An analysis of real time implementation of Fourier transform-based frequency recognition algorithms

Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

MIMO Wiener model identification for large scale fading of wireless mobile communications links

The large scale fading of wireless mobile communications links is modelled assuming the mobile receiver motion is described by a dynamic linear system in state-space. The geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A Wiener system subspace identification algorithm in conjunction with polynomial regression is used to identify a model from time-domain estimates of the field intensity assuming a multitude of emitters and an antenna array at the receiver end.

A comparative study of Java and C performance in two large-scale parallel applications

In the 1990s the Message Passing Interface Forum defined MPI bindings for Fortran, C, and C++. With the success of MPI these relatively conservative languages have continued to dominate in the parallel computing community. There are compelling arguments in favour of more modern languages like Java. These include portability, better runtime error checking, modularity, and multi-threading. But these arguments have not converted many HPC programmers, perhaps due to the scarcity of full-scale scientific Java codes, and the lack of evidence for performance competitive with C or Fortran. This paper tries to redress this situation by porting two scientific applications to Java. Both of these applications are parallelized using our thread-safe Java messaging system—MPJ Express. The first application is the Gadget-2 code, which is a massively parallel structure formation code for cosmological simulations. The second application uses the finite-domain time-difference method for simulations in the area of computational electromagnetics. We evaluate and compare the performance of the Java and C versions of these two scientific applications, and demonstrate that the Java codes can achieve performance comparable with legacy applications written in conventional HPC languages. Copyright © 2009 John Wiley & Sons, Ltd.

Intelligent agents for fault tolerance: from multi-agent simulation to cluster-based implementation

Recent research in multi-agent systems incorporate fault tolerance concepts, but does not explore the extension and implementation of such ideas for large scale parallel computing systems. The work reported in this paper investigates a swarm array computing approach, namely 'Intelligent Agents'. A task to be executed on a parallel computing system is decomposed to sub-tasks and mapped onto agents that traverse an abstracted hardware layer. The agents intercommunicate across processors to share information during the event of a predicted core/processor failure and for successfully completing the task. The feasibility of the approach is validated by simulations on an FPGA using a multi-agent simulator, and implementation of a parallel reduction algorithm on a computer cluster using the Message Passing Interface.

Kinetic multi-layer model of aerosol surface and bulk chemistry (KM-SUB): the influence of interfacial transport and bulk diffusion on the oxidation of oleic acid by ozone

We present a novel kinetic multi-layer model that explicitly resolves mass transport and chemical reaction at the surface and in the bulk of aerosol particles (KM-SUB). The model is based on the PRA framework of gas-particle interactions (Poschl-Rudich-Ammann, 2007), and it includes reversible adsorption, surface reactions and surface-bulk exchange as well as bulk diffusion and reaction. Unlike earlier models, KM-SUB does not require simplifying assumptions about steady-state conditions and radial mixing. The temporal evolution and concentration profiles of volatile and non-volatile species at the gas-particle interface and in the particle bulk can be modeled along with surface concentrations and gas uptake coefficients. In this study we explore and exemplify the effects of bulk diffusion on the rate of reactive gas uptake for a simple reference system, the ozonolysis of oleic acid particles, in comparison to experimental data and earlier model studies. We demonstrate how KM-SUB can be used to interpret and analyze experimental data from laboratory studies, and how the results can be extrapolated to atmospheric conditions. In particular, we show how interfacial and bulk transport, i.e., surface accommodation, bulk accommodation and bulk diffusion, influence the kinetics of the chemical reaction. Sensitivity studies suggest that in fine air particulate matter oleic acid and compounds with similar reactivity against ozone (carbon-carbon double bonds) can reach chemical lifetimes of many hours only if they are embedded in a (semi-)solid matrix with very low diffusion coefficients (< 10(-10) cm(2) s(-1)). Depending on the complexity of the investigated system, unlimited numbers of volatile and non-volatile species and chemical reactions can be flexibly added and treated with KM-SUB. We propose and intend to pursue the application of KM-SUB as a basis for the development of a detailed master mechanism of aerosol chemistry as well as for the derivation of simplified but realistic parameterizations for large-scale atmospheric and climate models.

