• Title/Summary/Keyword: 미디어 기반 학습

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A Study on Gesture Interface through User Experience (사용자 경험을 통한 제스처 인터페이스에 관한 연구)

  • Yoon, Ki Tae;Cho, Eel Hea;Lee, Jooyoup
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.6
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    • pp.839-849
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    • 2017
  • Recently, the role of the kitchen has evolved from the space for previous survival to the space that shows the present life and culture. Along with these changes, the use of IoT technology is spreading. As a result, the development and diffusion of new smart devices in the kitchen is being achieved. The user experience for using these smart devices is also becoming important. For a natural interaction between a user and a computer, better interactions can be expected based on context awareness. This paper examines the Natural User Interface (NUI) that does not touch the device based on the user interface (UI) of the smart device used in the kitchen. In this method, we use the image processing technology to recognize the user's hand gesture using the camera attached to the device and apply the recognized hand shape to the interface. The gestures used in this study are proposed to gesture according to the user's context and situation, and 5 kinds of gestures are classified and used in the interface.

The influence of social capital on knowledge sharing behavior of mobile learners (사회적 자본이 이동학습자의 지식공유행위에 미치는 영향)

  • Qin, Ying;Lee, Kyeong-Rak;Lee, Sang-Joon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.9
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    • pp.647-658
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    • 2018
  • Modern society is complex and rapidly changing, and knowledge sharing is needed to acquire and create knowledge. Knowledge sharing is the act of providing information knowledge and know-how of their own in order to cooperate with or help their colleagues. This study presents a research model using social capital theory to explain the mobile knowledge sharing behavior of virtual community members. Based on previous studies, social capital theory is divided into structural, relational, and cognitive aspects. It was composed of social interaction ties as a measure of structural aspect, trust as a measure of cognitive aspect, shared language, shared vision and relational aspect. After collecting survey data, factor analysis and regression analysis were performed using SPSS 22. In this way, we examined how the detailed factors of social capital affect information sharing behavior and how the level of knowledge sharing affects community promotion. The results showed that social interaction ties, shared language, shared vision, and trust affect knowledge sharing. Knowledge sharing has had a positive impact on community promotion.

The Development of a Variety of Blended Global Courses and Their Comparative Analysis (블렌디드 글로벌 강좌 유형 개발 및 비교 분석)

  • Kim, Seong-Baeg;Kwon, Sang-Chul;Park, Chan-Jung
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.6 no.5
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    • pp.173-185
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    • 2016
  • As a dual-degree program/exchange student program becomes widespread, the faculty and students consisting of a course are being globalized. Recently, there has been an online or blended learning-based course, which is evolved from a conventional offline course. However, the course has no consideration of a dual-degree program or exchange student program because it is limited to a domestic university. To create and manage a global course, there have several of difficulties in the aspects of cost or effectiveness. As a solution to tackle them, it is necessary to do research on providing blended global courses with a fusion approach of online and offline. In this paper, we studied and presented a model of blended global courses. To create and maintain overseas scholar-oriented courses, we devised eight types of blended global courses depedning on their opening time and the cooperative relation between online and offline and made their comparative analysis. The blended global course proposed in this paper can be applied to cultivating global human resources in universities.

On Optimizing Dissimilarity-Based Classifications Using a DTW and Fusion Strategies (DTW와 퓨전기법을 이용한 비유사도 기반 분류법의 최적화)

  • Kim, Sang-Woon;Kim, Seung-Hwan
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.2
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    • pp.21-28
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    • 2010
  • This paper reports an experimental result on optimizing dissimilarity-based classification(DBC) by simultaneously using a dynamic time warping(DTW) and a multiple fusion strategy(MFS). DBC is a way of defining classifiers among classes; they are not based on the feature measurements of individual samples, but rather on a suitable dissimilarity measure among the samples. In DTW, the dissimilarity is measured in two steps: first, we adjust the object samples by finding the best warping path with a correlation coefficient-based DTW technique. We then compute the dissimilarity distance between the adjusted objects with conventional measures. In MFS, fusion strategies are repeatedly used in generating dissimilarity matrices as well as in designing classifiers: we first combine the dissimilarity matrices obtained with the DTW technique to a new matrix. After training some base classifiers in the new matrix, we again combine the results of the base classifiers. Our experimental results for well-known benchmark databases demonstrate that the proposed mechanism achieves further improved results in terms of classification accuracy compared with the previous approaches. From this consideration, the method could also be applied to other high-dimensional tasks, such as multimedia information retrieval.

