Optimal size,hydraulic retention time and volatile solids loading rate of biogas unit using water hyacinth

With a view to evaluate the effects of hydraulic retention time and volatile solids loading rate on methane production using water hyacinth, experiments were conducted in a 160 dm³ capacity, well-mixed continuous digestion unit at ambient temperature. The optimal design of biogas plant using water hyacinth was elucidated, to provide a unit giving a maximum methane yield of 0.16 nm³ kg^?1 volatile solids added, which was 60% greater than the conventional plant using cowdung. The calculations of optimal design factors were based on reactor size, hydraulic retention time and volatile solids loading rate; considerations were made of capital cost, running costs and operational revenue.     

A 4.5-GHz 130-nm 32-KB L0 cache with a leakage-tolerant self reverse-bias bitline scheme

This paper describes a 32-KB two-read, one-write ported L0 cache for 4.5-GHz operation in 1.2-V 130-nm dual-V/sub TH/ CMOS technology. The local bitline uses a leakage-tolerant self reverse-bias (SRB) scheme with nMOS source-follower pullup access transistors, while preserving robust full-swing operation. Gate-source underdrive of -220 mV on the bitline read-select transistors is established without external bias voltages or gate-oxide overstress. Device-level measurements in the 130-nm technology show 72/spl times/ bitline active leakage reduction, enabling low-V/sub TH/ usage, 40% bitline keeper downsizing, and 16 bitcells/bitline. 11% faster read delay and 2/spl times/ higher dc noise robustness are achieved compared with high-performance dual-V/sub TH/ bitline scheme. Sustained performance and robustness benefits of the SRB technique against conventional dynamic bitline with scaling to 100- and 70-nm technology is also presented.     

An actor-critic algorithm for constrained Markov decision processes

An actor-critic type reinforcement learning algorithm is proposed and analyzed for constrained controlled Markov decision processes. The analysis uses multiscale stochastic approximation theory and the envelope theorem' of mathematical economics.     

A stochastic Kaczmarz algorithm for network tomography

We develop a stochastic approximation version of the classical Kaczmarz algorithm that is incremental in nature and takes as input noisy real time data. Our analysis shows that with probability one it mimics the behavior of the original scheme: starting from the same initial point, our algorithm and the corresponding deterministic Kaczmarz algorithm converge to precisely the same point. The motivation for this work comes from network tomography where network parameters are to be estimated based upon end-to-end measurements. Numerical examples via Matlab based simulations demonstrate the efficacy of the algorithm.     

Express Virtual Channels with Capacitively Driven Global Links

Networks on chip must deliver high bandwidth at low latencies while keeping within a tight power envelope. Using express virtual channels for flow control improves energy-delay throughput by letting packets bypass intermediate routers, but EVCs have key limitations. Nochi (NoC with hybrid interconnect) overcomes these limitations by transporting data payloads and control information on separate planes, optimized for bandwidth and latency respectively.     

Laser-Deposited In Situ TiC-Reinforced Nickel Matrix Composites: 3D Microstructure and Tribological Properties

A new class of Ni-Ti-C-based metal-matrix composites has been developed using the laser-engineered net shaping? process. These composites consist of an in situ formed and homogeneously distributed titanium carbide (TiC) phase reinforcing the nickel matrix. Additionally, by tailoring the Ti/C ratio in these composites, an additional graphitic phase can also be engineered into the microstructure. Serial-sectioning, followed by three-dimensional reconstruction of the microstructure in these composites, reveals homogeneously distributed primary and eutectic titanium carbide precipitates as well as a graphitic phase encompassing the primary carbides within the nickel matrix. The morphology and spatial distribution of these phases in three dimensions reveals that the eutectic carbides form a network linked by primary carbides or graphitic nodules at the nodes, which suggests interesting insights into the sequence of phase evolution. These three-phase Ni-TiC-C composites exhibit excellent tribological properties, in terms of an extremely low coefficient of friction while maintaining a relatively high hardness.     

Low computation and low latency algorithms for distributed sensor network initialization

In this paper, we show how an underlying system’s state vector distribution can be determined in a distributed heterogeneous sensor network with reduced subspace observability at the individual nodes. The presented algorithm can generate the initial state vector distribution for networks with a variety of sensor types as long as the collective set of measurements from all the sensors provides full state observability. Hence the network, as a whole, can be capable of observing the target state vector even if the individual nodes are not capable of observing it locally. Initialization is accomplished through a novel distributed implementation of the particle filter that involves serial particle proposal and weighting strategies that can be accomplished without sharing raw data between individual nodes. If multiple events of interest occur, their individual states can be initialized simultaneously without requiring explicit data association across nodes. The resulting distributions can be used to initialize a variety of distributed joint tracking algorithms. We present two variants of our initialization algorithm: a low complexity implementation and a low latency implementation. To demonstrate the effectiveness of our algorithms we provide simulation results for initializing the states of multiple maneuvering targets in smart sensor networks consisting of acoustic and radar sensors. Prepared through collaborative participation in the Advanced Sensors Consortium sponsored by the US Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-02-0008.     

Thousand-Core Chips [Roundtable]

The 2007 Design Automation Conference (DAC) had a special session entitled "1000 Core Chips," which was organized by Radu Marculescu (Carnegie Mellon University) and Li-Shiuan Peh (Princeton University). This session examined some of the ramifications of multicore chip design from four perspectives: technology, architecture, programming, and design automation. In this roundtable, held immediately following the conference session, the presenters expounded on the future of multicore chips with respect to education, programming languages, operating systems, and design automation.