Kinetic multi-layer model of aerosol surface and bulk chemistry (KM-SUB): the influence of interfacial transport and bulk diffusion on the oxidation of oleic acid by ozone

We present a novel kinetic multi-layer model that explicitly resolves mass transport and chemical reaction at the surface and in the bulk of aerosol particles (KM-SUB). The model is based on the PRA framework of gas–particle interactions (P¨oschl et al., 5 2007), and it includes reversible adsorption, surface reactions and surface-bulk exchange as well as bulk diffusion and reaction. Unlike earlier models, KM-SUB does not require simplifying assumptions about steady-state conditions and radial mixing. The temporal evolution and concentration profiles of volatile and non-volatile species at the gas-particle interface and in the particle bulk can be modeled along with surface 10 concentrations and gas uptake coefficients. In this study we explore and exemplify the effects of bulk diffusion on the rate of reactive gas uptake for a simple reference system, the ozonolysis of oleic acid particles, in comparison to experimental data and earlier model studies. We demonstrate how KM-SUB can be used to interpret and analyze experimental data from laboratory stud15 ies, and how the results can be extrapolated to atmospheric conditions. In particular, we show how interfacial transport and bulk transport, i.e., surface accommodation, bulk accommodation and bulk diffusion, influence the kinetics of the chemical reaction. Sensitivity studies suggest that in fine air particulate matter oleic acid and compounds with similar reactivity against ozone (C=C double bonds) can reach chemical lifetimes of 20 multiple hours only if they are embedded in a (semi-)solid matrix with very low diffusion coefficients (10−10 cm2 s−1). Depending on the complexity of the investigated system, unlimited numbers of volatile and non-volatile species and chemical reactions can be flexibly added and treated with KM-SUB. We propose and intend to pursue the application of KM-SUB 25 as a basis for the development of a detailed master mechanism of aerosol chemistry as well as for the derivation of simplified but realistic parameterizations for large-scale atmospheric and climate models.

