Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border

Students’ feedback is crucial for educational institutions to assess the performance of their teachers, most opinions are expressed in their native language, especially for people in south Asian regions. In Pakistan, people use Roman Urdu to express their reviews, and this applied in the education domain where students used Roman Urdu to express their feedback. It is very time-consuming and labor-intensive process to handle qualitative opinions manually. Additionally, it can be difficult to determine sentence semantics in a text that is written in a colloquial style like Roman Urdu. This study proposes an enhanced word embedding technique and investigates the neural word Embedding (Word2Vec and Glove) to determine which perfo

Aim of the study: This study's goal was to determine how laser surface alteration affected wettability of injectable thermoplastic acrylic and heat cure acrylic denture base materials. Materials and methods: Injectable thermoplastic acrylic resin (Deflex) and heat cure acrylic (Procryla) were used in this study to produce forty-disc shaped specimens, 20 specimens for each material type. The control group was made up of ten samples of each type of plastic denture base material. The other ten samples were treated with a nano-pulse fiber-optic lens Nd:YAG laser. The results were looked at with the Kruskal-Wallis test and the unpaired t-test (a=.05). Results: Compared to the control groups, the laser-treated groups were more likely to sti

This work aimed to investigate the effect of Diode laser 805 nm on plasmid DNA and RNA
contents of some Gram negative bacteria represented by Escherichia coli and Proteus mirabilis isolates
.Plasmid extraction was done using two methods (Salting out and CTAB method).Different powers and
pulse repetition rates for 805 nm Diode Laser were used to study this effect. Results revealed that the
plasmid profile of the two species were highly affected using (2, 3) W at different frequencies including
5and 10 kHz as compared with 1 kHz while plasmids were gradually disappeared at 1W, 10 kHz. In the
same time the shining of RNA was also decreased gradually then disappeared with increasing powers
especially at 2W and 10 kHz cau

The size and the concentration of the gold nanoparticles (GNPs)
synthesized in double distilled deionized water (DDDW) have been
found to be affected by the laser energy and the number of pulses.
The absorption spectra of the nanoparticles DDDW, and the
surface plasmon resonance (SPR) peaks were measured, and found to
be located between (509 and 524)nm using the UV- Vis
spectrophotometer. SPR calculations, images of transmission
electron microscope, and dynamic light scattering (DLS) method
were used to determine the size of GNPs, which found to be ranged
between (3.5 and 27) nm. The concentrations of GNPs in colloidal
solutions found to be ranged between (37 and 142) ppm, and
measured by atomic absorptio

The aim of the study is to detect the malignant conditions of the skin tumors through the features of optical images. This research included some of image processing techniques to detect skin cancer as a strong threat to human beings' lives. Using image processing and analysis methods to improves the ability of pathologists to detect this disease leading to more specified diagnosis and better treatment of them. One hundred images were collected from Benign and Malignant tumors and some appropriate image features were calculated, like Maximum Probability, Entropy, Coefficient of Variation, Homogeneity and Contrast, and using Minimum Distance method to separate these images. These features with Minimum Distance as a proposed making decision a

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For