This research aimed to diagnose the perception based on Telecommunications of Iraq to the importance of activating knowledge management marketing in possession, as well as Indication of impediments to activate the management of marketing knowledge in the researched companies, also aimed to show the extent of the existence of significant differences in perception based on Telecommunications Iraqi importance of activating the management marketing knowledge in possession. To achieve the objectives of this research, the questionnaire was developed and distributed to a sample of telecommunications companies in the city of Sulaimaniya, was selected on the criterion according to the company's life in terms of seniority in the telecommunication

Bentonite is widely used in industrial applications. The present study reports the effect of adding different weights of ZnO to the Iraqi bentonite, on surface area, pore volume and real density. These surface properties were evaluated for pure and modified bentonite. The modification was made by adding different ZnO weights such as; ( 0.5%, 1%, 5%, 10% ). The effect of heat exposing for all modified clay samples at 500 ?C have been also evaluated. The results show that the addition of 0.5% ZnO leads to increase the surface area percentage about 36%, increase pore volume percentage about 5.48% and increase the real density percentage about 27.116%. When the samples exposed to 500 ?C, their surface area and pore volumes have been decreased a

The present study deals with the effect of teaching speaking Strategies (SS) on
EFL Iraqi College students. The use of speaking strategies not only solves learners’
communication problems, but also enhances the learner’s interaction in target language,
and improves their oral proficiency .The aim of the study is to find out the effect of
teaching SS used by EFL College students .The learner of the first stage is population of
the study at the Department of English, College of Education /Ibn-Rushd .The sample
consists of (60) students distributed on experimental group(A) as well as control
group(B) each group contains (30) students . In order to achieve the aim of the study,
questionnaire has been constructed t

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

Watermarking operation can be defined as a process of embedding special wanted and reversible information in important secure files to protect the ownership or information of the wanted cover file based on the proposed singular value decomposition (SVD) watermark. The proposed method for digital watermark has very huge domain for constructing final number and this mean protecting watermark from conflict. The cover file is the important image need to be protected. A hidden watermark is a unique number extracted from the cover file by performing proposed related and successive operations, starting by dividing the original image into four various parts with unequal size. Each part of these four treated as a separate matrix and applying SVD

Audio classification is the process to classify different audio types according to contents. It is implemented in a large variety of real world problems, all classification applications allowed the target subjects to be viewed as a specific type of audio and hence, there is a variety in the audio types and every type has to be treatedcarefully according to its significant properties.Feature extraction is an important process for audio classification. This workintroduces several sets of features according to the type, two types of audio (datasets) were studied. Two different features sets are proposed: (i) firstorder gradient feature vector, and (ii) Local roughness feature vector, the experimentsshowed that the results are competitive to