Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models

Abstract A method of speaker adaptation for continuous density hidden Markov models (HMMs) is presented. An initial speaker-independent system is adapted to improve the modelling of a new speaker by updating the HMM parameters. Statistics are gathered from the available adaptation data and used to calculate a linear regression-based transformation for the mean vectors. The transformation matrices are calculated to maximize the likelihood of the adaptation data and can be implemented using the forward–backward algorithm. By tying the transformations among a number of distributions, adaptation can be performed for distributions which are not represented in the training data. An important feature of the method is that arbitrary adaptation data can be used—no special enrolment sentences are needed. Experiments have been performed on the ARPA RM1 database using an HMM system with cross-word triphones and mixture Gaussian output distributions. Results show that adaptation can be performed using as little as 11 s of adaptation data, and that as more data is used the adaptation performance improves. For example, using 40 adaptation utterances, a 37% reduction in error from the speaker-independent system was achieved with supervised adaptation and a 32% reduction in unsupervised mode.
Towards workload shift detection and prediction for autonomic databases

Due to the complexity of industry-scale database systems, the total cost of ownership for these systems is no longer dominated by hardware and software, but by administration expenses. Autonomic databases intend to reduce these costs by providing self-management features. Existing approaches towards this goal are supportive advisors for the database administrator and feedback control loops for online monitoring, analysis and re-configuration. But while advisors are too resource-consuming for continuous operation, feedback control loops suffer from overreaction, oscillation and interference. In this position paper we give a general analysis of the parameters that affect the self-management of a database. Out of these parameters, we identify that the workload has major influence on both physical design of data and DBMS configuration. Hence, we propose to employ a workload model for light-weight, continuous workload monitoring and analysis. This model can be used for the identification and prediction of significant workload shifts, which require autonomic re-configuration of the database.
Partial Efficacy of Vipassana Mindfulness Approach in Alcohol-Dependent Persons

ABSTRACT Alcohol-dependent persons who drink to manage negative emotions are likely to become lifetime drinkers. The study aimed at assessing the effectiveness of Vipassana mindfulness on alcohol intake, depression, and empathetic responses at a rehabilitation center. Mixed methods were employed, with a battery of self-report instruments (depression, cognitive, and daily drinking) and a focus group interview. There were 23 alcohol-dependent males in the intervention group and 22 in the control group. Participants completed questionnaires one week before and one month after intervention, and a focus group was held with 15 intervention participants at one-month follow-up. The intervention consisted of 2 hours a day of sitting and walking with Vipassana mindfulness for 5 consecutive days. At pretest, intervention and control groups had similar scores on demographic, alcohol intake, and depression variables. When comparing pre- and posttest scores within each group, the intervention group had lower cognitive and total depression scores postintervention, but the difference was not significant. In the focus group, participants said they had no time to practice mindfulness regularly, which may have been a reason for only gaining partial benefits from Vipassana mindfulness. Additionally, participants’ previous mindfulness experiences may have limited the success of the mindfulness approach.
Integrating probabilistic models of perception and interactive neural networks: a historical and tutorial review

This article seeks to establish a rapprochement between explicitly Bayesian models of contextual effects in perception and neural network models of such effects, particularly the connectionist interactive activation (IA) model of perception. The article is in part an historical review and in part a tutorial, reviewing the probabilistic Bayesian approach to understanding perception and how it may be shaped by context, and also reviewing ideas about how such probabilistic computations may be carried out in neural networks, focusing on the role of context in interactive neural networks, in which both bottom-up and top-down signals affect the interpretation of sensory inputs. It is pointed out that connectionist units that use the logistic or softmax activation functions can exactly compute Bayesian posterior probabilities when the bias terms and connection weights affecting such units are set to the logarithms of appropriate probabilistic quantities. Bayesian concepts such the prior, likelihood, (joint and marginal) posterior, probability matching and maximizing, and calculating vs. sampling from the posterior are all reviewed and linked to neural network computations. Probabilistic and neural network models are explicitly linked to the concept of a probabilistic generative model that describes the relationship between the underlying target of perception (e.g., the word intended by a speaker or other source of sensory stimuli) and the sensory input that reaches the perceiver for use in inferring the underlying target. It is shown how a new version of the IA model called the multinomial interactive activation (MIA) model can sample correctly from the joint posterior of a proposed generative model for perception of letters in words, indicating that interactive processing is fully consistent with principled probabilistic computation. Ways in which these computations might be realized in real neural systems are also considered.
The asymmetric impact of other-blame regret versus self-blame regret on negative word of mouth: Empirical evidence from China

Purpose This study aims to distinguish two regret conditions, other-blame regret (O-regret) and self-blame regret (S-regret), and investigate the underlying mechanism and boundary conditions of the relationship between regret and negative word of mouth (NWOM). Design/methodology/approach Four experiments and one survey study test hypotheses regarding how O-regret and S-regret influence NWOM through mediating mechanism of anger and sadness and how the impact of regret on NWOM is moderated by boundary conditions. Findings The results show that consumers who experience O-regret transmit more NWOM than those who experience S-regret. Anger is a dominant emotion when consumers experience O-regret and mediates the impact of regret on NWOM, and sadness is a dominant emotion when consumers experience S-regret and mediates the impact of regret on NWOM. In addition, purchased price (full vs discount price), regret context (private vs public context) and return policy (strict vs lenient policy) are found to moderate the effect of regret on NWOM. Research limitations/implications This study was conducted in China, which has a unique business environment that may differ from other countries. Therefore, this research opens a new avenue to further examine such a phenomenon in countries where a more lenient return policy is a standard business practice. Cross-nation studies comparing how different return policies and other business environment conditions are warranted in future research. Practical implications The study provides several insights for marketers considering the management of NWOM by understanding consumer O-regret and S-regret in either online or offline retailing situations. Originality/value This paper contributes to the extant literature by distinguishing different outcome regrets. The theoretical conceptualization and empirical findings shed further lights on the relationship between regret and other negative emotions and how O-regret and S-regret lead to different impacts on NWOM through different paths of mediation mechanism.
A methodology to design kinematics of fixations between an orthosis and a human member

The design of robotic orthoses focuses strongly on replicating kinematics of human limb. However, often sophisticated mechanisms which attempt at reproducing complex kinematics of human joints fails in adapting to geometrical variations of subjects sizes and eccentricities. One major that arrises from this mismatching is an occurrence of hyperstaticity induced by the uncontrolled interaction forces. In this paper, we take the point of view of statics to investigate the force transmission problem, which is required for a fine force control. The main result of this study focuses on designing fixations between the orthosis and the human limb that provide additional degrees of freedom. The method involves two steps. Firstly, a set of possible solutions with respect to the isostaticity criterion is derived. Then, among these possible solutions, a set of design rules considering physiological aspects of transmitting forces to human limbs is used to select a preferred configuration. As an example, the method is applied to an existing 4 active DOF arm orthosis.
Statistical Framework for Phylogenomic Analysis of Gene Family Expression Profiles

Microarray technology has produced massive expression data that are invaluable for investigating the genomewide evolutionary pattern of gene expression. To this end, phylogenetic expression analysis is highly desirable. On the basis of the Brownian process, we developed a statistical framework (called the E0 model), assuming the independent expression of evolution between lineages. Several evolutionary mechanisms are integrated to characterize the pattern of expression diversity after gene duplications, including gradual drift and dramatic shift (punctuated equilibrium). When the phylogeny of a gene family is given, we show that the likelihood function follows a multivariate normal distribution; the variance-covariance matrix is determined by the phylogenetic topology and evolutionary parameters. Maximum-likelihood methods for multiple microarray experiments are developed, and likelihood-ratio tests are designed for testing the evolutionary pattern of gene expression. To reconstruct the evolutionary trace of expression diversity after gene (or genome) duplications, we developed a Bayesian-based method and use the posterior mean as predictors. Potential applications in evolutionary genomics are discussed.
Hybrid structure of inverse filtering and DOA-parameterized wavefront synthesis

Weakness against a user's position shifting is one of the most important problems of binaural reproduction using loudspeakers. In this paper we propose a new method of inverse filtering of room acoustics with high robustness against a user's position shifting by presenting a wavefront estimated from the binaural recording. To analyze and synthesize the wavefront, we introduce a new physical modelling of the superimposition of the wavefronts weighted by multiple sound sources. By following the fluctuation of the wavefront with a time-varying filter, the analysis and synthesis overcome the limitation of the number of sound sources. Utilizing arbitrary components of the generalized inverse matrix, wavefront approximation does not degrade the accuracy of reproduction at the controlled area of the inverse filter.
Therian Femora from the Late Cretaceous of Uzbekistan

