High extinction, broadband polarisers using long-period fibre gratings in few-mode fibres

Long-period fibre gratings in specially designed birefringent few-mode fibres are used to demonstrate spectrally flat polarisers with bandwidths of 10 nm and polarisation extinction levels of 20 dB. This is enabled by the special dispersive properties of few-mode fibres, yielding fibre polarisers with performance approaching that of bulk-optic devices.     

Noisy recurrent neural networks: the continuous-time case

The classical stochastic analog of the deterministic linear system in engineering is the linear system driven by white noise. As the promise of artificial neural networks in modeling nonlinear systems continues to grow, the need for a stochastic analog with quantitative foundations for analysis and synthesis will increase. This paper presents recent work in this direction, examining recurrent neural nets (RNN driven by white noise. We examine the effect of noise on the typical continuous-time RNN model. First, we perform qualitative analysis establishing uniform boundedness of moments of the neuron states over time. To enable practical application, however, it is necessary to relate these properties to useful measures that can be estimated. We thus subsequently derive bias and variance measures for the noisy RNN with respect to the corresponding deterministic RNN. This has significant practical implications, since net design is nonminimal in the sense that several nets can solve the same problem. The results allow the user to evaluate given RNN for noise performance. The designer can use these results to constrain the design space so that the design satisfies performance specifications whenever possible. An example is provided using the measures derived in this paper to predetermine the best among several RNN designs for a given problem.     

Favorable influence of ssDNA-functionalized SWCNT on the navigation pattern of C. elegans

Microsystem Technologies - Single-Walled Carbon Nanotubes (SWCNTs) are widely used as potential carriers in drug delivery systems. The objective of this work was to observe the effects of pristine,...     

Evaluation of wear of turning carbide inserts using neural networks

Recent trends, being towards mostly unmanned automated machining systems and consistent system operations, need reliable on-line monitoring processes. A proper on-line cutting tool condition monitoring system is essential for deciding when to change the tool. Many methods have been attempted in this connection.Recently, artificial neural networks have been tried for this purpose because of its inherent simplicity and reasonably quick data-processing capability. The present work uses the back propagation algorithm for training the neural network of 5-3-1 structure. The technique shows close matching of estimation of average flank wear and directly measured wear value. Thus the system developed demonstrates the possibility of successful tool wear monitoring on-line.     

Experimental design in soap manufacturing for optimization of fuzzified process capability index

In manufacturing industries, the quality of a product depends on the combined effect of multiple input variables working singly or together and therefore attention has been given on process capability indices to shift from single to multivariate domain. In case of multivariable domain the capability to incorporate uncertainties at the time of decision making becomes necessary. Fuzzy system is introduced to take care of this requirement. In this article the process parameters of soap manufacturing industries have been analyzed. The process capability is determined using Fuzzy Inference System rule editor based on a set of justified if then statements as applicable for the process. The data has been collected in linguistic form to derive its process capability, using a set of justified rules and the effect of each factor has been determined using Design of Experiments (DoE) and analysis of variance technique (ANOVA) for improving the soap quality from perspective of its softness. This article ventures to propose a new methodology by integrating Fuzzy with DoE providing better result followed by DoE and Fuzzy Inference system in isolation.     

Victim retention for reducing cache misses in tiled chip multiprocessors

This paper presents CMP-VR (Chip-Multiprocessor with Victim Retention), an approach to improve cache performance by reducing the number of off-chip memory accesses. The objective of this approach is to retain the chosen victim cache blocks on the chip for the longest possible time. It may be possible that some sets of the CMPs last level cache (LLC) are heavily used, while certain others are not. In CMP-VR, some number of ways from every set are used as reserved storage. It allows a victim block from a heavily used set to be stored into the reserve space of another set. In this way the load of heavily used sets are distributed among the underused sets. This logically increases the associativity of the heavily used sets without increasing the actual associativity and size of the cache. Experimental evaluation using full-system simulation shows that CMP-VR has less off-chip miss-rate as compared to baseline Tiled CMP. Results are presented for different cache sizes and associativity for CMP-VR and baseline configuration. The best improvements obtained are 45.5% and 14% in terms of miss rate and cycles per instruction (CPI) respectively for a 4 MB, 4-way set associative LLC. Reduction in CPI and miss rate together guarantees performance improvement.     

The differential effect of polymyxin B1 on guinea pig lung mitochondrial and microsomal glycerophosphate acyltransferase

The activities of guinea pig lung mitochondrial and microsomal glycerophosphate acyltransferase differed in sensitivity to polymyxin B₁. At an antibiotic concentration of 1 mg/ml, the mitochondrial enzyme activity was stimulated twofold, but the microsomal enzyme activity was completely inhibited. Furthermore, the mitochondrial enzyme activity was stimulated by polymyxin B₁ without the addition of exogenous acyl-CoA. Additional experiments ruled out the possibility of polymyxin B₁ acting as a substrate for the mitochondrial acyltransferase. These results suggest either that the polymyxin B₁ sensitivity of mitochondrial and microsomal glycerophosphate acyltransferase is different or that their accessibility to substrates is different because the two isoenzymes are located differently in the different phospholipid microenvironment of the membranes.     

An expressive framework and efficient algorithms for the analysis of collaborative tagging

The rise of Web 2.0 is signaled by sites such as Flickr, del.icio.us, and YouTube, and social tagging is essential to their success. A typical tagging action involves three components, user, item (e.g., photos in Flickr), and tags (i.e., words or phrases). Analyzing how tags are assigned by certain users to certain items has important implications in helping users search for desired information. In this paper, we develop a dual mining framework to explore tagging behavior. This framework is centered around two opposing measures, similarity and diversity, applied to one or more tagging components, and therefore enables a wide range of analysis scenarios such as characterizing similar users tagging diverse items with similar tags or diverse users tagging similar items with diverse tags. By adopting different concrete measures for similarity and diversity in the framework, we show that a wide range of concrete analysis problems can be defined and they are NP-Complete in general. We design four sets of efficient algorithms for solving many of those problems and demonstrate, through comprehensive experiments over real data, that our algorithms significantly out-perform the exact brute-force approach without compromising analysis result quality.