One step self-aligned multilayer patterning process for the fabrication of organic complementary circuits in combination with inkjet printing

Recent development of solution processable organic semiconductors delineates the emergence of a new generation of air-stable, high performance p- and n-type materials. This makes it indeed possible for printed organic complementary circuits (CMOS) to be used in real applications. The main technical bottleneck for organic CMOS to be adopted as the next generation organic integrated circuit is how to deposit and pattern both p- and n-type semiconductor materials with high resolutions at the same time. It represents a significant technical challenge, especially if it can be done for multiple layers without mask alignment. In this paper, we propose a one-step self-aligned fabrication process which allows the deposition and high resolution patterning of functional layers for both p- and n-channel thin film transistors (TFTs) simultaneously. All the dimensional information of the device components is featured on a single imprinting stamp, and the TFT-channel geometry, electrodes with different work functions, p- and n-type semiconductors and effective gate dimensions can all be accurately defined by one-step imprinting and the subsequent pattern transfer process. As an example, we have demonstrated an organic complementary inverter fabricated by 3D imprinting in combination with inkjet printing and the measured electrical characteristics have validated the feasibility of the novel technique. © 2012 Elsevier B.V. All rights reserved.

Improving LVCSR system combination using neural network language model cross adaptation

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. The standard approach involves only cross adapting acoustic models. To fully exploit the complimentary features among sub-systems, language model (LM) cross adaptation techniques can be used. Previous research on multi-level n-gram LM cross adaptation is extended to further include the cross adaptation of neural network LMs in this paper. Using this improved LM cross adaptation framework, significant error rate gains of 4.0%-7.1% relative were obtained over acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. Copyright © 2011 ISCA.

Control of a shock-wave/boundary-layer interaction and subsequent subsonic diffuser using a combination of vortex generators and bleed

An experimental investigation has been undertaken in which vortex generators (VGs) have been employed to inhibit boundary-layer separation produced by the combined adversepressure- gradient of a terminal shock-wave and subsonic diffuser. This setup has been developed as part of a program to produce a more inlet relevant flow-field using a small-scale wind tunnel than previous studies. The resulting flow is dominated by large-scale separation, and as such, is thought to be a good test-bed for flow control. In this investigation, VGs have been added to determine their potential for shock-induced separation mitigation. In line with previous studies, it was observed that the application of VGs alone was not able to significantly alleviate separation overall, because enlarged corner separations was observed. Only when control of the corner separations using corner bleed was employed alongside centre-span control using VGs was a significant improvement in both wall pressure recovery (6% increase) and stagnation pressure recovery (2.4% increase) observed. Copyright © 2012 by the American Institute of Aeronautics and Astronautics, Inc.

Language model cross adaptation for LVCSR system combination

State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple sub-systems that may even be developed at different sites. Cross system adaptation, in which model adaptation is performed using the outputs from another sub-system, can be used as an alternative to hypothesis level combination schemes such as ROVER. Normally cross adaptation is only performed on the acoustic models. However, there are many other levels in LVCSR systems' modelling hierarchy where complimentary features may be exploited, for example, the sub-word and the word level, to further improve cross adaptation based system combination. It is thus interesting to also cross adapt language models (LMs) to capture these additional useful features. In this paper cross adaptation is applied to three forms of language models, a multi-level LM that models both syllable and word sequences, a word level neural network LM, and the linear combination of the two. Significant error rate reductions of 4.0-7.1% relative were obtained over ROVER and acoustic model only cross adaptation when combining a range of Chinese LVCSR sub-systems used in the 2010 and 2011 DARPA GALE evaluations. © 2012 Elsevier Ltd. All rights reserved.

Shock wave/boundary-layer interaction control using a combination of vortex generators and bleed

To investigate whether vortex generators can be an effective form of passive flow control an experimental investigation has been conducted in a small-scale wind tunnel. With specific emphasis on supersonic inlet applications flow separation was initiated using a combined terminal shock wave and subsonic diffuser: a configuration that has been developed as a part of a program to produce a more inlet-relevant flowfield in a small-scale wind tunnel than previous studies. When flow control was initially introduced little overall flow improvement was obtained as the losses tended to be redistributed instead of removed. It became apparent that there existed a strong coupling between the center-span flow and the corner flows. As a consequence, only when flow control was applied to both the corner flows and center-span flow was a significant flow improvement obtained. When corner suction and center-span vortex generators were employed in tandem separation was much reduced and wall-pressure and stagnation pressure were notably improved. As a result, when applied appropriately, it is thought that vortex generators do have the potential to reduce the dependence on boundary-layer bleed for the purpose of separation suppression. Copyright © 2012 by Neil Titchener and Holger Babinsky. Published by the American Institute of Aeronautics and Astronautics, Inc.

Design of diesel smoke feedback control using a combination of PI control algorithm and performance optimization

A novel smoke sensor was used to realize smoke feedback control on a diesel engine. The controller design based on a combination of PI control algorithm and the engine performance optimization is described. Experimental results demonstrate how this control system behave to meet both of the speed and smoke requirements during engine transients.

System combination and score normalization for spoken term detection

Spoken content in languages of emerging importance needs to be searchable to provide access to the underlying information. In this paper, we investigate the problem of extending data fusion methodologies from Information Retrieval for Spoken Term Detection on low-resource languages in the framework of the IARPA Babel program. We describe a number of alternative methods improving keyword search performance. We apply these methods to Cantonese, a language that presents some new issues in terms of reduced resources and shorter query lengths. First, we show score normalization methodology that improves in average by 20% keyword search performance. Second, we show that properly combining the outputs of diverse ASR systems performs 14% better than the best normalized ASR system. © 2013 IEEE.

