• Spatial Information Research
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• v.19 no.6
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• pp.101-109
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• 2011

Climate change affects all components of the global environment system and, in turn, all components mutually interact and affect climate change through non-linear feedback processes. It is thus necessary to study the interaction between the climate and the environment, in order to comprehensively understand and predict climate and environment change. However, current relevant systems are limited to particular areas and do not sufficiently support the mutual linking of research studies. Therefore, this study develops prototype a GIS based integrated DB management system for supporting the climate and environment data storage, management and distribution. The integrated DB management system was developed using VB.NET languages and ArcObjects component. First, considering the demands of climate environment experts, the study areas are selected and the methods of data management and utilization were defined. In addition, a location-based GIS DB was created in order to aid in understanding climate change through visual representation. Finally, the integrated DB management system provides an efficient data management and distribution data and it creates synergistic effect on climate and environment study. It also contributes significantly to the comprehensive diagnosis and prediction of climate change and environment systems.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.212-217
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• 2019

Bacterial wilt caused by Ralstonia solanacearum is a major disease that affects tomato plants widely. R. solanacearum is a soil born pathogen which limits the disease control measures. Therefore, breeding of resistant tomato variety to this disease is important. To identify the susceptible variety, degree of disease resistance has to be determined. In this study, micro sap flow sensor is used for accurate prediction of resistant degree. The sensor is designed to measure sap flow and water use in stems of plants. Using this sensor, the susceptibility to bacterial wilt disease can be identified two to three days prior to the onsite of symptoms after innoculation of R. solanacearum. Thus, this find of diagnosis approach can be utilized for the early detection of bacterial wilt disease.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.71-80
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• 2022

In the past, fish diseases were bacterial in aqua farms, but in recent years, the frequency of fish diseases has increased as they have become viral and mixed. Viral diseases in an enclosed space called a aqua farm have a high spread rate, so it is very likely to lead to mass death. Fast identification of fish diseases is important to prevent group death. However, diagnosis of fish diseases requires a high level of expertise and it is difficult to visually check the condition of fish every time. In order to prevent the spread of the disease, an automatic identification system of diseases or fish is needed. In this paper, in order to improve the performance of the disease identification system of Paralichthys olivaceus based on deep learning, the existing pre-processing method is compared and tested. Target diseases were selected from three most frequent diseases such as Scutica, Vibrio, and Lymphocystis in Paralichthys olivaceus. The RGB, HLS, HSV, LAB, LUV, XYZ, and YCRCV were used as image pre-processing methods. As a result of the experiment, HLS was able to get the best results than using general RGB. It is expected that the fish disease identification system can be advanced by improving the recognition rate of diseases in a simple way.

• The Mathematical Education
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• v.62 no.3
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• pp.303-326
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• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.399-408
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• 2022

The purpose of this study was to compare the usefulness of the lipid ratio indicators for the diagnosis of metabolic syndrome in the elderly aged 65 years or older. From January 2018 to December 2020, 1,464 people aged 65 years or older who underwent a health checkup at a general hospital in Seoul were included. Lipid ratio indicators were measured through blood tests. The prevalence of metabolic syndrome according to the quartiles of the lipid ratio index was confirmed by logistic regression analysis. In addition, the metabolic syndrome predictive ability and cutoff value of the lipid ratio indices were estimated with the receiver operating characteristic(ROC) curve. The correlation between atherogenic index of plasma(AIP) and waist circumference was the highest in both men and women(r=0.278, p<0.001 vs r=0.252, p<0.001). As for the lipid ratio indices, the incidence of metabolic syndrome was higher in the fourth quartile than in the first quartile. The area under the ROC curve(AUC) value of AIP was higher at 0.826(95% CI=0.799-0.850) and 0.852(95% CI=0.820-0.881) for men and women, respectively, compared to other lipid ratio indicators, and the optimal cutoff values for both men and women was 0.44(p<0.001). Therefore, the AIP among the lipid ratio indicators was found to be the most useful index for diagnosing metabolic syndrome in the elderly aged 65 years or older.

• Convergence Security Journal
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• v.22 no.4
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• pp.85-97
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• 2022

With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

• Tuberculosis and Respiratory Diseases
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• v.86 no.4
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• pp.284-293
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• 2023

Background: Attitudes towards smoking, lung cancer screening, and perceived risk of lung cancer have not been widely studied in Malaysia. The primary objective of this study was to describe the factors affecting the willingness of high-risk current smokers and ex-smokers to undergo low-dose computed tomography (LDCT) screening for lung cancer. Methods: A prospective, cross-sectional questionnaire study was conducted in current smokers or ex-smokers aged between 55 and 80 years at three hospitals in Kota Kinabalu, Sabah, Malaysia. The questionnaire recorded the following parameters: perceived lung cancer risk; Prostate Lung Colon Ovarian Cancer 2012 risk prediction model excluding race and ethnicity predictor (PLCO_m2012norace); demographic characteristics; psychosocial characteristics; and attitudes towards lung cancer and lung cancer screening. Results: A vast majority of the 95 respondents (94.7%) indicated their willingness to undergo screening. Stigma of lung cancer, low levels of knowledge about lung cancer symptoms, concerns about financial constraints, and a preference for traditional medication were still prevalent among the respondents, and they may represent potential barriers to lung cancer screening uptake. A desire to have an early diagnosis (odds ratio [OR], 11.33; 95% confidence interval [CI], 1.53 to 84.05; p=0.02), perceived time constraints (OR, 3.94; 95% CI, 1.32 to 11.73; p=0.01), and proximity of LDCT screening facilities (OR, 14.33; 95% CI, 1.84 to 111.4; p=0.01) had significantly higher odds of willingness to undergo screening. Conclusion: Although high-risk current smokers and ex-smokers are likely to undergo screening for lung cancer, several psychosocial barriers persist. The results of this study may guide the policymakers and clinicians regarding the need to improve lung cancer awareness in our population.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.102-110
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• 2023

