Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discriminate the polarity of sentiments. This paper proposes a hybrid method of linguistic and statistical features along with classification methods for Arabic sentiment analysis. Linguistic features contains stemming and POS tagging, while statistical contains the TF-IDF. A benchmark dataset of Arabic tweets have been used in the experiments. In addition, three classifiers have been utilized including SVM, KNN and ME. Results showed that SVM has outperformed the other classifiers by obtaining an f-score of 72.15%. This indicates the usefulness of using SVM with the proposed hybrid features.
Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T
... Show MoreThe extracting of personal sprite from the whole image faced many problems in separating the sprite edge from the unneeded parts, some image software try to automate this process, but usually they couldn't find the edge or have false result. In this paper, the authors have made an enhancement on the use of Canny edge detection to locate the sprite from the whole image by adding some enhancement steps by using MATLAB. Moreover, remove all the non-relevant information from the image by selecting only the sprite and place it in a transparent background. The results of comparing the Canny edge detection with the proposed method shows improvement in the edge detection.
DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio
... Show MoreIn this communication, introduce the split Mersenne and Mersenne-Lucas hybrid quaternions, also obtaining generating functions and Binet formulas for these hybrid quaternions and investigating some properties among them.
Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
... Show MoreMonthly water samples from three stations in Diwanya river at Diwanyia city were collected during December 1999 to June 2000. Variables from each stations were determined including ; temperature, pH ,dissolved oxygen, dissolved carbon dioxide , alkalinity ,total hardness, calcium ,magnesium , phosphate, nitrite, nitrate, chlorophyll-a , and total number of phytoplankton .The river considered as fresh water , alkaline ,very hard .The parameters recorded at different values from up and down stream.
In a hybrid cooling solar thermal systems , a solar collector is used to convert solar energy into heat energy in order to super heat the refrigerant leaving the compressor, and this process helps in the transformation of refrigerant state from gaseous state to the liquid state in upper two-thirds of the condenser instead of the lower two-thirds such as in the traditional air-conditioning systems and this will reduce the energy needed to run the process of cooling .In this research two systems with a capacity of 2 tons each were used, a hybrid air-conditioning system with an evacuated tubes solar collector and a traditional air-conditioning system . The refrigerant of each type was R22.The comparison was in the amou
... Show MoreThis study objective is to identify the visual pollution in Karrada district main streets as an example of main streets in Baghdad, the public opinion about each pollutants, solutions to reduce and eliminate the pollution were suggested as well. In order to accomplish this objective different methods were used, 16 pollutants were selected, pictures of each pollutants were taken and a questioner were distributed randomly for 270 people to evaluate the public opinion with statistical methods. Garbage, their disposal and storage areas took the first two places as the highest offensive pollutants. The people showed that they find long lines of vehicles, debris and generators appearance ranked third, fourth and fifth respectively .This resear
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