Providing QoS in a cognitive radio network

We consider the problem of wireless channel allocation (whenever the channels are free) to multiple cognitive radio users in a Cognitive Radio Network (CRN) so as to satisfy their Quality of Service (QoS) requirements efficiently. The CRN base station may not know the channel states of all the users. The multiple channels are available at random times. In this setup Opportunistic Splitting can be an attractive solution. A disadvantage of this algorithm is that it requires the metrics of all users to be an independent, identically distributed sequence. However we use a recently generalized version of this algorithm in which the optimal parameters are learnt on-line through stochastic approximation and metrics can be Markov. We provide scheduling algorithms which maximize weighted-sum system throughput or are throughput or delay optimal. We also consider the scenario when some traffic streams are delay sensitive.

Numerical and experimental investigation and optimization of an open wheeled race car cooling air duct

In this study the cooling performance due to air flow and aerodynamics of the Formula Student open wheeled race car has been investigated and optimized with the help of CFD simulations and experimental validation. The race car in context previously suffered from overheating problems. Flow analysis was carried out based on the detailed race car 3D model (NITK Racing 2012 formula student race car). Wind tunnel experiments were carried out on the same. The results obtained from the computer simulations are compared with experimental results obtained from wind tunnel testing of the full car. Through this study it was possible to locate the problem areas and hence choose the best configuration for the cooling duct. The CFD analysis helped in calculating the mass flow rate, pressure and velocity distribution for different velocities of the car which is then used to determine the heat dissipated by the radiator. Area of flow separation could be visualized and made sure smooth airflow into the radiator core area. This significantly increased the cooling performance of the car with reduction in drag.

A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.

Delamination Tolerance in Composites under Fatigue Loading

Delamination is one of the most commonly occurring defects in laminated composite structures. Under operating fatigue loads on the laminate this delamination could grow and totally delaminate certain number of layers from the base laminate. This will result in loss of both compressive residual strength and buckling margins available. In this paper, geometrically non-linear analysis and evaluation of Strain Energy Release Rates using MVCCI technique is presented. The problems of multiple delamination, effect of temperature exposure and delamination from pin loaded holes are addressed. Numerical results are presented to draw certain inferences of importance to design of high technology composite structures such as aircraft wing.