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Combined MHD and Pulsatile Flow on Porous Medium
Get PDFThis work investigates the dynamic behavior of a pulsatile flow electrically conducting through porous medium in a cylindrical conduit under the influence of a magnetic field. The imposed magnetic field is assumed to be uniform and constant. An exact solution of the equations governing magneto hydro-dynamics (MHD) flow in a conduit has been obtained in the form of Bessel functions. The analytical study has been used to establish an expression between the Hartmann number, Darcy number and the stress coefficient. The numerical method is based on an implicit finite difference time marching scheme using the Thomas algorithm and Gauss Seidel iterative method for solving the resulting algebraic system of equations. The results show that the flow behavior is strongly affected by the permeability parameter of medium porosity and the Hartmann number. It has also shown that the stress coefficient has a sinusoidal aspect and it increases with decreasing Darcy number
Recent Developments About IPMCs (Ionic Polymer-Metal) Composites: A Review of Performances for Different Conditions
Get PDFIt is of great significance for the production of micro robots and new sensors to develop actuators with “muscle” properties. As a kind of electroactive polymers (EAPs), IPMC (ionic polymer-metal composite) can exhibit significant deformation for very low electrical excitation. These composites, known as the “artificial muscle”, can be regarded as intelligent bionic materials. With regard to the mechanism of deformation of IPMC, a large number of experimental studies have proved that the variety of electrodes and water contents relating to IPMC have great influence on its electro-mechanical and mechanical properties. Recent research results about IPMC were summarized here to provide a reference for the design and manufacture of these materials. Our conclusions show that, among the main electrode material, though Pt and Au show excellent stability and conductivity, the utilization is limited due to high cost. While Ag, as electrode material, has better application prospect, due to good conductivity and tensile properties. But the optimal voltage under electrical excitation need to be considered when used in specific conditions, or it will cause rapid failure of Ag-IPMC. In addition, IPMC displays high sensitivity to the water content, the service life of IPMC can significantly be prolonged by increasing the degree of humidity of the working environment. So the prospect of IPMC is appropriate to be used in underwater robots, as drivers or actuators
Solution of Algebraic Lyapunov Equation on Positive-Definite Hermitian Matrices by Using Extended Hamiltonian Algorithm
Get PDFThis communique is opted to study the approximate solution of the Algebraic Lyapunov equation on the manifold of positive-definite Hermitian matrices. We choose the geodesic distance between -AHX - XA and P as the cost function, and put forward the Extended Hamiltonian algorithm (EHA) and Natural gradient algorithm (NGA) for the solution. Finally, several numerical experiments give you an idea about the effectiveness of the proposed algorithms. We also show the comparison between these two algorithms EHA and NGA. Obtained results are provided and analyzed graphically. We also conclude that the extended Hamiltonian algorithm has better convergence speed than the natural gradient algorithm, whereas the trajectory of the solution matrix is optimal in case of Natural gradient algorithm (NGA) as compared to Extended Hamiltonian Algorithm (EHA). The aim of this paper is to show that the Extended Hamiltonian algorithm (EHA) has superior convergence properties as compared to Natural gradient algorithm (NGA). Upto the best of author’s knowledge, no approximate solution of the Algebraic Lyapunov equation on the manifold of positive-definite Hermitian matrices is found so far in the literature
On Special Curves According to Darboux Frame in the Three Dimensional Lorentz Space
Get PDFIn the light of great importance of curves and their frames in many different branches of science, especially differential geometry as well as geometric properties and the uses in various fields, we are interested here to study a special kind of curves called Smarandache curves in Lorentz 3-space. Then, we present some characterizations for these curves and calculate their Darboux invariants. Moreover, we classify TP, TU, PU and TPU-Smarandache curves of a spacelike curve according to the causal character of the vector, curve and surface used in the study. Besides, we give some of differential geometric properties and important relations between that curves. Finally, to demonstrate our theoretical results a computational example is given with graph
Identifying Materials of Photographic Images and Photorealistic Computer Generated Graphics Based on Deep CNNs
