“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical

The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

DBN Rashid, International Journal of English Linguistics, 2019 - Cited by 2

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th