• Journal of Environmental Health Sciences
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• v.45 no.2
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• pp.192-202
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• 2019

Objectives: According to the central limit theorem, the samples in population might be considered to follow normal distribution if a large number of samples are available. Once we assume that toxicity dataset follow normal distribution, we can treat and process data statistically to calculate genus or species mean value with standard deviation. However, little is known and only limited studies are conducted to investigate whether toxicity dataset follows normal distribution or not. Therefore, the purpose of study is to evaluate the generally accepted normality hypothesis of aquatic toxicity dataset Methods: We selected the 8 chemicals, which consist of 4 organic and 4 inorganic chemical compounds considering data availability for the development of species sensitivity distribution. Toxicity data were collected at the US EPA ECOTOX Knowledgebase by simple search with target chemicals. Toxicity data were re-arranged to a proper format based on the endpoint and test duration, where we conducted normality test according to the Shapiro-Wilk test. Also we investigated the degree of normality by simple log transformation of toxicity data Results: Despite of the central limit theorem, only one large dataset (n>25) follow normal distribution out of 25 large dataset. By log transforming, more 7 large dataset show normality. As a result of normality test on small dataset (n<25), log transformation of toxicity value generally increases normality. Both organic and inorganic chemicals show normality growth for 26 species and 30 species, respectively. Those 56 species shows normality growth by log transformation in the taxonomic groups such as amphibian (1), crustacean (21), fish (22), insect (5), rotifer (2), and worm (5). In contrast, mollusca shows normality decrease at 1 species out of 23 that originally show normality. Conclusions: The normality of large toxicity dataset was not always satisfactory to the central limit theorem. Normality of those data could be improved through log transformation. Therefore, care should be taken when using toxicity data to induce, for example, mean value for risk assessment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.1-15
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• 2019

The purpose of this study is to analyze the relationship between entrepreneurship and entrepreneurial intention. This relationship has been conceptually addressed in many previous studies and has been empirically tested. However, this study is different from the previous studies in the following four points. First, we measured entrepreneurial intention by manipulating launching a start-up as a relative concept for employment, which is consistent with the conceptual definition of entrepreneurial intention (i.e. entrepreneurial decision making in the process of career choice). Second, it is distinguished from previous researches in that it uses the question of preference for "action" with regard to job choice. Third, we expanded the opportunity for discussion using the youth panel data of the Korea Employment Information Service. Fourth, the altruistic purpose is included in the category of entrepreneurship. Empirical results showed that intentions of entrepreneurship were stronger when the need for achievement was intense, internal control tendency was intended, risk-taking propensity was sturdy, and autonomous tendency was high. However, innovation and aggressiveness are not statistically related to entrepreneurial intention. On the other hand, the altruistic tendency was found to have a negative correlation with entrepreneurial intention. The results of this study can provide meaningful implications for both private sector investors and government policy makers.

• Journal of Hospice and Palliative Care
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• v.21 no.4
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• pp.158-162
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• 2018

Breast cancer related lymphedema (BCRL) is one of the most intractable complications after surgery. Patients suffer from physical impairment, as well as psychological depression. Moreover, a recent study revealed that cellulitis significantly increased the risk of BCRL, and cellulitis has been suggested as a risk factor of BCRL development. We describe a patient treated with stellate ganglion blocks (SGBs) without steroid for relief of symptoms and reduction of the arm circumference of breast cancer-related infectious lymphedema in a month. We measured the arm circumference at four locations; 10 cm and 5 cm above and below the elbow crease, numeric rating scale (NRS) score, lymphedema and breast cancer questionnaire (LBCQ) score on every visit to the pain clinic. A serial decrease of the arm circumference and pain score were observed after second injection. In the middle of the process, cellulitis recurred, we performed successive SGBs to treat infectious lymphedema. The patient was satisfied with the relieved pain and swelling, especially with improved shoulder range of motion as it contributes to better quality of life. This case describes the effects of SGB for infectious BCRL patients. SGB could be an alternative or ancillary treatment for infectious BCRL patients.

