In this paper an accurate Indian handwritten digits recognition system is
proposed. The system used three proposed method for extracting the most effecting
features to represent the characteristic of each digit. Discrete Wavelet Transform
(DWT) at level one and Fast Cosine Transform (FCT) is used for features extraction
from the thinned image. Besides that, the system used a standard database which is
ADBase database for evaluation. The extracted features were classified with KNearest
Neighbor (KNN) classifier based on cityblock distance function and the
experimental results show that the proposed system achieved 98.2% recognition
rate.

The propagation of laser beam in the underdense deuterium plasma has been studied via computer simulation using the fluid model. An appropriate computer code “HEATER” has been modified and is used for this purpose. The propagation is taken to be in a cylindrical symmetric medium. Different laser wavelengths (1 = 10.6 m, 2 = 1.06 m, and 3 = 0.53 m) with a Gaussian pulse type and 15 ns pulse widths have been considered. Absorption energy and laser flux have been calculated for different plasma and laser parameters. The absorbed laser energy showed maximum for  = 0.53 m. This high absorbitivity was inferred to the effect of the pondermotive force.

Background: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP),

In modern times face recognition is one of the vital sides for computer vision. This is due to many reasons involving availability and accessibility of technologies and commercial applications. Face recognition in a brief statement is robotically recognizing a person from an image or video frame. In this paper, an efficient face recognition algorithm is proposed based on the benefit of wavelet decomposition to extract the most important and distractive features for the face and Eigen face method to classify faces according to the minimum distance with feature vectors. Faces94 data base is used to test the method. An excellent recognition with minimum computation time is obtained with accuracy reaches to 100% and recognition time decrease

Background: Tuberculosis (TB) is a major public health issue and a main cause of global morbidity and mortality. TB is the world's ninth leading cause of death despite the numerous treatment strategies for managing the disease.
Objective: To assess the traditional method (direct smear examination and culture) against real-time PCR as pulmonary and extrapulmonary tuberculosis laboratory diagnostic techniques.
Cases and methods: Samples were collected from (612) TB cases, (409) of whom were pulmonary tuberculosis (PTB) and (203) were extrapolmonary tuberculosis (EPTB). The cases were seeking care at the Specialized Chest and Respiratory Disease Center/ National Reference Laboratory for Tuberculosis (NRL) in Baghdad, during the period

   A common problem facing many Application models is to extract and combine information from multiple, heterogeneous sources and to derive information of a new quality or abstraction level. New approaches for managing consistency, uncertainty or quality of Arabic data and enabling e-client analysis of distributed, heterogeneous sources are still required. This paper presents a new method by combining two algorithms (the partitioning and Grouping) that will be used to transform information in a real time heterogeneous Arabic database environment

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     The time fractional order differential equations are fundamental tools that are used for modeling neuronal dynamics. These equations are obtained by substituting the time derivative of order  where , in the standard equation with the Caputo fractional formula. In this paper, two implicit difference schemes: the linearly Euler implicit and the Crank-Nicolson (CN) finite difference schemes, are employed in solving a one-dimensional time-fractional semilinear equation with Dirichlet boundary conditions. Moreover, the consistency, stability and convergence of the proposed schemes are investigated. We prove that the IEM is unconditionally stable, while CNM is conditionally stable. Furthermore, a comparative study between these two s

This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s

We consider some nonlinear partial differential equations in higher dimensions, the negative order of the Calogero-Bogoyavelnskii-Schiff (nCBS) equationin (2+1) dimensions, the combined of the Calogero-Bogoyavelnskii-Schiff equation and the negative order of the Calogero-Bogoyavelnskii-Schiff equation (CBS-nCBS) in (2+1) dimensions, and two models of the negative order Korteweg de Vries (nKdV) equations in (3+1) dimensions. We show that these equations can be reduced to the  same class of ordinary differential equations via wave reduction variable. Solutions in terms of symmetrical Fibonacci and Lucas functions are presented by implementation of the modified Kudryashov method.