• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.735-742
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• 2023

Non-alcoholic fatty liver disease is an independent risk factor for the development of cardiovascular disease, diabetes, hypertension, and kidney disease, and the clinical importance of non-alcoholic fatty liver disease has recently been increasing. In this study, we aim to extract feature values by applying GLCM, a texture analysis method, to ultrasound images of patients with non-alcoholic fatty liver disease. By applying an artificial neural network model using extracted feature values, we would like to classify the degree of fat deposition in non-alcoholic fatty liver into normal liver, mild fatty liver, moderate fatty liver, and severe fatty liver. As a result of applying the GLCM algorithm, the parameters Autocorrelation, Sum of squares, Sum average, and sum variance showed a tendency for the average value of the feature values to increase as it progressed from mild fatty liver to moderate fatty liver to severe fatty liver. The four parameters of Autocorrelation, Sum of squares, Sum average, and sum variance extracted by applying the GLCM algorithm to ultrasound images of non-alcoholic fatty liver disease were applied as inputs to the artificial neural network model. The classification accuracy was evaluated by applying the GLCM algorithm to the ultrasound images of non-alcoholic fatty liver disease and applying the extracted images to an artificial neural network, showing a high accuracy of 92.5%. Through these results, we would like to present the results of this study as basic data when conducting a texture analysis GLCM study on ultrasound images of patients with non-alcoholic fatty liver disease.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.27-33
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• 2023

Recently, water shortages have occurred due to climate change, and the need for water management of agricultural water has increased due to the occurrence of algal blooms in reservoirs. Existing algae prevention is operated by putting many people on site and misses the optimal spraying time due to movement through boats. In order to solve this problem, it is necessary to block contamination in advance and move within time to uniformly spray complex microorganisms uniformly. Control drones are used for pesticide spraying and can be applied to algae prevention work by utilizing control drones. In this paper, basic research for the establishment of a marine control system was conducted for application to the reservoir environment, and as one of the results, the characteristics of a drone nozzle, a core technology that can be used for control drones, were calculated. In particular, it was found that the existing agricultural control drones had a disadvantage that the concentration was non-uniform within the suggested spraying interval, and to compensate for this, nozzle positioning and nozzle spraying uniformity were calculated. Based on the experimental results, we develop a core algorithm for establishing an algal bloom monitoring system in the reservoir environment and propose a precision control technology that can be used for marine control work in the future.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.4
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• pp.409-420
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• 2023

The purpose of this study is to analyze trends in the prevalence of dental caries and demand for dental caries treatment among children under 14 years old using Health Insurance Review and Assessment data. The analysis was conducted using treatment records from a random sample of approximately 1 million pediatric patients from a population that included all children and adolescents for each year from 2011 to 2020. In this study, the number of children diagnosed with K02 dental caries and the number of children receiving dental caries treatment across all ages have increased. However, the number of children aged 10 to 14 who received pulp treatment or extraction has decreased. In the National Survey of Children's Oral Health, the decay-missing-filled teeth index for 5- and 12-year-olds has stagnated or increased slightly, but the percentage of the population with active dental caries has decreased. Accessibility and local environments for dental caries treatment have generally improved compared to the past, but preventive dental care has stagnated over the past decade. Therefore, it is necessary to evaluate the effectiveness of oral health programs implemented in Korea to promote and prevent dental caries among children.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.213-226
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• 2011

