The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed system's performance. method, the classification accuracy has been compared using different types of classifiers. These classifiers are Naïve Bayesian, KNN, J48, and SVM. The range of the identification accuracy for all the processed databases using the proposed scenario is between (%93.8- %97.8). The system was executed using MATHLAB R2017, 2.10 GHz processor, and 4 GB RAM.
Future wireless communication systems must be able to accommodate a large number of users and simultaneously to provide the high data rates at the required quality of service. In this paper a method is proposed to perform the N-Discrete Hartley Transform (N-DHT) mapper, which are equivalent to 4-Quadrature Amplitude Modulation (QAM), 16-QAM, 64-QAM, 256-QAM, … etc. in spectral efficiency. The N-DHT mapper is chosen in the Multi Carrier Code Division Multiple Access (MC-CDMA) structure to serve as a data mapper instead of the conventional data mapping techniques like QPSK and QAM schemes. The proposed system is simulated using MATLAB and compared with conventional MC-CDMA for Additive White Gaussian Noise, flat, and multi-path selective fa
... Show MoreAbstract To ensure that the distribution system has safe drinking water. It is necessary to know the residual chlorine concentrations at various points in the network. A chlorine photometer device was used to measure twenty points taken every day for a week at a selected time in the distribution system. Both pressures and flows in the network were measured using bourdon gauge and Tuf-2000H Handheld Digital ultrasonic flow meters. WaterGEMS CONNECT Edition update one software was used to simulate the flow in the network. The Baghdad water department provided the data about the network, such as the lengths of pipes, the layout of the network, and pipes diameters. The network calibrated consists of 781 pipes of different lengths and 542 juncti
... Show MoreOver the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame
In this research, optical communication coding systems are designed and constructed by utilizing Frequency Shift Code (FSC) technique. Calculations of the system quality represented by signal to noise ratio (S/N), Bit Error Rate (BER),and Power budget are done. In FSC system, the data of Nonreturn- to–zero (NRZ ) with bit rate at 190 kb/s was entered into FSC encoder circuit in transmitter unit. This data modulates the laser source HFCT-5205 with wavelength at 1310 nm by Intensity Modulation (IM) method, then this data is transferred through Single Mode (SM) optical fiber. The recovery of the NRZ is achieved using decoder circuit in receiver unit. The calculations of BER and S/N for FSC system a
... Show MoreRenewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of
... Show MoreWildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show MoreNowadays power systems are huge networks that consist of electrical energy sources, static and lumped load components, connected over long distances by A.C. transmission lines. Voltage improvement is an important aspect of the power system. If the issue is not dealt with properly, may lead to voltage collapse. In this paper, HVDC links/bipolar connections were inserted in a power system in order to improve the voltage profile. The load flow was simulated by Electrical Transient Analyzer Program (ETAP.16) program in which Newton- Raphson method is used. The load flow simulation studies show a significant enhancement of the power system performance after applying HVDC links on Kurdistan power systems. Th
... Show MoreIn this paper the process of metal ions extraction (Zn(II) and Cu(II)) was studied in PEG-KCl aqueous two phase system was investigated without using an extracting agent. The experimental runs were performance at constant temperature (25 oC), constant mixing time (30 min), and constant PH of the solution (about 3). The effect of KCl salt concentration (from 10% to 25%), volumetric phase ratio of PEG solution to KCl solution (from 0.5 to 2), and the initial metal ion concentration (from 0.25 ml to 2 ml of 1 gm/L solution) were investigated on the percent extraction of Zn(II) and Cu(II). The results indicated that the percent extraction of metal ions increase with increasing of salt concentration and phase ratio, and slightly de
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