In this paper, a FPGA model of intelligent traffic light system with power saving was built. The intelligent traffic light system consists of sensors placed on the side's ends of the intersection to sense the presence or absence of vehicles. This system reduces the waiting time when the traffic light is red, through the transition from traffic light state to the other state, when the first state spends a lot of time, because there are no more vehicles. The proposed system is built using VHDL, simulated using Xilinx ISE 9.2i package, and implemented using Spartan-3A XC3S700A FPGA kit. Implementation and Simulation behavioral model results show that the proposed intelligent traffic light system model satisfies the specified operational requirements.
The effect of UV-light on the tensile properties of pure PC has been studied. It was shown that irradiation of PC undergo a drop in the tensile properties of 30 hour of exposure. The results of irradiated samples shows that the addition of ZnO and TiO2 with different percentages (0.5, 1, 1.5 %) will reduce the Young modulus and ultimate stress of PC/ZnO ,PC/ TiO2 composites
Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.
Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
... Show MoreThrough this research, We have tried to evaluate the health programs and their effectiveness in improving the health situation through a study of the health institutions reality in Baghdad to identify the main reasons that affect the increase in maternal mortality by using two regression models, "Poisson's Regression Model" and "Hierarchical Poisson's Regression Model". And the study of that indicator (deaths) was through a comparison between the estimation methods of the used models. The "Maximum Likelihood" method was used to estimate the "Poisson's Regression Model"; whereas the "Full Maximum Likelihood" method were used for the "Hierarchical Poisson's Regression Model
... Show MoreThis research focuses on the characteristics of polyvinyl alcohol and starch polymer blends doping with Rhodamine-B. The polymer blends were prepared using the solution cast method, which comprises 1:1(wt. /wt.). The polymer blends of PVA and starch with had different ratios of glycerin 0, 25, 30, 35, and 40 % wt. The ratio of 30% wt of glycerin was found to be the most suitable mechanical properties by strength and elasticity. The polymer blend of 1:1 wt ratios of starch/PVA and 30% wt of glycerin were doped with different ratios of Rhoda mine-B dye 0, 1, 2, 3, 4, 5, and 6% wt and the electrical properties of doping biodegradable blends were studied. The ratio of Rhodamine-B 5% wt to the polymer blends showed hi
... Show MoreQuantum dots of CdSe, CdS and ZnS QDs were prepared by chemical reaction and used to fabricate organic quantum dot hybrid junction device. QD-LEDs were fabricated using ITO/TPD: PMMA/CdSe/Al, ITO/TPD: PMMA/CdS/Al and ITO/TPD: PMMA/ZnS/Al QDs devices which synthesized by phase segregation method. The hybrid white light emitting devices consists, of two-layers deposited successively on the ITO glass substrate; the first layer was of N, N’-bis (3-methylphenyl)-N, N’-bis (phenyl) benzidine (TPD) polymer mixed with polymethyl methacrylate (PMMA) polymers in ratio 1:1, while the second layer was 0.5wt% from each type of the (CdSe, CdS and ZnS) QDs for each device.The optical properties of QDs were characterized by UV-Vis. and photolum
... Show MoreA theoretical study to design a conformal microstrip antennas was introduced in this work. Conformal microstrip antennas define antennas which can be conformed to a certain shape or to any curved surface. It is used in high-speed trains, aircraft, defense and navigation systems, landing gear and various communications systems, as well as in body wearable. Conformal antennas have some advantages such as a wider-angle coverage compared to flat antennas and low radar cross-sectional (RCS) and they are suitable for using in Radome. The main disadvantage of these antennas is the narrow bandwidth. The FDTD method is extremely useful in simulating complicated structures because it allows for direct integration of Maxwell's equations depending o
... Show MoreA simulation study is used to examine the robustness of some estimators on a multiple linear regression model with problems of multicollinearity and non-normal errors, the Ordinary least Squares (LS) ,Ridge Regression, Ridge Least Absolute Value (RLAV), Weighted Ridge (WRID), MM and a robust ridge regression estimator MM estimator, which denoted as RMM this is the modification of the Ridge regression by incorporating robust MM estimator . finialy, we show that RMM is the best among the other estimators
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
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