• The Korean Society of Law and Medicine
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• v.17 no.1
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• pp.139-168
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• 2016

Two alternative dispute resolutions for medical dispute have been operated under the States of German Medical Associations. The first is the medical mediation committee of North german area, the other is the advisory committee on medical errors in North-Rhine area. The former has focused on the mediation itself, the latter commission has focused on the expert review itself whether the physician has maintained reasonable care in diagnosis and treatment. Even though these organizations have maintained under the medical associations, to maintain the neutrality on legal and medical decision, the North German mediation committee is composed of a lawyer and a medicine doctor respectively and North-Rhine advisory committee has a lawyer chair person and four medicine doctors. The main difference of Korean Medical Dispute Mediation Agency in respect from the german system is that expert review is subordinated to the mediation process. The neutrality of expert review is suspected from the medicine doctors. The neytrality and the efficiency should be improved to treat the medical disputes. To do so, lawyer and medicine doctor work together in mediation process and lawyer should manage the expert review process but not involved. Mediation process and expert review should be checked and balanced, and they could be developed as a separated process itself.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.2
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• pp.158-162
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• 2005

The objective of this study was to assess the assimilable organic carbon (AOC) in processing water, a measurement of biostability, at several stages of a full-scale nanofiltration (NF) water treatment plant. The NF membrane plant investigated was a $45,400\;m^3$/day (12 mgd) water softening facility at Plantation City in southern Florida, which utilized an organic rich groundwater (dissolved organic carbon (DOC) = 17.6 mg/L) originated from a surficial aquifer. The average AOC concentration of raw feed water was estimated at 158 g/L acetate-C. After pretreatment(acid and antiscalant addition), AOC levels increased by 12.7%, suggesting that pretreatment chemicals used to control scaling may deteriorate feed water biostability. The results also demonstrated that nanofiltration was capable of effectively removing 63.4% of AOC and 94.8% of DOC from the raw water. AOC rejection in stage 1 (${\approx}\;68%$) was slightly higher than that of stage 2 (${\approx}\;58%$) indicating that AOC was removed less at the solution environment (i.e. low pH, high ionic strength and high hardness), which was often created in the $2^{nd}$ stage of full-scale membrane plants due to pretreatment (acid addition) and high recovery operation.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.7
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• pp.776-781
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• 2006

Perchlorate ion($ClO_4^-$), which is present in the solid propellant for rocket, herbicide and some fertilizers. Perchlorate inhibits iodide uptake by the human thyroid gland. Impairment of thyroid function in expectant mothers may impact the fetus and result in effects including cerebral palsy, give rise to thyroid gland cancer. The US EPA(Environmental Protection Agency) adopted a reference dose(RfD) for perchlorate 0.0007 mg/kg-day, and this guidance lead to a Drinking Water Equivalent Level(DWEL) of 24.5 ${\mu}g/L$. The studies about perchlorate are actively performed in foreign countries, especially in USA but there is no study which surveyed the perchlorate contamination in Korea. Therefore, this study was done to investigate perchlorate contamination in Nak-dong river and tap water. The perchlorate was detected in Nakdong river and ranged from ND to 278.4 ${\mu}g/L$. The highest concentration was observed in Kumichon. The perchlorate concentration was decreased with the down stream of Nakdong river. The perchlorate concentration in tap water was varied with the cities and the concentration levels were $ND{\sim}34.1$ ppb. The highest perchlorate concentration was observed in DalsuGoo in Daegu and the similar concentration($9{\sim}11$ ${\mu}g/L$) was detected in most of the districts in Busan. The result of this study suggests that there is a perchlorate source near the Nakdong river and the urgent policy is needed to control perchlorate for the cities which are supplied from Nakdong river as for their tap water.

• Membrane Journal
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• v.15 no.4
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• pp.297-309
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• 2005

