Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing the Performance of Automatic Speech Recognition for Ageing Voice: Does it Correlate with Dependency Level?

Ambient Assisted Living aims at providing assistance by allowing people with special needs to perform tasks which they have increasing difficulty with and to provide reassurance through surveillance in order to detect distress and accidental falls. Aged people are among the ones who might benefit from advances in ICT to live as long as possible in their own home. Voice-base smart home is a promising way to provide AAL, but even mature technologies must be evaluated from the perspective of its potential beneficiaries. In this paper, we investigate which characteristics of the ageing voice that challenge a state of the art ASR system. Though in the literature, chronological age is retained as the sole factor predicting decrease in performance, we show that degree of loss of autonomy is even more correlated to ASR performance. Index Terms: Ambient Assisted Living (AAL), Dependency, Elderly speech, Voice command
Narrative Skills, Gender, Culture, and Children’s Long-Term Memory Accuracy of a Staged Event

ABSTRACT This study examined the extent to which school-aged children’s general narrative skills provide cognitive benefits for accurate remembering or enable good storytelling that undermines memory accuracy. European American and Chinese American 6-year-old boys and girls (N = 114) experienced a staged event in the laboratory and were asked to tell a story from a picture book that accessed their narrative skill. Children were interviewed about the staged event 6 months later to assess memory accuracy. Greater narrative skill when storytelling was associated with decreased free recall and recognition memory accuracy for the staged event. In free recall responses, this effect was driven by an increase in the likelihood that inaccurate details would be included in responses from children with better general narrative skills. For girls only, narrative skill predicted poorer recognition accuracy. Girls were also more language-proficient and provided more correct details in free recall than did boys. Chinese American children were more accurate than European American children when responding to recall prompts due to less frequent provision of incorrect details, particularly in girls. Findings are discussed in light of the roles of socialization in memory-reporting accuracy.
On Asymptotic BER Performance of the Optimal Spatial-Temporal Power Adaptation Scheme with Imperfect CSI

This paper studies the asymptotic bit-error-rate (BER) performance of the joint spatio-temporal (S-T) power adaptation which has recently been proposed for beamforming space-time-coded multiantenna systems in the presence of imperfect channel state information at the transmitter (CSIT). We derive a closed-form asymptotic solution of the power adaptation, which is instrumental in characterizing the asymptotic BER performance. We show that with imperfect CSIT, the optimal S-T scheme gives exponential diversity gain in the low and medium SNR regions when the quality of CSIT is relatively good, but cannot increase the diversity order of the space-time-coded MIMO link at very high SNR. Compared to the previous design by treating imperfect CSIT as perfect to adjust the temporal power, the optimal S-T is more robust in retaining the exponential decrease in BER over a larger range of SNR. The results sharpen our understanding of the behavior of the optimal S-T strategy.
Using Tendon Vibration between Trials to Alter Proprioceptive Sensitivity and its Influence on Upper-limb Control during Voluntary Reaching

The current study investigated the effects of a novel tendon vibration method on upperlimb position sense and upper-limb rapid movement control. The relative contributions of proprioception and vision during action were assessed. Vibration of elbow extension muscles was applied between trials to avoid reflexive activations that typically occur with vibration during movement. In the position-sense task, participants were asked to move the non-vibrated arm to match the position of the vibrated arm. In the action task, participants were asked to perform a discrete reaching movement. Vibration was found to decrease position sense precision and yielded increased trajectory variability towards the end of the movement. Notably, the influence of vibration on trajectory variability was also observed for reaches made in the presence of vision. Tendon vibration presented between trials likely perturbs proprioceptive feedback during trials. Also, it is concluded that proprioceptive information contributes significantly to the control of visually guided movements.
A Network Clustering Based Software Attribute Selection for Identifying Fault-Prone Modules

The software defect can damage the reliability and the quality of the software. The static code software metrics have been widely used and played an important role in software defect prediction. Instead of using whole features, it is quite necessary to remove the redundant features and select some meaningful features to improve the prediction performance. This study focuses on the effective attribute selection technique for the software fault classification. We proposed the software attributes network that indicates the mutual information between features and the clustering based attribute selection techniques. The results demonstrate that the proposed network clustering based feature selection performs the best on fault-prone modules prediction. The comparative feature selection techniques are examined to evaluate the result. Furthermore, the best-performed software attributes and the relations between them are shown and carefully analyzed.
A Methodology for Detecting New Binary Rootkit Exploits

