• 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.

• Food Science of Animal Resources
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• v.41 no.4
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• pp.563-588
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• 2021

Increasing meat demand in terms of both quality and quantity in conjunction with feeding a growing population has resulted in regulatory agencies imposing stringent guidelines on meat quality and safety. Objective and accurate rapid non-destructive detection methods and evaluation techniques based on artificial intelligence have become the research hotspot in recent years and have been widely applied in the meat industry. Therefore, this review surveyed the key technologies of non-destructive detection for meat quality, mainly including ultrasonic technology, machine (computer) vision technology, near-infrared spectroscopy technology, hyperspectral technology, Raman spectra technology, and electronic nose/tongue. The technical characteristics and evaluation methods were compared and analyzed; the practical applications of non-destructive detection technologies in meat quality assessment were explored; and the current challenges and future research directions were discussed. The literature presented in this review clearly demonstrate that previous research on non-destructive technologies are of great significance to ensure consumers' urgent demand for high-quality meat by promoting automatic, real-time inspection and quality control in meat production. In the near future, with ever-growing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.

• Journal of Veterinary Clinics
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• v.39 no.3
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• pp.114-120
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• 2022

The purpose of this study is to examine the status of quality control using multipurpose phantom of ultrasound equipment used in hospital of veterinary college in South Korea by using ATS-539 multipurpose phantom so as to examine quantitative and objective new image evaluation method. Specialists discussed and analyzed multipurpose phantom images acquired by using convex transducer of 10 ultrasound imaging devices, currently used in 9 veterinary colleges, at 4.0-6.0 MHz. Total 8 items that can be measured with ATS-539 multipurpose phantom including dead zone, vertical and horizontal measurement, axial/lateral resolution, sensitivity, focal zone, functional resolution and gray scale/dynamic range were evaluated. For qualitative evaluation, valid decisions were made based on dead zone, axial/lateral resolution, and gray scale/dynamic range which are resolution index, and coefficient of variation (COV) and blind referenceless image spatial quality evaluator (BRISQUE) were found to increase objectivity. As a result of experiment, all the targeted ultrasonic devices were found appropriate from qualitative evaluation items of dead zone, axial/lateral resolution, and gray scale/dynamic range. In other evaluation items, they were found to be appropriate from focal zone and vertical measurement of quantitative evaluation while inappropriate from horizontal measurement, sensitivity, and functional resolution. COV value was 0.12 ± 0.04, and BRISQUE value was 47.77 ± 2.77, both analysis results show that the noise level of all ultrasonic devices was located within tolerance range. Upon image examination using ATS-539 multipurpose phantom, they were 100% appropriate with inspection standards of dead zone, axial/lateral resolution, and gray scale/dynamic range, and besides, focal zone and functional resolution can be used as evaluation items. In the field of veterinary medicine, 8 standard items using ATS-539 multipurpose phantom and image evaluation items using COV and BRISQUE can be used as standards for quality control of ultrasonography machine.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.4
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• pp.593-599
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• 2022

In this study, a crack monitoring system capable of detecting cracks based on image processing techniques was developed to effectively check cracks, which are the main damage of concrete structures, and a program capable of imaging and analyzing cracks was developed using machine vision. This system provides objective and quantitative data by replacing the appearance inspection that checks cracks with the naked eye. The verification of the development system was applied to the construction site of a self-healing concrete water tank to monitor the crack and the amount of change in the crack width according to age. In the case of crack width detected by image analysis, the difference from the measured value using a digital microscope was up to 0.036 mm, and the crack healing effect of self-healing concrete could be confirmed through the reduction of crack width.

• Convergence Security Journal
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• v.23 no.5
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• pp.117-123
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• 2023

Recently, as the demand for Generative Artificial Intelligence (AI) and artificial intelligence has increased, the seriousness of misuse and abuse has emerged. However, intelligent CCTV, which maximizes detection of abnormal behavior, is of great help to prevent crime in the military and police. AI performs learning as taught by humans and then proceeds with self-learning. Since AI makes judgments according to the learned results, it is necessary to clearly understand the characteristics of learning. However, it is often difficult to visually judge strange and abnormal behaviors that are ambiguous even for humans to judge. It is very difficult to learn this with the eyes of artificial intelligence, and the result of learning is very many False Positive, False Negative, and True Negative. In response, this paper presented standards and methods for clarifying the learning of AI's strange and abnormal behaviors, and presented learning measures to maximize the judgment ability of intelligent CCTV's False Positive, False Negative, and True Negative. Through this paper, it is expected that the artificial intelligence engine performance of intelligent CCTV currently in use can be maximized, and the ratio of False Positive and False Negative can be minimized..

