This paper involves the development of the Tau method with Bernstein multi-scaling (BMS) functions basis for the numerical solution of the Volterra-Fredholm Hammerstein integro-differential equations (VFHIDEs). For this purpose at the beginning we define BMS functions and express briefly some properties of BMS functions and after function approximation by using BMS functions, will be presented. Then, the operator matrix representation for the differential and integral parts seeming in the equation using the operational Tau method base on BMS functions basis, will be displaced. The operational Tau method transforms the differential and integration parts of the desired VFHIDEs to some operational matrices. In fact, this method reduces VFHIDEs to a system of algebraic equations. Numerical examples demonstrate the validity and applicability of the proposed method with BMS functions basis.

Software process improvement (SPI) has emerged as the dominant approach for improving quality and productivity in software development organizations. It is an important activity which starts when an organization plans to enhance/purify the capabilities of its on-going processes. When improvement or change is planned or initiated, there are a number of process-improvement-factors which originate and affect the effectiveness of software process improvement. Therefore the biggest challenge is to find a route for appropriate SPI technologies to realize their company’s improvement goals. A software Industry focused on two different research fields work on the issues of software process: first - software process modeling and second - software process evaluation and improvement. In this paper, the most relevant results of second approaches are presented to evaluate the process improvement for development of IVR software using Square Model. This paper also suggests to IVR application software companies that require collaboration and strengthening to transform their current perspective into inseparable global IT scenario.

In this paper, we describe fully parallelized architectures for one-to-one, one-to-many, and many-to-many sequence alignments using Smith-Waterman algorithm. The architectures utilize the principles of parallelism and pipelining to the greatest extent in order to take advantage of both intra- sequence and inter-sequence parallelization and to achieve high speed and throughput. First, we describe a parallelized Smith-Waterman algorithm for general single instruction, multiple data (SIMD) computers. The algorithm has an execution time of O(m+n), where m and n are the lengths of the two biological sequences to be aligned. Next, we propose a very-large-scale integration (VLSI) implementation of the parallel algorithm. Thirdly, we incorporate a pipelined architecture into the proposed VLSI circuit, producing a pipelined processor that can align a query sequence with a database of sequences at the speed of O(m+n+L), where m is the length of the query sequence and n and L are the maximum length and the number of sequences in the database, respectively. Finally, we make use of our pipeline architecture to perform all possible pairs of pair-wise alignments for a group of L sequences with a maximum sequence length of m in O(mL) time. Checking all pairs of pair-wise alignments is essential to the overlap-layout-consensus (OLC) approach for de novo assembly.

In this paper , a numerical solution based on parametric cubic spline is used for finding the solution of boundary value problems arising in the calculus of variations . The present approach has less computational coast and gives better approximation . This approximation reduce the problems to an explicit system of algebraic equations . Some numerical examples are also given to illustrate the accuracy and applicability of the presented method.

Throughout the paper we consider relative order of functions of several complex variables analytic in the unit poly disc with respect to an entire function and after proving several theorems, we show that relative order of analytic function and its partial derivatives are same.

In this paper, a new Hardy-Hilbert integral inequality is obtained by proving an inequality on weight coefficients.

The stability of a second-order system is studied under diffusion process modeling for damping ratio and natural frequency parameters. The probability of stability is derived and it is described how this probability is computed for various selects of parameters of diffusion processes. Finally, a conclusion section is also given.

In this paper we discuss some growth rates of iterated entire functions improving some earlier results.

In this paper, we propose a new approach to recognize the maize disease, which is based on fuzzy least square vector machine (FLSVM) algorithm. According to the texture characteristics of Maize diseases, it uses YCbCr color space technology to segment disease spot, and uses the co-occurrence matrix spatial gray level layer to extract disease spot texture feature, and uses FLSVM to class the maize disease. In this method, the sample mean is calculated, and the center of each class is got; then the distance between the sample and the center is calculated, according to the distance sample’s initial membership is got; by finding K neighbors for each sample point, the sample membership degree is calculated according to the fuzzy K nearest neighbor method. Extensive experiments on public datasets show that the algorithm can effectively identify the disease image, the accuracy was as high as 98% or more.