• Smart Structures and Systems
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• v.14 no.4
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• pp.719-741
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• 2014

Monitoring surface cracks is important to ensure the health of concrete structures. However, traditional visual inspection to monitor the concrete cracks has disadvantages such as subjective inspection nature, associated time and cost, and possible danger to inspectors. To alter the visual inspection, a complete procedure for automated crack assessment based on adaptive digital image processing has been proposed in this study. Crack objects are extracted from the images using the subtraction with median filter and the local binarization using the Niblack's method. To adaptively. determine the optimal window sizes for the median filter and the Niblack's method without distortion of crack object an optimal filter size index (OFSI) is proposed. From the extracted crack objects using the optimal size of window, the crack objects are decomposed to the crack skeletons and edges, and the crack width is calculated using 4-connected normal line according to the orientation of the local skeleton line. For an image, a crack width nephogram is obtained to have an intuitive view of the crack distribution. The proposed procedure is verified from a test on a concrete reaction wall with various types of cracks. From the crack images with different crack widths and patterns, the widths of cracks in the order of submillimeters are calculated with high accuracy.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7607-7612
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• 2015

Aims: The purpose of our study was to evaluate the diagnostic performance of breast magnetic resonance imaging (MRI) in the evaluation of contralateral breast in patients with diagnosed breast cancer. A secondary objective was to determine accuracy of breast MRI in diagnosing multi-focal and multicentric lesions in the ipsilateral breast. Materials and Methods: Using a non-probability convenience sampling technique, patients with histopathologically diagnosed breast cancer with MRI of breast performed to exclude additional lesions were included. MRI findings were correlated with histopathology. In addition, follow-up imaging with mammography and ultrasound was also assessed for establishing stability of negative findings and for the detected of benign lesions. Results: Out of 157 MRI breast conducted during the period of 2008 to 2013, 49 were performed for patients with diagnosed breast cancer. The sample comprised of all females with mean age $50.7{\pm}11.0years$. The patient follow-up imaging was available for a period of 2-5 years. The sensitivity, specificity, and positive and negative predictive values of MRI in the detection of multifocal/multicenteric lesions was 85.7%, 88.8%, 60% and 96.6% respectively and for the detection of lesions in the contralateral breast were 100%, 97%, 83.3% and 100% respectively. Conclusions: Our study highlights the diagnostic performance and the added value of MRI in the detection of multifocal/multicenteric and contralateral malignant lesions. In patients with diagnosed breast cancer having dense breast parenchyma and with infiltrating lobular carcinoma as the index lesion MRI is particularly useful with excellent negative predictive value in the exclusion of additional malignant foci in the ipsilateral and contralateral breasts.

• Korean Journal of Agricultural Science
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• v.9 no.1
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• pp.314-356
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• 1982

In order to improve the efficiency of the main economic traits in layers the present selection index is based on body weight, age at first egg, egg production and egg weight. But as the edible parts of the egg, the yolk and the albumin, are very important economic traits, this study was conducted to estimate the selection indices combining the latter traits with the former traits, and to examine the accuracy of the indices. The experiment were 351 Single Comb White Leghorns(S. C. W. Leghorn) and 326 Rhode Island Reds (R. I. Red), improved by the closed flock breeding system at the Daejeon Branch Station of the National Livestock Breeding Station. The egg compositions were checked a total of 6097 eggs. The data for each traits were collected and analysed until 500 days of age from March 1, 1979.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.9 s.114
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• pp.897-903
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• 2006

The reduction of the vehicle interior noise has been the main interest of noise and vibration harshness (NVH) engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the heating, ventilation and air conditioning (HVAC) system sound among the vehicle interior noise has been reflected sensitively in psychoacoustics view point. Even though the HVAC noise is not louder than overall noise level, it clearly affects subjective perception to drivers in the way of making to be nervous or annoyed. Therefore, these days a vehicle engineer takes aim at developing sound quality as well as reduction of noise. In this paper, we acquired noises in the HVAC from many vehicles. Through the objective and subjective sound quality (SQ) evaluation with acquiring noises recorded by the vehicle HVAC system, the simple and multiple regression models were obtained for the subjective evaluation 'Pleasant' using the semantic differential method (SDM). The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Furthermore, the neural network (NN) model were obtained using three inputs(loudness, sharpness and roughness) of the SQ metrics and one output(subjective 'Pleasant'). Because human's perception is very complex and hard to estimate their pattern, we used NN model. The estimated models were compared with correlations between output indexes of SQ and hearing test results for verification data 'Pleasant'. As a result of application of the SQ indexes, the NN model was shown with the largest correlation of SQ indexes and we found possibilities to predict the SQ metrics.

