A new and robust method for character segmentation and recognition in license plate images

This paper provides a new and fast method for segmentation and recognition of characters in license plate images. For this purpose, various methods have been proposed in literature. However, most of them suffer from: sensitivity to non-uniform illumination distribution, existence of shade in license plate, license plate color and the need for receiving an exact image of the license plate. In the proposed algorithm, non-uniform illumination and noise are reduced by a Gaussian lowpass filter and also by an innovational Laplacian-like transform and characters are segmented by a set of indigenous and relative features. To be prepared for recognition, the segmented characters are normalized by a local algorithm. Two feed-forward neural networks with back-propagation learning method are employed for character recognition. The principal component analysis (PCA) is used to decrease input data and, consequently, computational complexity. The proposed algorithm does not necessarily need an exact plate image and can receive a band from the vehicle original image as an input, which includes the plate. Our proposed method is completely robust to the disturbances such as non-uniform brightness distribution on the various positions of a license plate image and the plate color. In order to evaluate our algorithm, we applied it on a database including 120 vehicle images with different backgrounds, plate colors, brightness distributions, distances and viewing angles. The results confirm the robustness of the proposed method against severe imaging conditions.     

NanoHDA: A nanoparticle-assisted isothermal amplification technique for genotyping assays

Isothermal methods, such as helicase-dependent amplification (HDA), have an advantage over polymerase chain reaction for DNA amplification owing to their ease of operation. Here, we developed a new HDA method that is nanoparticle-assisted, termed nanoHDA. This method uses gold nanoparticles (AuNPs) to improve the sensitivity and specificity of the isothermal method. In HDA, the denaturation of DNA templates is mediated by helicases, but this method is limited by the low denaturation efficiency of helicases. In this report, AuNPs with preferential affinity for single-stranded DNA (ssDNA) were utilized to improve the denaturation efficiency of helicases. The same affinity property of nanoparticles can also enhance specificity by suppressing primer-dimer formation. This nanoHDA method was employed to genotype the KRAS gene in genomic DNA samples from colorectal cancer patients, as achieved by the hybridization of nanoHDA amplicons using the NanoBioArray chip.

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Static and Dynamic Pull-In Instability of Nano-Beams Resting on Elastic Foundation Based on the Nonlocal Elasticity Theory

This paper provides the static and dynamic pull-in behavior of nano-beams resting on the elastic foundation based on the nonlocal theory which is able to capture the size effects for structures in micron and sub-micron scales. For this purpose, the governing equation of motion and the boundary conditions are driven using a variational approach. This formulation includes the influences of fringing field and intermolecular forces such as Casimir and van der Waals forces. The differential quadrature (DQ) method is employed as a high-order approximation to discretize the governing nonlinear differential equation, yielding more accurate results with a considerably smaller number of grid points. In addition, a powerful analytical method called parameter expansion method (PEM) is utilized to compute the dynamic solution and frequency-amplitude relationship. It is illustrated that the first two terms in series expansions are sufficient to produce an acceptable solution of the mentioned structure. Finally, the effects of basic parameters on static and dynamic pull-in instability and natural frequency are studied.     

An insight into mode II fracture toughness testing using SCB specimen

The effect of friction forces between the test specimen and its bottom supports on the mode II fracture toughness values obtained using the semicircular bend (SCB) specimen is investigated. First, a number of experiments were conducted on SCB specimen in order to determine the mode II fracture toughness of polymethyl methacrylate (PMMA) according to the conventional approaches available in the literature. Three different types of supports that have been frequently employed by researchers in recent years were used to evaluate the effect of support type on the fracture loads. It was found that the friction forces between the supports and the SCB specimen have a significant effect on the value of mode II fracture toughness measured using the SCB samples. Then, the specimen was simulated using finite element method for more detailed investigation on the near crack tip stress field evolution when friction forces increase between the supports and the SCB specimen. The finite element results confirmed that the type of support affects not only the stress intensity factors K_I and K_II but also the T‐stress. The experimental and numerical results showed that the use of the crack tip parameters available in literature for frictionless contact between the supports and the SCB specimen can result in significant errors when the mode II experiments are performed by using the fixed or roller‐in‐grove types of supports.     

Optimal Spectrum Allocation Based on Primary User Activity Model in Cognitive Radio Wireless Sensor Networks

Wireless Personal Communications - In Cognitive Radio Wireless Sensor Networks, the licensed spectrum bands are highly dynamic, and their status varies overtime. With the expansion of these...     

Depth-optimized reversible circuit synthesis

In this paper, simultaneous reduction of circuit depth and synthesis cost of reversible circuits in quantum technologies with limited interaction is addressed. We developed a cycle-based synthesis algorithm which uses negative controls and limited distance between gate lines. To improve circuit depth, a new parallel structure is introduced in which before synthesis a set of disjoint cycles are extracted from the input specification and distributed into some subsets. The cycles of each subset are synthesized independently on different sets of ancillae. Accordingly, each disjoint set can be synthesized by different synthesis methods. Our analysis shows that the best worst-case synthesis cost of reversible circuits in the linear nearest neighbor architecture is improved by the proposed approach. Our experimental results reveal the effectiveness of the proposed approach to reduce cost and circuit depth for several benchmarks.     

Automatic translation of quantum circuits to optimized one-way quantum computation patterns

One-way quantum computation (1WQC) is a model of universal quantum computations in which a specific highly entangled state called a cluster state (or graph state) allows for quantum computation by only single-qubit measurements. The needed computations in this model are organized as measurement patterns. Previously, an automatic approach to extract a 1WQC pattern from a quantum circuit has been proposed. It takes a quantum circuit consisting of CZ and \(J(\alpha )\) gates and translates it into an optimized 1WQC pattern. However, the quantum synthesis algorithms usually decompose circuits using a library containing CNOT and any single-qubit gates. In this paper, we show how this approach can be modified in a way that it can take a circuit consisting of CNOT and any single-qubit gates to produce an optimized 1WQC pattern. The single-qubit gates are first automatically \(J\) -decomposed and then added to the measurement patterns. Moreover, a new optimization technique is proposed by presenting some algorithms to add Pauli gates to the measurement patterns directly, i.e., without their \(J\) -decomposition which leads to more compact patterns for these gates. Using these algorithms, an improved approach for adding single-qubit gates to measurement patterns is proposed. The optimized pattern of CNOT gates is directly added to the measurement patterns. Experimental results show that the proposed approach can efficiently produce optimized patterns for quantum circuits and that adding CNOT gates directly to the measurement patterns decreases the translation runtime.     

Effects of aluminum and copper cover tube casing on the ECAP process of AM30 magnesium alloy

Aluminum (Al) and copper (Cu) thin tube casings were employed to facilitate the equal channel angular pressing (ECAP) process of wrought AM30 magnesium (Mg) alloy. We covered the Mg rods (diameter, 14?mm) with pure copper (Mg/Cu) and Al-1050 alloy (Mg/Al) sheaths in the form of tubes (thickness, 2.5?mm). We then performed the ECAP processes at 200, 250, and 275°C using the conventional ECAP of AM30 alloy and covered tube casing (CTC) methods with a single pass. We assessed the effect of CTC on ECAP temperature, grain refinement, uniformity of structure, hardness distribution, and strength. The results of Mg/Cu and Mg/Al bimetal sample tests showed that there was a significant decrease in the process temperature when compared with the conventional ECAP of AM30. The sheath resolved the segmented material flow that occurred in a conventional ECAP of material at 250°C, and transformed it to a uniform flow in CTC bimetal samples. Grain sizes of the CTC samples decreased by 20% compared with the conventional ECAP of AM30 samples. Furthermore, grain uniformity, strain distribution homogeneity, tensile yield strength (TYS), and elongation increased. However, we observed a similar trend of deformation twinning in compression test results for the ECAP and CTC methods, and there was no significant variation in material yield asymmetry between the ECAP and CTC samples.