Customizing the technology roadmapping technique for software companies

Software importance keeps growing fast and consistently for many organizations. The growth of software functionality in manufactured products and the emergence of digital media, convergent spaces including digital content, software, and multi-channels to the market, are recent examples of organizational changes where software assumed a central position for the corporate strategy. This paper analyzes the alignment between strategic objectives and software development processes at software companies and proposes a methodology to ensure that development processes are aligned with the corporate capabilities required to exploit future market opportunities. The methodology includes the categorization of different software companies according to their core capabilities and the customization of the technology roadmapping technique for software companies. The research process included the realization of case studies and a survey. (c) 2006 PICMET.

Fast L0-based sparse signal recovery

This paper develops an algorithm for finding sparse signals from limited observations of a linear system. We assume an adaptive Gaussian model for sparse signals. This model results in a least square problem with an iteratively reweighted L2 penalty that approximates the L0-norm. We propose a fast algorithm to solve the problem within a continuation framework. In our examples, we show that the correct sparsity map and sparsity level are gradually learnt during the iterations even when the number of observations is reduced, or when observation noise is present. In addition, with the help of sophisticated interscale signal models, the algorithm is able to recover signals to a better accuracy and with reduced number of observations than typical L1-norm and reweighted L1 norm methods. ©2010 IEEE.

BarraCUDA - a fast short read sequence aligner using graphics processing units.

BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

Fast-switching phase gratings using in-plane addressed short-pitch polymer stabilized chiral nematic liquid crystals

We demonstrate a fast-switching (sub-millisecond) phase grating based upon a polymer stabilized short-pitch chiral nematic liquid crystal that is electrically addressed using in-plane electric fields. The combination of the short-pitch and the polymer stabilization enables the diffraction pattern to be switched on and off reversibly in 600 μs. Results are presented on the far-field diffraction pattern along with the intensity of the diffraction orders as a function of the applied electric field and the response times. © 2011 American Institute of Physics.

Gaussian processes for fast policy optimisation of POMDP-based dialogue managers

Modelling dialogue as a Partially Observable Markov Decision Process (POMDP) enables a dialogue policy robust to speech understanding errors to be learnt. However, a major challenge in POMDP policy learning is to maintain tractability, so the use of approximation is inevitable. We propose applying Gaussian Processes in Reinforcement learning of optimal POMDP dialogue policies, in order (1) to make the learning process faster and (2) to obtain an estimate of the uncertainty of the approximation. We first demonstrate the idea on a simple voice mail dialogue task and then apply this method to a real-world tourist information dialogue task. © 2010 Association for Computational Linguistics.

Cold-gas chemical vapor deposition to identify the key precursor for rapidly growing vertically-aligned single-wall and few-wall carbon nanotubes from pyrolyzed ethanol

Vertically-aligned carbon nanotubes (VA-CNTs) were rapidly grown from ethanol and their chemistry has been studied using a "cold-gas" chemical vapor deposition (CVD) method. Ethanol vapor was preheated in a furnace, cooled down and then flowed over cobalt catalysts upon ribbon-shaped substrates at 800 °C, while keeping the gas unheated. CNTs were obtained from ethanol on a sub-micrometer scale without preheating, but on a millimeter scale with preheating at 1000 °C. Acetylene was predicted to be the direct precursor by gas chromatography and gas-phase kinetic simulation, and actually led to millimeter-tall VA-CNTs without preheating when fed with hydrogen and water. There was, however a difference in CNT structure, i.e. mainly few-wall tubes from pyrolyzed ethanol and mainly single-wall tubes for unheated acetylene, and the by-products from ethanol pyrolysis possibly caused this difference. The "cold-gas" CVD, in which the gas-phase and catalytic reactions are separately controlled, allowed us to further understand CNT growth. © 2012 Elsevier Ltd. All rights reserved.

Safety implications of reactivity variations in fast thorium ADSRs

Nuclear power generation offers a reliable, low-impact and large-scale alternative to fossil fuels. However, concerns exist over the safety and sustainability of this method of power production, and it remains unpopular with some governments and pressure groups throughout the world. Fast thorium fuelled accelerator-driven sub-critical reactors (ADSRs) offer a possible route to providing further re-assurance regarding these concerns on account of their properties of enhanced safety through sub-critical operation combined with reduced actinide waste production from the thorium fuel source. The appropriate sub-critical margin at which these reactors should operate is the subject of continued debate. Commercial interests favour a small sub-critical margin in order to minimise the size of the accelerator needed for a given power output, whilst enhanced safety would be better satisfied through larger sub-critical margins to further minimise the possibility of a criticality excursion. Against this background, this paper examines some of the issues affecting reactor safety inherent within thorium fuel sources resulting from the essential Th90232→Th90233→Pa91233→U92233 breeding chain. Differences in the decay half-lives and fission and capture cross-sections of 233Pa and 233U can result in significant changes in the reactivity of the fuel following changes in the reactor power. Reactor operation is represented using a homogeneous lumped fast reactor model that can simulate the evolution of actinides and reactivity variations to first-order accuracy. The reactivity of the fuel is shown to increase significantly following a loss of power to the accelerator. Where the sub-critical operating margins are small this can result in a criticality excursion unless some form of additional intervention is made, for example through the insertion of control rods. © 2012 Elsevier Ltd. All rights reserved.

