Human urinary Adenosine-3',5'-cyclic monophosphate (cAMP) was studied in 90 normal healthy volunteers (49 males and 41 females) aged between (11 months -55 years), and 86 leukemia patients (48 males and 38 females) of four types (25 ALL, 28 AML, 14 CLL, 19 CML) aged between (11 months - 65 years). The study includes the following:- Extraction and purification of urinary cAMP from the interfering nucleotides, proteins, phosphates and pyrophosphates, by using Zinc sulphate –Barium hydroxide precipitation. The extracted cAMP was purified by using Dowax 50W-H+ hydrogen form column chromatography (1x5 cm). Identification of the purified cAMP, this was achieved by applying the following techniques: a- U.V analysis: -

Five species of Lactic acid bacteriawere isolated from raw milk, yoghurt, vegetables and pickles, Lactobacillus plantarum, Lactobacillus acidophilus, Lactobacillus brevis, Lactobacillus casei and Lactobacillus bulgaricus isolates were identified by 16S rRNA gene. Evaluate of antimicrobial activity against all the bacterial strains Staphylococcus aureus, Salmonella spp., Pseudomonas fluorescens, Escherichia coli, Bacillus cereus and Bacillus subtilis. It showed that bacteriocin of Lactic acid bacteriamore effective than supernatant of lactic acid bacteria, the results showed that isolatemost efficient isolate belonging to Lactobacillus brevis, the diameter of the inhibition of the bacteriocin of Lactobacillus brevis were 27.7, 26.3 and 25.1

Vascular patterns were seen to be a probable identification characteristic of the biometric system. Since then, many studies have investigated and proposed different techniques which exploited this feature and used it for the identification and verification purposes. The conventional biometric features like the iris, fingerprints and face recognition have been thoroughly investigated, however, during the past few years, finger vein patterns have been recognized as a reliable biometric feature. This study discusses the application of the vein biometric system. Though the vein pattern can be a very appealing topic of research, there are many challenges in this field and some improvements need to be carried out. Here, the researchers reviewed

The primary objective of this research is to determine the best EDI
software application that meets the users' requirements, and to show
the functionality potentially presented in any software of electronic
data interchange (EDI) system. Also, in this paper, will be addressed
issues relating to integration EDI system into business process, and
the issues regarding the performance of EDI application will also be
discussed

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

A Multiple System Biometric System Based on ECG Data

This study attempts to test the possibility of developing organizational performance in Zain Telecom by adapting the philosophy and concept of Organizational Identification and its dimensions, the most important of which are (Organizational Identification, organizational loyalty, organizational affiliation).To achieve the goal, the research relied on the questionnaire method, which is one of the methods of collecting information in field studies.

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu