Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved spontaneous Mandarin speech recognition by disfluency interruption point (IP) detection using prosodic features

In this paper, a new approach for improved spontaneous Mandarin speech recognition with disfluencies well considered is presented. The basic idea is to detect the disfluency interruption points (IPs) prior to the recognition, and then to use these information during rescoring in the recognition process. For accurate detection of disfluency interruption points (IPs), a whole set of new features were proposed and tested by carefully considering the special characteristics of Mandarin Chinese. A new approach of incorporating the decision tree into the maximum entropy model training was also developed to enhance the IP detection accuracy. Experimental results indicated that the proposed set of features and the IP detection approach were very useful, and the obtained information about disfluency actually benefited the speech recognition performance.
Sensor Health Monitoring in Wireless Sensor Networks

Wireless Sensor Network (WSN) has been widely used in information collection and monitoring applications. At the center of attention in these applications are data, which come from the sensor part of each WSN node. Sensor faults are common due to the sensor device itself and the harsh deployment environment. These faults may degrade the data quality from the very beginning and thus have a possible large influence on the final success of specific WSN application. Our work presented in this paper is to monitor the health status of sensors in WSN. Inspired by the latest development of time series data mining technology, a flexible approach is proposed for unspecific fault monitoring. Each deployed WSN node learns the frequent patterns periodically. Any sensor fault follows a pattern that is different from the node’s learned frequent patterns. The proposed method can find fault patterns efficiently. We show how this method works well in Castalia simulation environment.
Mars-Like Soils in the Atacama Desert, Chile, and the Dry Limit of Microbial Life

The Viking missions showed the martian soil to be lifeless and depleted in organic material and indicated the presence of one or more reactive oxidants. Here we report the presence of Mars-like soils in the extreme arid region of the Atacama Desert. Samples from this region had organic species only at trace levels and extremely low levels of culturable bacteria. Two samples from the extreme arid region were tested for DNA and none was recovered. Incubation experiments, patterned after the Viking labeled-release experiment but with separate biological and nonbiological isomers, show active decomposition of organic species in these soils by nonbiological processes.
On the Feasibility of Attribute-Based Encryption on Internet of Things Devices

The Internet of Things (IoT) is emerging with the pace of technology evolution, connecting people and things through the Internet. IoT devices enable large-scale data collection and sharing for a wide range of applications. However, it is challenging to securely manage interconnected IoT devices because the collected data could contain sensitive personal information. The authors believe that attribute-based encryption (ABE) could be an effective cryptographic tool for secure management of IoT devices. However, little research has addressed ABE's actual feasibility in the IoT thus far. This article investigates such feasibility considering well-known IoT platforms--specifically, Intel Galileo Gen 2, Intel Edison, Raspberry Pi 1 Model B, and Raspberry Pi Zero. A thorough evaluation confirms that adopting ABE in the IoT is indeed feasible.
Until it's Over, Over There: The U.S. Economy in World War I

The process by which the US economy was mobilized during World War I was the subject of considerable criticism both at the time and since. Nevertheless, when viewed in the aggregate the degree of mobilization achieved during the short period of active US involvement was remarkable. The United States entered the war in 1917 having made only limited preparations. In 1918 the armed forces were expanded to include 2.9 million sailors, soldiers, and marines; 6 percent of the labor force in the 15 to 44 age bracket. Overall in 1918, one fifth or more of the nation's resources was devoted to the war effort. By the time the Armistice was signed in 1919 a profusion of new weapons was flowing from American factories. This essay describes how mobilization was achieved so quickly, including how it was financed, and some of the long-term consequences.
Government Transfers and Growth: Is there Evidence of Genuine Effect?

This paper investigates how government transfers affect economic growth. Using meta-analysis techniques, we systematically review 24 primary studies with 164 estimates that examine the effect of government transfers on economic growth. After addressing heterogeneity and issues of publication bias in the existing literature, we find a negative association between government transfers and growth. This negative growth impact of government transfers also holds for developed countries. Meta-regression results also reveal that the effect size of reported estimates largely depends on individual study characteristics. In particular, data time period, measure of government transfers, econometric specification and underlying theoretical models are important factors that explain the variations in the empirical results.
Changes in and Efficacies of Indications for Invasive Prenatal Diagnosis of Cytogenomic Abnormalities: 13 Years of Experience in a Single Center

Background Because the future application of cell-free fetal DNA screening is expected to dramatically improve the diagnostic yield and reduce unnecessary invasive procedures, it is time to summarize the indications of invasive prenatal diagnosis. This retrospective study was performed to evaluate the changes and efficacies of indications of invasive procedures for detecting cytogenomic abnormalities from 2000 to 2012. Material/Methods From our regional obstetric unit, 7818 invasive procedures were referred by indications of advance maternal age (AMA), abnormal ultrasound findings (aUS), abnormal maternal serum screening (aMSS), and family history (FH). Chromosome, fluorescence in situ hybridization (FISH), and array comparative genomic hybridization (aCGH) analyses were performed on chorionic villus sampling (CVS) and amniotic fluid (AF) specimens at the Yale Cytogenetics Laboratory. The abnormal findings from single or combined indications were compared to evaluate the diagnostic yield. Results The annual caseload declined by 57.2% but the diagnostic yield increased from 7.2% to 13.4%. Chromosomal and genomic abnormalities were detected in 752 cases (9.6%, 752/7818) and 12 cases (4%, 12/303), respectively. Significantly decreased AMA referrals and increased aUS and aMSS referrals were noted. The top 3 indications by diagnostic yield were AMA/aUS (51.4% for CVS, 24.2% for AF), aUS (34.7% for CVS, 14.5% for AF), and AMA/aMSS (17.8% for CVS, 9.9% for AF). Conclusions Over a period of 13 years, the indication of aMSS and aUS were increasing while AMA was decreasing for prenatal diagnosis of cytogenomic abnormalities, and there was a continuous trend of reduced invasive procedures. Prenatal evaluation using AMA/aUS was the most effective in detecting chromosomal abnormalities, but better indications for genomic abnormalities are needed.
Visual Saliency Models for Text Detection in Real World

This paper evaluates the degree of saliency of texts in natural scenes using visual saliency models. A large scale scene image database with pixel level ground truth is created for this purpose. Using this scene image database and five state-of-the-art models, visual saliency maps that represent the degree of saliency of the objects are calculated. The receiver operating characteristic curve is employed in order to evaluate the saliency of scene texts, which is calculated by visual saliency models. A visualization of the distribution of scene texts and non-texts in the space constructed by three kinds of saliency maps, which are calculated using Itti's visual saliency model with intensity, color and orientation features, is given. This visualization of distribution indicates that text characters are more salient than their non-text neighbors, and can be captured from the background. Therefore, scene texts can be extracted from the scene images. With this in mind, a new visual saliency architecture, named hierarchical visual saliency model, is proposed. Hierarchical visual saliency model is based on Itti's model and consists of two stages. In the first stage, Itti's model is used to calculate the saliency map, and Otsu's global thresholding algorithm is applied to extract the salient region that we are interested in. In the second stage, Itti's model is applied to the salient region to calculate the final saliency map. An experimental evaluation demonstrates that the proposed model outperforms Itti's model in terms of captured scene texts.
Quantitative network analysis for passenger pattern recognition: An analysis of railway stations

As recent attacks in trains and train stations show, the protections of such critical infrastructure plays a major role for public decision makers. Thereby, security installations in the railway network are a frequently discussed topic. Especially the need for an open system demands for technologies that do not influence or delay passenger flows. This also leads to the question of optimal placement of security installations such as smart camera systems or stand-off detectors. For answering this question we observed passenger flows in the Munich central station. The observation data was transferred into a quantitative network and analyzed using various measures. With its help, critical parameter constellations can be identified and investigated in detail. Furthermore we are able to identify special groups of passengers and the differences in their behavior.
Statistical Methods for Financial Engineering

Black-Scholes Model The Black-Scholes Model Dynamic Model for an Asset Estimation of Parameters Estimation Errors Black-Scholes Formula Greeks Estimation of Greeks using the Broadie-Glasserman Methodologies Multivariate Black-Scholes Model Black-Scholes Model for Several Assets Estimation of Parameters Estimation Errors Evaluation of Options on Several Assets Greeks Discussion of the Black-Scholes Model Critiques of the Model Some Extensions of the Black-Scholes Model Discrete Time Hedging Optimal Quadratic Mean Hedging Measures of Risk and Performance Measures of Risk Estimation of Measures of Risk by Monte Carlo Methods Measures of Risk and the Delta-Gamma Approximation Performance Measures Modeling Interest Rates Introduction Vasicek Model Cox-Ingersoll-Ross (CIR) Model Other Models for the Spot Rates Levy Models Complete Models Stochastic Processes with Jumps Levy Processes Examples of Levy Processes Change of Distribution Model Implementation and Estimation of Parameters Stochastic Volatility Models GARCH Models Estimation of Parameters Duan Methodology of Option Pricing Stochastic Volatility Model of Hull-White Stochastic Volatility Model of Heston Copulas and Applications Weak Replication of Hedge Funds Default Risk Modeling Dependence Bivariate Copulas Measures of Dependence Multivariate Copulas Families of Copulas Estimation of the Parameters of Copula Models Tests of Independence Tests of Goodness-of-Fit Example of Implementation of a Copula Model Filtering Description of the Filtering Problem Kalman Filter IMM Filter General Filtering Problem Computation of the Conditional Densities Particle Filters Applications of Filtering Estimation of ARMA Models Regime-Switching Markov Models Replication of Hedge Funds Appendix A: Probability Distributions Appendix B: Estimation of Parameters Index Suggested Reading, Exercises, Assignment Questions, Appendices, and References appear at the end of each chapter.
Uplink Capacity of Multi-Class IEEE 802.16j Relay Networks with Adaptive Modulation and Coding

The emerging IEEE 802.16j mobile multi-hop relay (MMR) network is currently being developed to increase the user throughput and extend the service coverage as an enhancement of existing 802.16e standard. In 802.16j, the intermediate relay stations (RSs) help the base station (BS) communicate with those mobile stations (MSs) that are either too far away from the BS or placed in an area where direct communication with BS experiences unsatisfactory level of service. In this paper, we investigate the uplink Erlang capacity of a two-hop 802.16j relay system supporting both voice and data traffics with adaptive modulation and coding (AMC) scheme applied in the physical layer. We first develop analytical models to calculate the blocking probability in the access zone and the outage probability in the relay zone, respectively. Then a joint algorithm is proposed to determine the bandwidth distribution between the access zone and the relay zone, and to derive the Erlang capacity region of the system. The numerical examples show that some capacity gains can be obtained with a relay-enhanced 802.16j system compared to the conventional single-hop 802.16e system.
Lack of Association between the GPR 3 Gene and the Risk for Alzheimer ’ s Disease

1 Azienda Ospedaliera Ospedale Civile di Legnano, Ospedale “G.Fornaroli” di Magenta, Via Al Donatore di Sangue 50, 20013 Magenta, Italy 2 Section of Biochemistry, Faculty of Medicine, University of Brescia and III Servizio Analisi, Spedali Civili di Brescia, 25123 Brescia, Italy 3 Department of Neurological Sciences, “Dino Ferrari” Center University of Milan, Fondazione Cà Granda, IRCSS Ospedale Maggiore Policlinico Fondazione, Via F. Sforza 35, 20122 Milan, Italy
Smoothing equations for large Pólya urns 1 May 29 th 2013

