This study aims to compare the efficiency of Intuitionistic Fuzzy Neural Network with Genetic Algorithm (IFNN-GA) in detecting real-time traffic signs in different road conditions compared with the human eyes in order to prove that they are more efficient in understanding the surrounding environment, support safe driving, and overcome human defects. Highlighting the driver's obstacles such as weather conditions, uneven lighting, shadows everywhere, intensity and brightness fluctuations and contrast in shape and texture of traffic signs and time spent for entry and exit. In order to realize all aspects of the road, a model was proposed: Intuitionistic Fuzzy Neural Network with Genetic Algorithm (IFNN-GA).

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Journal: , Journal of Telecommunication, Electronic and Computer Engineering (JTEC), Volume 10 Issue 2-4 Pages 193-196,

In this paper will discuss and examine message transmission from the attacker process within the scope of Delay Tolerance Networks (DTNs). DTNs are a new area of research that can be developed in networking. Delay-tolerant networks are those networks that may not have a complete path between networks end-to-end via direct links and may be under development for a long time. As part of the improvement, we will compare a survey of DTN routing protocols with a real region area, and then taking into account the possibilities of detecting the presence of areas of weakness that lead to penetration, which will occur in the nodes while on the move. In this study, we will use the ONE simulator to track messages within nodes

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Journal: Computer and Information Science , Vol. 14, No. 2 (2021)

Vehicular Ad hoc Networks (VANETs) is new sort in wireless ad-hoc networks. Vehicle-to-Vehicle (V2V) communication is one of the main communication paradigms that provide a level of safety and convenience to drivers and passengers on the road. In such environment, routing data packet is challenging due to frequently changed of network topology because of highly dynamic nature of vehicles. Thus, routing in VANETs in require for efficient protocols that guarantee message transmission among vehicles. Numerous routing protocols and algorithms have been proposed or enhanced to solve the aforementioned problems. Many position based routing protocols have been developed for routing messages that have been identified to be appropriate for VANETs. This work explores the performances of selected unicast non-delay tolerant overlay position-based routing protocols. The evaluation has been conducted in highway and urban environment in two different scenarios. The evaluation metrics that are used are Packet Delivery Ratio (PDR), Void Problem Occurrence (VPO), and Average Hop Count (AHC).

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Journal: Vol. 13 No. 2

this study aimed to identifying the impact of social media on electronic loyalty to the Jordanian consumer. The current study is based on four dimensions of social media for measuring and it’s as follows: informatics, interaction, credibility and content sharing. This study has also followed two dimensions for measuring electronic loyalty, namely; electronic trust and electronic satisfaction. The study was conducted on a sample of 739 Jordanian consumers who use social media for purchasing goods and services on a regular basis. This study has found that there are middle levels of average for three dimensions of social media (informatics, interaction and content sharing), while the level of credibility dimension was high. Also the study results found out that the electronic loyalty and its dimensions (electronic trust and electronic satisfaction), they came as high levels. Results also indicated that there is a significant effect of social media on electronic loyalty of Jordanian consumer, and there is a significant effect for social media on electronic trust and electronic satisfaction of Jordanian consumer.

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Journal: INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 9, ISSUE 02, FEBRUARY 2020

This study aimed to test the role of information security on enhancing cloud computing effectiveness in Jordanian Commercial Banks. The study adopted a fivedimensional scale to measure information security (confidentiality, physical security, application security, availability, identity management), while the cloud computing effectiveness was measured through six dimensions: control, transmission costs, accuracy, performance, reliability and privacy. To achieve study aims, a descriptive-analytical method was used equal random sample. The study was conducted on a sample of (212) employees working in these banks. This study found that there is a high-level average for information security dimensions and cloud computing effectiveness dimensions. Also, the results showed a significant impact of information security dimensions (confidentiality, physical security, application security, availability, identity management) on cloud computing effectiveness. It was also evident that there a significant impact of information security on cloud computing effectiveness dimensions (control, transmission costs, accuracy, performance, reliability and privacy).

