Heat transport at the microscale is of vital importance in microtechnology applications. The heat transport equation is different from the traditional heat diffusion equation since a second-order derivative of temperature with respect to time and a third-order mixed derivative of temperature with respect to space and time are introduced. In this paper, the reduced differential transform method (reduced-DTM), is employed to obtain the numerical/analytical solutions of this equation. We begin by showing that how the reduced-DTM applies to a linear and non-linear part of any PDEs. In this method, the solution is calculated in the form of a convergent series with an easily computable component. This approach does not need linearization, weak nonlinearity assumptions or perturbation theory. We also compare obtained approximation solution against exact solution. These results show that the technique introduced here is accurate and easy to apply.
Abstract —in this paper, first, we color the gray level pictures but later we want to perform the coloring of human pictures automatically and intelligently by means of the implemented neural network .Because of the technique applied in this paper, this method can be used in colorizing medical images. Color images achieved have good distinction and separation. For this purpose, a combination of artificial neural networks and some image processing algorithms was developed to transfer colors from a user-selected source image to a target grayscale image. The proposed method can be used to separate the objects in gray images. Our method is based on a simple premise: neighboring pixels in space-time that have similar intensities should have similar colors. We formalize this premise using a quadratic cost function and obtain an optimization problem that can be solved efficiently using standard techniques. In our approach an artist only needs to annotate the image with a few color scribbles, and the indicated colors are automatically propagated in both space and time to produce a fully colorized image or sequence.
This study was conducted EEG experiments to characterize the influence of visual orthography on the most robust auditory event-related potentials (ERPs) and focused the analysis on systematic variation of the auditory ERP as a function of visual orthography information. To study the human brain’s audiovisual integration mechanisms for letters, the subjects received auditory, visual, and audiovisual letters of the Chinese character and were required to identify them, regardless of stimulus modality. Audiovisual letters included matching letters, in which the auditory and visual stimulus corresponded to each other based on previous experience, and nonmatching (randomly paired) letters. Meaningless auditory, visual, and audiovisual control stimuli were presented as well. Fourteen adult, native speakers of Mandarin Chinese were participated in the ERP experiment. The result demonstrates that the audiovisual interaction is an indicator for investigating the automatic processing of suprasegmental information in tonal language. The finding gives support for the view that both sensory-specific and heteromodal cortices are involved in the AV integration of speech. Sensory-specific and heteromodal cortical regions are involved in the AV integration process at separate latencies and are sensitive to different features of AV speech stimuli.
In this study the results of implementation of two costing systems are illustrated. These systems are Activity Based Costing (ABC) and Traditional Costing. In order to analyze the cost structure for electronic channel transactions, an Iranian bank (Agricultural bank) is chosen as a sample. After explaining the calculation methods of unit costs of the systems, a statistical pair-wise comparison is done to find the probably usefulness of the information. Although this study indicates that electronic channels help to reduce the cost of the banks, but the results shows that there is no difference between the unit costs of two systems. Therefore it suggests doing more research to explain the reasons of insignificant differences between ABC and traditional systems.
In this paper we first introduce a new class of multivariate generalized asymmetric skew-normal distributions with two parameters λ1, λ2 that we present it by BGSNn,m( λ1, λ2), and we finally obtain some special properties of BGSNn,m( λ1, λ2).
Abstract\nIn a country like Pakistan, Written examination is a conventional tool to evaluate the student’s performance in any subject area, where the required cognitive ability is defined through items such as learning outcomes.So in such a system, students’ ability depends very much on the questions asked in the written examination question papers. A good and reasonable examination paper must, therefore, consist of various difficulty levels to accommodate the different capabilities of students. \nIn this work, the difficulty level of each question in the examination paper is determined from the criteria of keyword/s found in the question. The paper provides conclusions on the current relationship between examination questions, learning outcomes and student performance, as well as providing some indication of the relative changes required to move toward a more appropriate association and hence improve an assessment strategy.
We first introduce a new class of bivariate asymmetric skew-normal distribution with two skew parameters λ1, λ2 and denote it by SGN2( λ1, λ2), as an extended distribution of generalized skew-normal distribution (SGN) with single parameter λ, introduced by Arellano-Valle [1]. Then, we obtain some interesting results and properties of SGN2( λ1, λ2) distribution.
