• Journal of the Korean Wood Science and Technology
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• 제43권1호
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• pp.25-35
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• 2015

본 연구에서는 국산 침엽수재의 육안 등급구분과 허용응력설정에 관한 국내의 학술논문을 정리하였다. 국립산림과학원 고시(KFRI 1995-27, KFRI 2000-39, KFRI 2007-3, KFRI 2009-1)를 활용하여 국산 낙엽송재의 육안 등급 구분한 연구를 비교한 결과 등급구분 비율이 연구자마다 상이했다. 보다 신뢰할 수 있는 등급구분 분류를 위해서 공증된 목재이용 기관에서 숙련된 연구자에 의한 등급구분을 시행하여야 할 것으로 사료된다. 허용응력설정에 관한 연구를 고찰한 결과, 연구자 마다 허용응력산출 방법이 ASTM D 245, KS F 2152, JAS 1990으로 모두 상이했다. 이는 침엽수 구조용재(KS F 3020)에서 기준허용응력을 제시하고 있지만 허용응력을 산출하는 명확한 방법이 제시되어 있지 않기 때문인 것으로 나타났다. 따라서 공식적인 허용응력 결정방법이 제정되어야 할 것으로 사료된다.

• 한국멀티미디어학회논문지
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• 제25권10호
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• pp.1386-1394
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• 2022

As consumption of high-quality fruits increases and sales and packaging units become smaller, the demand for automatic fruit grading systems is increasing. Compared to other crops, the quality of fruit is determined by visual characteristics such as shape, color, and scratches, rather than just physical size and weight. Accordingly, this study presents a CNN model that can effectively extract and classify the visual features of fruits and a perceptron that classifies fruits using physical features, and proposes a stacking ensemble model that can effectively combine the classification results of these two neural networks. The experiments with AI Hub public data show that the stacking ensemble model is effective for grading fruits. However, the ensemble model does not always improve the performance of classifying all the fruit grading. So, it is necessary to adapt the model according to the kind of fruit.

• Korean Journal of Radiology
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• 제24권4호
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• pp.284-293
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• 2023

Objective: To validate a simplified ordinal scoring method, referred to as modified length-based grading, for assessing coronary artery calcium (CAC) severity on non-electrocardiogram (ECG)-gated chest computed tomography (CT). Materials and Methods: This retrospective study enrolled 120 patients (mean age ± standard deviation [SD], 63.1 ± 14.5 years; male, 64) who underwent both non-ECG-gated chest CT and ECG-gated cardiac CT between January 2011 and December 2021. Six radiologists independently assessed CAC severity on chest CT using two scoring methods (visual assessment and modified length-based grading) and categorized the results as none, mild, moderate, or severe. The CAC category on cardiac CT assessed using the Agatston score was used as the reference standard. Agreement among the six observers for CAC category classification was assessed using Fleiss kappa statistics. Agreement between CAC categories on chest CT obtained using either method and the Agatston score categories on cardiac CT was assessed using Cohen's kappa. The time taken to evaluate CAC grading was compared between the observers and two grading methods. Results: For differentiation of the four CAC categories, interobserver agreement was moderate for visual assessment (Fleiss kappa, 0.553 [95% confidence interval {CI}: 0.496-0.610]) and good for modified length-based grading (Fleiss kappa, 0.695 [95% CI: 0.636-0.754]). The modified length-based grading demonstrated better agreement with the reference standard categorization with cardiac CT than visual assessment (Cohen's kappa, 0.565 [95% CI: 0.511-0.619 for visual assessment vs. 0.695 [95% CI: 0.638-0.752] for modified length-based grading). The overall time for evaluating CAC grading was slightly shorter in visual assessment (mean ± SD, 41.8 ± 38.9 s) than in modified length-based grading (43.5 ± 33.2 s) (P < 0.001). Conclusion: The modified length-based grading worked well for evaluating CAC on non-ECG-gated chest CT with better interobserver agreement and agreement with cardiac CT than visual assessment.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1993년도 Proceedings of International Conference for Agricultural Machinery and Process Engineering
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• pp.1243-1253
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• 1993

