• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2509-2528
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• 2019

There are various styles of license plates for different countries and use cases that require style-specific methods. In this paper, we propose and illustrate a multi-style license plate recognition system. The proposed system performs a series of processes for license plate candidates detection, structure classification, character segmentation and character recognition, respectively. Specifically, we introduce a license plate structure classification process to identify its style that precedes character segmentation and recognition processes. We use a K-Nearest Neighbors algorithm with pre-training steps to recognize numbers and characters on multi-style license plates. To show feasibility of our multi-style license plate recognition system, we evaluate our system for multi-style license plates covering single line, double line, different backgrounds and character colors on Korean and the U.S. license plates. For the evaluation of Korean license plate recognition, we used a 50 minutes long input video that contains 138 vehicles of 6 different license plate styles, where each frame of the video is processed through a series of license plate recognition processes. From two experiments results, we show that various LP styles can be recognized under 50 ms processing time and with over 99% accuracy, and can be extended through additional learning and training steps.

• 한국항공운항학회지
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• 제27권1호
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• pp.26-33
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• 2019

It is necessary to establish a UAV pilot license and training system because the number of UAV-related accidents has rapidly risen. Most of accidents are caused by the human factors such as the lack of control skill and aviation knowledge. In this paper, we investigate licensing policy of small UAV pilots and examine the level of UAV licensing system and classification criteria based on comparative analysis of national cases such as USA, UK and China. Recently, the Ministry of Land, Infrastructure and Transport Affairs is planning to improve the safety regulation by taking into account the risk level of the licensing system, which has been classified according to the existing weight and commercial purpose. From the comparative analysis, we suggested a improvement policy for UAV licensing system in the view of pilot license segmentation, beyond Visual Line-of-sight flight and high risk UAV for non-commercial.

• 의학교육논단
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• 제15권2호
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• pp.69-74
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• 2013

This study aimed to review the expected changes in the medical educational environment and to evaluate approaches to coping with the abolition of the postgraduate intern training system. It is expected that after the intern training system is dismantled, postgraduate medical students will be deprived of the opportunity to practice opportunity for clinical practice and to inquire into their medical specialization. Therefore, major improvements in the clinical education curriculum must be made so that students can do so through the clinical education program. Offering students the opportunity to perform clinical practice through the clinical education program might require a revision in the laws and regulations on clinical education as well as the standardization of the clinical education curriculum in line with international practices. Reform measures to provide students the opportunity to inquire their specializations might be the introduction of a medical curriculum containing diverse fields and the establishment of a matching program to assign medical students to their residency programs after medical school. Finally, the fact that the basic concern of postgraduate medical education is the cultivation of primary care physicians must not be forgotten even after the dismantling of the postgraduate intern training system.

• Nuclear Engineering and Technology
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• 제54권8호
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• pp.3027-3033
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• 2022

Background: In this study, various types of deep-learning models for predicting in vitro radiosensitivity from gene-expression profiling were compared. Methods: The clonogenic surviving fractions at 2 Gy from previous publications and microarray gene-expression data from the National Cancer Institute-60 cell lines were used to measure the radiosensitivity. Seven different prediction models including three distinct multi-layered perceptrons (MLP), four different convolutional neural networks (CNN) were compared. Folded cross-validation was applied to train and evaluate model performance. The criteria for correct prediction were absolute error < 0.02 or relative error < 10%. The models were compared in terms of prediction accuracy, training time per epoch, training fluctuations, and required calculation resources. Results: The strength of MLP-based models was their fast initial convergence and short training time per epoch. They represented significantly different prediction accuracy depending on the model configuration. The CNN-based models showed relatively high prediction accuracy, low training fluctuations, and a relatively small increase in the memory requirement as the model deepens. Conclusion: Our findings suggest that a CNN-based model with moderate depth would be appropriate when the prediction accuracy is important, and a shallow MLP-based model can be recommended when either the training resources or time are limited.

• International Journal of Industrial Entomology and Biomaterials
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• 제8권1호
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• pp.107-112
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• 2004

The combining abilities in the 5 newly evolved thermo tolerant breeds viz., SR6, SR7, SR8 SR9 and SR10 of silkworm Bombyx mori L. and their 15 hybrids were made in a line${\times}$tester crossing programme. Data were analysed for seven quantitative traits i.e., pupation rate, cocoon yield, cocoon weight, cocoon shell weight, cocoon shell ratio, filament length and raw silk percentage under optimum room temperature $(25{\pm}{1^{\circ}C})$ conditions (In case of high temperature $(36{\pm}{1^{\circ}C})$ stress conditions five economic traits except filament length and raw silk percentage) with 3 widely adapted testers i.e., KA, CSR2 and CC1 as lines (females) and testers (males) respectively. The performance at high temperature and low humidity conditions aye only taken into consideration for selecting the best lines/hybrids. Among the lines SR6 exhibited positive General combining ability (GCA) effects for pupation rate, cocoon yield, cocoon weight and cocoon shell ratio traits, followed by SR7 for pupation rate, cocoon yield and cocoon shell weight and cocoon shell ratio. Among testers, KA exhibited positive GCA effects for two quantitative traits cocoon yield, cocoon weight and CSR2 for cocoon shell weight and cocoon shell ratio under adverse temperature conditions. The hybrid SR6${\times}$CC1 and SR7${\times}$CSR2 exhibited significant positive Specific combining ability (SCA) effects for majority of the traits in high temperature stress conditions of rearing. The better parent value of heterosis(Heterobeltiosis) was exhibited by the hybrid SR6${\times}$CC1 for pupation rate, cocoon yield, cocoon weight and cocoon shell weight and SR7${\times}$CSR2 for all the trails evaluated under high temperature conditions. Based on the results, the lines SR6 and SR7 was judged as best combiners and the hybrids SR6${\times}$CC1 and SR7${\times}$CSR2 can be selected for commercial exploitation in tropical climate.

