Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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

(Social values) are of great importance in the lives of nations and peoples as they are the frame of reference that governs the relations of members of society to each other and regulates their life affairs.

And the Prophet of Islam (may God’s prayers and peace be upon him) has told about a group of (social values) such as: spreading peace, feeding food, being fair in dealing with others, and clarifying what a Muslim should have towards his Muslim brother from the safety of the chest and refraining from harming him with the tongue and hand, and so on. Ethics and behaviors that are directly and closely related to (social values).

The best book that abounds with these (social valu

Objectives: The study aims at identifying the nurses’ knowledge about peritoneal dialysis complications, to
construct an education program for nurses in peritoneal dialysis units, to determine the effectiveness of the
education program upon the nurses' knowledge about complications of peritoneal dialysis, and to identify the
relationship between the nurses’ knowledge and their demographic characteristics of level of education and
years of experience.
Methodology: A quasi-experimentai study was carried out at the peritoneal dialysis units of Baghdad teaching
hospitals, from April 2004 to April 2006.
٨ purposive sample of (50) nurse was selected from Baghdad teaching hospitals. These nurses working at the
perit

Heading of this research, to interrogate the text Sufi Andalusia, one of the displayed cognitive embodied the spirit of the experiment with Walsh nudity Sufi, who ascended to the world of spirituality within their experience of poetry, taking pictures of the perceived symbol cognitively carry through to the worlds transparent based Almwaged related Bashan soul and heart, has tried to invest communicative potential offered by .      

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

In Algeria, education is compulsory for males and females. This foundational decision was taken right after the independence of the country in 1962. Soon after, in 1963, the central government decided the Arabisation of the whole educational levels starting from primary school till university. At the same period, illiteracy-eradication programmes were launched by the Ministry of Education to get rid of this post-colonial scourge. In the administrative department (or Wilaya) of Adrar, former Tuat, young males and females attend Quranic schools (Zawaya) well before any formal education, that is as early as 4-5 years of age. The adult people who are not enrolled in formal classes could sit for non-formal ones. However, actual measurements a