An interference-aware virtual clustering paradigm for resource management in cognitive femtocell networks

Femtocells represent a promising alternative solution for high quality wireless access in indoor scenarios where conventional cellular system coverage can be poor. They are randomly deployed by the end user, so only post deployment network planning is possible. Furthermore, this uncoordinated deployment creates severe interference to co-located femtocells, especially in dense deployments. This paper presents a new architecture using a generalised virtual cluster femtocell (GVCF) paradigm, which groups together FAP into logical clusters. It guarantees severely interfering and overlapping femtocells are assigned to different clusters. Since each cluster operates on different band of frequencies, the corresponding virtual cluster controller only has to manage its own FAPs, so the overall system complexity is low. The performance of the GVCF algorithm is analysed from both a resource availability and cluster number perspective. Simulation results conclusively corroborate the superior performance of the GVCF model in interference mitigation, particularly in high density FAP scenarios

Stability of the pentaquark in a naive string model

The pentaquark is studied in a simple model of confinement where the quarks and the antiquark are linked by flux tubes of minimal cumulated length, and the Coulomb-like interaction, the spin-dependent terms and the antisymmetrization constraints are neglected.. The ground-state is found to be stable against spontaneous dissociation into a meson and a baryon, both in the case of five equal-mass constituents and for a static quark or antiquark surrounded by four equal masses.Comment: 8 pages, 2 figures, minor corrections, references added, to appear in Phys. Rev.

Accurate monitoring and fault detection in wind measuring devices through wireless sensor networks

Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models

Pooling serum samples may lead to loss of potential biomarkers in SELDI-ToF MS proteomic profiling

BACKGROUND: High throughput proteomic technology offers promise for the detection of disease biomarkers and proteomic signature patterns but biomarker discovery studies can be limited by cost factors when large sample size numbers are required. Pooling sera or plasma samples from disease cases potentially offers a solution to cost implications by reducing the standard errors of mass to charge values. Surface enhanced laser desorption/ionization time of flight (SELDI-ToF) mass spectra obtained from individual and pooled sera from invasive aspergillosis cases and controls were compared. RESULTS: Pooling resulted in 50% loss of peak clusters detected in individual samples. Overall, loss was greatest for low intensity clusters. Peak intensities and case:control intensity ratios, among clusters not lost, demonstrated good reproducibility. CONCLUSION: Pooling sera results in significant potential biomarker loss when using SELDI-ToF MS