Hackers who gain root privilege on a computer system usually want to maintain this level of privilege for future exploits. They do not want to have to go through the steps to regain this level of privilege because of the effort involved and the increased risk of being discovered as well as the possibility that the original exploit used to gain root access gets patched. A hacker who gains access to a system will install some method for use at a later time allowing the hacker to come back onto the system with root privilege. The hacker accomplishes this by the installation of some type of software known as a backdoor or a Trojan. One type of Trojan is known as a rootkit, in which specific system binaries necessary for the day-to-day operation of the computer system are modified or replaced by the hacker. These binaries still maintain their original functionality while allowing the hacker to maintain the ability to operate clandestinely on the host system. We propose a methodology for determining the unique signatures of common rootkits and how to determine if a compromised system is infected with a new unknown or modified previously known rootkit.
Using the Structure of HTML Documents to Improve Retrieval

The World Wide Web (WWW) is a gigantic information resource, which is growing daily. As more and more data are added to the WWW, it is becoming increasingly difficult to effectively locate useful information from this environment. In this paper, we propose a method for making use of the structures and hyperlinks of HTML documents to improve the effectiveness of retrieving HTML documents. Our study assigns the occurrences of terms in a document collection into six classes according to the tags in which a particular term appears (such as Title, H1-H6, and Anchor). Based on the assignment, we extend the weighting schemes in traditional information retrieval by incorporating different importance factors to terms in different classes. The rationale is that terms appearing in different places of a document may have different significance in identifying the document. For this research we have built a Web based search tool, Webor, created a testbed, and conducted extensive experiments to determine an optimal class importance factor combination. Our study indicates that substantial improvement of retrieval effectiveness can be achieved using this technique.
Stochastic approximation for speeding up LSTD (and LSPI)

We propose a stochastic approximation (SA) based method with randomization of samples for policy evaluation using the least squares temporal difference (LSTD) algorithm. Our method results in an $O(d)$ improvement in complexity in comparison to regular LSTD, where $d$ is the dimension of the data. We provide convergence rate results for our proposed method, both in high probability and in expectation. Moreover, we also establish that using our scheme in place of LSTD does not impact the rate of convergence of the approximate value function to the true value function and hence a low-complexity LSPI variant that uses our SA based scheme has the same order of the performance bounds as that of regular LSPI. These rate results coupled with the low complexity of our method make it attractive for implementation in big data settings, where $d$ is large. Furthermore, we analyze a similar low-complexity alternative for least squares regression and provide finite-time bounds there. We demonstrate the practicality of our method for LSTD empirically by combining it with the LSPI algorithm in a traffic signal control application. We also conduct another set of experiments that combines the SA based low-complexity variant for least squares regression with the LinUCB algorithm for contextual bandits, using the large scale news recommendation dataset from Yahoo.
The effect of eye contact on arousal and attention : A psychophysiological perspective

Eye gaze plays a special role in human interaction by carrying nonverbal information about others’ focus of attention, intentions, and mental states. In the present thesis, the effects of direct gaze on a perceiver’s arousal and attentional responses, indexed by autonomic nervous system responses, were investigated in typically developing adults (Study I and II) and in young children with and without autism spectrum disorders (ASD) (Study III). In Study I, it was shown that the direct gaze of a live person causes elevated arousal responses, measured with skin conductance, when compared with averted gaze or closed eyes. Enhanced arousal responses to direct gaze were observed irrespective of the length of the direct gaze, overruling previous speculations that enhanced arousal responses would be restricted to prolonged eye contact. In addition, enhanced arousal responses were found irrespective of individual differences in personality. Instead, individual differences in emotional stability were found to affect subjective evaluations of approach-avoidance tendency in response to direct gaze. In Study II, it was shown that direct gaze (vs. downcast gaze) had an effect on performance in a story recall task, and this effect was partially mediated by arousal. The effect of arousal on performance was negative. However, the arousal-mediated process was paralleled by another process that positively affected performance. This process was presumably related to effort allocation and motivation. The effects of participants’ belief of being seen by the storyteller on performance and arousal were also investigated, but none were found. Finally, according to the results of Study III, children with ASD did not respond to direct (vs. averted) gaze with an enhanced physiological orientation response, measured with heart rate deceleration, whereas their typically developing and developmentally delayed peers did. The results indicate that a reason for reduced eye contact behaviour in ASD might be related to omitting direct gaze as it is not a socially salient signal for them. Altogether, the present studies showed that people respond to direct gaze with enhanced autonomic arousal, and arousal partially mediates the effect of direct gaze on memory performance. In addition, autonomic nervous system responses were used as a means to broaden the understanding of the atypical eye contact behaviour of children with ASD.
Energy-efficient power control in multipath CDMA channels via large system analysis

