• 제목/요약/키워드: learning curve

검색결과 424건 처리시간 0.033초

한국 정유산업의 학습곡선과 생산성에 관한 연구 (A Study on the Learning Curve and Productivity)

  • 이종철;강규철
    • 산업경영시스템학회지
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    • 제20권43호
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    • pp.175-195
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    • 1997
  • The learning curve has an important effect the growth of corporation. But, in Korea, the study and inference on the learning rate of each industry are unprepared, and so, Korean industires have difficult in productivity and cost. At this point, this study infers the learning rate of the oil industries and investigates the productivity and growth of them. In conclusion, this study presents the direction of the oil industries' development. With the intention of this objects, this study seizes the status which is concerned the total quantity, the operating rate, the plant capacity, the indicators concerning productivity, the investment of R & D and the scales, and then, infers and verifies the relevancy in connection with the learning rate. In the oil industry, the average rate of learning is 65.96% from 1982 to 1994 which the total quantity and the average operation time are used to infer the rate. To observe the low rate within a same period of time, this study takes the consequences that the learning rate is almost indentical with them each year. This steady state is caused by a difference between the employee and the decision maker about the acquirement and assimiliated of technology. When the high-quality technologies posses the environment to applicate in the scene of labor with them, this technology applies to the productivities. As the learning rate increases, the productivity has more effectiveness. The result of analysis about the effectiveness of the learning rate follows that the R & D unfoldes to exist and does not contribute to the growth of the oil industry. To analyze the variables of the growth, such as the learning rate, the investement of R & D, the operating rate and the gross value added to property, plant and equipment, the model is established and examined. The business strategy in the oil industry must be developed to achive the internal growth as well as the external.

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점진적 중심 갱신을 이용한 deep support vector data description 기반의 온라인 비정상 탐지 알고리즘 (Online anomaly detection algorithm based on deep support vector data description using incremental centroid update)

  • 이기배;고건혁;이종현
    • 한국음향학회지
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    • 제41권2호
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    • pp.199-209
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    • 2022
  • 일반적인 비정상 탐지 알고리즘은 사전 데이터를 이용하여 학습된다. 따라서 시간에 따른 정상 데이터의 특징이 변화되는 경우에 기존의 배치 학습 기반 알고리즘의 성능 저하가 불가피하다. 본 논문에서는 정상 데이터의 점진적 특징 변화를 고려할 수 있는 온라인 비정상 탐지 알고리즘을 제안한다. 제안하는 알고리즘은 단일 클래스 분류 모델에 기반하며 오프라인 및 온라인 단계의 학습 과정을 포함한다. 제안된 알고리즘의 오프라인 학습 단계에서는 사전 데이터가 잠재 공간의 중심에 근접하도록 학습하고, 이후 온라인 학습단계에서는 신규 데이터에 의한 점진적 잠재 공간의 중심을 갱신하고, 갱신된 중심을 기준으로 계속 학습을 진행한다. 공개된 수중 음향 데이터를 이용한 실험결과 제안된 온라인 비정상 탐지 알고리즘은 점진적 중심 갱신 및 학습을 위해 단지 2 % 정도의 추가 학습시간이 소요되는 것으로 확인되었다. 반면에 시변 정상데이터가 수신되는 경우에 오프라인 학습 모델과 비교하여 19.10 % 개선된 Area Under the receiver operating characteristic Curve(AUC) 성능을 보였다.

Endotracheal intubation by inexperienced trainees using the Clarus Video System: learning curve and orodental trauma perspectives

  • Moon, Young-Jin;Kim, Juyoung;Seo, Dong-Woo;Kim, Jae-Won;Jung, Hye-Won;Suk, Eun-Ha;Ha, Seung-Il;Kim, Sung-Hoon;Kim, Joung-Uk
    • Journal of Dental Anesthesia and Pain Medicine
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    • 제15권4호
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    • pp.207-212
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    • 2015
  • Background: The ideal alternative airway device should be intuitive to use, yielding proficiency after only a few trials. The Clarus Video System (CVS) is a novel optical stylet with a semi-rigid tip; however, the learning curve and associated orodental trauma are poorly understood. Methods: Two novice practitioners with no CVS experience performed 30 intubations each. Each trial was divided into learning (first 10 intubations) and standard phases (remaining 20 intubations). Total time to achieve successful intubation, number of intubation attempts, ease of use, and orodental trauma were recorded. Results: Intubation was successful in all patients. In 51 patients (85%), intubation was accomplished in the first attempt. Nine patients required two or three intubation attempts; six were with the first 10 patients. Learning and standard phases differed significantly in terms of success at first attempt, number of attempts, and intubation time (70% vs. 93%, $1.4 {\pm}0.7$ vs. $1.1{\pm}0.3$, and $71.4{\pm}92.3s$ vs. $24.6{\pm}21.9s$, respectively). The first five patients required longer intubation times than the subsequent five patients ($106.8{\pm}120.3s$ vs. $36.0{\pm}26.8s$); however, the number of attempts was similar. Sequential subgroups of five patients in the standard phase did not differ in the number of attempts or intubation time. Dental trauma, lip laceration, or mucosal bleeding were absent. Conclusions: Ten intubations are sufficient to learn CVS utilization properly without causing any orodental trauma. A relatively small number of experiences are required in the learning curve compared with other devices.

