• Journal of Korean Society on Water Environment
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• v.35 no.3
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• pp.224-233
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• 2019

Nitrogen components in liquid manure can reduce safety and quality of environment harmfully. To minimize the environmental risks of manure, understanding fate of manure in environment is necessary. This study aimed at investigating applicability of a simplified Level III fugacity model for simulating $NH_3-N$ component to analyze environmental fate and transport of $NH_3-N$ in liquid manure and to provide basis for improving management of N in the liquid manure system and for minimizing the environmental impacts of N. The model simulation conducted for four environmental compartments (air, water, soil, and rice plants) during rice-cropping to trace $NH_3-N$ component and provided applicability of the Level III fugacity model in studying the environmental fate of $NH_3-N$ in manure. Most of $NH_3-N$ was found in water body and in rice plants depending upon the physicochemical properties and proper removal processes. For more precise model results, the model is needed to modify with the detailed removal processes in each compartment and to collect proper and accurate information for input parameters. Further study should be about simulations of various N-typed fertilizers to compare with the liquid manure based on a modified and relatively simplified Level III fugacity model.

• The Journal of Bigdata
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• v.6 no.1
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• pp.23-35
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• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.4
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• pp.483-491
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• 2021

The identification of regional collision risks in water areas is significant for the safety of navigation. This paper introduces a new method of collision risk assessment that incorporates a clustering method based on the distance factor - hierarchical clustering - and uses real-time data in case of several surrounding vessels, group methodology and preliminary assessment to classify vessels and evaluate the basis of collision risk evaluation (called HCAAP processing). The vessels are clustered using the hierarchical program to obtain clusters of encounter vessels and are combined with the preliminary assessment to filter relatively safe vessels. Subsequently, the distance at the closest point of approach (DCPA) and time to the closest point of approach (TCPA) between encounter vessels within each cluster are calculated to obtain the relation and comparison with the collision risk index (CRI). The mathematical relationship of CRI for each cluster of encounter vessels with DCPA and TCPA is constructed using a negative exponential function. Operators can easily evaluate the safety of all vessels navigating in the defined area using the calculated CRI. Therefore, this framework can improve the safety and security of vessel traffic transportation and reduce the loss of life and property. To illustrate the effectiveness of the framework proposed, an experimental case study was conducted within the coastal waters of Mokpo, Korea. The results demonstrated that the framework was effective and efficient in detecting and ranking collision risk indexes between encounter vessels within each cluster, which allowed an automatic risk prioritization of encounter vessels for further investigation by operators.

• Journal of Navigation and Port Research
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• v.45 no.1
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• pp.33-41
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• 2021

In the last 5 years, a total of 567 accidents of operating vessels occurred under the influence of alcohol at sea, most of which occurred in fishing boats. Accidents caused by operating vessels under the influence of alcohol at sea are causing human and physical damages. There were 69 accidents caused by operating vessels under the influence of alcohol, leading to five deaths and one missing. The social damage due to operating vessels under the influence of alcohol is also increasing. Under the current law, punishment is given lightly compared to the seriousness of violation. In order to prevent the recurrence of accidents caused by operating vessels under the influence of alcohol, cases in Korea need to be analyzed. Regulations on the crackdown in foreign countries were compared to those in Korea and reviewed. In addition, risks of operating vessels under the influence of alcohol should be provided to ship workers while improving related laws and systems. In addition, efforts should be made to reduce the number of accidents due to operating vessels under the influence of alcohol by strengthening crackdowns on ships at sea so that accidents caused by operating vessels under the influence of alcohol could be prevented in advance in the future.

• Convergence Security Journal
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• v.20 no.4
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• pp.187-196
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• 2020

In order to manage information security risk, various information security level evaluation and information security management system certification have been conducted on a larger scale than ever. However, there are continuous cases of infringement of information protection for companies with excellent information security evaluation and companies with excellent information security management system certification. The existing information security risk management methodology identifies and analyzes risks by identifying information assets inside the information system. Existing information security risk management methodology lacks a review of where cyber threats come from and whether security devices are properly operated for each route. In order to improve the current risk management plan, it is necessary to look at where cyber threats come from and improve the containment level for each inflow section to absolutely reduce unnecessary cyber threats. In addition, it is essential to measure and improve the appropriate configuration and operational level of security equipment that is currently overlooked in the risk management methodology. It is necessary to block and enter cyber threats as much as possible, and to detect and respond to cyber threats that inevitably pass through open niches and use security devices. Therefore, this paper proposes additional evaluation items for evaluating the containment level against cyber threats in the ISMS-P authentication items and vulnerability analysis and evaluation items for major information and communication infrastructures, and evaluates the level of security equipment configuration for each inflow.

