EXPERIENCE OF OPERATING OPEN TOP BIOMASS GASIFIER USING A LOW DENSITY FUEL-COCONUT FRONDS

Use of fuel other than woody generally has been limited to rice husk and other residues are rarely tried as a fuel in a gasification system. With the availability of woody biomass in most countries like India, alternates fuels are being explored for sustainable supply of fuel. Use of agro residues has been explored after briquetting. There are few feedstock's like coconut fronts, maize cobs, etc, that might require lesser preprocessing steps compared to briquetting. The paper presents a detailed investigation into using coconut fronds as a fuel in an open top down draft gasification system. The fuel has ash content of 7% and was dried to moisture levels of 12 %. The average bulk density was found to be 230 kg/m3 with a fuel size particle of an average size 40 mm as compared to 350 kg/m3 for a standard wood pieces. A typical dry coconut fronds weighs about 2.5kgs and on an average 6 m long and 90 % of the frond is the petiole which is generally used as a fuel. The focus was also to compare the overall process with respect to operating with a typical woody biomass like subabul whose ash content is 1 %. The open top gasification system consists of a reactor, cooling and cleaning system along with water treatment. The performance parameters studied were the gas composition, tar and particulates in the clean gas, water quality and reactor pressure drop apart from other standard data collection of fuel flow rate, etc. The average gas composition was found to be CO 15 1.0 % H-2 16 +/- 1% CH4 0.5 +/- 0.1 % CO2 12.0 +/- 1.0 % and rest N2 compared to CO 19 +/- 1.0 % H-2 17 +/- 1.0 %, CH4 1 +/- 0.2 %, CO2 12 +/- 1.0 % and rest N2. The tar and particulate content in the clean gas has been found to be about 10 and 12 mg/m3 in both cases. The presence of high ash content material increased the pressure drop with coconut frond compared to woody biomass.

PriDyn: Enabling Differentiated I/O Services in Cloud Using Dynamic Priorities

Virtualization is one of the key enabling technologies for Cloud computing. Although it facilitates improved utilization of resources, virtualization can lead to performance degradation due to the sharing of physical resources like CPU, memory, network interfaces, disk controllers, etc. Multi-tenancy can cause highly unpredictable performance for concurrent I/O applications running inside virtual machines that share local disk storage in Cloud. Disk I/O requests in a typical Cloud setup may have varied requirements in terms of latency and throughput as they arise from a range of heterogeneous applications having diverse performance goals. This necessitates providing differential performance services to different I/O applications. In this paper, we present PriDyn, a novel scheduling framework which is designed to consider I/O performance metrics of applications such as acceptable latency and convert them to an appropriate priority value for disk access based on the current system state. This framework aims to provide differentiated I/O service to various applications and ensures predictable performance for critical applications in multi-tenant Cloud environment. We demonstrate through experimental validations on real world I/O traces that this framework achieves appreciable enhancements in I/O performance, indicating that this approach is a promising step towards enabling QoS guarantees on Cloud storage.

Exploring Technology Evolution Using Patent Classification: A Case of Cochlear Implant Technology Patents

Understanding technology evolution through periodic landscaping is an important stage of strategic planning in R&D Management. In fields like that of healthcare, where the initial R&D investment is huge and good medical product serve patients better, these activities become crucial. Approximately five percentage of the world population has hearing disabilities. Current hearing aid products meet less than ten percent of the global needs. Patent data and classifications on cochlear implants from 1977-2010, show the landscapes and evolution in the area of such implant. We attempt to highlight emergence and disappearance of patent classes over period of time showing variations in cochlear implant technologies. A network analysis technique is used to explore and capture technology evolution in patent classes showing what emerged or disappeared over time. Dominant classes are identified. The sporadic influence of university research in cochlear implants is also discussed.

