• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회
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• pp.658-663
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• 2010

Recently the most of deep foundation were socketed into weathered rock or soft rock to carry large foundation loads. The end bearing behavior of piles socketed in rock is generally dependent on the rock mass conditions with discontinuities and rock strength. Therefore, it is very important that the estimating rock classification with relation of TCR, RQD and unpredicted rock condition. In this study, the construction failure example of drilled shaft due to mistaking to estimate the rock classification on penetration were analyzed in site, so we hope to discuss problems of determining the rock socketed length of drilled shaft on construction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1743-1758
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• 2023

Automatic modulation classification is a critical algorithm for non-cooperative communication systems. This paper addresses the challenging problem of closed-set and open-set signal modulation classification in complex channels. We propose a novel approach that incorporates a self-learning filter and center-loss in Deep Residual Shrinking Networks (DRSN) for closed-set modulation classification, and the Opendistance method for open-set modulation classification. Our approach achieves better performance than existing methods in both closed-set and open-set recognition. In closed-set recognition, the self-learning filter and center-loss combination improves recognition performance, with a maximum accuracy of over 92.18%. In open-set recognition, the use of a self-learning filter and center-loss provide an effective feature vector for open-set recognition, and the Opendistance method outperforms SoftMax and OpenMax in F1 scores and mean average accuracy under high openness. Overall, our proposed approach demonstrates promising results for automatic modulation classification, providing better performance in non-cooperative communication systems.

• Korean Chemical Engineering Research
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• 제48권4호
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• pp.483-489
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• 2010

본 연구에서는 화상분석(image analysis)에 기반한 소프트 센서를 설계하고, 이를 색상-질감 특성을 가진 제품의 외관품질 자동분류에 적용하였다. 색상과 질감(texture)을 동시에 가진 화상을 분석하기 위해 다중해상도 다변량 화상분석(Multiresolutional Multivariate Image Analysis, MR-MIA) 기법을 이용하였으며, 자동 분류를 위한 감독 학습법(supervised learning)으로는 Fisher의 판별분석(Fisher's discriminant analysis)을 사용하였다. 잠재변수법의 하나인 Fisher의 판별분석을 사용하였기 때문에, 제품의 외관을 서로 다른 불연속적인 부류로의 분류할 수 있을 뿐 아니라, 연속적인 외관 변화를 일관적이고 정량적으로 추정함은 물론, 외관의 특성 해석 또한 가능하였다. 이 방법은 인조대리석 제조 공정에서 중간 및 최종 제품의 외관 품질을 자동으로 분류하는 데에 성공적으로 적용되었다.

• 전자공학회논문지SC
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• 제37권6호
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• pp.50-63
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• 2000

본 논문에서는 소프트 컴퓨팅 기법을 이용한 새로운 근전도 신호 패턴 분류 방법을 제안한다. 재활 로봇시스템에서 기존에 사용되었던 여러 가지 입력 장치(음성, 레이저 포인터, 키패드, 3차원 입력기 등)에 비해 근전도 신호를 이용한 방식이 가지는 장점을 서술한다. 기존의 근전도 신호 분류 방법의 문제점인 사용자 의존성을 줄이기 위해 제안한 사용자 독립적인 특징 선택 방법에 대해 상술한다. 선택된 특징 집합을 이용하여 퍼지 패턴 분류기 및 퍼지 최대-최소 신경망을 구성하여 학습 전(퍼지 패턴 분류기)과 학습 후(퍼지 최대-최소 신경망)에 각각 83%와 90%의 분류 성공률을 얻어 제안된 방법의 유용성을 확인할 수 있었다.

