Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show

Voucher documents have become a very important information carrier in daily lives to be used in many applications. A certain class of people could exploit the trust and indulge in forging or tampering for short or long term benefits unlawfully. This holds a serious threat to the economics and the system of a nation. The aim of this paper is to recognize original voucher document through its contents. Forgery of voucher document could have serious repercussions including financial losses, so the signature, logo and stamp that are used to determine being a genuine or not by using multilevel texture analysis. The proposed method consists of several operations. First, detection and extraction of signature, logo and stamp images from original

The wound healing process is incredibly intricate, consisting of a series of cellular activities. Although, this complex process has the potential to degenerate and result in chronic wound problems that are resistant to biological healing mechanisms. Nanoparticles can help to reduce inflammation, promote tissue regeneration, and accelerate wound healing. The proteolytic enzymes are believed to break down proteins and other molecules that can cause inflammation and impede the healing process. Wound was created in vivo using adult mice, and by taking blood samples the hematological parameters were evaluated to detected the effects of bromelain, silver nanoparticles and Br-AgNPs. The results shows an increased in white blood cells WBC, RBC, MC

This study introduced the effect of using magnetic abrasive finishing method (MAF) for finishing flat surfaces. The results of experiment allow considering the MAF method as a perspective for finishing flat surfaces, forming optimum physical mechanical properties of surfaces layer, removing the defective layers and decreasing the height of micro irregularities. Study the characteristics which permit judgment parameters of surface quality after MAF method then comparative with grinding

The aim for this research is to investigate the effect of inclusion of crack incidence into the 2D numerical model of the masonry units and bonding mortar on the behavior of unreinforced masonry walls supporting a loaded reinforced concrete slab. The finite element method was implemented for the modeling and analysis of unreinforced masonry walls. In this paper, ABAQUS, FE software with implicit solver was used to model and analyze unreinforced masonry walls which are subjected to a vertical load. Detailed Micro Modeling technique was used to model the masonry units, mortar and unit-mortar interface separately. It was found that considering potential pure tensional cracks located vertically in the middle of the mortar and units show

.

     In this article, we investigate the heat transfer on nanoparticles Jeffrey Hamel flow problem between two rigid plane walls. Water is used as a main fluid using four different types of nanoparticles, namely aluminum, cuprous, titanium, and silver. The results of nonlinear transformational equations with boundary conditions are solved analytically and numerically. The perturbation iteration scheme (PIS) is used for the analytic solution, while for determining the numerical results, the Rang-Kutta of the four-order scheme (RK4S) is used. The effects on the behavior of non-dimensional velocity and temperature distributions are presented in the form of tables and graphs for different values ​​of emerging physical parameters (Rey

Seismic facies analysis constrained with well log information have been used to predict lithofacies distribution across the Okam Field of Niger Delta. Density and gamma ray logs were cross-plotted and the seismic section was subdivided vertically into different seismic facies. The delineated lithologies, from well logs were correlated with seismic facies signatures using lines of intersection across the wells. Gamma ray and resistivity logs were used to identify the interfaces between the lithofacies and correlated across the field. Structural interpretation was carried out. Time slices were generated and examined at different intervals within the identified reservoirs. Stratigraphic related attribute and envelope were extracted on these