Get PDFCurrently, some photorealistic computer graphics are very similar to photographic images. Photorealistic computer generated graphics can be forged as photographic images, causing serious security problems. The aim of this work is to use a deep neural network to detect photographic images (PI) versus computer generated graphics (CG). In existing approaches, image feature classification is computationally intensive and fails to achieve real-time analysis. This paper presents an effective approach to automatically identify PI and CG based on deep convolutional neural networks (DCNNs). Compared with some existing methods, the proposed method achieves real-time forensic tasks by deepening the network structure. Experimental results show that this approach can effectively identify PI and CG with average detection accuracy of 98%
Controlled Cyclic Remote State Preparation of Arbitrary Qubit States
Get PDFQuantum secure communications could securely transmit quantum information by using quantum resource. Recently, novel applications such as bidirectional and asymmetric quantum protocols have been developed. In this paper, we propose a new method for generating entanglement which is highly useful for multiparty quantum communications such as teleportation and Remote State Preparation (RSP). As one of its applications, we propose a new type of quantum secure communications, i.e. cyclic RSP protocols. Starting from a four-party controlled cyclic RSP protocol of one-qubit states, we show that this cyclic protocol can be generalized to a multiparty controlled cyclic RSP protocol for preparation of arbitrary qubit states. We point out that previous bidirectional and asymmetric protocols can be regarded as a simpler form of our cyclic RSP protocols
Rare Bird Sparse Recognition via Part-Based Gist Feature Fusion and Regularized Intraclass Dictionary Learning
Get PDFRare bird has long been considered an important in the field of airport security, biological conservation, environmental monitoring, and so on. With the development and popularization of IOT-based video surveillance, all day and weather unattended bird monitoring becomes possible. However, the current mainstream bird recognition methods are mostly based on deep learning. These will be appropriate for big data applications, but the training sample size for rare bird is usually very short. Therefore, this paper presents a new sparse recognition model via improved part detection and our previous dictionary learning. There are two achievements in our work: (1) after the part localization with selective search, the gist feature of all bird image parts will be fused as data description; (2) the fused gist feature needs to be learned through our proposed intraclass dictionary learning with regularized K-singular value decomposition. According to above two innovations, the rare bird sparse recognition will be implemented by solving one l1-norm optimization. In the experiment with Caltech-UCSD Birds-200-2011 dataset, results show the proposed method can have better recognition performance than other SR methods for rare bird task with small sample size
Automatic Mining of Security-Sensitive Functions from Source Code
Get PDFWhen dealing with the large-scale program, many automatic vulnerability mining techniques encounter such problems as path explosion, state explosion, and low efficiency. Decomposition of large-scale programs based on safety-sensitive functions helps solve the above problems. And manual identification of security-sensitive functions is a tedious task, especially for the large-scale program. This study proposes a method to mine security-sensitive functions the arguments of which need to be checked before they are called. Two argument-checking identification algorithms are proposed based on the analysis of two implementations of argument checking. Based on these algorithms, security-sensitive functions are detected based on the ratio of invocation instances the arguments of which have been protected to the total number of instances. The results of experiments on three well-known open-source projects show that the proposed method can outperform competing methods in the literature
Crowdsourcing-Based Framework for Teaching Quality Evaluation and Feedback Using Linguistic 2-Tuple
Get PDFCrowdsourcing is widely used in various fields to collect goods and services from large participants. Evaluating teaching quality by collecting feedback from experts or students after class is not only delayed but also not accurate. In this paper, we present a crowdsourcing-based framework to evaluate teaching quality in the classroom using a weighted average operator to aggregate information from students’ questionnaires described by linguistic 2-tuple terms. Then we define crowd grade based on similarity degree to distinguish contribution from different students and minimize the abnormal students’ impact on the evaluation. The crowd grade would be updated at the end of each feedback so it can guarantee the evaluation accurately. Moreover, a simulated case is shown to illustrate how to apply this framework to assess teaching quality in the classroom. Finally, we developed a prototype and carried out some experiments on a series of real questionnaires and two sets of modified data. The results show that teachers can locate the weak points of teaching and furthermore to identify the abnormal students to improve the teaching quality. Meanwhile, our approach provides a strong tolerance for the abnormal student to make the evaluation more accurate