• The Journal of Society for e-Business Studies
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• v.24 no.1
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• pp.121-137
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• 2019

De-identification is a method by which the remaining information can not be referred to a specific individual by removing the personal information from the data set. As a result, de-identification can lower the exposure risk of personal information that may occur in the process of collecting, processing, storing and distributing information. Although there have been many studies in de-identification algorithms, protection models, and etc., most of them are limited to structured data, and there are relatively few considerations on de-identification of unstructured data. Especially, in the medical field where the unstructured text is frequently used, many people simply remove all personally identifiable information in order to lower the exposure risk of personal information, while admitting the fact that the data utility is lowered accordingly. This study proposes a new method to perform de-identification by applying the k-anonymity protection model targeting unstructured text in the medical field in which de-identification is mandatory because privacy protection issues are more critical in comparison to other fields. Also, the goal of this study is to propose a new utility metric so that people can comprehend de-identified data set utility intuitively. Therefore, if the result of this research is applied to various industrial fields where unstructured text is used, we expect that we can increase the utility of the unstructured text which contains personal information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.599-606
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• 2019

Most facilities that manufacture products made from the hazardous materials operate at high temperatures and pressures. Therefore, there is a risk of fire explosion. In particular, an explosion accident is a major risk factor for facilities with hazardous materials, such as oil, chemical, and gas. Propylene is often used in sites producing basic raw materials and synthetic materials by addition polymerization at petrochemical plants. To prevent an explosion in the business using propylene, the explosion range with the oxygen concentration was calculated according to the changes in temperature and pressure using an inert gas, carbon dioxide. In these measurements, the temperature was $25^{\circ}C$, $100^{\circ}C$, and $200^{\circ}C$ and the amount of carbon dioxide in the container was $1.0kgf/cm^2.G$, $1.5kgf/cm^2.G$, $2.0kgf/cm^2.G$, and $2.5kgf/cm^2.G$. The explosion limit was related to temperature, pressure, and oxygen concentration. The minimum oxygen concentration for an explosion decreased with increasing temperature and pressure. The range of explosion narrowed with decreasing oxygen concentration. In addition, no explosion occurred at concentrations below the minimum oxygen concentration, even with steam and an ignition source of propylene.

• Korean Journal of Psychosomatic Medicine
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• v.28 no.2
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• pp.99-107
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• 2020

Fibromyalgia is a disorder characterized by the core symptom of chronic widespread pain, along with fatigue, sleep disturbances, mood changes, and cognitive difficulties. The etiology of fibromyalgia involves a combination of biological factors, such as genetic vulnerability, alterations in pain processing and stress response system ; psychological factors, such as anxiety, depression, anger, and perceived stress ; environmental factors, such as infections, febrile diseases, and trauma. Central sensitization, which is amplified in the process of sensory stimulation, has been emphasized as a key etiological factor, as supported by enhanced wind-up, delayed aftersensation, decreased nociceptive flexion reflex threshold and functional imaging studies. Several guidelines recommend that a multimodal approach be used to treat fibromyalgia, including both pharmacological and non-pharmacological treatments, tailored to each individual, and that clinicians should provide an intellectual framework through sufficient education and emphasis on the importance of self-management. The prevalence of mood disorders, anxiety disorders, and other psychiatric problems is 7-9 times higher in patients with fibromyalgia than in the general population ; moreover, the association between fibromyalgia and certain psychopathologies or sleep problems has also been suggested. Since psychiatric problems, with shared vulnerabilities and risk factors, interact with fibromyalgia bidirectionally and also affect the disease course, an integrated management approach is needed to determine the risk of comorbidities.

• Geomechanics and Engineering
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• v.28 no.3
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• pp.299-311
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• 2022

