• Clinical and Experimental Reproductive Medicine
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• v.29 no.1
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• pp.57-66
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• 2002

Objective : This study was designed to investigate the interrelationship and clinical usefulness of sperm morphology by strict criteria (SM), acrosome reaction following ionophore challenge test (ARIC) and sperm penetration assay (SPA) using zona-free hamster ova as prognostic factors in in vitro fertilization. Materials and Methods: Semen samples were provided by 83 patients undergoing IVF. We first evaluated the differences between normal fertilization group and poor fertilization group on three andrologic tests. Secondly, we analyzed the relationship between the three andrologic tests and in vitro fertilization on IVF settings. Finally, we evaluated the effectiveness of the three andrologic tests as the prognostic indicators for fertilizing ability. Results: The fertilization rate of all men in the poor fertilization group was less than 30%; but there was no evidence that this poor fertilization was due to oocyte defects. The results of three andrologic tests were significatly higher in normal fertilization group. Fertilization rate (%) in vitro was highly correlated (p<0.001) with % normal sperm by SM, ARIC value (%), and SPA result. By using Receiver-Operator-Characteristic curve (ROC), we evaluated the effectiveness of these three tests. The sensitivity and specificity of SM, ARIC test and SPA in predicting fertilization potential in IVF setting were 76% and 75%, 84% and 90%, and 76% and 95%, respectively. Conclusion: Our data suggest that the three andrologic tests can be reliable tools as prognostic factors of sperm fertilizing ability. Among these test, ARIC test and SPA gave more accurate information on fertilizing capacity. ARIC test was shown to have a predictive value for fertilizing ability comparable to that of SPA that appears to be a simple and cost-effective addition to current andrology laboratory. Combined application of these three tests may give more information on predicting sperm fertilizing capacity.

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.691-703
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• 2003

In this paper, a new and integrated approach easily used to calculate the pollutant loads from agricultural watersheds is suggested. Basic concepts of this empirical tool are based on the hypotheses that variations in event mean concentrations(EMCs) of the pollutants from a given agricultural watershed during rainstorms are only due to the rainfall pattern. This assumption would be feasible to agricultural watersheds whose land uses does not change during the cultivation period overlapped by rainy season and also in which point-sources of the pollutants are rare. Therefore, if EMC data sets through extensive sampling from various rural areas are available, it is possible to establish relationships between EMCs, shapes and land uses of the watersheds, and rainfall events. For this purpose, fifty one sets of EMC values were obtained from nine different watersheds, and those data were used to develop predictive tools for the EMCs of 55, COD, TN and TP in rainfall runoff. The results of the statistical tests for those formulas show that they are not only fairly good in predicting actual EMC values of some parameters, but also useful in terms of calculating pollutant loads on any time-spans such as the day of rainfall event or weekly, monthly, and yearly. Their applicability was briefly demonstrated and discussed. Also, the unit loads calculated from EMCs based on different land uses and real rainfall data over one of the watershed used for this study. were provided, and they are compared with other well-known unit loads.

• Journal of Preventive Medicine and Public Health
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• v.34 no.4
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• pp.427-436
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• 2001

Objective : To estimate the prevalence of congenital heart disease from the 1990 student heart disease screening program. Methods : The heart disease screening program for elementary students was conducted in Kyonggi-do, in 1998. The subjects of the present study comprised the 40,402 students who attended the schools in the catchment area of a collaborative university hospital and who participated in the primary examination. The congenital heart disease (CHD) patients were initially identified through a questionnaire about prior medical history, and further through diagnostic tests & medical examinations in the secondary & the tertiary examinations. Certain assumptions were used in the estimation of the number of CHD cases among non-participants of the secondary & tertiary examinations. The overall prevalence of CHD was estimated by adding the CHD detection rates of the participants and the estimated prevalence of the non-participants. Results : Among the 40,402 primary participants, 1,655 were referred further, of whom 79.1% (1,309) participated in the secondary examination. Of these, 121 were referred to the tertiary examination, with a participation rate at this last stage of 80.2%. The positive predictive value (PPV) of the screening tools was the highest when the results of both EKG and the questionnaire were positive. Because 85.9% of the detected cases had a past history of CHD, PPV was higher when the selection criteria in the questionnaire included past CHD history than when it didnt. The CHD defection rate among the participants was 1.76 cases/1,000 and the presumed number of cases among the non-participants was 31; giving an estimated final CHD prevalence of 2.52 cases/1,000 (95% CI : 2.06-3.06). Among the identified cases of CHD, VSD (52.8%) was the most common, followed by PDA (9.7%), TOF (9.7%) & PS (9.7%). Conclusion : Because the characteristics of the non-participants differed from those of the participants, the estimation of prevalence was influenced by the participation rate. Of the detected cases, 85.9% had a past history of diagnosis or operation for CMD. These findings suggested that the prevalence estimated in this study may be an underestimation of the actual condition. Therefore, a birth cohort study is required in order to more accurately estimate the prevalence and the effects of the program.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.2
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• pp.141-158
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• 2019

Objectives: An adverse outcome pathway is a biological pathway that disturbs homeostasis and causes toxicity. It is a conceptual framework for organizing existing biological knowledge and consists of the molecular initiating event, key event, and adverse output. The AOP concept provides intuitive risk identification that can be helpful in evaluating the carcinogenicity of chemicals and in the prevention of cancer through the assessment of chemical carcinogenicity predictions. Methods: We reviewed various papers and books related to the application of AOPs for the prevention of occupational cancer. We mainly used the internet to search for the necessary research data and information, such as via Google scholar(http://scholar.google.com), ScienceDirect(www.sciencedirect.com), Scopus(www.scopus. com), NDSL(http: //www.ndsl.kr/index.do) and PubMed(http://www.ncbi.nlm.nih.gov/pubmed). The key terms searched were "adverse outcome pathway," "toxicology," "risk assessment," "human exposure," "worker," "nanoparticle," "applications," and "occupational safety and health," among others. Results: Since it focused on the current state of AOP for the prediction of toxicity from chemical exposure at work and prospects for industrial health in the context of the AOP concept, respiratory and nanomaterial hazard assessments. AOP provides an intuitive understanding of the toxicity of chemicals as a conceptual means, and it works toward accurately predicting chemical toxicity. The AOP technique has emerged as a future-oriented alternative to the existing paradigm of chemical hazard and risk assessment. AOP can be applied to the assessment of chemical carcinogenicity along with efforts to understand the effects of chronic toxic chemicals in workplaces. Based on these predictive tools, it could be possible to bring about a breakthrough in the prevention of occupational and environmental cancer. Conclusions: The AOP tool has emerged as a future-oriented alternative to the existing paradigm of chemical hazard and risk assessment and has been widely used in the field of chemical risk assessment and the evaluation of carcinogenicity at work. It will be a useful tool for prediction, and it is possible that it can help bring about a breakthrough in the prevention of occupational and environmental cancer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.126-136
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• 2018

The purpose of this study was to develop a severity-adjustment model for predicting mortality in acute stroke patients using machine learning. Using the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2015, the study population with disease code I60-I63 (KCD 7) were extracted for further analysis. Three tools were used for the severity-adjustment of comorbidity: the Charlson Comorbidity Index (CCI), the Elixhauser comorbidity index (ECI), and the Clinical Classification Software (CCS). The severity-adjustment models for mortality prediction in patients with acute stroke were developed using logistic regression, decision tree, neural network, and support vector machine methods. The most common comorbid disease in stroke patients were hypertension, uncomplicated (43.8%) in the ECI, and essential hypertension (43.9%) in the CCS. Among the CCI, ECI, and CCS, CCS had the highest AUC value. CCS was confirmed as the best severity correction tool. In addition, the AUC values for variables of CCS including main diagnosis, gender, age, hospitalization route, and existence of surgery were 0.808 for the logistic regression analysis, 0.785 for the decision tree, 0.809 for the neural network and 0.830 for the support vector machine. Therefore, the best predictive power was achieved by the support vector machine technique. The results of this study can be used in the establishment of health policy in the future.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.10 no.1
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• pp.36-43
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• 2007

Purpose: The ultrasonography (USG) and computed tomography (CT) are popular diagnostic tools for the diagnosis of acute appendicitis in children, but there are many debates about their clinical significance. The purpose of this study is to clarify the clinical significance of USG, CT and follow-up CT performed subsequently to USG, especially in perforated acute appendicitis in children. Methods: We have reviewed 419 cases of surgically confirmed acute appendicitis in children under the age of sixteen, who had been treated in Inje University Ilsan Paik Hospital from March 2002 to February 2006. All the clinical data including the results of USG and CT were collected and analyzed. Results: Sensitivity, specificity, positive and negative predictive values of USG were 98.7%, 96.8%, 98.1%, 97.8% in non-perforation group and 90.8%, 100%, 100%, 81.9% in perforation group. Those of CT were 96.4%, 100%, 100%, 96.5% and 86.6%, 100%, 100%, 87.5% respectively. Those of follow-up CT after USG were 100%, 100%, 100%, 100% and 87.5%, 100%, 100%, 92.0% respectively. The duration of using antibiotics in seven patients showed positive correlation with the interval between two imaging studies (r=0.0472, p=0.019). There was no statistical significance of correlation when these imaging studies performed within 30 hours together. Conclusion: In most of the cases, single choice between USG and CT would be enough to diagnose the acute appendicitis in children. But, it may be helpful to perform CT as early as possible subsequently to USG when there is discrepancy between initial USG and clinical impression.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.187-197
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• 2010