As a number of potential endocrine disrupting compounds (EDCs) are released into the environment, recently growing attention has been drawn to them. Therefore sensitive and reliable analytical methods are essential to monitor those compounds. In this study, complementary CC-MS and LC-MS were employed to analyze the endocrine disrupters, and the results of two methods were compared for di(2-ethylhexyl)phthalate (DEHP), benzylbutylphthalate (BBP), pentachlorophenol (PCP), and 4,4'-Isopropylidenediphenol (Bisphenol-A, or BPA). The results indicate that it was possible to lower the detection limits of EDCs by LC-MS. Also, LC-MS enabled to identify the EDCs as almost intact molecules. Furthermore, this study presented a nanofiltration membrane (MWCO 250) and a ultrafiltration membrane (MWCO 1,000) filtration system as methods far removing EDCs from drinking water containing $\gamma$-BHC, p,p'-DDE, BBP, p,p'-DDT, DEHP, PCP, and BPA. Cross-flow type nanofiltrations showed $100\%$ removal of EDCs, and the result implies that MWCO 250 nanofilter was sufficient for treatment of EDCs. The ratio of permeate flux to mass transfer coefficient of nanofiltration, high flux ultrafiltration, and low flux ultrafiltration with ultrapure water were 0.67, 3.4, and 0.44, respectively. It was found that nanofiltration and low flux ultrafiltration were operated at a diffusion dominant condition, and the high flux ultrafiltration was operated at a convection dominant condition. Furthermore, a diffusion dominant process attained reasonable rejection of EDCs. The removal in the ultrafiltration was depending on the molecular weight of an EDC, and the filtration was governed by diffusion-dominant hydrodynamic conditions.

• Korean Journal of Community Nutrition
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• v.26 no.4
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• pp.280-295
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• 2021

Objectives: This study aimed to examine the characteristics of patients according to their nutritional status as assessed by five nutritional screening tools: Patient-Generated Subjective Global Assessment (PG-SGA), NUTRISCORE, Nutritional Risk Index (NRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) and to compare the agreement, sensitivity, and specificity of these tools. Methods: A total of 952 gastric cancer patients who underwent gastrectomy and chemotherapy from January 2009 to December 2012 at the Samsung Medical Center were included. We categorized patients into malnourished and normal according to the five nutritional screening tools 1 month after surgery and compared their characteristics. We also calculated the Spearman partial correlation, Cohen's Kappa coefficient, the area under the curve (AUC), sensitivity, and specificity of each pair of screening tools. Results: We observed 86.24% malnutrition based on the PG-SGA and 85.82% based on the NUTRISCORE among gastric cancer patients in our study. When we applied NRI or CONUT, however, the malnutrition levels were less than 30%. Patients with malnutrition as assessed by the PG-SGA, NUTRISCORE, or NRI had lower intakes of energy and protein compared to normal patients. When NRI, PNI, or CONUT were used to identify malnutrition, lower levels of albumin, hemoglobin, total lymphocyte count, total cholesterol, and longer postoperative hospital stays were observed among patients with malnutrition compared to those without malnutrition. We found relatively high agreement between PG-SGA and NUTRISCORE; sensitivity was 90.86% and AUC was 0.78. When we compared NRI and PNI, sensitivity was 99.64% and AUC was 0.97. AUC ranged from 0.50 to 0.67 for comparisons between CONUT and each of the other nutritional screening tools. Conclusions: Our study suggests that PG-SGA and NRI have a relatively high agreement with the NUTRISCORE and PNI, respectively. Further cohort studies are needed to examine whether the nutritional status assessed by PG-SGA, NUTRISCORE, NRI, PNI, and CONUT predicts the gastric cancer prognosis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

• Korean Journal of Community Nutrition
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• v.27 no.3
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• pp.205-222
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• 2022

Objectives: This study examined the characteristics of patients according to nutritional status assessed by five nutritional screening tools: Patient-Generated Subjective Global Assessment (PG-SGA), NUTRISCORE, Nutritional Risk Index (NRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) and to compare the agreement, sensitivity, and specificity of these tools. Methods: A total of 952 gastric cancer patients who underwent gastrectomy and chemotherapy from January 2009 to December 2012 were included. The patients were categorized into malnutrition and normal status according to five nutritional screening tools one month after surgery. The Spearman partial correlation, Cohen's Kappa coefficient, the area under the curve (AUC), sensitivity, and specificity of each two screening tools were calculated. Results: Malnutrition was observed in 86.24% of patients based on the PG-SGA and 85.82% based on the NUTRISCORE. When NRI or CONUT were applied, the proportions of malnutrition were < 30%. Patients with malnutrition had lower intakes of energy and protein than normal patients when assessed using the PG-SGA, NUTRISCORE, or NRI. Lower levels of albumin, hemoglobin, total lymphocyte count, and total cholesterol and longer postoperative hospital stays were observed among patients with malnutrition compared to normal patients when NRI, PNI, or CONUT were applied. Relatively high agreement for NUTRISCORE relative to PG-SGA was found; the sensitivity was 90.86%, and the AUC was 0.78. When NRI, PNI, and CONUT were compared, the sensitivities were 23.72% for PNI relative to NRI, 44.53% for CONUT relative to NRI, and 90.91% for CONUT relative to PNI. The AUCs were 0.95 for NRI relative to PNI and 0.91 for CONUT relative to PNI. Conclusions: NUTRISCORE had a high sensitivity compared to PG-SGA, and CONUT had a high sensitivity compared to PNI. NRI had a high specificity compared to PNI. This relatively high sensitivity and specificity resulted in 77.00% agreement between PNI and CONUT and 77.94% agreement between NRI and PNI. Further cohort studies will be needed to determine if the nutritional status assessed by PG-SGA, NUTRISCORE, NRI, PNI, and CONUT predicts the gastric cancer prognosis.

