A prototype 3D optically interconnected neural network

We report the implementation of a prototype three-dimensional (3D) optoelectronic neural network that combines free-space optical interconnects with silicon-VLSI-based optoelectronic circuits. The prototype system consists of a 16-node input, 4-neuron hidden, and a single-neuron output layer, where the denser input-to-hidden-layer connections are optical. The input layer uses PLZT light modulators to generate optical outputs which are distributed over an optoelectronic neural network chip through space-invariant holographic optical interconnects. Optical interconnections provide negligible fan-out delay and allow compact, purely on-chip electronic H-tree type fan-in structure. The small prototype system achieves a measured 8-bit electronic fan-in precision and a calculated maximum speed of 640 million interconnections per second. The system was tested using synaptic weights learned off system and was shown to distinguish any vertical line from any horizontal one in an image of 4×4 pixels. New, more efficient light detector and small-area analog synapse circuits and denser optoelectronic neuron layouts are proposed to scale up the system. A high-speed, feed-forward optoelectronic synapse implementation density of up to 10⁴/cm² seems feasible using new synapse design. A scaling analysis of the system shows that the optically interconnected neural network implementation can provide higher fan-in speed and lower power consumption characteristics than a purely electronic, crossbar-based neural network implementation     

Microstructural Investigation on Failure of Internal Drive Shaft

17-4 PH stainless steel is used as internal drive shaft material in liquid engine pumps. One of the drive shafts failed during operation. The shaft pieces were in contact for short duration after failure, which has resulted in abrasion of fractured surfaces. Samples from the location of failure were taken, and investigation of the failure was carried out using optical and scanning electron microscopy. The microstructural analysis of the material and fractographic analysis of the fractured surface show that the failure was caused by excessive torsion.     

A.c. conductivity studies on the silver molybdo-arsenate glassy system

A new quaternary fast-ion conducting silver molybdo-arsenate [Agl-Ag₂O-(MoO₃ + As₂O₅)] (SMA) glassy system has been prepared using the melt-quenching technique for various dopant salt (Agl) concentrations by fixing the formers (MoO₃ + As₂O₅) composition and the modifier (Ag₂O) to formers (M/F) ratio. The prepared compounds were characterized by X-ray diffraction. The impedance measurements were made on different Agl compositions of the SMA glasses as a function of frequency (6.5 Hz–65 kHz) and temperature (303–343 K), using the Solatron frequency-response analyser (model 1250). The bulk conductivity and the appropriate physical model (equivalent circuit) of the SMA glass were obtained from the impedance analysis. The a.c. conductivity was calculated for different Agl compositions of SMA glasses at various temperatures and the obtained a.c. conductivity results were analysed using Jonscher's Universal Law. The conduction mechanism for the highest conducting SMA glassy compound has been explained using the diffusion path model.     

Inelastic post-buckling analysis of truss structures by dynamic relaxation method

The paper presents the inelastic post-buckling analysis of truss structures by the Dynamic Relaxation (DR) method. A simplified inelastic finite element formulation for truss element and new algorithms are proposed for Elastic Post-Buckling (EPB) analysis and Inelastic Post-Buckling (IEPB) analysis using the DR method. The post-buckling paths for elastic, EPB and IEPB analyses are completely traced using the variable-arc-length method. Four numerical examples are presented to illustrate the application of the proposed algorithms.     

Microstructural developments in Mg-Ti-PSZ systems

The microstructure of titania-added Mg-partially-stabilized zirconia (PSZ) is dramatically influenced by thermal treatments. Effects of various sintering, heat-treatment and thermal shock cycling parameters on the microstructure of the Mg-Ti-PSZ system are described. Conditions favourable for the growth of needle-like Ti-rich reinforcements in highly thermalshock-resistant Mg-Ti-PSZ ceramics are identified. TiO₂ seems to play a catalytic role in the formation of Zr-rich networks during high-temperature (1700°C) sintering of the Mg-Ti-PSZ system, quite similar to those found in Mg-PSZ, heat-treated above 1300 °C.     

