• Advances in aircraft and spacecraft science
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• 제6권1호
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• pp.51-67
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• 2019

AMOSC (Automatic Margin Of Safety Calculation) is a SW tool which has been developed to calculate the failure index of layered composite structures by referring to the cutting edge state-of-the-art LaRC05 criterion. The stress field is calculated by a finite element code. AMOSC allows the user to calculate the failure index also by referring to the classical Hoffman criterion (which is commonly applied in the aerospace industry). When developing the code, particular care was devoted to the computational efficiency of the code and to the automatic reporting capability. The tool implemented is an API which has been embedded into Femap Siemens SW custom tools. Then, a user friendly graphical interface has been associated to the API. A number of study-cases have been solved to validate the code and they are illustrated through this work. Moreover, for the same structure, the differences in results produced by passing from Hoffman to LaRC05 criterion have been identified and discussed. A number of additional comparisons have thus been produced between the results obtained by applying the above two criteria. Possible future developments could explore the sensitivity of the failure indexes to a more accurate stress field inputs (e.g. by employing finite elements formulated on the basis of higher order/hierarchical kinematic theories).

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.53-64
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• 2023

Early detection of endometrial carcinoma in uterus is essential for effective treatment. Endometrial carcinoma is the worst kind of endometrium cancer among the others since it is considerably more likely to affect the additional parts of the body if not detected and treated early. Non-invasive medical computer vision, also known as medical image processing, is becoming increasingly essential in the clinical diagnosis of various diseases. Such techniques provide a tool for automatic image processing, allowing for an accurate and timely assessment of the lesion. One of the most difficult aspects of developing an effective automatic categorization system is the absence of huge datasets. Using image processing and deep learning, this article presented an artificial endometrium cancer diagnosis system. The processes in this study include gathering a dermoscopy images from the database, preprocessing, segmentation using hybrid Fuzzy C-Means (FCM) and optimizing the weights using the Whale Optimization Algorithm (WOA). The characteristics of the damaged endometrium cells are retrieved using the feature extraction approach after the Magnetic Resonance pictures have been segmented. The collected characteristics are classified using a deep learning-based methodology called Long Short-Term Memory (LSTM) and Bi-directional LSTM classifiers. After using the publicly accessible data set, suggested classifiers obtain an accuracy of 97% and segmentation accuracy of 93%.

• 센서학회지
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• 제32권6호
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• pp.357-369
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• 2023

Wound healing is a complex and dynamic process, making the accurate and timely assessment of skin wounds a crucial aspect of effective wound care management, especially for chronic wounds. Unlike conventional wound dressings that simply cover the wound area once some form of medicine is administered onto the wound, recent studies have introduced versatile approaches to smart wound dressings capable of interacting with wound fluids to monitor physicochemical and pathological parameters to determine the wound healing status. Such electrochemical wound dressings can be integrated with on-demand, closed-loop drug delivery or stimulation systems and ultimately expanded into an ideal technological platform for the prevention, treatment, and management of skin wounds or illnesses. This article briefly reviews the wound healing mechanism and recent strategies for effective wound care management. Specifically, this review discusses the following aspects of smart wound dressings: sensor-integrated smart bandages to detect wound biomarkers, smart bandages developed to accelerate wound healing, and wireless, closed-loop automatic (on-demand) wound healing systems. This review concludes by providing future perspectives on effective wound care management.

• 정보교육학회논문지
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• 제9권1호
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• pp.113-124
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• 2005

본 연구는 학습자 특성을 고려한 교사의 수행평가기준 선택 및 개발을 돕기 위한 툴의 설계 및 개발을 목적으로 한다. 본 연구에서는 데이터마이닝의 분류 및 연관규칙 탐사 기법을 적용하여 교사의 선택 경향과 학생의 특성에 따른 수행평가 유형을 분석하였으며, 이를 통하여 기존 루브릭의 활용 및 신규개발에 대한 적용 방안을 제공하였다. 학습자의 환경, 관심 및 능력을 고려한 수행평가기준의 개발 및 활용은 데이터마이닝의 "분류"를 통한 학습자 중심의 루브릭 적용으로 가능하다. 또한 교사의 학습영역별로 축적된 루브릭 선택 성향을 연관규칙을 통해 추출하여 교수자의 루브릭 선택을 지원함으로써 수행평가에 소요되는 노력과 시간을 경감시키는 효과가 있다. 수행평가나 루브릭 간의 연관성과 학생의 특성 및 성취도에 따라 수행평가를 분류하는 본 프로그램은 교육행정 정보시스템(National Education Information System; NEIS)의 수행평가 요소와 연계하여 교수자의 루브릭 선택, 변경 및 생성을 지원한다.

