• 한국멀티미디어학회논문지
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• 제17권3호
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• pp.277-286
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• 2014

본 논문에서는 Gabor 특징과 MDLC 특징, 그리고 co-occurrence 특징의 융합에 의한 질감 특징 기반언어 인식 방법을 제안한다. 제안된 방법에서는 먼저 시험 영상에 Gabor 변환에 이은 크기 연산자를 적용하여 Gabor 크기 영상을 얻고 그 통계치를 계산하여 결과를 벡터화한다. 이어서 MDLC 연산자를 이용하여 MDLC 영상을 얻고 역시 그 통계치를 계산하여 벡터화한다. 다음으로 시험 영상으로부터 GLCM을 계산하고 이를 이용하여 co-occurrence 특징을 계산한 다음 벡터화한다. 이들 Gabor, MDLC, co-occurrence 특징에 의한 벡터들은 벡터 융합에 의하여 특징 벡터로 사용된다. 분류 단계에서는 얼굴 인식에 주로 사용되는 WPCA를 분류기로 하여 시험 특징 벡터와 가장 유사한 학습 특징 벡터를 찾는다. 제안된 방법의 성능은 15개국 언어의 문서를 스캔하여 얻은 시험 문서 영상 DB에 대한 평균 인식률을 조사하여 알아본다. 실험 결과 제안된 방법은 시험 DB에 대하여 비교적 낮은 특징 벡터 차원으로 매우 우수한 언어 인식 성능을 보여준다.

• Journal of Information Technology Applications and Management
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• 제26권3호
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• pp.61-80
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• 2019

The cooperation between universities and industries is already one of the most important factors driving the national economy in the knowledge-based society of the 21st century represented by the Fourth Industrial Revolution. The Korean government has also been carrying out legal and institutional re-adjustments to promote industrial-university cooperation in line with demands for such changes in the times. However, despite this industry-academic cooperation system, there is still a significant mismatch between industrial demand and the university's workforce development system. By the way, there is a Cooperative Education(CO-OP) in Canada and the United States. It's an innovative link between the university and the industry. The reason is that the CO-OP program not only allows students to gain experience with their majors in the industrial field, but also plays a positive role in improving their specialty expertise. In particular, field information, ideas, and job insights that students acquire through CO-OP also serve as motivation for starting a business beyond employment after graduation. Furthermore, CO-OP experience is an important opportunity for future researchers to come up with commercialized research results that are not separated from the field sites The purpose of this study is to overcome the gap between industrial demand and the college manpower training system, and develop a Korean-style coaching program model as a growth engine for creative talent-building policies, represented by 'creation of start-ups and new industry.' In addition, this study suggested measures that can be applied in real universities. In addition, the study also highlighted that the introduction of CO-OP programs with field practices in Korea could also boost start-ups. Based on the Korean CO-OP program model, the curricula applicable to domestic universities consisted of two types : general and research-oriented university types.

• 한국화재소방학회:학술대회논문집
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• 한국화재소방학회 2002년도 춘계학술대회 논문집
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• pp.21-29
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• 2002

가스계 소화약제시스템의 인명안전 또는 기타 안전관련으로 CO2 시스템과 청정약제시스템을 중심으로 기술해보았습니다. 인명에 대한 위험을 최소화하면서 CO2 소화시스템의 혜택을 얻기 위해서는 설계, 시공, 유지관리면에서의 인명안전에 대해 상당한 관심을 기울여야한다. 청정 소화약제를 통상의 거주구역에 사용할 경우의 주요요소는 독성문제이다. 할로겐화탄소약제 테스트에서의 주요 관점은 급성효과, 즉 단기간 노출의 경우이다. 주요급성효과에는 마취성과 심장감작성이 있다. 불활성가스약제의 경우 주요 신체적 영향으로는 산소농도의 저하문제를 들 수 있다.

