Robust named entity detection from optical character recognition output

In this paper, we focus on information extraction from optical character recognition (OCR) output. Since the content from OCR inherently has many errors, we present robust algorithms for information extraction from OCR lattices instead of merely looking them up in the top-choice (1-best) OCR output. Specifically, we address the challenge of named entity detection in noisy OCR output and show that searching for named entities in the recognition lattice significantly improves detection accuracy over 1-best search. While lattice-based named entity (NE) detection improves NE recall from OCR output, there are two problems with this approach: (1) the number of false alarms can be prohibitive for certain applications and (2) lattice-based search is computationally more expensive than 1-best NE lookup. To mitigate the above challenges, we present techniques for reducing false alarms using confidence measures and for reducing the amount of computation involved in performing the NE search. Furthermore, to demonstrate that our techniques are applicable across multiple domains and languages, we experiment with optical character recognition systems for videotext in English and scanned handwritten text in Arabic.     

Randomized constraint solvers: a comparative study

The complexity of constraints is a major obstacle for constraint-based software verification. Automatic constraint solvers are fundamentally incomplete: input constraints often build on some undecidable theory or some theory the solver does not support. This paper proposes and evaluates several randomized solvers to address this issue. We compared the effectiveness of a symbolic solver (CVC3), a random solver, two heuristic search solvers, and seven hybrid solvers (i.e. mix of random, symbolic, and heuristic solvers). We evaluated the solvers on a benchmark generated with a concolic execution of 9 subjects. The performance of each solver was measured by its precision, which is the fraction of constraints that the solver can find solution out of the total number of constraints that some solver can find solution. As expected, symbolic solving subsumes the other approaches for the 4 subjects that only generate decidable constraints. For the remaining 5 subjects, which contain undecidable constraints, the hybrid solvers achieved the highest precision (fraction of constraints that a solver can find a solution out of the total number of satisfiable constraints). We also observed that the solvers were complementary, which suggests that one should alternate their use in iterations of a concolic execution driver.     

Influence of pH on particle size and sensing response of chemically synthesized chromium oxide nanoparticles to alcohols

Nanoparticles of chromium oxide have been synthesized by following a co-precipitation route at various pH values of the precursor solution. Structural and morphological analysis were carried out by using XRD and TEM techniques which revealed that the size of nanoparticles synthesized at pH 9 was smaller as compared to those synthesized at other pH values. The thick films of synthesized samples were deposited on alumina substrate and their sensing response to methanol, ethanol and isopropanol was investigated at different operating temperatures. It was observed that all the sensors gave optimum response at 250 °C. It has been observed that sample prepared at pH 9, being a collection of smallest particles as compared to other samples, exhibited high sensing response to alcohol vapour. Sensor response of all the samples tested was significantly higher towards isopropanol vapour than towards methanol or ethanol.In the present study the effect of particle size on intergranular activation energy has been studied as well. It was found that smaller particles possess high activation energy and exhibit higher sensing response as compared to that of larger particles. This type of study may help in the selection of particle suitable for gas sensing.     

Lévy flight artificial bee colony algorithm

Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-based probabilistic approach for global optimisation. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. In the ABC, there is a high chance to skip the true solution due to its large step sizes. In order to balance between diversity and convergence in the ABC, a Lévy flight inspired search strategy is proposed and integrated with ABC. The proposed strategy is named as Lévy Flight ABC (LFABC) has both the local and global search capability simultaneously and can be achieved by tuning the Lévy flight parameters and thus automatically tuning the step sizes. In the LFABC, new solutions are generated around the best solution and it helps to enhance the exploitation capability of ABC. Furthermore, to improve the exploration capability, the numbers of scout bees are increased. The experiments on 20 test problems of different complexities and five real-world engineering optimisation problems show that the proposed strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.     

