Vector-extrapolated fast maximum likelihood estimation algorithms for emission tomography

A new class of fast maximum-likelihood estimation (MLE) algorithms for emission computed tomography (ECT) is developed. In these cyclic iterative algorithms, vector extrapolation techniques are integrated with the iterations in gradient-based MLE algorithms, with the objective of accelerating the convergence of the base iterations. This results in a substantial reduction in the effective number of base iterations required for obtaining an emission density estimate of specified quality. The mathematical theory behind the minimal polynomial and reduced rank vector extrapolation techniques, in the context of emission tomography, is presented. These extrapolation techniques are implemented in a positron emission tomography system. The new algorithms are evaluated using computer experiments, with measurements taken from simulated phantoms. It is shown that, with minimal additional computations, the proposed approach results in substantial improvement in reconstruction.     

Learning Sparse Feature Representations Using Probabilistic Quadtrees and Deep Belief Nets

Learning sparse feature representations is a useful instrument for solving an unsupervised learning problem. In this paper, we present three labeled handwritten digit datasets, collectively called n-MNIST by adding noise to the MNIST dataset, and three labeled datasets formed by adding noise to the offline Bangla numeral database. Then we propose a novel framework for the classification of handwritten digits that learns sparse representations using probabilistic quadtrees and Deep Belief Nets. On the MNIST, n-MNIST and noisy Bangla datasets, our framework shows promising results and outperforms traditional Deep Belief Networks.     

Multi-stage deep probabilistic prediction for travel demand

Applied Intelligence - Accurate demand prediction is an essential component of any decision support system for smart vehicle dispatching. However, predicting real time demand at the...     

Integration of Ceramics Research with the Development of a Microsystem

Rapid implementation of new materials into engineering systems may require a paradigm shift in our approach to materials research. One option is to obtain fundamental material properties from experimental systems that can also serve as devices. This concept is applied to the measurement of Young's modulus of a novel ceramic, a polymer-derived silicon carbonitride (SiCN), directly from the performance of a microelectromechanical system (MEMS) device. The device is an electrostatic actuator. The flexure resistance of the arms of the actuator is measured and analyzed for the elastic modulus of SiCN. The comparison between theory and experiment yields a value for Young's modulus in the range 130–155 GPa.     

Chromium(VI) adsorption from aqueous solution by Hevea Brasilinesis sawdust activated carbon

Adsorption capacity of Cr(VI) onto Hevea Brasilinesis (Rubber wood) sawdust activated carbon was investigated in a batch system by considering the effects of various parameters like contact time, initial concentration, pH and temperature. Cr(VI) removal is pH dependent and found to be maximum at pH 2.0. Increases in adsorption capacity with increase in temperature indicate that the adsorption reaction is endothermic. Based on this study, the thermodynamic parameters like standard Gibb's free energy (DeltaG degrees ), standard enthalpy (DeltaH degrees ) and standard entropy (DeltaS degrees ) were evaluated. Adsorption kinetics of Cr(VI) ions onto rubber wood sawdust activated carbon were analyzed by pseudo first-order and pseudo second-order models. Pseudo second-order model was found to explain the kinetics of Cr(VI) adsorption most effectively. Intraparticle diffusion studies at different temperatures show that the mechanism of adsorption is mainly dependent on diffusion. The rate of intraparticle diffusion, film diffusion coefficient and pore diffusion coefficient at various temperatures were evaluated. The Langmuir, Freundlich and Temkin isotherm were used to describe the adsorption equilibrium studies of rubber wood sawdust activated carbon at different temperatures. Langmuir isotherm shows better fit than Freundlich and Temkin isotherm in the temperature range studied. The result shows that the rubber wood sawdust activated carbon can be efficiently used for the treatment of wastewaters containing chromium as a low cost alternative compared to commercial activated carbon and other adsorbents reported.     

