Enabling node repair in any erasure code for distributed storage

Erasure codes are an efficient means of storing data across a network in comparison to data replication, as they tend to reduce the amount of data stored in the network and offer increased resilience in the presence of node failures. The codes perform poorly though, when repair of a failed node is called for, as they typically require the entire file to be downloaded to repair a failed node. A new class of erasure codes, termed as regenerating codes were recently introduced, that do much better in this respect. However, given the variety of efficient erasure codes available in the literature, there is considerable interest in the construction of coding schemes that would enable traditional erasure codes to be used, while retaining the feature that only a fraction of the data need be downloaded for node repair. In this paper, we present a simple, yet powerful, framework that does precisely this. Under this framework, the nodes are partitioned into two types and encoded using two codes in a manner that reduces the problem of node-repair to that of erasure-decoding of the constituent codes. Depending upon the choice of the two codes, the framework can be used to avail one or more of the following advantages: simultaneous minimization of storage space and repair-bandwidth, low complexity of operation, fewer disk reads at helper nodes during repair, and error detection and correction.

Verification of Masonry Building Code to Flexural Behavior of Cement-Stabilized Soil Block

Most studies involving cement-stabilized soil blocks (CSSB) concern material properties, such as the characteristics of erosion and strength and how the composition of the block affects these properties. Moreover, research has been conducted on the performance of various mortars, investigating their material properties and the tensile bond strength between CSSB units and mortar. In contrast, very little is currently known about CSSB masonry structural behavior. Because structural design codes of traditional masonry buildings were well developed over the past century, many of the same principles may be applicable to CSSB masonry buildings. This paper details the topic of flexural behavior of CSSB masonry walls and whether the Masonry Standards Joint Committee (MSJC) code can be applied to this material for improved safety of such buildings. DOI: 10.1061/(ASCE)MT.1943-5533.0000566. (C) 2013 American Society of Civil Engineers.

Euglena sp as a suitable source of lipids for potential use as biofuel and sustainable wastewater treatment

Prolific algal growth in sewage ponds with high organic loads in the tropical regions can provide cost-effective and efficient wastewater treatment and biofuel production. This work examines the ability of Euglena sp. growing in wastewater ponds for biofuel production and treatment of wastewater. The algae were isolated from the sewage treatment plants and were tested for their nutrient removal capability. Compared to other algae, Euglena sp. showed faster growth rates with high biomass density at elevated concentrations of ammonium nitrogen (NH4-N) and organic carbon (C). Profuse growth of these species was observed in untreated wastewaters with a mean specific growth rate (mu) of 0.28 day(-1) and biomass productivities of 132 mg L-1 day(-1). The algae cultured within a short period of 8 days resulted in the 98 % removal of NH4-N, 93 % of total nitrogen 85 % of ortho-phosphate, 66 % of total phosphate and 92 % total organic carbon. Euglenoids achieved a maximum lipid content of 24.6 % (w/w) with a biomass density of 1.24 g L-1 (dry wt.). Fourier transform infrared spectra showed clear transitions in biochemical compositions with increased lipid/protein ratio at the end of the culture. Gas chromatography and mass spectrometry indicated the presence of high contents of palmitic, linolenic and linoleic acids (46, 23 and 22 %, respectively), adding to the biodiesel quality. Good lipid content (comprised quality fatty acids), efficient nutrient uptake and profuse biomass productivity make the Euglena sp. as a viable source for biofuel production in wastewaters.

Integrated sustainable irrigation planning with multiobjective Fuzzy optimization approach

Multiobjective fuzzy methodology is applied to a case study of Khadakwasla complex irrigation project located near Pune city of Maharashtra State, India. Three objectives, namely, maximization of net benefits, crop production and labour employment are considered. Effect of reuse of wastewater on the planning scenario is also studied. Three membership functions, namely, nonlinear, hyperbolic and exponential are analyzed for multiobjective fuzzy optimization. In the present study, objective functions are considered as fuzzy in nature whereas inflows are considered as dependable. It is concluded that exponential and hyperbolic membership functions provided similar cropping pattern for most of the situations whereas nonlinear membership functions provided different cropping pattern. However, in all the three cases, irrigation intensities are more than the existing irrigation intensity.

