The current study included the collection of 175 samples (blood-urea) of patients suffering from rheumatism, collected from Baghdad Teaching Hospital (Educational Laboratory), Al-Kindy Teaching Hospital, Al-Imamian Al-Kadhimya in Medical City in Baghdad at different duration between 2016/10/1-2017/2/1. The bacterial growth results showed that 80% of urea samples positive for bacterial culture, while the rate of samples did not show any bacterial grow this 20%. The isolation subjugates to morphological, microscopically and biochemical tests, as also diagnosis by Api system. The most frequent bacterial pathogenic is E. coli which appeared highly rate (41.97)% followed by E. cloacae (21.25)%, P. aeruginosa (12.5)%, Salmonella (10)% and the proportion of K. pneumonia (7.5)%, while S. marcescens showed (6.25)%. When the measurement of the concentration of liver enzymes Glutamic Oxalate Transaminase (GOT), Glutamic Pyruvate Transaminase (GPT), Alkaline phosphates’(ALP), the results showed a significant degreaseP≤ 0.05 in the level of enzyme GPT in patients serum which reachto16. 94±0.84 mg/ml, while its level in the healthy serum was 0.68±6.78 mg/ml. ALP enzyme results showed non-significant high atP≤ 0.05 in the level of patients serum with rheumatoid arthritis, as it reached the level in the serum 2.46±134.42 mg/ml, while the level in the healthy serum was 0.50±4.11 mg/ml. The enzyme GOT showed on-significant high at P≤ 0.05 in the level of patients serum as it reached the level in the serum 0.88±21.51 mg/ml, while the level in the healthy serum was 0.50±4.11 mg/ml.
This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
... Show MoreThe main purpose of this work is to introduce some types of fuzzy convergence sequences of operators defined on a standard fuzzy normed space (SFN-spaces) and investigate some properties and relationships between these concepts. Firstly, the definition of weak fuzzy convergence sequence in terms of fuzzy bounded linear functional is given. Then the notions of weakly and strongly fuzzy convergence sequences of operators are introduced and essential theorems related to these concepts are proved. In particular, if ( ) is a strongly fuzzy convergent sequence with a limit where linear operator from complete standard fuzzy normed space into a standard fuzzy normed space then belongs to the set of all fuzzy bounded linear operators
In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured. The manufactured physical model could be used to simulate steady state harmonic load at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into considerations include loading frequency, size of footing and different soil conditions. The footing parameters were related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used (100 200 12.5 mm) and (200 400 5.0 mm).
... Show MoreBiaxial hollow slab is a reinforced concrete slab system with a grid of internal spherical voids included to reduce the self-weight. This paper presents an experimental study of behavior of one-way prestressed concrete bubbled slabs. Twelve full-scale one-way concrete slabs of (3000mm) length with rectangular cross-sectional area of (460mm) width and (150mm) depth. Different parameters like type of specimen (solid or bubbled slabs), type of reinforcement (normal or prestress), range of PPR and diameter of plastic spheres (100 or 120mm) are considered. Due to the using of prestressing force in bubbled slabs (with ratio of plastic sphere diameter D to slab thickness H, D/H=0.67), the specimens showed an increase in ultimat
... Show MoreCipher security is becoming an important step when transmitting important information through networks. The algorithms of cryptography play major roles in providing security and avoiding hacker attacks. In this work two hybrid cryptosystems have been proposed, that combine a modification of the symmetric cryptosystem Playfair cipher called the modified Playfair cipher and two modifications of the asymmetric cryptosystem RSA called the square of RSA technique and the square RSA with Chinese remainder theorem technique. The proposed hybrid cryptosystems have two layers of encryption and decryption. In the first layer the plaintext is encrypted using modified Playfair to get the cipher text, this cipher text will be encrypted using squared
... Show More