• Korean journal of food and cookery science
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• v.32 no.1
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• pp.123-135
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• 2016

The purpose of this study was to evaluate the effectiveness of an intervention program using dietary consult and physical exercise conducted by public health center in Chuncheon city for obese adults. This study used a pretest-posttest design. The subjects were 58 out of 90 obese adults with body mass index (BMI) greater than $25kg/m^2$ who completed all education sessions for 8 weeks. Data on dietary habits, dietary behaviors, nutritional knowledge, anthropometric parameters and biochemical indices and daily nutrient intakes assessed by a 24-hour recall were collected before and after the intervention program., in order to evaluate program effectiveness. After the intervention, there were positive changes in exercise status and dietary habits and nutrition knowledge accuracy. Especially, the answer of 'I drink a cup of milk every day' were significantly improved (p<0.001), and the answer of 'I don't overeat', which is a dietary attitude question was significantly improved (p<0.05). Dietary intakes of most of nutrients were not significantly different between pre-test and post-test. But calcium (p<0.05), potassium (p<0.05), vitamin A (p<0.01), vitamin E (p<0.05), and folic acid (p<0.05) were significantly increased in the female group after the intervention. Weight (p<0.05), BMI (p<0.01), blood pressure (p<0.001), were significantly decreased after program, but changes of skeletal muscle mass, body fat mass were not significant. Resting heart rate (p<0.01), flexibility (p<0.001), whole body reaction (p<0.05), grip strength (p<0.01) and balance (p<0.01) showed positive changes after the intervention. Blood glucose level in serum was significantly decreased (p<0.001). These results indicated that dietary education and exercise program was effective not only for weight reduction but also for the improvement of physical fitness in obese adults.

• Structural Engineering and Mechanics
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• v.75 no.2
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• pp.193-209
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• 2020

This paper presents a new hyperbolic shear deformation plate theory including the stretching effect for free vibration of the simply supported functionally graded plates in thermal environments. The theory accounts for parabolic distribution of the transverse shear strains and satisfies the zero traction boundary conditions on the surfaces of the plate without using shear correction factors. This theory has only five unknowns, which is even less than the other shear and normal deformation theories. The present one has a new displacement field which introduces undetermined integral variables. Material properties are assumed to be temperature-dependent, and graded in the thickness direction according to a simple power law distribution in terms of the volume power laws of the constituents. The equation of motion of the vibrated plate obtained via the classical Hamilton's principle and solved using Navier's steps. The accuracy of the proposed solution is checked by comparing the present results with those available in existing literature. The effects of the temperature field, volume fraction index of functionally graded material, side-to-thickness ratio on free vibration responses of the functionally graded plates are investigated. It can be concluded that the present theory is not only accurate but also simple in predicting the natural frequencies of functionally graded plates with stretching effect in thermal environments.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.6
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• pp.614-620
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• 1997

Pedigree data were used to predict the performance of 1,166 imported Americas Brahman breeder cattle, composed of 104 bulls and 1,062 heifers with an average age of 24.4 months (range of 17 to 40 months). A total of 13 full sib, 10 maternal half sib, and 228 paternal half sib groups were identified, each with average group size of 2.08, 2.00, and 4.49, respectively. Only 758 (64.9% of total) imported cattle were found to have at least one ancestor with expected progeny differences (EPDs) reported in the Spring 1995 Brahman Sire Summary. Moderate average accuracy values of .71, .69, .52, and .52 for birth weight, weaning weight, yearling weight, and maternal milk, respectively, were noted for EPDs of the ancestors. Prediction equations were derived by multiple regression analysis of available EPDs of sire, paternal grand sire, and maternal grand sire. Based on pedigree indexes that involve various combinations of available ancestral information, the average predicted EPDs (lbs) for imported cattle were $1.76{\pm}0.54$, $14.93{\pm}4.86$, $25.10{\pm}9.50$, and $5.86{\pm}2.08$ for birth weight, weaning weight, yearling weight, and maternal milk, respectively. Significant correlations (p < .05) were also found between sire and son EPDs (+.27) for yearling weight; and between sire and paternal grand sire EPDs for birth weight (+.34), weaning weight (+.51), yearling weight (+.49), and maternal milk (+.55).

• Korean Journal of Fisheries and Aquatic Sciences
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• v.53 no.1
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• pp.50-56
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• 2020

Determination of the precise size at sexual maturity is very important for science-based stock assessment and fisheries resource management. In this study, two different models, (1) a visual method and (2) a gonadosomatic index (GSI) method, were employed to estimate length at sexual maturity of the small yellow croaker Larimichthys polyactis in the Yellow Sea of Korea. The visual method is a common qualitative method using visual gonadal identification. Conversely, the GSI method is a quantitative method using the GSI, which can be easily and precisely collected. We compared results from these methods to determine the best approach, and to examine the practicality of the GSI method. Logistic regression of the maturity ogive was conducted using a general linear model (GLM) with the R statistics program. Also, the bootstrapped 95% confidence intervals of all estimates were calculated. The best-fit model was the visual method (R_Mc²=0.805, AUC=0.989, L₅₀=15.1). Among models using the GSI method, the model computing GSI_ref=0.94 was the best-fit model (R_Mc²=0.792, AUC=0.989, L₅₀=15.2). There was no significant difference between the two models, evidencing the effectiveness and accuracy of the GSI method.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.338-344
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• 2015

The national competency standards (NCS) is a systematize and standardize for skills required to perform their job. The NCS has developed a learning module with materialization and standardize by competence unit element, which is the unit of specific job competency. The existing curriculum is material to gab analysis for use in education training with competence unit element. The existing gab analysis has evaluated subjectively by experts. The gab analysis by experts bring up a subject subjective decision, accuracy lack, temporal and spatial inefficiency by psychological factor. This paper is proposed automated evaluation model for problem resolve of subjective evaluation. This paper use index term extraction, term frequency-inverse document frequency for feature value extraction, cosine similarity algorithm for gab analysis between existing curriculum and competence unit element. This paper was presented similarity mapping table between existing curriculum and competence unit element. The evaluation model in this paper should be complemented by an improved algorithm from the structural characteristics and speed.

• The Journal of Information Systems
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• v.26 no.3
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.