• Korean Journal of Environmental Biology
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• v.32 no.2
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• pp.95-101
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• 2014

In order to investigate effects of elevated $CO_2$ concentration and temperature on the ecological niche of Quercus serrata in Korea. We divided experimental condition in the greenhouse that are control (ambient condition) and treatment with elevated $CO_2$ (approximately 1.6 above than control) and increased air temperature (approximately $2.2^{\circ}C$ above than control). We measured twenty kind characters of seedlings and calculated the ecological niche breadth. As a result, the ecological niche breadth, treatment was widened in the light gradient than the control, was narrowed in the moisture and nutrient gradient. This is may be predicted when the global warming progress, Q. serrata is increases resistance to light environment, and decrease resistance to moisture and nutrient environment. According to the principal component analysis (PCA), control and treatment were arranged based on factor 1 and 2 in each environment gradients. Ecological response is involved variety characters. Among them, indicating that Characters of production is involved in many a parts.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5280-5287
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• 2014

This paper proposes a method in which classes are grouped as a hierarchical tree structure for the effective classification of the Raman spectra. As experimental data, the Raman spectra of 28 chemical compounds were obtained, and pre-treated with noise removal and normalization. The spectra that induced a classification error were grouped into the same class and the hierarchical structure class was composed. Each high and low class was classified using a PCA-MAP method. According to the experimental results, the classification of 100% was achieved with 2.7 features on average when the proposed method was applied. Considering that the same classification rates were achieved with 6 features using the conventional method, the proposed method was found to be much better than the conventional one in terms of the total computational complexity and practical application.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.6
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• pp.579-589
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• 2004

The radar signals are generally very sensitive to relative orientations between radar and target. Thus, the performance of a target recognition system significantly deteriorates as the region of aspect angles becomes broader. To address this difficulty, in this paper, we propose a method based on the multi-aspect information in order to improve the classification capability ever for a wide angular region. First, range profiles are used to extract feature vectors based on the central moments and principal component analysis(PCA). Then, a classifier with the use of multi-aspect information is applied to them, yielding an additional improvement of target recognition capability. There are two different strategies among the classifiers that can fuse the information from multi-aspect radar signals: independent methodology and dependent methodology. In this study, the performances of the two strategies are compared within the frame work of target recognition. The radar cross section(RCS) data of six aircraft models measured at compact range of Pohang University of Science and Technology are used to demonstrate and compare the performances of the two strategies.

• Food Science of Animal Resources
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• v.36 no.2
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• pp.223-229
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• 2016

The carcass size performances and the meat quality of Gannan and Sibu yak were determined using M. supraspinatus (SU), M. longissimus thoracis (LT) and M.quadriceps femoris (QF). It is found that Sibu yak had significantly higher carcass weight (CW) than Gannan yak with difference of nearly 40 kg, as well as significantly higher eye muscle area (EMA), carcass thorax depth (CTD), round perimeter (RP), etc. The carcass performances of steer yak were significantly higher than heifer yak except meat thickness at round (MTR) (p<0.05). The results show that both yak breed and gender had significant effects on carcass performances. It could be seen that the variation of carcass size performances from breeds is as large as from gender (50.22% and 46.25% of total variation, respectively) through principal component analysis (PCA). Sibu yak had significantly higher L*, b*, WBSF, cooking loss and Fat content, while Gannan yak had significantly higher a*, press loss, protein content and moisture (p<0.05). Yak gender and muscle had insignificant effects on meat colour and water holding capacity (p>0.05). The variation of meat quality of yak from breed is up to 59.46% of total variation according to PCA. It is shown that the difference between breeds, for Gannan yak and Sibu yak, plays an important role in carcass size performance and meat quality.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.19-26
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• 2010

This paper proposes a classifier based on rectangular feature to detect face in real time. The goal is to realize a strong detection algorithm which satisfies both efficiency in calculation and detection performance. The proposed algorithm consists of the following three stages: Feature creation, classifier study and real time facial domain detection. Feature creation organizes a feature set with the proposed five rectangular features and calculates the feature values efficiently by using SAT (Summed-Area Tables). Classifier learning creates classifiers hierarchically by using the AdaBoost algorithm. In addition, it gets excellent detection performance by applying important face patterns repeatedly at the next level. Real time facial domain detection finds facial domains rapidly and efficiently through the classifier based on the rectangular feature that was created. Also, the recognition rate was improved by using the domain which detected a face domain as the input image and by using PCA and KNN algorithms and a Class to Class rather than the existing Point to Point technique.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.81-87
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• 2004