Consider a balanced non triangular two-color Pólya-Eggenberger urn process, assumed to be large which means that the ratio σ of the replacement matrix eigenvalues satisfies 1/2 < σ < 1. The composition vector of both discrete time and continuous time models admits a drift which is carried by the principal direction of the replacement matrix. In the second principal direction, this random vector admits also an almost sure asymptotics and a real-valued limit random variable arises, named W in discrete time and W in continous time. The paper deals with the distributions of both W . Appearing as martingale limits, known to be nonnormal, these laws remain up to now rather mysterious. Exploiting the underlying tree structure of the urn process, we show that W and W are the unique solutions of two distributional systems in some suitable spaces of integrable probability measures. These systems are natural extensions of distributional equations that already appeared in famous algorithmical problems like Quicksort analysis. Existence and unicity of the solutions of the systems are obtained by means of contracting smoothing transforms. Via the equation systems, we find upperbounds for the moments of W and W and we show that the laws of W and W are moment-determined. We also prove that W is supported by the whole real line and admits a continuous density (W was already known to have a density, infinitely differentiable on R \ {0} and not bounded at the origin).
Validation of ERA-Interim Precipitation Estimates over the Baltic Sea

European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis total precipitation estimates are validated against ten years of in situ precipitation measurements onboard of ships over the Baltic Sea. A statistical analysis for binary forecasts and mean rain rates derived from all data show a good agreement with observations. However, a closer look reveals an underestimation of ERA-Interim total precipitation in spring and an overestimation in autumn, obviously related to stability. Deriving stability and evaporation by a bulk flux scheme it could be shown, in fact, that ERA-Interim underestimates precipitation for conditions with low evaporation and strongly overestimates it for conditions with high evaporation. Since ERA-Interim surface fields become too dry with increasing evaporation compared to independent synoptic ship observations, uncertainties in the ECMWF convection scheme may possibly cause these biases in seasonal precipitation.
Facial Feature Localization Using Robust Active Shape Model and POEM Descriptors

Active Shape Model (ASM) has been shown to be a powerful tool for image interpretation, especially in feature points localization for face image. The original ASM model parameter estimation is based on the assumption that the profiles follow a Gaussian distribution. Its performance is always vulnerable to distortion due to pose, illumination and expression variations. In this paper, the improvement of ASM model concerns the following two aspects. Firstly, an adaptive parameter estimation method are proposed by defining a rotation factor. Secondly, local appearances of landmarks are originally represented by Patterns of Oriented Edge Magnitudes (POEM) descriptors, which can provide more robust and accurate guidance for searching than intensity profiles. The simulations are carried out using the IMM dataset, which contains 240 face images. Experimental results show that the proposed method significantly outperforms the original ASM and ASM plus LBP method under exterior variations.
SMT-Based Cost Optimization Approach for the Integration of Avionic Functions in IMA and TTEthernet Architectures

The design of avionic systems is a complex engineering activity. The iterative integration approach helps in controlling the complexity of such activity. On the other hand, using such approach to design evolving systems requires the reconfiguration of scheduling parameters of already integrated parts. This reconfiguration results in a recertification process having a cost that depends on the criticality level of the affected application. We propose a new approach which helps the system designer at each integration step in establishing the new scheduling parameters that minimize such cost. In this work, we focus on the Integrated Modular Avionic (IMA) architecture connected through a Time-Triggered Ethernet (TTEthernet) network. We present a formal model for such systems and we use this model to define a set of constraints that ensure the real-time requirements. These constraints are expressed using an SMTbased language and we used the SMT-solver YICES to find automatically a feasible scheduling parameters that minimize the cost of integration. We show our framework at work by analyzing the iterative integration of some functionalities of the Flight Management System.
Monolithic Multigrid Methods for Two-Dimensional Resistive Magnetohydrodynamics

Magnetohydrodynamic (MHD) representations are used to model a wide range of plasma physics applications and are characterized by a nonlinear system of partial differential equations that strongly couples a charged fluid with the evolution of electromagnetic fields. The resulting linear systems that arise from discretization and linearization of the nonlinear problem are generally difficult to solve. In this paper, we investigate multigrid preconditioners for this system. We consider two well-known multigrid relaxation methods for incompressible fluid dynamics: Braess--Sarazin relaxation and Vanka relaxation. We first extend these to the context of steady-state one-fluid viscoresistive MHD. Then we compare the two relaxation procedures within a multigrid-preconditioned GMRES method employed within Newton's method. To isolate the effects of the different relaxation methods, we use structured grids, inf-sup stable finite elements, and geometric interpolation. We present convergence and timing results for a t.
A Self-Tracking Augmented Reality System for Assembly-Guidance Applications

