Mobility is essential for individuals with physical disabilities, and wheelchairs significantly enhance their quality of life. Recent advancements focus on developing sophisticated control systems for effective and efficient interaction. This study evaluates the usability and performance of three wheelchair control modes manual, automatic, and voice controlled using a virtual reality (VR) simulation tool. VR provides a controlled and repeatable environment to assess navigation performance and motion sickness across three scenarios: supermarket, museum, and city. Twenty participants completed nine tests each, resulting in 180 trials. Findings revealed significant differences in navigation efficiency, distance, and collision rates across control modes and scenarios. Automatic control consistently achieved faster navigation times and fewer collisions, particularly in the supermarket. Manual control offered precision but required greater user effort. Voice control, while intuitive, resulted in longer distances traveled and higher collision rates in complex scenarios like the city. Motion sickness levels varied across scenarios, with higher discomfort reported in the city during voice and automatic control. Participant feedback, gathered via a Likert scale questionnaire, highlighted the potential of VR simulation for evaluating user comfort and performance. This research underscores the advantages of VR-based testing for rapid prototyping and user-centered design, offering valuable insights into improving wheelchair control systems. Future work will explore adaptive algorithms to enhance usability and accessibility in real world applications.

DNA fragment assembly represents an important challenge to the development of efficient and practical algorithms due to the large number of elements to be assembled. In this study, we present some graph theoretical linear time algorithms to solve the problem. To achieve linear time complexity, a heap with constant time operations was developed, for the special case where the edge weights are integers and do not depend on the problem size. The experiments presented show that modified classical graph theoretical algorithms can solve the DNA fragment assembly problem efficiently.