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This paper shows a new study on the effect of various dry and isotropic friction levels on the progression and dynamic response of a vibro-impact locomotion system. An experimental vibro-impact self-propelled apparatus, which is able to vary the friction force while remaining the total weight of the system, was practically implemented. A new dimensionless model was developed based on the validated mathematical model, allowing to examine the effects of the excitation force and the friction force independently. The experimental data revealed that, the force ratio between the excitation magnitude and friction level would not be totally correct to represent the excitation effects in dimensionless modeling the system. The level of friction force may have a significant effect not only on how fast the system move, but also on which direction of the progression. Bifurcation analysis and basin of attraction were calculated to scrutinize the effect of friction on the scaled model. The results showed that various friction would lead to either period-1 or chaotic motion of the system. The new findings would be useful for further studies on the design and operation of vibro-impact driven locomotion systems and capsule robots.

In this paper, we study the multipath routing problem in MPTCP-enable software-defined networks. We have proposed an efficient multipath routing algorithm for creating bandwidth-abundant and flexible future software-defined core networks. Our proposed algorithm will figure out k-least-jointed shortest paths by using conventional k-shortest path algorithm, e.g., Yen's algorithm, incorporating with a greedy algorithm for the path selection. Thanks to that, the algorithm can help to exploit the use of MPTCP while reducing the bottleneck problem that may occur with shared links in the networks. In order to verify the efficiency of our proposal, we have implemented an MPTCP-enable software-defined testbed based on mininet, Ryu controller, and Kali Linux OS and perform numerical experiments to compare the network performance of our approach to traditional MPTCP as well as conventional TCP (without MPTCP). The obtained results confirmed that, by reducing the number of jointed links in the set of selected k-shortest paths, our solution outperforms the traditional MPTCP as well as that of conventional TCP networks.

This report presents some experimental results of the effect of the Coulomb friction on the resonant frequency of the two-mass system connected by a nonlinear leaf spring. The experimental apparatus designed and built has an ability to vary the excitation frequency, the excitation force and friction force. Experimental data show that the resonance frequency of the system tends to decrease when increasing the friction force. The resonant frequency of the system can be expressed as the functions depending both on the amplitude of excitation force and on the Coulomb friction force. The experimental results serve as the basic premise for the development of studies applied in self-movement structure operating under different resistant environments.

3D scene shape retrieval is a brand new but important research direction in content-based 3D shape retrieval. To promote this research area, two Shape Retrieval Contest (SHREC) tracks on 2D scene sketch-based and image-based 3D scene model retrieval have been organized by us in 2018 and 2019, respectively. In 2018, we built the first benchmark for each track which contains 2D and 3D scene data for ten (10) categories, while they share the same 3D scene target dataset. Four and five distinct 3D scene shape retrieval methods have competed with each other in these two contests, respectively. In 2019, to measure and compare the scalability performance of the participating and other promising Query-by-Sketch or Query-by-Image 3D scene shape retrieval methods, we built a much larger extended benchmark for each type of retrieval which has thirty (30) classes and organized two extended tracks. Again, two and three different 3D scene shape retrieval methods have contended in these two tracks, separately. To solicit state-of-the-art approaches, we perform a comprehensive comparison of all the above methods and an additional new retrieval methods by evaluating them on the two benchmarks. The benchmarks, evaluation results and tools are publicly available at our track websites (Yuan et al., 2019 [1]; Abdul-Rashid et al., 2019 [2]; Yuan et al., 2019 [3]; Abdul-Rashid et al., 2019 [4]), while code for the evaluated methods are also available: http://github.com/3DSceneRetrieval .

This paper shows experimental analysis results of the study on vibration-driven locomotion system, which can be applied in capsule robots. The experimental apparatus provided a capacity of varying friction force when keeping the weight of the whole system unchanged. Twelve experimental sets with 16 runs for each set were implemented, providing a deep insight of the system behavior, both in progression rate and the relative motions of the masses. The experimental data revealed that, the force ratio between the excitation magnitude and friction level would not be totally correct to present the excitation effects in modeling the system. The level of friction force may have a significant effect on not only how fast the system move, but also which direction of the progression. The new findings would be useful for further studies on the design and operation of vibration driven locomotion systems.