Delay optimal scheduling of a discrete-time batch service queue for point-to-point channel code rate selection

We consider the problem of characterizing the minimum average delay, or equivalently the minimum average queue length, of message symbols randomly arriving to the transmitter queue of a point-to-point link which dynamically selects a (n, k) block code from a given collection. The system is modeled by a discrete time queue with an IID batch arrival process and batch service. We obtain a lower bound on the minimum average queue length, which is the optimal value for a linear program, using only the mean (λ) and variance (σ2) of the batch arrivals. For a finite collection of (n, k) codes the minimum achievable average queue length is shown to be Θ(1/ε) as ε ↓ 0 where ε is the difference between the maximum code rate and λ. We obtain a sufficient condition for code rate selection policies to achieve this optimal growth rate. A simple family of policies that use only one block code each as well as two other heuristic policies are shown to be weakly optimal in the sense of achieving the 1/ε growth rate. An appropriate selection from the family of policies that use only one block code each is also shown to achieve the optimal coefficient σ2/2 of the 1/ε growth rate. We compare the performance of the heuristic policies with the minimum achievable average queue length and the lower bound numerically. For a countable collection of (n, k) codes, the optimal average queue length is shown to be Ω(1/ε). We illustrate the selectivity among policies of the growth rate optimality criterion for both finite and countable collections of (n, k) block codes.

Eco-friendly wood polymer composites for sustainable design applications

Environmental inputs can improve the level of innovation by interconnecting them with traditional inputs regarding the properties of materials and processes as a strategic eco-design procedure. Advanced engineered polymer composites are needed to meet the diverse needs of users for high-performance automotive, construction and commodity products that simultaneously maximize the sustainability of forest resources. In the current work, wood polymer composites (WPC) are studied to promote long-term resource sustainability and to decrease environmental impacts relative to those of existing products. A series of polypropylene wood–fiber composite materials having 20, 30, 40 and 50 wt. % of wood–fibers were prepared using twin-screw extruder and injection molding machine. Tensile and flexural properties of the composites were determined. Polypropylene (PP) as a matrix used in this study is a thermoplastic material, which is recyclable. Suitability of the prepared composites as a sustainable product is discussed.

Magnetic and dielectric interactions in nano zinc ferrite powder: Prepared by self-sustainable propellant chemistry technique

The structural, magnetic and dielectric properties of nano zinc ferrite prepared by the propellant chemistry technique are studied. The PXRD measurement at room temperature reveal that the compound is in cubic spinel phase, belong to the space group Fd (3) over barm. The unit cell parameters have been estimated from Rietveld refinement. The calculated force constants from FTIR spectrum corresponding to octahedral and tetrahedral sites at 375 and 542 cm(-1) are 6.61 x 10(2) and 3.77 x 10(2) N m(-1) respectively; these values are slightly higher compared to the other ferrite systems. Magnetic hysteresis and EPR spectra show superparamagnetic property nearly to room temperature due to comparison values between magnetic anisotropy energy and the thermal energy. The calculated values of saturation magnetization, remenant magnetization, coercive field and magnetic moment supports for the existence of multi domain particles in the sample. The temperature dependent magnetic field shows the spin freezing state at 30 K and the blocking temperature at above room temperature. The frequency dependent dielectric interactions show the variation of dielectric constant, dielectric loss and impedance as similar to other ferrite systems. The AC conductivity in the prepared sample is due to the presence of electrons, holes and polarons. The synthesized material is suitable for nano-electronics and biomedical applications. (C) 2014 Elsevier B.V. All rights reserved.

Using Relationships for Matching Textual Domain Models with Existing Code

We address the task of mapping a given textual domain model (e.g., an industry-standard reference model) for a given domain (e.g., ERP), with the source code of an independently developed application in the same domain. This has applications in improving the understandability of an existing application, migrating it to a more flexible architecture, or integrating it with other related applications. We use the vector-space model to abstractly represent domain model elements as well as source-code artifacts. The key novelty in our approach is to leverage the relationships between source-code artifacts in a principled way to improve the mapping process. We describe experiments wherein we apply our approach to the task of matching two real, open-source applications to corresponding industry-standard domain models. We demonstrate the overall usefulness of our approach, as well as the role of our propagation techniques in improving the precision and recall of the mapping task.

