Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of long-term training on aided speech-recognition performance in noise in older adults.

PURPOSE This study examined how repeated presentations of words in noise affected understanding of both trained and untrained words in noise (in isolation and in sentences). METHOD Eight older listeners with hearing impairment completed a word-based auditory training protocol lasting approximately 12 weeks. Training materials were presented in a closed-set condition with both orthographic and auditory feedback on a trial-to-trial basis. Performance on both trained and untrained lexically easy and hard words, as well as generalization to sentences, was measured. Listeners then returned for an additional 14 weeks to monitor retention of the trained materials. RESULTS Training listeners on 1 set of words improved both their open- and closed-set recognition of the trained materials but did not improve performance on another set of untrained words. When training switched to the other set, performance for the new set of words improved significantly, whereas significant improvements on the previously trained words were maintained. Training generalized to unfamiliar talkers but did not generalize to untrained words or untrained keywords within running speech. Listeners were able to maintain improved performance over an extended period. CONCLUSION Older listeners were able to improve their word-recognition performance in noise on a set of 150 words with training.
Objective Determination of Cloud Heights and Radar Reflectivities Using a Combination of Active Remote Sensors at the ARM CART Sites

Abstract The U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Program is deploying sensitive, millimeter-wave cloud radars at its Cloud and Radiation Test Bed (CART) sites in Oklahoma, Alaska, and the tropical western Pacific Ocean. The radars complement optical devices, including a Belfort or Vaisala laser ceilometer and a micropulse lidar, in providing a comprehensive source of information on the vertical distribution of hydrometeors overhead at the sites. An algorithm is described that combines data from these active remote sensors to produce an objective determination of hydrometeor height distributions and estimates of their radar reflectivities, vertical velocities, and Doppler spectral widths, which are optimized for accuracy. These data provide fundamental information for retrieving cloud microphysical properties and assessing the radiative effects of clouds on climate. The algorithm is applied to nine months of data from the CART site in Oklahoma for initial evaluation. Much of.
An ICP inspired inverse sensor model with unknown data association

This paper introduces an Iterative Closest Point (ICP) inspired inverse sensor model for robot localisation given multiple simultaneous observations of aliased landmarks. Combined with a Kalman filter, the sensor model offers a robust alternative to maximum likelihood data association, or a computationally inexpensive alternative to a particle filter. The technique can also be used as a means for re-localising a kidnapped robot, or a sensor resetting method for a particle filter. In the RoboCup Standard Platform League, this sensor model is able to localise the robot from a single observation in 42% of field positions where multiple landmarks are visible.
Off-the-shelf sensor integration for mono-SLAM on smart devices

This work proposes a fusion of inertial measurement units (IMUs) and a visual tracking system on an embedded device. The sensor-to-sensor calibration and the pose estimation are both achieved through an unscented Kalman filter (UKF). Two approaches for a UKF-based pose estimation are presented: The first uses the estimated pose of the visual SLAM system as measurement input for the UKF; The second modifies the motion model of the visual tracking system. Our results show that IMUs increase tracking accuracy even if the visual SLAM system is untouched, while requiring little computational power. Furthermore, an accelerometer-based map scale estimation is presented and discussed.
Adverse childhood experiences and sexual risk behaviors in women: a retrospective cohort study.

CONTEXT Adverse childhood experiences such as physical abuse and sexual abuse have been shown to be related to subsequent unintended pregnancies and infection with sexually transmitted diseases. However, the extent to which sexual risk behaviors in women are associated with exposure to adverse experiences during childhood is not well-understood. METHODS A total of 5,060 female members of a managed care organization provided information about seven categories of adverse childhood experiences: having experienced emotional, physical or sexual abuse; or having had a battered mother or substance-abusing, mentally ill or criminal household members. Logistic regression was used to model the association between cumulative categories of up to seven adverse childhood experiences and such sexual risk behaviors as early onset of intercourse, 30 or more sexual partners and self-perception as being at risk for AIDS. RESULTS Each category of adverse childhood experiences was associated with an increased risk of intercourse by age 15 (odds ratios, 1.6-2.6), with perceiving oneself as being at risk of AIDS (odds ratios, 1.5-2.6) and with having had 30 or more partners (odds ratios, 1.6-3.8). After adjustment for the effects of age at interview and race, women who experienced rising numbers of types of adverse childhood experiences were increasingly likely to see themselves as being at risk of AIDS: Those with one such experience had a slightly elevated likelihood (odds ratio, 1.2), while those with 4-5 or 6-7 such experiences had substantially elevated odds (odds ratios, 1.8 and 4.9, respectively). Similarly, the number of types of adverse experiences was tied to the likelihood of having had 30 or more sexual partners, rising from odds of 1.6 for those with one type of adverse experience and 1.9 for those with two to odds of 8.2 among those with 6-7. Finally, the chances that a woman first had sex by age 15 also rose progressively with increasing numbers of such experiences, from odds of 1.8 among those with one type of adverse childhood experience to 7.0 among those with 6-7. CONCLUSIONS Among individuals with a history of adverse childhood experiences, risky sexual behavior may represent their attempts to achieve intimate interpersonal connections. Having grown up in families unable to provide needed protection, such individuals may be unprepared to protect themselves and may underestimate the risks they take in their attempts to achieve intimacy. If so, coping with such problems represents a serious public health challenge.
Adopting animal concepts in hierarchical reinforcement learning and control of intelligent agents

