Average interstellar extinction curves for Galaxy and Large Magellanic Cloud (LMC) over the range of wavelengths (1100 A0 – 3200 A0) were obtained from observations via IUE satellite. The two extinctions of our galaxy and LMC are normalized to Av=0 and E (B-V)=1, to meat standard criteria. It is found that the differences between the two extinction curves appeared obviously at the middle and far ultraviolet regions due to the presence of different populations of small grains, which have very little contribution at longer wavelengths. Using new IUE-Reduction techniques lead to more accurate result.

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

  This study deals with thirty non-insulin dependent diabetes mellitus patients suffering from diabetic nephropathy in addition to twenty five healthy control.Some biochemical parameters were determined in the serum of all subjects enrolled in the study.These parameters are serum glucose,serum urea,serum creatinine,total serum protein and serum albumin.The aim of the present study was to estimate these parameters in diabetic nephropathy  patients.     The results of the present study revealed a significant increase in glucose,urea and creatinine in patients as compared to controls . Also a significant decrease was found in total serum protein, serum albumin and albumin to globulin ratio (A/G) in patients com

This study deals with thirty non-insulin dependent diabetes mellitus patients suffering from diabetic nephropathy in addition to twenty five healthy control.Some biochemical parameters were determined in the serum of all subjects enrolled in the study.These parameters are serum glucose,serum urea,serum creatinine,total serum protein and serum albumin.The aim of the present study was to estimate these parameters in diabetic nephropathy patients. The results of the present study revealed a significant increase in glucose,urea and creatinine in patients as compared to controls . Also a significant decrease was found in total serum protein, serum albumin and albumin to globulin ratio (A/G) in patients compared to controls,whi

The element carbon Carbon dioxide emissions are increasing primarily as a result of people's use of fossil fuels for electricity. Coal and oil are fossil fuels that contain carbon that plants removed from the atmosphere by photosynthesis over millions of years; and in just a few hundred years we've returned carbon to the atmosphere. The element carbon Carbon dioxide concentrations rise primarily as a result of the burning of fossil fuels and Freon for electricity. Fossil fuels such as coal, oil and gas produce carbon plants that were photosynthesized from the atmosphere over many years, since in just two centuries, carbon was returned to the atmosphere. Climate alter could be a noteworthy time variety in weather designs happening ov

    Examining of 80 feces samples showed that 31 samples of the house and stray cats harbored either single or mixed infection with eight species of parasites and protozoa with a total infection rate 38.75 %.The results on parasite classes are: Toxocara cati (5%), Ancylostoma tubeforme (3.75%), Capillaria felis(3.75%), Isospora sp.(10%), Cryptosporidium parvum(3.75%), Cryptosporidium muris (6.25%), Toxoplasma gondi (3.75%), Giardia sp.(2.5%) infection from feces of cats that showed single, double and triple infections. Our findings revealed the risk for public health, thus preventive measures should be implemented.

Routing protocols are responsible for providing reliable communication between the source and destination nodes. The performance of these protocols in the ad hoc network family is influenced by several factors such as mobility model, traffic load, transmission range, and the number of mobile nodes which represents a great issue. Several simulation studies have explored routing protocol with performance parameters, but few relate to various protocols concerning routing and Quality of Service (QoS) metrics. This paper presents a simulation-based comparison of proactive, reactive, and multipath routing protocols in mobile ad hoc networks (MANETs). Specifically, the performance of AODV, DSDV, and AOMDV protocols are evaluated and analyz

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an