Browsing by Author "Chen, Guan-Wen"

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Development of fibroblast-seeded collagen gels under planar biaxial mechanical constraints: a biomechanical study
(2013-10-01)
Hu, Jin-Jia
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Liu, Yen-Ching
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Chen, Guan-Wen
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Wang, Mei-Xuan
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Lee, Pei-Yuan
Prior studies indicated that mechanical loading influences cell turnover and matrix remodeling in tissues, suggesting that mechanical stimuli can play an active role in engineering artificial tissues. While most tissue culture studies focus on influence of uniaxial loading or constraints, effects of multi-axial loading or constraints on tissue development are far from clear. In this study, we examined the biaxial mechanical properties of fibroblast-seeded collagen gels cultured under four different mechanical constraints for 6 days: free-floating, equibiaxial stretching (with three different stretch ratios), strip-biaxial stretching, and uniaxial stretching. Passive mechanical behavior of the cell-seeded gels was also examined after decellularization. A continuum-based two-dimensional Fung model was used to quantify the mechanical behavior of the gel. Based on the model, the value of stored strain energy and the ratio of stiffness in the stretching directions were calculated at prescribed strains for each gel, and statistical comparisons were made among the gels cultured under the various mechanical constraints. Results showed that gels cultured under the free-floating and equibiaxial stretching conditions exhibited a nearly isotropic mechanical behavior, while gels cultured under the strip-biaxial and uniaxial stretching conditions developed a significant degree of mechanical anisotropy. In particular, gels cultured under the equibiaxial stretching condition with a greater stretch ratio appeared to be stiffer than those with a smaller stretch ratio. Also, a decellularized gel was stiffer than its non-decellularized counterpart. Finally, the retained mechanical anisotropy in gels cultured under the strip-biaxial stretching and uniaxial stretching conditions after cell removal reflected an irreversible matrix remodeling.
Microscopic Traffic Monitoring and Data Collection Cloud Platform Based on Aerial Video
(2020-01-01)
Chen, Guan-Wen
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Yeh, Tzu-Chuan
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Liu, Ching-Yu
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Ik, Tsi-Ui
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資訊工程學系
Real-time traffic video streaming, such as roadside surveillance and aerial video, has been widely used in traffic monitoring nowadays. However, most of the traditional traffic data collection methods lack mobility that can only collect macroscopic data. In this paper, an intelligent traffic monitoring system based on an open source cooperative platform called SAGE2 was developed. Based on the integrated big screen TV wall of SAGE2, a map-based aerial traffic video streaming management interface was designed. In the image pre-processing section, it provides functions such as lens distortion removal, top view projection transforms, and video stabilization; simulate video streaming to provide instant and long-term micro-flow data collection. Micro-traffic flow data provides high-resolution information both in time and space which can be used to analyze the driving behavior of individuals and the public. Combined with the lane level map, it can provide a variety of visual vehicle flow presentations, such as intersection traffic distribution that can also be used to develop an innovative application in the future.
Stitching Aerial Images for Vehicle Positioning and Tracking
(2018-01-01)
Tsao, Paul
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Ik, Tsi-Ui
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Chen, Guan-Wen
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Peng, Wen-Chih
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資訊工程學系
In recent years, applications such as reproduction of traffic accident scene, calculation of traffic flow, etc. use UAVs to collect data by aerial images. If a UAV does not move, the coordinates of objects in images can be considered as reference for predicting parameters such as distance and direction. However, this does not apply if the UAV is moving. In this research, methods of image processing are used to obtain the pinhole model which is similar to perpendicularly taken images, which should be distance-preserving. Then, the method of image stitching is used to find out the correlation of relative position between each image in order to construct a global coordinates system over every images. The common used methods of image stitching are not considered about distance-preserving, and cause the cumulative error usually. In this case, GPS information is used to estimate the starting position of images, then stitching those images to a panorama through applying SIFT feature pair and fine-tuning by the gradient method. At last, this paper integrates methods as mentioned into implementation and presents visualized data, then both the trajectory of UAV and the relative position of objects between images and the panorama can be observed by user in order to verify feasibility and precision of methods. Also the results of this paper can be applied with traffic flows detection in the future.