PSC-I girder bridges constitute the largest proportion among highway bridges in Korea. According to the precision safety diagnosis data for the past 10 years, approximately 41.3% of the PSC-I bridges have been graded as C. Furthermore, with the increase in the aging of bridges, preemptive management is becoming more important. Damage and deterioration to the deck and girder with a long replacement cylce can have considerable impacts on the service and deterioration of a bridge. In addition, the high rate of device damages, including expansion joints and bearings, necessitates an investigation into the influence of the device damage in the structural members of the bridge. Therefore, this study defined representative PSC-I girder bridges with single and multiple spans to evaluate heterogeneous damages that incorporate the damage of the bridge member and device with the deterioration of the deck. The heterogeneous damages increased a crack area ratio compared to the individual single damage. For the single-span bridge, the occurrence of bearing damage leads to the spread of crack distribution in the girder, and in the case of multi-span bridges, expansion joint damage leads to the spread of crack distribution in the deck. The research underscores that bridge devices, when damaged, can cause subsequent secondary damage due to improper repair and replacement, which emphasizes the need for continuous observation and responsive action to the damages of the main devices.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1057-1065
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• 2023

Non-invasive liver fibrosis diagnosis is crucial for patients with chronic liver diseases. Many patients cannot undergo liver tissue biopsy, so predicting the degree of liver fibrosis early through meaningful methods can reduce complications related to chronic liver diseases, such as liver cell carcinoma and cirrhosis. This study compared and analyzed the quantitative measurement of liver fibrosis using shear wave elastography in conjunction with liver ultrasound findings and their associations with serum biomarkers (p<0.05). The results showed that the shear wave elastography measurement in the normal group was 4.55 ± 0.69 kPa, while the abnormal contrast group with echogenic patterns had a measurement of 8.27 ± 1.83 kPa. The hepatitis B carrier group exhibited higher shear wave elastography measurements, and among serum biomarkers, AST, ALT, GGT, and PT showed statistically significant positive correlations with fibrosis severity according to SWE categories (p<0.05), while ALP and TB did not demonstrate statistically significant differences (p=0.163, p=0.567). Conversely, Albumin and PLT showed significant negative correlations (p<0.05). Clinically, utilizing shear wave elastography measurements through liver ultrasound in the tracking and repeat testing of liver fibrosis in chronic hepatitis B patients without cirrhosis can assist in achieving more objective diagnoses among healthcare providers.

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.681-689
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• 2023

Objective : Subarachnoid hemorrhage (SAH) is a condition characterized by bleeding in the subarachnoid space, often resulting from the rupture of a cerebral aneurysm. Delayed cerebral ischemia caused by vasospasm is a significant cause of mortality and morbidity in SAH patients, and inflammatory markers such as systemic inflammatory response index (SIRI), systemic inflammatory index (SII), neutrophil-to-lymphocyte ratio (NLR), and derived NLR (dNLR) have shown potential in predicting clinical vasospasm and outcomes in SAH patients. This article aims to investigate the relationship between inflammatory markers and cerebral vasospasm after aneurysmatic SAH (aSAH) and evaluate the predictive value of various indices, including SIRI, SII, NLR, and dNLR, in predicting clinical vasospasm. Methods : A retrospective analysis was performed on a cohort of 96 patients who met the inclusion criteria out of a total of 139 patients admitted Trakya University Hospital with a confirmed diagnosis of aSAH between January 2013 and December 2021. Diagnostic procedures, neurological examinations, and laboratory tests were performed to assess the patients' condition. The Student's t-test compared age variables, while the chi-square test compared categorical variables between the non-vasospasm (NVS) and vasospasm (VS) groups. Receiver operating characteristic (ROC) curve analyses were used to evaluate the diagnostic accuracy of laboratory parameters, calculating the area under the ROC curve, cut-off values, sensitivity, and specificity. A significance level of p<0.05 was considered statistically significant. Results : The study included 96 patients divided into two groups : NVS and VS. Various laboratory parameters, such as NLR, SII, and dNLR, were measured daily for 15 days, and statistically significant differences were found in NLR on 7 days, with specific cut-off values identified for each day. SII showed a significant difference on day 9, while dNLR had significant differences on days 2, 4, and 9. Graphs depicting the values of these markers for each day are provided. Conclusion : Neuroinflammatory biomarkers, when used alongside radiology and scoring scales, can aid in predicting prognosis, determining severity and treatment decisions for aSAH, and further studies with larger patient groups are needed to gain more insights.