• Title/Summary/Keyword: Learning model

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Development of real-time defect detection technology for water distribution and sewerage networks (시나리오 기반 상·하수도 관로의 실시간 결함검출 기술 개발)

  • Park, Dong, Chae;Choi, Young Hwan
    • Journal of Korea Water Resources Association
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    • v.55 no.spc1
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    • pp.1177-1185
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    • 2022
  • The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

Development of a Novel Science Curiosity Questionnaire through Modification and Verification of the Science Curiosity Questionnaire -Through the Analysis of Science Curiosity of Pre-Service Elementary Teachers- (과학호기심 설문지의 수정 및 검증을 통한 새로운 과학호기심 설문지의 개발 - 초등예비교사의 과학호기심 분석을 통하여 -)

  • Kim, Dong Uk;Shin, Min Hyeon
    • Journal of Korean Elementary Science Education
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    • v.42 no.1
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    • pp.149-160
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    • 2023
  • A Korean-version science curiosity questionnaire (Science Curiosity in Learning Environments [SCILE(15)]) was developed after factor analysis of the Korean-version SCILE(30) questionnaire. Pre-service elementary school teachers were surveyed using the Korean-version SCILE(30), and a factor analysis based on their responses was performed. The factor analysis demonstrated that the Korean-version SCILE(15) consisted of three curiosity factors: a 'science practices' factor, a 'stretching' factor, and an 'embracing' factor. Confirmatory factor analysis of the factor structure revealed correlations between all the factors, thus confirming their commonality as a science curiosity factors. The Cronbach alpha for the reliability of all items in the Korean-version SCILE(15) and of items by factor was greater than 0.700. The Korean-version SCILE(15) was therefore evaluated to be reliable as a science curiosity questionnaire. Pre-service elementary teachers who participated in the survey for the development of the SCILE(15) were aware of the 'science practices', 'stretching', and 'embracing' science curiosity factors. Analysis in a general linear model of the degree of recognition accorded by pre-service elementary teachers to the three science curiosity factors demonstrated significant differences between the curiosity factors in terms of recognition. This cohort of pre-service elementary teachers showed the highest level of recognition of the 'stretching' curiosity factor and the lowest level of recognition of the 'embracing' curiosity factor.

A Study on MRD Methods of A RAM-based Neural Net (RAM 기반 신경망의 MRD 기법에 관한 연구)

  • Lee, Dong-Hyung;Kim, Seong-Jin;Park, Sang-Moo;Lee, Soo-Dong;Ock, Cheol-Young
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.9
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    • pp.11-19
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    • 2009
  • A RAM-based Neural Net(RBNN) which has multi-discriminators is more effective than RBNN with a discriminator. Experience Sensitive Cumulative Neural Network and 3-D Neuro System(3DNS) that accumulate the features point improved the performance of BNN, which were enabled to train additional and repeated patterns and extract a generalized pattern. In recognition process of Neural Net with multi-discriminator, the selection of class was decided by the value of MRD which calculates the accumulated sum of each class. But they had a saturation problem of its memory cells caused by learning volume increment. Therefore, the decision of MRD has a low performance because recognition rate is decreased by saturation. In this paper, we propose the method which improve the MRD ability. The method consists of the optimum MRD and the matching ratio prototype to generalized image, the cumulative filter ratio, the gap of prototype response MRD. We experimented the performance using NIST database of NIST without preprocessor, and compared this model with 3DNS. The proposed MRD method has more performance of recognition rate and more stable system for distortion of input pattern than 3DNS.

