Njala University Research Repository

Njala University, a rural comprehensive public research university in Sierra Leone, is committed to providing the highest standards of excellence in higher education in Sierra Leone and beyond, fostering intellectual and personal development, and stimulating meaningful research and service to humankind. The University operates on two campuses, the Njala campus, the main campus, and the Bo campus located in Bo, and offers sub-degree, degree and postgraduate programmes in the following areas

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A Multivariate Biomarker for Parkinson’s Disease
(In the Proceedings of 12th Annual Research Day, 2014 - Pace University, 2015-05-15) Crocetti, Giancarlo; Coakley, Michael; Dressner, Phil; Kellum, Wanda; Lamin, Tamba
In this study, we executed a genomic analysis with the objective of selecting a set of genes (possibly small) that would help in the detection and classification of samples from patients affected by Parkinson Disease. We performed a complete data analysis and during the exploratory phase, we selected a list of differentially expressed genes. Despite their association with the diseased state, we could not use them as a biomarker tool. Therefore, our research was extended to include a multivariate analysis approach resulting in the identification and selection of a group of 20 genes that showed a clear potential in detecting and correctly classify Parkinson Disease samples even in the presence of other neurodegenerative disorders.
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Transforming telemedicine through big data analytics
(In the Proceedings of 12th Annual Research Day, 2014 - Pace University, 2015-05-15) Coakley, Michael; Crocetti, Giancarlo; Dressner, Phil; Kellum, Wanda; Lamin, Tamba
A look at how big data is transforming telemedicine to provide better care by tapping into a larger source of patient information. Telemedicine will have a profound impact on patient care, increase access and quality, and represent an opportunity to keep health care costs down. Data generated by smart devices will enable the real-time monitoring of chronic diseases, allowing optimal dosage of drugs and improve patient outcomes
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(Proceedings of 12th Annual Research Day, 2014 - Pace University, 2025-02-27) Coakley, Michael; Lukulay, Philip; Rogers, Ambrose T.; David, Emma; Sesay, Momodu
Energy has become an increasingly large financial and scaling burden for computing. With the increasing demand for and scale of Data-Intensive Scalable Computing (DISC), the costs of running large data centers are becoming dominated by power and cooling. In this thesis we propose to help reduce the energy consumed by large-scale computing by using a FAWN: A Fast Array of Wimpy Nodes. FAWN is an approach to building datacenters using low-cost, low-power hardware devices that are individually optimized for energy efficiency (performance/watt) rather than raw performance alone. FAWN nodes are individually resource-constrained, motivating the development of distributed systems software with efficient processing, low memory consumption, and careful use of flash storage. In this proposal, we investigate the applicability of FAWN to data-intensive workloads. First, we present FAWN-KV: a deep study into building a distributed key-value storage system on a FAWN prototype. We then present a broader classification and workload analysis showing when FAWN can be more energy-efficient, and under what conditions that wimpy nodes perform poorly. Based on our experiences building software for FAWN, we finish by presenting Storage Click: a software architecture for providing efficient processing of remote, small storage objects.