Traffic flow analysis is essential for intelligent transportation systems. In this paper, we introduce our Intelligent Traffic Analysis Software Kit (iTASK) to tackle three challenging problems: vehicle flow counting, vehicle re-identification, and abnormal event detection. For the first problem, we propose to real-time track vehicles moving along the desired direction in corresponding motion-of-interests (MOIs). For the second problem, we consider each vehicle as a document with multiple semantic words (i.e., vehicle attributes) and transform the given problem to classical document retrieval. For the last problem, we propose to forward and backward refine anomaly detection using GAN-based future prediction and backward tracking completely stalled vehicle or sudden-change direction, respectively. Experiments on the datasets of traffic flow analysis from AI City Challenge 2020 show our competitive results, namely, S1 score of 0.8297 for vehicle flow counting in Track 1, mAP score of 0.3882 for vehicle re-identification in Track 2, and S4 score of 0.9059 for anomaly detection in Track 4. All data and source code are publicly available on our project page. 1

This study proposes a nonlinear dynamic model of the heavy trucks to evaluate the influence of the various working conditions on the ride comfort and road friendliness of the heavy vehicles based on Matlab/Simulink software. The weighted root mean square (RMS) acceleration responses of the vertical driver’s seat, the cab’s pitch and roll angles, and the dynamic load coefficient (DLC) are chosen as objective functions. The influence of the vehicle velocity and loads on the different road surfaces are evaluated based on the standard ISO 2631-1. The results show that the vehicle’s ride comfort is clearly affected on the road surfaces of ISO level C and D at the range of the vehicle velocity. Especially, the vehicle’s ride comfort is very poor at the velocity of 10-30 m.s-1 on ISO level D. The road friendliness of the vehicle is greatly decreased in the condition of the half-loaded vehicle. Particularly the vertical dynamic wheel loads at 2nd axle strongly affect the road damage at the velocity of 10-30 m.s-1.

In order to improve the vibratory roller’s ride comfort, a 3-D nonlinear dynamic model of the vehicle interacting with the off-road terrain is established. A damper hydraulic mount is studied and combined with the cab’s rubber mounts to simulate and evaluate the performance of the ride comfort. The weighted RMS acceleration responses of the vertical driver’s seat, the cab’s pitch and roll angle are chosen as objective functions. The results show that the cab’s rubber mounts combined with the damper hydraulic mount are clearly improved the ride comfort under various operating conditions. Especially, with damping coefficients cc3,4= 1.8 kN.s.m-1, the weighted RMS values of the vertical driver’s seat, the cab’s pitch and roll angle are greatly reduced by 27.8 %, 22.7 % and 64.3 % in condition of the vehicle traveling, and by 23.8 %, 20.0 % and 63.7 % in condition of the vehicle compacting on an elastic-plastic terrain.

In order to improve the vibratory roller ride comfort, a multi-objective optimization method based on the improved genetic algorithm NSGA-II is proposed to optimize the design parameters of cab’s isolation system when vehicle operates under the different conditions. To achieve this goal, 3D nonlinear dynamic model of a single drum vibratory roller was developed based on the analysis of the interaction between vibratory roller and soil. The weighted r.m.s acceleration responses of the vertical driver’s seat, pitch and roll angle of the cab are chosen as the objective functions. The optimal design parameters of cab’s isolation system are indentified based on a combination of the vehicle nonlinear dynamic model of Matlab/Simulink and the NSGA - II genetic algorithm method. The results indicate that three objective function values are reduced significantly to improve vehicle ride comfort.

As inertial sensors are low-cost, easy-to-use, and can be integrated in wearable devices, they can be used to establish as a new modality for user authentication in the smart environment in which computing systems can recognize persons implicitly by their walking patterns. This motivates our proposal to use multi-region size Convolutional Neural Network to recognize users from their gait patterns recorded from accelerometers and gyroscopes in mobile and wearable devices.