Carbon dioxide Capture and Storage(CCS) is regarded as one of the most promising options to response climate change. CCS is a three-stage process consisting of the capture of carbon dioxide($CO_2$), the transport of $CO_2$ to a storage location, and the long term isolation of $CO_2$ from the atmosphere for the purpose of carbon emission mitigation. Up to now, process design for this $CO_2$ marine geological storage has been carried out mainly on pure $CO_2$. Unfortunately the $CO_2$ mixture captured from the power plants and steel making plants contains many impurities such as $N_2$, $O_2$, Ar, $H_2O$, $SO_2$, $H_2S$. A small amount of impurities can change the thermodynamic properties and then significantly affect the compression, purification, transport and injection processes. In order to design a reliable $CO_2$ marine geological storage system, it is necessary to analyze the impact of these impurities on the whole CCS process at initial design stage. The purpose of the present paper is to compare and analyse the relevant physical property models including BWRS, PR, PRBM, RKS and SRK equations of state, and NRTL-RK model which are crucial numerical process simulation tools. To evaluate the predictive accuracy of the equation of the state for $CO_2-SO_2$ mixture, we compared numerical calculation results with reference experimental data. In addition, optimum binary parameter to consider the interaction of $CO_2$ and $SO_2$ molecules was suggested based on the mean absolute percent error. In conclusion, we suggest the most reliable physical property model with optimized binary parameter in designing the $CO_2-SO_2$ mixture marine geological storage process.

• Development and Reproduction
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• v.13 no.1
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• pp.1-11
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• 2009

Implantation itself is governed by an array of endocrine, paracrine and autocrine modulators, of embryonic and maternal origin. Window of implantation is the unique temporal and spatial expression of factors allows the embryo to implant via signaling, appositioning, attachment, and invasion in a specific time frame of $2{\sim}4$ days. When the embryo has arrived in the uterine cavity, a preprogrammed sequence of events occurs, which involves the production and secretion of a multitude of biochemical factors such as cytokines, growth factors, and adhesion molecules by the endometrium and the embryo, thus leading to the formation of a receptive endometrium. Cytokines such as LIF, CSF-1, and IL-1 have all been shown to play important roles in the cascade of events that leads to implantation. Integrin, L-selectin ligands, glycodelin, mucin-1, HB-EGF and pinopodes are involved in appositioning and attachment. The embryo also produces cytokines and growth factors (ILs, VEGF) and receptors for endometrial signals such as LIF, CSF-1, IGF and HB-EGF. The immune system and angiogenesis play an important role. The usefulness of these factors to assess endometrial receptivity and to estimate the prognosis for pregnancy in natural and artificial cycles remains to be proven. Integrins, pinopodes, glycodelin and LIF (from biopsies) are promising candidates; from uterine flushings, glycodelin and LIF are also candidates. The ideal serum marker is not available, but VEGF, glycodelin and CSF have some clinical implications. Further evaluation that includes larger groups of infertile women and fertile controls are needed to elucidate whether their presence in plasma, flushing fluid, or endometrial samples can be used as some kind of a screening tool to assess endometrial function and prognosis for pregnancy before and after artificial reproductive therapy. A better understanding of their function in human implantation may lead to therapeutic intervention, thereby improving the success rate in reproduction treatment. New molecular techniques are becoming available for measuring both embryonic and endometrial changes prior to and during implantation. The use of predictive sets of markers may prove to be more reliable than a single marker. Ultimately, the aim is to use these tools to increase implantation in artificial cycles and consequently improve live-birth rates.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.802-811
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• 2023

Marine spatial planning (MSP) is a crucial element for rational allocation and sustainable use of marine areas. Particularly, Fishing Activity Protected Areas constitute essential zones accounting for 45.6% designated for sustainable fishing activities. However, the current assessment of these zones does not adequately consider future demands and potential values, necessitating appropriate evaluation methods and predictive tools for long-term planning. In this study, we selected key fish species (Scomber japonicus, Trichiurus lepturus, Engraulis japonicus, and Larimichthys polyactis) within the Fishing Activity Protected Area to predict their distribution and compare it with the current designated zones for evaluating the ability of the prediction tool. Employing the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report scenarios (SSP1-2.6 and SSP5-8.5), we used species distribution models (such as MaxEnt) to assess the movement and distribution changes of these species owing to future variations. The results indicated a 30-50% increase in the distribution area of S. japonicus, T. lepturus, and L. polyactis, whereas the distribution area of E. japonicus decreased by approximately 6-11%. Based on these results, a species richness map for the four key species was created. Within the marine spatial planning boundaries, the overlap between areas rated "high" in species richness and the Fishing Activity Protected Area was approximately 15%, increasing to 21% under the RCP 2.6 scenario and 34% under the RCP 8.5 scenario. These findings can serve as scientific evidence for future evaluations of use zones or changes in reserve areas. The current and predicted distributions of species owing to climate change can address the limitations of current use zone evaluations and contribute to the development of plans for sustainable and beneficial use of marine resources.