Binary GH Sequences for Multiparty Communication

This paper investigates cross correlation properties of sequences derived from GH sequences modulo p, where p is a prime number and presents comparison with cross correlation properties of pseudo noise sequences. For GH sequences modulo prime, a binary random sequence B(n) is constructed, based on whether the period is p-1 (or a divisor) or 2p+2 (or a divisor). We show that B(n) sequences have much less peak cross correlation compared to PN sequence fragments obtained from the same generator. Potential applications of these sequences to cryptography are sketched.Comment: 7 pages, 6 figure

AN APPROACH TO INVERSE MODELING THROUGH THE INTEGRATION OF ARTIFICIAL NEURAL NETWORKS AND GENETIC ALGORITHMS

A hybrid model integrating predictive capabilities of Artificial Neural Network (ANN) and optimization feature of Genetic Algorithm (GA) is developed for the purpose of inverse modeling. The proposed approach is applied to Superplastic forming of materials to predict the material properties which characterize the performance of a material. The study is carried out on two problems. For the first problem, ANN is trained to predict the strain rate sensitivity index m given the temperature and the strain rate. The performance of different gradient search methods used in training the ANN model is demonstrated. Similar approach is used for the second problem. The objective of which is to predict the input parameters, i.e. strain rate and temperature corresponding to a given flow stress value. An attempt to address one of the major drawbacks of ANN, which is the black box behavior of the model, is made by collecting information about the weights and biases used in training and formulating a mathematical expression. The results from the two problems are compared to the experimental data and validated. The results indicated proximity to the experimental data

SoTL as Sherwood Forest: A review of the SoTL Commons Conference 2014

A review of the SoTL Commons Conference 2014

Role of diffusion Weighted Imaging (DWI) in determining response to neoadjuvant chemoradiation in locally advanced carcinoma rectum

OBJECTIVES: To assess the role of DWI in predicting response to neoadjuvant chemoradiotherapy in patients with locally advanced carcinoma rectum (LARC) compared with T2W imaging. Secondarily, to evaluate the accuracy of tumour regression grade (TRG) assessed using MRI (T2W and DWI) in comparison with histopathological TRG. METHODS: A prospective analysis of 70 patients with LARC, who underwent neoadjuvant CRT and subsequent surgery was done. All patients underwent pre- and post-CRT T2W MR and DWI. The tumour volumes on T2W and DW images, difference in tumour volumes, pre and post-CRT ADC, difference in tumour ADC were measured. The TRG on T2W MRI and DWI were independently assessed. Histopathologic tumour regression grade was the standard of reference. The diagnostic accuracy of the tests in predicting complete response was compared using ROC analysis. The agreement between the MR tumour regression grades and histopathology was assessed using kappa statistic. RESULTS: The range of volumetric and ADC values in each TRG category were derived. The groups were subdivided into complete response (CR, n=13) and non-CR groups. Tumour volume reduction rate (TVRR) calculated on DWI and T2W MR were both useful in assessing complete response, with the accuracy of DWI being superior (AUC 0.92 for DWI vs 0.72 for T2W). The tumour ADC increase rate (TAIR) and absolute increase (ΔADC) though statistically significant as a predictor of response was inferior to tumour volumetry on DWI (AUC 0.7). Using a cut-off value for the tumour volume reduction rate of more than 94% on DWI, the sensitivity and specificity for predicting CR was 83.3% with NPV of 95.7%. There was fair agreement between the TRG based on MRI (76.4%, kappa 0.25, p <0.01) /DWI (74.6%, kappa 0.24, p <0.01) and histopathological TRG Pre- and post-CRT volumetry, ADC values when viewed independently were not reliable. CONCLUSION: The parameters found to be of significance in assessing response to neoadjuvant CRT are tumour volume reduction rate - TVRR on DWI and T2W, tumour ADC increase rate – TAIR and ΔADC. Among these, volumetry based on DWI was superior with high diagnostic accuracy in predicting complete response. TVRR based on T2W and changes in ADC values had similar diagnostic accuracies. Tumour regression grade assessed using T2W MRI and DWI are also useful as prognostic markers for disease recurrence and overall survival

The representation of the visual field on the sub-cortical centers of the cat and rabbit

In the visual system the primary problem has been the identification of the visual pathway - the fiber systems along which the impulses arising in the eyes pass to the various subcortical levels and finally to the cortex - their precise localization, boundaries, and the extent of the terminal areas of the pathway. The second problem has been to determine whether, and to what extent, the original spatial and dimensional relationships present in visual space and in the retina are preserved in the pathways and centers, and if they are, how and where the various distinct areas of the retina, i.e. the fovea, the extra-foveal peripheral quadrants, the horizontal and vertical meridians, were represented in the various levels of the visual pathway