Joint decoding of multiple speech patterns for robust speech recognition

We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.

Electrical and structural properties of zirconia thin films prepared by reactive magnetron sputtering

Thin films of ZrO2 were prepared by reactive magnetron sputtering. Annealing of the films exhibited a drastic change in the properties due to improved crystallinity and packing density. The root mean square roughness of the sample observed from atomic force microscope is about 5.75 nm which is comparable to the average grain size of the thin film which is about 6 nm obtained from X-ray diffraction. The film annealed at 873 K exhibits an optical band gap of around 4.83 eV and shows +4 oxidation state of zirconium indicating fully oxidized zirconium, whereas higher annealing temperatures lead to oxygen deficiency in the films and this is reflected in their properties. A discontinuity in the imaginary part of the AC conductivity was observed in the frequency range of tens of thousands of Hz, where as, the real part does not show such behavior.

Multiple excitation nano-spot generation and confocal detection for far-field microscopy

An imaging technique is developed for the controlled generation of multiple excitation nano-spots for far-field microscopy. The system point spread function (PSF) is obtained by interfering two counter-propagating extended depth-of-focus PSF (DoF-PSF), resulting in highly localized multiple excitation spots along the optical axis. The technique permits (1) simultaneous excitation of multiple planes in the specimen; (2) control of the number of spots by confocal detection; and (3) overcoming the point-by-point based excitation. Fluorescence detection from the excitation spots can be efficiently achieved by Z-scanning the detector/pinhole assembly. The technique complements most of the bioimaging techniques and may find potential application in high resolution fluorescence microscopy and nanoscale imaging.

Forecasting day-ahead electricity load using a multiple equation time series approach

The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.

Target reliability based design optimization of anchored cantilever sheet pile walls

In this study, the stability of anchored cantilever sheet pile wall in sandy soils is investigated using reliability analysis. Targeted stability is formulated as an optimization problem in the framework of an inverse first order reliability method. A sensitivity analysis is conducted to investigate the effect of parameters influencing the stability of sheet pile wall. Backfill soil properties, soil - steel pile interface friction angle, depth of the water table from the top of the sheet pile wall, total depth of embedment below the dredge line, yield strength of steel, section modulus of steel sheet pile, and anchor pull are all treated as random variables. The sheet pile wall system is modeled as a series of failure mode combination. Penetration depth, anchor pull, and section modulus are calculated for various target component and system reliability indices based on three limit states. These are: rotational failure about the position of the anchor rod, expressed in terms of moment ratio; sliding failure mode, expressed in terms of force ratio; and flexural failure of the steel sheet pile wall, expressed in terms of the section modulus ratio. An attempt is made to propose reliability based design charts considering the failure criteria as well as the variability in the parameters. The results of the study are compared with studies in the literature.

The emerging role of microRNAs in resistance to lung cancer treatments

One of the major challenges in the treatment of lung cancer is the development of drug resistance. This represents a major obstacle in the treatment of patients, limiting the efficacy of both conventional chemotherapy and biological therapies. Deciphering the mechanisms of resistance is critical to further understanding the multifactorial pathways involved, and in developing more specific targeted treatments. To date, numerous studies have reported the potential role of microRNAs (miRNAs) in resistance to various cancer treatments. MicroRNAs are a family of small non-coding RNAs that regulate gene expression by sequence-specific targeting of mRNAs causing translational repression or mRNA degradation. More than 1200 validated human miRNAs have been identified to date. While as little as one miRNA can regulate hundreds of targets, a single target can also be affected by multiple miRNAs. Evidence suggests that dysregulation of specific miRNAs may be involved in the acquisition of resistance to a number of cancer treatments, thereby modulating the sensitivity of cancer cells to such therapies. Therefore, targeting miRNAs may be an attractive strategy for developing novel and more effective individualized therapies, improving drug efficiency, and for predicting patient response to different treatments. In this review, we provide an overview on the role of miRNAs in resistance to current lung cancer therapies and novel biological agents.

KAT5 (Tip60) is a potential therapeutic target in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a rare aggressive cancer of the pleura. Asbestos exposure (through inhalation) is the most well established risk factor for mesothelioma. The current standard of care for patients suffering from MPM is a combination of cisplatin and pemetrexed (or alternatively cisplatin and raltitrexed). Most patients, however, die within 24 months of diagnosis. New therapies are therefore urgently required for this disease. Lysine acetyltransferases (KATs) including KAT5 have been linked with the development of cisplatin resistance. This gene may therefore be altered in MPM and could represent a novel candidate target for intervention. Using RT-PCR screening the expression of all known KAT5 variants was found to be markedly increased in malignant tumors compared to benign pleura. When separated according to histological subtype, KAT5 was significantly overexpressed in both the sarcomatoid and biphasic subgroups for all transcript variants. A panel of MPM cell lines including the normal pleural cells LP9 and Met5A was screened for expression of KAT5 variants. Treatment of cells with a small molecule inhibitor of KAT5 (MG-149) caused significant inhibition of cellular proliferation (p<0.0001), induction of apoptosis and was accompanied by significant induction of pro-inflammatory cytokines/chemokines.

Molecular dynamics studies of nanoparticle impacts

This thesis concerns the dynamics of nanoparticle impacts on solid surfaces. These impacts occur, for instance, in space, where micro- and nanometeoroids hit surfaces of planets, moons, and spacecraft. On Earth, materials are bombarded with nanoparticles in cluster ion beam devices, in order to clean or smooth their surfaces, or to analyse their elemental composition. In both cases, the result depends on the combined effects of countless single impacts. However, the dynamics of single impacts must be understood before the overall effects of nanoparticle radiation can be modelled. In addition to applications, nanoparticle impacts are also important to basic research in the nanoscience field, because the impacts provide an excellent case to test the applicability of atomic-level interaction models to very dynamic conditions. In this thesis, the stopping of nanoparticles in matter is explored using classical molecular dynamics computer simulations. The materials investigated are gold, silicon, and silica. Impacts on silicon through a native oxide layer and formation of complex craters are also simulated. Nanoparticles up to a diameter of 20 nm (315000 atoms) were used as projectiles. The molecular dynamics method and interatomic potentials for silicon and gold are examined in this thesis. It is shown that the displacement cascade expansionmechanism and crater crown formation are very sensitive to the choice of atomic interaction model. However, the best of the current interatomic models can be utilized in nanoparticle impact simulation, if caution is exercised. The stopping of monatomic ions in matter is understood very well nowadays. However, interactions become very complex when several atoms impact on a surface simultaneously and within a short distance, as happens in a nanoparticle impact. A high energy density is deposited in a relatively small volume, which induces ejection of material and formation of a crater. Very high yields of excavated material are observed experimentally. In addition, the yields scale nonlinearly with the cluster size and impact energy at small cluster sizes, whereas in macroscopic hypervelocity impacts, the scaling 2 is linear. The aim of this thesis is to explore the atomistic mechanisms behind the nonlinear scaling at small cluster sizes. It is shown here that the nonlinear scaling of ejected material yield disappears at large impactor sizes because the stopping mechanism of nanoparticles gradually changes to the same mechanism as in macroscopic hypervelocity impacts. The high yields at small impactor size are due to the early escape of energetic atoms from the hot region. In addition, the sputtering yield is shown to depend very much on the spatial initial energy and momentum distributions that the nanoparticle induces in the material in the first phase of the impact. At the later phases, the ejection of material occurs by several mechanisms. The most important mechanism at high energies or at large cluster sizes is atomic cluster ejection from the transient liquid crown that surrounds the crater. The cluster impact dynamics detected in the simulations are in agreement with several recent experimental results. In addition, it is shown that relatively weak impacts can induce modifications on the surface of an amorphous target over a larger area than was previously expected. This is a probable explanation for the formation of the complex crater shapes observed on these surfaces with atomic force microscopy. Clusters that consist of hundreds of thousands of atoms induce long-range modifications in crystalline gold.

Electronic excitations in solids studied using inelastic x-ray scattering

Inelastic x-ray scattering can be used to study the electronic structure of matter. The x rays scattered from the target both induce and carry information on the electronic excitations taking place in the system. These excitations are the manifestations of the electronic structure and the physics governing the many-body system. This work presents results of non-resonant inelastic x-ray scattering experiments on a range of materials including metallic, insulating and semiconducting compounds as well as an organic polymer. The experiments were carried out at the National Synchrotron Light Source, USA and at the European Synchrotron Radiation Facility, France. The momentum transfer dependence of the experimental valence- and core-electron excitation spectra is compared with the results of theoretical first principles computations that incorporate the electron-hole interaction. A recently developed method for analyzing the momentum transfer dependence of core-electron excitation spectra is studied in detail. This method is based on real space multiple scattering calculations and is used to extract the angular symmetry components of the local unoccupied density of final states.

A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

Decomposition analysis to examine Australia’s 2030 GHGs emissions target: How hard will it be to achieve?