CAS 계산기를 활용한 고등학교 정규분포곡선의 교수-학습을 위한 시사점 탐구 (Pedagogical Implications for Teaching and Learning Normal Distribution Curves with CAS Calculator in High School Mathematics)

  • 조정수
    • 한국수학교육학회지시리즈E:수학교육논문집
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    • 제24권1호
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    • pp.177-193
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    • 2010
  • 본 연구는 고등학교 통계 영역의 확률분포에 제시되어 있는 정규분포를 이항분포에서 정규분포로의 근사, 정규분포곡선의 탐구, Monte Carlo 방법에 의한 정규분포곡선의 넓이 탐구, 정규분포곡선의 선형변환, 그리고 여러 형태의 정규분포곡선 탐구 등의 내용을 중심으로 CAS 계산기를 활용하여 탐구해보고자 한다. CAS 계산기의 도구적 기능인 사소화, 실험, 시각화, 집중의 측면에서 볼 때 지필로서는 교육과정에 제시된 확률분포의 목표를 달성하기 불가능하다고 판단된다. 따라서 본 연구에서는 CAS 계산기를 활용하여 정규분포곡선의 다양한 성질을 탐구하고 이러한 과정과 결과로부터 정규분포곡선에 대한 교수학적 시사점을 도출하고자 한다.

고등학교 수학과 교육을 위한 CAI 프로그램 개발 연구 - 정적분을 중심으로 - (A Study on the Development of Computer Assisted Instruction for the High School Mathematics Education)

  • 이덕호;김왕식
    • 한국학교수학회논문집
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    • 제2권1호
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    • pp.55-66
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    • 1999
  • In mathematics education, teaching-learning activity can be divided largely into the understanding the mathematical concepts, derivation of principles and laws acquirement of the mathematical abilities. We utilize various media, teaching tools, audio-visual materials, manufacturing materials for understanding mathematical concepts. But sometimes we cannot define or explain correctly the concepts as well as the derivation of principles and laws by these materials. In order to solve the problem we can use the computer. In this paper, ′the process of the length of curve being equal to the sum of the vectors when intervals get smaller′ and ′the process of calculating volume of spinning curve by using definite integral.′ Using the computers is more visible than other educational instruments like blackboards, O.H.Ps., etc. Also it can help students with solving mathematical problems intuitively. Consequently more effective teaching-learning activity can be done. Usage of computers is the best method for improving the mathematical abilities because computers have functions of the immediate reaction, operation, reference and deduction. One of the important characters of mathematics is accuracy, so we use computers for improving mathematical abilities. This paper is about the program focused on the part of "the application of definite integral", which exists in mathematical curriculum the second and third grade of high school. When this study is used for students as assisting materials, it is expected the following educational effect. 1. Students will have precise concepts because they can understand what they learn intuitively. 2. Students will have positive thought by arousing interests of learning because this program is composed of pictures, animations with effectiveness of sound. 3. It is possible to change the teacher-centered instruction into the student-centered instruction. 4. Students will understand the relation between velocity and distance correctly because they can see the process of getting the length of curve by vector through the monitor. For the purpose of increasing the efficiencies and qualities of mathematics education, we have to seek the various learning-teaching methods. But considering that no computer can replace the teacher′s role, teachers have to use the CIA program carefully.

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억양의 시각화를 통한 프랑스어의 억양학습 (Learning French Intonation with a Base of the Visualization of Melody)

  • 이정원
    • 음성과학
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    • 제10권4호
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    • pp.63-71
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    • 2003
  • This study aims to experiment on learning French intonation, based on the visualization of melody, which was employed in the early sixties to reeducate those with communication disorders. The visualization of melody in this paper, however, was used to the foreign language learning and produced successful results in many ways, especially in learning foreign intonation. In this paper, we used the PitchWorks to visualize some French intonation samples and experiment on learning intonation based on the bitmap picture projected on a screen. The students could see the melody curve while listening to the sentences. We could observe great achievement on the part of the students in learning intonations, as verified by the result of this experiment. The students were much more motivated in learning and showed greater improvement in recognizing intonation contour than just learning by hearing. But lack of animation in the bitmap file could make the experiment nothing but a boring pattern practices. It would be better if we can use a sound analyser, as like for instance a PitchWorks, which is designed to analyse the pitch, since the students can actually see their own fluctuating intonation visualized on the screen.

