Acceleration and visualization of Dynamic Network Optimization

With the emerging prevalence of smart phones and 4G LTE networks, the demand for faster-better-cheaper mobile services anytime and anywhere is ever growing. The Dynamic Network Optimization (DNO) concept emerged as a solution that optimally and continuously tunes the network settings, in response to varying network conditions and subscriber needs. Yet, the DNO realization is still at infancy, largely hindered by the bottleneck of the lengthy optimization runtime. This paper presents the design and prototype of a novel cloud based parallel solution that further enhances the scalability of our prior work on various parallel solutions that accelerate network optimization algorithms. The solution aims to satisfy the high performance required by DNO, preliminarily on a sub-hourly basis. The paper subsequently visualizes a design and a full cycle of a DNO system. A set of potential solutions to large network and real-time DNO are also proposed. Overall, this work creates a breakthrough towards the realization of DNO.

Body fat MRS

The increasing levels of obesity, and its associated comorbidities, have prompted a reassessment of the techniques used for assessing body fat, including content, distribution, and composition. Magnetic resonance spectroscopy (MRS) is one among the many invaluable in vivo tools available today to evaluate the role of body fat in health and disease. However, although MRS has become a powerful technique for assessing ectopic fat in vivo, it has had limited use in other areas of research associated with body fat. MRS has found some success as a fast method to determine whole body adiposity in rodent models of disease, as well as a noninvasive method of obtaining an index of the overall composition of body fat in human subjects. Its more significant use has been in the understanding of bone marrow fat content, where important advances have been made, especially in longitudinal studies. In conclusion, in the area of body fat, MRS continues to be an adjunct technique to more precise and versatile MRI methods.