Semiconductor thick film gas sensors based on tin oxide are fabricated and their gas response characteristics are examined for four simulant gases of chemical warfare agent (CWA)s. The sensing materials are prepared in three different sets. 1) The Pt or Pd $(1,\;2,\;3\;wt.\%)$ as catalyst is impregnated in the base material of $SnO_2$ by impregnation method.2) $Al_2O_3\;(0,\;4,\;12,\;20\;wt.\%),\;In_2O_3\;(1,\;2,\;3\;wt.\%),\;WO_3\;(1,\;2,\;3\;wt.\%),\;TiO_2\;(3,\;5,\;10\;wt.\%)$ or $SiO_2\;(3,\;5,\;10\;wt.\%)$ is added to $SnO_2$ by physical ball milling process. 3) ZnO $(1,\;2,\;3,\;4,\;5\;wt.\%)$ or $ZrO_2\;(1,\;3,\;5\;wt.\%)$ is added to $SnO_2$ by co-precipitation method. Surface morphology, particle size, and specific surface area of fabricated sensing films are performed by the SEM, XRD and BET respectively. Response characteristics are examined for simulant gases with temperature in the range 200 to $400^{\circ}C$, with different gas concentrations. These sensors have high sensitivities more than $50\%$ at 500ppb concentration for test gases and also have shown good repetition tests. Four sensing materials are selected with good sensitivity and stability and are fabricated as a sensor array A sensor array Identities among the four simulant gases through the principal component analysis (PCA). High sensitivity is acquired by using the semiconductor thick film gas sensors and four CWA gases are classified by using a sensor array through PCA.

• Journal of IKEEE
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• v.19 no.4
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• pp.541-547
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• 2015

In current semiconductor manufacturing, as the feature size of integrated circuit (IC) devices continuously shrinks, detecting endpoint in plasma etching process is more difficult than before. For endpoint detection, various kinds of sensors are installed in semiconductor manufacturing equipments, and sensor data are gathered with predefined sampling rate. Generally, detecting endpoint is performed using OES data of by-product. In this study, OES data of both by-product and etchant gas are used to improve reliability of endpoint detection. For the OES data pre-processing, a combination of Signal to Noise Ratio (SNR) and Principal Component Analysis (PCA),are used. Polynomial Regression and Expanded Hidden Markov model (eHMM) technique are applied to pre-processed OES data to detect endpoint.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.936-941
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• 2006

To apply object recognition techniques to real environment, illumination compensation method should be developed. As effective illumination compensation model, we focused our attention on Retinex model and illumination-Reflectance model, implemented them, and experimented on their performance. We implemented Retinex model with Single Scale Retinex, Multi-Scale Retinex, and Retinex Neural Network and Multi-Scale Retinex Neural Network, neural network model of Retinex model. Also, we implemented illumination-Reflectance model with reflectance image calculation by calculating an illumination image by low frequency filtering in frequency domain of Discrete Cosine Transform and Wavelet Transform, and Gaussian blurring. We compare their illumination compensation performance to facial images under nine illumination directions. We also compare their performance after post processing using Principal Component Analysis(PCA). As a result, illumination Reflectance model showed better performance and their overall performance was improved when illumination compensated images were post processed by PCA.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.227-232
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• 2010

This paper proposes the real time lip reading method in the embedded environment. The embedded environment has the limited sources to use compared to existing PC environment, so it is hard to drive the lip reading system with existing PC environment in the embedded environment in real time. To solve the problem, this paper suggests detection methods of lip region, feature extraction of lips, and awareness methods of phonetic words suitable to the embedded environment. First, it detects the face region by using face color information to find out the accurate lip region and then detects the exact lip region by finding the position of both eyes from the detected face region and using the geometric relations. To detect strong features of lighting variables by the changing surroundings, histogram matching, lip folding, and RASTA filter were applied, and the properties extracted by using the principal component analysis(PCA) were used for recognition. The result of the test has shown the processing speed between 1.15 and 2.35 sec. according to vocalizations in the embedded environment of CPU 806Mhz, RAM 128MB specifications and obtained 77% of recognition as 139 among 180 words were recognized.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.3
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• pp.371-374
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• 2011

The objectives of the present study evaluated aquatic animals on the water in a rice field. Field investigation was carried out in conventional tillage without rice straw or green manure crop treatment (CTFS, check plot), no-tillage without cover crops (NTNT), no-tillage amended with rape (NTRA), no-tillage amended with rye (NTRY), no-tillage amended with hairyvetch (NTHV), and no-tillage amended with Chinese milk vetch (NTCM). Total dense population of aquatic animals in HTHV was significantly higher than the other plots (p<0.05) on May 30. Dense populations of Daphniidae and Culicidae on June 20 were lowest in CTFS compared to no-tillage plots (p<0.05). Furthermore, in principal component analysis (PCA), PC1 explained 44.9% of variance, whereas PC2 explained 26%, for a cumulative total of 70.9% and the PC1 of the PCA separated the samples from NT treatments and CFS (p<0.05).