• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1437-1444
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• 2020

With the development of computer vision systems, many advances have been made in the fields of surveillance, biometrics, medical imaging, and autonomous driving. In the field of autonomous driving, in particular, the object detection technique using deep learning are widely used, and the paved road detection is a particularly crucial problem. Unlike the ROI detection algorithm used in general object detection, the structure of paved road in the image is heterogeneous, so the ROI-based object recognition architecture is not available. In this paper, we propose a deep neural network architecture for atypical paved road detection using Semantic segmentation network. In addition, we introduce the multi-scale semantic segmentation network, which is a network architecture specialized to the paved road detection. We demonstrate that the performance is significantly improved by the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1351-1356
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• 2019

The purpose of this study is to investigate the effect of personal factors and community factors on the quality of life based on the presence of chronic patients based on the Big Data Platform. As a method of study, second data of 2017 community health survey and Statistics Korea by City·Gun·Gu public office were used and a multi-level analysis was conducted after separating EQ-5D index, individual factor and community factor. As a result, men, age, education level, monthly household income, having economic activity, the number of sports infrastructure were positively associated with the quality of life, and subjective health not good, extremely perceived stress were negatively associated with the quality of life. Research will continue to provide a platform independent of hardware that can utilize the cloud and open source for medical big data analysis in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.795-801
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• 2020

In the event of a fatal infectious disease in the country, it is very important that the government respond quickly and prevent the secondary infection of the people to prevent the subsequent spread of damage. However, in order to detect infectious diseases in existing medical institutions, and to reach the KCDCP(Korea Centers for Disease Control and Prevention) a total of four steps must be taken. In this paper, we simplifies the existing reporting process using the open blockchain. In addition, not only infectious disease related organizations share infectious disease information on the blockchain, but also grant access to the blockchain to ordinary citizens. By sharing information quickly and transparently revealing the process, we can add credibility to the response to the outbreak and official announcements. The public can also build efficient next-generation defense systems by checking information on the blockchain to prevent secondary infections.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1179-1187
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• 2019

In today's technology environment, most big data-based applications and solutions are based on real-time processing of streaming data. Real-time processing and analysis of big data streams plays an important role in the development of big data-based applications and solutions. In particular, in the maritime data processing environment, the necessity of developing a technology capable of rapidly processing and analyzing a large amount of real-time data due to the explosion of data is accelerating. Therefore, this paper analyzes the characteristics of NiFi, Kafka, and Druid as suitable open source among various open data technologies for processing big data, and provides the latest information on external linkage necessary for maritime service analysis in Korean e-Navigation service. To this end, we will lay the foundation for applying open data framework technology for real-time data processing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1298-1304
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• 2019

Since the 9·11 terror attack in 2001, the Maritime Logistics Security System has been strengthened and required X-ray image for every imported cargos from manufacturing countries to United States. For scanning cargos, the container inspection systems use high energy X-rays for examination of contents of a container to check the nuclear, explosive, dangerous and illegal materials. Nowadays, the X-ray cargo scanners are established and used by global technologies for inspection of suspected cargos in the customs agency but these technologies have not been localized and developed sufficiently. In this paper, we propose the X-ray array detector system which is a core component of the container scanning system. For implementation of X-ray array detector, the analog and digital signal processing units are fabricated with integrated hardware, FPGA logics and GUI software for real-time X-ray images. The implemented system is superior in terms of resolution and power consumption compared to the existing products currently used in ports.

• Korea Journal of Hospital Management
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• v.25 no.4
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• pp.1-12
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• 2020

During the COVID-19 pandemic, most of the western countries with advanced medical technology failed to contain coronavirus. This fact triggered our research question of what factors influence the clinical outcomes like infection rates and case mortality rates. This study aims to identify the determinants of COVID-19 related infection rates and case mortality rates. We considered three sets of independent variables: 1) socio-demographic characteristics; 2) cultural characteristics; 3) healthcare system characteristics. For the analysis, we created an international dataset from diverse sources like World Bank, Worldometers, Hofstede Insight, GHS index etc. The COVID-19 related statistics were retrieved from Aug. 1. Total cases are from 95 countries. We used hierarchical regression method to examine the linear relationship among variables. We found that obesity, uncertainty avoidance, hospital beds per 1,000 made a significant influence on the standardized COVID-19 infection rates. The countries with higher BMI score or higher uncertainty avoidance showed higher infection rates. The standardized COVID-19 infection rates were inversely related to hospital beds per 1,000. In the analysis on the standardized COVID-19 case mortality rates, we found that two cultural characteristics(e.g., individualism, uncertainty avoidance) showed statistically significant influence on the case mortality rates. The healthcare system characteristics did not show any statistically significant relationship with the case mortality rates. The cultural characteristics turn out to be significant factors influencing the clinical outcomes during COVID-19 pandemic. The results imply that the persuasive communication is important to trigger the public commitment to follow preventive measures. The strategy to keep the hospital surge capacity needs to be developed.