• Korean Journal of Animal Reproduction
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• v.23 no.4
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• pp.323-331
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• 1999

The effects of insulin-like growth factor-I (IGF-I) and cumulus cells during in vitro maturation in porcine oocytes were examined. When follicular oocytes were cultured in medium with different concentrations of IGF-I, maturation rates were 60, 61 and 62 and 72% for 0, 15 and l0ng/$m\ell$ IGF-I. In medium with 10ng/$m\ell$ IGF-I, maturation rates were not significantly difference between oocytes with (68%) and without (52%) cumulus cells during the culture. In medium with-out IGF-I, however, the maturation rates in oocytes with cumulus cells (63%) was significantly (P＜0.05) higher than oocytes without cumulus cells (32%). On the other hand, when IGF-I was added for first 24 h period or later 24 h period of culture, maturation rates were higher in oocytes with (61 and 49%) that than without (49 and 45%) cumulus cells. In experiment used medium without fetal calf serum (FCS) and porcine follicular fluid (PFF), the maturation rates in oocytes with cumulus cells for 48 h (48 and 67%) or first 24 h (46 and 63%) period after culture were significantly (P＜0.01) higher than in oocytes without cumulus cells (16 and 18%) in the presence or absence of IGF-I. These results indicated that cumulus cells is essential on maturation in vitro in porcine oocytes, but IGF-I can promote oocytes maturation of oocytes without cumulus cells in medium with FCS and PFF.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.517-524
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• 2024

This study aims to train and implement a deep learning model for the fusion of website creation and artificial intelligence, in the era known as the AI revolution following the launch of the ChatGPT service. The deep learning model was trained using 3,000 collected web page images, processed based on a system of component and layout classification. This process was divided into three stages. First, prior research on AI models was reviewed to select the most appropriate algorithm for the model we intended to implement. Second, suitable web page and paragraph images were collected, categorized, and processed. Third, the deep learning model was trained, and a serving interface was integrated to verify the actual outcomes of the model. This implemented model will be used to detect multiple paragraphs on a web page, analyzing the number of lines, elements, and features in each paragraph, and deriving meaningful data based on the classification system. This process is expected to evolve, enabling more precise analysis of web pages. Furthermore, it is anticipated that the development of precise analysis techniques will lay the groundwork for research into AI's capability to automatically generate perfect web pages.

• Journal of environmental and Sanitary engineering
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• v.22 no.3
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• pp.1-12
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• 2007

This study was investigated hazardous substances in agricultural products of baggage by Incheon Port from chinese. We tested 293 kinds of dried red pepper, cereal, sesame, bean, nut, herbal medicine and sesame oil for pesticides residue, mold, tar color, sudan I, II, III, IV, aflatoxin, Pb, Cd, Hg, As and sulfur dioxide residues. Violated samples over standard limits by Korean Food and Drug Administration (KFDA) were 76 dried red pepper over the number of mold and 1 dried red pepper detected red 102 tar color and 1 dried red pepper over the number of mold and detected red 102 tar color simultaneously. And 2 rice, 1 sticky rice, 1 adlay and 1 millet were over lead. Violated herbal medicine were 2 Zizyphi Furctus and 2 Zingiberis Rhizoma over sulfur dioxide residue and 1 Zingiberis Rhizoma over sulfur dioxide residue and cadmium simultaneously. The contents of heavy metals in cereal were as follow; $Pb\;0.000{\sim}0.740mg/kg(0.191{\pm}0.209),\;Cd\;0.000{\sim}0.108mg/kg(0.007{\pm}0.020),\;Hg\;0.000{\sim}4.201mg/kg(0.162{\pm}0.319)$. The contents of heavy metals in herbal medicine were as follow; $Pb\;0.000{\sim}2.480mg/kg(1.130{\pm}0.730),\;Cd\;0.000{\sim}0.761mg/kg(0.044{\pm}0.122),\;Hg\;0.000{\sim}0.157mg/kg(0.022{\pm}0.033),\;As\;0.000{\sim}0.560mg/kg(0.040{\pm}0.082)$. Contents of $SO_2$ ranged $2.0{\sim}1459.4ppm(303.1{\pm}324.2)$.