• Korean Journal of Environment and Ecology
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• v.20 no.4
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• pp.415-424
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• 2006

This study was carried out to analyze the characteristics of forest watershed factors by using the quantification theory(I) for evaluation and prediction of the failure hazard area. Present $sediment(m^3/yr/ha)$ of erosion control dams were investigated in 95 sites of erosion control dam constructed during 1986 to 1999 in Gyeongnam province. The results obtained from this study were summarized as follows; General condition of class I(Very hazard area) were as follow; Igneous rock in parent rock, coniferous in forest type, below 20year in stand age, below 30cm in soil depth, SCL in soil texture, $31{\sim}40%$ in gravel contents, $S{\sim}E$ in aspect, $2,501{\sim}3,600m$ in length of main stream, $26{\sim}30$ in number of total streams, $6,601{\sim}10,000m$ in length of total streams, over 3 in stream order, over 16 in number of first streams order and over $31^{\circ}$ of slope gradient. General condition of class IIl(hazard area) were as follow; Metamorphic rock in parent rock, hardwood in forest type, over $21{\sim}24year$ in stand age, $31{\sim}40cm$ in soil depth, SiCL or SCL in soil texture, $11{\sim}20%$ in gravel contents, $S{\sim}W$ in aspect, $1,501{\sim}2,600m$ in length of main stream, $6{\sim}10$ in number of total streams, $3,501{\sim}5,500m$ in length of total streams, 2 in stream order, $6{\sim}10$ in number of first streams order and over $31^{\circ}$ of slope gradient. General condition of class III(Un hazard area) were as follow; Sedimentary rock in parent rock, mixed in forest type, over 25year in stand age, $41{\sim}50cm$ in soil depth, SiCL in soil texture, below 10% in gravel contents, $N{\sim}W$ in aspect, below 500m in length of main stream, below 5 in number of total streams, below 1,000m in length of total treams, below 1 in stream order, below 2 in number of first streams order and below $25^{\circ}$ of slope gradient. The prediction method of suitable for failure hazard area divided into class I, II, and III for the convenience of use. The score of class I evaluated as a very hazard area was over 4.8052. A score of class II was 4.8051 to 2.5602, it was evaluated as a hazard area, and class III was below 2.5601, it was evaluated as a un hazard area.

• Journal of the Korean Society of Radiology
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• v.10 no.6
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• pp.443-450
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• 2016

In this study, we are using a computer tomography image of the abdomen, as an experimental linear research for the image of the fatty liver patients texture features analysis and computer-aided diagnosis system of implementation using the ROC curve analysis, from the computer tomography image. We tried to provide an objective and reliable diagnostic information of fatty liver to the doctor. Experiments are usually a fatty liver, via the wavelet transform of the abdominal computed tomography images are configured with the experimental image section, shows the results of statistical analysis on six parameters indicating a feature value of the texture. As a result, the entropy, average luminance, strain rate is shown a relatively high recognition rate of 90% or more, the control also, flatness, uniformity showed relatively low recognition rate of about 70%. ROC curve analysis of six parameters are all shown to 0.900 (p = 0.0001) or more, showed meaningful results in the recognition of the disease. Also, to determine the cut-off value for the prediction of disease six parameters. These results are applicable from future abdominal computed tomography images as a preliminary diagnostic article of diseases automatic detection and eventual diagnosis.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.11-21
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• 2008

In conventional video coding, the complexity of encoder is much higher than that of decoder. However, as more needs arises for extremely simple encoder in environments having constrained energy such as sensor network, much investigation has been carried out for eliminating motion prediction/compensation claiming most complexity and energy in encoder. The Wyner-Ziv coding, one of the representative schemes for the problem, reconstructs video at decoder by correcting noise on side information using channel coding technique such as turbo code. Since the encoder generates only parity bits without performing any type of processes extracting correlation information between frames, it has an extremely simple structure. However, turbo decoding errors occur in noisy side information. When there are high-motion or occlusion between frames, more turbo decoding errors appear in reconstructed frame and look like Salt & Pepper noise. This severely deteriorates subjective video quality even though such noise rarely occurs. In this paper, we propose a computationally extremely light encoder based on symbol-level Wyner-Ziv coding technique and a new corresponding decoder which, based on a decision whether a pixel has error or not, applies median filter selectively in order to minimize loss of texture detail from filtering. The proposed method claims extremely low encoder complexity and shows improvements both in subjective quality and PSNR. Our experiments have verified average PSNR gain of up to 0.8dB.

• Korean Journal of Food Science and Technology
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• v.24 no.2
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• pp.117-121
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• 1992

The changes in sensory and mechanical texture of chewing gum during storage at various relative humidity were studied to define the quality index for the prediction of shelf-life. The initial moisture content of chewing gum was 2.57% (dry basis). The BET monolayer value at $a_{w}$ 0.19 was calculated to be 1.57% (dry basis). The sensory scores of chewing gum were closely correlated with moisture content and instrumental texture parameters with 0.1% significant level. Therefore the quality of stored chewing gum was directly related with moisture content above BET monolayer. The products became organoleptically acceptable in the range of moisture content $2.17{\sim}3.16%(dry basis)$. This range of moisture content ie equivalent to the ranges of instrumental parameter, fracture force$0.8{\sim}1.8{\times}10^{7}$, fracture modulus $1.1{\sim}2.4{\times}10^{8}$, puncture force $0.5{\sim}1.1{\times}10^{7}[dyne/cm^{2}]$ and brittleness $0.7{\sim}1.4{\times}10^{8}[dyne/cm^{3}]$, respectively.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.188-199
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• 2008