• 한국멀티미디어학회논문지
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• 제22권1호
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• pp.1-9
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• 2019

Single image rain removal is a typical inverse problem which decomposes the image into a background scene and a rain streak. Recent works have witnessed a substantial progress on the task due to the development of convolutional neural network (CNN). However, existing CNN-based approaches train the network with synthetically generated training examples. These data tend to make the network bias to the synthetic scenes. In this paper, we present an unsupervised framework for removing rain streaks from real-world rainy images. We focus on the natural phenomena that static rainy scenes capture a common background but different rain streak. From this observation, we train siamese network with the real rain image pairs, which outputs identical backgrounds from the pairs. To train our network, a real rainy dataset is constructed via web-crawling. We show that our unsupervised framework outperforms the recent CNN-based approaches, which are trained by supervised manner. Experimental results demonstrate that the effectiveness of our framework on both synthetic and real-world datasets, showing improved performance over previous approaches.

• 대한방사선기술학회지:방사선기술과학
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• 제44권4호
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• pp.351-358
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• 2021

This research project is a program promoted to seek diversification of domestic radioactive waste analysis institutions, and seeks public development, win-win cooperation, and cooperation between the entrusted institution and the entrusted institution. Accordingly, the entrusted institution established a standard analysis procedure for establishing a quality control system for radioactivity analysis, establishing a radiation control zone, obtaining KOLAS accreditation, and performing proficiency tests, which are the performance ranges requested by the entrusted institution, and intersecting the radioactive isotope waste generated at the actual site. Verification was performed to confirm the analysis quality. In addition, facilities and equipment for radioactivity analysis were supplemented and expanded, and the basic technology foundation and technical skills were secured through securing professional technicians and education/training. It is judged that the entrusted institution will contribute to securing radiation safety through the smooth execution of treatment, disposal, and transportation through value creation and analysis of radioactive waste generated by radioactive isotope-using institutions (research institutes, hospitals, industries, etc.) by succeeding in this research project do.

• 공학교육연구
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• 제26권3호
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• pp.49-59
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• 2023

On July 6, 2021, the Ministry of Education revised and announced the operating regulations of the undergraduate co-op with the aim of protecting students rights and student-centered operation based on mutual benefits for students and institutions. Therefore, the purpose of this study is to analyze universities' perceptions against the amendment of regulation of the Ministry of Education's into universities/college, regions. According to a survey of 75 KACE, we found that colleges are more difficult than universities in terms of administrative work, company participation, reduced opportunities for co-op, and managing participating companies. Next, most of the regional differences in difficulties were not significant, and only the decline in company participation rate was more difficult in Daegyoung/Gangwon/Chungcheong/Jeju than in the metropolitan area. Finally, policy directions such as the differential application of practical support expenses according to the size of the company, tax benefits for institutions, and clarification of the concept of job training were presented.

• 산업진흥연구
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• 제2권1호
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• pp.63-68
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• 2017

본 연구는 직장에서 교육훈련을 1회 이상 참여한 근로자를 대상으로 2016년 10월 10일부터 10월 28일까지 총 63부를 설문 조사 분석하였으며, 교육훈련이 직무스트레스에 어떠한 영향을 미치는지를 분석 하였다. IBM SPSS Statistics 20을 이용하여 요인분석 32개 문항을 사용하여 4개 요인을 도출하였고 유의확률 p=.000로 검증되었다. 연구결과 첫째. 직장의 교육훈련과 직무스트레스에 미치는 영향은 직장의 OJT 교육이 직무 스트레스 해소에 유의한 영향을 미치는 것으로 나타났다. 둘째, 교육훈련이 업무스트레스 간의 상관성은 OJT 교육(p<.01, ${\beta}=.526$)과 Off-JT 교육(p<.01, ${\beta}=.508$)이 업무스트레스와 상관관계가 높은 것으로 나타났다. 셋째, 경력에 따른 업무 스트레스 간의 차이는 통계적으로 유의한 영향을 미치지 못한 것으로 나타났다. 경력은 10년 이상보다 3~6년 미만이 업무스트레스에 더 민감한 것으로 분석되었다. 본 연구에서 교육훈련이 직무스트레스에 미치는 영향을 검증한 것에 의의가 있다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2018년도 추계학술대회
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• pp.12-13
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• 2018