• 대한치과의사협회지
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• 제48권9호
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• pp.670-679
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• 2010

Esthetic demands for dental treatment are increasing every day. The interdisciplinary relationship of the restorative treatment, periodontal therapy and other treatments such as endodontics, orthodontics and so on is more emphasized nowadays to reconstruct the hard and soft tissue foundation for the esthetic restorative treatment. This article will focus on the periodontal plastic surgery for esthetic restorative treatment. These followings will be discussed. 1. Understand the relationship between teeth and gingival scaffold for esthetics 2. Discuss the classification and treatment of gummy smile 3. Recognize the gingival margin irregularities by gingival recession and how to achieve the harmonic soft tissue margins 4. describe the hard and soft tissue augmentation for ridge augmentation.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2002년도 추계학술발표논문집 (하)
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• pp.2375-2378
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• 2002

우리 나라의 건설산업은 건설시장 개방으로 외국기업과의 경쟁체제 돌입이 불가피하고, 건설정책과 각종 행정규제의 급변으로 대응전략 수립이 불가피하다. 또한, 건설정보의 지식관리체제의 부재와 건설지식관리시스템의 미구축, 그리고 정보 공유와 공공정보 공개 마인드의 미성숙으로 인하여 적극적인 대처가 불가능한 실정이다. 따라서 본 논문에서는 건설업체, 설계사무소, 감리업체 등이 안고 있는 제반 현황을 고찰하여 건설지식관리시스템 구현방안을 제시 이를 건설지식관리시스템에 적용하여 국내 건설분야 건설지식 맵을 도출하고 환용 실태를 파악하고, 해외 파국에서 지식관리의 활용관련 자료를 분석하여 국제기준 및 국내 건설환경에 적합한 지식 맵 및 분류체계 적용한 시스템 개발 건설업체에 적용하였다.

• 한국농공학회지
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• 제45권2호
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• pp.96-106
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• 2003

134 Dutch cone (mechanical cone) and 9 piezocone (electronic cone) penetration tests have been performed in the southwestern part of Korea. In general, Dutch cone results may be different from that of piezocone due to the difference in structure of the cones. 6 Dutch cone and piezocone test data which were obtained at the same point respectively, were analyzed and plotted in soil classification chart proposed by Robertson et. al.(1986, 1990). Cone factors of Dutch cone and piezocone test empirically have been determined using laboratory and field vane test results. Using this cone factors, it was shown that there was good correlation between shear strength estimated using cone resistance and that of laboratory test and field vane tests. It was found that there was a good correlation between cone resistance from Dutch cone and that from piezocone. Relationship formula was also suggested. Dutch cone test provides a useful means for stratigraphic profiling in large project and has some advantage over piezocone in particular situations, such as very soft clay ground and dredged area.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2002년도 가을 학술발표회 논문집
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• pp.237-244
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• 2002

A comparative study of 134 mechanical (Dutch cone) and 9. electronic cone (Piezocone) penetration data from the southern part of Korea has been performed. In general, Dutch cone results may be different from piezocone results due to the difference in structure of the cones. Cone penetrometer test data were analyzed and plotted in soil classification chart proposed by Robertson et. al.(1986,1990) Cone factors of Dutch cone and piezocone test have empirically been determined using laboratory and field vane test results. Using this cone factors, it was shown that there was good correlation between shear strength estimated using cone resistance and that of laboratory test and field vane tests. It was found that there was a good correlation between cone resistance from Dutch cone and that from piezocone. Dutch cone test provides a useful means for stratigraphic profiling in large project and has some advantage over piezocone in particular situations, such as very soft clay ground and dredged area.

• 한국컴퓨터정보학회논문지
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• 제23권4호
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• pp.147-153
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• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

• Structural Engineering and Mechanics
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• 제91권3호
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• pp.279-289
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• 2024

The purpose of this study is to represent a useful alternative for the preliminary seismic vulnerability assessment of existing reinforced concrete buildings by introducing a statistical approach employing the binary logistic regression technique. Two different predictive statistical models, namely full and reduced models, were generated utilizing building characteristics obtained from the damage database compiled after 1999 Düzce earthquake. Among the inspected building parameters, number of stories, overhang ratio, priority index, soft story index, normalized redundancy ratio and normalized lateral stiffness index were specifically selected as the predictor variables for vulnerability classification. As a result, normalized redundancy ratio and soft story index were identified as the most significant predictors affecting seismic vulnerability in terms of life safety performance level. In conclusion, it is revealed that both models are capable of classifying the set of buildings being severely damaged or collapsed with a balanced accuracy of 73%, hence, both are able to filter out high-priority buildings for life safety performance assessment. Thus, in this study, having the same high accuracy as the full model, the reduced model using fewer predictors is proposed as a simple and viable classifier for determining life safety levels of reinforced concrete buildings in the preliminary seismic risk assessment.