Health Nursing
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• v.13 no.2
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• pp.376-386
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• 2002

Objectives: The purpose of this study was to investigate factors influencing the smoking behavior of adolescents, in order to provide basic data to develop a future nursing intervention program for smoking prevention. Methods: The study subjects were 162 adolescents attending high schools, who were living in K city. The instruments included the Self Esteem Scale translated by Jeon (1974), beliefs about the social rule scale developed by the Committee for Adolescence Guidance (1988), differential peer association developed by Krohn et. al. (1982), perceived behavioral control scale developed by Hanson (1997), intention of smoking scale developed by Newman et. al.(1982), and self-efficacy scale developed by Sherer et. al. (1982). The data were analyzed using descriptive statistics, Pearson correlation coefficient, and stepwise multiple regression. Results: 1. The smoking behaviors of the subjects were significantly correlated with beliefs about social rule, perceived behavioral control. differential peer association, intention of smoking, self efficacy, grade, father's level of education, monthly pocket money, time of onset for smoking, degree of alcoholic intake, and drug abuse. 2. The multiple regression analysis revealed the most powerful predictor for smoking behavior was time of onset for smoking. A combination of beliefs about social rule, perceived behavioral control, grade, differential peer association, and intention of smoking accounted for 54.0% of the variance for smoking behavior in adolescents. Conclusion: It is recommended that these influencing factors for smoking behavior be considered when developing future nursing intervention programs for the antismoking behaviors of adolescents.

• International Journal of Automotive Technology
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• v.6 no.4
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• pp.367-374
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• 2005

This paper proposes a sound quality index to evaluate the vehicle interior noise. The index was developed using a correlation analysis of an objective measurement and a subjective evaluation data. First, the objective set of measurements was obtained at two specified driving conditions. One is from a wide-open test condition and the other is from a constant-speed test condition. At the same time, subjective evaluation was carried out using a score of ten scale where 17 test engineers participated in the experiment. The correlation analysis between the psycho-acoustic parameters derived from the objective measurement and the subjective evaluation was performed. The most critical factors at both test conditions were determined, and the corresponding equations for the sound quality were obtained from the multiple factor regression method. Finally, a comparative work between previous index and present index was performed to validate the effectiveness of the proposed index.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.767-779
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• 2017

Automated mission planning for unmanned aerial vehicles (UAVs) is difficult because of the propagation of several sources of error into the solution, as for any large scale autonomous system. To ensure reliable system performance, we quantify all sources of error and their propagation through a mission planner for operation of UAVs in an obstacle rich environment we developed in prior work. In this sequel to that work, we show that the mission planner developed before can be made robust to errors arising from the mapping, sensing, actuation, and environmental disturbances through creating systematic buffers around obstacles using the calculations of uncertainty propagation. This robustness makes the mission planner truly autonomous and scalable to many UAVs without human intervention. We illustrate with simulation results for trajectory generation of multiple UAVs in a surveillance problem in an urban environment while optimizing for either maximal flight time or minimal fuel consumption. Our solution methods are suitable for any well-mapped region, and the final collision free paths are obtained through offline sub-optimal solution of an mTSP (multiple traveling salesman problem).

• Smart Structures and Systems
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• v.26 no.2
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• pp.185-193
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• 2020

Nonlinear vibration of sandwich plate with functionally graded material (FGM) core and carbon nano tubes reinforced (CNTs) nano-composite layers by considering temperature-dependent material properties are studied in this paper. Base on Classical plate theory (CPT), the governing partial differential equations of motion for sandwich plate are derived using Hamilton principle. The Galerkin procedure and multiple scales perturbation method are used to find relation between nonlinear frequency and amplitude of vibration response. The dynamic responses of the sandwich plate are also investigated in both time and frequency domains. Then, the effects of nonlinearity, excitation, power law index of FG core, volume fraction of carbon nanotube, the function of material variations of FG core, temperature changes, scale transformation parameter and damping factor on the frequency responses are investigated.

• Journal of Power Electronics
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• v.8 no.4
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• pp.317-324
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• 2008

This paper proposes a Multiband Shunt Hybrid Active Filter (SHAF) with sensorless control. A plant is modeled in the discrete- time domain and a controller is designed using the Pole shifting law in the polynomial domain. This control approach is very useful for filtering the load harmonics with reduced sensor counts where a low cost solution like SHAF is required. Multiple Synchronous Reference Frames (MSRF) and low pass filters are used to measure the $5^{th}$ and $7^{th}$ harmonic components separately from the load and filter currents. Individual current controllers are designed for the $5^{th}$ and $7^{th}$ harmonic currents. Control is realized in the stationary, three-phase (abc) reference frame. Performance of the controller is validated through simulation, using realistic plant and controller models, as well as experimentally on a full-scale distribution system.