• 환경영향평가
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• 제16권6호
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• pp.381-391
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• 2007

The air quality modeling was carried out to assess the impact of air quality for large scale urban development. The site for the assessment is Multi-fuctional Administrative City which locates in Yeongi-gun, Chungcheongnam-do and estimated population in 2030 is 500,000. Two automatic weather monitoring stations were installed to monitor the meteorological variables for a year and upper air meteorological parameters were measured using radiosonde for 5 days with 4 hours interval in every season. The air quality of standard air pollutants were also measured for 5 days continuously in every season. The results of wind field analysis based on the site measurements and CALMET modeling showed that the valley and mountain winds were prevailed when the sypnotic wind was weak. It also showed that wind speed and directions were highly space-variable within the site basin. The variable wind characteristics implies that the Gaussian dispersion model such ISC3 and AERMOD are not appropriate and the unsteady-sate Lagrangian model such as CALPUFF is preferable. CALPUFF model was applied to assess air quality impact of new sources. The new sources were those for individual and group heating facilities as well as the traffic increases. The results showed that the estimated concentrations of CO and $SO_2$ pollutants by summing the impact concentration of new sources by the dispersion model and the ambient air concentrations by the site measurements were acceptable but those of PM-10 and $NO_2$ would violate ambient air quality standards at several locations due to high ambient air concentrations. It is recommended that the emission reductions near the site should be enforced to improve the ambient air quality.

• 한국항공우주학회지
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• 제44권6호
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• pp.530-536
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• 2016

고-신뢰도 모델을 이용한 조종성 평가 시뮬레이션 환경은 비행제어시스템의 설계/평가에 필수적으로 요구된다. 한국항공우주산업(주)에서는 소형민수헬기 핵심기술 개발과 관련하여 자동비행조종장치 소프트웨어 개발과제를 수행 중에 있으며 제어법칙 설계를 위한 비행동역학 모델 및 해석을 위해 상용 도구인 FLIGHTLAB을 이용하고 있다. 본 연구에서는 기존에 개발된 레거시 시뮬레이터를 FLIGHTLAB 모델과 연동하고 이를 조종성 평가에 활용한 내용을 다루었다. 본 논문에서는 외부 연동을 위한 FLIGHTLAB 모델의 설정, 연동 프로그램 개발 및 연동 방안에 대한 내용을 수록하였다. 또한 본 논문에서는 레거시 시뮬레이터와의 연동을 통해 ADS-33E-PRF의 호버 및 pirouette MTE 기동비행을 수행하고 평가 결과를 수록하였다.

• Investigative Magnetic Resonance Imaging
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• 제23권2호
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• pp.114-124
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• 2019

Purpose: We investigate biases in the assessments of left ventricular function (LVF), by compressed sensing (CS)-cine magnetic resonance imaging (MRI). Materials and Methods: Cardiovascular cine images with short axis view, were obtained for 8 volunteers without CS. LVFs were assessed with subsampled data, with compression factors (CF) of 2, 3, 4, and 8. A semi-automatic segmentation program was used, for the assessment. The assessments by 3 CS methods (ITSC, FOCUSS, and view sharing (VS)), were compared to those without CS. Bland-Altman analysis and paired t-test were used, for comparison. In addition, real-time CS-cine imaging was also performed, with CF of 2, 3, 4, and 8 for the same volunteers. Assessments of LVF were similarly made, for CS data. A fixed compensation technique is suggested, to reduce the bias. Results: The assessment of LVF by CS-cine, includes bias and random noise. Bias appeared much larger than random noise. Median of end-diastolic volume (EDV) with CS-cine (ITSC or FOCUSS) appeared -1.4% to -7.1% smaller, compared to that of standard cine, depending on CF from (2 to 8). End-systolic volume (ESV) appeared +1.6% to +14.3% larger, stroke volume (SV), -2.4% to -16.4% smaller, and ejection fraction (EF), -1.1% to -9.2% smaller, with P < 0.05. Bias was reduced from -5.6% to -1.8% for EF, by compensation applied to real-time CS-cine (CF = 8). Conclusion: Loss of temporal resolution by adopting missing data from nearby cardiac frames, causes an underestimation for EDV, and an overestimation for ESV, resulting in underestimations for SV and EF. The bias is not random. Thus it should be removed or reduced for better diagnosis. A fixed compensation is suggested, to reduce bias in the assessment of LVF.

