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

Deep 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

In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

Polycaprolactone is one of the natural biodegradable polymers mainly used in bioplastics production for packaging, usually composed of non-toxic compounds and biodegradable. The aim was to examine the role of zinc oxide (ZnO) nanopowder on the,wettability , thermal and anti-bacterial effect nanocomposites.  Pure PCL and PCL-based bio- nanocomposites doped with various ratios of ZnO nanoparticles from 0% to 5wt% were prepared through the arrangement of throwing procedure.  The results show that wettability properties in relation to ideal PCL and that they were increasingly hydrophobic from 57º.8 to 69º.53 because add ZnO  nanocomposites,the thermal stability between 300 and 400 ° C makes them perfect for the application

Objective: Zerumbone (ZER) is a well-known natural compound that has been reported to have anti-cancer effect. Thus, this study investigated the ZER potential to inhibit Thymidine Phosphorylase (TP) and the ability to trigger Reactive oxygen species (ROS)-mediated cytotoxicity in non-small cell lung cancer, NCI-H460, cell line. Material and Method: The antiangiogenic activity for ZER was evaluated by using the thymidine phosphorylase inhibitory test. Reactive oxygen species (ROS) production was determined via DCFDA dye by using flow cytometry. Result and Discussion: ZER was found to be potent TP inhibitory with the IC50 value of 50.3± 0.31 μg/ml or 230±1.42 µM. NCI-H460 cells upon treatment with ZER produced sign

Fusarium pseudograminearum and Fusarium graminearum commonly cause crown rot (FCR) and head blight (FHB) in wheat, respectively. Disease infection and spread can be reduced by the deployment of resistant cultivars or through management practices that limit inoculum load. Plants deficient in micronutrients, including zinc, tend to be more susceptible to many diseases. On the other hands, and zinc deficiency in cereals is widespread in Australian soils. Zinc deficiency may have particular relevance to crown rot, the most important and damaging Fusarium disease of wheat and barley in Australia. Four wheat genotypes; Batavia, Sunco and two lines from the International Maize and Wheat Improvement Center (CIMMYT) were tested for response

Objective: Zerumbone (ZER) is a well-known natural compound that has been reported to have anti-cancer effect. Thus, this study investigated the ZER potential to inhibit Thymidine Phosphorylase (TP) and the ability to trigger Reactive oxygen species (ROS)-mediated cytotoxicity in non-small cell lung cancer, NCI-H460, cell line. Material and Method: The antiangiogenic activity for ZER was evaluated by using the thymidine phosphorylase inhibitory test. Reactive oxygen species (ROS) production was determined via DCFDA dye by using flow cytometry. Result and Discussion: ZER was found to be potent TP inhibitory with the IC50 value of 50.3± 0.31 μg/ml or 230±1.42 µM. NCI-H460 cells upon treatment with ZER produced sign