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Journal: European Journal of Scientific Research ISSN 1450-216X / 1450-202X Vol. 156 No 3 May, 2020, pp.242 - 252

This study aimed to test the impact of information technology on Information systems effectiveness in Jordanian Telecom Companies. The study adopted a five-dimensional scale to measure information technology (people, hardware, software, databases, and networks), while the information systems' effectiveness was measured through four dimensions: end-user satisfaction, system usage, system security and suitability of the system for management levels. To achieve study aims, a descriptive-analytical method was used. The study was conducted on a sample of (152) managers working in these companies. This study found that there is a high-level average for information technology dimensions and Information Systems effectiveness dimensions. Also, the results showed a significant impact of information technology dimensions (people, software, databases, and networks) except hardware on effectiveness information systems. It was also evident that there a significant impact of information technology on Information systems effectiveness dimensions (end-user satisfaction, system usage, system security and suitability of the system for management levels).

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Journal: Computer and Information Science; Vol. 13, No. 1; 2020 ISSN 1913-8989 E-ISSN 1913-8997

This study aimed at testing the role of Deep learning techniques on predicting COVID-19 big data. The study adopted two tasks to measure Deep learning (classification, clustering), while the big data was measured through three dimensions: volume, variety and velocity. To achieve study aims, the researcher relied on measuring accuracy and parameters settings of classification and clustering techniques, and measuring the features of the covid-19 dataset. First, by presenting questions that reflects the dimensionality of the dataset and the features of the two techniques. Second, by analyzing the outcomes of the artificial neural network and K-means to answer those questions. Also, the results of both techniques, artificial neural network and K-means, proved to be suitable to classify instances into two categories of negative and positive covid-19 cases and some features of both techniques are of no significant impact on accuracy, and the classification has a greatest impact on accuracy contributed to a number of features

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Journal: International Journal of Applied Engineering Research ISSN 0973-4562 Volume 15, Number 8 (2020) pp. 873-883

Arabic stemming is a technique that finds the stem or lexical root for Arabic words through the process of eliminating affixes attached to their roots. Many studies have been conducted to generate the stem of Arabic words according to the desirable level of analysis, i.e., rootbased approach, stem-based approach and statistical approach. Arabic language, which is the focus of this paper, is a Semitic language which means that it is a derivational rather than a concatinative language. In this paper we implemented an Arabic triliteral Morphological Analyser that is capable of analysing the classical and modern standard Arabic (MSA) effectively and able to analyse vowelised, semi-vowelised and nonvowelised text. the system is integratable with other applications. one shortcomming for the developed system is that the output obtained from the morphological analyser may contain several alternative solutions which leads to extraction ambiguity.

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Journal: California USA 2019 - Second International Conference on Artificial Intelligence for Industries

Predicting changes in air pollutant concentrations due to human and nature drivers are critical and challenging, particularly in areas with scant data inputs and high variability of parameters. This paper builds an Air Quality Index (AQI) model using Machine Learning algorithms and techniques. The paper employs Machine Learning Algorithms such as Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Random Forest (RF) and Logistic Regression. The model can predict the most pollutant factors from real readings published daily by the Jordan Ministry of Environment (MoEnv) for the period from January 2017 to April 2019. Jordan has prioritized air quality problems by establishing detection and monitoring stations in 12 positions across the country to measure Air Quality (AQ). Pollutant concentrations recorded by MoEnv use fully forewarn official organizations and individuals of daily air quality in the atmosphere over time and beneficially used by health and climate studies organizations. The study has detected the most contaminated sites and determined the pollutant concentrations. These estimates will indicate the most influenced pollutants and their behavior in the pollution process for further recommendations and actions to effects cardiopulmonary patients, environmental and climate researches, as well as to vulnerable ecosystems.

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Journal: 9(9), September-2020

This paper proposes a new enhanced algorithm called modernised genetic algorithm for solving the travelling salesman problem (MGA-TSP). Recently, the most successful evolutionary algorithm used for TSP problem, is GA algorithm. The main obstacles for GA is building its initial population. Therefore, in this paper, three neighbourhood structures (inverse, insert, and swap) along with 2-opt is utilised to build strong initial population. Additionally, the main operators (i.e., crossover and mutation) of GA during the generation process are also enhanced for TSP. Therefore, powerful crossover operator called EAX is utilised in the proposed MGA-TSP to enhance its convergence. For validation purpose, we used TSP datasets, range from 150 to 33,810 cities. Initially, the impact of each neighbouring structure on the performance of MGA-TSP is studied. In conclusion, MGA-TSP achieved the best results. For comparative evaluation. MGA-TSP is able to outperform six comparative methods in almost all TSP instances used.

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Journal: 2019 Vol.11 No.3, pp.215 - 226