The use of deep learning.
Social networking sites represent one of the modern communication technologies that have contributed to the expression of public opinion trends towards various events and crises of which security crisis is most important being characterized by its ability to influence the community life of the public. In order to recognize its role in shaping opinions of the educated class of the public that is characterized by a high level of knowledge, culture and having experience in dealing with the media. Its advantage is that they have an active audience by expressing their views on the situations, events, and news published on them as well as expressing their attitudes and sympathy with the events. So a number of questions are included in the ques
... Show MoreBackground: Most primary Health Care Centers (PHCCs) in Iraq have a referral system records; however, this mechanism does not function well because of the lack of other requirements for an efficient referral system.
Objective: To assess the practice & opinion of doctors in PHCs toward the referral system, and to determine the doctors in PHC's commitment to referral system instructions and guidelines.
Subjects and methods: A cross-sectional study with analytic elements was conducted in nine health directorates in Iraq, from the 1st October 2018 – 30th June 2019.One PHC was selected randomly form each sector in every governorate, A questionnaire was used to collect the required information.
... Show More15 local isolates of Pseudomonas were obtained from 35 samples from several sources such as soil, water and some high-fat foods. The ability of isolates to produce lipase was measured by the size of the clarification zone formed around the colonies on the lipase production medium and by measuring the enzymatic activity and specific enzymatic activity, the isolate M3 was found to be the most efficient for production of the enzyme, This isolate was identified by microscopic, morphological, some biochemical tests and genetic diagnosis of 16S gene sequences by using the (PCR) technique, and then comparing the results obtained with the National Center for Biotechnology Inform
... Show MoreThis research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff
... Show MoreThe speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi
... Show MoreFace Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a
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