Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

The research aims to demonstrate the quality of the auditor’s report by analyzing a number of models represented by the auditor’s report based on the Iraqi audit evidence and the auditor’s report in light of the application of international auditing standards for the report and the auditor’s report in light of the application of the International Auditing Standard 701, in addition to explaining the impact of applying the International Auditing Standard 701. International Auditing 701 in enhancing the quality of the auditor's report, and in order to reach these goals, a comparison was made on international experiences before and after the application of the standard in addition to the results of the questionnaire distribut

This study aims to identify the impact of social support on breast cancer patients’ psychological rigidity using a sample in Ramallah and al-Bireh. A descriptive correlative approach was adopted to fulfill the goals of the study and a questionnaire consisted of two criteria: social support and psychological rigidity, which was adopted as a tool for data collection for the study. In order to achieve the goals of the study, the researcher selected a convenient sample that consisted of 123 female breast cancer patients in Ramallah and al-Bireh. This sample represented 50% of the original patient population. The study showed that the average estimated percentage of social support and psychological rigidity for women with breast cancer, in

The talk about the relationship between the media and industrialists can be the core of a bigger and deeper subject which is the role of these means in increasing sales : First, increasing the customer’s awareness of the importance of goods and the result of the promotion of products. Secondly, increasing investments which do require continuous studies and deep research in order to understand the constantly changing market conditions, and the public’s taste. In this research, we try to find out how industrialists see the role of media in the promotion of products in Iraq today, and how it develops in the future.

There was a reluctance of the industrialists to advertise in the local media, also industrialists see the role of t

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

The present study deals with the effect of teaching oral Communication Strategies on English language learners. The use of oral communication strategies not only solves learners’ communication problems, but also enhances the learner’s interaction in target language, which in turn, improves their oral proficiency .The sample of this study is EFL students in the first stage at the Department of English Language, morning studies, College of Education /Ibn-Rushd .The sample of the study consists of (60) students distributed on experimental group(A) includes (30) students, and (30) students as control group(B). In order to achieve the aim of the study, and to gain a closer idea about the impact of teaching oral Communication Strategies on th

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

Abstract:
Rabi’a tribe lived on the land of Euphrates since the first century of the
Christ. Then that land becomes her homeland. The Persians tried many times
to drive her away from that land, but with out result.
In the course of time Rabi’a become more knowledgeable of Persia.
This tribe proved her love and sanctification to the land of Euphrates, in the
battle of Dhyqar.
Rabi’a converted to Islam quickly and helped the Muslims to conquer
Iraq with a big number of fighters in many battles like al- Qadisyyah. That
influenced the anger of Mudriat Arab tribes who were their old enemies.
Mudriat tribes did their efforts to reduce the importance of Rabi’a because of
some its branches were among of t