• 디지털산업정보학회논문지
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• 제11권3호
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• pp.99-112
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• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

• 열처리공학회지
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• 제14권3호
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• pp.151-154
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• 2001

$TiO_2$ thin film has wide application because of its high capacitanca, reflection, and good transmissivity in visible range. $TiO_2$ thin film can be made by thermal deposition method, reactive evaporation method, activated reactive evaporation(ARE) method. In the case of thermal deposition, the oxygen deficiency can occur because the melting point of Ti is very high. While in the case of reactive evaporation, high density $TiO_2$ can not be made, because reactive gas($O_2$) and evaporated material(Ti) are not fully combined, activated reactive evaporation, $TiO_2$ is easily deposited at lower gas pressure compared with reactive evaporation because the ionized reactive gas is made by plasma. Therefore, activated reactive evaporation is very useful to deposit the material having the high melting point. In this work, we formed $TiO_2$ thin film by activated reactive evaporation method. The surface of $TiO_2$ thin film was analyzed by X-ray photoelectron spectroscopy. The surface morphology which was analyzed by atomic force microscopy(AFM) shows that feature of the film surface is uniform. The dielectric capacitance, withstanding voltage were $600{\mu}F/cm^2$, 0.4V respectively. In further work, we can increase the withstanding voltage by improving the deposition parameter of substrates.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.411-420
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• 1999

In geology, lineament features have been used to identify geological events, and many of scientists have been developed the algorithm that can be applied with the computer to recognize the lineaments. We choose several edge detection filter, line detection filters and Hough transform to detect an edge, line, and to vectorize the extracted lineament features, respectively. firstly the edge detection filter using a first-order derivative is applied to the original image In this step, rough lineament image is created Secondly, line detection filter is used to refine the previous image for further processing, where the wrong detected lines are, to some extents, excluded by using the variance of the pixel values that is composed of each line Thirdly, the thinning process is carried out to control the thickness of the line. At last, we use the Hough transform to convert the raster image to the vector one. A Landsat image is selected to extract lineament features. The result shows the lineament well regardless of directions. However, the degree of extraction of linear feature depends on the values of parameters and patterns of filters, therefore the development of new filter and the reduction of the number of parameter are required for the further study.

• 한국멀티미디어학회논문지
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• 제13권12호
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• pp.1786-1797
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• 2010

Automatic understanding of contents in document image is a very hard problem due to involvement with mathematically challenging problems originated mainly from the over-determined system induced by document segmentation process. In both academic and industrial areas, there have been incessant and various efforts to improve core parts of content retrieval technologies by the means of separating out segmentation related issues using semi-structured document, e.g., invoice,. In this paper we proposed classification models for text lines on invoice document in which text lines were clustered into the five categories in accordance with their contents: purchase order header, invoice header, summary header, surcharge header, purchase items. Our investigation was concentrated on the performance of machine learning based models in aspect of linear-discriminant-analysis (LDA) and non-LDA (logic based). In the group of LDA, na$\"{\i}$ve baysian, k-nearest neighbor, and SVM were used, in the group of non LDA, decision tree, random forest, and boost were used. We described the details of feature vector construction and the selection processes of the model and the parameter including training and validation. We also presented the experimental results of comparison on training/classification error levels for the models employed.

• Journal of Communications and Networks
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• 제18권5호
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• pp.725-734
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• 2016

For multi-mode radar signals in complex electromagnetic environment, different modes of one emitter tend to be deinterleaved into several emitters, called as "extension", when processing received signals by use of existing sorting methods. The "extension" problem inevitably deteriorates the sorting performance of multi-mode radar signals. In this paper, a novel method based on spatial data mining is presented to address above challenge. Based on theories of data field, we describe the distribution information of feature parameters using potential field, and makes partition clustering of parameter samples according to revealed distribution features. Additionally, an evaluation criterion based on cloud model membership is established to measure the relevance between different cluster-classes, which provides important spatial knowledge for the solution of the "extension" problem. It is shown through numerical simulations that the proposed method is effective on solving the "extension" problem in multi-mode radar signal sorting, and can achieve higher correct sorting rate.