Visual features of a mushroom(Lentinus Edodes L) are critical in sorting and grading as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. Though actions involved in human grading looks simple, a decision making undereath the simple action comes form the results of the complex neural processing of the visual image. And processing details involved in the visual recognition of the human brain has not been fully investigated yet. Recently, however, an artificial neural network has drawn a great attention because of its functional capability as a partial substitute of the human brain. Since most agricultural products are not uniquely defined in its physical properties and do not have a well defined job structure, a research of the neuro-net based human like information processing toward the agricultural product and processing are widely open and promising. In this pape , neuro-net based grading and sorting system was developed for a mushroom . A computer vision system was utilized for extracting and quantifying the qualitative visual features of sampled mushrooms. The extracted visual features and their corresponding grades were used as input/output pairs for training the neural network and the trained results of the network were presented . The computer vision system used is composed of the IBM PC compatible 386DX, ITEX PFG frame grabber, B/W CCD camera , VGA color graphic monitor , and image output RGB monitor.

• Journal of the Korean Wood Science and Technology
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• 제38권6호
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• pp.470-479
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• 2010

본 연구는 국산 백합나무의 육안 특성을 이용한 등급구분과 실대재 휨시험을 실시하여 이들의 강도 및 강성의 특성 구명을 통해 국산 백합나무의 구조용재로서의 이용가능성을 평가하였다. 활엽수의 육안등급구분규정이 국내에 존재하지 않아 몇몇 활엽수 제재목에 대한 규정을 포함하고 있는 NSLB (Northern Softwood Lumber Bureau) 규정에 따라 육안등급을 수행하였다. 수행 결과로부터 계산된 백합나무의 휨허용응력을 NDS (National Design Specification)에 제시된 설계치와의 비교를 통해 국산 백합나무가 충분한 강도성능을 가지고 있음을 확인 하였다. 또한 백합나무 제재목을 국내 등급규정에 따라 허용응력을 산정하여 이를 적용하는 데 있어 타당성을 평가하기 위해 국내 국립산림과학원 고시에 따라 육안등급을 수행하였다. 백합나무는 국립산림과학원 고시에 제시된 비중에 따른 수종군 중 소나무류에 포함되었다. 적합분포로 판단된 웨이블분포에 따른 휨허용응력은 1등급 10.0 MPa, 2등급 7.4 MPa, 3등급 4.1 MPa로 제시된 설계치보다 높은 값이 나타났다. 본 실험의 결과로부터 국내 규정에 준하여 국산 백합나무를 구조용재로 이용이 가능함을 확인하였다. 국산 백합나무의 휨탄성계수는 국내외 기준 설계치를 모두 충족시키지 못하였으나, 국산백합나무를 구조용재로 이용하기 위해 본 실험을 통해 얻어진 백합나무의 평균 휨탄성계수를 제안하되, 1등급과 2등급은 9,000 MPa, 3등급 이하는 8,000 MPa를 적용 하는 것이 타당한 것으로 보인다.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.773-779
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• 1996

Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

• 생물환경조절학회지
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• 제3권1호
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• pp.42-51
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• 1994

대다수 농산물과 마찬가지로 건조표고의 등급판정은 외관특징에 주로 의존한다. 표고 갓의 전후면에 걸친 복잡하고 다양한 외관특징들로 인하여 표고의 등급판정은 임의로 추출한 표고샘플에 대하여 전문가가 수작업으로 판정하고 있으며, 선별작업 역시 전적으로 수작업에 의존하고 있다. 단순한 반복작업으로 보이는 농산물의 등급판정은 사실 시각과 촉각을 위시한 고도의 감각신경계를 통하여 상호 복잡하게 얽혀 들어오는 정보를 지능적으로 처리하는 고기능의 작업이다. 농산물의 경우, 외관특성을 비롯한 물성은 종류별로 그 경계치를 일괄적으로 명확하게 규정할 수 없기 때문에 대개는 오차를 포함한 통계적 접근에 의하여 규정하고 있다. 따라서 농산작업에 있어서는 농산물 물성이 갖는 모호성을 효율적으로 처리할 수 있는 가변적인 작업구조 및 정보처리가 필수적으로 요구된다. 본 연구에서는 인간 뇌의 정보처리 기능을 부분적으로 구현할 수 있는 인공신경회로망을 컴퓨터 시각 시스템에 적용하여 단순 기하도형의 분류 및 표고의 등급판정을 성공적으로 수행하였다. 회로망 입력으로는 컴퓨터시각 시스템을 이용하여 건조표고의 정성적 외관특징을 자동으로 추출한 후 정량화한 특징점 값들을 이용하였다. 신경회로망의 학습은 표본 추출한 등급표고와 이들의 정량적 특징점 값들을 입출력 쌍으로 하여 수행하였다. 학습한 회로망의 등급판정 성능시험은 표본추출한 미지의 표고에 대한 컴퓨터 영상 특징점 값들을 입력하여 수행하였다.

