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Corrective Feedback through Computer-Mediated Communication in EFL College Level
Juseong Lee,Kilryoung Lee 팬코리아영어교육학회(구 영남영어교육학회) 2010 영어교육연구 Vol.22 No.1
The purpose of this study was to explore the effectiveness of written corrective feedback (CF) in Computer-Mediated Communication (CMC) on the English language ability of Korean college students. This also investigated their attitudes toward direct-CF and indirect-CF in CMC. This study was carried out with three Korean EFL college students for fourteen weeks. They wrote essays weekly and uploaded them to a blog. One of the researchers gave each essay feedback-direct CF for the first seven weeks and indirect CF for the second seven weeks. The essays were analyzed, based on the grounded theory, for the development of learner language. There were three major findings: Firstly, there was a gradual improvement in accuracy, fluency, and complexity. However, one of the participants showed different fluency and complexity performance depending on different writing tasks and learning strategies. Secondly, written CF in CMC was helpful in reducing errors in all error categories. Finally, the students reported that they preferred to receive indirect CF. This study shows important pedagogical implications about CF, bringing into attention to the most effective method of written CF and the role that CMC can play in providing the feedback.
( Juseong Lee ),( Junghoon Kim ) 대한운동사협회 2022 대한운동사협회 운동사대회자료집 Vol.2022 No.-
OBJECTIVES Electrical Muscle Stimulation (EMS) has originally used to help people who are partially or completely immobile with rehabilitation. Recently, EMS was used as a training tool for athletes and healthy people to improve the muscular strength and function. Although many studies have been evaluated that EMS training has been proven to be effective in energy expenditure, body composition, and muscle function, it was still no certain whether it was the additional effects of EMS on non-athletic populations. Therefore, we aimed to investigate the acute (energy expenditure and metabolism) and chronic (body composition and muscle function) effects of the EMS training in female adults. METHODS To identify the acute and chronic effects of EMS, we performed two experiments. In a first study, to verify the acute effects of EMS, ten young females (age: 23.0±3.6 years) recruited in the randomized cross-over trials (weight-bearing training without EMS vs weight-bearing training with EMS). Oxygen consumption and blood lactate were measured to evaluate the energy expenditure and metabolism during each type of training. In a second study, 23 adults were randomly allocated to weight-bearing (WB-G; n=11) and EMS training group (EMS-G, n=12), and 21 participants (WB-G: n=10, 40.0±5.0 years; and EMS-G: n=11, 41.1±3.7 years) completed the 10 weeks intervention. A computer-tomography scan was used to evaluate visceral fat area of abdomen, and cross-sectional area of thigh. The maximum muscle strength in a knee joint was evaluated by Biodex System 3. RESULTS The acute EMS training showed higher energy expenditure per exercise than weight-bearing training (WB-G: 72.1±10.3 kcal/session vs EMS-G: 87.0±17.0 kcal/session; p=0.018) and showed more lactate production (Lactate: 1.8±2.1 mmol/L vs 4.4±2.6 mmol/L; p=0.005). As a result of intervention in 10 weeks based on effects of energy expenditure and metabolism, visceral fat area of the abdomen significantly reduced in EMS group (Pre: 96.4±33.5 cm2, Post: 90.4±30.8 cm2; p=0.017) with significant the interaction of time and group (Time×Group: p=0.017). In addition, isokinetic peak torque at high angular speeds (90°/s, 180°/s) was significantly increased after EMS training, but there was no significant difference between both groups. CONCLUSIONS We found that the EMS training contributes to higher energy expenditure and lactate production. In addition, these metabolic benefits of EMS may affect the reduction of the abdominal visceral fat area with long-term exercise. Consequently, these findings suggest that the change of body composition may attribute to improved energy expenditure caused by EMS application during weight-bearing training.
Energy Efficient Canny Edge Detector for Advanced Mobile Vision Applications
Lee, Juseong,Tang, Hoyoung,Park, Jongsun IEEE 2018 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDE Vol.28 No.4
<P>In this paper, we present an energy-efficient architecture of the Canny edge detector for advanced mobile vision applications. Three key techniques for reducing computational complexity of the Canny edge detector are presented. First, by exploiting the rank characteristic of the convolution kernel of Gaussian smoothing and Sobel gradient filters, common computations are identified and shared in the image filter design to reduce the number of additions and multiplications. For the gradient magnitude/direction computation, only three directions of neighboring pixels are considered to reduce computation energy with minor degradation on conformance performance (CP). For the adaptive threshold selections, an interesting observation is that the mean values of gradient magnitudes show small variations depending on the classified block types. Thus, the threshold selection process can be simplified as multiplying the mean value of the local block with predecided constants. The proposed low complexity Canny edge detector has been implemented using both field-programmable gate arrays (FPGAs) and a 65-nm standard-cell library. The FPGA implementation with Xilinx Virtex-V (XC5VSX240T) shows that our edge detector achieves 48% of area and 73% of execution time savings over the conventional architecture without seriously sacrificing the detection performance. The proposed edge detector implemented with 65-nm standard-cell library can easily support real-time ultrahigh definition video data processing (50 frames/s) with the power consumption of 5.48 mW (108.84 <TEX>$\mu \text{J}$</TEX>/frame).</P>
블록 유형 분류 알고리즘 기반 고속 특징추출 시스템 구현에 관한 연구
이주성(Juseong Lee),안호명(Ho-Myoung An) 한국정보전자통신기술학회 2019 한국정보전자통신기술학회논문지 Vol.12 No.3
본 논문은 고속 특징추출 알고리즘의 구현 방법을 제안한다. 제안하는 방법은 블록 유형 분류 알고리즘을 기반으로, 블록 유형 분류 알고리즘 적용 시, 영상 특징 정보가 발생하지 않는 스무스 블록에서 연산을 생략하여 영상 특징 검출에 필요한 연산시간을 감소시킬 수 있다. 200장의 표준 테스트 이미지를 활용해 매크로 블록의 크기를 64×64로 나누어 스무스 블록의 발생 빈도를 측정한 결과 전체의 29.5%만큼 발생하는 것을 정량적으로 확인했다. 이 의미는 다양한 영상 정보를 포함하고 있는 표준 테스트 이미지 내에서는 29.5%에 해당하는 만큼 연산의 복잡도를 감소시킬 수 있다는 의미를 나타낸다. 제안된 방법을 케니 윤곽선 검출 알고리즘에 적용하면 이차원 미분 필터, 그라디언트 크기 및 방향 연산, 비최대 억제, 적응형 임계값 연산, 히스테리시스 임계 처리와 같은 총 다섯 단계의 영상처리에 필요한 지연시간을 완전히 제거할 수 있다. 이와 같은 방법으로 다양한 특징 검출 알고리즘에 블록 유형 구분 알고리즘을 적용해, 연산에 필요한 시간을 감소할 수 있을 것을 기대한다. In this paper, we propose a implementation approach of the high-speed feature extraction algorithm. The proposed method is based on the block type classification algorithm which reduces the computation time when target macro block is divided to smooth block type that has no image features. It is quantitatively identified that occurs at 29.5% of the total image using 200 standard test images with 64×64 macro block size. This means that within a standard test image containing various image information, 29.5% can reduce the complexity of the operation. When the proposed approach is applied to the Canny edge detection, the required latency of the edge detection can be completely eliminated, such as 2D derivative filter, gradient magnitude/direction computation, non-maximal suppression, adaptive threshold calculation, hysteresis thresholding. Also, it is expected that operation time of the feature detection can be reduced by applying block type classification algorithm to various feature extraction algorithms in this way.