Selection and thermodynamic analysis of a turbocharger for a producer gas-fuelled multi-cylinder engine

The current work addresses the use of producer gas, a bio-derived gaseous alternative fuel, in engines designed for natural gas, derived from diesel engine frames. Impact of the use of producer gas on the general engine performance with specific focus on turbo-charging is addressed. The operation of a particular engine frame with diesel, natural gas and producer gas indicates that the peak load achieved is highest with diesel fuel (in compression ignition mode) followed by natural gas and producer gas (both in spark ignite mode). Detailed analysis of the engine power de-rating on fuelling with natural gas and producer gas indicates that the change in compression ratio (migration from compression to spark ignited mode), difference in mixture calorific value and turbocharger mismatch are the primary contributing factors. The largest de-rating occurs due to turbocharger mismatch. Turbocharger selection and optimization is identified as the strategy to recover the non-thermodynamic power loss, identified as the recovery potential (the loss due to mixture calorific value and turbocharger mismatch) on operating the engine with a fuel different from the base fuel. A turbocharged after-cooled six cylinder, 5.9 l, 90 kWe (diesel rating) engine (12.2 bar BMEP) is available commercially as a naturally aspirated natural gas engine delivering a peak load of 44.0 kWe (6.0 bar BMEP). The engine delivers a load of 27.3 kWe with producer gas under naturally aspirated mode. On charge boosting the engine with a turbocharger similar in configuration to the diesel engine turbocharger, the peak load delivered with producer gas is 36 kWe (4.8 bar BMEP) indicating a de-rating of about 60% over the baseline diesel mode. Estimation of knock limited peak load for producer gas-fuelled operation on the engine frame using a Wiebe function-based zero-dimensional code indicates a knock limited peak load of 76 kWe, indicating the potential to recover about 40 kWe. As a part of the recovery strategy, optimizing the ignition timing for maximum brake torque based on both spark sweep tests and established combustion descriptors and engine-turbocharger matching for producer gas-fuelled operation resulted in a knock limited peak load of 72.8 kWe (9.9 bar BMEP) at a compressor pressure ratio of 2.30. The de-rating of about 17.0 kWe compared to diesel rating is attributed to the reduction in compression ratio. With load recovery, the specific biomass consumption reduces from 1.2 kg/kWh to 1.0 kg/kWh, an improvement of over 16% while the engine thermal efficiency increases from 28% to 32%. The thermodynamic analysis of the compressor and the turbine indicates an isentropic efficiency of 74.5% and 73%, respectively.

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Programming for parallel architectures that do not have a shared address space is extremely difficult due to the need for explicit communication between memories of different compute devices. A heterogeneous system with CPUs and multiple GPUs, or a distributed-memory cluster are examples of such systems. Past works that try to automate data movement for distributed-memory architectures can lead to excessive redundant communication. In this paper, we propose an automatic data movement scheme that minimizes the volume of communication between compute devices in heterogeneous and distributed-memory systems. We show that by partitioning data dependences in a particular non-trivial way, one can generate data movement code that results in the minimum volume for a vast majority of cases. The techniques are applicable to any sequence of affine loop nests and works on top of any choice of loop transformations, parallelization, and computation placement. The data movement code generated minimizes the volume of communication for a particular configuration of these. We use a combination of powerful static analyses relying on the polyhedral compiler framework and lightweight runtime routines they generate, to build a source-to-source transformation tool that automatically generates communication code. We demonstrate that the tool is scalable and leads to substantial gains in efficiency. On a heterogeneous system, the communication volume is reduced by a factor of 11X to 83X over state-of-the-art, translating into a mean execution time speedup of 1.53X. On a distributed-memory cluster, our scheme reduces the communication volume by a factor of 1.4X to 63.5X over state-of-the-art, resulting in a mean speedup of 1.55X. In addition, our scheme yields a mean speedup of 2.19X over hand-optimized UPC codes.