Effects of Collective Intelligence-Based SSI Instruction on Promoting Middle School Students' Key Competencies as Citizens (집단지성을 강조한 과학기술 관련 사회쟁점 수업이 중학교 영재학급 학생들의 역량 함양에 미치는 효과)

  • Lee, Hyunju;Choi, Yunhee;Ko, Yeonjoo
    • Journal of The Korean Association For Science Education
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    • v.35 no.3
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    • pp.431-442
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    • 2015
  • SSI instruction can be an effective tool to promote key competencies for future citizens. Our assumption of the study is that applying the concept of collective intelligence in the context of SSI learning would facilitate the learning. Thus, we designed and implemented Collective Intelligence-based SSI instruction over almost a year and observed the effects of the instruction on enhancing students' collaboration, information management, critical thinking, and communication skills. Twenty 9th grade students enrolled in a science-gifted program voluntarily participated. Data was collected by administering a questionnaire to examine the skills before, in the middle of, and after the instruction, and by conducting classroom observations and focus student group interviews. The results indicated some degree of improvement in their targeted skills. First, they experienced the expansion of their thoughts by actively sharing information and ideas using the web platform. Second, they became more flexible and open to different points of views in order to accomplish a common goal. Third, they appreciated having independent time and space to explore their own positions on the issues and to search necessary information, and believed that the process encouraged them to more pro-actively participate and communicate in the group debates. Lastly, they positively perceived the values that collaboration with diverse group members could produce.

Vehicle Headlight and Taillight Recognition in Nighttime using Low-Exposure Camera and Wavelet-based Random Forest (저노출 카메라와 웨이블릿 기반 랜덤 포레스트를 이용한 야간 자동차 전조등 및 후미등 인식)

  • Heo, Duyoung;Kim, Sang Jun;Kwak, Choong Sub;Nam, Jae-Yeal;Ko, Byoung Chul
    • Journal of Broadcast Engineering
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    • v.22 no.3
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    • pp.282-294
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    • 2017
  • In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

A Digital Twin Software Development Framework based on Computing Load Estimation DNN Model (컴퓨팅 부하 예측 DNN 모델 기반 디지털 트윈 소프트웨어 개발 프레임워크)

  • Kim, Dongyeon;Yun, Seongjin;Kim, Won-Tae
    • Journal of Broadcast Engineering
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    • v.26 no.4
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    • pp.368-376
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    • 2021
  • Artificial intelligence clouds help to efficiently develop the autonomous things integrating artificial intelligence technologies and control technologies by sharing the learned models and providing the execution environments. The existing autonomous things development technologies only take into account for the accuracy of artificial intelligence models at the cost of the increment of the complexity of the models including the raise up of the number of the hidden layers and the kernels, and they consequently require a large amount of computation. Since resource-constrained computing environments, could not provide sufficient computing resources for the complex models, they make the autonomous things violate time criticality. In this paper, we propose a digital twin software development framework that selects artificial intelligence models optimized for the computing environments. The proposed framework uses a load estimation DNN model to select the optimal model for the specific computing environments by predicting the load of the artificial intelligence models with digital twin data so that the proposed framework develops the control software. The proposed load estimation DNN model shows up to 20% of error rate compared to the formula-based load estimation scheme by means of the representative CNN models based experiments.