This paper is focused on the design and analysis of power control procedures for the uplink of multipath code-division-multiple-access (CDMA) channels based on the large system analysis (LSA). Using the tools of LSA, a new decentralized power control algorithm aimed at energy efficiency maximization and requiring very little prior information on the interference background is proposed; moreover, it is also shown that LSA can be used to predict with good accuracy the performance and operational conditions of a large network operating at the equilibrium over a multipath channel, i.e. the power, signal-to-interference-plus-noise ratio (SINR) and utility profiles across users, wherein the utility is defined as the number of bits reliably delivered to the receiver for each energy-unit used for transmission. Additionally, an LSA-based performance comparison among linear receivers is carried out in terms of achieved energy efficiency at the equilibrium. Finally, the problem of the choice of the utility-maximizing training length is also considered. Numerical results show a very satisfactory agreement of the theoretical analysis with simulation results obtained with reference to systems with finite (and not so large) numbers of users.
Multiscale response of ionic systems to a spatially varying electric field

In this paper the response of ionic systems subjected to a spatially varying electric field is studied. Following the Nernst-Planck equation, two forces driving the mass flux are present, namely, the concentration gradient and the electric potential gradient. The mass flux due to the concentration gradient is modelled through Fick's law, and a new constitutive relation for the mass flux due to the potential gradient is proposed. In the regime of low screening the response function due to the potential gradient is closely related to the ionic conductivity. In the large screening regime, on the other hand, the response function is governed by the charge-charge structure. Molecular dynamics simulations are conducted and the two wave vector dependent response functions are evaluated for models of a molten salt and an ionic liquid. In the low screening regime the response functions show same wave vector dependency, indicating that it is the same underlying physical processes that govern the response. In the screening regime the wave vector dependency is very different and, thus, the overall response is determined by different processes. This is in agreement with the observed failure of the Nernst-Einstein relation.
SILEN-C3, a Phase 2 Randomized Trial with Faldaprevir plus Pegylated Interferon α-2a and Ribavirin in Treatment-Naive Hepatitis C Virus Genotype 1-Infected Patients

ABSTRACT Faldaprevir is an investigational hepatitis C virus (HCV) NS3/4A protease inhibitor which, when administered for 24 weeks in combination with pegylated interferon α-2a and ribavirin (PegIFN/RBV) in treatment-naive patients in a prior study (SILEN-C1; M. S. Sulkowski et al., Hepatology 57:2143–2154, 2013, doi:10.1002/hep.26276), achieved sustained virologic response (SVR) rates of 72 to 84%. The current randomized, open-label, parallel-group study compared the efficacy and safety of 12 versus 24 weeks of 120 mg faldaprevir administered once daily, combined with 24 or 48 weeks of PegIFN/RBV, in 160 treatment-naive HCV genotype 1 patients. Patients with maintained rapid virologic response (HCV RNA of <25 IU/ml at week 4 and undetectable at weeks 8 and 12) stopped all treatment at week 24, otherwise they continued PegIFN/RBV to week 48. SVR was achieved by 67% and 74% of patients in the 12-week and 24-week groups, respectively. Virologic response rates were lower in the 12-week group from weeks 2 to 12, during which both groups received identical treatment. SVR rates were similar in both groups for patients achieving undetectable HCV RNA. Most adverse events were mild or moderate, and 6% of patients in each treatment group discontinued treatment due to adverse events. Once-daily faldaprevir at 120 mg for 12 or 24 weeks with PegIFN/RBV resulted in high SVR rates, and the regimen was well tolerated. Differences in the overall SVR rates between the 12-week and 24-week groups were not statistically significant and possibly were due to IL28B genotype imbalances; IL28B genotype was not tested, as its significance was not known at the time of the study. These results supported phase 3 evaluation. (This study has been registered at ClinicalTrials.gov under registration no. NCT00984620).
Enhancing Transposition Per formance

Transposition is a new genetic operator alternative to crossover and allows a classical GA to achieve better results. This mechanism characterized by the presence of mobile genetic units must be used with the right parameters to enable maximum performance to the GA. This paper presents the results of an empir ical study which offers the main guidelines to choose the proper sett ing of parameters to use with transposition, which will l ead the GA to the best solutions.
Cerebral cross-perfusion and the Circle of Willis: does physiology trump anatomy?

php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Journal of Vascular Diagnostics and Interventions 2017:5 35–40 Journal of Vascular Diagnostics and Interventions Dovepress
Série Scientifique Scientific Series 2011 s24 Robust Sign-Based and Hodges-Lehmann Estimators in Linear Median Regressions with Heterogenous Serially Dependent Errors

