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.     

An automated, parallel processing approach to biomolecular sample preparation

Sample preparation for DNA and RNA assays is a prime candidate for laboratory automation. A novel, parallel processing device that performs the three separate liquid-handling functions necessary for such sample preparation-dispensing, pipetting, and pressurizing-is presented. The device comprises an array of fine nozzles connected by fluidic channels to automatically and precisely distribute flow between one source and an array of points. The design principles, as well as the experimental and computational methods used to develop the device, are described. Test results, including accuracy, uniformity, volume range, and timing, are presented. The functionality of the device is demonstrated by performing a solid-phase extraction of DNA with two types of microcolumns.     

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.     

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.     

An Experimental Study to Evaluate the Effect of Ambient Temperature during Manual Lifting and Design of Optimal Task Parameters

In the present study, the effect of lifting task parameters on the heart rate and oxygen uptake of workers during manual lifting tasks in different ambient conditions was evaluated. The experiments conducted in two different temperature conditions showed a significantly higher oxygen uptake and heart rate in colder conditions as compared to warmer conditions. Three other factors, namely, load, lifting frequency, and vertical distance were found to significant affect the responses. Various combinations of significant factors were used to calculate oxygen uptake and heart rate. These were then compared with the safe limits as per the maximum aerobic capacity of workers. Based on these comparisons, the safe combinations were identified that can be used to design lifting tasks in varied ambient conditions. The study further concluded that lifting tasks performed in winter should have different relaxation or fatigue allowances built into the cycle time of the task to compensate for higher exertion. © 2011 Wiley Periodicals, Inc.     

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.     

Ion-solvent interaction from viscosity and apparent molar volume of bromates,iodates and sulphates of potassium and sodium in dioxane-water mixtures at different temperatures

The viscosity and apparent molar volume of solutions of KBrO₃, NaBrO₃ KIO₃, NaIO₃, K₂SO₄ and Na₂SO₄ in dioxane (mass fraction: 10, 20 and 30%)-water mixtures at 30, 35, 40 and 45°C have been measured. The ions appear to interact appreciably and the ion-solvent interaction is of the order BrO^?₃ > IO^?₃ > SO^2?₄ and K⁺ > Na⁺.