Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg

Solanum americanum is a new annual shrubby plant seen recently in fields and gardens of Baghdad city. A new species is described and illustrated, inhabit wet or semi dry places and have consequently a mesophytic habit. A detailed morphological study of the stems, leaves, Inflorescence, flower, male and female reproductive organs and fruits has been done, revealed several interesting taxonomic characteristics, which have not previously been studied in Iraq. Also, anatomical studies reveals constant taxonomical characteristics such as the presence of anthocayanine in outer row of epidermis, distinct chlorenchyma in whole cortex, the wide pith of stems, and presence of distinct mesophyll that differentiated into palisade layer and spongy laye

Studies in Iraq that concerned identification of free-living Protozoa (sarcodina) are scarce; so the current study deals with these protozoan communities inhabiting the Tigris River in Baghdad City. Sampling collection stations have been selected at each of AL-Gheraiˈat and AL-Adhamiyah area adjacent to the river. Monthly intervals sampling with three samples were collected from each station from June to September 2020. Total of 23 sarcodina taxa were listed, out of them 5 taxa were new record to the Tigris River in Baghdad: Difflugia urceolata Carter, 1864 (Arcellinida, Difflugiidae), Heleopera perapetricola Leidy, 1879 (Arcellinida, Heleoperidae), Rhaphidiophrys pallida F.E. Schulze, 1874 (Centrohelida, Raphidiophridae), Saccamoeba sp

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

The free zone or the free economy cities are cities with classification and functional specificity, although the history of  the concept of these areas has been It dates back to distant eras, but the intellectual and philosophical construction with the support of intellectual approaches, the most important of which is globalization contributed to its rapid spread globally and taking a variety of forms and models. With the diversity of its formulas and objectives countries have competed in adopting the establishment of these areas, meanwhile The influence of related trends affected the contemporary formation of these sites. Therefore ,the research was directed focus on the importance of adopting a set of common indicators (collection

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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