Currently, the size of biological databases has in creased significantly with the growing number of users and the rate of queries where some databases are of terabyte size.Hence, there is an increasing need to access databases at the fastest possible rate. Where biologists are concerned, the need is more of a means to fast, scalable and accuracy searching in biological databases. This may seem to be a simple task, given the speed of current available gigabytes processors. However, this is far from the truth as the growing number of data which are deposited into the database are ever increasing. Hence, searching the database becomes a difficult and time-consuming task. Here, the computer scientist can help to organize data in a way that allows biologists to quickly search existing information and to predict new entries. In this paper, a decision tree indexing method is presented. This method of indexing can effectively and rapidly retrieve all the similar proteins from a large database for a given protein query. A theoretical and conceptual frameworks is derived, based on published works using indexing techniques for different applications.

No abstract

No abstract

<span lang="EN-US">In this research, approaches to making e-learning accessible to students with impairments were studied based on the authors’ experience at Jordan’s Al-Zaytoonah University. The educational, organizational, and instructional concerns are underlined when analyzing the university’s experience in giving access to online content. Furthermore, these difficulties must be addressed in order to create the necessary organizational change to effectively solve accessibility concerns. This study looked into the e-learning issues that 56 university students with disabilities had reported. Students reported issues with: accessibility to websites and learning course management systems; accessibility to digital audio and video; time management in completing online tasks; trouble handling data during lectures; and a lack of appropriate adaptive strategies in online questionnaires. Students also noted technical issues with using e-learning, instructors’ communication with e-learning, and their treatment of all students equally, overlooking the necessity of considering the needs of students with impairments. In this study, we present the problems raised by students with disabilities and how the e-learning affects students’ outcomes in the e-learning experience. We also make recommendations based on the students’ realistic special-needs experience at Al-Zaytoonah University in Jordan during the COVID-19 pandemic to inspire decision-makers in educational institutions and those interested in this field.</span>

Like many countries, Jordan has resorted to lockdown in an attempt to contain the outbreak of Coronavirus (Covid-19). A set of precautions such as quarantines, isolations, and social distancing were taken in order to tackle its rapid spread of Covid-19. However, the authorities were facing a serious issue with enforcing quarantine instructions and social distancing among its people. In this paper, a social distancing mentoring system has been designed to alert the authorities if any of the citizens violated the quarantine instructions and to detect the crowds and measure their social distancing using an object tracking technique that works in real-time base. This system utilises the widespread surveillance cameras that already exist in public places and outside many residential buildings. To ensure the effectiveness of this approach, the system uses cameras deployed on the campus of Al-Zaytoonah University of Jordan. The results showed the efficiency of this system in tracking people and determining the distances between them in accordance with public safety instructions. This work is the first approach to handle the classification challenges for moving objects using a shared-memory model of multicore techniques. Keywords: Covid-19, Parallel computing, Risk management, Social distancing, Tracking system.