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Journal of Food Hygiene and Safety
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• v.36 no.1
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• pp.42-50
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• 2021

Along with the rapid growth of the food service industry, food safety requirements and hygiene are increasing in importance in restaurants and hotels. Accordingly, there is a need for quick and practical monitoring techniques to determine hygiene status in the field. In this study, we investigated 5 domestic 5-star hotels specifically, personal hygiene (hands of workers), cooking utensils (knife, cutting board, food storage container, slicing machine blade, ice-maker scoop) and other facilities (refrigerator handle, sink). In addition, we examined the hygiene management status of customer contact points (tongs for buffet, etc.) to derive the correlation between the ATP values as a, a verification method. As a result of our five-hotel survey, we found that cooking utensils and personal hygiene were relatively sanitary compared to other inspection items (cookware 92.2%, personal hygiene 91.4%, facilities and equipment 76.19%, customer contact items 88.6%). According to our ATP-based mothod, kitchen utensils (51 ± 45 RLU/25㎠) were relatively clean compared to other with facilities and equipment (167 ± 123 RLU/25㎠). In the present study, we also evaluated the usefulness of the ATP bioluminescence method for monitoring surface hygiene at hotel restaurants. After correlation analysis of surveillance of hygienic status points and ATP assay, most results showed negative and high correlation (-0.64--0.89). Our ATP assay (92 ± 67 RLU/25㎠) of each item after cleaning showed signigicantly reduced results compared to the ATP assay (1020 ± 1254 RLU/25㎠) for normal status, thereby indicating its suitability as a tool to verify the validity of cleaning. By our results, ATP bioluminescence could be used as an effective tool for visual numerical evaluation of invisible contaminants.

• Journal of Sericultural and Entomological Science
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• no.12
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• pp.37-45
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• 1970

The processing management forms of our country's filature factories in 1969 are summarized as follows. (1) About 80％ of total cocoon collection is made within 5 days involving peak day, and 10％ of cocoon collection is finished until 3 days before and after the peak day, (2) About 92％ of alive cocoons transported on unpaved road, and about 40％ of the cocoons purchased by all factories are loaded on trucks from common selling station which is far beyond 40km, therefore a new packing system of alive cocoons to drop the damage of cocoon qualities, should be taken. (3) 22％ of all factories in our. country have only low-temperature cocoon drying machine. Therefore the installment of hot-air cocoon drying machine is required urgently. (4) In view of cocoon qualities in our country, the grouping method of cocoon for reeling. taken by about 50％ of the factories at percent, which classify cocoons for reeling as high group (1,2,3,4 grades) and low group(5,6 grades), will have to be replaced by the method tat classify them high group (1,2 grades) middle group (3,4 grades), low group (5,6 grades). (5) The .ratio of cocoon assorting stood about 10％ in multi-ends reeling, about 15％ in automatic reeling, conclusively, the ratio of cocoon assorting for automatic reeling was higher tan that for multi-ends reeling. One person's ability for a day in cocoon assorting reaches to about 80-100kg. (6) Cocoon cooking condition requires the increase of the cooking time, the pressure and temperature used to be prolonged as much as the qualities of cocoons are material cocoon ior automatic and double cocoon machines are treated uncompletely. (7) Automatic silk reeling is being performed at 1-2$^{\circ}C$ lower in reeling water temperature and operated at about twice velocity. (8) The temperature and humidity of rereeling room stood at 25$^{\circ}C$, 67.2％ R.H and 32.3$^{\circ}C$, 51.9％ R.H of rereeling machine are showed, Average rereeling velocity is 233m/min and large reefs charged for one person are 7.5 reels and form of skein used in all factories is double skein. (9) About 73％ of water sources for filature used under-earth water. About 48％ of all filature factories in our country have not yet water purifying equipments. Installation of the equipment for these factories seems to be urgent, (10) Denier .balance, sizing reel, seriplane, are being used in most factories as self-inspection apparatus. (11) More than 90％ of the factories use the vacum tank in rereeling process and about 20％ of them use it in cocoon cooing process (12) Only 21％ of the factories use chemicals in filature process. About all them use "Seracol 100" in cocoon cooking process and "Seracol 500" in rereeling process, (13) Above survey results explain each all factories show large difference in the processing management. Therefore, it is believed that intercommunication through seminar or technical exchange will contribute to the production evaluation of cocoon in our filature industry.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.307-325
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• 2023

Due to the prolonged COVID-19 pandemic, the frequency of people who are tired of living indoors visiting nearby mountains and national parks to relieve depression and lethargy has exploded. There is a place where thousands of people who came out of nature stop walking and breathe and rest, that is the mineral spring. Even in mountains or national parks, there are about 600 mineral springs that can be found occasionally in neighboring parks or trails in the metropolitan area. However, due to irregular and manual water quality tests, people drink mineral water without knowing the test results in real time. Therefore, in this study, we intend to develop a model that can predict the quality of the spring water in real time by exploring the factors affecting the quality of the spring water and collecting data scattered in various places. After limiting the regions to Seoul and Gyeonggi-do due to the limitations of data collection, we obtained data on water quality tests from 2015 to 2020 for about 300 mineral springs in 18 cities where data management is well performed. A total of 10 factors were finally selected after two rounds of review among various factors that are considered to affect the suitability of the mineral spring water quality. Using AutoML, an automated machine learning technology that has recently been attracting attention, we derived the top 5 models based on prediction performance among about 20 machine learning methods. Among them, the catboost model has the highest performance with a prediction classification accuracy of 75.26%. In addition, as a result of examining the absolute influence of the variables used in the analysis through the SHAP method on the prediction, the most important factor was whether or not a water quality test was judged nonconforming in the previous water quality test. It was confirmed that the temperature on the day of the inspection and the altitude of the mineral spring had an influence on whether the water quality was unsuitable.

• Korean Journal of Veterinary Research
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• v.21 no.2
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• pp.151-159
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• 1981

An investigation on various causes of milking disturbances resulting from injuries and abnormalities of mammary system were made in 2,179 Holstein cows. To perform this investigation, 69 dairy farms of the suburban area of Seoul city, Gyeonggi-do and Chungnam provinces were andomly selected and subjected. Diagnosis was made by means of inspection and palpation of teat, insertion of teat canula, checking milk machines, anamneses and farm records. This investigation was, actively done from March 1977 to February 1979, The results obtained were summerized as follows; 1. It was found that 446 cows, accounting for 20.48% of 2,179 cows inspected, had supernumerary teats. Among them 53.59% had one, 43.72% had two, 2.47% had three, and 0.22% had four supernumerary teats, respectively. 2. Dry off quarters were found in 158 quarters which turned out to be 1.8% of 8,716 quarters inspected. Among dry off quarters, 62.02% seemed to be caused by mastitis, 30.37% by acquired teat obstructions, and 7.59% by congenital blind teats and glands respectively. 3. Teat sphincter stenosis was found in 154 teats of 50 cows, which represents 1.76% of 8,716 teats and 2.29% of 2,179 cows inspected, respectively. Among 154 teats with teat sphincter stenosis, 138 teats (85.7%) of 33 cows were found to be congenital and revealed highest incidence. 4. Loose sphincter was found in 78 teats of 36 cows, which figure 0.89% of 8,7l6 teats and 1.69% of 2,179 cows inspected, respectively. Among 78 teats with loose sphincter, 52 teats (66.66%) of 13 cows were found to be congenital and revealed highest incidence. 5. Injured teat tip caused by over milking of milk machine, was found in 229 teats of 156 cows, which figure 2.63% of 8,716 teats and 7.15% of 2,179 cows observed, respectively. 6. Other miscellaneous injuries and congenital abnormalities of teats and udders were diagnosed as follows: The teat laceration was found in 34 teats (0.39% of 8,716 teats), fissure of teat skin in 24 teats (0.28% of 8,716 teats), stricture of teat cistern in 21 teats (0.24% of 8,716 teats), teat fistula in 12 teats (0.14% of 8,716 teats), papillomas on testes in 8 teats (0.09% of 8,716 teats). Knothole orifice in 7 teats (0.08% of 8,716 teats), subcutaneous abscess of udder in 5 quarters (0.05% of 8,716 teats), membraneous obstruction of teat cistern in 4 teats (0.05% of 8,716 teats), and congenital short teat in 8 teats (0.09% of 8,716 teats), respectively.