Exploring sand and bentonite - enhanced sand as filter media for nitrate removal

Increasing nitrate concentrations in ground water is deleterious to human health as ingestion of such water can cause methemoglobinemia in infants and even cancer in adults (desirable limit for nitrate as NO3 - 45 mg/L, IS code 10500-1991). Excess nitrate concentrations in ground water is contributed by reason being disposal of sewage and excessive use of fertilizers. Though numerous technologies such as reverse osmosis, ion exchange, electro-dialysis, permeable reactive barriers using zerovalent iron etc exists, nitrate removal continues to be one of challenging issue as nitrate ion is highly mobile within the soil strata. The tapping the denitrification potential of soil denitrifiers which are inherently available in the soil matrix is the most sustainable approach to mitigate accumulation of nitrate in ground water. The insitu denitrification of sand and bentonite enhanced sand (bentonite content = 5%) in presence of easily assimilable organic carbon such as ethanol was studied. Batch studies showed that nitrate reduction by sand follows first order kinetics with a rate constant 5.3x10(-2) hr(-1) and rate constant 4.3 x 10(-2) hr(-1) was obtained for bentonite-enhanced sand (BS) at 25 degrees C. Filter columns (height = 5 cm and diameter = 8.2 cm) were constructed using sand and bentonite-enhanced sand as filter media. The filtration rate through both the filter columns was maintained at average value of 2.60 cm/h. The nitrate removal rates through both the filter media was assessed for solution containing 22.6 mg NO3-N/L concentrations while keeping C/N mass ratio as 3. For sand filter column, the nitrate removal efficiency reached the average value of 97.6% after passing 50 pore volumes of the nitrate solution. For bentonite-enhanced sand filter column, the average nitrate removal efficiency was 83.5%. The time required for effective operation for sand filter bed was 100 hours, while bentonite-enhanced sand filter bed did not require any maturation period as that of sand filter bed for effective performance because the presence of micropores in bentonite increases the hydraulic retention time of the solution inside the filter bed.

LDPC Code Designs Based on root I Matrices

LDPC codes can be constructed by tiling permutation matrices that belong to the square root of identity type and similar algebraic structures. We investigate into the properties of such codes. We also present code structures that are amenable for efficient encoding.

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.

Multiobjective fuzzy optimization for sustainable groundwater management using particle swarm optimization and analytic element method

Groundwater management involves conflicting objectives as maximization of discharge contradicts the criteria of minimum pumping cost and minimum piping cost. In addition, available data contains uncertainties such as market fluctuations, variations in water levels of wells and variations of ground water policies. A fuzzy model is to be evolved to tackle the uncertainties, and a multiobjective optimization is to be conducted to simultaneously satisfy the contradicting objectives. Towards this end, a multiobjective fuzzy optimization model is evolved. To get at the upper and lower bounds of the individual objectives, particle Swarm optimization (PSO) is adopted. The analytic element method (AEM) is employed to obtain the operating potentio metric head. In this study, a multiobjective fuzzy optimization model considering three conflicting objectives is developed using PSO and AEM methods for obtaining a sustainable groundwater management policy. The developed model is applied to a case study, and it is demonstrated that the compromise solution satisfies all the objectives with adequate levels of satisfaction. Sensitivity analysis is carried out by varying the parameters, and it is shown that the effect of any such variation is quite significant. Copyright (c) 2015 John Wiley & Sons, Ltd.

Pursuit of Sustainable Iron-Based Sodium Battery Cathodes: Two Case Studies

Rechargeable batteries have been the torchbearer electrochemical energy storage devices empowering small-scale electronic gadgets to large-scale grid storage. Complementing the lithium-ion technology, sodium-ion batteries have emerged as viable economic alternatives in applications unrestricted by volume/weight. What is the best performance limit for new-age Na-ion batteries? This mission has unravelled suites of oxides and polyanionic positive insertion (cathode) compounds in the quest to realize high energy density. Economically and ecologically, iron-based cathodes are ideal for mass-scale dissemination of sodium batteries. This Perspective captures the progress of Fe-containing earth-abundant sodium battery cathodes with two best examples: (i) an oxide system delivering the highest capacity (similar to 200 mA h/g) and (ii) a polyanionic system showing the highest redox potential (3.8 V). Both develop very high energy density with commercial promise for large-scale applications. Here, the structural and electrochemical properties of these two cathodes are compared and contrasted to describe two alternate strategies to achieve the same goal, i.e., improved energy density in Fe-based sodium battery cathodes.