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

Abstract: Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In this paper, genetic algorithms proposed to solve the word sense disambiguation problem that can automatically select the intended meaning of a word in context without any additional resource. The proposed algorithm is evaluated on a col

Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal image co

A green and low-cost method was used to prepare graphene oxide (GO) and reduced graphene oxide (rGO) by chemical exfoliation of graphite powder by modified Hummers method, followed by reduction using ascorbic acid. X-ray diffractometry (XRD) and field emission scanning electron microscopy (FE-SEM) were used to analyze the structure and morphology of the synthesized materials. Fourier transform infrared spectroscopy (FTIR) and ultraviolet-visible spectroscopy were used to identify the formation of the GO and rGO

This article deals with estimations of system Reliability for one component, two and s-out-of-k stress-strength system models with non-identical component strengths which are subjected to a common stress, using Exponentiated Exponential distribution with common scale parameter. Based on simulation, comparison studies are made between the ML, PC and LS estimators of these system reliabilities when scale parameter is known.

A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

The objective of all planning research is to plan for human comfort and safety, and one of the most significant natural dangers to which humans are exposed is earthquake risk; therefore, earthquake risks must be anticipated, and with the advancement of global technology, it is possible to obtain information on earthquake hazards. GIS has been utilized extensively in the field of environmental assessment research due to its high potential, and GIS is a crucial application in seismic risk assessment. This paper examines the methodologies used in recent GIS-based seismic risk studies, their primary environmental impacts on urban areas, and the complexity of the relationship between the applied methodological approaches and the resulting env

Copper, and its, alloys and composites (being the matrix), are broadly used in the electronic as well as bearing materials due to the excellent thermal and electrical conductivities it has.

In this study, powder metallurgy technique was used for the production of copper graphite composite with three volume perc ent of graphite.  Processing parameters selected is (900) °C sintering temperature and (90) minutes holding time for samples that were heated in an inert atmosphere (argon gas). Wear test results showed a pronounced improvement in wear resistance as the percent of graphite increased which acts as solid lubricant (where wear rate was decreased by about 88% as compared with pure Cu). Microhardness and