• Journal of Animal Environmental Science
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• v.18 no.1
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• pp.25-34
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• 2012

Noxious gases with malodorous substance concentrations in each stages of pig buildings were determined at a typical 400sow-scale farm to improve piggery environment. Using IAQ-300 and pDR-1000AN, continuous records for the concentration of $NH_3$, CO, $CO_2$, $NO_2$, $SO_2$, $H_2S$, $O_2$, and along with temperature, humidity, dust concentrates from individual pig pens were collected to analyze every 6 hours' condition of indoor environment for 24 hours' period. In most pig houses, the air quality at noon was good, while at night (00:00~06:00), air composition became noxious in all buildings. The order of buildings' air quality for 24 hrs was pregnant > farrowing > nursery > growing > finishing. The cause of air quality differences was presumed to be the differences of stocking density, defecating amount and the length of exposure time of slurry in indoors. In conclusion, well-designed building structure, proper control of stocking density, quick removal of excreta from pig pens and continuous ventilation are prerequisites to improve pig housing environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.68-78
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• 2013

In this paper, we propose an early spectrum sensing(ESS) as an advance preparation for radio-access trial, which enables multi-mode terminals to access the most appropriate radio-access system in a cloud-conceptual base station system where multiple radio access technologies(RATs) coexist. Prior to a random access to one of RATs, a multi-mode terminal conducts a spectrum sensing over entire frequency bands of whole RATs, then select the RAT with the lowest sensing power, that is likely to have the most available spectrum. Thus, an access failure caused by that the selected RAT has no available radio spectrum could be avoidable in advance. In computer simulation, we consider as various RATs as possible. First, circuit and packet systems are taken into consideration. In addition, the packet systems are classified according to the feasibility of carrier aggregation(CA). In case of terminal, three modes are considered with circuit-only, packet-only, and multi-mode. Subsequently, packet traffic is classified into real-time and non-real-time traffic with three different tolerable delay levels. The simulation includes a call process starting with a call generation and ending up with a resource allocation reflecting individual user's QoS requirements and evaluates the proposed scheme in terms of the successful access probability, system access time, system balancing factor and packet loss probability.

• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.53-60
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• 2018

To diagnosis the local damages of the steel plates, magnetic flux leakage (MFL) method that is known as a adaptable non-destructive evaluation (NDE) method for continuum ferromagnetic members was applied in this study. To analysis the sensitivity according to thickness of steel plate in MFL method based damage diagnosis, several steel plate specimens that have different thickness were prepared and three depths of artificial damage were formed to the each specimens. To measured the MFL signals, a MFL sensor head that have a constant magnetization intensity were fabricated using a hall sensor and a magnetization yoke using permanent magnets. The magnetic flux signals obtained by using MFL sensor head were improved through a series of signal processing methods. The capability of local damage detection was verified from the measured MFL signals from each damage points. And, the peak to peak values (P-P value) extracted from the detected MFL signals from each thickness specimen were compared each other to analysis the MFL based local damage detection sensitivity according to the thickness of steel plate.

• Applied Biological Chemistry
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• v.50 no.1
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• pp.48-52
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• 2007

Yogurt base was prepared from skim milk supplemented with 0.2-1.0% (w/v) garlic powder and fermented with lactic acid bacteria (the mixed strain of Lactobacillus acidophilus, Bifidobacterium longum and Streptococcus thermophilus) at 40$^{\circ}C$ for 18 h. Quality characteristics of the prepared yogurt were evaluated for acid production (pH and titratable acidity), number of viable cells, viscosity and sensory properties. The addition of garlic powder inhibited the growth of lactic acid bacteria and decreased the acid production. After 18 h incubation, titratable acidity of garlic yogurt was 1.28-1.08% and was lower than that (1.35%) of yogurt made with only skim milk. However, the viscosity of yogurt was remarkably increased by the addition of garlic powder. The sensory score of yogurt added with 0.2% garlic powder was similar to ordinary yogurt in flavor and overall acceptability. According to sensory score and fermentation characteristics, the optimum concentration of garlic powder was around 0.2%.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.327-340
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• 2021