Mapping the intriguing transient morphologies and the demixing behavior in PS/PVME blends in the presence of rod-like nanoparticles

The demixing behavior, transient morphologies and mechanism of phase separation in PS/PVME blends were greatly altered in the presence of a very low concentration of rod-like particles (multiwall carbon nanotubes, MWNTs). This phenomenon is due to the specific interaction of one of the phases (PVME) with the anisotropic MWNTs, which creates a heterogeneous environment in the blend. This specific interaction alters the chain dynamics in the interfacial region as against the bulk. A comprehensive analysis using isochronal temperature sweep was performed to understand the demixing temperature in the blends. The evolution of phase morphology as a function of time and temperature was assessed by polarizing optical microscopy (POM), atomic force microscopy (AFM) and scanning electron microscopy (SEM). The addition of MWNTs increased the rheological demixing temperature and the spinodal temperature in almost all the compositions. The intriguing transient morphologies were mapped, which varied from nucleation and growth to coalescence-induced viscoelastic phase separation (C-VPS) in PVME-rich blends, to spinodal decomposition in the near-critical compositions, to transient gel-induced VPS (T-VPS) in the PS-rich compositions. Mapping of the morphology development displayed two types of fracture mechanisms: ductile fracture for near-critical compositions and brittle fracture for off-critical composition. The change in the phase separation mechanism in the presence of MWNTs was due to the variation in dynamic asymmetry brought about by these anisotropic particles. All these observations were correlated by POM, SEM and AFM studies. The length of the cooperatively rearranging region (CRR), as evaluated using modulated differential scanning calorimetry (MDSC) measurements, was found to be composition-independent. The observed variation of effective glass transition of PVME (low T-g component) on blending with PS (high Tg component) and by the addition of MWNTs accounts for the dynamic heterogeneity introduced by MWNTs in the system.

Robust Whisper Activity Detection Using Long-Term Log Energy Variation of Sub-Band Signal

The goal in the whisper activity detection (WAD) is to find the whispered speech segments in a given noisy recording of whispered speech. Since whispering lacks the periodic glottal excitation, it resembles an unvoiced speech. This noise-like nature of the whispered speech makes WAD a more challenging task compared to a typical voice activity detection (VAD) problem. In this paper, we propose a feature based on the long term variation of the logarithm of the short-time sub-band signal energy for WAD. We also propose an automatic sub-band selection algorithm to maximally discriminate noisy whisper from noise. Experiments with eight noise types in four different signal-to-noise ratio (SNR) conditions show that, for most of the noises, the performance of the proposed WAD scheme is significantly better than that of the existing VAD schemes and whisper detection schemes when used for WAD.

Linking carbon metabolism to carotenoid production in mycobacteria using Raman spectroscopy

Bacteria can utilize multiple sources of carbon for growth, and for pathogenic bacteria like Mycobacterium tuberculosis, this ability is crucial for survival within the host. In addition, phenotypic changes are seen in mycobacteria grown under different carbon sources. In this study, we use Raman spectroscopy to analyze the biochemical components present in M. smegmatis cells when grown in three differently metabolized carbon sources. Our results show that carotenoid biosynthesis is enhanced when M. smegmatis is grown in glucose compared to glycerol and acetate. We demonstrate that this difference is most likely due to transcriptional upregulation of the carotenoid biosynthesis operon (crt) mediated by higher levels of the stress-responsive sigma factor SigF. Moreover, we find that increased SigF and carotenoid levels correlate with greater resistance of glucose-grown cells to oxidative stress. Thus, we demonstrate the use of Raman spectroscopy in unraveling unknown aspects of mycobacterial physiology and describe a novel effect of carbon source variation on mycobacteria.

Human Action Recognition in Compressed Domain using PBL-McRBFN Approach

Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.

An Optimizing Code Generator for a Class of Lattice-Boltzmann Computations

The Lattice-Boltzmann method (LBM), a promising new particle-based simulation technique for complex and multiscale fluid flows, has seen tremendous adoption in recent years in computational fluid dynamics. Even with a state-of-the-art LBM solver such as Palabos, a user has to still manually write the program using library-supplied primitives. We propose an automated code generator for a class of LBM computations with the objective to achieve high performance on modern architectures. Few studies have looked at time tiling for LBM codes. We exploit a key similarity between stencils and LBM to enable polyhedral optimizations and in turn time tiling for LBM. We also characterize the performance of LBM with the Roofline performance model. Experimental results for standard LBM simulations like Lid Driven Cavity, Flow Past Cylinder, and Poiseuille Flow show that our scheme consistently outperforms Palabos-on average by up to 3x while running on 16 cores of an Intel Xeon (Sandybridge). We also obtain an improvement of 2.47x on the SPEC LBM benchmark.