안전운항을 위해 항해사가 숙지하고 있어야하는 것은 선박의 조종성능이다. 선박이 조우하는 상황이나 위험상황에 처했을 때 피항동작을 취하기 위해 변침을 하게 되는데 그러한 조치를 취하기 위해 타각을 얼마큼 줄 건지를 판단하고 직진상태에서 타각을 사용한 이후 정해진 방향으로 바꾸는데 필요한 시간과 어떻게 운동하는지를 예측할 수 있어야 선박의 안전을 확보할 수 있다. 실습선 한바다호의 조종성능을 확인하기 위해 IMO에서 제시하는 $10^{\circ}/10^{\circ}$ 및 $20^{\circ}/20^{\circ}$ 지그재그 테스트와 좌현/우현 선회시험을 시행하였고 실선계측을 통해 이 때 나타나는 선박의 운동을 함께 측정하여 항해사들이 적절한 피항동작을 취할 수 있도록 실습선 한바다호의 조종성능과 선박운동의 정보를 제공하고자 한다.

• The Journal of Korean Physical Therapy
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• 제26권6호
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• pp.442-448
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• 2014

Purpose: The objective of this study is to evaluate the effect of neuro-feedback training and transcutaneous electrical nerve stimulation (TENS) on stress, quantitative sensory threshold and pain in patients suffering from tension type headache. Methods: 22 participants who passed the preliminary evaluation were enrolled in the study and 11 participants were randomly assigned to each group. The control group (n=11) was subject to the TENS treatment of which was composed of a 20-minute session for 5 times a week during 4 weeks, and the experimental group (n=11) was subject to both neuro feedback training and TENS treatment for 10 minutes a day and 5 days a week during 4 weeks. The Perceived Stress Scale (PSS) was used to measure a level of stress and the quantitative sensory testing (QST) was used for the measurement of cold pain threshold (CPT) and heat pain threshold (HPT); A degree of pain was evaluated through the headache impact test-6 (HIT-6). Results: In comparision of all dependent variables between the control and subject groups, there were significant differences in stress, quantitative sensory threshold and pain after the treatment (p<0.05), and the experimental group showed significant differences in stress, CPT, HPT and pain (p<0.05) and the control group showed only a significant difference in HPT (p<0.05). Conclusion: Findings of this study demonstrate that the concomitant administration of the TENS treatment and neuro feedback training is effective on alleviation of stress, quantitative sensory threshold and pain in patients with tension type headache.

• Journal of Radiation Protection and Research
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• 제46권4호
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• pp.204-212
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• 2021

Background: Identification of radioisotopes for plastic scintillation detectors is challenging because their spectra have poor energy resolutions and lack photo peaks. To overcome this weakness, many researchers have conducted radioisotope identification studies using machine learning algorithms; however, the effect of data normalization on radioisotope identification has not been addressed yet. Furthermore, studies on machine learning-based radioisotope identifiers for plastic scintillation detectors are limited. Materials and Methods: In this study, machine learning-based radioisotope identifiers were implemented, and their performances according to data normalization methods were compared. Eight classes of radioisotopes consisting of combinations of ²²Na, ⁶⁰Co, and ¹³⁷Cs, and the background, were defined. The training set was generated by the random sampling technique based on probabilistic density functions acquired by experiments and simulations, and test set was acquired by experiments. Support vector machine (SVM), artificial neural network (ANN), and convolutional neural network (CNN) were implemented as radioisotope identifiers with six data normalization methods, and trained using the generated training set. Results and Discussion: The implemented identifiers were evaluated by test sets acquired by experiments with and without gain shifts to confirm the robustness of the identifiers against the gain shift effect. Among the three machine learning-based radioisotope identifiers, prediction accuracy followed the order SVM > ANN > CNN, while the training time followed the order SVM > ANN > CNN. Conclusion: The prediction accuracy for the combined test sets was highest with the SVM. The CNN exhibited a minimum variation in prediction accuracy for each class, even though it had the lowest prediction accuracy for the combined test sets among three identifiers. The SVM exhibited the highest prediction accuracy for the combined test sets, and its training time was the shortest among three identifiers.