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

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

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

The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. This work modernize the feedforward neural network, so the secret message will be encrypted by unsupervised neural network method to get the cipher text that can be decrypted using the same network to get the original text. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding lengths. In this work, the key is the final weights

In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.

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

Abstract The main purpose of the research is to clarify and investigate in details about Susan Glaspell’s role in shedding light on the predicament of women in American society in the early twentieth century showing how sense of the place played an important role in limiting the opportunities of female protagonists who try to escape the roles imposed upon them by society. Glaspell lived in the early twentieth century in the Midwest and tackled the important issues like: women's suffrage, birth control, socialism, union organizing when women were not able to vote or sit as a member on juries. Her Feminist cause is quite obvious through her works from her first one act play Suppressed Desire to the final three act play, Alison’s House. Th