• The Korean Society of Law and Medicine
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• v.22 no.3
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• pp.31-55
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• 2021

The Personal Information Protection Act, one of the revised 3 Data Laws, established a special cases concerning pseudonymous data. As a result, a personal information controller may process pseudonymized information without the consent of data subjects for statistical purposes, scientific research purposes, and archiving purposes in the public interest, etc. In addition, as a follow-up to the revised Personal Information Protection Act, a 'Guidelines for Utilization of Healthcare Data' was prepared, which deals with the pseudonymization in the medical sector. The guidelines are meaningful in that they provide practical criteria for accomplices by defining specific interpretations and examples that take into account the characteristics of healthcare data. However, the guidelines need to clarify the purpose of using pseudonymous data and strengthen the fairness of the composition of the data deliberation committee. The guidelines also require establishing a healthcare data compensation framework and strengthening the protection of rights for vulnerable subjects. In addition, the guidelines need to be adjusted for inconsistency with the Bioethics and Safety Act and the Medical Service Act. It is expected that this study will contribute to the creation of a safe environment for the utilization of healthcare data as well as the improvement of related laws and systems.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.936-939
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• 2022

As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

• Journal of the Korea Computer Graphics Society
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• v.28 no.1
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• pp.1-9
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• 2022

Non-small cell lung cancer (NSCLC) accounts for a high proportion of 85% among all lung cancer and has a significantly higher mortality rate (22.7%) compared to other cancers. Therefore, it is very important to predict the prognosis after surgery in patients with non-small cell lung cancer. In this study, the types of preoperative chest CT image patches for non-small cell lung cancer patients with tumor as a region of interest are diversified into five types according to tumor-related information, and performance of single classifier model, ensemble classifier model with soft-voting method, and ensemble classifier model using 3 input channels for combination of three different patches using pre-trained ResNet and EfficientNet CNN networks are analyzed through misclassification cases and Grad-CAM visualization. As a result of the experiment, the ResNet152 single model and the EfficientNet-b7 single model trained on the peritumoral patch showed accuracy of 87.93% and 81.03%, respectively. In addition, ResNet152 ensemble model using the image, peritumoral, and shape-focused intratumoral patches which were placed in each input channels showed stable performance with an accuracy of 87.93%. Also, EfficientNet-b7 ensemble classifier model with soft-voting method using the image and peritumoral patches showed accuracy of 84.48%.

• The Mathematical Education
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• v.61 no.3
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• pp.419-439
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• 2022

This study is based on Freudenthal's mathmatising process and the didactical phenomenology of linear function concept, I have described and examined the process in which students represent the constant rate of change into tables, graphs and equations and, in this way, how they construct mental objects and essence of the linear function concept. The students used the proportionality as composite units, when they represented the phenomenon with constant rate of change into tables. When representing in graphs, all but one student represented it into a line. There were differences among the students in the level they were using the given conditions, co-variation perspective, and corresponding rules when formulating equations. The students compared the relationship between two variables in a multiplicative way, and under the guidance of teachers they reached to the understanding that its relationship becomes a constant. Moreover, they could construct mental objects of a constant rate of change, understanding the situation where the relationship between time difference and distance difference becomes one value, namely speed. The students had difficulties in connecting the rate of change with the inclination of a line. The students constructed the essence (concept) of linear functions, after building and organizing the image that the rate of change is constant, the graph is linear, and the equation is formulated as y=ax+b (a: inclination, b: intercept).