Femora referable to metatherians and eutherians recovered from the Bissekty Formation, Dzharakuduk, Kyzylkum Desert, Uzbekistan (90 Mya), are described. Fourteen isolated specimens were sorted based on size and morphology into groups that likely correspond to the species level or higher. Groups were then tentatively assigned to taxa known from teeth, petrosals, and/or other postcrania at these localities. One distal femur of a small arboreal metatherian, and several eutherian distal femora that probably represent zhelestids and/or zalambdalestids were identified. With the exception of one proximal femur that is similar in some aspects to the zalambdalestid Barunlestes, and a previously described multituberculate specimen, all other proximal femora from the Bissekty Formation exhibit a metatherian-like morphology. The dental record currently suggests the presence of twelve eutherian species and only one metatherian at Dzharakuduk, whereas the humeral and crurotarsal evidence supports the presence of at least two or four metatherian species, respectively. Given the sample size of the proximal femora, the morphological diversity present, and the overwhelming presence of eutherians at these localities, it is highly unlikely that the overwhelming majority of proximal femora actually represent metatherians. Therefore, this sample may suggest that the metatherian proximal femoral condition is primitive for Theria and that some eutherian taxa (probably including Zhelestidae, which are dentally most abundant at these localities) retain this condition.
Shrinkage estimation of the power spectrum covariance matrix

We seek to improve estimates of the power spectrum covariance matrix from a limited number of simulations by employing a novel statistical technique known as shrinkage estimation. The shrinkage technique optimally combines an empirical estimate of the covariance with a model (the target) to minimize the total mean squared error compared to the true underlying covariance. We test this technique on N-body simulations and evaluate its performance by estimating cosmological parameters. Using a simple diagonal target, we show that the shrinkage estimator significantly outperforms both the empirical covariance and the target individually when using a small number of simulations. We find that reducing noise in the covariance estimate is essential for properly estimating the values of cosmological parameters as well as their confidence intervals. We extend our method to the jackknife covariance estimator and again find significant improvement, though simulations give better results. Even for thousands of simulations we still find evidence that our method improves estimation of the covariance matrix. Because our method is simple, requires negligible additional numerical effort, and produces superior results, we always advocate shrinkage estimation for the covariance of the power spectrum and other large-scale structure measurements when purely theoretical modelling of the covariance is insufficient.
TRAINING METHOD OF A PIECEWISE LINEAR CLASSIFIER FOR A MULTI-MODAL PERSON VERIFICATION SYSTEM

In this paper we propose a training method for a Piece-wise Linear (PL) binary classifier used in a multi-modal person verification system. The training criterion used minimizes the false acceptance rate as well as false rejection rate, leading to a lower Total Error (TE) made by a multi-modal verification system. The performance of the PL classifier and Support Vector Machine (SVM) binary classifier, trained using the traditional Minimum Total Misclassification Error (MTME) criterion, is compared. The PL classifier consistently outperforms the SVM classifier with the TE on average 50% lower.
Palatal tactile sensitivity in adults with repaired cleft lip and palate

KATHERINE A. STEERE: Palatal Tactile Sensitivity in Adults with Repaired Cleft Lip and Palate (Under the direction of David Zajac) Individuals with repaired cleft lip and palate (CLP) may be at risk for decreased tactile sensitivity in the oral cavity due to surgical intervention and scarring. Three research questions were proposed: 1) Do adults with repaired CLP demonstrate reduced palatal sensitivity compared to a control group? 2) Do adults with repaired CLP exhibit longer speech segment durations of alveolar-palatal targets? 3) Is there a relationship between palatal sensitivity and duration of speech segment durations? Tongue and alveolar-palatal tactile thresholds were determined for five adults with repaired CLP and five adults without CLP, using Semmes-Weinstein monofilaments. Normalized speech segment durations were determined for the alveolar-palatal sounds The difference between groups for tactile thresholds approached significance (p=.0741). Within subjects, significant differences occurred between the tongue and alveolar-palatal sites. Correlations among tactile thresholds and speech segment durations were not significant. Clinical implications are discussed. iv ACKNOWLEDGEMENTS
Uncertainty Modeling for Expensive Functions: A Rank Transformation Approach

An uncertainty model for an expensive function greatly improves the effectiveness of a design decision based on the use of a less accurate function. In this paper, we propose a method that exploits the concept of rank transformation to aggregate high fidelity information in a cost effective manner. This information is used to develop an empirical cumulative probability distribution function for residue such that it models the uncertainty with greater precision in the regions where the expensive function is potentially attractive as compared to other regions in the design space. The performance and robustness of the algorithm are demonstrated for univariate synthetic functions.
Contribution to the Formalization of Individualized Processes during Product Innovation