In conventional video coding, encoder complexity is much higher than that of decoder. However, investigations for lightweight encoder to eliminate motion prediction/compensation claiming most complexity in encoder have recently become an important issue. The Wyner-Ziv coding is one of the representative schemes for the problem and, in this scheme, since encoder generates only parity bits of a current frame without performing any type of processes extracting correlation information between frames, it has an extremely simple structure compared to conventional coding techniques. However, in Wyner-Ziv coding, channel decoding errors occur when noisy side information is used in channel decoding process. These channel decoding errors appear more frequently, especially, when there is not enough correlation between frames to generate accurate side information and, as a result, those errors look like Salt & Pepper type noise in the reconstructed frame. Since this noise severely deteriorates subjective video quality even though such noise rarely occurs, previously we proposed a computationally extremely light encoding method based on selective median filter that corrects such noise using spatial correlation of a frame. However, in the previous method, there is a problem that loss of texture from filtering may exceed gain from error correction by the filter for video sequences having complex torture. Therefore, in this paper, we propose an improved lightweight encoding method that minimizes loss of texture detail from filtering by allowing information of texture and that of noise in side information to be utilized by the selective median filter. Our experiments have verified average PSNR gain of up to 0.84dB compared to the previous method.

• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.360-372
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• 2007

We propose a fast inter-layer mode decision method by utilizing coding information of base layer upward its enhancement layer inscalable video coding (SVC), also called MPEG-4 part 10 Advanced Video Coding Amendment 3 or H.264 Scalable Extension (SE) which is being standardized. In this paper, when the motion vectors from the base layer have zero motion (0, 0) in inter-layer motion prediction or the Integer Transform coefficients of the residual between current MB and the motion compensated MB by the predicted motion vectors from the base layer are all zero, the block mode of the corresponding block to be encoded at the enhancement layer is determined to be the $16{\times}16$ mode. In addition, if the predicted mode of the MB to be encoded at the enhancement layer is not equal to the $16{\times}16$ mode, then the rate-distortion optimization is only performed on the reduced candidated modes which are same or smaller partitioned modes. Our proposed method exhibits the complexity reduction in encoding time up to 72%. Nevertheless, it shows negligible PSNR degradation and bit rate increase up to 0.25dB and 1.73%, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.1
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• pp.116-123
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• 2003

Forages are the most important feed resource for ruminants worldwide, whether fed as pastures, forage crops or conserved hay, silage or haylage. There is large variability in the quality of forages so measurement and prediction of feeding value and nutritive value are essential for high levels of production. Within a commercial animal production system, methods of prediction must be inexpensive and rapid. At least 50% of the variation in feeding value of forages is due to variation in voluntary feed intake. Identification of the factors that constrain voluntary feed intake allows these differences to be managed and exploited in forage selection. Constraints to intake have been predicted using combinations of metabolic and physical factors within the animal while simple measurements such as the energy required to shear the plant material are related to constraints to intake with some plant material. Animals respond to both pre- and post-ingestive feedback signals from forages. Pre-ingestive signals may play a role in intake with signals including taste, odour and texture together with learned aversions to nutrients or toxins (post-ingestive feedback signals). The challenge to forage evaluation is identification of the factors which are most important contributors to these feedback signals. Empirical models incorporating chemical composition are also widely used. The models tend to be useful within the ranges of the datasets used in their development but none can claim to have universal application. Mechanistic models are becoming increasingly complex and sophisticated and incorporate both feed characteristics and use of biochemical pathways within the animal. Improvement in utilisation through the deliberate selection of pasture plants for high feeding value appears to have potential and has been poorly exploited. Use of Near Infrared Reflectance Spectroscopy is a simple method that offers significant potential for the preliminary screening of plants with genetic differences in feeding value. Near Infrared Reflectance Spectroscopy will only be as reliable as the calibration sets from which the equations are generated.

• Korean journal of food and cookery science
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• v.3 no.2
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• pp.68-74
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• 1987

Objective and subjective methods were performed together for TPA analysis of acorn mook, and their correlations were analyzed. As the result of sensory evaluation, hardness and fracturability were most important factors for prediction of preference. Meanwhile, compression test with Instron Universal Testing Machine revealed that P1(maximum peak in first bite) was very effective factor representing the cheracteristics of first bite, and that P2 the latter peak in first bite) was valuable for prediction of characteristics of second bite.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.45-52
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• 2021

In this paper, we propose a prediction model for osteopenia and osteoporosis based on a convolutional neural network(CNN) using computed tomography(CT) images. In a single CT image, CNN had a limitation in utilizing important local features for diagnosis. So we propose a compound model which has two identical structures. As an input, two different texture images are used, which are converted from a single normalized CT image. The two networks train different information by using dissimilarity loss function. As a result, our model trains various features in a single CT image which includes important local features, then we ensemble them to improve the accuracy of predicting osteopenia and osteoporosis. In experiment results, our method shows an accuracy of 77.11% and the feature visualize of this model is confirmed by using Grad-CAM.

• Animal Bioscience
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• v.36 no.9
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• pp.1435-1444
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• 2023

Objective: This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle. Methods: Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups. Results: Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R² = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm^-1, suggests that the content of this amino acid could explain the differences between samples. Conclusion: Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.