Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's performance was evaluated, and tests were run. Line-to-ground faults were examined. The study demonstrates how effective, rapid, and precise this method is at locating faults. The neural network's performance was examined, and tests were run on it. The overall performance of the mean square error in the trained network execution was 0.11792 at 35 epochs. The correlation coefficient at the entire target was 0.99987 percent of an error on the Doukan-Erbil double transmission lines.
Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay
... Show MoreMachine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
... Show MoreThis research includes a study of Methylenetetrahydrofolate reductase gene’s allele 677C?T and its correlation with oxidative stress and their impact on female infertility. Fifty infertile women with the range age (23-42) years and twenty five fertile women with the range age (22-39) years as control group living in Erbil city were selected. The serum level of Malondialdehyde (MDA), superoxide dismutase (SOD), prolactin hormone (PRL), Luteinizing hormone (LH), Thyroid stimulating hormone (TSH), Triiodothyronine hormone (T3), and Thyroxine hormone (T4) were measured, also a body mass index (BMI) was calculated. A restriction enzyme (Hinf1) was used to improve the mutation in DNA bands of infertile women. The results showed significant inc
... Show MoreIn our world, technological development has become inherent in all walks of life and is characterized by its speed in performance and uses. This development required the emergence of new technologies that represent a future revolution for a fourth industrial revolution in various fields, which contributed to finding many alternatives and innovative technical solutions that shortened time and space in terms of making Machines are smarter, more accurate, and faster in accomplishing the tasks intended for them, and we find the emergence of what is called artificial intelligence (artificial intelligence), which is the technology of the future, which is one of the most important outputs of the fourth industrial revolution, and artificial inte
... Show MoreDue to that the Ultra Wide Band (UWB) technology has some attractive features like robustness to multipath fading, high data rate, low cost and low power consumption, it is widely use to implement cognitive radio network. Intuitively, one of the most important tasks required for cognitive network is the spectrum sensing. A framework for implementing spectrum sensing for UWB-Cognitive Network will be presented in this paper. Since the information about primary licensed users are known to the cognitive radios then the best spectrum sensing scheme for UWB-cognitive network is the matched filter detection scheme. Simulation results verified and demonstrated the using of matched filter spectrum sensing in cognitive radio network with UWB and pro
... Show MoreIn this paper a WLAN network that accesses the Internet through a GPRS network was implemented and tested. The proposed network is managed by the Linux based server. Because of the limited facilities of GPRS such as dynamic IP addressing besides to its limited bandwidth a number of techniques are implemented to overcome these limitations.
Dynamic Host Configuration Protocol (DHCP) server was added to provide a single central control for all TCP/IP resources. Squid Proxy was added to provide caching of the redundant accessed Web content to reduce the Internet bandwidth usage and speeding up the client’s download time. Network Address Translation (NAT) service was configured to share one IP ad
... Show MoreDouble drum dryer is operated for producing pregelatinized maize starches using feed starch slurries of different
solids(7, 10 and13 g/100 g )content . Steam pressure (2,3,and 4 bar), the level of pool between the drums (4,7,and 10
cm) , and speed of drums rotation (3,4,and 6 rpm) are varied together with the feed solids content in a practical range of
values. The response of the dryer is registered by measuring several output variables, i.e. external drum temperature,
product moisture content, mass flow rate.
Meaning letters in Arabic are characterized by the diversity and abundance of their linguistic material, and are also distinguished by their large number and types, to the point that some of them have reached a hundred letters confined to five categories