• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1109-1122
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• 2020

The aim of this study was to develop a marbling classification and prediction model using small parts of sirloin images based on a deep learning algorithm, namely, a convolutional neural network (CNN). Samples were purchased from a commercial slaughterhouse in Korea, images for each grade were acquired, and the total images (n = 500) were assigned according to their grade number: 1++, 1+, 1, and both 2 & 3. The image acquisition system consists of a DSLR camera with a polarization filter to remove diffusive reflectance and two light sources (55 W). To correct the distorted original images, a radial correction algorithm was implemented. Color images of sirloins of Hanwoo (mixed with feeder cattle, steer, and calf) were divided and sub-images with image sizes of 161 × 161 were made to train the marbling prediction model. In this study, the convolutional neural network (CNN) has four convolution layers and yields prediction results in accordance with marbling grades (1++, 1+, 1, and 2&3). Every single layer uses a rectified linear unit (ReLU) function as an activation function and max-pooling is used for extracting the edge between fat and muscle and reducing the variance of the data. Prediction accuracy was measured using an accuracy and kappa coefficient from a confusion matrix. We summed the prediction of sub-images and determined the total average prediction accuracy. Training accuracy was 100% and the test accuracy was 86%, indicating comparably good performance using the CNN. This study provides classification potential for predicting the marbling grade using color images and a convolutional neural network algorithm.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.591-602
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• 2020

Several alternative rock-cutting concepts, which are modified from the conventional ones, have been developed lately. Of the concepts, undercutting is one of the latest technologies. In this study, as a fundamental study on the undercutting technique, the rock-cutting mechanism and important parameters of the undercutting were introduced. This study built up cutting test system for evaluating the cutting performance of an actuated undercutting disc cutter (ADC), and carried out a series of cutting tests under different cutting parameters of ADC. The characteristics of cutter forces obtained from ADC rock-cutting tests were analyzed. The both average and peak values of the three directional cutter forces were linearly increased with the increases of linear velocity, penetration depth in vertical direction and eccentricity of ADC.

• Journal of the Korean Geotechnical Society
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• v.36 no.12
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• pp.125-132
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• 2020

Embedded joints in the rock mass are a major constituent influencing its mechanical behavior. Numerical analysis requires a rigorous modeling methodology for the rock mass with detailed information regarding joint properties, orientation, spacing, and persistence. This paper provides a mechanical model for a jointed rock mass based on the implicit joint-continuum approach. Stiffness tensors for rock mass are evaluated for an assemblage of intact rock separated by sets of joint planes. It is a linear summation of compliance of each joint sets and intact rock in the serial stiffness system. In the application example, kinematic analysis for a planar failure of rock slope is comparable with empirical daylight envelope and its lateral limits. Since the developed implicit joint-continuity model is formulated on a continuum basis, it will be a major tool for the numerical simulations adopting published plenteous thermal-hydro-chemical experimental results.

• Smart Structures and Systems
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• v.26 no.6
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• pp.681-692
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• 2020

Conventional Piezoelectric Energy Harvesters (CPEH) have been extensively studied for maximizing their electrical output through material selection, geometric and structural optimization, and adoption of efficient interface circuits. In this paper, the performance of Stepped Piezoelectric Energy Harvester (SPEH) under harmonic base excitation is studied analytically, numerically and experimentally. The motivation is to compare the energy harvesting performance of CPEH and SPEHs with the same characteristics (resonant frequency). The results of this study challenge the notion of achieving higher voltage and power output through incorporation of geometric discontinuities such as step sections in the harvester beams. A CPEH consists of substrate material with a patch of piezoelectric material bonded over it and a tip mass at the free end to tune the resonant frequency. A SPEH is designed by introducing a step section near the root of substrate beam to induce higher dynamic strain for maximizing the electrical output. The incorporation of step section reduces the stiffness and consequently, a lower tip mass is used with SPEH to match the resonant frequency to that of CPEH. Moreover, the electromechanical coupling coefficient, forcing function and damping are significantly influenced because of the inclusion of step section, which consequently affects harvester's output. Three different configurations of SPEHs characterized by the same resonant frequency as that of CPEH are designed and analyzed using linear electromechanical model and their performances are compared. The variation of strain on the harvester beams is obtained using finite element analysis. The prototypes of CPEH and SPEHs are fabricated and experimentally tested. It is shown that the power output from SPEHs is lower than the CPEH. When the prototypes with resonant frequencies in the range of 56-56.5 Hz are tested at 1 m/s2, three SPEHs generate power output of 482 μW, 424 μW and 228 μW when compared with 674 μW from CPEH. It is concluded that the advantage of increasing dynamic strain using step section is negated by increase in damping and decrease in forcing function. However, SPEHs show slightly better performance in terms of specific power and thus making them suitable for practical scenarios where the ratio of power to system mass is critical.

