Eigenvoice modeling for cross likelihood ratio based speaker clustering : a Bayesian approach

This paper proposes the use of Bayesian approaches with the cross likelihood ratio (CLR) as a criterion for speaker clustering within a speaker diarization system, using eigenvoice modeling techniques. The CLR has previously been shown to be an effective decision criterion for speaker clustering using Gaussian mixture models. Recently, eigenvoice modeling has become an increasingly popular technique, due to its ability to adequately represent a speaker based on sparse training data, as well as to provide an improved capture of differences in speaker characteristics. The integration of eigenvoice modeling into the CLR framework to capitalize on the advantage of both techniques has also been shown to be beneficial for the speaker clustering task. Building on that success, this paper proposes the use of Bayesian methods to compute the conditional probabilities in computing the CLR, thus effectively combining the eigenvoice-CLR framework with the advantages of a Bayesian approach to the diarization problem. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 33.5% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

Are academics messy? Testing the broken windows theory with a field experiment in the work environment

We test the broken windows theory using a field experiment in a shared area of an academic workplace(the department common room). More specifically, we explore academics’ and postgraduate students’ behavior under an order condition (a clean environment) and a disorder condition (a messy environment). We find strong evidence that signs of disorderly behavior trigger littering: In 59% of the cases, subjects litter in the disorder treatment as compared to 18% in the order condition. These results remain robust in a multivariate analysis even when controlling for a large set of factors not directly examined by previous studies. Overall, when academic staff and postgraduate students observe that others have violated the social norm of keeping the common room clean, all else being equal, the probability of littering increases by around 40%.

On the commonly accepted assumptions regarding observed motor vehicle crash counts at transport system locations

Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.

Melt-textured YBa2Cu3O7-x wires having plate-like grains

YBCO wires which consist of well oriented plate-like fine grains are fabricated using a moving furnace to achieve higher mechanical strength. Melt-texturing experiments have been undertaken on YBCO wires with two different compositions: YBa1.5Cu2.9O7-x, and YBa1.8Cu3.0O7-x. Wires are extruded from a mixture of precursor powders (formed by a coprecipitation process) then textured by firing in a moving furnace. Size of secondary phases such as barium cuprate and copper oxide, and overall composition of the sample affect the orientation of the fine grains. At zero magnetic field, the YBa1.5Cu2.9O7-x wire shows the highest critical current density of 1,450 Acm-2 and 8,770 Acm-2 at 77K and 4.2K, respectively. At 1 T, critical current densities of 30 Acm-2 and 200 Acm-2, respectively, are obtained at 77K and 4.2K. Magnetisation curves are also obtained for one sample to evaluate critical current density using the Bean model. Analysis of the microstructure indicates that the starting composition of the green body significantly affects the achievement of grain alignment via melt-texturing processes.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

Aluminosilicates of zeolite N structure

A process for making aluminosilicates of zeolite N structure comprising the steps of: (i) combining a water soluble monovalent cation, a solution of hydroxyl anions and an aluminosilicate to form a resultant mixture having a pH greater than 10 and a H.sub.2O/Al.sub.2O.sub.3 ratio in the range 30 to 220; (ii) heating the resultant mixture to a temperature of between 50.degree. C. and boiling point of the mixture for a time between 1 minute and 100 hours until a crystalline product of zeolite N structure is formed as determined by X-ray diffraction or other suitable characteristic; and (iii) separating the zeolite N product as a solid from the mixture.

Flammability and Sensitivity of Materials in Oxygen-Enriched Atmospheres : 13th Volume

"Seventeen peer-reviewed papers cover the latest research on the ignition and combustion of metals and non-metals, oxygen compatibility of components and systems, analysis of ignition and combustion, failure analysis and safety. It includes aerospace, military, scuba diving, and industrial oxygen applications. Topics cover: • Development of safe oxygen systems • Ignition mechanisms within oxygen systems and how to avoid them • Specific hazards that exist with the oxygen mixture breathed by divers in the scuba industry • Issues related to oxygen system level safety • Issues related to oxygen safety in breathing systems • Detailed investigations and discussions related to the burn curves that have been generated for metals that are burning in a standard test fixture This new publication is a valuable resource for professionals in the air separation industries, oxygen manufacturers, manufacturers of materials intended for oxygen service, and users of oxygen and oxygen-enriched atmospheres, including aerospace, medical, industrial gases, chemical processing, steel and metals refining, as well as to military, commercial or recreational diving."--- publisher website

Genome-wide search for markers associated with bovine spongiform encephalopathy

A genome-wide search for markers associated with BSE incidence was performed by using Transmission-Disequilibrium Tests (TDTs). Significant segregation distortion, i.e., unequal transmission probabilities of alleles within a locus, was found for three marker loci on Chromosomes (Chrs) 5, 10, and 20. Although TDTs are robust to false associations owing to hidden population substructures, it cannot distinguish segregation distortion caused by a true association between a marker and bovine spongiform encephalopathy (BSE) from a population-wide distortion. An interaction test and a segregation distortion analysis in half-sib controls were used to disentangle these two alternative hypotheses. None of the markers showed any significant interaction between allele transmission rates and disease status, and only the marker on Chr 10 showed a significant segregation distortion in control individuals. Nevertheless, the control group may have been a mixture of resistant and susceptible but unchallenged individuals. When new genotypes were generated in the vicinity of these three markers, evidence for an association with BSE was confirmed for the locus on Chr 5.