A Deep Learning-based Real-time Deblurring Algorithm on HD Resolution (HD 해상도에서 실시간 구동이 가능한 딥러닝 기반 블러 제거 알고리즘)

  • Shim, Kyujin;Ko, Kangwook;Yoon, Sungjoon;Ha, Namkoo;Lee, Minseok;Jang, Hyunsung;Kwon, Kuyong;Kim, Eunjoon;Kim, Changick
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.3-12
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    • 2022
  • Image deblurring aims to remove image blur, which can be generated while shooting the pictures by the movement of objects, camera shake, blurring of focus, and so forth. With the rise in popularity of smartphones, it is common to carry portable digital cameras daily, so image deblurring techniques have become more significant recently. Originally, image deblurring techniques have been studied using traditional optimization techniques. Then with the recent attention on deep learning, deblurring methods based on convolutional neural networks have been actively proposed. However, most of them have been developed while focusing on better performance. Therefore, it is not easy to use in real situations due to the speed of their algorithms. To tackle this problem, we propose a novel deep learning-based deblurring algorithm that can be operated in real-time on HD resolution. In addition, we improved the training and inference process and could increase the performance of our model without any significant effect on the speed and the speed without any significant effect on the performance. As a result, our algorithm achieves real-time performance by processing 33.74 frames per second at 1280×720 resolution. Furthermore, it shows excellent performance compared to its speed with a PSNR of 29.78 and SSIM of 0.9287 with the GoPro dataset.

Recognition of General arts classes based on movie - Focused on the movie "Untouchables: 1% friendship" (영화 기반 교양교과 수업 활동 탐색 - 영화 「언터처블: 1%의 우정」 중심으로)

  • Kim, Seong-Won;Youn, Jeong-Jin
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.6
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    • pp.63-72
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    • 2017
  • This study made of centrally actual application in general arts classes based on movie in university. Especially, I analyzed the activities of the class with 'Untouchable: 1% friendship' among 6 films. The objects of this study are 44 students of D university in Busan Metropolitan City who take 'creative fusion from movie' general arts class which opened first semester in 2016. In this study, students were able to watch movies through the creative class, which was out of the traditional classroom method, and after 15 hours of learning the quiz online, they conducted 15 weeks as a teaching method to perform tasks, presentations, experiments, and experiences in regular class time. The results of this study are as follows. 'It is a general arts class that makes movements live,' 'It is a general arts class that shows movies from various perspectives,' and 'It is a general arts class that makes me know.' This suggests that the educational medium, which is easily accessible in everyday life, and the general arts class, which is active in the space outside the framework, are perceived as stimulating curiosity and adding fun to college students.

Development of Processing Program for Audio-vision System Based on Auditory Input (청각을 이용한 시각 재현장치의 분석프로그램 개발)

  • Heo, Se-Jin;Bang, Sung-Sik;Seo, Jee-Hye;Choi, Hyun-Woo;Kim, Tae-Ho;Lee, Na-Hee;Lee, Yu-Jin;Park, Ji-Won;Lee, Hui-Joong;Won, Chul-Ho;Lee, Jong-Min
    • Journal of Korea Multimedia Society
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    • v.13 no.1
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    • pp.58-65
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    • 2010
  • The final goal of our research is developing not a simple collision a1ann equipment for the blinded walkers, but the apparatus (Audio- Vision System) which can simulate vision based on auditory information so that the blinds can figure the three dimensional space in front of them. On the way to the final goal, in this study, simulation software was developed and verified. Thirty normal volunteers were included in the subject group and the average age Was 25.8 years old. After being accustomed to the system by evaluating 10 blinded virtual spaces, the volunteers performed test using another set of 10 blinded virtual spaces. The results of test were scored by shape, center, margin, and gradient surface of objects in virtual space. The score of each checking point ranged from 1 to 5, and the full score was converted to 100. As results of this study, the total score ranged from 77 to 97 with the average of 88.7. In this study, a simulation software was developed and verified to have acceptable success rale. By combining to visual sensors, the vision-reconstruction system based on auditory signal (Audio-vision System) may be developed.