In this paper, method of steganography in Audio is introduced for hiding secret data in audio media file (WAV). Hiding in audio becomes a challenging discipline, since the Human Auditory System is extremely sensitive. The proposed method is to embed the secret text message in frequency domain of audio file. The proposed method contained two stages: the first embedding phase and the second extraction phase. In embedding phase the audio file transformed from time domain to frequency domain using 1-level linear wavelet decomposition technique and only high frequency is used for hiding secreted message. The text message encrypted using Data Encryption Standard (DES) algorithm. Finally; the Least Significant bit (LSB) algorithm used to hide secr

The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi

This study included effect of polyherbs mixture treatment of diabetic patients type II for two months. The polyherbs mixture contains Nigella sativa seeds, Boswellia carterri gum, Citrus aurantifolia fruits, Elettaria cardamomum fruits. Also this study included estimation of some biochemical parameters in the serum Diabetes Mellitus (D.M.) patients-type II and knowing the relationship of these parameters with this disease. The parameters are glucose, cholesterol ,High density , Low density lipoproteins( HDL-C, LDL-C) respectively , Triglycerides TG, urea, total protein , albumin , Alkaline phosphatase ALP,Transaminase GOT, GPT enzymes . Take (77) samples of diabetic patients serum type II which included (47) samples for group one: herbs

هدف البحث إلى التعرف على مستوى الثقافة الغذائية الرياضية لدى عدائي مسافات ركض (400 و800) و(400) متر حواجز الشباب، والتعرف على العلاقة وإسهام وأثر الثقافة الغذائية الرياضية ببعض المؤشرات البيوكيميائية لدى عدائي مسافات ركض (400 و800) و(400) متر حواجز الشباب، أعتمد المنهج الوصفي بأسلوب العلاقات الإرتباطية، و تمثلت حدود مجتمع البحث بالعدائين الشباب لفعاليات ركض (400 و800) و(400) متر حواجز، يمثلون لاعبي الأندية العراقية الب

Background: The association between diabetes and inflammatory dental diseases had been studied extensively for more than 50 years. A large evidence base suggests that diabetes is associated with an increased prevalence, extent and severity of gingivitis and periodontitis and loss of teeth. Many patients do not aware that they are diabetic.Objectives:The aim of the current study was to assess a fast, non-invasive, safe procedure to screen for diabetes and its severity in dental clinics and to assess the change in blood glucose level before and after tooth extraction during periodontalResults: there were no significant differences between the blood samples collected before tooth extraction from finger puncture method (FPB) and the gingival

Gas sensors are essential for detecting noxious gases that have a detrimental effect on people's health and welfare. Carbon quantum dots (CQDs) are the fundamental component of gas detectors. CQDs and graphene (Gr) were prepared using the electrochemical method. The gas sensitivity of these materials was evaluated at different temperatures (150, 200, 250 °C) to assess their effectiveness. Subsequently, experiments were conducted at different temperatures to ascertain that the combination of CQDs and Gr, with various percentages of Gr and CQDs, exhibited superior gas sensitization properties compared to CQDs alone. This was evaluated based on criteria such as sensitivity, recovery time, and reaction time. Interestingly, the combination was

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

In this study, the modified size-strain plot (SSP) method was used to analyze the x-ray diffraction lines pattern of diffraction lines (1 0 1), (1 2 1), (2 0 2), (0 4 2), (2 4 2) for the calcium titanate(CaTiO3) nanoparticles, and to calculate lattice strain, crystallite size, stress, and energy density, using three models: uniform (USDM). With a lattice strain of (2.147201889), a stress of (0.267452615X10), and an energy density of (2.900651X10-3 KJ/m3), the crystallite was 32.29477611 nm in size, and to calculate lattice strain of Scherrer (4.1644598X10−3), and (1.509066023X10−6 KJ/m3), a stress of(6.403949183X10−4MPa) and (26.019894 nm).