Air pollution is one of the most serious hazards to humans′ health nowadays, it is an invisible killer that takes many human lives every year. There are many pollutants existing in the atmosphere today, ozone being one of the most threatening pollutants. It can cause serious health damage such as wheezing, asthma, inflammation, and early mortality rates. Although air pollution could be forecasted using chemical and physical models, machine learning techniques showed promising results in this area, especially artificial neural networks. Despite its importance, there has not been any research on predicting ground-level ozone in Jordan. In this paper, we build a model for predicting ozone concentration for the next day in Amman, Jordan using a mixture of meteorological and seasonal variables of the previous day. We compare a multi-layer perceptron neural network (MLP), support vector regression (SVR), decision tree regression (DTR), and extreme gradient boosting (XGBoost) algorithms. We also explore the effect of applying various smoothing filters on the time-series data such as moving average, Holt-Winters smoothing and Savitzky-Golay filters. We find that MLP outperformed the other algorithms and that using Savitzky-Golay improved the results by 50% for coefficient of determination (R 2) and 80% for root mean square error (RMSE) and mean absolute error (MAE). Another point we focus on is the variables required to predict ozone concentration. In order to reduce the time required for prediction, we perform feature selection which greatly reduces the time by 91% as well as shrinking the number of features required for prediction to the previous day values of ozone, humidity, and temperature. The final model scored 98.653% for R 2 , 1.016 ppb for RMSE and 0.800 ppb for MAE.
Today, there are many educational institutions and organizations around the world, especially the universities have adopted the e-learning and learning management system concepts because they want to enhance and support their educational process since the number of students who would like to attend universities and educational institutions is increasing. This paper has many objectives, the first one is comparing between different types of most popular learning management system (LMS) software such as Moodle and Blackboard based on their uniqueness features. The second objective is presenting the learning management systems and their benefits in e-learning. Finally, this research paper presents a proposed model, which consists of six independent variables (application and integration, communication, assessment, content, cost, and security), and one dependent variable which is e-learning success. A questionnaire has been developed and distributed to 450 respondents, and then data was collected from 418 valid questionnaires. The result showed that there is a statistically significant impact of learning management system major characteristics on e-learning success.
Abstract-Genetic Algorithms (GAs) is a type of local search that mimics biological evolution by taking a population of string, which encodes possible solutions and combines them based on fitness values to produce individuals that are fitter than others. One of the most important operators in Genetic Algorithm is the selection operator. A new selection operator has been proposed in this paper, which is called Clustering Selection Method (CSM). The proposed method was implemented and tested on the traveling salesman problem. The proposed CSM was tested and compared with other selection methods, such as random selection, roulette wheel selection and tournament selection methods. The results showed that the CSM has the best results since it reached the optimal path with only 8840 iterations and with minimum distance which was 79.7234 when the system has been applied for solving Traveling Salesman Problem (TSP) of 100 cities.
The aim of this research is to study the acceptance of university students to use Microsoft Teams e-Learning system and their intention to use it as a Learning Management System (LMS) for education during the COVID-19 pandemic in Jordan. An ex-tended Technology Acceptance Model (TAM) with a blend of external factors that are used together for the first time was developed and used for the purpose of this study. TAM was used because of its wide use and success during the past few years for evaluating the influence of different factors affecting the acceptance and intention to use e-Learning platforms within educational institutes. However, all the studies were examining the variables and factors affecting the behavioral intention and acceptance to use LMSs when normal and conventional classroom study is available. In this research, seven external variables, in addition to the four TAM variables, were introduced in a model including one external variable, Internet Connectivity (IC), used for the first time in the field of education. A model is constructed by extending TAM with the introduced external variables, hypotheses are constructed and a questionnaire for 396 students at two universities in Jordan is conducted. Reliability, confirmatory factor, model fit, and hypothesized structural model analyses are presented. Results show that all the variables tested affect, either directly or indirectly, the acceptance and intention to use MS Teams during the pandemic. 21 hypotheses were tested between the constructs and found significant except the relations between (Social Norm - Perceived Usefulness) and (Technical Support - Perceived Usefulness).
Although E-business and E-commerce have become essential in our daily lives, the use of E-business in the Middle East / Jordan is still limited due to many factors.This study has three objectives; first, it determines whether the government in Jordan supports E-business; second, it determines whether people in Jordan are aware of the concept of E-business and its use; third, whether introducing a proposed Governmental Consumer Agency will help to expand and grow E-business in Jordan.According to the result of the study (740) respondents indicated that the government in Jordan is not supporting the development of E-business and does not play any roles in encouraging the E-business expansion and it has to pay attention to the concept of E-business and support its development completely. Another indication was that the people in Jordan are aware of E-business.Finally the establishment of a Jordanian Governmental Consumer Agency would have a significant impact on expanding the use of E-business and on encouraging people in Jordan to go online.
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