This research integrates rigorous methods of reinforcement learning (RL) and control engineering with a behavioral (ethology) approach to the agent technology. The main outcome is a hybrid architecture for intelligent autonomous agents targeted to the Artificial Life like environments. The architecture adopts several biology concepts and shows that they can provide robust solutions to some areas. The resulting agents perform from primitive behaviors, simple goal directed behaviors, to complex planning. The agents are fully autonomous through environment feedback evaluating internal agent state and motivates the agent to perform behaviors that return the agent towards optimal conditions. This principle is typical to animals. Learning and control is realized by multiple RL controllers working in a hierarchy of Semi Markov Decision Processes (SMDP). Used model free Q(lambda) learning works online, the agents gain experiences during interaction with the environment. The decomposition of the root SMDP into hierarchy is automated as opposed to the conventional methods that are manual. The agents assess utility of the behavior and provide rewards to RL controller as opposed to the conventional RL methods where the rewards-situations map is defined by the designer upfront. The resulting learning algorithm converges to a recursively optimal solution with probability 1. Agent behavior is continuously optimized according to the distance from the agentpsilas optimal conditions.
LQG control over finite capacity channels: the role of data losses, delays and SNR limitations

In this work we address the problem feedback control design in the present of a finite capacity communication channel, which gives rise to tightly coupled limitations in terms of quantization errors, decoding/computational delays and packet loss affecting the closed loop control performance. We restrict our analysis in the context of LQG control subject to SNR limitations, packet loss, and delay and we derive their impact on optimal design for the controller parameters. In particular, we show that the stability of the closed loop system depends on a tradeoff among quantization, packet loss probability and delay. Through this analysis we are also able to recover, as special cases, several results already available in the literature that have treated packet loss, quantization error and delay separately. We also show that the separation principle does not hold even if the controller has full knowledge of the packet loss sequence and the control inputs entering the plants. In fact the optimal control gain, when accounting for the communication constraints is, in general, different from the optimal gain derived under the classical LQG scenario, which is recaptured when the SNR over the channel goes to infinity.
Revisiting LFSRs for Cryptographic Applications

Linear finite state machines (LFSMs) are particular primitives widely used in information theory, coding theory and cryptography. Among those linear automata, a particular case of study is linear feedback shift registers (LFSRs) used in many cryptographic applications such as design of stream ciphers or pseudo-random generation. LFSRs could be seen as particular LFSMs without inputs. In this paper, we first recall the description of LFSMs using traditional matrices representation. Then, we introduce a new matrices representation with polynomial fractional coefficients. This new representation leads to sparse representations and implementations. As direct applications, we focus our work on the Windmill generators case, used for example in the E0 stream cipher and on other general applications that use this new representation. In a second part, a new design criterion called diffusion delay for LFSRs is introduced and well compared with existing related notions. This criterion represents the diffusion capacity of an LFSR. Thus, using the matrices representation, we present a new algorithm to randomly pick LFSRs with good properties (including the new one) and sparse descriptions dedicated to hardware and software designs. We present some examples of LFSRs generated using our algorithm to show the relevance of our approach.
Gamma ray energy measurement using the multiple Compton technique

Modern developments in detector and electronics technology now enable a new generation of gamma ray detectors based on recording each and every energy loss associated with an incident gamma ray. The energy of an incident gamma ray is determined by measuring the positions of the first three interactions, and the energy loss of the first two. The direction of the incident gamma ray is restricted to a conical range of possible directions. The significance of such a detector is at least three-fold: first, a gamma ray need not be totally absorbed in order to measure its full energy. Thus, relatively thinner detectors are possible. Detection efficiencies approaching 40% at 1 MeV are possible in a Si detector system of only 40 g/cm/sup 2/ thickness. Second, these detectors are naturally imaging without the need for a complex aperture or collimator. Third, these detectors have little or no Compton shelf, thus Compton rejection or heavy shielding is no longer required. We report on a simple demonstration measurement using three position sensitive detectors.
A probabilistic perspective on ensemble diversity