In global supply chain, the scheduling problems of large products such as ships, airplanes, space shuttles, assembled constructions, and/or automobiles are complicated by nature. New scheduling systems are often developed in order to reduce inherent computational complexity. As a result, a problem can be decomposed into small sub-problems, problems that contain independently small scheduling systems integrating into the initial problem. As one of the authors experienced, DAS (Daewoo Shipbuilding Scheduling System) has adopted a two-layered hierarchical architecture. In the hierarchical architecture, individual scheduling systems composed of a high-level dock scheduler, DAS-ERECT and low-level assembly plant schedulers, DAS-PBS, DAS-3DS, DAS-NPS, and DAS-A7 try to search the best schedules under their own constraints. Moreover, the steep growth of communication technology and logistics enables it to introduce distributed multi-nation production plants by which different parts are produced by designated plants. Therefore vertical and lateral coordination among decomposed scheduling systems is necessary. No standard coordination mechanism of multiple scheduling systems exists, even though there are various scheduling systems existing in the area of scheduling research. Previous research regarding the coordination mechanism has mainly focused on external conversation without capacity model. Prior research has heavily focuses on agent-based coordination in the area of agent research. Yet, no scheduling domain has been developed. Previous research regarding the agent-based scheduling has paid its ample attention to internal coordination of scheduling process, a process that has not been efficient. In this study, we suggest a general framework for agent-based coordination of multiple scheduling systems in global supply chain. The purpose of this study was to design a standard coordination mechanism. To do so, we first define an individual scheduling agent responsible for their own plants and a meta-level coordination agent involved with each individual scheduling agent. We then suggest variables and values describing the individual scheduling agent and meta-level coordination agent. These variables and values are represented by Backus-Naur Form. Second, we suggest scheduling agent communication protocols for each scheduling agent topology classified into the system architectures, existence or nonexistence of coordinator, and directions of coordination. If there was a coordinating agent, an individual scheduling agent could communicate with another individual agent indirectly through the coordinator. On the other hand, if there was not any coordinating agent existing, an individual scheduling agent should communicate with another individual agent directly. To apply agent communication language specifically to the scheduling coordination domain, we had to additionally define an inner language, a language that suitably expresses scheduling coordination. A scheduling agent communication language is devised for the communication among agents independent of domain. We adopt three message layers which are ACL layer, scheduling coordination layer, and industry-specific layer. The ACL layer is a domain independent outer language layer. The scheduling coordination layer has terms necessary for scheduling coordination. The industry-specific layer expresses the industry specification. Third, in order to improve the efficiency of communication among scheduling agents and avoid possible infinite loops, we suggest a look-ahead load balancing model which supports to monitor participating agents and to analyze the status of the agents. To build the look-ahead load balancing model, the status of participating agents should be monitored. Most of all, the amount of sharing information should be considered. If complete information is collected, updating and maintenance cost of sharing information will be increasing although the frequency of communication will be decreasing. Therefore the level of detail and updating period of sharing information should be decided contingently. By means of this standard coordination mechanism, we can easily model coordination processes of multiple scheduling systems into supply chain. Finally, we apply this mechanism to shipbuilding domain and develop a prototype system which consists of a dock-scheduling agent, four assembly- plant-scheduling agents, and a meta-level coordination agent. A series of experiments using the real world data are used to empirically examine this mechanism. The results of this study show that the effect of agent-based platform on coordinated scheduling is evident in terms of the number of tardy jobs, tardiness, and makespan.

• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.

• Journal of Preventive Medicine and Public Health
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• v.36 no.2
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• pp.93-100
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• 2003

Objectives : Because shipyard workers are involved with various manufacturing process, they are exposed to many kinds of hazardous materials. Welders especially, are exposed to bisphenol-A (BPA) during the welding and flame cutting of coated steel, This study was conducted to assess the exposure status of the endocrine disrupter based on the job-exposure matrix. The effects of the genetic polymorphism of xenobiotic enzyme metabolisms involved in the metabolism of BPA on the levels of urinary metabolite were investigated. Methods : The study population was recruited from a shipyard company in the f province. A total of 84 shipbuilding workers 47 and 37 in the exposed and control groups, respectively, were recruited for this study. The questionnaire variables included, age, sex, use of personal protective equipment, smoking, drinking and work duration. The urinary metabolite was collected in the afternoon and correction made for the urinary creatinine concentration. The of the CYP1A1, CYP2E1 and UGT1A6 genotypes were investigated using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) methods with the DNA extracted from venous blood. Results : The urinary BPA level in the welders group was significantly higher than in the control group (p<0.05). The urinary BPA concentration with the wild type UGT1A6 was higher than the other UGT1A6 genotypes, but with no statistical significant. From themultiple regression analysis of the urinary BPA, the regression coefficient for job grade was statistically significant (p<0.05). Conclusions : The grade of exposure to BPA affected the urinary BPA concentration was statistically significant. However, the genetic polymorphisms of xenobiotics enzyme metabolism were not statistically significant. Further investigation of the genetic polymorphisms with a larger sample size is needed.

• Journal of Life Science
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• v.25 no.5
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• pp.496-506
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• 2015

This study explored adequate water temperature ranges for maintaining stable water quality in a biofloc- based zero-water exchange culture system. Five experimental tanks with the following temperatures were set up: 10℃, 15℃, 20℃, 25℃, and 30℃. First, a biofloc-based culture system was developed in the experimental tanks; then, the tanks were stocked with goldfish and went without a water exchange for 60 days. Conditions for developing a biofloc-based culture system and stable water quality in low concentrations of inorganic nitrogen compounds at 10℃, 15℃, 20℃, 25℃, and 30℃ were maintained after 17, 26, 43, 68, and 78 days, respectively. Beginning from when the goldfish were stocked in the biofloc-based culture tanks, concentrations of $NH_4{^+}-N$ remained constant and at low levels at 10℃ and 15℃, but they showed a gradual increase at 20℃, 25℃, and 30℃. Concentrations of $NO_2{^-}-N$ and $NO_3{^-}-N$ at 10℃ and 15℃ did not remain at low levels and immediately increased. While $NO_2{^-}-N$ concentrations at above 20℃ remained constant and stable at relatively low levels, $NO_3{^-}-N$ concentrations showed a gradual increase. Conditions of 15℃ and below could not maintain low and stable concentrations of $NO_2{^-}-N$. In the pH range of 4.0 to 6.0, $NH_4{^+}-N$ concentration decreased as the pH rose. However, there was no correlation between pH and $NH_4{^+}-N$ concentration in the pH range of 6.0 to 8.0. These results indicate that pH levels should be kept at pH 6.0 and above to maintain a low and stable concentration of $NH_4{^+}-N$ at above 20℃.

