LCME Planning and Self-Study Materials

Cope of the LCME's planning and self-study materials. Includes information on the LCME accreditation process and policies, as well as an overview of the LCME as an an organization.

Wireless Sensor Network Deployment

Wireless Sensor Networks (WSNs) are widely used for various civilian and military applications, and thus have attracted significant interest in recent years. This work investigates the important problem of optimal deployment of WSNs in terms of coverage and energy consumption. Five deployment algorithms are developed for maximal sensing range and minimal energy consumption in order to provide optimal sensing coverage and maximum lifetime. Also, all developed algorithms include self-healing capabilities in order to restore the operation of WSNs after a number of nodes have become inoperative. Two centralized optimization algorithms are developed, one based on Genetic Algorithms (GAs) and one based on Particle Swarm Optimization (PSO). Both optimization algorithms use powerful central nodes to calculate and obtain the global optimum outcomes. The GA is used to determine the optimal tradeoff between network coverage and overall distance travelled by fixed range sensors. The PSO algorithm is used to ensure 100% network coverage and minimize the energy consumed by mobile and range-adjustable sensors. Up to 30% - 90% energy savings can be provided in different scenarios by using the developed optimization algorithms thereby extending the lifetime of the sensor by 1.4 to 10 times. Three distributed optimization algorithms are also developed to relocate the sensors and optimize the coverage of networks with more stringent design and cost constraints. Each algorithm is cooperatively executed by all sensors to achieve better coverage. Two of our algorithms use the relative positions between sensors to optimize the coverage and energy savings. They provide 20% to 25% more energy savings than existing solutions. Our third algorithm is developed for networks without self-localization capabilities and supports the optimal deployment of such networks without requiring the use of expensive geolocation hardware or energy consuming localization algorithms. This is important for indoor monitoring applications since current localization algorithms cannot provide good accuracy for sensor relocation algorithms in such indoor environments. Also, no sensor redeployment algorithms, which can operate without self-localization systems, developed before our work.

Institutional Self study for the Liaison Committee on Medical Education

Draft of the College of Medicine's Institutional Self-Study for the LCME. Includes an overview of the College of Medicine's history, development, and vision, as well as details regarding the organization of the college, educational programs and resources, and future goals.

Perceived Stress and Self‑rated Health of Haitian and African Americans with and without Type 2 Diabetes

Background: Blacks have a higher incidence of diabetes and its related complications. Self-rated health (SRH) and perceived stress indicators are associated with chronic diseases. The aim of this study was to examine the associations between SRH, perceived stress and diabetes status among two Black ethnicities. Materials and Methods: The cross-sectional study included 258 Haitian Americans and 249 African Americans with (n = 240) and without type 2 diabetes (n = 267) (N = 507). Recruitment was performed by community outreach. Results: Haitian-Americans were less likely to report ‘fair to poor’ health as compared to African Americans [OR=0.58 (95% CI: 0.35, 0.95), P = 0.032]; yet, Haitian Americans had greater perceived stress than African Americans (P = 0.002). Having diabetes was associated with ‘fair to poor’ SRH [OR=3.14 (95% CI: 2.09, 4.72),P < 0.001] but not perceived stress (P = 0.072). Haitian-Americans (P = 0.023), females (P = 0.003) and those participants having ‘poor or fair’ SRH (P < 0.001) were positively associated with perceived stress (Nagelkerke R2=0.151). Conclusion: Perceived stress associated with ‘poor or fair’ SRH suggests that screening for perceived stress should be considered part of routine medical care; albeit, further studies are required to confirm our results. The findings support the need for treatment plans that are patient-centered and culturally relevant and that address psychosocial issues.