In IRAQ, the air conditioners are the principal cause of high electrical demand. In summer, the outer temperature sometimes exceeds 50⁰C which significantly effects on the A/C system performance and power consumed. In the present work, the improvement in mechanical and electrical performance of split A/C system is investigated experimentally and analytically. In this paper, performance and energy saving enhancement of a split-A/C system was experimentally investigated to be efficiently compatible with elevated temperature weathers. This improvement is accomplished via Smart Control System integrate with Proportional-Integral- Differential PID algorithm. The PIC16F877A micro-controller has been programmed with the PID and PWM c

In this paper, a fusion of K models of full-rank weighted nonnegative tensor factor two-dimensional deconvolution (K-wNTF2D) is proposed to separate the acoustic sources that have been mixed in an underdetermined reverberant environment. The model is adapted in an unsupervised manner under the hybrid framework of the generalized expectation maximization and multiplicative update algorithms. The derivation of the algorithm and the development of proposed full-rank K-wNTF2D will be shown. The algorithm also encodes a set of variable sparsity parameters derived from Gibbs distribution into the K-wNTF2D model. This optimizes each sub-model in K-wNTF2D with the required sparsity to model the time-varying variances of the sources in the s

This research aims at studying the relation between fair value and the Financial Reports Quality  to achieve a number of aims such as :-

1- Throw light on the problems of the measurement that depends on the historic cost as it paves the way towards the method of the fair value in the accounting measurement.

2-Give a general definition for  fair value in the accounting via analyzing the theoretical aspects that relates the subject and the  scientific bases on which the relating accounting treatment depend.

3- Exhibit the characteristics that could be added by the fair value  to the accounting Information .

       The study problem is summarized in that the e

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different