<span lang="EN-GB">Transmitting the highest capacity throughput over the longest possible distance without any regeneration stage is an important goal of any long-haul optical network system. Accordingly, Polarization-Multiplexed Quadrature Phase-Shift-Keying (PM-QPSK) was introduced lately to achieve high bit-rate with relatively high spectral efficiency. Unfortunately, the required broad bandwidth of PM-QPSK increases the linear and nonlinear impairments in the physical layer of the optical fiber network. Increased attention has been spent to compensate for these impairments in the last years. In this paper, Single Mode Fiber (SMF), single channel, PM-QPSK transceiver was simulated, with a mix of optical and electrical (Digi

The systems cooling hybrid solar uses solar collector to convert solar energy into the source of heat for roasting Refrigerant outside of the compressor and this process helps in the transformation of Refrigerant from the gas to a liquid state in two-thirds the top of the condenser instead of two-thirds the bottom of the condenser as in Conventional cooling systems and this in turn reduces the energy necessary to lead the process of cooling. The system cooling hybrid use with a capacity of 1 ton and Refrigerant type R22 and the value of current drawn by the system limits (3.9-4.2A), the same value of electric current calculated by the system are  Conventional  within this atmosphere of Iraq, and after taking different readings

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 object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000, 2002, and MODIS 2009, 2010. A new technique of the unsupervised classification called (Color Extracting Technique) was used to classify the satellite images. MATLAP programming used the technique and separated Al-Hammar Marsh from other water features (rivers, irrigated lands, etc.) when calculated the changes in the water content of the study region. ArcGIS 9.3 (arcMAP, arcToolbox) were used to achieve this work and calculate area of each class.

This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manne

Objective: To evaluate nurses' practices concerning isolation techniques for Adult Leukemic Patients (ALP).
Methodology: A descriptive study was carried out at the isolation rooms at leukemic wards in Baghdad Teaching
Hospitals, starting from Jan. 27th 2008 up to the 27th of Apr. 2008. To achieve the objectives of study, a non-probability
"purposive" sample of (50) nurse was selected out of four Teaching Hospitals in Baghdad city were selected according
to the criteria of the study sample.
The study instrument consisted of two major parts. It is based on the review of literature. First is concerned with
demographic data for nurses; and the second part is observational tool (checklist) is composed of (83) item. The conte

In the modern world, wind turbine (WT) has become the largest source of renewable energy. The horizontal-axis wind turbine (HAWT) has higher efficiency than the vertical-axis wind turbine (VAWT). The blade pitch angle (BPA) of WT is controlled to increase output power generation over the rated wind speed. This paper proposes an accurate controller for BPA in a 500-kw HAWT. Three types of controllers have been applied and compared to find the best controller: PID controller (PIDC), fuzzy logic type-2 controller (T2FLC), and hybrid type-2 fuzzy-PID controller (T2FPIDC). This paper has been used Mamdani and Sugeno fuzzy inference systems (FIS) to find the best inference system for WT controllers. Furthermore, genetic algorithm (GA) and particl

In this research, the structural behavior of reinforced concrete columns made of normal and hybrid reactive powder concrete (hybrid by steel and polypropylene fibers) subjected to chloride salts with concentration was 8341.6 mg/l. The study consists of two parts, the first one is experimental study and the second one is theoretical analysis.  Three main variables were adopted in the experimental program; concrete type, curing type and loading arrangement. Twenty (120x120x1200) mm columns were cast and tested depending on these variables. The samples were reinforced using two different bars; Ø8 for ties and Ø12 with minimum longitudinal reinforcement (0.01Ag). The specimens were divided into two main groups based o