ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

The spectral response of the Si solar cell does not coincidence with the sun irradiance spectrum, so the efficiency of the Si solar cell is not high. To improve the Si solar cell one try to make use of most region of the sun spectrum by using dyes which absorb un useful wavelengths and radiate at useful region of spectrum (by stock shift). Fluorescence's dye is used as luminescent concentrator to increase the efficiency of the solar cell. The results show that the performance efficiency and out power for crystalline silicon solar cells are improved.

In the digital age, protecting intellectual property and sensitive information against unauthorized access is of paramount importance. While encryption helps keep data private and steganography hides the fact that data are present, using both together makes the security much stronger. This paper introduces a new way to hide encrypted text inside color images by integrating discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD), along with AES-GCM encryption, to guarantee data integrity and authenticity. The proposed method operates in the YCbCr color space, targeting the luminance (Y) channel to preserve perceptual quality. Embedding is performed within the HL subband obtained from DWT deco

              -convex sets and -convex functions, which are considered as an important class of generalized convex sets and convex functions, have been introduced and studied by Youness [5] and other researchers. This class has recently extended, by Youness, to strongly -convex sets and strongly -convex functions. In these generalized classes, the definitions of the classical convex sets and convex functions are relaxed and introduced with respect to a mapping . In this paper, new properties of strongly -convex sets are presented. We define strongly -convex hull, strongly -convex cone, and strongly -convex cone hull and we proof some of their properties.  Some examples to illustrate the aforementioned concepts and to cl

In this research PbS and PbS:Cu films were prepered with thicknesses (0.85±0.05)?m and (0.55±0.5)?m deposit on glass and silicon substrate respectively using chemical spray pyrolysis technique with a substrate temperature 573K, from lead nitrate salt, thiourea and copper chloride. Using XRD we study the structure properties for the undoped and doped films with copper .The analysis reveals that the structure of films were cubic polycrystalline FCC with a preferred orientation along (200) plane for the undoped films and 1% doping with copper but the orientation of (111) plane is preferred with 5% doping with the rest new peaks of films and appeared because of doping. Surface topography using optical microscope were be checked, it was found

Abstract

Objectives: To assess patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention, and to find out the relationship between patients’ knowledge and their adherence to Clopidogrel Therapy Post Percutaneous Coronary Intervention

Methodology: A descriptive design was carried out at Al- Nasiriyah Heart Center in Thi-Qar Governorate for the period between May 19^th, 2022 to October 25^th, 2022. A non-probability sampling was used among (50) patients after their Percutaneous Coronary Intervention. The study instrument that used to collect data was composed of three parts namely: sociodemographic charac

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect