• Title/Summary/Keyword: Automated Evaluation

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A Novel, Deep Learning-Based, Automatic Photometric Analysis Software for Breast Aesthetic Scoring

  • Joseph Kyu-hyung Park;Seungchul Baek;Chan Yeong Heo;Jae Hoon Jeong;Yujin Myung
    • Archives of Plastic Surgery
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    • v.51 no.1
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    • pp.30-35
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    • 2024
  • Background Breast aesthetics evaluation often relies on subjective assessments, leading to the need for objective, automated tools. We developed the Seoul Breast Esthetic Scoring Tool (S-BEST), a photometric analysis software that utilizes a DenseNet-264 deep learning model to automatically evaluate breast landmarks and asymmetry indices. Methods S-BEST was trained on a dataset of frontal breast photographs annotated with 30 specific landmarks, divided into an 80-20 training-validation split. The software requires the distances of sternal notch to nipple or nipple-to-nipple as input and performs image preprocessing steps, including ratio correction and 8-bit normalization. Breast asymmetry indices and centimeter-based measurements are provided as the output. The accuracy of S-BEST was validated using a paired t-test and Bland-Altman plots, comparing its measurements to those obtained from physical examinations of 100 females diagnosed with breast cancer. Results S-BEST demonstrated high accuracy in automatic landmark localization, with most distances showing no statistically significant difference compared with physical measurements. However, the nipple to inframammary fold distance showed a significant bias, with a coefficient of determination ranging from 0.3787 to 0.4234 for the left and right sides, respectively. Conclusion S-BEST provides a fast, reliable, and automated approach for breast aesthetic evaluation based on 2D frontal photographs. While limited by its inability to capture volumetric attributes or multiple viewpoints, it serves as an accessible tool for both clinical and research applications.

S/W Development of Flying Qualities Evaluation in Virtual Flight Test using MATLAB GUI (GUI 기반 가상모의시험 비행성 평가 S/W 개발)

  • Cho, Seung-Gyu;Rhee, Ihn-Seok;Kim, Byoung-Soo
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.41 no.1
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    • pp.61-69
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    • 2013
  • In an evaluation process of aircraft flying qualities, a clear and concise application interface is important since an evaluation process requires numerous repeated evaluation. This flight evaluation program have implemented efficient flight evaluation user interface along with changed trim condition interface and composed of comprehensive evaluation interface have mounted all automated FQ evaluation modules that was selected to be compose of 14 items in respect of an unmanned fixed-wing aircraft. Accordingly when it is necessary to design the flight control system as well as to develop a FQ considered aircraft, this S/W can be utilized as a tool that is a useful test evaluation S/W with scalability and enable to reduce the time and the cost of verification and evaluation process.

Evaluation Category Selection For Automated Essay Evaluation of Korean Learner (한국어 학습자 작문 자동 평가를 위한 평가 항목 선정)

  • Kwak, Yong-Jin
    • Annual Conference on Human and Language Technology
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    • 2017.10a
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    • pp.270-271
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    • 2017
  • 본 연구는 한국어 학습자 작문의 자동 평가 시스템 개발의 일환으로, 자동 평가 결과에 대한 설명과 근거가 될 수 있는 평기 기준 범주를 선정하기 위한 데이터 구축과 선정 방법을 제시한다. 작문의 평가 기준의 영역과 항목은 평가체계에 대한 이론적 연구에 따라 다양하다. 이러한 평가 기준은 자동 평가에서는 식별되기 어려운 경우도 있고, 각각의 평가 기준이 적용되는 작문 오류의 범위도 다양하다. 그러므로 본 연구에서는 자동 평가 기준 선정의 문제는 다양한 평가 기준에 중 하나를 선정하는 분류의 문제로 보고, 학습데이터를 구축, 기계학습을 통해 자동 작문 평가에 효과적인 평가 기준을 선정 가능성을 제시한다.

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Development of Personal-Credit Evaluation System Using Real-Time Neural Learning Mechanism

  • Park, Jong U.;Park, Hong Y.;Yoon Chung
    • The Journal of Information Technology and Database
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    • v.2 no.2
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    • pp.71-85
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    • 1995
  • Many research results conducted by neural network researchers have claimed that the classification accuracy of neural networks is superior to, or at least equal to that of conventional methods. However, in series of neural network classifications, it was found that the classification accuracy strongly depends on the characteristics of training data set. Even though there are many research reports that the classification accuracy of neural networks can be different, depending on the composition and architecture of the networks, training algorithm, and test data set, very few research addressed the problem of classification accuracy when the basic assumption of data monotonicity is violated, In this research, development project of automated credit evaluation system is described. The finding was that arrangement of training data is critical to successful implementation of neural training to maintain monotonicity of the data set, for enhancing classification accuracy of neural networks.

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A Study on the Evaluation of Automation & Flexibility in Assembly Systems (조립시스템의 자동화 및 유연성 평가방법에 대한 연구)

  • Mok, Hak-Su;Gang, Won-Cheol
    • Journal of the Korean Society for Precision Engineering
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    • v.9 no.2
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    • pp.69-80
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    • 1992
  • This paper deals with the evaluation methods for flexible automated assembly systems based on characteristics of automation and flexibility. In this study, the degrees of automation and flexibility are calculated quantitatively as the means of evaluating assembly systems. The degree of automation is grasped wheter the detailed assembly flexibility can be calculated indirectly14 by the estimation of cost and time which are caused to adapt the changed environment of the assembly system. As a case study, an assembly system is evaluated for showing the procedures of the developed method.

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Automated data interpretation for practical bridge identification

  • Zhang, J.;Moon, F.L.;Sato, T.
    • Structural Engineering and Mechanics
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    • v.46 no.3
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    • pp.433-445
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    • 2013
  • Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

Requirements Validation Plan for korean Rubber-Tired AGT System (한국형 고무차륜 경량전철시스템에 대한 요구사항 검증계획)

  • Mok, Jae-Gyun;Lee, An-Ho;Han, Seok-Yun
    • 시스템엔지니어링워크숍
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    • s.1
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    • pp.27-31
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    • 2003
  • This study is in a part of requirements validation plan for korean rubber-tired AGT system on test track. The AGT system is consisted subsystems as vehicle, signalling, communication, power distribution and infrastructure for rubber tire running on track. The subsystems will be installed and integrated on test track till next year for test and evaluation. This paper shows overview for test and evaluation in terms of system requirements and its validation classification, test track configuration, measuring system requirements and its configuration. The whole process of system integration and its validation will be controlled by means of KMS including documentation.

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DEVSIF Composer: A Synthesis Tool for Fast Interpretation of Simulation Models

  • Lee, Wan-Bok
    • Journal of information and communication convergence engineering
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    • v.6 no.1
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    • pp.59-63
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    • 2008
  • The methods or algorithms which can accelerate simulation speed became of great importance, as the modeling and simulation methodology for discrete event systems is used in many areas such as model validation/verification and performance evaluation. This paper proposes a tool named, DEVSIF composer. The tool is made of an automated compiled simulation technology and it builds a new composed model which can be executed much fast by composing the component models together. Models are described by our new specification language DEVSIF, which is compatible with object-oriented language and supports representation of a hierarchical model structure. Experimental results demonstrates that DEVSIF composer enhances the simulation speed of a transformed DEVS model 5 times faster than that of the original ones in average.

A study on capability evaluation and machine selection in RP processes (쾌속 조형 공정의 성능 평가 및 선정에 관한 연구)

  • 신행재;변홍석;이관행
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2001.04a
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    • pp.37-40
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    • 2001
  • This paper describes the selection and evaluation of RP processes. Major rapid prototyping processes such as SLS, SLA, FDM and LOM, which are wide spread in use are selected. A test part, which includes various primitives, is designed in order to evaluate these RP processes. Measurement of the test part is automated by using a CMN program. To visualize and analyze measured data, Microsoft Access and Visual C++ are used. Also, from measured data obtained, TOPSIS, one of the decision making methods, and Shannon Entropy is used to select an appropriate RP process for specific application.

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모멘트 생성 함수 기법을 이용한 유연 제조 셀의 해석적 성능 평가

  • 박용수;김종원
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.04a
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    • pp.506-511
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    • 1996
  • The performance evaluation of flexible manufacturing systems or cells at the stages of design and planning is one of important issues in manufacturing. For that reason, Guo has presented an approachbased on moment generating function and generalized stochastic PetriNets for performance analysis. In this paper, Buo's approach is extended tothe cases of flexible manufacturing cell including one machining center with a local buffer, AS/RS(Automatic Storage and Retrieval System), set-up station and AGV(Automated Guided Vehicle). Then the performance measures from this approach is compared with simulation. The major advantage ofthis method over existing performance evaluation methods is the ability to compute analytic solutions for performance measures.

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