Technologies for biological containment of GM and Non-GM crops

International Perspective The development of GM technology continues to expand into increasing numbers of crops and conferred traits. Inevitably, the focus remains on the major field crops of soybean, maize, cotton, oilseed rape and potato with introduced genes conferring herbicide tolerance and/or pest resistance. Although there are comparatively few GM crops that have been commercialised to date, GM versions of 172 plant species have been grown in field trials in 31 countries. European Crops with Containment Issues Of the 20 main crops in the EU there are four for which GM varieties are commercially available (cotton, maize for animal feed and forage, and oilseed rape). Fourteen have GM varieties in field trials (bread wheat, barley, durum wheat, sunflower, oats, potatoes, sugar beet, grapes, alfalfa, olives, field peas, clover, apples, rice) and two have GM varieties still in development (rye, triticale). Many of these crops have hybridisation potential with wild and weedy relatives in the European flora (bread wheat, barley, oilseed rape, durum wheat, oats, sugar beet and grapes), with escapes (sunflower); and all have potential to cross-pollinate fields non-GM crops. Several fodder crops, forestry trees, grasses and ornamentals have varieties in field trials and these too may hybridise with wild relatives in the European flora (alfalfa, clover, lupin, silver birch, sweet chestnut, Norway spruce, Scots pine, poplar, elm, Agrostis canina, A. stolonifera, Festuca arundinacea, Lolium perenne, L. multiflorum, statice and rose). All these crops will require containment strategies to be in place if it is deemed necessary to prevent transgene movement to wild relatives and non-GM crops. Current Containment Strategies A wide variety of GM containment strategies are currently under development, with a particular focus on crops expressing pharmaceutical products. Physical containment in greenhouses and growth rooms is suitable for some crops (tomatoes, lettuce) and for research purposes. Aquatic bioreactors of some non-crop species (algae, moss, and duckweed) expressing pharmaceutical products have been adopted by some biotechnology companies. There are obvious limitations of the scale of physical containment strategies, addressed in part by the development of large underground facilities in the US and Canada. The additional resources required to grow plants underground incurs high costs that in the long term may negate any advantage of GM for commercial productioNatural genetic containment has been adopted by some companies through the selection of either non-food/feed crops (algae, moss, duckweed) as bio-pharming platforms or organisms with no wild relatives present in the local flora (safflower in the Americas). The expression of pharmaceutical products in leafy crops (tobacco, alfalfa, lettuce, spinach) enables growth and harvesting prior to and in the absence of flowering. Transgenically controlled containment strategies range in their approach and degree of development. Plastid transformation is relatively well developed but is not suited to all traits or crops and does not offer complete containment. Male sterility is well developed across a range of plants but has limitations in its application for fruit/seed bearing crops. It has been adopted in some commercial lines of oilseed rape despite not preventing escape via seed. Conditional lethality can be used to prevent flowering or seed development following the application of a chemical inducer, but requires 100% induction of the trait and sufficient application of the inducer to all plants. Equally, inducible expression of the GM trait requires equally stringent application conditions. Such a method will contain the trait but will allow the escape of a non-functioning transgene. Seed lethality (‘terminator’ technology) is the only strategy at present that prevents transgene movement via seed, but due to public opinion against the concept it has never been trialled in the field and is no longer under commercial development. Methods to control flowering and fruit development such as apomixis and cleistogamy will prevent crop-to-wild and wild-to-crop pollination, but in nature both of these strategies are complex and leaky. None of the genes controlling these traits have as yet been identified or characterised and therefore have not been transgenically introduced into crop species. Neither of these strategies will prevent transgene escape via seed and any feral apomicts that form are arguably more likely to become invasives. Transgene mitigation reduces the fitness of initial hybrids and so prevents stable introgression of transgenes into wild populations. However, it does not prevent initial formation of hybrids or spread to non-GM crops. Such strategies could be detrimental to wild populations and have not yet been demonstrated in the field. Similarly, auxotrophy prevents persistence of escapes and hybrids containing the transgene in an uncontrolled environment, but does not prevent transgene movement from the crop. Recoverable block of function, intein trans-splicing and transgene excision all use recombinases to modify the transgene in planta either to induce expression or to prevent it. All require optimal conditions and 100% accuracy to function and none have been tested under field conditions as yet. All will contain the GM trait but all will allow some non-native DNA to escape to wild populations or to non-GM crops. There are particular issues with GM trees and grasses as both are largely undomesticated, wind pollinated and perennial, thus providing many opportunities for hybridisation. Some species of both trees and grass are also capable of vegetative propagation without sexual reproduction. There are additional concerns regarding the weedy nature of many grass species and the long-term stability of GM traits across the life span of trees. Transgene stability and conferred sterility are difficult to trial in trees as most field trials are only conducted during the juvenile phase of tree growth. Bio-pharming of pharmaceutical and industrial compounds in plants Bio-pharming of pharmaceutical and industrial compounds in plants offers an attractive alternative to mammalian-based pharmaceutical and vaccine production. Several plantbased products are already on the market (Prodigene’s avidin, β-glucuronidase, trypsin generated in GM maize; Ventria’s lactoferrin generated in GM rice). Numerous products are in clinical trials (collagen, antibodies against tooth decay and non-Hodgkin’s lymphoma from tobacco; human gastric lipase, therapeutic enzymes, dietary supplements from maize; Hepatitis B and Norwalk virus vaccines from potato; rabies vaccines from spinach; dietary supplements from Arabidopsis). The initial production platforms for plant-based pharmaceuticals were selected from conventional crops, largely because an established knowledge base already existed. Tobacco and other leafy crops such as alfalfa, lettuce and spinach are widely used as leaves can be harvested and no flowering is required. Many of these crops can be grown in contained greenhouses. Potato is also widely used and can also be grown in contained conditions. The introduction of morphological markers may aid in the recognition and traceability of crops expressing pharmaceutical products. Plant cells or plant parts may be transformed and maintained in culture to produce recombinant products in a contained environment. Plant cells in suspension or in vitro, roots, root cells and guttation fluid from leaves may be engineered to secrete proteins that may be harvested in a continuous, non-destructive manner. Most strategies in this category remain developmental and have not been commercially adopted at present. Transient expression produces GM compounds from non-GM plants via the utilisation of bacterial or viral vectors. These vectors introduce the trait into specific tissues of whole plants or plant parts, but do not insert them into the heritable genome. There are some limitations of scale and the field release of such crops will require the regulation of the vector. However, several companies have several transiently expressed products in clinical and pre-clinical trials from crops raised in physical containment.

