Coinage Metals in the Nanometer Length Scale

Cetylpyridinium chloride (CPC)-stabilized gold organosol in toluene has been prepared by using a two-phase (water-toluene) extraction of AuCl₄^- followed by its reduction with sodium borohydride in the presence of the surfactant, CPC. The surfactant-stabilized gold nanoparticles were exploited to examine their optical properties when exposed to various solvent systems by measuring the changes in the localized surface plasmon resonance (LSPR) spectrum.     

Incorporating Ancestors' Influence in Genetic Algorithms

A new criterion of fitness evaluation for Genetic Algorithms is introduced where the fitness value of an individual is determined by considering its own fitness as well as those of its ancestors. Some guidelines for selecting the weighting coefficients for quantifying the importance to be given to the fitness of the individual and its ancestors are provided. This is done both heuristically and automatically under fixed and adaptive frameworks. The Schema Theorem corresponding to the proposed concept is derived. The effectiveness of this new methodology is demonstrated extensively on the problems of optimizing complex functions including a noisy one and selecting optimal neural network parameters.     

Finding short structural motifs for re-construction of proteins 3D structure

With a view to find useful building blocks (short structural motifs) for reconstruction of 3D structure of proteins, we propose a modified neural gas learning algorithm that we call structural neural gas (SNG) algorithm. The SNG is applied on a benchmark protein data set and its performance is compared with a well known algorithm from the literature (two stage clustering algorithm (TSCA)). The SNG algorithm is found to generate better building blocks compared to TSCA. We have also compared the performance of SNG algorithm with that of a recently reported Incremental Structural Mountain Clustering Method (ISMCM). In general, ISMCM is found to use more building blocks to yield results comparable to that of SNG algorithm. We demonstrate the superiority of SNG over TSCA both in terms of local-fit and global-fit errors using fragments of length five, six, and seven. We also use a graphical means for comparison of the performance of the two algorithms.     

A Markov Decision Process based flow assignment framework for heterogeneous network access

We consider a scenario where devices with multiple networking capabilities access networks with heterogeneous characteristics. In such a setting, we address the problem of efficient utilization of multiple access networks by devices via optimal assignment of traffic flows with given utilities to different networks. We develop and analyze a device middleware functionality that monitors network characteristics and employs a Markov Decision Process (MDP) based control scheme that in conjunction with stochastic characterization of the available bit rate and delay of the networks generates an optimal policy for allocation of flows to different networks. The optimal policy maximizes, under available bit rate and delay constraints on the access networks, a discounted reward which is a function of the flow utilities. The flow assignment policy is periodically updated and is consulted by the flows to dynamically perform network selection during their lifetimes. We perform measurement tests to collect traces of available bit rate and delay characteristics on Ethernet and WLAN networks on a work day in a corporate work environment. We implement our flow assignment framework in ns-2 and simulate the system performance for a set of elastic video-like flows using the collected traces. We demonstrate that the MDP based flow assignment policy leads to significant enhancement in the QoS provisioning (higher rate allocation, lower packet delays and packet loss rates) for the flows and better access network utilization, as compared to policies that allocate flows to different networks using greedy approaches or heuristics like average available bit rate on the networks.     

The effect of surface recombination on the frequency-dependentcharacteristics of an ion-implanted GaAs OPFET

The effect of modulation frequency and surface recombination on the characteristics of an ion-implanted GaAs OPFET is determined analytically. The drain-source current is found to decrease with the increase in both modulation frequency and trap center density. The current changes significantly with the trap center density only when the latter is greater than 10²⁰/m². The threshold voltage does not change appreciably with the modulation frequency as in a silicon OPFET. However, the increased in the trap center density causes V_T to increase in the enhancement device and decrease in the depletion device. Further, V_T increases under the normally ON condition and decreases under the normally OFF condition with an increase in the photon absorption coefficient in GaAs. Some anomalous behavior is observed for higher values of the absorption coefficient     

Optimal actuation of micro-cantilevers by laser radiation pressure

Singly-clamped cantilevers actuated by optical radiation pressure exerted by a laser are analysed. An expression for optimum point of actuation giving the maximum amount of deflection is obtained.