• 한국정보전자통신기술학회논문지
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• 제2권2호
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• pp.51-56
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• 2009

본 논문에서는 카메라-투영 시스템에서 비전에 기반을 둔 손동작 인식을 위한 새로운 알고리즘을 제안하고 있다. 제안된 인식방법은 정적인 손동작 분류를 위하여 푸리에 변환을 사용하였다. 손 분할은 개선된 배경 제거 방법을 사용하였다. 대부분의 인식방법들이 같은 피검자에 의해 학습과 실험이 이루어지고 상호작용에 이전에 학습단계가 필요하다. 그러나 학습되지 않은 다양한 상황에 대해서도 상호작용을 위해 동작 인식이 요구된다. 그러므로 본 논문에서는 인식 작업 중에 검출된 불완전한 동작들을 정정하여 적용하였다. 그 결과 사용자와 독립되게 동작을 인식함으로써 새로운 사용자에게 신속하게 온라인 적용이 가능하였다.

• 한국정보통신학회논문지
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• 제11권7호
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• pp.1348-1353
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• 2007

본 논문에서는 카메라-투영 시스템에서 비전에 기반을 둔 손동작 인식을 위한 새로운 알고리즘을 제안하고 있다. 제안된 인식방법은 정적인 손동작 분류를 위하여 푸리에 변환을 사용하였다. 손 분할은 개선된 배경 제거 방법을 사용하였다. 대부분의 인식방법들이 같은 피검자에 의해 학습과 실험이 이루어지고 상호작용에 이전에 학습단계가 필요하다. 그러나 학습되지 않은 다양한 상황에 대해서도 상호작용을 위해 동작 인식이 요구된다. 그러므로 본 논문에서는 인식 작업 중에 검출된 불완전한 동작들을 정정하여 적용하였다. 그 결과 사용자와 독립되게 동작을 인식함으로써 새로운 사용자에게 신속하게 온라인 적용이 가능하였다.

• 한국융합학회논문지
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• 제8권10호
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• pp.9-17
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• 2017

이 연구는 클라우드 컴퓨팅과 인공지능의 융합기술을 적용하여 운동처방전문가시스템을 개발하고, 운동 건강관리 전문가들이 인터넷 환경에서 사용할 수 있도록 구현하고자 한다. 최근 우리사회는 의료기술의 발전으로 평균 수명이 늘어나고, 웰빙과 함께 근육질 몸매 가꾸기 붐이 일면서 사람들의 건강에 대한 관심이 높아지고 있다. 이러한 사회적 현상에 따라 건강관리를 전문적으로 하는 퍼스널 트레이너 및 운동 건강관리 전문가의 수요가 증가하고 있다. 하지만, 현재 오프라인 위주의 운동 교육으로 인하여 전문가가 많이 부족한 실정이다. 따라서 이 논문에서는 운동처방전문가 시스템을 개발하여 분산된 데이터를 모으고, 이를 바탕으로 인공지능 룰을 생성하여, 퍼스널 트레이너 및 운동건강관리 전문가들이 사용하는 시스템과 교육시스템을 구현하고자 한다. 또한 이 시스템은 오프라인 위주의 운동 교육시스템을 온라인에서 할 수 있도록 하여 많은 운동처방 전문가 육성에 기여 할 것이다. 향후 연구로는 다양한 IoT 기기의 연동을 통해 수집한 빅데이터를 바탕으로 현재 시스템의 기능을 더 발전시킬 것이다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.310-313
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• 1996

In this paper, a neural control algorithm is proposed on the automation of adjustment process. The adjustment processes in camcoder production line are modelled, and the processes are adjusted automatically by means of off-line supervisory trained multi-layer neural network. We have made many experiments on the several adjustment processes by using the control algorithm. There are many unexpected troubles to achieve the desirable adjust time in the practical application. To overcome those, some auxiliary algorithms are demanded. As a result, our proposed algorithm has some advantages - simple architecture, easy extraction of the training data without expertises, adaptability to the varying systems, and wide application for the other resemble processes.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2006년도 전력전자학술대회 논문집
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• pp.345-347
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• 2006

In this paper, a novel method for wind speed estimation in wind power generation systems is presented. The proposed algorithm is based on estimating the wind speed using Support-Vector-Machines for regression (SVR). The wind speed is estimated using the generator power-speed characteristics as a set of training vectors. SVR is trained off-line to predict a continuos-valued function between the system's inputs and wind speed value. The predicted off-line function as well as the instantaneous generator power and speed are then used to determine the unknown winds speed on-line. The simulation results show that SVR can define the corresponding wind speed rapidly and accurately to determine the optimum generator speed reference for maximum power point tracking.