• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.169-169
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• 2016

농업 유역 내 수문 순환 및 비점오염원의 발생 및 거동에 대해서 유역단위로서의 많은 연구가 진행되어 왔다. 하지만 유역단위로서의 모의를 통해서는 필지 별 발생되는 농업 비점오염물질을 평가하고 대책을 세우기에는 한계가 있다. 따라서 농업 유역의 농경지를 대상으로 유역단위 모의가 아닌 필지단위 모의를 진행함으로써 농업 비점오염물질에 대한 관리를 해야 할 필요성이 있다. 그리하여 본 연구에서는 필지단위로 상세한 모의가 가능한 ArcAPEX 모형을 사용하였으며 모형 내 임계값 조정을 통한 유역 구분 시 우리나라 지형 및 농업특성 상 지형인자 추출의 어려움으로 Pre-defined Streams and Watersheds 기능을 활용하는 것이 농경지를 대상으로 정확한 필지 분할 및 필지 특성 반영이 될 것이라 판단하였다. 하지만 Pre-defined Streams and Watersheds 기능에 필요한 자료를 구축하는데 시간과 노력이 많이 소모되고 어려움이 있었다. 따라서 본 연구에서는 입력 자료 구축의 편의를 도모하고자 Subarea-Stream 자동 연결 모듈을 개발하여 그 활용성을 평가하고자 하였다. 이를 위해 지형적 특성으로 인해 집약적인 농업이 행해지고 있는 강원도 양구군에 위치한 해안면 유역의 농경지 경계와 하천 및 수로에 대한 자료를 Subarea-Stream 자동 연결 모듈에 입력하여 최종적으로 Pre-defined Streams and Watersheds 기능에 필요한 입력 자료를 변환시켜 모형에 적용하였다. 본 연구결과 Pre-defined Streams and Watersheds 기능에 필요한 입력 자료를 단시간에 편리하게 구축할 수 있었으며, 농경지를 대상으로 필지 단위로 분할이 된 것을 확인 할 수 있었다. 최종적으로 본 연구를 통해 지형인자 추출 오류로 인해 수계 추출 시 나타날 수 있는 문제점에 대한 해결을 할 수 있었으며 모형 내 Pre-defined Streams and Watersheds 입력 자료 구축 시 Subarea-Stream 자동 연결 모듈을 활용한다면 농업 유역 내 농경지에 대해서 편리하게 유역단위에서의 모의가 아닌 필지단위에서의 상세한 모의를 하는데 큰 기여를 할 것이라 판단된다.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.335-344
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• 2021

The purpose of this paper is the development of course data models and learning achievement computation algorithms for enabling the course-embedded assessment(CEA), which is essential of competency-based education in higher education. The previous works related CEA have weakness in the development of the systematic solution for CEA computation. In this paper, we propose data models and algorithms to implement competency-based assessment system. Our data models are composed of a layered architecture of learning outcomes, learning modules and activities, and an associative matrix of learning outcomes and activities. The proposed methods can be applied to the development of the course-embedded assessment system as core modules. We evaluated the effectiveness of our proposed models through applying the models to a practical course, Java Programing. From the result of the experiments we found that our models can be used in the assessment system as a core module.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.79-94
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• 2021

A GNSS receiver installed in autonomous vehicles is the most essential device for its navigation. However, if an intentional jamming signal is generated, there is a risk of exposure to an accident risk due to deterioration of the GNSS sensor's performance. Research is required to prevent this, and accordingly, a jamming generating device must be provided. However, according to the provisions of the law related to jamming, this is illegal. In this paper, we implement an in-vehicle jamming device that complies with the provisions of the law and does not affect the surrounding GNSS sensors. Driving simulation is used to evaluate the performance of the GNSS algorithm, and the malfunction of autonomous vehicles occurring in the interference environment and data errors output from the GNSS sensor are analyzed.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.263-271
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• 2021

Optoelectronic shooting training systems are used in shooting training sites to improve the accuracy of shooting by tracking the trajectories of gun movements. However, optoelectronic-based systems have limitations in terms of cost, complexity of installation, and the risk that electronic targets may be broken. In this study, we developed and verified a shooting training system that measures postural tremors using a low-cost accelerometer. The acceleration sensor module was designed to be attached to the air cylinder of a gun. Postural tremors were evaluated based on amplitude, frequency, and spatial pattern index, which were computed using acceleration data. The postural tremor indices between the accelerometer and optoelectronic-based system were highly correlated (left-right and up-down directions: r = 0.76 and r = 0.70, respectively). We validated the developed shooting training system using an independent two-sample t-test, which identified a significant difference (p < 0.05) in the calculated postural tremor index according to the athlete's shooting score (i.e., best and worst shots).