• 환경영향평가
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• 제29권1호
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• pp.61-77
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• 2020

현재 국내 주요 공공수역은 국가차원 아래 체계적인 물환경 관리가 되어왔고, 특히 하천, 호소 등 생태계의 실태파악 및 대응을 위해 지속적인 모니터링 및 관리가 이루어져 왔다. 그 중, 수질측정망은 수질측정 주기가 8일에서 한 달 주기로 조사되는 반면, 자동측정망의 경우, 실시간 자료를 수집함으로써 일 데이터 자료를 제공하고 있다. 따라서 측정망 자료를 활용하여 동일한 수질항목에 대해 추세변화를 분석하고 통계적 방법을 통해 비교하였다. Mann-kendall test 결과 Water Temperature (WT)와 DO는 모든 지점이 통계적으로 유의하지 않은 것으로 확인되었고, 특히 TOC에서는 4개 지점, TN은 2개 지점, TP는 3개 지점, Water Temperature (WT)는 7개 지점, pH는 2개 지점, EC는 5개 지점, DO는 6개 지점에서 동일한 추세 경향을 보였다. LOWESS 분석 결과, TOC와 pH의 측정망 결과는 서로 다른 추세를 보이는 것으로 분석되었다. 지점별, 항목간 상관관계 분석결과에 따르면 안동댐하류-안동1 지점에서는 TP, 도개-산곡지점에서는 TOC, 고령(자동)-고령 지점에서는 pH, 적포-창녕 지점에서는 TP, 감천-감천2-1 지점에서는 TN, TP, pH, EC, DO 항목을 제외하고 나머지 항목에서 유의한 양의 상관관계를 보이는 것으로 분석되었다. 그리고 신암-상주2 지점과 남강-남강4 지점에서는 모든 항목에서 유의한 양의 상관관계를 나타내는 것으로 분석되었다.

• 한국수학교육학회지시리즈A:수학교육
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• 제63권2호
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• pp.165-186
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• 2024

학교 현장과 대규모 평가에서 서술형 문항 도입을 지원하기 위한 방안 중 하나로 인공지능 기반의 자동 채점 기술이 주목받고 있음에도 불구하고, 수학 교과에서는 타 교과에 비해 이에 대한 기초 연구가 부족한 상황이다. 이에 본 연구는 중학교 1학년 수학 서술형 문항 두 개를 대상으로 랜덤 포레스트 알고리즘을 활용하여 자동 채점 모델을 개발하고 그 성능을 평가하였다. 연구 결과, 두 문항에 대한 최종 모델의 평가요소별 정확도는 각각 0.95-1.00, 0.73-0.89의 범위로 나타났으며, 이는 타 교과에 비해 상대적으로 높은 수준이다. 데이터의 양을 고려한 평가 범주 설정의 중요성을 확인하였으며, 수학 교육전문가에 의한 텍스트 전처리와 데이터 특성에 맞는 벡터화 방법의 선택이 모델의 성능 및 해석 가능성을 향상시키는 데 기여하였다. 또한, 현실적 한계로 인해 균형적인 데이터 수집이 어려운 상황에서 오버샘플링이 성능을 보완하는 유용한 방법임을 확인하였다. 교육적 활용도를 높이기 위해, 랜덤 포레스트 기반 모델에서 도출된 특성 중요도를 활용하여 피드백과 같이 교수-학습에 유용한 정보를 생성하는 추가 연구가 필요하다. 본 연구는 수학 서술형 자동 채점에 관한 기초 연구로서 의미가 있으며, 인공지능 전문가와 수학교육 전문가 간의 긴밀한 협력을 통해 다양한 후속 연구가 진행될 필요가 있다.

• 대한의용생체공학회:의공학회지
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• 제41권4호
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• pp.147-153
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• 2020

This study was to evaluate the usability of self-developed phantom for evaluating automatic exposure control (AEC) using three-dimensions (3D) printer. 3D printer of fused deposition modeling (FDM) type was utilized to make the self-developed AEC phantom and image acquisitions were conducted by two different type of scanners. The self-developed AEC phantom consisted of four different size of portions. As a result, two types of phantom (pyramid and pentagon shape) were created according to the combination of the layers. For evaluating the radiation dose with the two types of phantom, the values of tube current, computed tomography dose index volume (CTDIvol), and dose length product (DLP) were compared. As a result, it was confirmed that the values of tube current were properly reflected according to the thickness, and the CTDIvol and DLP were not significantly changed regardless of AEC functions of different scanners. In conclusion, the self-developed phantom by using 3D printer could assess whether the AEC function works well. So, we confirmed the possibility that a self-made phantom could replace the commercially expensive AEC performance evaluation phantom.