In this research, the covariance estimates were used to estimate the population mean in the stratified random sampling and combined regression estimates. were compared by employing the robust variance-covariance matrices estimates with combined regression estimates by employing the traditional variance-covariance matrices estimates when estimating the regression parameter, through the two efficiency criteria (RE) and mean squared error (MSE). We found that robust estimates significantly improved the quality of combined regression estimates by reducing the effect of outliers using robust covariance and covariance matrices estimates (MCD, MVE) when estimating the regression parameter. In addition, the results of the simulation study proved

Abstract: Narrow laser pulses have been essential sources in optical communication system. High data rate optical communication network system demands compressed laser source with unique optical property. In this work using pulsed duration (9) ns, peak power 1.2297mW, full width half maximum (FWHM) 286 pm, and wavelength center 1546.7 nm as compression laser source. Mach Zehnder interferometer (MZI) is built by considering two ways. First, polarization maintaining fiber (PMF) with 10 cm length is used to connect between laser source and fiber brag grating analysis (FBGA). Second, Nested Mach Zehnder interferometer (NMZI) was designed by using three PMFs with 10 cm length. These three Fibers are splicing to sing

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

In this paper different channel coding and interleaving schemes in DS/CDMA system over multipath fading channel were used. Two types of serially concatenated coding were presented. The first one composed of Reed-Solomon as outer code, convolutional code as inner code and the interleaver between the outer and inner codes and the second consist of convolutional code as outer code, interleaved in the middle and differential code as an inner code. Bit error rate performance of different schemes in multipath fading channel was analyzed and compared. Rack receiver was used in DS/CDMA receiver to combine multipath components in order to enhance the signal to noise ratio at the receiver.

In accordance with epidemic COVID-19, the elevated infection rates, disinfectant overuse and antibiotic misuse what led to immune suppression in most of the population in addition to genotypic and phenotypic alterations in the microorganisms, so a great need to reevaluate the genetic determinants that responsible for bacterial community (biofilm) has been raised. A total of 250 clinical specimens were obtained from patients in Baghdad hospitals and streaked on Mannitol salt agar medium. The results revealed that 156 isolates appeared as round yellow colonies, indicating that they were mostly identified as Staphylococcus aureus from 250 specimens. The antibiotic resistance pattern of the isolates for methicillin 37.17% (n=58), Amoxic

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

A mathematical method with a new algorithm with the aid of Matlab language is proposed to compute the linear equivalence (or the recursion length) of the pseudo-random key-stream periodic sequences using Fourier transform. The proposed method enables the computation of the linear equivalence to determine the degree of the complexity of any binary or real periodic sequences produced from linear or nonlinear key-stream generators. The procedure can be used with comparatively greater computational ease and efficiency. The results of this algorithm are compared with Berlekamp-Massey (BM) method and good results are obtained where the results of the Fourier transform are more accurate than those of (BM) method for computing the linear equivalenc

Information security in data storage and transmission is increasingly important. On the other hand, images are used in many procedures. Therefore, preventing unauthorized access to image data is crucial by encrypting images to protect sensitive data or privacy. The methods and algorithms for masking or encoding images vary from simple spatial-domain methods to frequency-domain methods, which are the most complex and reliable. In this paper, a new cryptographic system based on the random key generator hybridization methodology by taking advantage of the properties of Discrete Cosine Transform (DCT) to generate an indefinite set of random keys and taking advantage of the low-frequency region coefficients after the DCT stage to pass them to

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2