• Journal of the korean academy of Pediatric Dentistry
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• v.46 no.4
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• pp.369-381
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• 2019

The aim of this study was to analyze the changes and improvements in symptoms of sleep-disordered breathing (SDB) using semi-rapid maxillary expansion (SRME) in children with narrow maxilla and SDB symptoms. Subjects were 15 patients with sleep disorder (apnea-hypopnea index, AHI ≥ 1) and narrow maxillary arch between 7 and 9 years of age. Before the SRME was applied, all subjects underwent pediatric sleep questionnaires (PSQ), lateral cephalometry, and portable sleep monitoring before expansion (T0). All subjects were treated with SRME for 2 months, followed by maintenance for the next 3 months. All subjects had undergone PSQ, lateral cephalometry, and portable sleep monitoring after expansion (T1). Adenoidal-nasopharyngeal ratio (ANR), upper airway width and hyoid bone position were measured by lateral cephalometry. The data before and after SRME were statistically analyzed with frequency analysis and Wilcoxon signed rank test. As reported by PSQ, the total PSQ scale was declined significantly from 0.45 (T0) to 0.18 (T1) (p = 0.001). Particularly, snoring, breathing, and inattention hyperactivity were significantly improved (p = 0.001). ANR significantly decreased from 0.63 (T0) to 0.51 (T1) (p = 0.003). After maxillary expansion, only palatopharyngeal airway width was significantly increased (p = 0.035). There was no statistically significant difference in position of hyoid bone after expansion (p = 0.333). From analysis of portable sleep monitoring, changes in sleep characteristics showed a statistically significant decrease in AHI and ODI, and the lowest oxygen desaturation was significantly increased after SRME (p = 0.001, 0.004, 0.023). In conclusion, early diagnosis with questionnaires and portable sleep monitoring is important. Treatment using SRME will improve breathing of children with SDB.

• Journal of the korean academy of Pediatric Dentistry
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• v.48 no.2
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• pp.221-228
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• 2021

The aim of this study was to evaluate the use of easily accessible machine learning application to identify mesiodens, and to compare the ability to identify mesiodens between trained model and human. A total of 1604 panoramic images (805 images with mesiodens, 799 images without mesiodens) of patients aged 5 - 7 years were used for this study. The model used for machine learning was Google's teachable machine. Data set 1 was used to train model and to verify the model. Data set 2 was used to compare the ability between the learning model and human group. As a result of data set 1, the average accuracy of the model was 0.82. After testing data set 2, the accuracy of the model was 0.78. From the resident group and the student group, the accuracy was 0.82, 0.69. This study developed a model for identifying mesiodens using panoramic radiographs of children in primary and early mixed dentition. The classification accuracy of the model was lower than that of the resident group. However, the classification accuracy (0.78) was higher than that of dental students (0.69), so it could be used to assist the diagnosis of mesiodens for non-expert students or general dentists.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.603-611
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• 2020

This study collected and analyzed transportation card data in order to better understand the operation and usage of city buses in Ulsan Metropolitan City in Korea. The analysis used quantitative and qualitative indicators according to the characteristics of the data, and also the categories were classified as general status, operational status, and satisfaction. The existing city bus survey method has limitations in terms of survey scale and in the survey process itself, which incurs various types of errors as well as requiring a lot of time and money to conduct. In particular, the bus means indicators calculated using transportation card data were analyzed to compensate for the shortcomings of the existing operational status survey methods that rely entirely on site surveys. The city bus index calculated by using the transportation card data involves quantitative operation status data related to the user, and this results in the advantage of being able to conduct a complete survey without any data loss in the data collection process. We took the transportation card data from the entire city bus network of Ulsan Metropolitan City on Wednesday April 3, 2019. The data included information about passenger numbers/types, bus types, bus stops, branches, bus operators, transfer information, and so on. From the data analysis, it was found that a total of 234,477 people used the city bus on the one day, of whom 88.6% were adults and 11.4% were students. In addition, the stop with the most passengers boarding and alighting was Industrial Tower (10,861 people), A total of 20,909 passengers got on and off during the peak evening period of 5 PM to 7 PM, and 13,903 passengers got on and off the No. 401 bus route. In addition, the top 26 routes in terms of the highest number of passengers occupied 50% of the total passengers, and the top five bus companies carried more than 70% of passengers, while 62.46% of the total routes carried less than 500 passengers per day. Overall, it can be said that this study has great significance in that it confirmed the possibility of replacing the existing survey method by analyzing city bus use by using transportation card data for Ulsan Metropolitan City. However, due to limitations in the collection of available data, analysis was performed only on one matched data, attempts to analyze time series data were not made, and the scope of analysis was limited because of not considering a methodology for efficiently analyzing large amounts of real-time data.