Manifold learning is a dimension reduction method for extracting nonlinear structures of high-dimensional data. Many methods have been introduced for this purpose. Most of these methods usually extract a global manifold for data. However, in many real-world problems, there is not only one global manifold, but also additional information about the objects is shared by a large number of manifolds...

Design of exhaust manifold is important due to its effects on performance of catalyst, thermal and thermo- mechanical loads. In this paper, first transient analysis of fluid was carried out with FLUENT software, then time-average temperature and heat transfer coefficient contour for three cycle were mapped on inner surface of exhaust manifold with MATLAB software for thermomechanical analysis. ...

NNowadays, car manufactures in order to increasing torque and power with consider to fuel consumption, have swept to production of turbocharged engines. With consider to exhaust gas-temperature rises in boosted engines, recognition of critical locations of exhaust manifold in the worse condition of engine (full load and maximum speed), to prevent fracture of exhaust manifold is very important. ...

In this paper, attempting to improve the recognition rate and solve some problems such as pose, lighting variations and partial occlusion in video sequences using Orthogonal Locality Preserving Projection (OLPP). In this research, first of all face in video frames is detected for background removing. Then each set of images is distributed on a nonlinear manifold and clustered using appropriate ...