The Australian government has recently pledged a reduction in GHGs emissions of 26–28% below the 2005 level by 2030. How big is the challenge for the country to achieve this target in terms of its present emissions profile, recent historical trends, and the contributions to those trends from key proximate factors contributing to emissions? In this paper, we attempt a quantitative judgement of the challenge by using decomposition analysis. Based on the analysis it appears the announced target will be quite challenging to achieve if the average annual mitigating effects from economic restructuring, energy efficiency improvements and movement towards less emissions-intensive energy sources in evidence over 2002–2013 continued through to 2030; however, if the contribution from these mitigating sources in evidence over 2006–2013 can be sustained, achievement of the target will be much less challenging. The challenge for government then will be to provide a policy framework to ensure the more pronounced beneficial impacts of the mitigating factors evidenced during 2006–2013 can be maintained over the years to 2030.

Proteomic identification of putative microRNA394 target genes in Arabidopsis thaliana identifies MLP family members critical for normal development

Expression of the F-Box protein Leaf Curling Responsiveness (LCR) is regulated by microRNA, miR394, and alterations to this interplay in Arabidopsis thaliana produce defects in leaf polarity and shoot apical meristem (SAM) organisation. Although the miR394-LCR node has been documented in Arabidopsis, the identification of proteins targeted by LCR F-box itself has proven problematic. Here, a proteomic analysis of shoot apices from plants with altered LCR levels identified a member of the Major Latex Protein (MLP) family gene as a potential LCR F-box target. Bioinformatic and molecular analyses also suggested that other MLP family members are likely to be targets for this post-translational regulation. Direct interaction between LCR F-Box and MLP423 was validated. Additional MLP members had reduction in protein accumulation, in varying degrees, mediated by LCR F-Box. Transgenic Arabidopsis lines, in which MLP28 expression was reduced through an artificial miRNA technology, displayed severe developmental defects, including changes in leaf patterning and morphology, shoot apex defects, and eventual premature death. These phenotypic characteristics resemble those of Arabidopsis plants modified to over-express LCR. Taken together, the results demonstrate that MLPs are driven to degradation by LCR, and indicate that MLP gene family is target of miR394-LCR regulatory node, representing potential targets for directly post-translational regulation mediated by LCR F-Box. In addition, MLP28 family member is associated with the LCR regulation that is critical for normal Arabidopsis development.

Stadilaispojat, rikokset ja lastensuojelu : Viisi tapaustutkimusta kuudelta vuosikymmeneltä

Societal reactions to norm breaking behavior of children reveal, how we understand childhood, the relations between generations and communitie's ratio of tolerance. In Finland the children that repeatedly commit crimes receive social service measures that are based on Child Welfare Act. In the city of Helsinki (Stadi in the slang of Helsinki) existed an agency specifically established for ill-behaving children until the 1980's, agter which an unified agency for the maltreated and maladjusted children was founded. Through five boys' welfare cases, this research aims at defining what kind of positions, social relations and structures are constructed in the social dynamics of these children's everyday lives. The cases cover different decades from the 1940s to the present. At the same time the cases reflect the child welfare and societal practices, and reveal how the communities have participated in constructing deviance in different eras. The research is meta-theoretically based on critical realism and specifically on Roy Bhaskar's transformative model of social activity. The cases are analyzed in the framework of Edwin M. Lemert's societal reaction theory. Thus the focus of the study is on the wide structural context of the institutional and societal definitions of deviance. The research is methodologically based on a qualitative multiple case study research. The primary data consist of classified child welfare case files collected from the archives of the city of Helsinki. The data of the institutional level consist of the annual reports from 1943 to 2004 and the ordinances from 1907 onwards, and of various committee documents produced in the law-making process of child welfare, youth and criminal legislation of the 20th century. Empirical finding are interpreted in a dialogue with previous historical and child welfare research, contemporary literature and studies on the urban development. The analysis is based on Derek Layder's model of adaptive theory. The research forms a viewpoint to the historical study of child welfare, in which the historical era, its agents and the dynamics of their mutual relations are studied through an individual level reconstruction based on the societal reaction theory. The case analyses reveal how the positions of the children form differently in the different eras of child welfare practices. In the 1940s the child is positioned as a psychopath and a criminal type. The measures are aimed at protecting the community from the disturbed child, and at adjusting the individual by isolation. From 1960s to 1980s the child is positioned as a child in need of help and support. The child becomes a victim, a subject that occupies rights, and a target of protection. In the turn of the millennium a norm breaking child is positioned as a dangerous individual that, in the name of the community safety, has to be confined. The case analyses also reveal the prevailing academic and practical paradigms of the time. Keywords: childhood, youth, child protection, child welfare, delinquency, crime, deviance, history, critical realism, case study research