We present a color video-based augmented reality (AR) system that is designed to be self-tracking, that is, it requires no separate tracking subsystem. Rather, tracking is performed strictly from the video images acquired through the lens of the camera also used to view the real world. The methods for tracking are rooted in prior research in photogrammetry and computer vision. This approach to tracking for AR systems enables a variety of new applications in assembly guidance that are not feasible with current AR technology. Our initial application is in aircraft manufacturing. We outline our approaches to feature detection, correspondence, pose determination, and system calibration. The results obtained thus far are summarized along with the problems we encountered.
Multi user MIMO cooperation for wireless network: A survey

The key challenges faced by the wireless network are fading and interference. Fading is the time variation of channel strength due to environmental effect. Interference limits the capacity of spectral resource. Fading can be mitigated with cooperative transmission, as it helps to achieve diversity among user, whereas Multiple Input Multiple Output (MIMO) technique exploits interference by jointly processing the user data. Cooperative communication is type of antenna diversity among other diversity technique and there are different cooperation protocols for various scenarios. We present a review of currently known technique for Multi user MIMO cooperation and consideration of research issues related to performance. The study includes models for network, grouping and partner selection algorithm, coded cooperation and finally adaptive technique for power and bandwidth efficiency.
Analyzing Virtual Sound Source Attributes Using a Binaural Auditory Model

Virtual sound sources created with different techniques are evaluated using a computational model of auditory perception. A binaural model estimates the perceived localization cues and coloration. The cues of real and virtual sound sources are compared and the spatial attributes of the sources are discussed. The model predicts many known phenomena in loudspeaker listening and shows good agreement with empirical listening results.
Serological and infection statuses of dogs from a visceral leishmaniasis-endemic area

OBJECTIVE This study investigated the serological status of dogs living in a visceral leishmaniasis-endemic area and its correlation with the parasitological condition of the animals. METHODS Canine humoral response was evaluated using the sera of 134 dogs by enzyme-linked immunosorbent assay and immunohistochemistry to detect parasites in the skin, lymph node, and spleen of the animals. The specific antibodies investigated were IgG, IgG1, IgG2, and IgE. RESULTS According to the parasitological, laboratory, and clinical findings, the dogs were placed into one of four groups: asymptomatic with (AP+, n = 21) or without (AP-, n = 36) Leishmania tissue parasitism and symptomatic with (SP+, n = 52) or without (SP-, n = 25) parasitism. Higher IgG and IgE levels were positively correlated with the infection condition and parasite load, but not with the clinical status. In all groups, total IgG was the predominant antibody, which occurred at the expense of IgG2 instead of IgG1. Most of the infected dogs tested positive for IgG (SP+, 98.1%; AP+, 95.2%), whereas this was not observed with IgE (SP+, 80.8%; AP+, 71.2%). The most relevant finding was the high positivity of the uninfected dogs for Leishmania-specific IgG (SP-, 60.0%; AP-, 44.4%), IgE (SP-, 44.0%; AP-, 27.8%), IgG1 (SP-, 28.0%; AP-, 22.2%), and IgG2 antibodies (SP-, 56.0%; AP-, 41.7%). CONCLUSIONS The serological status of dogs, as determined by any class or subclass of antibodies, did not accurately distinguish dogs infected with L. (L.) infantum chagasi from uninfected animals. The inaccuracy of the serological result may impair not only the diagnosis, but also epidemiological investigations and strategies for visceral leishmaniasis control. This complex serological scenario occurring in a visceral leishmaniasis-endemic area highlights the challenges associated with canine diagnosis and points out the difficulties experienced by veterinary clinicians and coordinators of control programs.