A Study on the Introduction of Library Services Based on Blockchain (블록체인 기반의 도서관 서비스 도입 및 활용방안에 관한 연구)

  • Ro, Ji-Yoon;Noh, Younghee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.33 no.1
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    • pp.371-401
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    • 2022
  • If the blockchain means storing information in a distributed environment that cannot be forged or altered, it is mentioned that this is similar to what librarians collect, preserve, and share authoritative information. In this way, this study examined blockchain technology as a way to collect and provide reliable information, increase work efficiency inside and outside the library, and strengthen cooperative networks. This study attempted to propose various ways to utilize blockchain technology in book relations based on literature surveys and case studies in other fields. To this end, this study first analyzed the field and cases of blockchain application to confirm the possibility and value of blockchain application in the library field, and proposed 12 ways to utilize it based on this. The utilization model was proposed by dividing it into operation and service sectors. In the operation sector, it is a digital identity-based user record storage and authentication function, transparent management and traceable monitoring function, voting-based personnel and recruitment system, blockchain governance-based network efficiency function, and blockchain-based next-generation device management and information integration function. The service sector includes improved book purchase and sharing efficiency due to simplification of intermediaries, digital content copyright protection and management functions, customized service provision based on customer behavior analysis, blockchain-based online learning platforms, sharing platforms, and P2P-based reliable information sharing platforms.

Job Analysis of Visiting Nurses in the Process of Change Using FGI and DACUM (변화의 과정에 있는 방문간호사의 직무분석: FGI와 DACUM을 적용하여)

  • Kim, Jieun;Lee, Insook;Choo, Jina;Noh, Songwhi;Park, Hannah;Gweon, Sohyeon;Lee, kyunghee;Kim, Kyoungok
    • Research in Community and Public Health Nursing
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    • v.33 no.1
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    • pp.13-31
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    • 2022
  • Purpose: This study conducted a job analysis of visiting nurses in the process of change. Methods: Participants were the visiting nurses working for the Seoul Metropolitan city. On the basis of the Public Health Intervention Wheel model, two times of the focus group interview (FGI) with seven visiting nurses and one time of the Developing a Curriculum (DACUM) with 34 visiting nurses were performed. A questionnaire survey of 380 visiting nurses was conducted to examine the frequency, importance and difficulty levels of the tasks created by using the FGI and DACUM. Results: Visiting nurses' job was derived as the theme of present versus transitional roles. The present role was categorized as 'providing individual- and group-focused services' and 'conducting organization management', while the transitional role was categorized as 'providing district-focused services' and 'responding to new health issues'. The job generated 13 duties, 28 tasks, and 73task elements. The tasks showed the levels of frequency (3.65 scores), importance (4.27 scores), and difficulty (3.81 scores). All the tasks were determined as important, exceeding the average 4.00 scores. The group- and district-focused services of the tasks were recognized as more difficult but less frequent tasks. Conclusion: The visiting nurses exert both present and transitional roles. The transitional roles identified in the present study should be recognized as an extended role of visiting nurses in accordance with the current changing healthcare needs in South Korea. Finally, the educational curriculum for visiting nurses that reflects the transitional roles from the present study is needed.

A study on the prediction of aquatic ecosystem health grade in ungauged rivers through the machine learning model based on GAN data (GAN 데이터 기반의 머신러닝 모델을 통한 미계측 하천에서의 수생태계 건강성 등급 예측 방안 연구)