Multi-satellite observed responses of precipitation and its extremes to interannual climate variability

The consistency of precipitation variability estimated from the multiple satellite-based observing systems is assessed. There is generally good agreement between TRMM TMI, SSM/I, GPCP and AMSRE datasets for the inter-annual variability of precipitation since 1997 but the HOAPS dataset appears to overestimate the magnitude of variability. Over the tropical ocean the TRMM 3B42 dataset produces unrealistic variabilitys. Based upon deseasonalised GPCP data for the period 1998-2008, the sensitivity of global mean precipitation (P) to surface temperature (T) changes (dP/dT) is about 6%/K, although a smaller sensitivity of 3.6%/K is found using monthly GPCP data over the longer period 1989-2008. Over the tropical oceans dP/dT ranges from 10-30%/K depending upon time-period and dataset while over tropical land dP/dT is -8 to -11%/K for the 1998-2008 period. Analyzing the response of the tropical ocean precipitation intensity distribution to changes in T we find the wetter area P shows a strong positive response to T of around 20%/K. The response over the drier tropical regimes is less coherent and varies with datasets, but responses over the tropical land show significant negative relationships over an interannual time-scale. The spatial and temporal resolutions of the datasets strongly influence the precipitation responses over the tropical oceans and help explain some of the discrepancy between different datasets. Consistency between datasets is found to increase on averaging from daily to 5-day time-scales and considering a 1o (or coarser) spatial resolution. Defining the wet and dry tropical ocean regime by the 60th percentile of P intensity, the 5-day average, 1o TMI data exhibits a coherent drying of the dry regime at the rate of -20%/K and the wet regime becomes wetter at a similar rate with warming.

Revealing ensemble state transition patterns in multi-electrode neuronal recordings using hidden Markov models

In order to harness the computational capacity of dissociated cultured neuronal networks, it is necessary to understand neuronal dynamics and connectivity on a mesoscopic scale. To this end, this paper uncovers dynamic spatiotemporal patterns emerging from electrically stimulated neuronal cultures using hidden Markov models (HMMs) to characterize multi-channel spike trains as a progression of patterns of underlying states of neuronal activity. However, experimentation aimed at optimal choice of parameters for such models is essential and results are reported in detail. Results derived from ensemble neuronal data revealed highly repeatable patterns of state transitions in the order of milliseconds in response to probing stimuli.

Beyond tokenism? Community-led planning and rational choices: findings from participants in local agenda-setting at the neighbourhood scale in England

The article confronts some key issues raised in the literature on public participation via a series of interrogatory questions drawn from rational choice theory. These are considered in relation to the design and process of public participation opportunities in planning and wider processes of local governance at the neighbourhood scale. In doing this, the article draws on recent research that has looked in some depth at a form of community-led planning (CLP) in England. The motives and expectations of participants, the abilities of participants, as well as the conditions in which participation takes place are seen as important factors. It is contended that the issues raised by rational choice theory are pertinent to emerging efforts to engage communities. As such, the article concludes that advocates of public participation or community engagement should not be afraid of responding to the challenges posed by questions of motive and reward of participants if lasting and worthwhile participation is to be established. Indeed, questions such as 'what's in it for me?' should be regarded as legitimate, necessary and indeed standard, in order to co-devise meaningful and durable participation opportunities and appropriate institutional environments. However, it is also maintained that wider considerations and capacity questions will also need to be confronted if participation is to become embedded as part of participatory neighbourhood-scale planning.