Formal Analysis of Multiparty Contract Signing

We analyze the multiparty contract-signing protocols of Garay and MacKenzie (GM) and of Baum and Waidner (BW). We use a finite-state tool, Mocha, which allows specification of protocol properties in a branching-time temporal logic with game semantics. While our analysis does not reveal any errors in the BW protocol, in the GM protocol we discover serious problems with fairness for four signers and an oversight regarding abuse-freeness for three signers. We propose a complete revision of the GM subprotocols in order to restore fairness.     

Fast and efficient extraction algorithm for high-speed interconnects with arbitrary boundaries

In this paper, we present an accurate and general interconnect model for planar transmission line interconnects with arbitrary boundary conditions. Based on the unified approach, we develop a SPICE-compatible parameter extraction algorithm that can be used in high-performance computer-aided-design applications. A range of multilayered interconnect geometries with arbitrary boundaries are analyzed. Different typical configurations of ground placement are considered to verify the applicability of this method. For all such cases, results are compared for admittance, line parameters, and delay giving physical insight on the effect of boundary conditions on them. Compared with existing industry standard numerical field-solvers, like HFSS, the proposed model demonstrates more than 10× speedup within 2% accuracy.     

SUSANS With Polarized Neutrons

Super Ultra-Small Angle Neutron Scattering (SUSANS) studies over wave vector transfers of 10^–4 nm^–1 to 10^–3 nm^–1 afford information on micrometer-size agglomerates in samples. Using a right-angled magnetic air prism, we have achieved a separation of ≈10 arcsec between ≈2 arcsec wide up- and down-spin peaks of 0.54 nm neutrons. The SUSANS instrument has thus been equipped with the polarized neutron option. The samples are placed in a uniform vertical field of 8.8 × 10⁴ A/m (1.1 kOe). Several magnetic alloy ribbon samples broaden the up-spin neutron peak significantly over the ±1.3 × 10^–3 nm^–1 range, while leaving the down-spin peak essentially unaltered. Fourier transforms of these SUSANS spectra corrected for the instrument resolution, yield micrometer-range pair distribution functions for up- and down-spin neutrons as well as the nuclear and magnetic scattering length density distributions in the samples.     

Note: Compact high voltage pulse transformer made using a capacitor bank assembled in the shape of primary

The experimental results of an air-core pulse transformer are presented, which is very compact (<10 Kg in weight) and is primed by a capacitor bank that is fabricated in such a way that the capacitor bank with its switch takes the shape of single-turn rectangular shaped primary of the transformer. A high voltage capacitor assembly (pulse-forming-line capacitor, PFL) of 5.1 nF is connected with the secondary of transformer. The transformer output voltage is 160 kV in its second peak appearing in less than 2 μS from the beginning of the capacitor discharge. The primary capacitor bank can be charged up to a maximum of 18 kV, with the voltage delivery of 360 kV in similar capacitive loads.     

Augmented photoelectrochemical response of CdS/ZnS quantum dots sensitized hematite photoelectrode

A visible light active and stable photoelectrode has been developed by depositing a passivating layer of ZnS QDs on CdS QDs sensitized hematite photoelectrode (Hematite‐CdS/ZnS) for PEC generation of hydrogen. Photoelectrochemical properties, in terms of stability and efficiency, have been investigated on the various hematite photoelectrodes sensitized with CdS QDs and CdS/ZnS QDs by varying number of SILAR cycles. I–V characteristics show that two layers of ZnS QDs deposited over three layers of CdS could enhance PEC response of hematite and efficiency by a factor of 3 and 11 respectively. Chronoamperometry measurement ensures that after adding a layer of ZnS QDs, CdS sensitized hematite film turns out to be a stable photoelectrode in the electrolyte. Prepared photoelectrodes have been characterized by XRD, SEM, HRTEM and UV–Vis spectrophotometer for various structural, morphological and optical properties to analyze PEC results. Mott–Schottky analysis and incident photon to current conversion efficiency (IPCE) measurements of sensitized hematite photoelectrode supported the improved PEC response of CdS/ZnS QDs sensitized hematite thin films. Copyright © 2016 John Wiley & Sons, Ltd.