Multiclass Core Vector Machine

Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these approaches to handle large data sets still needs much of exploration. Core Vector Machine(CVM) is a technique for scaling up a two class SVM to handle large data sets. In this paper we propose a Multiclass Core Vector Machine(MCVM). Here we formulate the multiclass SVM problem as a Quadratic Programming(QP) problem defining an SVM with vector valued output. This QP problem is then solved using the CVM technique to achieve scalability to handle large data sets. Experiments done with several large synthetic and real world data sets show that the proposed MCVM technique gives good generalization performance as that of SVM at a much lesser computational expense. Further, it is observed that MCVM scales well with the size of the data set.

Two-level Mapping Based Cache Index Selection for Packet Forwarding Engines

Packet forwarding is a memory-intensive application requiring multiple accesses through a trie structure. The efficiency of a cache for this application critically depends on the placement function to reduce conflict misses. Traditional placement functions use a one-level mapping that naively partitions trie-nodes into cache sets. However, as a significant percentage of trie nodes are not useful, these schemes suffer from a non-uniform distribution of useful nodes to sets. This in turn results in increased conflict misses. Newer organizations such as variable associativity caches achieve flexibility in placement at the expense of increased hit-latency. This makes them unsuitable for L1 caches.We propose a novel two-level mapping framework that retains the hit-latency of one-level mapping yet incurs fewer conflict misses. This is achieved by introducing a secondlevel mapping which reorganizes the nodes in the naive initial partitions into refined partitions with near-uniform distribution of nodes. Further as this remapping is accomplished by simply adapting the index bits to a given routing table the hit-latency is not affected. We propose three new schemes which result in up to 16% reduction in the number of misses and 13% speedup in memory access time. In comparison, an XOR-based placement scheme known to perform extremely well for general purpose architectures, can obtain up to 2% speedup in memory access time.

Experimental study of a small partial admission axial turbine with low aspect ratio blade

Experimental study of a small partial admission axial turbine with low aspect ratio blade has been done. Tests were also performed with full admission stator replacing the partial one for the same rotor to assess the losses occurring due to partial admission. Further tests were conducted with stator admission area split into two and three sectors to study the effects of multiple admission sectors. The method of Ainley and Mathieson with suitable correction for aspect ratio in secondary losses, as proposed by Kacker and Okapuu, gives a good estimate of the efficiency. Estimates of partial admission losses are made and compared with experimentally observed values. The Suter and Traupel correlations for partial admission losses yielded reasonably accurate estimates of efficiency even for small turbines though limited to the region of design u/c(is). Stenning's original concept of expansion losses in a single sector is extended to include multiple sectors of opening. The computed efficiency debit due to each additional sector opened is compared with test values. The agreement is observed to be good. This verified Stenning's original concept of expansion losses. When the expression developed on this extended concept is modified by a correction factor, the prediction of partial admission efficiencies is nearly as good as that of Suter and Traupel. Further, performance benefits accrue if the turbine is configured with increased aspect ratio at the expense of reduced partial admission.

Microstructure-Wear Resistance Correlation and Wear Mechanisms of Spark Plasma Sintered Cu-Pb Nanocomposites

The dispersion of a softer phase in a metallic matrix reduces the coefficient of friction (COF), often at the expense of an increased wear rate at the tribological contact. To address this issue, unlubricated fretting wear tests were performed on spark plasma sintered Cu-Pb nanocomposites against bearing steel. The sintering temperature and the Pb content as well as the fretting parameters were judiciously selected and varied to investigate the role of microstructure (grain size, second-phase content) on the wear resistance properties of Cu-Pb nanocomposites. A combination of the lowest wear rate (similar to 1.5 x 10(-6) mm(3)/Nm) and a modest COF (similar to 0.4) was achieved for Cu-15 wt pct Pb nanocomposites. The lower wear rate of Cu-Pb nanocomposites with respect to unreinforced Cu is attributed to high hardness (similar to 2 to 3.5 GPa) of the matrix, Cu2O/Fe2O3-rich oxide layer formation at tribological interface, and exuding of softer Pb particles. The wear properties are discussed in reference to the characteristics of transfer layer on worn surface as well as subsurface damage probed using focused ion beam microscopy. Interestingly, the flash temperature has been found to have insignificant effect on the observed oxidative wear, and alternative mechanisms are proposed. Importantly, the wear resistance properties of the nanocomposites reveal a weak Hall-Petch-like relationship with grain size of nanocrystalline Cu. (C) The Minerals, Metals & Materials Society and ASM International 2013

First and second law thermodynamic analysis of air and oxy-steam biomass gasification

Gasification is an energy transformation process in which solid fuel undergoes thermochemical conversion to produce gaseous fuel, and the two most important criteria involved in such process to evaluate the performance, economics and sustainability of the technology are: the total available energy (exergy) and the energy conserved (energy efficiency). Current study focuses on the energy and exergy analysis of the oxy-steam gasification and comparing with air gasification to optimize the H-2 yield, efficiency and syngas energy density. Casuarina wood is used as a fuel, and mixture of oxygen and steam in different proportion and amount is used as a gasifying media. The results are analysed with respect to varying equivalence ratio and steam to biomass ratio (SBR). Elemental mass balance technique is employed to ensure the validity of results. First and second law thermodynamic analysis is used towards time evaluation of energy and exergy analysis. Different component of energy input and output has been studied carefully to understand the influence of varying SBR on the availability of energy and irreversibility in the system to minimize the losses with change in input parameters for optimum performance. The energy and exergy losses (irreversibility) for oxy-steam gasification system are compared with the results of air gasification, and losses are found to be lower in oxy-steam thermal conversion; which has been argued and reasoned due to the presence of N-2 in the air-gasification. The maximum exergy efficiency of 85% with energy efficiency of 82% is achieved at SBR of 0.75 on the molar basis. It has been observed that increase in SBR results in lower exergy and energy efficiency, and it is argued to be due to the high energy input in steam generation and subsequent losses in the form of physical exergy of steam in the product gas, which alone accounts for over 18% in exergy input and 8.5% in exergy of product gas at SBR of 2.7. Carbon boundary point (CBP), is identified at the SBR of 1.5, and water gas shift (WGS) reaction plays a crucial role in H-2 enrichment after carbon boundary point (CBP) is reached. Effects of SBR and CBP on the H-2/CO ratio is analysed and discussed from the perspective of energy as well as the reaction chemistry. Energy density of syngas and energy efficiency is favoured at lower SBR but higher SBR favours H-2 rich gas at the expense of efficiency. Copyright (C) 2014, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.