We propose estimators for the parameters of a linear median regression without any assumption on the shape of the error distribution – including no condition on the existence of moments – allowing for heterogeneity (or heteroskedasticity) of unknown form, noncontinuous distributions, and very general serial dependence (linear or nonlinear) including GARCH-type and stochastic volatility of unknown order. The estimators follow from a reverse inference approach, based on the class of distribution-free sign tests proposed in Coudin and Dufour (2009, Econometrics J.) under a mediangale assumption. As a result, the estimators inherit strong robustness properties from their generating tests. Since the proposed estimators are based on maximizing a test statistic (or a p-value function) over different null hypotheses, they can be interpreted as Hodges-Lehmann-type (HL) estimators. It is easy to adapt the sign-based estimators to account for linear serial dependence. Both finite-sample and large-sample properties are established under weak regularity conditions. The proposed estimators are median unbiased (under symmetry and estimator unicity) and satisfy natural equivariance properties. Consistency and asymptotic normality are established without any condition on error moment existence, allowing for heterogeneity (or heteroskedasticity) of unknown form, noncontinuous distributions, and very general serial dependence (linear or nonlinear). These conditions are considerably weaker than those used to show corresponding results for LAD estimators. In a Monte Carlo study on bias and mean square error, we find that sign-based estimators perform better than LAD-type estimators, especially in heteroskedastic settings. The proposed procedures are applied to a trend model of the Standard and Poor’s composite price index, where disturbances are affected by both heavy tails (non-normality) and heteroskedasticity.
Surface object recognition with CNN and SVM in Landsat 8 images

There is a series of earth observation satellites called Landsat, which send a very large amount of image data every day such that it is hard to analyze manually. Thus an effective application of machine learning techniques to automatically analyze such data is called for. In surface object recognition, which is one of the important applications of such data, the distribution of a specific object on the surface is surveyed. In this paper, we propose and compare two methods for surface object recognition, one using the convolutional neural network (CNN) and the other support vector machine (SVM). In our experiments, CNN showed higher performance than SVM. In addition, we observed that the number of negative samples have a influence on the performance, and it is necessary to select the number of them for practical use.
Deterministic distribution sort in shared and distributed memory multiprocessors

We present an elegant deterministic load balancing strategy for distribution sort that is applicable to a wide variety of parallel diska and parallel memory hierarchies with both single and parallel processors. The simplest application of the strategy is an optimal deterministic algorithm for external sorting with multiple disks and parallel processors. In each input/output (1/0) operation, each of the D ~ 1 disks can simultaneously transfer a block of B contiguous records. Our two measures of performance are the number of 1/0s and the amount of work done by the CPU(s); our algorithm ia simultaneously optimal for both measures. We also show how to sort determiniatically in parallel memory hierarchies. When the processors are interconnected by any sort of a PRAM, our algorithms are optimal for all parallel memory hierarchies; when the interconnection network is a hypercube, our algorithms are either optimal or best-known. ●Part of this research was done while the author was at Brown University, supported in part by an IBM Graduate Fellowship, by NSF research grants CCR-9007851 and IRI-91 16451, and by Army Research Office grant DAAL03-91-G–0035. Email: nOdine@mcrc.mOt . com. t P=t of this ~csem& WM done while the author WM at Brown University. Support was provided in part by Presidential Young Investigator Award CCR-9047466 with matching funds from IBM, by NSF research grant CCR-9007851, and by Army Research Office grant DAAL03-91-G-O035. Email: jsvtlcs.duke. edu. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. ACM-SPAA’93-6/93 /Velen,Germany. Q 1993 ACM 0-8979 j-599_ 2J93/0006/OJ 20. $1-50 Jeflreg Scott Vitterf Dept. of Computer Science Duke University, Box 90129 Durham, NC 27708-0129
Integrating ROS into Educational Robotics: Bridging the Gap between Grade School and Grad School

Robots and robot competitions have been used throughout the entire STEM (science, technology, engineering, and math) education pipeline [8]. However, a gap has been identified in the focus and reinforcement of educational robotics concepts between K-12 and higher education [3]; for example, K-12 robot competitions tend to focus more on open-loop, reactive, and/or rule-based solutions with limited sensing and processing, while university-level robot competitions tend of focus more on closed-loop, deliberative, and/or inference-based solutions with advanced sensing and processing. ROS (Robot Operating System) [7] is an open-source robotics software framework that has resulted in reusable software packages [9] developed and shared by a community of robotics researchers, professionals, and hobbyists [15]. Making such advanced tools and technologies accessible to K-12 students could help bridge the education gap between K-12 and university robotics and promote more artificially intelligent (AI) solutions.