Joint congestion and contention avoidance in a scalable QoS-aware opportunistic routing in wireless ad-hoc networks.

Opportunistic routing (OR) can greatly increase transmission reliability and network throughput in wireless ad-hoc networks by taking advantage of the broadcast nature of the wireless medium. However, network congestion is a barrier in the way of OR's performance improvement, and network congestion control is a challenge in OR algorithms, because only the pure physical channel conditions of the links are considered in forwarding decisions. This paper proposes a new method to control network congestion in OR, considering three types of parameters, namely, the backlogged traffic, the traffic flows' Quality of Service (QoS) level, and the channel occupancy rate. Simulation results show that the proposed algorithm outperforms the state-of-the-art algorithms in the context of OR congestion control in terms of average throughput, end-to-end delay, and Packet Delivery Ratio (PDR). Due to the higher PDR at different traffic loads and different node densities, it can be concluded that the proposed algorithm also improves network scalability, which is very desirable given the recent changes in wireless networks.

On fractality of functional near-infrared spectroscopy signals: analysis and applications.

Significance: The human brain is a highly complex system with nonlinear, dynamic behavior. A majority of brain imaging studies employing functional near-infrared spectroscopy (fNIRS), however, have considered only the spatial domain and have ignored the temporal properties of fNIRS recordings. Methods capable of revealing nonlinearities in fNIRS recordings can provide new insights about how the brain functions. Aim: The temporal characteristics of fNIRS signals are explored by comprehensively investigating their fractal properties. Approach: Fractality of fNIRS signals is analyzed using scaled windowed variance (SWV), as well as using visibility graph (VG), a method which converts a given time series into a graph. Additionally, the fractality of fNIRS signals obtained under resting-state and task-based conditions is compared, and the application of fractality in differentiating brain states is demonstrated for the first time via various classification approaches. Results: Results from SWV analysis show the existence of high fractality in fNIRS recordings. It is shown that differences in the temporal characteristics of fNIRS signals related to task-based and resting-state conditions can be revealed via the VGs constructed for each case. Conclusions: fNIRS recordings, regardless of the experimental conditions, exhibit high fractality. Furthermore, VG-based metrics can be employed to differentiate rest and task-execution brain states.

Building a more diverse biomedical engineering workforce: Biomedical engineering at the university of the district of Columbia, a historically black college & university.

Biomedical Engineering (BME) is a new, multidisciplinary, and rapidly growing field, however, the BME Workforce suffers from limited ethnic and gender diversity. Despite the demand and growth of this new field due to its public health importance, only 4 out of the 107 Historically Black Colleges and Universities (HBCUs) nationwide offers a Bachelor's of Science (B.S.) in Bio-Engineering related fields. In order to contribute to a growing BME Workforce, HBCUs need to react and offer more degree-programs relevant to BME. At the University of the District of Columbia (UDC), an HBCU and the District's only public institution for higher learning, we have recently established a new, degree program: Bachelor of Science in Biomedical Engineering (B.S. in BME) full-board approved in Fall 2014, with program activities initiated in Fall 2015. The educational goal of this program is to enhance the quality and diversity of the BME Workforce via student professional development, new and relevant BME courses, and BME scholarly activities (e.g., guest lectures and journal club sessions), ultimately to increase the number of ethnic minorities pursuing careers and degrees in BME. Through our program activities, we are aiming to meet the nation's demand to contribute to a diverse BME workforce, directed towards solving problems in human health. A secondary, but related goal, is to increase the diversity of STEM-related fields. This paper summarizes our initial, but encouraging, BME activity-related findings. However, this study will be longitudinal (on a multiple year time period) to observe the true outcomes of our initiative.