Purpose: The purpose of this study is to propose a system predicting whether an electricity distribution system is abnormal by analyzing the temperature of the deteriorated system. Traditional electricity distribution system abnormality diagnosis was mainly limited to post-inspection. This research presents a remote monitoring system for detecting thermal images of the deteriorated electricity distribution system efficiently hereby providing safe and efficient abnormal diagnosis to electricians. Methods: In this study, an object detection algorithm (YOLOv5) is performed using 16,866 thermal images of electricity distribution systems provided by KEPCO(Korea Electric Power Corporation). Abnormality/Normality of the extracted system images from the algorithm are classified via the limit temperature. Each classification model, Random Forest, Support Vector Machine, XGBOOST is performed to explore 463,053 temperature datasets. The process capability index is employed to indicate the quality of the electricity distribution system. Results: This research performs case study with transformers representing the electricity distribution systems. The case study shows the following states: accuracy 100%, precision 100%, recall 100%, F1-score 100%. Also the case study shows the process capability index of the transformers with the following states: steady state 99.47%, caution state 0.16%, and risk state 0.37%. Conclusion: The sum of caution and risk state is 0.53%, which is higher than the actual failure rate. Also most transformer abnormalities can be detected through this monitoring system.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.84-90
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• 2022

Machine tool state monitoring is a process that automatically detects the states of machine. In the manufacturing process, the efficiency of machining and the quality of the product are affected by the condition of the tool. Wear and broken tools can cause more serious problems in process performance and lower product quality. Therefore, it is necessary to develop a system to prevent tool wear and damage during the process so that the tool can be replaced in a timely manner. This paper proposes a method for diagnosing five tool states using a deep learning-based hierarchical convolutional neural network to change tools at the right time. The one-dimensional acoustic signal generated when the machine cuts the workpiece is converted into a frequency-based power spectral density two-dimensional image and use as an input for a convolutional neural network. The learning model diagnoses five tool states through three hierarchical steps. The proposed method showed high accuracy compared to the conventional method. In addition, it will be able to be utilized in a smart factory fault diagnosis system that can monitor various machine tools through real-time connecting.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.421-431
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• 2009

This paper is the study on the verification of structural health monitoring (SHM) algorithm based on the ultrasonic guided wave. An active inspection system using Lamb wave (LW) for SHM was considered. The basic study about the application of this algorithm was performed for detecting the circular notch defect in steel plate. LW testing technique, pitch-catch method, was used for interpretation of circular notch defect with depth of 50% of plate thickness and 7 mm width. Damage characterization takes place by comparing $S_0$ mode sensor signals collected before and after the damage event. By subtracting the signals of both conditions from each other, a scatter signal is produced which can be used for damage localization. The continuous Gabor wavelet transform is used to attain the time between the arrivals of the scatter and sensor signals. A new practical damage monitoring algorithm, based on damage monitoring polygon and pitch-catch method, has been proposed and verified with good accuracy. The possible damage location can be estimated by the average on calculated location points and the damage extent by the standard deviation.

• Journal of the Korean Society of Radiology
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• v.83 no.2
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• pp.344-359
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• 2022

Purpose To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging. Materials and Methods A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order. Results Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences. Conclusion Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.9
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• pp.117-123
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• 2009

Recently, the failures of electrical equipment have been reduced due to the improvement of its quality and the advance of operation techniques but the failure rates caused by natural disasters such as wind and lightning have been increased. To reduce the failures due to lightning, it is necessary for insulation design of transmission lines to be done, effectively. Also the analysis on the lightning characteristics is essential to the effective insulation design. In this paper, we describe lightning distribution, multiplicity, IKL(Iso-Keraunic Level) and amplitude distribution of lightning current base on the lightning data by KLDNet.

• Tribology and Lubricants
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• v.27 no.3
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• pp.125-133
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• 2011

The purpose of this study is to develop an engine oil quality monitoring system to warn the abnormal condition of engine oil. To do this, first of all, it is needed a personal controller development to measure the capacitance of a pre-developed engine oil deterioration detection sensor integrated with an oil filter. To measure the capacitance of engine oil in the sensor, it is used the way measuring the electric charging time in a capacitor by impressing DC volt. This method has merits on cost and signal stability. The measured capacitance is compensated by comparing with the one measured by an impedance analyzer. Also, using the dielectric constant gained by an impedance analyzer, the calculating equation of the dielectric constant of engine oil related with the currently developed sensor is decided. Then, the deterioration degree of engine oil is estimated according to the change rate of dielectric constant between green oil and used oil. Finally, using this dielectric constant information together with engine oil temperature and pressure, the currently developed engine oil quality monitoring system is to tell the abnormal state of engine oil.