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주기적 반복법을 적용한 영단어 학습콘텐츠 스마트 융합 설계 연구 (A Study of Smart Convergence Design of English Vocabulary Learning Contents Applying the Periodic Repetitive Method)

  • 김영상
    • 한국융합학회논문지
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    • 제7권4호
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    • pp.133-140
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    • 2016
  • 본 연구에서는 영단어 학습 콘텐츠 개발 필요에 따른 새로운 스마트 영단어 암기방법을 설계 제안한다. 이 방법은 스마트 폰에서 효과적으로 영단어 학습을 지원하는 콘텐츠로 개발 가능하다. 본 연구의 핵심 아이디어는 첫째, 30개의 단어를 하루에 3분씩 10회(학습 1회 및 복습 9회)로 나누어 학습한다. 둘째, 망각주기를 고려하여 최초학습 1일 후, 10일 후, 30일 후 등의 3회 반추 복습을 제안한다. 본 콘텐츠의 개발과정은 크게 앱ID 생성부, 앱 접속부, 알람 설정부, 단어학습 처리부, 학습결과 모니터링부 등 5개의 단계로 이루어져 있다. 제안된 방법은 에빙하우스 주기적 반복 학습전략으로 최적화되어 있어 사용자의 영단어 학습 만족도를 높일 수 있다.

인간의 습관적 특성을 고려한 악성 도메인 탐지 모델 구축 사례: LSTM 기반 Deep Learning 모델 중심 (Case Study of Building a Malicious Domain Detection Model Considering Human Habitual Characteristics: Focusing on LSTM-based Deep Learning Model)

  • 정주원
    • 융합보안논문지
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    • 제23권5호
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    • pp.65-72
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    • 2023
  • 본 논문에서는 LSTM(Long Short-Term Memory)을 기반으로 하는 Deep Learning 모델을 구축하여 인간의 습관적 특성을 고려한 악성 도메인 탐지 방법을 제시한다. DGA(Domain Generation Algorithm) 악성 도메인은 인간의 습관적인 실수를 악용하여 심각한 보안 위협을 초래한다. 타이포스쿼팅을 통한 악성 도메인의 변화와 은폐 기술에 신속히 대응하고, 정확하게 탐지하여 보안 위협을 최소화하는 것이 목표이다. LSTM 기반 Deep Learning 모델은 악성코드별 특징을 분석하고 학습하여, 생성된 도메인을 악성 또는 양성으로 자동 분류한다. ROC 곡선과 AUC 정확도를 기준으로 모델의 성능 평가 결과, 99.21% 이상 뛰어난 탐지 정확도를 나타냈다. 이 모델을 활용하여 악성 도메인을 실시간 탐지할 수 있을 뿐만 아니라 다양한 사이버 보안 분야에 응용할 수 있다. 본 논문은 사용자 보호와 사이버 공격으로부터 안전한 사이버 환경 조성을 위한 새로운 접근 방식을 제안하고 탐구한다.

Classification of mandibular molar furcation involvement in periapical radiographs by deep learning

  • Katerina Vilkomir;Cody Phen;Fiondra Baldwin;Jared Cole;Nic Herndon;Wenjian Zhang
    • Imaging Science in Dentistry
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    • 제54권3호
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    • pp.257-263
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    • 2024
  • Purpose: The purpose of this study was to classify mandibular molar furcation involvement (FI) in periapical radiographs using a deep learning algorithm. Materials and Methods: Full mouth series taken at East Carolina University School of Dental Medicine from 2011-2023 were screened. Diagnostic-quality mandibular premolar and molar periapical radiographs with healthy or FI mandibular molars were included. The radiographs were cropped into individual molar images, annotated as "healthy" or "FI," and divided into training, validation, and testing datasets. The images were preprocessed by PyTorch transformations. ResNet-18, a convolutional neural network model, was refined using the PyTorch deep learning framework for the specific imaging classification task. CrossEntropyLoss and the AdamW optimizer were employed for loss function training and optimizing the learning rate, respectively. The images were loaded by PyTorch DataLoader for efficiency. The performance of ResNet-18 algorithm was evaluated with multiple metrics, including training and validation losses, confusion matrix, accuracy, sensitivity, specificity, the receiver operating characteristic (ROC) curve, and the area under the ROC curve. Results: After adequate training, ResNet-18 classified healthy vs. FI molars in the testing set with an accuracy of 96.47%, indicating its suitability for image classification. Conclusion: The deep learning algorithm developed in this study was shown to be promising for classifying mandibular molar FI. It could serve as a valuable supplemental tool for detecting and managing periodontal diseases.