Two of the main advantages of segmental construction are economics, as well as the rapid construction technique. One of the forms of segmental construction, for structural elements, is the segmental beams that built-in short sections, which referred to segments. This research aims to exhibit a new technique for the fabrication of short-span segmental beams from wedge-shaped concrete segments and carbon fiber reinforced polymers (CFRP) in laminate form. The experimental campaign included eight short-span segmental beams. In this study, two selected parameters were considered. These parameters are; the number of layers of CFRP laminates and the adhesive material that used to bond segments to each other, forming short-span segmental be

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

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

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 ،

The sensors based on Nickel oxide doped chromic oxide (NiO: Cr2O3) nanoparticals were fabricated using thick-film screen printing of sol-gel grown powders. The structural, morphological investigations were carried out using XRD, AFM, and FESEM. Furthermore, the gas responsivity were evaluated towards the NH3 and NO2 gas. The NiO0.10: Cr2O3 nanoparticles exhibited excellent response of 95 % at 100oC and better selectivity towards NH3 with low response and recovery time as compared to pure Cr2O3 and can stand as reliable sensor element for NH3 sensor related applications.

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