Paraphrastic language models and combination with neural network language models

In natural languages multiple word sequences can represent the same underlying meaning. Only modelling the observed surface word sequence can result in poor context coverage, for example, when using n-gram language models (LM). To handle this issue, paraphrastic LMs were proposed in previous research and successfully applied to a US English conversational telephone speech transcription task. In order to exploit the complementary characteristics of paraphrastic LMs and neural network LMs (NNLM), the combination between the two is investigated in this paper. To investigate paraphrastic LMs' generalization ability to other languages, experiments are conducted on a Mandarin Chinese broadcast speech transcription task. Using a paraphrastic multi-level LM modelling both word and phrase sequences, significant error rate reductions of 0.9% absolute (9% relative) and 0.5% absolute (5% relative) were obtained over the baseline n-gram and NNLM systems respectively, after a combination with word and phrase level NNLMs. © 2013 IEEE.

Site-directed gene integration in transgenic zebrafish mediated by cre recombinase using a combination of mutant Lox sites

With current gene-transfer techniques in fish, insertion of DNA into the genome occurs randomly and in many instances at multiple sites. Associated position effects, copy number differences, and multiple gene interactions make gene expression experiments difficult to interpret and fish phenotype less predictable. To meet different fish engineering needs, we describe here a gene targeting model in zebrafish. At first, four target zebrafish lines, each harboring a single genomic lox71 target site, were generated by zebrafish transgenesis. The zygotes of transgenic zebrafish lines were coinjected with capped Cre mRNA and a knockin vector pZklox66RFP. Site-specific integration event happened from one target zebrafish line. In this line two integrant zebrafish were obtained from more than 80,000 targeted embryos (integrating efficiency about 10(-4) to 10(-5)) and confirmed to have a sole copy of the integrating DNA at the target genome site. Genomic polymerase chain reaction analysis and DNA sequencing verified the correct gene target events where lox71 and lox66 have accurately recombined into double mutant lox72 and wild-type loxP. Each integrant zebrafish chosen for analysis harbored the transgene rfp at the designated egfp concatenates. Although the Cre-mediated recombination is site specific, it is dependent on a randomly placed target site. That is, a genomic target cannot be preselected for integration based solely on its sequence. Conclusively, an rfp reporter gene was successfully inserted into the egfp target locus of zebrafish genome by Cre-lox-mediated recombination. This site-directed knockin system using the lox71/lox66 combination should be a promising gene-targeting platform serving various purposes in fish genetic engineering.

Using the moving window incorporated neural network to forecast the population behavior of Nostocales spp. in the River Darling, Australia

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical populations of Nostocales spp. in the River Darling, Australia. Freshwater ecosystems are more likely to be nonstationary, instead of stationary. Nonstationarity implies that only the near past behaviors could forecast the near future for the system. However, nonstionarity was not considered seriously in previous research efforts for modeling and predicting algal population behaviors. Therefore the moving window technique was incorporated with radial basis function neural network (RBFNN) approach to deal with nonstationarity when modeling and forecasting the population behaviors of Nostocales spp. in the River Darling. The results showed that the RBFNN model could predict the timing and magnitude of algal blooms of Nostocales spp. with high accuracy. Moreover, a combined model based on individual RBFNN models was implemented, which showed superiority over the individual RBFNN models. Hence, the combined model was recommended for the modeling and forecasting of the phytoplankton populations, especially for the forecasting.

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Comparison and combination of several stress relief methods for cubic boron nitride films deposited by ion beam assisted deposition

Cubic boron nitride (c-BN) films were prepared by ion beam assisted deposition (IBAD) technique, and the stresses were primary estimated by measuring the frequency shifts in the infrared-absorption peaks of c-BN samples. To test the possible effects of other factors, dependencies of the c-BN transversal optical mode position on film thickness and c-BN content were investigated. Several methods for reducing the stress of c-BN films including annealing, high temperature deposition, two-stage process, and the addition of a small amount of Si were studied, in which the c-BN films with similar thickness and cubic phase content were used to evaluate the effects of the various stress relief methods. It was shown that all the methods can reduce the stress in c-BN films to various extents. Especially, the incorporation of a small amount of Si (2.3 at.%) can result in a remarkable stress relief from 8.4 to similar to 3.6 GPa whereas the c-BN content is nearly unaffected, although a slight degradation of the c-BN crystallinity is observed. The stress can be further reduced down below I GPa by combination of the addition of Si with the two-stage deposition process. (c) 2008 Elsevier B.V. All rights reserved.

Optical characteristics of InAs quantum dots capped with short period GaAs/InAs superlattices and InGaAs combination layers

Long wavelength light emission was realized by capping InAs quantum dots (QDs) with short period GaAs/InAs superlattices (SLs) and an InGaAs strain-reducing layer (SRL). The optical properties were systematically investigated by photoluminescence tests. With increasing the periods of SLs, the emission wavelength of InAs QDs shifts from 1.27 to 1.53 mum. We explain the redshift as a result of the increased QD height with the SLs and the reduced strain in the dot caused by InGaAs SRL. (C) 2004 Published by Elsevier Ltd.