Optimum combined test plans for systems and components

Since mathematical models based on component reliabilities are frequently used for prediction of system reliability, it stands to reason that cost-effective inferences on the reliability of a system could be made on the basis of tests of its constituent components. Prior research in the area of system-based component testing has for the most part addressed the development of plans that test only the components. From a practitioner's point of view, this is an issue of concern since system failures are often caused by imperfect interfaces and other causes that are not directly attributable to component failures. The exclusion of system tests may thus be an erroneous approach. This paper addresses the development of test plans that explicitly consider the possibility of interface failures. The paper analyzes a series system to determine when testing should be performed on the system alone, on the components only, and on both, depending on test costs and interface reliabilities. Optimum test plans are: derived by solving a two-stage mathematical program.     

Sodium–Bioglass/Polythene Composites

We present the studies conducted on sodium–bioglass/polythene (Na–BG/PE) composites and their bioactivity in simulated body fluid (SBF). Several compositions of Na–BG/PE composites were made by hot pressing and the activity studies of the samples were carried out by immersing the composites in SBF for periods of 7, 14, and 21 days. The activity of the samples was confirmed by the cauliflower-like growth of phosphates on the surface of the samples observed in an environmental scanning electron microscope and further confirmed by energy-dispersive X-ray spectrometry (EDS). X-ray diffraction showed the presence of various types of calcium phosphate phases. Ionic movement was observed by inductively coupled plasma atomic emission spectroscopy from the sample to the SBF solution and the reverse trend was observed on the surface of the sample by EDS. Modulus of rupture of the composites increased when the polymer content was increased up to 30% by weight of polythene, beyond which the processing of composites became difficult.     

Power conscious CAD tools and methodologies: a perspective

Power consumption is rapidly becoming an area of growing concern in IC and system design houses. Issues such as battery life, thermal limits, packaging constraints and cooling options are becoming key factors in the success of a product. As a consequence, IC and system designers are beginning to see the impact of power on design area, design speed, design complexity and manufacturing cost. While process and voltage scaling can achieve significant power reductions, these are expensive strategies that require industry momentum, that only pay off in the long run. Technology independent gains for power come from the area of design for low power which has a much higher return on investment (ROI). But low power design is not only a new area but is also a complex endeavour requiring a broad range of synergistic capabilities from architecture/microarchitecture design to package design. It changes traditional IC design from a two-dimensional problem (Area/performance) to a three-dimensional one (Area/Performance/Power). This paper describes the CAD tools and methodologies required to effect efficient design for low power. It is targeted to a wide audience and tries to convey an understanding of the breadth of the problem. It explains the state of the art in CAD tools and methodologies. The paper is written in the form of a tutorial, making it easy to read by keeping the technical depth to a minimum while supplying a wealth of technical references. Simultaneously the paper identifies unresolved problems in an attempt to incite research in these areas. Finally an attempt is made to provide commercial CAD tool vendors with an understanding of the needs and time frames for new CAD tools supporting low power design     

Minimal sensor integrity: Measuring the vulnerability of sensor grids

Given the increasing importance of optimal sensor deployment for battlefield strategists, the converse problem of reacting to a particular deployment by an enemy is equally significant and not yet addressed in a quantifiable manner in the literature. We address this issue by modeling a two stage game in which the opponent deploys sensors to cover a sensor field and we attempt to maximally reduce his coverage at minimal cost. In this context, we introduce the concept of minimal sensor integrity which measures the vulnerability of any sensor deployment. We find the best response by quantifying the merits of each response. While the problem of optimally deploying sensors subject to coverage constraints is NP-complete [Chakrabarty et al., IEEE Trans. Comput., to appear], in this paper we show that the best response (i.e., the maximum vulnerability) can be computed in polynomial time for sensors with arbitrary coverage capabilities deployed over points in any dimensional space. In the special case when sensor coverages form an interval graph (as in a linear grid), we describe a better O(min(M²,NM)) dynamic programming algorithm.