• Journal of Korean Society on Water Environment
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• v.39 no.4
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• pp.288-301
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• 2023

This study aims to identify benthic macroinvertebrate fauna inhabiting at the mountain valley stream (Mt. Cheonggye) in Korea and the relationship between physical environmental factors and biological indices. Benthic macroinvertebrates were collected at five locations on August 24 and October 14, 2020, and were identified as 4 phyla, 7 classes, 16 orders, 42 families, and 72 species. Dominance ranged from 0.38 to 0.59, diversity 2.81 to 3.75, richness 3.25 to 4.63, evenness 0.65 to 0.84, and %EPT (Ephemeroptera-PlecopteraTrichoptera) richness value 42% to 73%, respectively. All sites were evaluated as a very good status by mostly biological indices based on tolerance of indicator organisms in Korea. As a result of principal component analysis, biological indices are classified into species-level indices and higher cartegory-level indices according to the taxonomic level of the indicator organism considered in each index. As a result of canonical correspondence analysis, it was confirmed that current velocity was a major factor that increased species richness and classified biological indices according to taxonomic category level. Water depth was a major factor related to the community indices, and the deeper the water depth, the lower the diversity and the evenness.

• Child Health Nursing Research
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• v.4 no.1
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• pp.128-149
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• 1998

Cigarette smoking has been identified as the single most important source of preventable morbidity and mortality. Smoking behavior varies each individual, so individuality & subjectivity of smoking behavior must be specially focused upon to understand smoking behavior. The purpose of this study was to find attitudes of university students in the prediction of smoking behavior. Q-Methodological method was used as a research design and data were collected during the period from Jan.1, 1997 to Feb. 28, 1998. As the research method, Q-statements were collected through in- depth interviews and a literature review. For the study 33 Q-statements were selected. There were 45 university students as subjects for the research. The 45 university students sorted the 33 statements using the principle of Forced Normal Distribution. The principle of Forced Normal Distribution, which has nine scales to measure the individual opinions, Pc Quanl program was used for analysis and Q-factors were analyzed by using principal component analysis. According to the results of this study, there were four categories of opinion about the smoking behavior in university students. The first type is seeking the habitual dependency. The second type is seeking the stress relief : The third type is seeking the active disapproval : The fourth type is seeking the self control. As a result, The meaning of the smoking behavior is affected by perceived subjective experience, so we need to understand each persons meaning of the smoking behavior and to develop appropriate nursing interventions based on the typology of smoking behavior. Finally, The result of the study will provide basic data for smoking prevention and cessation program.

• Culinary science and hospitality research
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• v.20 no.5
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• pp.34-42
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• 2014

The study explores the sensory properties of Backsulgi prepared with dry non-glutinous rice flour sweetened with various sweeteners(sugar, honey, oligosaccharide, trehalos, erythritol and accesulfame K). Sensory attributes of Backsulgi were evaluated by quantitative descriptive analysis(QDA), PCA and PLSR. The QDA results revealed that the sample sweetened with trehalose showed highest value in dryness, and samples with accesulfame K, honey and erythriol had relatively high levels in moisture and springiness. Principle component analysis (PCA) results showed 78.89 % of the total variation with PC1 (54.92%) and PC2 (23.98%), respectively. The samples with accesulfame K(AF) and honey, which showed high values in moisture level, springiness and sweet taste, showed similar attributes which led to a positive direction of PC1. The correlation between the sensory attributes and consumer acceptance showed that the most important factors for high consumer acceptance were moistness, springiness, sweet taste and sweet flavor. Overall, the samples with accesulfame K(AF) had the closest position in the PLSR results with highest overall consumer satisfaction.

• Journal of Physiology & Pathology in Korean Medicine
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• v.33 no.3
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• pp.163-168
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• 2019

In order to enhance the 8 principle pattern diagnosis rate comparing with diagnostic method by self-report questionnaire on cold/heat pattern in the clinical practice, a new diagnostic method using form-color-pulse-symptom (FCPS) system is proposed. FCPS system is composed of outputs of cold/heat pattern through the calculation process of contribution degree to the cold, heat pattern and qi, blood, yin, yang deficiency patterns, based on analysis of 16 mechanisms of disease calculated by diagnostic system of oriental medicine (DSOM) first. And second component is an output of differentiated 8 principle patterns in detail through binding and calculating process with digital informations of pulse, color, form, constitution obtained by computerized measurement system. Putting together above two processes consecutively, cold-heat complex or true/false cold/heat patterns and personalized characters of cold/heat patterns of each patient can be subdivided through a computation method of determining each pattern. In conclusion, 8 principle pattern identification can be performed more accurately using FCPS system than existent self report questionnaire method. These hypothetic proposal is needed to be proven by clinical trial for the future and then the accurate numbers used in each calculational function should be revised properly.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.982-987
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• 2015

