Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to

In this paper we generalize some of the results due to Bell and Mason on a near-ring N admitting a derivation D , and we will show that the body of evidence on prime near-rings with derivations have the behavior of the ring. Our purpose in this work is to explore further this ring like behavior. Also, we show that under appropriate additional hypothesis a near-ring must be a commutative ring.

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

Die vorliegende Forschung handelt es um die Satzfelder, besonders das Mittelfeld des Satzes im deutschen und Arabischen. Diese Forschung wurde mit der Satzdefinition, Satzglieder begonnen, damit wir diese klar werden und dann werden die Felder des Satzes gut gekannt. Der erste Abschnitt schlieβt auch den Mittelfeld des Satzes und, wie man das Feld erkennen und bestimmen kann. Die Forschung untersucht auch. Ob es in der arabischen Sprache den selben Struktur wie im Deutschen gibt, z.B Bildung des Satzes sowie Satzfelder bezügllich das Mittelfeld.

Der zweite Abschnitt handelt sich um den arabischen Teil und behandelt die Wortarten im Arabischen sowie den Satz als auch Satzarten (Nominal- Verbal- Halbsatz).

Danach befinden

In this paper we will investigate some Heuristic methods to solve travelling salesman problem. The discussed methods are Minimizing Distance Method (MDM), Branch and Bound Method (BABM), Tree Type Heuristic Method (TTHM) and Greedy Method (GRM).

The weak points of MDM are manipulated in this paper. The Improved MDM (IMDM) gives better results than classical MDM, and other discussed methods, while the GRM gives best time for 5≤ n ≤500, where n is the number of visited cities.

This article discusses the estimation methods for parameters of a generalized inverted exponential distribution with different estimation methods by using Progressive type-I interval censored data. In addition to conventional maximum likelihood estimation, the mid-point method, probability plot method and method of moments are suggested for parameter estimation. To get maximum likelihood estimates, we utilize the Newton-Raphson, expectation -maximization and stochastic expectation-maximization methods. Furthermore, the approximate confidence intervals for the parameters are obtained via the inverse of the observed information matrix. The Monte Carlo simulations are used to introduce numerical comparisons of the proposed estimators. In ad

The three parameters distribution called modified weibull distribution (MWD) was introduced first by Sarhan and Zaindin (2009)[1]. In theis paper, we deal with interval estimation to estimate the parameters of modified weibull distribution based on singly type one censored data, using Maximum likelihood method and fisher information to obtain the estimates of the parameters for modified weibull distribution, after that applying this technique to asset of real data which taken for Leukemia disease in the hospital of central child teaching .

In this review paper, several studies and researches were surveyed for assisting future researchers to identify available techniques in the field of classification of Synthetic Aperture Radar (SAR) images. SAR images are becoming increasingly important in a variety of remote sensing applications due to the ability of SAR sensors to operate in all types of weather conditions, including day and night remote sensing for long ranges and coverage areas. Its properties of vast planning, search, rescue, mine detection, and target identification make it very attractive for surveillance and observation missions of Earth resources.  With the increasing popularity and availability of these images, the need for machines has emerged to enhance t

The charge density distributions (CDD) and the elastic electron scattering form
factors F(q) of the ground state for some odd mass nuclei in the 2s 1d shell, such
as K Mg Al Si 19 25 27 29 , , , and P 31
have been calculated based on the use of
occupation numbers of the states and the single particle wave functions of the
harmonic oscillator potential with size parameters chosen to reproduce the observed
root mean square charge radii for all considered nuclei. It is found that introducing
additional parameters, namely; 1  , and , 2  which reflect the difference of the
occupation numbers of the states from the prediction of the simple shell model leads
to very good agreement between the calculated an