INVESTIGATION OF INTRAOCULAR PRESSURE AS A PREDICTOR OF TRAUMATIC EYE INJURIES

Eye injuries are a large societal problem in both the military and civilian sectors. Eye injury rates are increasing in recent military conflicts, and there are over 1.9 million eye injuries in the United States civilian sector annually. In order to develop a better understanding of eye injury risk, several previous studies have developed eye injury criteria based on projectile characteristics. While these injury criteria have been used to estimate eye injury potential of impact scenarios, they require that the mass, size and velocity of the projectile are known. It is desirable to develop a method to assess the severity of an eye impact in environments where it would be difficult or impossible to determine these projectile characteristics. The current study presents a measurement technique for monitoring intraocular pressure of the eye under impactloading. Through experimental tests with a custom pressure chamber, a subminiature pressure transducer was validated to be thermally stable and suitable for testing in an impact environment.Once validated, the transducer was utilized intraocularly, inserted through the optic nerve, to measure the pressure of the eye during blunt-projectile impacts. A total of 150 impact tests were performed using projectiles ranging from 3.2 mm to 17.5 mm in diameter. Investigation of the relationship between projectile energy and intraocular pressure lead to the identification of at least two distinct trends. Intraocular pressure and normalized energy measurements indicated a different response for penetrating-type globe rupture injuries with smaller diameter (d < 1 cm)projectiles, and blunt-type globe rupture injuries with larger diameter (d > 1 cm) projectiles. Furthermore, regression analysis indicates that relationships exist between intraocular pressureand projectile energy that may allow quantification of eye injury risk based on pressure data, and also that intraocular pressure measurements of impact may lead to a better understanding of thetransition between penetrating and blunt globe rupture injury mechanisms.

Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing

We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.

Performance Modeling Of Reconfigurable Distributed Systems Based On The Opensparc Fpga Board And The Sirc Communication Framewor

This thesis explores system performance for reconfigurable distributed systems and provides an analytical model for determining throughput of theoretical systems based on the OpenSPARC FPGA Board and the SIRC Communication Framework. This model was developed by studying a small set of variables that together determine a system¿s throughput. The importance of this model is in assisting system designers to make decisions as to whether or not to commit to designing a reconfigurable distributed system based on the estimated performance and hardware costs. Because custom hardware design and distributed system design are both time consuming and costly, it is important for designers to make decisions regarding system feasibility early in the development cycle. Based on experimental data the model presented in this paper shows a close fit with less than 10% experimental error on average. The model is limited to a certain range of problems, but it can still be used given those limitations and also provides a foundation for further development of modeling reconfigurable distributed systems.