  • Lee, Seoro;Lee, Jimin;Lee, Gwanjae;Kim, Jonggun;Lim, Kyoung Jae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.448-448
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    • 2021
  • 최근 급격한 기후변화와 도시화 및 산업화로 인한 지류하천에서의 수량과 수질의 변동은 생물 다양성 감소와 수생태계 건강성 저하에 큰 영향을 미치고 있다. 효율적인 수생태 관리를 위해서는 지속적인 유량, 수질, 그리고 수생태 모니터링을 통한 데이터 축적과 더불어 면밀한 상관 분석을 통해 수생태계 건강성의 악화 원인을 규명해야 할 필요가 있다. 그러나 수많은 지류하천을 대상으로 한 지속적인 모니터링은 현실적으로 어려움이 있으며, 수생태계의 특성 상 단일 영향 인자만으로 수생태계의 건강성 변화와의 관계를 정확히 파악하는데 한계가 있다. 따라서 지류하천에서의 유량 및 수질의 시공간적인 변동성과 다양한 영향 인자를 고려하여 수생태계의 건강성을 효율적으로 예측할 수 있는 기술이 필요하다. 이에 본 연구에서는 경험적 데이터 기반의 머신러닝 모델 구축을 통해 미계측 하천에서의 수생태계 건강성 지수(BMI, TDI, FAI)의 등급(A to E)을 예측하고자 하였다. 머신러닝 모델은 학습 데이터셋의 양과 질에 따라 성능이 크게 달라질 수 있으며, 학습 데이터셋의 분포가 불균형적일 경우 과적합 또는 과소적합 문제가 발생할 수 있다. 이를 보완하고자 본 연구에서는 실제 측정망 데이터셋을 바탕으로 생성적 적대 신경망 GAN(Generative Adversarial Network) 알고리즘을 통해 머신러닝 모델 학습에 필요한 추가 데이터셋(유량, 수질, 기상, 수생태 등급)을 확보하였다. 머신러닝 모델의 성능은 5차 교차검증 과정을 통해 평가하였으며, GAN 데이터셋의 정확도는 실제 측정망 데이터셋의 정규분포와의 비교 분석을 통해 평가하였다. 최종적으로 SWAT(Soil and Water Assessment Tool) 모형을 통해 예측 된 미계측 하천에서의 데이터셋을 머신러닝 모델의 검증 자료로 사용하여 수생태계 건강성 등급 예측 정확도를 평가하였다. 본 연구에서의 GAN에 의해 강화된 머신러닝 모델은 수질 및 수생태 관리가 필요한 우심 지류하천 선정과 구조적/비구조적 최적관리기법에 따른 수생태계 건강성 개선 효과를 평가하는데 활용될 수 있을 것이다. 또한 이를 통해 예측된 미계측 하천에서의 수생태계 건강성 등급 자료는 수량-수질-수생태를 유기적으로 연계한 통합 물관리 정책을 수립하는데 기초자료로 활용될 수 있을 것이라 사료된다.

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Case Study on the Pre-Service Earth Science Teachers' Faults Discrimination on Geological Map using Eye Tracker (시선 추적기를 활용한 지질도에서 예비 지구과학교사들의 단층 판별에 대한 사례 연구)

  • Woong Hyeon Jeon;Duk Ho Chung;Chul Min Lee
    • Journal of the Korean earth science society
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    • v.44 no.3
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    • pp.210-221
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    • 2023
  • The purpose of this study is to evaluate the content knowledge and problem solving process used by pre-service earth science teachers while discriminating faults on geological maps. For this, we collected and evaluated data on fixation duration and gaze plot, while pre-service earth science teachers (N=12) solved the problem on faults interpretation using an eye tracker (Tobii Pro Glass 2 model). The results were as follows. First, most of the pre-service earth science teachers know the concepts of the normal and reverse fault but they do not know the procedural knowledge essential for fault interpretation on geological maps. Second, the pre-service earth science teachers did not draw a geological cross-sectional map to interpret the fault on the geological map and interpreted the fault based on two-dimensional information collected from the geological map rather than three-dimensional information. Therefore, it is essential to improve the teaching and learning environment so that pre-service earth science teachers who will become earth science teachers in the future can learn procedural knowledge essential to comprehend natural phenomena including understanding natural phenomena. The results of this study can substantially help organize a new earth science curriculum or develop materials on teachers' education in the future.

A Study on the Educational Methods of Self-Narrative Writing for University Students (대학생 자기 서사 글쓰기의 교육 방안 연구)

