Development of Platform Independent Remote Experiments

Remote laboratory or online laboratory is the use of the Internet to conduct real experiments remotely when the client is geographically away from the real experiments. Current remote laboratories such as the remote laboratory in Mechanical Engineering at University of Houston require the client to install plug-ins before conducting remote experiments. This thesis presents an advanced technology using JavaScript and Socket.IO to develop plug-in free remote experiments without firewall issue. A scalable plug-in free remote laboratory integrated with two remote experiments has been set up in the Mechanical Engineering Department at the Texas A&M University at Qatar (TAMUQ) in Qatar under the collaboration from the University of Houston and the Texas Southern University in Houston, Texas. The plug-free remote laboratory has been successfully tested in Windows PC, Mac OS, iPhone and iPad (iOS).Mechanical Engineering, Department o

Slip of fluid molecules on solid surfaces by surface diffusion

The mechanism of fluid slip on a solid surface has been linked to surface diffusion, by which mobile adsorbed fluid molecules perform hops between adsorption sites. However, slip velocity arising from this surface hopping mechanism has been estimated to be significantly lower than that observed experimentally. In this paper, we propose a re-adsorption mechanism for fluid slip. Slip velocity predictions via this mechanism show the improved agreement with experimental measurements

Stress Monitoring for Anchor Rods System in Subway Tunnel Using FBG Technology

This paper presents a model test, used on the tunnels on Xi’an Metro Line 2, as the prototype for evaluating the reinforcing effect of the anchor rod in tunnel construction in loess areas. An independently designed fiber Bragg grating (FBG) sensor was used to monitor the seven strain conditions of the rock bolts during the construction. The result shows that the axial stress of the rock bolt changes after the excavation and increases steadily with the growing pressure in the wall rock. Results additionally show that the anchor rods at the tunnel vault are subjected to a compressive stress that remains relatively constant after the primary and the secondary lining, while those at the spandrel and the corner of the tunnel are subjected to increased tensile stress. This paper demonstrates the feasibility and the superiority of FBG technology for tunnel model tests

PartCom: Part Composition Learning for 3D Open-Set Recognition

3D recognition is the foundation of 3D deep learning in many emerging fields, such as autonomous driving and robotics.Existing 3D methods mainly focus on the recognition of a fixed set of known classes and neglect possible unknown classes during testing. These unknown classes may cause serious accidents in safety-critical applications, i.e. autonomous driving. In this work, we make a first attempt to address 3D open-set recognition (OSR) so that a classifier can recognize known classes as well as be aware of unknown classes. We analyze open-set risks in the 3D domain and point out the overconfidence and under-representation problems that make existing methods perform poorly on the 3D OSR task. To resolve above problems, we propose a novel part prototype-based OSR method named PartCom. We use part prototypes to represent a 3D shape as a part composition, since a part composition can represent the overall structure of a shape and can help distinguish different known classes and unknown ones. Then we formulate two constraints on part prototypes to ensure their effectiveness. To reduce open-set risks further, we devise a PUFS module to synthesize unknown features as representatives of unknown samples by mixing up part composite features of different classes. We conduct experiments on three kinds of 3D OSR tasks based on both CAD shape dataset and scan shape dataset. Extensive experiments show that our method is powerful in classifying known classes and unknown ones and can attain much better results than SOTA baselines on all 3D OSR tasks. The project will be released