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1411-1416
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• 2018

Currently, most of the industrial areas like chemistry, manufacturing, shipbuilding, and steel, perform the work related to gas, and the staffs who are in charge of this work have a risk of suffocation without cognizing incidents like gas leak. For example, when the nitrogen gas leaked in 2015 at Paju, two people were killed and four people were injured. In 2018 at Pohang, four workers were suffocated to death from nitrogen gas. In order to solve this problem, this study realized the system in which workers could immediately cognize the gas leak and also deliver the situation to the staff in charge of safety at the same time, by installing the IoT device composed of gas sensor and communication module on the safety helmet that should be worn by field workers. This study is expected to be able to reduce the casualties caused by gas leak in industrial sites.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.13-19
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• 2019

In order to register an application with Apple's App Store, it must pass a rigorous verification process through the Apple verification center. That's why spyware applications are difficult to get into the App Store. However, malicious code can also be executed through normal application vulnerabilities. To prevent such attacks, research is needed to detect and analyze early to patch potential vulnerabilities in applications. To prove a potential vulnerability, it is necessary to identify the root cause of the vulnerability and analyze the exploitability. A tool for analyzing iOS applications is the debugger named LLDB, which is built into Xcode, the development tool. There are various functions in the LLDB, and these functions are also available as APIs and are also available in Python. Therefore, in this paper, we propose a method to efficiently analyze potential vulnerabilities of iOS application by using LLDB API.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.22-33
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• 2018

Recently domestic manufacturing companies have been experiencing worsening profitability and stunted growth due to the long-term economic recession and the rapid rise of developing countries such as China and Southeast Asia. These difficulties force many companies to concentrate their core competencies on new value creation and innovation in order to gain momentum for new growth. Enterprise Resource Planning (ERP) has been considered as one of viable solutions. Among the various modules in ERP, shop floor control function in the production management module is rather limited. In order to overcome this problem, Manufacturing Execution System (MES) has been used as a subsystem which has a strong information gathering power and flexibility. Both systems interact closely with each other. In particular, ERP requires fast, accurate shop floor information at MES. This paper describes how to synchronize relevant information between ERP and MES with theory of constraints (TOC). The processing time information transmitted from the MES workplace is received at the ERP workplace. In the process, the received processing time is causing information distortion in ERP, when the information gathering standard of MES is different from the ERP information interpretation standard. The Drum-Buffer-Rope theory of TOC was applied to resolve this problem, therefore, information synchronization between both systems was made. As a precondition, the standard time of the upper ERP system was rearranged according to the capacity constraints resource. As a result, standard time restructuring has affected changes in labor costs. Standard labor costs have come close to actual ones, and information synchronization of MES transmission data has improved the reliability of standard product costs, such that it enabled various company-wide restructuring actions to be much more effective.

• Clinical and Experimental Reproductive Medicine
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• v.46 no.3
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• pp.125-131
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• 2019

Objective: To investigate serum 25-hydroxyl vitamin D (25(OH)D) and vitamin D-binding protein (VDBP) concentrations in women with endometriosis according to the severity of disease. Methods: Women with mild endometriosis (n = 9) and advanced endometriosis (n = 7), as well as healthy controls (n = 16), were enrolled in this observational study. Serum total 25(OH)D concentrations were analyzed using the Elecsys vitamin D total kit with the Cobas e602 module. Concentrations of bioavailable and free 25(OH)D were calculated. Concentrations of VDBP were measured using the Human Vitamin D BP Quantikine ELISA kit. Variables were tested for normality and homoscedasticity using the Shapiro-Wilk test and Leven F test, respectively. Correlation analysis was used to identify the variables related to total 25(OH)D and VDBP levels. To assess the effects of total 25(OH)D and VDBP levels in the three groups, multivariate generalized additive modeling (GAM) was performed. Results: Gravidity and parity were significantly different across the three groups. Erythrocyte sedimentation rate (ESR) and CA-125 levels increased as a function of endometriosis severity, respectively (p= 0.051, p= 0.004). The correlation analysis showed that total 25(OH)D levels were positively correlated with gravidity (r = 0.59, p< 0.001) and parity (r = 0.51, p< 0.003). Multivariate GAM showed no significant relationship of total 25(OH)D levels with EMT severity after adjusting for gravidity and ESR. However, the coefficient of total 25(OH)D levels with gravidity was significant (1.87; 95% confidence interval, 0.12-3.63; p= 0.040). Conclusion: These results indicate that vitamin D and VDBP levels were not associated with the severity of endometriosis.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.4
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• pp.81-91
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• 2019

The 3-dimensional grain burn-back analysis is performed using the face offsetting method for calculating the solid rocket motor performance. The grain burning configuration analysis is a moving surface problem that calculates the regression of the burning surface. In the previous study, various moving interface analysis methods were applied for the grain burn-back analysis, but the results were imperfect. In this study, a 3-dimensional grain burn-back analysis module is developed using the face offsetting method, which combines the advantages of the existing moving interface analysis methods to increase the accuracy and robustness. As a result, the face offsetting method is proved to be efficient for the grain burn-back analysis.

• Korean Journal of Materials Research
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• v.29 no.1
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• pp.11-15
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• 2019

Severe wall thinning is found on the tube of a low-pressure evaporator(LPEVA) module that is used for a heat recovery steam generator(HRSG) of a district heating system. Since wall thinning can lead to sudden failure or accidents that lead to shutdown of the operation, it is very important to investigate the main mechanism of the wall thinning. In this study, corrosion analysis associated with a typical flow-accelerated corrosion(FAC) is performed using the corroded tube connected to an upper header of the LPEVA. To investigate factors triggering the FAC, the morphology, composition, and phase of the corroded product of the tube are examined using optical microscopy, scanning electron microscopy combined with energy dispersive spectroscopy, and x-ray diffraction. The results show that the thinnest part of the tube is in the region where gas directly contacts, revealing the typical orange peel type of morphology frequently found in the FAC. The discovery of oxide scales containing phosphate indicates that phosphate corrosion is the main mechanism that weakens the stability of the protective magnetite film and the FAC accelerates the corrosion by generating the orange peel type of morphology.