Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

In this work the structural, optical and sensitive properties of Cerium - Copper oxide thin film prepared on silicon and glass substrate by the spray pyrolysis technique at a temperature of (200, 250, 300 °C). The results of (XRD) showed that all the prepared films were of a polycrystalline installation and monoclinic crystal structure with a preferable directions was (111) of CuO. Optical characteristics observed that the absorption coefficient has values for all the prepared CuO: Ce% (104 cm-1) in the visible spectrum, indicating that all the thin films prepared have a direct energy gap. Been fabrication of gas sensors of (CuO: Ce %) within optimum preparation conditions and study sensitivity properties were examined her exposed to ni

Review of multidrug sensitivity and resistance in enterococcus

In this work gold nanoparticles (AuNPs), were prepared. Chemical method (Seed-Growth) was used to prepare it, then doping AuNPs with porous silicon (PS), used silicon wafer p-type to produce (PS) the processes doping achieved by electrochemical etching, the solution etching consist of HF, ethanol and AuNPs suspension, the result UV-visible absorption for AuNPs suspension showed the single peak located at ~(530 – 521) nm that related to SPR, the single peak is confirmed that the NPs present in the suspension is spherical shape and non-aggregated. X-ray diffraction analysis indicated growth AuNPs with PS. compare the PS layer without AuNPs and with AuNPs doped for electrical properties and sensitivity properties we found AuNPs:PS is more

Background: The antimicrobial resistance is one of the most serious and expanding health problems world -wide in the last decades. The esbl escherichia coli. (extended – spectrum beta-lactamase e.coli) represents an important aspect of it .Objectives: To get an overview on the esbl e.coli prevalence profile in general. Also to assess the antibiotic sensitivity of esbl e. coli trying to specify the most effective antibiotics in combating this micro-organism.Methods: this study tries to focus on this problem in Iraq which through a prospective study approach by taking 35 clinical samples from various sources (urine, blood, abscess, eye ,vagina ,stool and others),and after confirming the presence of e.coli, the presence of esbl e.coli and

Nowadays, energy demand continuously rises while energy stocks are dwindling. Using current resources more effectively is crucial for the world. A wide method to effectively utilize energy is to generate electricity using thermal gas turbines (GT). One of the most important problems that gas turbines suffer from is high ambient air temperature especially in summer. The current paper details the effects of ambient conditions on the performance of a gas turbine through energy audits taking into account the influence of ambient conditions on the specific heat capacity ( , isentropic exponent ( ) as well as the gas constant of air . A computer program was developed to examine the operation of a power plant at various ambient temperature

The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.