• Journal of Biosystems Engineering
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• 제26권2호
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• pp.147-154
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• 2001

In Korea and Japan, dried oak mushrooms are classified into 12 to 16 different categories based on its external visual quality. And grading used to be done manually by the human expert and is limited to the randomly sampled oak mushrooms. Visual features of dried oak mushrooms dominate its quality and are distributed over both sides of the gill and the cap. The 2nd prototype computer vision based automatic grading and sorting system for dried oak mushrooms was developed based on the 1st prototype. Sorting function was improved and overall system for grading was simplified to one stage grading instead of two stage grading by inspecting both front and back sides of mushrooms. Neuro-net based side(gill or cap) recognition algorithm of the fed mushroom was adopted. Grading was performed with both images of gill and cap using neural network. A real time simultaneous discharge algorithm, which is good for objects randomly fed individually and for multi-objects located along a series of discharge buckets, was developed and implemented to the controller and the performance was verified. Two hundreds samples chosen from 10 samples per 20 grade categories were used to verify the performance of each unit such as feeding, reversing, grading, and discharging unites. Test results showed that success rates of one-line feeding, reversing, grading, and discharging functions were 93%, 95%, 94%, and 99% respectively. The developed prototype revealed successful performance such as the approximate sorting capability of 3,600 mushrooms/hr per each line i.e. average 1sec/mushroom. Considering processing time of approximate 0.2 sec for grading, it was desired to reduce time to reverse a mushroom to acquire the reversed surface image.

• Journal of the Korean Wood Science and Technology
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• 제39권1호
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• pp.1-7
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• 2011

최근 재종에 따른 등급별 품질기준 및 결점의 측정방법이 개정되었다. 외국 규격과의 호환성을 비롯하여 보다 현실에 맞고 적용하기 쉽게 개선하기 위해서는 개정에 따른 구조용제재의 구조성능에 대한 고찰이 필요하다. 본 연구에서는 국산 침엽수재 중 대표적으로 사용되는 낙엽송과 잣나무를 대상으로 구조용제재 규정 개정에 따른 휨강도 성능을 구명하였다. 개정된 등급구분규정은 구조재로 적합한 1, 2등급의 비율을 높인다는 측면과 1, 2 등급과 3등급 이하 등급과의 구분을 보다 명료하게 한다는 점에서 개정전의 등급구분에 비해 효과적인 것으로 나타났고, 각 등급별 5% 하한치와 허용응력은 전체적으로 감소하였다. 특히, 건축구조기준(KBC 2009)에서 제시하고 있는 기준허용응력은 실대재 실험값에 비해 더 낮은 값을 제시하고 있으므로 보다 정확한 허용응력의 사용과 효율적인 구조설계를 위해서는 기준허용응력의 개선 또한 필요할 것으로 판단된다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.3121-3121
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• 2001

The factors involved in development of electronic grading systems for commodities such as grains and seeds include determination of the factors that influence the end-product utilization of the commodities, and the degree to which these can be predicted by electronic methods. The possibility of exchanging existing methods of grading by electronic methods has to be considered. The respective merits of techniques such as Digital Imaging and Near-infrared (NIR) spectroscopy have to be considered. Digital Imaging is a computerized version of visual inspection and grading, whereas NIR spectroscopy has the potential for grading on the basis of composition and functionality, Selection and evaluation of NIR instruments is an important factor, as are sampling and sample presentation to electronic instruments, and particularly the engineering involved in sample presentation. Sample assembly, and software for calibration development are described in the presentation. Finally the impact and implications of introduction of electronic grading are discussed with particular attention to marketing of the commodities.