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.15-15
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• 2023

2020년 기준 국내 상수도 보급률은 99.1% 차지하고 있으며(환경부, 2019), 수도관리차원에서 수돗물은 먹는 물로 시판되어질 만큼 우수한 관리체계를 유지하고 있다. 그 반면에 지하수는 생활용수, 식품가공, 농·축산, 양어, 군부대를 비롯한 전국지역에서 연간 10억 8천만톤 용수를 소비하고 있음에도 (환겨례 신문, 2013; 환경부, 2019) 사용되는 지하수의 약 65%가 음용수 불가판정을 받았으며, 최근 지하수의 오염비율은 급격히 증가하는 추세이다. 특히, 지하수관정의 관리부주의에 의한 수질오염 및 수인성 다제내성균(슈퍼박테리아) 등에 의한 오염사례가 국내는 물론, 국제적으로 다수 보고되고 있는 실정이다 (환경부, 2013). 현재 지하수 수질관리는 공공기관 및 지자체 지정기관을 통해 진행되고 있으며, 검사기간은 수질채취로부터 통상 7~15일정도 소요되어 수질 관리 및 기준, 검사주기에 대한 애로가 많다. 현장 지하수관정에서 실시간 수질을 모니터링하고 이에 연동된 자동 수처리 시스템의 개발 및 도입은 나날이 심각해지는 환경오염 상황에서 선제적 예방과 해결방법으로 중요한 요소기술이다. 현재 지하수오염 및 부적합 음용의 수질처리는 화학약품, 필터여과, UV살균, O₃ (플라즈마)을 이용하는 것이 대표적이나, 화학약품의 경우 2차 오염이나 식품 세척 및 가공에 있어 부적합성의 한계점이 있다. 필터여과의 대표적인 RO필터의 경우 약 50% 순손실이 발생하고, UV 살균의 경우 UV에 의한 사용관리자의 위험 및 장비의 광부식 문제, O₃ 의 경우 고압전류 사용에 따른 위험성 등의 한계점이 나타나고 있다. 지하수 수질정화를 위한 광유도 활성산소(¹O₂, ·O^-₂)는 광감응제에 가시광의 빛 조사를 통해 생성되는 활성산소로의 에너지 및 전자 전이가 동시 진행되어 단일항 산소(¹O₂)와 슈퍼옥사이드 이온(·O^-₂)을 생성하게 된다. 생성된 활성산소는 유해미생물 또는 유기화학물과 개열, 제거, 치환 반응 등을 통해 미생물사멸 및 유해화학물질들이 분해 가능하다. 이를 이용한 지하수 유해미생물 사멸기술, 장비, 실시간 지하수의 분석기술 및 정수처리, 지하수 물순환 시스템 개발뿐만 아니라 지하수 음용수 및 오염개선, 지하수 기저유출에 의한 오염원 저감으로부터 지류·지천, 하천 본류 수질개선 등의 대상지역에 활용 가능하다. 또한 광유도 활성산소는 기존 상수도 수처리에 있어 오존(O₃) 처리와 이산화티탄을 이용한 AOP과정을 단일처리 공정으로, 기존 O₃ 의 특성상 확산 거리가 매우 길어 사람을 포함한 생체 내에 유입 시 다양한 부작용 발생과 O₃ 차폐시설 요구의 문제점 극복의 대안으로 환경 및 인체에 무해한 광유도 활성산소 시스템을 적극적으로 도입 및 적용해야 한다. 본 연구 목적은 정류상태 흡광분광기술을 이용한 실시간 수질 모니터링과 광유도 활성산소를 이용한 유해 미생물의 멸균효능 및 지하수 수질관리 기술로의 적용 가능성을 제시하고자 한다.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.169-181
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• 2022

Purpose: This paper addresses a case study of developing a flame retardant wood-plastic composites (WPC) by adding tannic acid to the existing synthetic wood. The optimal mixing ratios of six components are explored to minimize the burning time using two mixture designs. Methods: In the preliminary experiment, six components are considered to find important components and their ranges. Seven D-optimal mixture design points are generated. Two points are removed for the balance of plastic components to be maintained, and the remaining five points are augmented with two basic compositions. Four components are selected to be considered in the main experiment. In the main experiment, pellets are extruded at the eight mixture design points. In-house testing of burning time is executed three times. Specimens made of pellets from two promising flame retardant compositions are sent to the accredited laboratories and tested. Results: The test results are as follows: 1) The best composition (Wood flour, Tannic acid, PE, Lubricant) = (25, 41, 10, 2) (wt%) shows the burning time of 1 second, which is 9-fold improvement compared to the the burning time of 9 seconds from the existing composition (58, 0, 10, 2) (wt%). 2) The second best composition (41, 25, 10, 2) (wt%) results in the burning time of 2 seconds. This composition is inferior to the best composition in terms of the flame retardancy, but more economical since it needs less tannic acid which is 100-fold expensive than the wood flour. Conclusion: Flame retardant compositions are found by adding tannic acid to the existing WPC employing optimal mixture designs. This case study will be helpful to practitioners who try to develop new products with additional physical properties with as small number of experimental trials as possible. Future research direction includes exploring conditions which satisfy both performance level and cost limitation simultaneously.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.124-133
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• 2023