• Journal of Veterinary Science
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• v.23 no.4
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• pp.55.1-55.12
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• 2022

Background: ASF was first reported in Kenya in 1910 in 1921. In China, ASF spread to 31 provinces including Henan and Jiangsu within six months after it was first reported on August 3, 2018. The epidemic almost affected the whole China, causing direct economic losses of tens of billions of yuan. Cause great loss to our pig industry. As ELISA is cheap and easy to operate, OIE regards it as the preferred serological method for ASF detection. P54 protein has good antigenicity and is an ideal antigen for detection. Objective: To identify a conservative site in the African swine fever virus (ASFV) p54 protein and perform a Cloth-enzyme-linked immunosorbent assay (ELISA) for detecting the ASFV antibody in order to reduce risks posed by using the live virus in diagnostic assays. Method: We used bioinformatics methods to predict the antigen epitope of the ASFV p54 protein in combination with the antigenic index and artificially synthesized the predicted antigen epitope peptides. Using ASFV-positive serum and specific monoclonal antibodies (mAbs), we performed indirect ELISA and blocking ELISA to verify the immunological properties of the predicted epitope polypeptide. Results: The results of our prediction revealed that the possible antigen epitope regions were A23-29, A36-45, A72-94, A114-120, A124-130, and A137-150. The indirect ELISA showed that the peptides A23-29, A36-45, A72-94, A114-120, and A137-150 have good antigenicity. Moreover, the A36-45 polypeptide can react specifically with the mAb secreted by hybridoma cells, and its binding site contains a minimum number of essential amino acids in the sequence 37DIQFINPY44. Conclusions: Our study confirmed a conservative antigenic site in the ASFV p54 protein and its amino acid sequence. A competitive ELISA method for detecting ASFV antibodies was established based on recombinant p54 and matching mAb. Moreover, testing the protein sequence alignment verified that the method can theoretically detect antibodies produced by pigs affected by nearly all ASFVs worldwide.

• Journal of the Korean Orthopaedic Association
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• v.55 no.6
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• pp.534-539
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• 2020

The management of severe scoliosis remains a challenge to spine surgeons. The rapid intraoperative correction of severe scoliosis may increase the risk of perioperative complications, such as neurological compromise and implant failure. To minimize these risks, various preoperative traction methods have been employed to achieve partial correction before performing definitive corrective surgery. On the other hand, some studies have shown that one of the complications associated with halo traction could lead to cranial nerve palsy, with the sixth nerve (abducens nerve) being most commonly affected. To reduce the complications, gradual increases in the traction weight and detailed neurological examinations are needed, particularly for patients who have previously undergone brain or cervical surgery. The authors report a case of sixth cranial nerve palsy by preoperative halo-pelvic traction in patients with severe scoliosis who underwent previous decompression surgery for a Chiari I malformation with a review of the relevant literature.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.3
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• pp.242-252
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• 2022

Objectives: Firefighters and police officers are exposed to various occupational hazards. No studies in Korea have investigated the occurrence of cancer by type of cancer for the two occupations. This study aims to investigate the risk of occurrences associated with types of cancers in firefighters and police officers. Methods: Utilizing National Health Insurance(NHI) Claims data from 2006-2015, the study included 8,871,468 general workers, 25,001 firefighters, and 102,274 police officers. Using general workers as a control group, we calculated the standardized incidence ratios(SIR) by types of cancer for firefighters and police officers. After calculating the SIR for all subjects, the SIR was calculated by stratifying according to gender. Results: SIR of colon cancer 1.38(95% CI, 1.11-1.69), cancer of the liver and intrahepatic bile ducts 1.27(95% CI, 1.04-1.54), and 1.88(95% CI, 1.28-2.65) bladder cancer were higher firefighters than general workers. SIR of Lip, oral cavity, and pharynx 1.26(95% CI, 1.07-1.47), Stomach 1.14(95% CI, 1.06-1.23), colon 1.33(95% CI, 1.21-1.46), liver and intrahepatic bile ducts 1.21(95% CI, 1.10-1.32), pancreas 1.24(95% CI, 1.02-1.49), other skin 1.60(95% CI, 1.26-2.00), bladder 1.27(95% CI, 1.04-1.54), other urinary tract 1.46(95% CI, 1.27-1.68), other parts of central nervous system 1.68(95% CI, 1.10-2.46) were higher police officers than general workers. Conclusions: Both firefighters and police officers are exposed to various cancer occurrence risks, necessitating the development of occupational medical protection measures to reduce risk exposure factors.

• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.207-215
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• 2021

A forklift is an industrial vehicle with a power-operated fork for lifting and moving heavy loads over short distances. A significant number of accidents are caused by forklifts every year. Most of them are known to be caused by the unsafe acts of workers. However, only a few studies have focused on the risks of forklift work from the perspective of human error. In addition, various methods have been developed to analyze the risk of human error, while it is hard to find studies that directly compare the effectiveness or strengths/weaknesses of those methods. This study aims to analyze risk factors related to unsafe behavior in forklift operations using two representative human error analysis techniques, i.e., .SHERPA and HE-HAZOP, and compare their advantages and disadvantages. The analysis was performed on three main forklift operations ('unloading from the truck', 'moving and loading into the storage', and 'loading on the truck'). As a result, 118 errors and 34 remedial measures were derived by SHERPA. Through HAZOP, 139 errors and 54 measures were derived. The two techniques were compared in terms of the number of results and the method of deriving errors and remedial measures, cause analysis, and risk assessment. This study might be used to reduce human error related disasters in workplaces using forklifts. In order to provide a guide for choosing an appropriate analysis method, more comparative studies on different techniques involving wide range of tasks are needed in the future.