A fast 600-V Tandem PiN Schottky (TPS) rectifier with ultra-low on-state voltage

The Tandem PiN Schottky (TPS) rectifier features lowly-doped p-layers in both active and termination regions, and is applied in 600-V rating for the first time. In the active region, the Schottky contact is in series connection with a transparent p-layer, leading to a superior forward performance than the conventional diodes. In addition, due to the benefit of moderate hole injection from the p-layer, the TPS offers a better trade-off between the on-state voltage and the switching speed. The active p-layer also helps to stabilise the Schottky contact, and hence the electrical data distributions are more concentrated. Regarding the floating p-layer in the termination region, its purpose is to reduce the peak electric fields, and the TPS demonstrates a high breakdown voltage with a compact termination width, less than 70% of the state-of-the-art devices on the market. Experimental results have shown that the 600-V TPS rectifier has an ultra-low on-state voltage of 0.98 V at 250 A/cm 2, a fast turn-off time of 75 ns by the standard RG1 test (I F=0.5A, I R=1A, and I RR=0.25A) and a breakdown voltage over 720 V. It is noteworthy that the p-layers in the active and termination regions can be formed at no extra cost for the use of self-alignment process. © 2012 IEEE.

Making a shallow network deep: Conversion of a boosting classifier into a decision tree by boolean optimisation

This paper presents a novel way to speed up the evaluation time of a boosting classifier. We make a shallow (flat) network deep (hierarchical) by growing a tree from decision regions of a given boosting classifier. The tree provides many short paths for speeding up while preserving the reasonably smooth decision regions of the boosting classifier for good generalisation. For converting a boosting classifier into a decision tree, we formulate a Boolean optimization problem, which has been previously studied for circuit design but limited to a small number of binary variables. In this work, a novel optimisation method is proposed for, firstly, several tens of variables i.e. weak-learners of a boosting classifier, and then any larger number of weak-learners by using a two-stage cascade. Experiments on the synthetic and face image data sets show that the obtained tree achieves a significant speed up both over a standard boosting classifier and the Fast-exit-a previously described method for speeding-up boosting classification, at the same accuracy. The proposed method as a general meta-algorithm is also useful for a boosting cascade, where it speeds up individual stage classifiers by different gains. The proposed method is further demonstrated for fast-moving object tracking and segmentation problems. © 2011 Springer Science+Business Media, LLC.

The Silent Period of Evidence Integration in Fast Decision Making

In a typical experiment on decision making, one out of two possible stimuli is displayed and observers decide which one was presented. Recently, Stanford and colleagues (2010) introduced a new variant of this classical one-stimulus presentation paradigm to investigate the speed of decision making. They found evidence for "perceptual decision making in less than 30 ms". Here, we extended this one-stimulus compelled-response paradigm to a two-stimulus compelled-response paradigm in which a vernier was followed immediately by a second vernier with opposite offset direction. The two verniers and their offsets fuse. Only one vernier is perceived. When observers are asked to indicate the offset direction of the fused vernier, the offset of the second vernier dominates perception. Even for long vernier durations, the second vernier dominates decisions indicating that decision making can take substantial time. In accordance with previous studies, we suggest that our results are best explained with a two-stage model of decision making where a leaky evidence integration stage precedes a race-to-threshold process. © 2013 Rüter et al.

Towards a fast electro-thermo-mechanical IGBT/Diode simulation framework for design of reliable power electronic converters

This paper describes a methodology that enables fast and reasonably accurate prediction of the reliability of power electronic modules featuring IGBTs and p-i-n diodes, by taking into account thermo-mechanical failure mechanisms of the devices and their associated packaging. In brief, the proposed simulation framework performs two main tasks which are tightly linked together: (i) the generation of the power devices' transient thermal response for realistic long load cycles and (ii) the prediction of the power modules' lifetime based on the obtained temperature profiles. In doing so the first task employs compact, physics-based device models, power losses lookup tables and polynomials and combined material-failure and thermal modelling, while the second task uses advanced reliability tests for failure mode and time-to-failure estimation. The proposed technique is intended to be utilised as a design/optimisation tool for reliable power electronic converters, since it allows easy and fast investigation of the effects that changes in circuit topology or devices' characteristics and packaging have on the reliability of the employed power electronic modules. © 2012 IEEE.