Detection moving car in front view is difficult operation because of the dynamic background due to the movement of moving car and the complex environment that surround the car, to solve that, this paper proposed new method based on linear equation to determine the region of interest by building more effective background model to deal with dynamic background scenes. This method exploited the permitted region between cars according to traffic law to determine the region (road) that in front the moving car which the moving cars move on. The experimental results show that the proposed method can define the region that represents the lane in front of moving car successfully with precision over 94%and detection rate 86

In this study, we attempt to provide healthcare service to the pilgrims. This study describes how a multimedia courseware can be used in making the pilgrims aware of the common diseases that are present in Saudi Arabia during the pilgrimage. The multimedia courseware will also be used in providing some information about the symptoms of these diseases, and how each of them can be treated. The multimedia courseware contains a virtual representation of a hospital, some videos of actual cases of patients, and authentic learning activities intended to enhance health competencies during the pilgrimage. An examination of the courseware was conducted so as to study the manner in which the elements of the courseware are applied in real-time learn

 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the

Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

  The reaction of LAs-Cl8 : [ (2,2- (1-(3,4-bis(carboxylicdichloromethoxy)-5-oxo-2,5dihydrofuran-2-yl)ethane – 1,2-diyl)bis(2,2-dichloroacetic acid)]with sodium azide in ethanol with drops of distilled water has been investigated . The new product L-AZ :(3Z ,5Z,8Z)-2azido-8-[azido(3Z,5Z)-2-azido-2,6-bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H-1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide was isolated and characterized by elemental analysis (C.H.N) , 1H-NMR , Mass spectrum and Fourier transform infrared spectrophotometer (FT-IR) . The reaction of the L-AZ withM+n: [ ( VO(II) , Cr(III)  ,Mn(II) , Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) and

Abstract: The M(II) complexes [M2(phen)2(L)(H2O)2Cl2] in (2:1:2 (M:L:phen) molar ratio, (where M(II) =Mn(II), Co(II), Cu(II), Ni(II) and Hg(II), phen = 1,10-phenanthroline; L = 2,2'-(1Z,1'Z)-(biphenyl-4,4'-diylbis(azan-1-yl-1-ylidene))bis(methan-1-yl-1- ylidene)diphenol] were synthesized. The mixed complexes have been prepared and characterized using 1H and13C NMR, UV/Visible, FTIR spectra methods and elemental microanalysis, as well as magnetic susceptibility and conductivity measurements. The metal complexes were tested in vitro against three types of pathogenic bacteria microorganisms: Staphylococcus aurous, Escherichia coli, Bacillussubtilis and Pseudomonasaeroginosa to assess their antimicrobial properties. From this study shows that a

   The concept of implementing e-government systems is growing widely all around the world and becoming an interest to all governments. However, governments are still seeking for effective ways to implement e-government systems properly and successfully. As services of e-government increased and citizens’ demands expand, the e-government systems become more costly to satisfy the growing needs. The cloud computing is a technique that has been discussed lately as a solution to overcome some problems that an e-government implementation or expansion is going through. This paper is a proposal of a  new model for e-government on basis of cloud computing. E-Government Public Cloud Model EGPCM, for e-government is related t

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

In this paper, a compartmental differential epidemic model of COVID-19 pandemic transmission is constructed and analyzed that accounts for the effects of media coverage. The model can be categorized into eight distinct divisions: susceptible individuals, exposed individuals, quarantine class, infected individuals, isolated class, infectious material in the environment, media coverage, and recovered individuals. The qualitative analysis of the model indicates that the disease-free equilibrium point is asymptotically stable when the basic reproduction number R0 is less than one. Conversely, the endemic equilibrium is globally asymptotically stable when R0 is bigger than one. In addition, a sensitivity analysis is conducted to determine which