Global Navigation Satellite System (GNSS) is considered to be one of the most crucial tools for different applications, i.e. transportation, geographic information systems, mobile satellite communications, and others. Without a doubt, the GNSS has been widely employed for different scientific applications, such as land surveying, mapping, and precise monitoring for huge structures, etc. Thus, an intense competitive has appeared between companies which produce geodetic GNSS hardware devices to meet all the requirements of GNSS communities. This study aims to assess the performance of different GNSS receivers to provide reliable positions. In this study, three different receivers, which are produced by different manufacturers, were fi

Copper doped Zinc oxide and (n-ZnO / p-Si and n-ZnO: Cu / p-Si) thin films thru thickness (400±20) nm were deposited by thermal evaporation technique onto two substrates. The influence of different Cu percentages (1%,3% and 5%) on ZnO thin film besides hetero junction (ZnO / Si) characteristics were investigated, with X-ray diffractions examination supports ZnO films were poly crystal then hexagonal structural per crystallite size increase from (22.34 to 28.09) nm with increasing Cu ratio. The optical properties display exceptional optically absorptive for 5% Cu dopant with reduced for optically gaps since 3.1 toward 2.7 eV. Hall Effect measurements presented with all films prepared pure and doped have n-types conductive, with a ma

This study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts

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

Solar photovoltaic (PV) system has emerged as one of the most promising technology to generate clean energy. In this work, the performance of monocrystalline silicon photovoltaic module is studied through observing the effect of necessary parameters: solar irradiation and ambient temperature. The single diode model with series resistors is selected to find the characterization of current-voltage (I-V) and power-voltage (P-V) curves by determining the values of five parameters ( ). This model shows a high accuracy in modeling the solar PV module under various weather conditions. The modeling is simulated via using MATLAB/Simulink software. The performance of the selected solar PV module is tested experimentally for differ

Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

         The world's population growth and the increasing demand for new infrastructure facilities and buildings , present us with the vision of a higher resources consumption, specially in the form of more durable concrete such as High Performance Concrete (HPC) . Moreover , the growth of the world pollution by plastic waste has been tremendous. The aim of this research is to investigate the change in mechanical properties of HPC with added waste plastics in concrete. For this purpose 2.5%, 5% and 7.5% in volume of natural fine aggregate in the HPC mixes were replaced by an equal volume of Polyethylene Terephthalate (PET) waste , got by shredded PET bottles. The mechanical propert

اعداد : أسرار عبد الزهراء علي - علاء الدين - ب. جواد  حسن عودة عبد الله  - جامعة بغداد جامعة بغداد كلية البصرة للعلوم والتكنولوجيا - كلية الإدارة والاقتصاد. كلية الإدارة والاقتصاد المركز الديمقراطي العربي –   مجلة القانون الدستوري والعلوم الإدارية : العدد التاسع شباط – فبراير 2021 المجلد 3 ،