Dissecting Ubiquitin Folding Using the Self-Organized Polymer Model

Folding of Ubiquitin (Ub), a functionally important protein found in eukaryotic organisms, is investigated at low and neutral pH at different temperatures using simulations of the coarse-grained self-organized-polymer model with side chains (SOP-SC). The melting temperatures (T-m's), identified with the peaks in the heat capacity curves, decrease as pH decreases, in qualitative agreement with experiments. The calculated radius of gyration, showing dramatic variations with pH, is in excellent agreement with scattering experiments. At T-m Ub folds in a two-state manner at low and neutral pH. Clustering analysis of the conformations sampled in equilibrium folding trajectories at T-m with multiple transitions between the folded and unfolded states, shows a network of metastable states connecting the native and unfolded states. At low and neutral pH, Ub folds with high probability through a preferred set of conformations resulting in a pH-dependent dominant folding pathway. Folding kinetics reveal that Ub assembly at low pH occurs by multiple pathways involving a combination of nucleation-collapse and diffusion collision mechanism. The mechanism by which Ub folds is dictated by the stability of the key secondary structural elements responsible for establishing long-range contacts and collapse of Ub. Nucleation collapse mechanism holds if the stability of these elements are marginal, as would be the case at elevated temperatures. If the lifetimes associated with these structured microdomains are on the order of hundreds of microseconds, then Ub folding follows the diffusion collision mechanism with intermediates, many of which coincide with those found in equilibrium. Folding at neutral pH is a sequential process with a populated intermediate resembling that sampled at equilibrium. The transition state structures, obtained using a P-fold analysis, are homogeneous and globular with most of the secondary and tertiary structures being native-like. Many of our findings for both the thermodynamics and kinetics of folding are not only in agreement with experiments but also provide missing details not resolvable in standard experiments. The key prediction that folding mechanism varies dramatically with pH is amenable to experimental tests.

An Alternating l(p) - l(2) Projections Algorithm (ALPA) for Speech Modeling using Sparsity Constraints

We address the problem of separating a speech signal into its excitation and vocal-tract filter components, which falls within the framework of blind deconvolution. Typically, the excitation in case of voiced speech is assumed to be sparse and the vocal-tract filter stable. We develop an alternating l(p) - l(2) projections algorithm (ALPA) to perform deconvolution taking into account these constraints. The algorithm is iterative, and alternates between two solution spaces. The initialization is based on the standard linear prediction decomposition of a speech signal into an autoregressive filter and prediction residue. In every iteration, a sparse excitation is estimated by optimizing an l(p)-norm-based cost and the vocal-tract filter is derived as a solution to a standard least-squares minimization problem. We validate the algorithm on voiced segments of natural speech signals and show applications to epoch estimation. We also present comparisons with state-of-the-art techniques and show that ALPA gives a sparser impulse-like excitation, where the impulses directly denote the epochs or instants of significant excitation.

High Quality Photometric Reconstruction using a Depth Camera

In this paper we present a depth-guided photometric 3D reconstruction method that works solely with a depth camera like the Kinect. Existing methods that fuse depth with normal estimates use an external RGB camera to obtain photometric information and treat the depth camera as a black box that provides a low quality depth estimate. Our contribution to such methods are two fold. Firstly, instead of using an extra RGB camera, we use the infra-red (IR) camera of the depth camera system itself to directly obtain high resolution photometric information. We believe that ours is the first method to use an IR depth camera system in this manner. Secondly, photometric methods applied to complex objects result in numerous holes in the reconstructed surface due to shadows and self-occlusions. To mitigate this problem, we develop a simple and effective multiview reconstruction approach that fuses depth and normal information from multiple viewpoints to build a complete, consistent and accurate 3D surface representation. We demonstrate the efficacy of our method to generate high quality 3D surface reconstructions for some complex 3D figurines.

Shock tunnel measurements of surface pressures in shock induced separated flow field using MEMS sensor array

Characterized not just by high Mach numbers, but also high flow total enthalpies-often accompanied by dissociation and ionization of flowing gas itself-the experimental simulation of hypersonic flows requires impulse facilities like shock tunnels. However, shock tunnel simulation imposes challenges and restrictions on the flow diagnostics, not just because of the possible extreme flow conditions, but also the short run times-typically around 1 ms. The development, calibration and application of fast response MEMS sensors for surface pressure measurements in IISc hypersonic shock tunnel HST-2, with a typical test time of 600 mu s, for the complex flow field of strong (impinging) shock boundary layer interaction with separation close to the leading edge, is delineated in this paper. For Mach numbers 5.96 (total enthalpy 1.3 MJ kg(-1)) and 8.67 (total enthalpy 1.6 MJ kg(-1)), surface pressures ranging from around 200 Pa to 50 000 Pa, in various regions of the flow field, are measured using the MEMS sensors. The measurements are found to compare well with the measurements using commercial sensors. It was possible to resolve important regions of the flow field involving significant spatial gradients of pressure, with a resolution of 5 data points within 12 mm in each MEMS array, which cannot be achieved with the other commercial sensors. In particular, MEMS sensors enabled the measurement of separation pressure (at Mach 8.67) near the leading edge and the sharply varying pressure in the reattachment zone.

