Reem Alattas

Analyzing Modular Robotic Systems

This paper surveys modular robot systems, which consist of multiple modules and aim to create versatile, robust, and low cost systems. The modularity allows these robots to self-assemble, self-reconfigure, self-repair, and self-replicate. Therefore, the surveyed research covered the previous characteristics along with evolutionary robotics and 3D printed robots. These fields are interdisciplinary, so we organize the implemented systems according to the main feature in each one. The primary motivation for this is to categorize modular robots according to their main function and to discover the similarities and differences of implementing each system.

A comparative study of brain volume changes in Alzheimer's disease using MRI scans

Alzheimers (AD) is the most common form of dementia that negatively affects memory, thinking, behavior, and intellectual abilities in ones daily life. The risk of AD increases with age 65 and older although it may appear in people who are in their 40s or 50s. AD has no current cure. There are many ongoing research studies to understanding and treating this disease better. AD, a slowly progressive brain disease, begins well before clinical symptoms emerge. A diagnosis of AD is usually made by primary care physicians based on patients medical and family history, psychiatric history, and history of cognitive and behavioral changes. Magnetic resonance imaging (MRI) is the most common imaging modality to use to identify brain changes. In this study, MRI scans of 10 individuals without AD and 10 individuals with AD are compared and analyzed based on brain volume. Measurements included the occipital lobe and hippocampal.

Detecting and Minimizing Bad Posture Using Postuino among Engineering Students

To understand how good posture minimizes computer related injurys pain, we developed Postuino. A device that warns the computer users if they are leaning too close towards computer screen. Postuino has an accompanying web application that visualizes the collected data and displays a chart to simplify comparing between straight time and slouch time. Also, the app suggests taking frequent breaks to minimize the risk of injuries and to increase productivity. Then, we designed an experiment with different factors to evaluate the efficiency of Postuino. In our study, 24 subjects first use the computer for 3 hours after disabling Postuinos alert system. Afterwards, they use the computer again for two more 3 hour phases after enabling the alert system. We collected data, analyzed it, and presented the results in this paper.