Disentangling multi-level systems: averaging, correlations and memory

We consider two weakly coupled systems and adopt a perturbative approach based on the Ruelle response theory to study their interaction. We propose a systematic way of parameterizing the effect of the coupling as a function of only the variables of a system of interest. Our focus is on describing the impacts of the coupling on the long term statistics rather than on the finite-time behavior. By direct calculation, we find that, at first order, the coupling can be surrogated by adding a deterministic perturbation to the autonomous dynamics of the system of interest. At second order, there are additionally two separate and very different contributions. One is a term taking into account the second-order contributions of the fluctuations in the coupling, which can be parameterized as a stochastic forcing with given spectral properties. The other one is a memory term, coupling the system of interest to its previous history, through the correlations of the second system. If these correlations are known, this effect can be implemented as a perturbation with memory on the single system. In order to treat this case, we present an extension to Ruelle's response theory able to deal with integral operators. We discuss our results in the context of other methods previously proposed for disentangling the dynamics of two coupled systems. We emphasize that our results do not rely on assuming a time scale separation, and, if such a separation exists, can be used equally well to study the statistics of the slow variables and that of the fast variables. By recursively applying the technique proposed here, we can treat the general case of multi-level systems.

Improvement of the GenTHREADER method for genomic fold recognition

Motivation: In order to enhance genome annotation, the fully automatic fold recognition method GenTHREADER has been improved and benchmarked. The previous version of GenTHREADER consisted of a simple neural network which was trained to combine sequence alignment score, length information and energy potentials derived from threading into a single score representing the relationship between two proteins, as designated by CATH. The improved version incorporates PSI-BLAST searches, which have been jumpstarted with structural alignment profiles from FSSP, and now also makes use of PSIPRED predicted secondary structure and bi-directional scoring in order to calculate the final alignment score. Pairwise potentials and solvation potentials are calculated from the given sequence alignment which are then used as inputs to a multi-layer, feed-forward neural network, along with the alignment score, alignment length and sequence length. The neural network has also been expanded to accommodate the secondary structure element alignment (SSEA) score as an extra input and it is now trained to learn the FSSP Z-score as a measurement of similarity between two proteins. Results: The improvements made to GenTHREADER increase the number of remote homologues that can be detected with a low error rate, implying higher reliability of score, whilst also increasing the quality of the models produced. We find that up to five times as many true positives can be detected with low error rate per query. Total MaxSub score is doubled at low false positive rates using the improved method.

Smoothness of scale functions for spectrally negative Lévy processes

Scale functions play a central role in the fluctuation theory of spectrally negative Lévy processes and often appear in the context of martingale relations. These relations are often require excursion theory rather than Itô calculus. The reason for the latter is that standard Itô calculus is only applicable to functions with a sufficient degree of smoothness and knowledge of the precise degree of smoothness of scale functions is seemingly incomplete. The aim of this article is to offer new results concerning properties of scale functions in relation to the smoothness of the underlying Lévy measure. We place particular emphasis on spectrally negative Lévy processes with a Gaussian component and processes of bounded variation. An additional motivation is the very intimate relation of scale functions to renewal functions of subordinators. The results obtained for scale functions have direct implications offering new results concerning the smoothness of such renewal functions for which there seems to be very little existing literature on this topic.

Identifying time lags in the restoration of grassland butterfly communities: a multi-site assessment

Although grasslands are crucial habitats for European butterflies, large-scale declines in quality and area have devastated many species. Grassland restoration can contribute to the recovery of butterfly populations, although there is a paucity of information on the long-term effects of management. Using eight UK data sets (9-21 years), we investigate changes in restoration success for (1) arable reversion sites, were grassland was established on bare ground using seed mixtures, and (2) grassland enhancement sites, where degraded grasslands are restored by scrub removal followed by the re-instigation of cutting/grazing. We also assessed the importance of individual butterfly traits and ecological characteristics in determining colonisation times. Consistent increases in restoration success over time were seen for arable reversion sites, with the most rapid rates of increase in restoration success seen over the first 10 years. For grasslands enhancement there were no consistent increases in restoration success over time. Butterfly colonisation times were fastest for species with widespread host plants or where host plants established well during restoration. Low mobility butterfly species took longer to colonise. We show that arable reversion is an effective tool for the management of butterfly communities. We suggest that as restoration takes time to achieve, its use as a mitigation tool against future environmental change (i.e. by decreasing isolation in fragmented landscapes) needs to take into account such time lags.