We study diversity in classifier ensembles from a broader perspectivethan the 0/1 loss function, the main reason being that thebias-variance decomposition of the 0/1 loss function is not unique,and therefore the relationship between ensemble accuracy and diversityis still unclear. In the parallel field of regression ensembles,where the loss function of interest is the mean squared error, thisdecomposition not only exists, but it has been shown that diversitycan be managed via the Negative Correlation (NC) framework. In thefield of probabilistic modelling the expected value of the negativelog-likelihood loss function is given by its conditional entropy; thisresult suggests that interaction information might provide someinsight into the trade off between accuracy and diversity. Ourobjective is to improve our understanding of classifier diversity byfocusing on two different loss functions -- the mean squared error andthe negative log-likelihood.In a study of mean squared error functions, we reformulate the Tumer &Ghosh model for the classification error as a regression problem, andwe show how the NC learning framework can be deployed to managediversity in classification problems. In an empirical study ofclassifiers that minimise the negative log-likelihood loss function,we discuss model diversity as opposed to error diversity in ensemblesof Naive Bayes classifiers. We observe that diversity in low-varianceclassifiers has to be structurally inferred. We apply interactioninformation to the problem of monitoring diversity in classifierensembles. We present empirical evidence that interaction informationcan capture the trade-off between accuracy and diversity, and thatdiversity occurs at different levels of interactions between baseclassifiers. We use interaction information properties to buildensembles of structurally diverse averaged Augmented Naive Bayesclassifiers. Our empirical study shows that this novel ensembleapproach is computationally more efficient than an accuracy basedapproach and at the same time it does not negatively affect theensemble classification performance.
Emotional Labor, Performance Goal Orientation, and Burnout from the Perspective of Conservation of Resources: A United States/China Comparison

Abstract Drawing on conservation of resources theory, this study explores the relationship between emotional labor and job burnout in the context of individualist versus collectivist cultures. The moderating effect of performance goal orientation is included in the analysis to learn how it relates to burnout. Based on a sample of public servants in the United States and China, results show that: (1) emotive pretending has a positive main effect on burnout, regardless of culture; (2) authentic emotive expression has no effect on burnout, regardless of culture; (3) performance goal orientation does not have a significant effect on the relationship between emotive pretending and burnout in either culture; (4) despite the positive relationship between pretending and burnout in both, it is mitigated by collectivist culture. These findings indicate that there is less difference between East and West than is usually assumed, but the nuances of culture are instructive. Implications for performance consulting, training, and development are discussed.
The Research on Modeling Document Summarization for Audio-Based Knowledge Management

There exists great text information on the internet, and there is still big unknown area in the inspection of the information. How to analyze, forecast and inspect the information will be a new issue in the field of information security. The paper, based on the calculation of semantic comparability in the how-net, proposes a series of method for calculating the semantic similarity and thus identifying the features of the text.
Prover for TLA +

Many attempts have been made to build a tool for supporting mechanized reasoning about concurrent and distributed systems using TLA. In this report we show that the theorem prover Eves works well for TLA + and we develop a veriication and design tool based on TLA + and Eves. We pay particular attention to the practicability of the approach and use adequate encoding techniques in order to produce a user-friendly tool which can be applied to realistic examples. A consistent and sound encoding for action and temporal reasoning in TLA that does not require the extensive lifting of other approaches is an important feature of the work. One essential reason for this is that both Eves and TLA are based on Zermelo-Fraenkel set theory. This work also supports the thesis that it is easier to reason in untyped formal systems. The rst case study we consider is the Radio Link Protocol.
Reflection subgroups of Euclidean reflection groups

Let X be an n-dimensional Euclidean, spherical, or hyperbolic space. A convex polytope in X is called a Coxeter polytope if all its dihedral angles are integer submultiples of π. A group generated by reflections with respect to the facets of a Coxeter polytope is discrete; a fundamental domain of this group is the initial Coxeter polytope. From now on by polytope we mean a finite volume polytope in the n-dimensional Euclidean space E. A group generated by reflections with respect to the facets of Euclidean Coxeter polytope we call a Euclidean reflection group. Finite groups generated by reflections we call spherical groups. A classification of reflection subgroups of spherical reflection groups may be deduced from [1]. A classification of reflection subgroups of Euclidean and hyperbolic reflection groups is still incomplete. Papers [2], [3], [4] and [5] are devoted to reflection subgroups of hyperbolic reflection groups with simplicial fundamental domains. In this paper, we classify reflection subgroups of discrete Euclidean reflection groups.
Designing Access Methods: The RUM Conjecture

