This paper describes a research effort that aims of developing solar models for housing suitable for the Arabian region since the Arabian Peninsula is excelled with very high levels of solar radiation.
The current paper is focused on achieving energy efficiency through utilizing solar energy and conserving energy. This task can be accomplished by implementation the major elements related to energy efficiency in housing design , such as embark on an optimum photovoltaic system orientation to maximize seize solar energy and produce solar electricity. All the precautions were taken to minimizing the consumption of solar energy for providing the suitable air-condition to the inhibitor of the solar house in addition to use of energy effici

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The continuous technical development in the means of communication and information technologies has led to an increase in competition in the provision of service and product on the part of the organizations, as this competition does not know silence and stability on specific methods, but rather it is a world that is constantly moving and renewed in approaches, methods and approaches, and the focus of attention of integrated marketing communications practitioners are Customers, for them, organizations sell their goods, products, services, and ideas, and with them, they become stronger in competition.
This scientific study aimed to identify the trends of the initiators towards the integrated marketing communications of (the Emirates Tel

Background: The bond strength of root canal sealers to dentin and gutta-percha seems to be an important property for maintaining the stability of root canal filling, which potentially influences both leakage and root strength. The objective of this, in vitro, study was to evaluate the shear bond strength of three different endodontic sealers (Gutta-Flow, AH Plus, Apexit Plus) to dentin, in the presence and absence of the smear layer and gutta percha. Material and Methods: After slicing off the occlusal 2mm of 60 extracted human maxillary premolar teeth, the exposed dentin served as the tested surfaces; the teeth were fixed with cold cure acrylic, and were divided into two groups according to the smear layer presence, group A without smear

             Bioindicators have an important role in assessing the quality of water bodies. Aquatic oligocheates, was used as a bioindicator to assess the sediment quality of Al-Hindyia and AL-Abbasyia river (branches of Euphrates River in Iraq). Two sites in each river have been   chosen for this purpose, site S1 was located at Al-Hindyia River and S2 at Al-Abbasyia River. Some kinds of biological indices were used in this study, comprising the percentage of oligochaetes in benthic invertebrates, ranged from 20.3-60.16%. While the percentage of Tubificidae within benthic invertebrates was close 43.3-43.9%.Index of pollution D ranged from 0.13-0.21. The maximum percentage of aquatic oligochaetes to insects larvae of family

    Examining of 80 feces samples showed that 31 samples of the house and stray cats harbored either single or mixed infection with eight species of parasites and protozoa with a total infection rate 38.75 %.The results on parasite classes are: Toxocara cati (5%), Ancylostoma tubeforme (3.75%), Capillaria felis(3.75%), Isospora sp.(10%), Cryptosporidium parvum(3.75%), Cryptosporidium muris (6.25%), Toxoplasma gondi (3.75%), Giardia sp.(2.5%) infection from feces of cats that showed single, double and triple infections. Our findings revealed the risk for public health, thus preventive measures should be implemented.

Abstract—Background: Polycystic ovary syndrome (PCOS) is a prevalent hormonal disorder affecting reproductive- age women, often linked to metabolic issues like insulin resistance. Objective: this study aimed to evaluate ornithine decarboxylase (ODC) and ferric reducing capacity (FRC) levels in women with PCOS, with assess the effects of metformin and Primolut N treatment on their levels. Subjects and Methods: A case− control study was conducted with 150 married Iraqi women, categorized into three groups: 50 healthy controls, 50 untreated PCOS, 50 treated PCOS. Blood samples were analyzed for ODC, FRC levels and hormonal profiles. Statistical analysis applied independent t-test, Pearson’s correlation, ROC curve. Results: The ODC level