  • Hyun-ju Kim;Young-ha Yang
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.2
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    • pp.357-366
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    • 2023
  • In the purpose of this study, the college textbooks of self-narrative writing and examples of classroom practice are analyzed to find a way to educate it. The self- narrative writing subject with a learning of recognization, expression, and communication with oneself, emphasizes the necessity when they become college students through entrance exam-oriented education. The research methods are as follows. Firstly, three university textbooks which include a section on self-narrative writing were compared and analyzed. The analysis highlights the needs for a textbook covering self-narrative writing more extensively and comprehensively as what is offered by the existing textbooks is limited in facilitating students to fully develop the ability of self-reflection, which should be dealt as a long-term goal. Secondly, the current discussion on self-narrative writing and examples of real classroom practice were analyzed. It shows that a step-by-step approach is required to encourage the practice of deep self-reflection to be incorporated into writing. In addition, during the writing process, various correction and feedback activities should be carried out on a macro level and gradually while the communication and feedback should take place not only between a teacher and students, but also among students. As a result, it is expected that this study will help establish a teaching model of self-narrative writing by seeking complementary points and educational directions for self-narrative writing.

The Effect of Other Behaviors and Lecture Satisfaction on Lecture Flow in Online Classes of Nursing Students' (간호대학생의 온라인 수업에서 딴짓과 강의만족도가 수업몰입에 미치는 영향)

  • Hyun-hee Ma;Hwa-Young Kim;Eun-Su Lee
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.471-480
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    • 2023
  • The purpose of this study is to confirm the effect of recording online classes and real-time video classes on other behaviors, lecture satisfaction, and lecture flow in during the COVID-19 period. Data were collected and analysis using a structured questionnaire from May 20th to June 4th in 2021 for 550 nursing students in the D University. As a result of the study, it was found that there were more others behaviors in record online classes than in real-time online classes (t=-2.00, p=.046), lecture satisfaction(t=-1.54, p=.124) and lecture flow in real-time online classes it was higher in the record online classes (t=-.63, p=.529), but it was not statistically significant. However, the 2nd year students who participated in the two types of online classes showed statistically significantly higher lecture satisfaction (t=13.55, p=.000) and lecture flow(t=4.48, p=.004). And 4 th grade students of others behaviors was statistically significantly lower (t=4.68, p=.003). In the multiple regression analysis, the main factor affecting lecture flow was lecture satisfaction, and the explanatory power of the model was 55.1% in record online classes (F=128.49, p <.01), and in real-time classes 47.2%(F=77.24, p<.01). In the future, research should be conducted to confirm the difference between the two types of online classes of the same instructor and the difference in other things, lecture satisfaction, and class commitment that appear after applying learner-centered learning.

The Effect of Engineering Design Based Ocean Clean Up Lesson on STEAM Attitude and Creative Engineering Problem Solving Propensity (공학설계기반 오션클린업(Ocean Clean-up) 수업이 STEAM태도와 창의공학적 문제해결성향에 미치는 효과)

  • DongYoung Lee;Hyojin Yi;Younkyeong Nam
    • Journal of the Korean earth science society
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    • v.44 no.1
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    • pp.79-89
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    • 2023
  • The purpose of this study was to investigate the effects of engineering design-based ocean cleanup classes on STEAM attitudes and creative engineering problem-solving dispositions. Furthermore, during this process, we tried to determine interesting points that students encountered in engineering design-based classes. For this study, a science class with six lessons based on engineering design was developed and reviewed by a professor who majored in engineering design, along with five engineering design experts with a master's degree or higher. The subject of the class was selected as the design and implementation of scientific and engineering measures to reduce marine pollution based on the method implemented in an actual Ocean Clean-up Project. The engineering design process utilized the engineering design model presented by NGSS (2013), and was configured to experience redesign through the optimization process. To verify effectiveness, the STEAM attitude questionnaire developed by Park et al. (2019) and the creative engineering problemsolving propensity test tool developed by Kang and Nam (2016) were used. A pre and post t-test was used for statistical analysis for the effectiveness test. In addition, the contents of interesting points experienced by the learners were transcribed after receiving descriptive responses, and were analyzed and visualized through degree centrality analysis. Results confirmed that engineering design in science classes had a positive effect on both STEAM attitude and creative engineering problem-solving disposition (p< .05). In addition, as a result of unstructured data analysis, science and engineering knowledge, engineering experience, and cooperation and collaboration appeared as factors in which learners were interested in learning, confirming that engineering experience was the main factor.