Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

Picasso ceramics represented illuminated sign in ceramic art and excelled in accord ceramic art dimension aesthetically, and put it in a new prospects, despite the simplicity of the forms turn into a magical images and multiple interpretations.
So the search deliberately to choose purposive (37) samples divided into four groups, as follows: -
A flat shapes / palets or saucers / the vases /modified vases .
benefiting from indicators were spawned from literature ,to analyzing samples within the totals for the identification systems act forming art work`s:-
(1)Picasso's ceramic work product of a deliberate process represented a capacity of technical experience, and formal
(2)The system configuration in the ceramic art works c

The paper presents the design of a system consisting of a solar panel with Single Input/Multiple Outputs (DC-DC) Buck Converter by using Simulink dialogue box tools in MATLAB software package for simulation the system. Maximum Power Point Tracking (MPPT) technique depending on Perturb and Observe (P&O) algorithm is used to control the output power of the converter and increase the efficiency of the system. The characteristics of the MSX-60 PV module is chosen in design of the system, whereas the electrical characteristics (P-V, I-V and P-I curves) for the module are achieved, that is affected by the solar radiation and temperature variations. The proposed design module has been found to be stable for any change in atmospheric tempera

We must live in an era dominated by the call for equality between men and women, in which the voices of advocates of gender integration were heard. After women opened their doors to compete with their brother, Knowledge, and culture in the various forms of life, language as a science of the time and knowledge of the other had to match this reality and express the most accurate expression of this task

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

Specialized hardware implementations of Artificial Neural Networks (ANNs) can offer faster execution than general-purpose microprocessors by taking advantage of reusable modules, parallel processes and specialized computational components. Modern high-density Field Programmable Gate Arrays (FPGAs) offer the required flexibility and fast design-to-implementation time with the possibility of exploiting highly parallel computations like those required by ANNs in hardware. The bounded width of the data in FPGA ANNs will add an additional error to the result of the output. This paper derives the equations of the additional error value that generate from bounded width of the data and proposed a method to reduce the effect of the error to give

In this paper we present a method to analyze five types with fifteen wavelet families for eighteen different EMG signals. A comparison study is also given to show performance of various families after modifying the results with back propagation Neural Network. This is actually will help the researchers with the first step of EMG analysis. Huge sets of results (more than 100 sets) are proposed and then classified to be discussed and reach the final.