• Journal of Korean Clinical Nursing Research
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• v.27 no.2
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• pp.199-209
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• 2021

Purpose: This study was conducted to investigate the nursing needs and workload of nurses according to nursing dependency for effective placement of nursing staff in the emergency department (ED). Methods: In June 2020, 256 adult patients who visited the ED were classified as two groups, suspected COVID-19 patients and general patients. The participants'electronic medical records were analyzed using descriptive statistics, t-test, 𝑥²-test, and Fisher's exact test using the SPSS. Results: The patient dependence score showed a significant difference between the two groups, with an average of 13.99±1.85 for the suspected COVID-19 patient group and 10.58±2.10 for the general patient group (t=12.42, p<.001). There were statistically significant differences in communication (t=3.28, p=.001), mobility (t=3.29, p=.001), nutrition, elimination, and personal care (t=7.34, p<.001) among the six domains of nursing dependency. In the domains of environment, safety, health, and social needs, the dependency score was 3 for all suspected COVID-19 patients and 1 for all general patients. Conclusion: The results of this study confirmed that infection control activities of emergency patients who need isolation affect the patients' nursing dependency on nursing care.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.145-150
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• 2021

Patients with Pressure injuries (PIs) may have pain and discomfort, which results in poorer patient outcomes and additional cost for treatment. This study was a part of larger research project that aimed at prediction modeling using a big data. The purpose of this study were to describe the characteristics of patients with PI in critical care; and to explore comorbidity and diagnostic and interventive procedures that have been done for patients in critical care. This is a secondary data analysis. Data were retrieved from a large clinical database, MIMIC-III Clinical database. The number of unique patients with PI was 2,286 in total. Approximately 60% were male and 68.4% were White. Among the patients, 9.9% were dead. In term of discharge disposition, 56.2% (33.9% Home, 22.3% Home Health Care) where as 32.3% were transferred to another institutions. The rest of them were hospice (0.8%), left against medical advice (0.7%), and others (0.2%). The top three most frequently co-existing kinds of diseases were Hypertension, not otherwise specified (NOS), congestive heart failure NOS, and Acute kidney failure NOS. The number of patients with PI who have one or more procedures was 2,169 (94.9%). The number of unique procedures was 981. The top three most frequent procedures were 'Venous catheterization, not elsewhere classified,' and 'Enteral infusion of concentrated nutritional substances.' Patient with a greater number of comorbid conditions were likely to have longer length of ICU stay (r=.452, p<.001). In addition, patient with a greater number of procedures that were performed during the admission were strongly tend to stay longer in hospital (r=.729, p<.001). Therefore, prospective studies focusing on comorbidity; and diagnostic and preventive procedures are needed in the prediction modeling of pressure injury development in ICU patients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.526-532
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• 2022

With the development of IoT technology, image processing is being utilized in various fields such as image analysis, image recognition, medical industry, and factory automation. Noise is generated in image data from causes such as defect in transmission line. Image noise must be removed because it damages the performance of the image processing application program. Salt and Pepper noise is a representative type of image noise, and various studies have been conducted to remove Salt and Pepper noise. Widely known methods include A-TMF, AFMF, and SDWF. However, as the noise density increases, the performance deteriorates. Thus, this paper proposes an algorithm that performs filtering using a fuzzy logic weight mask only in case of noise after noise determination. In order to prove the noise removal performance of the proposed algorithm, an experiment was performed on images with 10% to 90% noise added and the PSNR was compared.

• Molecules and Cells
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• v.44 no.11
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• pp.784-794
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• 2021

Leiomyosarcoma (LMS) is a mesenchymal malignancy with a complex karyotype. Despite accumulated evidence, the factors contributing to the development of LMS are unclear. Here, we investigated the role of tight-junction protein 1 (TJP1), a membrane-associated intercellular barrier protein during the development of LMS and the tumor microenvironment. We orthotopically transplanted SK-LMS-1 cells and their derivatives in terms of TJP1 expression by intramuscular injection, such as SK-LMS-1 Sh-Control cells and SK-LMS-1 Sh-TJP1. We observed robust tumor growth in mice transplanted with LMS cell lines expressing TJP1 while no tumor mass was found in mice transplanted with SK-LMS-1 Sh-TJP1 cells with silenced TJP1 expression. Tissues from mice were stained and further analyzed to clarify the effects of TJP1 expression on tumor development and the tumor microenvironment. To identify the TJP1-dependent factors important in the development of LMS, genes with altered expression were selected in SK-LMS-1 cells such as cyclinD1, CSF1 and so on. The top 10% of highly expressed genes in LMS tissues were obtained from public databases. Further analysis revealed two clusters related to cell proliferation and the tumor microenvironment. Furthermore, integrated analyses of the gene expression networks revealed correlations among TJP1, CSF1 and CTLA4 at the mRNA level, suggesting a possible role for TJP1 in the immune environment. Taken together, these results imply that TJP1 contributes to the development of sarcoma by proliferation through modulating cell-cell aggregation and communication through cytokines in the tumor microenvironment and might be a beneficial therapeutic target.