Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

This study produces an image of theoretical and experimental case of high loading stumbling condition for hip prosthesis. Model had been studied namely Charnley. This model was modeled with finite element method by using ANSYS software, the effect of changing the design parameters (head diameter, neck length, neck ratio, stem length) on Charnley design, for stumbling case as impact load where the load reach to (8.7* body weight) for impact duration of 0.005sec.An experimental rig had been constructed to test the hip model, this rig consist of a wood box with a smooth sliding shaft where a load of 1 pound is dropped from three heights.
The strain produced by this impact is measured by using rosette strain gauge connected to Wheatstone

The aim of the research is to identify the level of both organizational trust and decentralized performance of those in charge of managing local championships for the Iraqi Athletics Federation, and to identify the effect of organizational trust in decentralized performance from their point of view. The descriptive approach was based on the method of relational relations on a sample of those in charge of managing local championships for the Iraqi Federation In athletics, represented by each of (coaches, referees, members, president and members of the administrative body of the central federation, and the president of members of sub-federations) for the sports season (2020/2021) of 260 individuals, all of them were intentionally chosen by (1

A field experiment was carried out in Horticulture Department / Collage of Agricultur e/University of Baghdad to study influence of adding ascorbic acid(asa) and bread yeast extract in snap bean cv.primel under irrigation with saline water using sodium chloride salt (NaCl) during spr ing season of 2016 .A factorial experiment using Randomized Complete Block Design( RCBD) with three replications wereconducted . The first factor includes three treatments of salinity which were tap water ( S0), 4ds.m-1(S1) and 8ds.m-1 (S2) . The second factor includes three treatments which were control treatment without any adding (C) ,ascorbic acid 0.3g.l-1( A ) and yeast extract 12g.l -1( Y ). Results showed significant and gradually decreases in all studie

The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

This study examines the transformation of political slogans, clichés, and stereotypes in Russia and Iraq during periods of political regime change in the late 20th and early 21st centuries. The main objective of the work is to identify and comparatively analyze the linguistic and cultural changes that accompanied political transformations in both countries. The research is based on theoretical concepts of political myth, framing, and critical discourse analysis. The research methodology includes content analysis of political texts, comparative analysis of linguistic transformations, and analysis of statistical data on cultural consumption. The main hypothesis is that, despite the presence of common trends in linguistic and cultural

This paper demonstrates the spatial response uniformity (SRU) of two types of heterojunctions (CdS, PbS /Si) laser detectors. The spatial response nonuniformity of these heterojunctions is not significant and it is negligible in comparison with p+- n silicon photodiode. Experimental results show that the uniformity of CdS /Si is better than that of PbS /Si heterojunction