Water-resisting key stratum (WKS) between coal seams is an important barrier that prevents water inrush from goaf in roof under multi-seam mining. The occurrence of water inrush can be evaluated effectively by analyzing the fracture of WKS in multi-seam mining. A "long beam" water inrush mechanical model was established using the multi-seam mining of No. 2+3 and No. 8 coal seams in Xiqu Mine as the research basis. The model comprehensively considers the pressure from goaf, the gravity of overburden rock, the gravity of accumulated water, and the constraint conditions. The stress distribution expression of the WKS was obtained under different mining distances in No. 8 coal seam. The criterion of breakage at any point of the WKS was obtained by introducing linear Mohr strength theory. By using the mechanical model, the fracture of the WKS in Xiqu Mine was examined and its breaking position was calculated. And the risk of water inrush was also evaluated. Moreover, breaking process of the WKS was reproduced with Flac3D numerical software, and was analyzed with on-site microseismic monitoring data. The results showed that when the coal face of No. 8 coal seam in Xiqu Mine advances to about 80 m ~ 100 m, the WKS is stretched and broken at the position of 60 m ~ 70 m away from the open-off cut, increasing the risk of water inrush from goaf in roof. This finding matched the result of microseismic analysis, confirming the reliability of the water inrush mechanical model. This study therefore provides a theoretical basis for the prevention of water inrush from goaf in roof in Xiqu Mine. It also provides a method for evaluating and monitoring water inrush from goaf in roof.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.85-100
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• 2022

Purpose: This study is aimed to examine the association between initial enteral nutrition (EN) and the clinical prognosis among patients with severe and multiple traumatic injuries, and to investigate whether this association is modified by the patients' catabolic status. Methods: This was a retrospective study of 302 adult patients with severe and multiple traumatic injuries admitted between January 2017 and September 2020 at Ajou University hospital in Suwon, Korea. The initial nutritional support by EN and parenteral nutrition were monitored up to day 7 after admission. Patients were classified into "No", "Low", and "High" EN groups according to the level of initial EN. Multivariable-adjusted logistic regression and linear regression models were used to estimate the association of the initial EN levels at hospital admission with the risk of mortality, morbidities, and levels of nutrition-associated biochemical markers. Results: High EN support was associated with reduced mortality (odds ratio, 0.07; 95% confidence interval [CI], 0.02, 0.32) and lower levels of C-reactive protein (β, -0.22; 95% CI, -8.66, 1.48), but longer stay in the intensive care unit (β, 0.19; 95% CI, 1.82, 11.32). In analyses stratified by catabolic status, there were fewer incidences of hospital-acquired infections with increasing EN levels in the moderate or higher nitrogen balance group than in the mild nitrogen balance group. Conclusion: Our observation of the inverse association between levels of initial EN administration with mortality risk and inflammatory markers may indicate the possible benefits of active EN administration to the recovery process of severe and multiple trauma patients. Further studies are warranted on whether the catabolic status modifies the association between the initial EN and prognosis.

• Safety and Health at Work
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• v.13 no.2
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• pp.163-169
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• 2022

Background: It is estimated that about 13 million artisanal and small-scale miners carry out their activities under harsh, precarious, unfriendly, and risky conditions. Yet, our understanding of the extent to which these workers use personal protective equipment (PPE) and navigate through the various risks and hazards they face is still limited. This article has two main objectives. First, it explores the extent of usage of PPE among artisanal and small-scale miners for the prevention of hazards and risks. Second, it examines the coping strategies used by these miners as a response to experiences of occupational injuries and risks Methods: A cross-sectional survey of small-scale miners was conducted in six communities across three districts in Ghana, West Africa. The mixed methods approach was adopted. A total of 148 small-scale miners participated in the study. Six focus group discussions (FGDs) were held across the six communities. The data were analysed using descriptive statistics. Chi-square tests were used to analyse the relationship between some socio-demographic characteristics (sex, age, and educational background) and the usage of PPE. Open-ended questions and responses from FGDs were analysed based on the content and verbatim quotations from miners. Results: Findings suggest that 78% of the miners interviewed do not use the appropriate PPE citing reasons such as cost, and their personal discomfort associated with use of PPE. There was no significant relationship between socio-demographic characteristics (i.e., sex, age, education and major mining activity) and the usage of PPE. The study further revealed four main coping strategies used by miners to handle the risks. These are rest, taking unprescribed medication and hard drugs, registration with health insurance scheme and savings and investments. Conclusion: This study shows that very few artisanal miners use PPE despite the significant hazards and risks to which they are exposed. The study recommends to the government to put in place measures to ensure that miners adhere to health and safety regulations before undertaking mining activities. This means that health and safety plans and use of PPE should be linked to the license acquisition process for miners.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.