Preservation processing for two combat boots was executed through application of 3-dimensional digital technology and with use of preservation materials providing outstanding reversibility and stability. The aim of this was to establish a method to preserve the relics of fallen Korean War soldiers that had been excavated by the soldiers remains excavation corps of the Ministry of National Defense. It was possible to estimate the foot size of the soldiers who would have worn the combat boots via 3-dimensional digital scanning and modeling of the boots. In this process, the original form of the combat boots was restored through the use of 3D-printed structures. The original form was restored through a process of removing contaminants from the excavated relics and performing a conditioning treatment, and through use of an antique-color treatment after bonding and filling in the sections that had been ripped or deteriorated. Following the aforementioned preservation processes, it was possible to confirm that both of the combat boots had soles and top sections made of rubber, and portions of the top section and ankle section of the boots were made of synthetic rubber. As such, it was confirmed that these were similar to the Shoe Pac(M-1944, 12-inch) winter boots that had been manufactured for the purposes of waterproofing and/or protection against cold, and introduced in 1944. Such results confirmed that it is possible to discover the manufacturing techniques, materials, and uses of relics excavated through application of preservation processing, thereby illustrating the importance of the convergent research of scientific preservation processing and 3-dimensional digital technology.

• Journal of the Korean Geotechnical Society
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• v.39 no.7
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• pp.31-37
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• 2023

Since tunnels are built underground, it is impossible to check visually the location and degree of deterioration of steel ribs. Therefore, in tunnel maintenance, GPR images are generally used to detect steel ribs. While research on GPR image analysis employing artificial neural networks has primarily focused on detecting underground pipes and road damage, there have been limited applications for analyzing tunnel GPR data, specifically for steel rib detection, both internationally and domestically. In this study, a one-step object detection algorithm called YOLO, based on a convolutional neural network, was utilized to automate the localization of steel ribs using GPR data. The performance of the algorithm is then analyzed. Two datasets were employed for the analysis. A dataset comprising 512 original images and another dataset consisting of 2,048 augmented images. The omission rate, which represents the ratio of undetected steel ribs to the total number of steel ribs, was 0.38% for the model using the augmented data, whereas the omission rate for the model using only the original data was 7.18%. Thus, from an automation standpoint, it is more practical to employ an augmented dataset.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.3
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• pp.20-34
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• 2023

Single or multi-layered two-dimensional (2D) materials, with thicknesses in the order of a few nanometers, have garnered substantial attention across diverse research domains owing to their distinct properties, including electrical conductivity, flexibility, and optical transparency. These materials are frequently subjected to repetitive mechanical actions in applications like electronic skin (E-Skin) and smart textiles. Moreover, they are often exposed to external factors like temperature, humidity, and pressure, which can lead to a deterioration in component durability and lifespan. Consequently, significant research efforts are directed towards developing self-healing properties in these components. Notably, recent investigations have revealed promising outcomes in the field of self-healing composite materials, with Ti₃Ci₂Ti_x MXene being a prominent component among the myriad of available 2D materials. In this paper, we aim to introduce various synthesis methods and characteristics of Ti₃Ci₂Ti_x MXene, followed by an exploration of self-healing application technologies based on Ti₃Ci₂Ti_x MXene.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.