• Journal of Ocean Engineering and Technology
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• v.35 no.1
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• pp.82-90
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• 2021

Owing to the advantages of assuring the best views and seawater exchange, submerged breakwaters have been widely installed along the eastern coast of Korea in recent years. It significantly contributes to promoting the advancement of shorelines by partially inhibiting incident wave energy. Observations were carried out by a pressure-type wave gauge in the Bongpo Beach to evaluate the coefficients of wave transmission via a submerged breakwater, and the results obtained were compared with those of existing conventional equations on the transmission coefficient derived from hydraulic experiments. After reviewing the existing equations, we proposed a transmission coefficient equation in terms of an error function. Although it exhibited robust relationships with the crest height and breaking coefficient, deviations from the observed data were evident and considered to be triggered by the difference in the incident wave climate. Therefore, in this study, we conducted a numerical experiment to verify the influence of wave period on the coefficients of wave transmission, in which we adopted a parabolic-type mild-slope equation model. Consequently, the deviation from calculated results appears to practically cover all deviation range in the observed data. The wave period and direction of the incident wave increased, the transmission coefficient decreased, and the wave direction was determined to demonstrate a relatively significant influence on the transmission coefficient. It was inferred that this numerical study is expected to be used practically in evaluating the design achievement of the submerged breakwater, which is adopted as a countermeasure to coastal beach erosion.

• Journal of the Korean Society of Radiology
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• v.14 no.7
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• pp.947-956
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• 2020

The human body becomes vulnerable to various diseases due to deterioration in structure and function as it ages. In particular, changes in brain structure weaken the immune system against diseases such as vascular and metabolic neuropsychiatric diseases. In this study, we used a magnetic resonance imaging technique that allows non-invasive observation of brain structures and measurement of how the volumes of the brain, gray matter, white matter, and subcortical regions changes with aging in women aged 65 to 85 years. As a result of our investigation, we observed a significant linear decrease in subcortical regions with age. These results suggest that the changes due to aging in the brain structure area are closely related to neuropsychiatric diseases in old age, and can provide information in understanding the vulnerability of the brain in old age.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.483-488
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• 2020

In recent years, the demand for wireless devices incorporating several wireless communication systems into one has been increasing in order to provide services that meet the diverse needs of consumers. Wireless devices consisting of various wireless communication systems require many frequency fixed filters. A frequency tunable filter can replace a number of frequency fixed filters in the wireless devices. If a frequency tunable filter is used in wireless systems, the system can be configured more efficiently. In this paper, a 3-pole frequency tunable BPF(bandpass filter) operating in the frequency band of 800 ~ 2400MHz is designed. In order to widen the operating frequency band, a tuning screw is designed to have a step and a linear motor is used to facilitate the adjustment of the tuning screw. The implemented frequency tunable BPF operates in the designed frequency range and has the maximum insertion loss of 2.82dB in the channel band and the minimum attenuation of 18.7dB at ± 50MHz frequency offset from the center frequency of the band.

• Journal of Integrative Natural Science
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• v.13 no.4
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• pp.132-140
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• 2020

With the recent introduction of artificial intelligence (AI) technology, the use of data is rapidly increasing, and newly generated data is also rapidly increasing. In order to obtain the results to be analyzed based on these data, the first thing to do is to classify the data well. However, when classifying data, if only one classification technique belonging to the machine learning technique is applied to classify and analyze it, an error of overfitting can be accompanied. In order to reduce or minimize the problems caused by misclassification of the classification system such as overfitting, it is necessary to derive an optimal classification by comparing the results of each classification by applying several classification techniques. If you try to interpret the data with only one classification technique, you will have poor reasoning and poor predictions of results. This study seeks to find a method for optimally classifying data by looking at data from various perspectives and applying various classification techniques such as LDA and QDA, such as linear or nonlinear classification, as a process before data analysis in data analysis. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable and the correlation between the variables. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified to suit the purpose of analysis. This is a process that must be performed before reaching the result by analyzing the data, and it may be a method of optimal data classification.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.6
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• pp.37-46
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• 2006

It is known to be hard to apply cryptographic one-way functions to the recognition system using bio-information directly. As one of the solutions about that problem there is a permutation transformation scheme. However, they did not show my algorithmic behavior or any performance analysis of the transformation by experiment. In this paper, by showing the recognition ratio of the transformed scheme by experiment, we prove that that scheme is sound. Also, we adopt their transformation to LDA(Linear Discriminant Analysis) to show the experimental results. In the negative side, we introduce a new type of attack against the permutation transformation schemes. finally, we briefly mention a generalization of the permutation transformation for countermeasure of the attack at the end of this paper.

• The Journal of Bigdata
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• v.5 no.2
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• pp.97-110
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• 2020

The global pandemics occurred in 2020 had a great economic impact on the world, and the impact was especially greater on self-employed people who were heavily affected by the floating population and tourism industry. To solve this problem, each country implemented emergency disaster support policies, and it was difficult to select the criteria and scope. The following research carried out two results. First, after analyzing the impact of global pandemics on the local economy, an economical index was defined that could explain the impact intuitively. Second, we propose linear programming methods to provide optimal budget policy using defined indicators, which present economic shock indicators and optimal years that can be considered quickly and easily by the government. Finally, the limitations and implications of the proposed study model are introduced.