The database research community has been building methods to store, access, and update data for more than four decades. Throughout the evolution of the structures and techniques used to access data, access methods adapt to the ever changing hardware and workload requirements. Today, even small changes in the workload or the hardware lead to a redesign of access methods. The need for new designs has been increasing as data generation and workload diversification grow exponentially, and hardware advances introduce increased complexity. New workload requirements are introduced by the emergence of new applications, and data is managed by large systems composed of more and more complex and heterogeneous hardware. As a result, it is increasingly important to develop application-aware and hardware-aware access methods. The fundamental challenges that every researcher, systems architect, or designer faces when designing a new access method are how to minimize, i) read times (R), ii) update cost (U), and iii) memory (or storage) overhead (M). In this paper, we conjecture that when optimizing the read-update-memory overheads, optimizing in any two areas negatively impacts the third. We present a simple model of the RUM overheads, and we articulate the RUM Conjecture. We show how the RUM Conjecture manifests in stateof-the-art access methods, and we envision a trend toward RUMaware access methods for future data systems.
A per-carrier semiblind multiuser receiver for SFBC downlink MIMO MC-CDMA systems

This paper proposes a per-carrier (PC) frequency-domain semiblind muliuser receiver for space-frequency block code (SFBC) downlink multiple-input multiple-output (MIMO) multi-carrier code division multiple access (MC-CDMA) with common pilot channel (CPICH) system where optimal pilot-to-data power ratio (PDPR) is considered. The receiver exploits the advantage of equalising for each carrier separately. The diversity from space-frequency (SF) and MIMO techniques passing formulated SF received multiuser shifted block signal sequence matrix can operate in systems with sufficient, insufficient or even without cyclic prefix (CP). The updated algorithm is based on projection to the subspace spanned by the pilot and the desired user spreading codes, and updated at the block level (low rate). Numerical results show that the proposed receiver significantly outperforms single-carrier (SC) semiblind and SC pilot-based receivers in MIMO fast time varying multipath frequency-selective fading channel with Doppler.
Estimating Botnet Populations from Attack Traffic

Botnets are one of the most significant perpetrators of malicious network activity; the virulence and, in particular, the number of active bots at any given time remains an open question. Previous studies have attempted to detect and monitor active bots through their “command and control” channels. This paper devises and evaluates a complementary approach: we monitor attack traffic (specifically, spamming behavior as observed at thousands of mail filtering appliances) to estimate bot populations. Our estimation method draws on population estimation techniques inspired by biology: We apply a variant of capture-recapture to logs from a large spam filtering provider that receives 300 million email messages per day from more than 8,000 unique domains. We validate our technique by comparing our estimates for the size of the Storm botnet against conventional estimation techniques and study the fluctuations in population over a two-week period.
Good Enough But I'll Just Check: Web-page Search as Attentional Refocusing

When people search a set of Web labels for links that are relevant to their information goal, they attend to the labels and estimate the likelihood that the link will lead to the goal. Recent findings indicate that people sometimes, but not always, assess only a subset of the links available. We report an ACT-R model of Web-page search that was inspired by Young’s (1998) rational account of exploratory choice, but which was also sensitive to the psychological constraints encoded in the ACT-R theory of the human cognitive architecture. The behavior of the model differs substantially from previous ACT-R models of Web navigation, at least for single-page search. We describe an experimental test of the models behavior and qualitative and quantitative fits of the
Biomimetic Remineralization of Demineralized Dentine Using Scaffold of CMC/ACP Nanocomplexes in an In Vitro Tooth Model of Deep Caries

Currently, it is still a tough task for dentists to remineralize dentine in deep caries. The aim of this study was to remineralize demineralized dentine in a tooth model of deep caries using nanocomplexes of carboxymethyl chitosan/amorphous calcium phosphate (CMC/ACP) based on mimicking the stabilizing effect of dentine matrix protein 1 (DMP1) on ACP in the biomineralization of dentine. The experimental results indicate that CMC can stabilize ACP to form nanocomplexes of CMC/ACP, which is able to be processed into scaffolds by lyophilization. In the single-layer collagen model, ACP nanoparticles are released from scaffolds of CMC/ACP nanocomplexes dissolved and then infiltrate into collagen fibrils via the gap zones (40 nm) to accomplish intrafibrillar mineralization of collagen. With this method, the completely demineralized dentine was partially remineralized in the tooth mode. This is a bottom-up remineralizing strategy based on non-classical crystallization theory. Since nanocomplexes of CMC/ACP show a promising effect of remineralization on demineralized dentine via biomimetic strategy, thereby preserving dentinal tissue to the maximum extent possible, it would be a potential indirect pulp capping (IPC) material for the management of deep caries during vital pulp therapy based on the concept of minimally invasive dentistry (MID).