The inspection machine in SMT (Surface Mount Technology) line detects the assembly defects such as missing, misalignment, loosing, or tombstone. We propose a new method to classify the defect types of chip components by processing the image of PCB. Two original images are obtained from horizontal lighting and vertical lighting. The image of the component is divided into two soldering regions and one packaging region. The features are extracted by appling the PCA (Principle Component Analysis) to each region. The MLP (Multilayer Perceptron) and SVM (Support Vector Machine) are then used to classify the defect types by learning. The experimental results are presented to show the usefulness of the proposed method.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.1
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• pp.28-43
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• 2001

Developed in these two series of paper is a complex dynamic model representing the motion of aircraft on the ground and a computer program for numerical simulation. The first part of paper presents the theoretical derivation of equations of motion of the landing gear system based on the physical principle. Developed model is 'structured' in the sense that the undercarriage system is regarded as an assembly of strut, tire, and wheel, where each component is modeled by a separate module. These modules are linked with two external modules-the aircraft and the runway characteristics-to carry out dynamic analysis and numerical simulation of the aircraft motion on the ground. Three sets of coordinate system associated with strut, wheel/tire and runway are defined, and external loads to each component and response characteristics are examined. Lagrangian formulation is used to derive the undercarriage equations of motion relative to the moving aircraft, and the resultant forces and moments from the undercarriage are transformed to aircraft body axes.

• Journal of Korean Society for Quality Management
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• v.20 no.2
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• pp.44-54
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• 1992

In conventional fault-tree analysis, the failure probabilities of components of a system are treated as exact values in estimating the failure probability of the top event. For the plant layout and systems of the products, however, it is often difficult to evaluate the failure probabilities of components from past occurences, because the environments of the systems change. Furthermore, it might be necessary to consider possible failure of components of the systems even if they have never failed before. In the paper, instead of the probability of failure, we propose the possibility of failure, viz, a fuzzy set defined in probability space. Thus, in this paper based on a fuzzy fault-tree model, the maximum possibility of system failure is determined from the possibility of failure of each component within the system according to the extension principle.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.12
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• pp.2949-2961
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• 1993

Dynamic cutting process can be represented by a closed-loop0 system consisted of machine tool structure and pure cutting process. On this paper, cutting system is modeled as a six degrees of freedom system using MARV(Modified Autoregressive Vector) model in face milling, and the modeled dynamic cutting process is used to predict dynamic cutting force component. Based on the double modulation principle, a dynamic cutting force model is developed. From the simulated relative displacements between tool and workpiece the dynamic force domponents can be calculated, and the dynamic force can be obtained by superposition of the static force and dynamic force components. The simulated dynamic cutting forces have a good agreement with the measured cutting force.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.49-55
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• 2010

Cast shadow caused by an illumination condition can produce troublesome effects for face recognition system using reflectance image. Consequently, we need to separate cast shadow area from feature area for improvement of recognition accuracy. A Bilateral filter smooths image while preserving edges, by means of a nonlinear combination of nearby pixel values. Processing such characteristics, this method is suited to our purpose in illumination estimation process based on Retinex. Therefore, in this paper, we propose a new illumination normalization method based on the Bilateral filter in face images. The proposed method produces a reflectance image that is preserved relatively exact cast shadow area, because coefficient of filter is designed to multiply proximity and discontinuity of pixels in input image. Performance of our method is measured by a recognition accuracy of principle component analysis(PCA) and evaluated to compare with other conventional illumination normalization methods.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.57-63
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• 2012

In this paper, a Bayesian classifier based on PCA (principle component analysis) is proposed to classify underwater transient signals using $16^{th}$ order LPC (linear predictive coding) coefficients as feature vector. The proposed classifier is composed of two steps. The mechanical signals were separated from biological signals in the first step, and then each type of the mechanical signal was recognized in the second step. Three biological transient signals and two mechanical signals were used to conduct experiments. The classification ratios for the feature vectors of biological signals and mechanical signals were 94.75% and 97.23%, respectively, when all 16 order LPC vector were used. In order to determine the effect of underwater noise on the classification performance, underwater ambient noise was added to the test signals and the classification ratio according to SNR (signal-to-noise ratio) was compared by changing dimension of feature vector using PCA. The classification ratios of the biological and mechanical signals under ocean ambient noise at 10dB SNR, were 0.51% and 100% respectively. However, the ratios were changed to 53.07% and 83.14% when the dimension of feature vector was converted to three by applying PCA. For correct, classification, it is required SNR over 10 dB for three dimension feature vector and over 30dB SNR for seven dimension feature vector under ocean ambient noise environment.