A Design for Performance Improvement of Clock Synchronization in WSNs using a TDMA-based MAC Protocol

Clock synchronization in a wireless sensor network (WSN) is quite essential as it provides a consistent and a coherent time frame for all the nodes across the network. Typically, clock synchronization is achieved by message passing using a contention-based scheme for media access, like carrier sense multiple access (CSMA). The nodes try to synchronize with each other, by sending synchronization request messages. If many nodes try to send messages simultaneously, contention-based schemes cannot efficiently avoid collisions. In such a situation, there are chances of collisions, and hence, message losses, which, in turn, affects the convergence of the synchronization algorithms. However, the number of collisions can be reduced with a frame based approach like time division multiple access (TDMA) for message passing. In this paper, we propose a design to utilize TDMA-based media access and control (MAC) protocol for the performance improvement of clock synchronization protocols. The basic idea is to use TDMA-based transmissions when the degree of synchronization improves among the sensor nodes during the execution of the clock synchronization algorithm. The design significantly reduces the collisions among the synchronization protocol messages. We have simulated the proposed protocol in Castalia network simulator. The simulation results show that the proposed protocol significantly reduces the time required for synchronization and also improves the accuracy of the synchronization algorithm.

Quantitative characterization of adhesion and stiffness of corneal lens of Drosophila melanogaster using atomic force microscopy

Atomic force Microscopy (AFM) has become a versatile tool in biology due to its advantage of high-resolution imaging of biological samples close to their native condition. Apart from imaging, AFM can also measure the local mechanical properties of the surfaces. In this study, we explore the possibility of using AFM to quantify the rough eye phenotype of Drosophila melanogaster through mechanical properties. We have measured adhesion force, stiffness and elastic modulus of the corneal lens using AFM. Various parameters affecting these measurements like cantilever stiffness and tip geometry are systematically studied and the measurement procedures are standardized. Results show that the mean adhesion force of the ommatidial surface varies from 36 nN to 16 nN based on the location. The mean stiffness is 483 +/- 5 N/m, and the elastic modulus is 3.4 +/- 0.05 GPa (95% confidence level) at the center of ommatidia. These properties are found to be different in corneal lens of eye expressing human mutant tau gene (mutant). The adhesion force, stiffness and elastic modulus are decreased in the mutant. We conclude that the measurement of surface and mechanical properties of D. melanogaster using AFM can be used for quantitative evaluation of `rough eye' surface. (C) 2015 Elsevier Ltd. All rights reserved.

Detection and estimation of liquid flow through a pipe in a tissue-like object with ultrasound-assisted diffuse correlation spectroscopy

Using coherent light interrogating a turbid object perturbed by a focused ultrasound (US) beam, we demonstrate localized measurement of dynamics in the focal region, termed the region-of-interest (ROI), from the decay of the modulation in intensity autocorrelation of light. When the ROI contains a pipe flow, the decay is shown to be sensitive to the average flow velocity from which the mean-squared displacement (MSD) of the scattering centers in the flow can be estimated. While the MSD estimated is seen to be an order of magnitude higher than that obtainable through the usual diffusing wave spectroscopy (DWS) without the US, it is seen to be more accurate as verified by the volume flow estimated from it. It is further observed that, whereas the MSD from the localized measurement grows with time as tau(alpha) with alpha approximate to 1.65, without using the US, a is seen to be much less. Moreover, with the local measurement, this super-diffusive nature of the pipe flow is seen to persist longer, i.e., over a wider range of initial tau, than with the unassisted DWS. The reason for the super-diffusivity of flow, i.e., alpha < 2, in the ROI is the presence of a fluctuating (thermodynamically nonequilibrium) component in the dynamics induced by the US forcing. Beyond this initial range, both methods measure MSDs that rise linearly with time, indicating that ballistic and near-ballistic photons hardly capture anything beyond the background Brownian motion. (C) 2015 Optical Society of America