• 전기학회논문지
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• 제64권6호
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• pp.864-871
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• 2015

Recently, one of the main research on the power distribution system is the microgrid. The microgrid is a combination of power sources and loads, which is controllable and has separable connection. The main objective of microgrid is the deployment of the renewable clean energy and the enhancement of load-side reliability. The modern power sources and loads have DC I/O interfaces, which is the major advantage of DC microgrid compared to the conventional AC grid. The components in the microgrid have diverse features, so there is need of proper coordination control. For achieving economic feature, the active power of renewable energy resources is regarded as major control parameter and the whole operation modes of DC microgrid are defined, and the proper operations of each component are described. From the inherent characteristics of DC, there are two control variables: voltage and active power. Through analysis of operation modes, it is possible to determine exact control objectives and optimized voltage & power control strategy in each mode. Because of consideration of whole operation modes, regardless of the number and capacity of components, this coordination control method can be used without modification. This paper defines operation mode of DC microgrid with several DC sources and suggests economic and efficient coordinated control methods. Simulation with PSCAD proves effectiveness.

• Structural Engineering and Mechanics
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• 제52권6호
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• pp.1193-1208
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• 2014

A simulation of failures on responsible elements is only one form of the extreme structural behavior analysis. By understanding the dynamic behavior in incidental situations, it is possible to make a special structural design from the point of the largest axial force, stress and redundancy. The numerical realization of one such simulation analysis was performed using FEM in this paper. The boundary parameters of transient analysis, such as overall structural damping coefficient, load accelerations, time of load fall and internal forces in the responsible structural elements, were determined on the basis of the dynamic experimental parameters. The structure eigenfrequencies were determined in modal analysis. In the study, the basic incidental models were set. The models were identified by many years of monitoring incidental situations and the most frequent human errors in work with heavy structures. The combined load models of structure are defined in the paper since the incidents simply arise as consequences of cumulative errors and failures. A feature of a combined model is that the single incident causes the next incident (consecutive timing) as well as that other simple dynamic actions are simultaneous. The structure was observed in three typical load positions taken from the crane passport (range-load). The obtained dynamic responses indicate the degree of structural sensitivity depending on the character of incident. The dynamic coefficient KD was adopted as a parameter for the evaluation of structural sensitivity.

• Smart Structures and Systems
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• 제11권1호
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• pp.19-34
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• 2013

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

• Structural Engineering and Mechanics
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• 제65권6호
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• pp.699-706
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• 2018

In the present contribution, fracture resistance of U-notched GPPS members under mixed mode I/III loading conditions is assessed by using the Averaged Strain Energy Density (ASED) criterion. This criterion has been founded based on the ASED parameter averaged over a well-defined control volume embracing the notch edge. The validation of the theoretical criterion predictions is evaluated through comparing with the results of a series of mixed mode I/III fracture tests conducted on rectangular-shaped GPPS specimens weakened by a single edge U-notch. A recently developed apparatus for mixed mode I/III fracture experiments is employed for measuring the fracture loads of the specimens. The test samples are fabricated with different notch tip radii with the aim of evaluating the influence of this major feature of the U-notched components on the mixed mode I/III fracture behavior. It is shown that the onset of brittle fracture in U-notched GPPS specimens under various combinations of tension and out-of-plane shear can well be predicted by means of the ASED criterion.

• 대한의용생체공학회:의공학회지
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• 제28권5호
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• pp.665-675
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• 2007

The morphological change of ECG is the important diagnostic parameter to finding the malfunction of a heart. Generally ST segment deviation is concerned with myocardial abnormality. The aim of this study is to detect the change of ST in shape using a polynomial approximation method and the reference ST type. The developed algorithm consists of feature point detection, ST level detection and ST shape classification. The detection of QRS complex is accomplished using it's the morphological characteristics such as the steep slope and high amplitude. The developed algorithm detects the ST level change, and then classifies the ST shape type using the polynomial approximation. The algorithm finds the least squares curve for the data between S wave and T wave in ECG. This curve is used for the classification of the ST shapes. ST type is classified by comparing the slopes of the specified points between the reference ST set and the least square curve. Through the result from the developed algorithm, we can know when the ST level change occurs and what the ST shape type is.