Over the years, innovation has become the central element of enterprise strategy. It is only thanks to innovation that a product or a service differentiates from its competitors and creates the conditions for growth. Nowadays, innovative enterprises have to consider two aspects about new product development: (1) that it generates large product variability and (2) that it increasingly tends to regard the needs of particular customers. These two angles related to product innovation activities cause an enhancement of informational complexity. This situation complicates the management of the product's information, especially during the first phases of its lifecycle. The Product Lifecycle Management (PLM) aims to integrate product information within an information system all through its life cycle. Product traceability throughout the PLM has been improved thanks to PLM Software and the RFID (Radio Frequency Identification) technology. In particular, this technology allows collecting information individually on a given product. Our work takes part in the scope of "Product-Driven Systems". Since the product carries information, it has been given an active role during its production. It interacts individually with some parts of its production system. However, this notion of individualization still hasn't been well identified. Indeed, up to date, there is no characterization that could permit a better comprehension of what product and process individualization are about. Our aim is to make a contribution to this formalization and characterization of an individualized product. Principally, our objective is to propose an intelligible and coherent representation of an individualized product and of its relationship with its production system during the product innovation phases in the context of Systems Engineering (SE). In this paper we present the state of the art of the concepts, theories, approaches, modeling languages and modeling tools to achieve our objective. We present as well the first models that have resulted from our research. These models are still to be developed. Finally, we give a conclusion and perspectives of our future work.
Effects of Parental Migration on Mental Health of Left‐Behind Children: Evidence from Northwestern China

China's rapid development and urbanization have induced large numbers of rural residents to migrate from their homes in the countryside to urban areas in search of higher wages. It is estimated that there are more than 60 million “left-behind children” (LBC) remaining in the countryside after their parents migrate, typically living with surrogate caregivers. Extensive research has focused on the impact of parental out-migration on children's mental health, but less attention has been paid to the effects of parental return-migration. The present paper examines the changes in mental health before and after the parents of fourth and fifth grade students out-migrate or return-migrate. We draw on a panel dataset collected by the authors of more than 19000 students from 252 rural primary schools in northwestern China. Using DID and propensity score matching approaches, our results indicate that parental out-migration has a significant negative impact on the mental health of LBC, as they tend to exhibit higher levels of anxiety and lower levels of self-esteem. However, we find that parental return-migration has no significant effect on the mental health of LBC.
What Happens in Between? Human Oscillatory Brain Activity Related to Crossmodal Spatial Cueing

Previous studies investigated the effects of crossmodal spatial attention by comparing the responses to validly versus invalidly cued target stimuli. Dynamics of cortical rhythms in the time interval between cue and target might contribute to cue effects on performance. Here, we studied the influence of spatial attention on ongoing oscillatory brain activity in the interval between cue and target onset. In a first experiment, subjects underwent periods of tactile stimulation (cue) followed by visual stimulation (target) in a spatial cueing task as well as tactile stimulation as a control. In a second experiment, cue validity was modified to be 50%, 75%, or else 25%, to separate effects of exogenous shifts of attention caused by tactile stimuli from that of endogenous shifts. Tactile stimuli produced: 1) a stronger lateralization of the sensorimotor beta-rhythm rebound (15–22 Hz) after tactile stimuli serving as cues versus not serving as cues; 2) a suppression of the occipital alpha-rhythm (7–13 Hz) appearing only in the cueing task (this suppression was stronger contralateral to the endogenously attended side and was predictive of behavioral success); 3) an increase of prefrontal gamma-activity (25–35 Hz) specifically in the cueing task. We measured cue-related modulations of cortical rhythms which may accompany crossmodal spatial attention, expectation or decision, and therefore contribute to cue validity effects. The clearly lateralized alpha suppression after tactile cues in our data indicates its dependence on endogenous rather than exogenous shifts of visuo-spatial attention following a cue independent of its modality.
A Study of Sequence Clustering on Protein's Primary Structure using a Statistical Method

The clustering of biological sequences into biologically meaningful classes denotes two computationally complex challenges: the choice of a biologically pertinent and computable criterion to evaluate the clusters homogenity, and the optimal exploration of the solution space. Here we are analysing the clustering potential of a new method of sequence similarity based on statistical sequence content evaluation. Applying on the same data the popular CLUSTAL W method for sequence similarity we contrasted the results. The analysis, computational efficiency and high accuracy of the results from the new method is encouraging for further development that could make it an appealing alternative to the existent methods.
A Model-independent Technique for Determining the Embedding Dimension

The method of lag-embedding, common in the analysis of signals in the context of nonlinear dynamics, requires the selection of an embedding dimension. This embedding dimension is analogous to the model order in a linear prediction model, but the order of a linear prediction model is of little use in characterizing chaotic signals or in indicating an appropriate embedding dimension for nonlinear analysis. Nonlinear prediction models, however, have been successfully used for this purpose. Here, we describe a technique for selecting an appropriate embedding dimension that is motivated by nonlinear prediction, but does not require the speciication of the form of a prediction model.