Astrophysics and the solar nebula

The following types of experiments for a proposed Space Station Microgravity Particle Research Facility are described: (1) nucleation of refractory vapors at low pressure/high temperature; (2) coagulation of refractory grains; (3) optical properties of refractory grains; (4) mantle growth on refractory cores; (5) coagulation of core-mantle grains; (6) optical properties of core-mantle grains; (7) lightning strokes in the primitive solar nebula; and (8) separation of dust from a grain/gas mixture that interacts with a meter-sized planetesimal to determine if accretion occurs. The required capabilities and desired hardware for the facility are detailed.

Users segmentations for recommendation

Traditional recommendation methods provide recommendations equally to all users. In this paper, a segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs in order to offer a specific recommendation strategy to each segment. Experiment is conducted using a live online dating network data.

Experimental investigation of the governing parameters in the electrospinning of poly(3-hydroxybutyrate) scaffolds : structural characteristics of the pores

We sought to determine the impact of electrospinning parameters on a trustworthy criterion that could evidently improve the maximum applicability of fibrous scaffolds for tissue regeneration. We used an image analysis technique to elucidate the web permeability index (WPI) by modeling the formation of electrospun scaffolds. Poly(3-hydroxybutyrate) (P3HB) scaffolds were fabricated according to predetermined conditions of levels in a Taguchi orthogonal design. The material parameters were the polymer concentration, conductivity, and volatility of the solution. The processing parameters were the applied voltage and nozzle-to-collector distance. With a law to monitor the WPI values when the polymer concentration or the applied voltage was increased, the pore interconnectivity was decreased. The quality of the jet instability altered the pore numbers, areas, and other structural characteristics, all of which determined the scaffold porosity and aperture interconnectivity. An initial drastic increase was observed in the WPI values because of the chain entanglement phenomenon above a 6 wt % P3HB content. Although the solution mixture significantly (p < 0.05) changed the scaffold architectural characteristics as a function of the solution viscosity and surface tension, it had a minor impact on the WPI values. The solution mixture gained the third place of significance, and the distance was approved as the least important factor.

Aspects of the kinetics and solubility of silica and calcium oxalate composites in sugar solutions

Fouling of industrial surfaces by silica and calcium oxalate can be detrimental to a number of process streams. Solution chemistry plays a large roll in the rate and type of scale formed on industrial surfaces. This study is on the kinetics and thermodynamics of SiO2 and calcium oxalate composite formation in solutions containing Mg2+ ions, trans-aconitic acid and sucrose, to mimic factory sugar cane juices. The induction time (ti) of silicic acid polymerization is found to be dependent on the sucrose concentration and SiO2 supersaturation ratio (SS). Generalized kinetic and solubility models are developed for SiO2 and calcium oxalate in binary systems using response surface methodology. The role of sucrose, Mg, trans-aconitic acid, a mixture of Mg and trans-aconitic acid, SiO2 SS ratio and Ca in the formation of com- posites is explained using the solution properties of these species including their ability to form complexes.

Pt/MoO3 nano-flower/SiC Schottky diode based hydrogen gas sensor

In this paper, we report the development of a novel Pt/MoO3 nano-flower/SiC Schottky diode based device for hydrogen gas sensing applications. The MoO3 nanostructured thin films were deposited on SiC substrates via thermal evaporation. Morphological characterization of the nanostructured MoO3 by scanning electron microscopy revealed randomly orientated thin nanoplatelets in a densely packed formation of nano-flowers with dimensions ranging from 250 nm to 1 μm. Current-voltage characteristics of the sensor were measured at temperatures from 25°C to 250°C. The sensor showed greater sensitivity in a reverse bias condition than in forward bias. Dynamic response of the sensor was investigated towards different concentrations of hydrogen gas in a synthetic air mixture at 250°C and a large voltage shift of 5.7 V was recorded upon exposure to 1% hydrogen.

Pt/Graphene Nano-sheet Based Hydrogen Gas Sensor

In this paper, we present gas sensing properties of Pt/graphene-like nano-sheets towards hydrogen gas. The graphene-like nano-sheets were produced via the reduction of spray-coated graphite oxide deposited on SiC substrates by hydrazine vapor. Structural and morphological characterizations of the graphene sheets were analyzed by scanning electron and atomic force microscopy. Current-voltage and dynamic responses of the sensors were investigated towards different concentrations of hydrogen gas in a synthetic air mixture at 100°C. A voltage shift of 100 mV was recorded at 1 mA reverse bias current.

Thermogravimetric analysis of selected layered double hydroxides

Thermogravimetric analysis (TG) and powder X-ray diffraction (PXRD) were used to study some selected Mg/Al and Zn/Al layered double hydroxides (LDHs) prepared by co-precipitation. A Mg/Al hydrotalcite was investigated before and after reformation in fluoride and nitrate solutions. Little change in the TG or PXRD patterns was observed. It was proposed that successful intercalation of nitrate anions has occurred. However, the absence of any change in the d(003) interlayer spacing suggests that fluoride anions were not intercalated between the LDH layers. Any fluoride anions that were removed from solution are most likely adsorbed onto the outer surfaces of the hydrotalcite. As fluoride removal was not quantified it is not possible to confirm that this has happened without further experimentation. Carbonate is probably intercalated into the interlayer of these hydrotalcites, as well as fluoride or nitrate. The carbonate most likely originates from either incomplete decarbonation during thermal activation or adsorption from the atmosphere or dissolved in the deionised water. Small and large scale co-precipitation syntheses of a Zn/Al LDH were also investigated to determine if there was any change in the product. While the small scale experiment produced a good quality LDH of reasonable purity; the large scale synthesis resulted in several additional phases. Imprecise measurement and difficulty in handling the large quantities of reagents appeared to be sufficient to alter the reaction conditions causing a mixture of phases to be formed.