Learning object dynamics for smooth tracking of moving lip contours

2000 ◽  
Vol 36 (6) ◽  
pp. 520 ◽  
Author(s):  
T. Wark ◽  
S. Sridharan ◽  
V. Chandran
Keyword(s):  
Learning Object ◽  
Smooth Tracking ◽  
Object Dynamics

Evaluasi Aksesibilitas Learning Object Berdasarkan Web Content Accessibility Guidelines 2.0

2017 ◽  
Vol 9 (2) ◽  
pp. 67-71
Author(s):  
Herru Darmadi ◽  
Yan Fi ◽  
Hady Pranoto
Keyword(s):  
Learning Objects ◽  
Authoring Tool ◽  
Learning Object ◽  
Web Content ◽  
Web Browser ◽  
E Learning ◽  
Index Terms ◽  
Accessibility Guidelines ◽  
Content Accessibility

Learning Object (LO) is a representation of interactive content that are used to enrich e-learning activities. The goals of this case study were to evaluate accessibility and compatibility factors from learning objects that were produced by using BINUS E-learning Authoring Tool. Data were compiled by using experiment to 30 learning objects by using stratified random sampling from seven faculties in undergraduate program. Data were analyzed using accessibility and compatibility tests based on Web Content Accessibility Guidelines 2.0 Level A. Results of the analysis for accessibility and compatibility tests of Learning Objects was 90% better than average. The result shows that learning objects is fully compatible with major web browser. This paper also presents five accessibility problems found during the test and provide recommendation to overcome the related problems. It can be concluded that the learning objects that were produced using BINUS E-learning Authoring Tool have a high compatibility, with minor accessibility problems. Learning objects with a good accessibility and compatibility will be beneficial to all learner with or without disabilities during their learning process. Index Terms—accessibility, compatibility, HTML, learning object, WCAG2.0, web

scholarly journals Object-Based Approach for Adaptive Source Coding of Surveillance Video

2019 ◽  
Vol 9 (10) ◽  
pp. 2003 ◽  
Author(s):  
Tung-Ming Pan ◽  
Kuo-Chin Fan ◽  
Yuan-Kai Wang
Keyword(s):  
Linear Model ◽  
Video Transmission ◽  
Moving Objects ◽  
Source Coding ◽  
Video Quality ◽  
Surveillance Video ◽  
Surveillance Videos ◽  
Object Based ◽  
High Recognition Accuracy ◽  
Object Dynamics

Intelligent analysis of surveillance videos over networks requires high recognition accuracy by analyzing good-quality videos that however introduce significant bandwidth requirement. Degraded video quality because of high object dynamics under wireless video transmission induces more critical issues to the success of smart video surveillance. In this paper, an object-based source coding method is proposed to preserve constant quality of video streaming over wireless networks. The inverse relationship between video quality and object dynamics (i.e., decreasing video quality due to the occurrence of large and fast-moving objects) is characterized statistically as a linear model. A regression algorithm that uses robust M-estimator statistics is proposed to construct the linear model with respect to different bitrates. The linear model is applied to predict the bitrate increment required to enhance video quality. A simulated wireless environment is set up to verify the proposed method under different wireless situations. Experiments with real surveillance videos of a variety of object dynamics are conducted to evaluate the performance of the method. Experimental results demonstrate significant improvement of streaming videos relative to both visual and quantitative aspects.

The influence of a learning object with virtual simulation for dentistry: A randomized controlled trial

2016 ◽  
Vol 85 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Rodrigo Alves Tubelo ◽  
Vicente Leitune Castelo Branco ◽  
Alessandra Dahmer ◽  
Susana Maria Werner Samuel ◽  
Fabrício Mezzomo Collares
Keyword(s):  
Randomized Controlled Trial ◽  
Controlled Trial ◽  
Virtual Simulation ◽  
Learning Object ◽  
Randomized Controlled

Suppression of heavy-truck driver-seat vibration using sliding-mode control and quantitative feedback theory

2007 ◽  
Vol 221 (5) ◽  
pp. 769-779
Author(s):  
N. I. Rajapakse ◽  
G. S. Happawana ◽  
Y Hurmuzlu
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
Optimization Methods ◽  
Heavy Vehicle ◽  
Quantitative Feedback Theory ◽  
Mode Control ◽  
Smooth Tracking ◽  
Noise Amplification ◽  
Seat Vibration

The current paper presents a robust control method that combines sliding-mode control (SMC) and quantitative feedback theory (QFT) for designing a driver seat of a heavy vehicle to reduce driver fatigue. A mathematical model is considered to analyse tracking control characteristics through computer simulation in order to demonstrate the effectiveness of the proposed control methodology. The SMC is used to track the trajectory of the desired motion behaviour of the seat. However, when the system enters into sliding regime, chattering occurs owing to switching delays as well as vehicle system vibrations. The chattering is eliminated with the introduction QFT inside the boundary layer to ensure smooth tracking. Furthermore, using SMC alone requires higher actuator forces for tracking than using both the control schemes together, and causes various problems in selecting hardware. Problems with noise amplification, resonances, presence of uncertainties, and unmodelled high-frequency dynamics can largely be avoided with the use of QFT over other optimization methods. The main contribution of the present paper is to provide guidance in designing the controller to reduce heavy vehicle seat vibration so that the driver's sensation of comfort maintains a certain level at all times.

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