The study aimed to evaluate the antimicrobial activity using different concentrations of aqueous and alcoholic extracts of dried lemongrass leaves. Chemical phytochemical tests were performed for aqueous and alcoholic extracts of lemongrass. Antimicrobials activity was tested using agar disc diffusion method against Escherichia coli and Staphylococcus aureus. The results of the study showed that the aqueous extract of dried lemon leaves was highly effective (P≤0.05) against S. aureus, as the inhibition diameter was 22 mm for 50 dilution, while the inhibition diameter decreased to 15 mm for concentration 100. As for the alcoholic extract only, the diameter of inhibition decreased significantly (P≤0.0

Since the advent of the sunrise of the immortal message, Islamic legislation has always established justice and the right guidance, and has prevented any perversion, injustice or corruption, with a divine system that called in its course the characteristics of the legislation on its general basis and its ability to develop, progressivity, and paving the way with a collective approach, accompanied by the worldly and moral punishment. When the corrupters went too far, reformers were delayed and values were missed; Mankind has been afflicted with the scourge of injustice and loss, and has lost sight of the approach that the Creator of the world has given to the people of the world, for what would guide them in their affairs sooner and later

A field experiment was carried out at the research station of the College of Agriculture - Wasit University / Kut, during the fall season 2021 in soil with texture (sandy mixture) using the RCBD design in the arrangement of splintered plates and with three replications, to study the effect of spraying different combinations of organic emulsion (Appetizer) and NPK nano fertilizer with urea fertilizer on the growth of synthetic cultivars of yellow corn. The main panels included three synthetic varieties of yellow corn (Fajr1, Sumer and Baghdad3), which symbolized by (V1,V2,V3) in sequence, while the secondary panels included five fertilization treatments in which mineral fertilizer (urea) was used 46% nitrogen with the full recomme

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

الخلاصة:
ة k تعتبر عملیة تشفیر البیانات الصوتیة من التكنولوجیا المألوفة لخزن ونقل الاشارات الصوتیة. العلامة المائی
ات k اق المعلوم k مح بالح k ذا تس k وتیة وھك k ارات الص k طة الاش k ة بواس k ات المنقول k تعطي القوة في عدم التحسس بوجود البیان
القیمة بالمحتوى مثل اسم المؤلف او الفنان او حقوق الطباعة المتعلقة بالبیانات.
ة k وع موج k ن ن k وتي م k ف ص k ي مل k ص ف k وع ن k ن ن k ة م k ة المائی k اء العلام k نة لاخف k ة محس k ث خوارز

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa