• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.215-215
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• 2022

현재 국내 정수시설은 정수공정별 감시제어-데이터수집시스템(SCADA: Supervisory Control And Data Acquisition)에 기반하여 감시제어 및 모니터링 위주로 운영·관리를 실시하고 있다. 또한, 주요 핵심 공정인 응집제 약품투입, 소독 및 여과 설비 공정의 운영방식에 있어서 선험적 운영지식에 의한 방식으로 운영되고 있기 때문에 지속적인 안정적 운영을 위해서는 표준적이고 체계적인 운영관리 수단이 필요하다. 국외에서는 다양한 운영 조건에 기반한 정수처리 효율을 예측할 수 있는 모의(simulation) 도구의 개발을 통해 기존 운영되고 있는 정수장의 효율을 예측하는 데 활용하고 있는 실정이다. 본 논문은 실시간 운영관리가 가능한 기반을 구축하여 정수처리의 효율을 예측할 수 있는 시뮬레이터 개발을 통해 정수처리 공정별 기본 및 조합의 공정 시뮬레이션 모의 모듈 기술을 개발하기 위한 연구를 수행하였다. 또한 개발된 기술의 실증 운영을 통해 검증된 모듈을 반영한 정수장 시뮬레이터 시스템을 개발을 위한 연구를 수행하였다. 정수장 시뮬레이터는 수질정보, 물질수지, 수두손실등의 운영현황 데이터를 수집하는 기능, 착수-혼화-응집-침전-여과-소독 등 개별 공정별 주요 운전변수의 모니터링 및 제어를 통한 운영관리 기능, 원수 수질변화에 신속한 대응을 위한 정수처리 공정제어 의사결정지원 기능, 그리고 온라인 관망해석을 포함한 정수처리 전(단위)공정 시뮬레이터 기능 및 공정별 운영인자 최적화 기능 등으로 구성되어 있다. 현재 운영 중인 정수장의 공정별 운전 상태를 평가·관리하여 정수공정 운영 안정화 체계를 확보하고, 정수장의 유량과 수질의 갑작스런 변화에 따른 모의를 통한 수질예측으로 실시간 정수장 최적운영관리가 가능하다. 또한 원수 성상에 따른 적정 공정운영 자동화로 운영비 절감 및 효율적 인력 활용으로 정수장 운영 효율성을 제고함으로써 지속적이고 안정적인 정수장 운영 체계를 확보할 수 있다.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.33-39
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• 2024

Inspecting cracks to determine a structure's condition is crucial for accurate safety diagnosis. However, visual crack inspection methods can be subjective and are dependent on field conditions, thereby resulting in low reliability. To address this issue, this study automates the detection of concrete cracks in image data using ResNet, FPN, and the Mask R-CNN components as the backbone, neck, and head of a convolutional neural network. The performance of the proposed model is analyzed using the intersection over the union (IoU). The experimental dataset contained 1,203 images divided into training (70%), validation (20%), and testing (10%) sets. The model achieved an IoU value of 95.83% for testing, and there were no cases where the crack was not detected. These findings demonstrate that the proposed model realized highly accurate detection of concrete cracks in image data.

• Journal of Platform Technology
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• v.11 no.6
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• pp.34-46
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• 2023

The design of non-pneumatic tires, which are created by filling the space between the wheel and the tread with elastomeric compounds or polygonal spokes, has become an important research topic in the automotive and aerospace industries. In this study, a system was designed for the design of non-pneumatic tires through the implementation of a generative adversarial network. We specifically examined factors that could impact the design, including the type of non-pneumatic tire, its intended usage environment, manufacturing techniques, distinctions from pneumatic tires, and how spoke design affects load distribution. Using OpenCV, various shapes and spoke configurations were generated as images, and a GAN model was trained on the projected GANs to generate shapes and spokes for non-pneumatic tire designs. The designed non-pneumatic tires were labeled as available or not, and a Vision Transformer image classification AI model was trained on these labels for classification purposes. Evaluation of the classification model show convergence to a near-zero loss and a 99% accuracy rate confirming the generation of non-pneumatic tire designs.

• Journal of Bio-Environment Control
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• v.24 no.4
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• pp.308-316
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• 2015

This study was conducted to investigate the situation of ICT apply to plastic greenhouse, and the results be apply to design of new one. A CFD analysis were conducted to monitering the ventilation and energy saving of the single span greenhouse newly designed. The causes of delay to apply ICT to plastic greenhouse are the high cost for installation(24%), insufficiency of after services(19%), often disorder(16%), unskillful management of soft ware(15%), insufficient ICT efficiency(13%) and unsatisfying of income increase(12%). The parts of problem occurred in ICT plastic greenhouse are the structure, actuator, environmental control system and sensor(approximate 14%, respectively), remote control technique(13%), plant management technique(12%), energy saving technique(10%) and utilization of software(8%). In the condition of lateral window closed, the average wind speed changed to slow, but it was faster in the condition of leeward side window opened than in the condition of lee and winward side window opened. The air movement in the condition of lateral window closed occur by air moving fan not by out air. It is not affect the room temperature but effective the uniformity of room temperature. The average temperature of low height greenhouse was uniform than high height one. The average temperature in condition of 3rd curtain opened become same with outside temperature after 2 hours, but take more 5 hours in condition of 3rd curtain closed.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.1-7
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• 2015

This study is a case study of the research study and education with high school students of natural sciences. Recent development of the Internet of Things (IoT) based on the subject of various studies exist. This study is one of the most portable communication devices of these infancy, yet students were easy to define the molding process of contacting a pager that can go along way in making research topics. We called a pager. Today, it is given a large and complex smart mobile communication devices that can be used for big data. Prior pagers are taught the meaning of the first mobile communication means in our lives were given device. The internal structure is relatively simple and is thought to function relatively simple, just suitable as a teaching practices of high school students with an interest in science and engineering universities. This study can see all of the mechanical, electronic information contents of the radio pager in a relatively simple analysis of the injection molding ONE CAVITY analysis. Furthermore, the students also rated good educational practices that give meaning to remind the convergence training on mass production and process automation.

• Journal of Astronomy and Space Sciences
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• v.23 no.3
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• pp.245-258
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• 2006

In this paper, an automation algorithm of analyzing and scheduling the station-keeping maneuver is presented for Communication, Ocean and Meteorological Satellite (COMS). The perturbation analysis for keeping the position of the geostationary satellite is performed by analytic methods. The east/west and north/south station-keeping maneuvers we simulated for COMS. Weekly east/west and biweekly north/south station-keeping maneuvers are investigated for a period of one year. Various station-keeping orbital parameters are analyzed. As the position of COMS is not yet decided at either $128.2^{\circ}E\;or\;116.0^{\circ}E$, both cases are simulated. For the case of $128.2^{\circ}E$, east/west station-keeping requires ${\Delta}V$ of 3.50m/s and north/south station-keeping requires ${\Delta}V$ of 52.71m/s for the year 2009. For the case of $116.0^{\circ}E,\;{\Delta}V$ of 3.86m/s and ${\Delta}V$ of 52.71m/s are required for east/west and north/south station-keeping, respectively. The results show that the station-keeping maneuver of COMS is more effective at $128.2^{\circ}E$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.579-584
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• 2017

The damper oil seal of a high-speed railway vehicle is made from nitrile butadiene rubber (NBR) in order to prevent lubricant from leaking into the damper and to stop harmful contaminants from entering the external environment while in service. Oil leakage through the seal primarily occurs from fatigue failure of the damper. Cumulative damage of the seal occurs due to the contact force between the rod and the rubber during movement due to track irregularities and cants, among other factors. Thus, the design of the oil seal should minimize the maximum principal strain at weak points. In this study, the optimal cross section of the damper oil seal was found using the multi-island genetic algorithm method to improve the durability of the damper. The optimal shape of the oil seal was derived using process automation and design optimization software. Nonlinear material properties for finite element analysis (FEA) of the rubber were determined by Marlow's model. The nonlinear FEA confirmed that the maximum principal strain at the oil leakage point was decreased 24% between the initial design and the optimum design.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.4
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• pp.350-358
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• 2017

The hemolysis index (HI) is semi-quantitative marker for hemolysis. Because the characteristics of the HI vary from one commercial platform to another, no standardization or harmonization of the HI is currently available. Specimens (N=40) randomly selected from clinical patients were artificially hemolyzed in vitro. The serum of the specimens was then diluted with a 20 mg/dL difference between 0~300 mg/dL based on serum hemoglobin measured using the XE-2100 hematology automation equipment (Sysmex, Japan). Diluted serum was measured using the Hitachi-7600 biochemical automation equipment (Hitachi, Japan) to differentiate between HI and serum hemoglobin. The data showed linearity between HI and serum hemoglobin and that HI 1 contained approximately 20 mg/dL of serum hemoglobin. To determine the blood rejection threshold, the HI was divided into three groups: HI 0~1, HI 4~6, HI 9~15. After another batch of clinical specimens (N=40) was measured using a Hitachi-7600 (Hitachi, Japan), each specimen was moved forward and backward with the piston of the syringe to induce an artificial in vitro hemolysis, then measured again with a Hitachi-7600 (Hitachi, Japan). The percentage difference between the three groups was analyzed by ANOVA or the Kruskal-Wallis test. In the post-test, there were significant differences between the HI 0~1 and the HI 5~6: Glucose, creatinine, total protein, AST, direct bilirubin, uric acid, phosphorus, triglyceride, LDH, CPK, Magnesium, and potassium levels. Because many clinical tests differed significantly, the threshold for hemolysis could be appropriate for HI 5 (serum hemoglobin 100 mg/dL).

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.