Dynamic provisioning in multi-tenant service clouds

Cloud-based systems promise an on-demand service provisioning system along with a ??pay-as-you-use?? policy. In the case of multi-tenant systems this would mean dynamic creation of a tenant by integrating existing cloud-based services on the fly. Presently, dynamic creation of a tenant is handled by building the required components from scratch. Although multi-tenant systems help providers save cost by allocating multiple tenants to the same instance of an application, they incur huge reconfiguration costs. Cost and time spent on these reconfiguration activities can be reduced by re-constructing tenants from existing tenant configurations supported by service providers. Multi-tenant cloud-based systems also lack the facility of allowing clients to specify their requirements. Giving clients the flexibility to specify requirements helps them avoid spending an excessive amount of time and effort looking through a list of services, many of which might not be relevant to them. Moreover, dynamic provisioning in the cloud requires an integrated solution across the technology stack (software, platform and infrastructure) combining functional, non-functional and resource allocation requirements. Existing research works in the area of web service matching, although numerous, still fall short, since they usually consider each requirement type in isolation and cannot provide an integrated solution. To that end, in this paper we investigate the features needed for dynamic service provisioning on the cloud. We propose a novel User Interface-Tenant Selector-Customizer (UTC) model and approach, which enables cloud-based services to be systematically modeled and provisioned as variants of existing service tenants in the cloud. Our approach considers functional, non-functional and resource allocation requirements, which are explicitly specified by the client via the user interface component of the model. To the best of our knowledge, ours is the first such integrated approach. We illustrate our ideas using a realistic running example, and also present a proof-of-concept prototype built using IBM??s Rational Software Architect modeling tool. We also present experimental results demonstrating the applicability of our matching algorithm. Our results show significant reduction in matching time with the help of an elimination process that reduces the search space needed for performing matching.     

Hydrogen production from used lubricating oils

Used lubricating oils (lube oils) are generated throughout the year and collected in central locations in many communities. Disposing lube oil in an improper manner contaminates environment to a great degree. Used lube oil can be valuable as a re-refined lubricant or as an energy source. Lube oil is a complex mixture of aliphatic and polycyclic hydrocarbons formulated to withstand high service temperatures in internal combustion engines. Both synthetic and mineral oils contain a high concentration of hydrogen (about 13–14 wt%). At the Florida Solar Energy Center, we have developed a process that converts lube oils to hydrogen and other valuable low molecular weight hydrocarbons. The lube oil reformation experiments were carried out using several commercially available dehydrogenation catalysts at a range of reactor temperatures and pressures, residence times and steam to carbon ratios. In this paper, the data obtained to date and the results are presented and discussed.     

Pricing strategies with reference effects in competitive industries

This paper examines the effect of reference prices on companies operating within competitive industries. We confirm that even with competition, firms optimally price high in the short term to generate a high reference price and then decrease this price over time. Competitors' prices converge toward each other over time, emphasizing the short‐term nature of reference prices. We then show that pricing optimally to take advantage of reference prices generates a positive externality for other firms in an industry, such that competitors may generate higher profit. The longer the focus of a given firm, the more profit the firm generates, but less relative to its competitors. This arises because the externalities created through pricing high to increase reference prices outweigh the benefits of the higher reference prices themselves. If pricing managers are compensated relative to their competition, this suggests that short‐termism may be implicitly encouraged to the detriment of profit.     

Mixing matrix estimation using discriminative clustering for blind source separation

Mixing matrix estimation in instantaneous blind source separation (BSS) can be performed by exploiting the sparsity and disjoint orthogonality of source signals. As a result, approaches for estimating the unknown mixing process typically employ clustering algorithms on the mixtures in a parametric domain, where the signals can be sparsely represented. In this paper, we propose two algorithms to perform discriminative clustering of the mixture signals for estimating the mixing matrix. For the case of overdetermined BSS, we develop an algorithm to perform linear discriminant analysis based on similarity measures and combine it with K-hyperline clustering. Furthermore, we propose to perform discriminative clustering in a high-dimensional feature space obtained by an implicit mapping, using the kernel trick, for the case of underdetermined source separation. Using simulations on synthetic data, we demonstrate the improvements in mixing matrix estimation performance obtained using the proposed algorithms in comparison to other clustering methods. Finally we perform mixing matrix estimation from speech mixtures, by clustering single source points in the time-frequency domain, and show that the proposed algorithms achieve higher signal to interference ratio when compared to other baseline algorithms.