Technology of key feature identification s in malware API calls sequences

Today, almost everyone is faced with computer security problems in one or another way. Antivirus programs are used to control threats to the security of malicious software. Conventional methods for detecting malware are no longer effective enough; nowadays, neural networks and behavioral analysis technology have begun to be used for these purposes. Analyzing the behavior of programs is a difficult task, since there is no clear sequence of actions to accurately identify a program as malicious. In addition, such programs use measures to resist such detection, for example, noise masking the sequence of their work with meaningless actions. There is also the problem of uniquely identifying the class of malware due to the fact that malware can use similar methods, while being assigned to different classes. In this paper, it is proposed to use NLP methods, such as word embedding, and LDA in relation to the problems of analyzing malware API calls sequences in order to reveal the presence of semantic dependencies and assess the effectiveness of the application of these methods. The results obtained indicate the possibility of identifying the key features of malware behavior, which in the future will significantly improve the technology for detecting and identifying such programs.

The impact of visible lip movements on silent pauses in simultaneous interpreting

Simultaneous interpreting requires interpreters to listen to a source text while producing the target text in a second language. In addition, the interpreter needs to process various types of visual input, which may further increase the already high cognitive load. A study with 14 students of interpreting was conducted to investigate the impact of a speaker’s visible lip movements on cognitive load in simultaneous interpreting by analysing the duration of silent pauses in the target texts. Background noise masking the source speech was introduced as a control condition for cognitive load. Silent pause durations were shorter when interpreters saw the speaker’s lip movements, which indicates that interpreters benefitted from visual input. Furthermore, silent pause durations were longer with noise, which suggests that comparative silent pause durations can indicate changes in cognitive load.

An analytical method reduces noise bias in motor adaptation analysis

When a person makes a movement, a motor error is typically observed that then drives motor planning corrections on subsequent movements. This error correction, quantified as a trial-by-trial adaptation rate, provides insight into how the nervous system is operating, particularly regarding how much confidence a person places in different sources of information such as sensory feedback or motor command reproducibility. Traditional analysis has required carefully controlled laboratory conditions such as the application of perturbations or error clamping, limiting the usefulness of motor analysis in clinical and everyday environments. Here we focus on error adaptation during unperturbed and naturalistic movements. With increasing motor noise, we show that the conventional estimation of trial-by-trial adaptation increases, a counterintuitive finding that is the consequence of systematic bias in the estimate due to noise masking the learner’s intention. We present an analytic solution relying on stochastic signal processing to reduce this effect of noise, producing an estimate of motor adaptation with reduced bias. The result is an improved estimate of trial-by-trial adaptation in a human learner compared to conventional methods. We demonstrate the effectiveness of the new method in analyzing simulated and empirical movement data under different noise conditions.

Low-complexity artificial noise suppression methods for deep learning-based speech enhancement algorithms

Deep learning-based speech enhancement algorithms have shown their powerful ability in removing both stationary and non-stationary noise components from noisy speech observations. But they often introduce artificial residual noise, especially when the training target does not contain the phase information, e.g., ideal ratio mask, or the clean speech magnitude and its variations. It is well-known that once the power of the residual noise components exceeds the noise masking threshold of the human auditory system, the perceptual speech quality may degrade. One intuitive way is to further suppress the residual noise components by a postprocessing scheme. However, the highly non-stationary nature of this kind of residual noise makes the noise power spectral density (PSD) estimation a challenging problem. To solve this problem, the paper proposes three strategies to estimate the noise PSD frame by frame, and then the residual noise can be removed effectively by applying a gain function based on the decision-directed approach. The objective measurement results show that the proposed postfiltering strategies outperform the conventional postfilter in terms of segmental signal-to-noise ratio (SNR) as well as speech quality improvement. Moreover, the AB subjective listening test shows that the preference percentages of the proposed strategies are over 60%.

The Effect of Noise-masking Earbuds (SleepBudsTM) on Reported Sleep Quality and Tension in Health Care Shift Workers: a Prospective, Single-Subject Design Study (Preprint)

BACKGROUND Shift work is associated with sleep disorders which impair alertness and increase risk of chronic physical and mental health disease. In health care workers, shift work and its associated sleep loss decreases provider wellness and can compromise patient care. Pharmacological sleep aids or substances such as alcohol are often used to improve sleep with variable effects on health and wellbeing. OBJECTIVE We tested whether use of noise-masking earbuds can improve reported sleep quality, sleepiness, and stress level in health care shift workers, and increase alertness and reaction time post-night shift. METHODS Emergency medicine resident physicians were recruited for a prospective, single-subject design study. Entrance surveys on current sleep habits were completed. For 14 days, participants completed daily surveys reporting sleep aid use, and self-rated perceived sleepiness, tension level, and last nights’ sleep quality using an 8-point Likert scale. After overnight shifts, 3-minute psychomotor vigilance tests (PVT) measuring reaction time were completed. At the end of 14 days participants were provided noise-masking earbuds and used them in addition to their baseline sleep regimens as needed for sleep for the remainder of the study period. Daily sleep surveys, post-overnight shift PVT, and earbud use data was collected for an additional 14 days. A linear mixed effects regression model was used to assess changes in the pre- and post-intervention outcomes with participants serving as their own controls. RESULTS 36 residents were recruited, of these, 26 participants who completed daily sleep surveys and used earbuds at least once during the study period were included in final analysis. The median number of days of earbud use was 5 days (IQR [2, 9]) of the available 14 days. On days when residents reported earbud use, previous nights’ sleep quality increased by 0.5 points (P<.0001, 95% CI 0.23-0.80), daily sleepiness decreased by 0.6 points (P<.0001, 95% CI -0.90 to -0.34), and total daily tension decreased by 0.6 points (P<.0001, 95% CI -0.81 to -0.32). These effects were more pronounced in participants who reported worse than average pre-intervention sleep scores. CONCLUSIONS Non-pharmacological noise-masking interventions such as earbuds may improve daily sleepiness, tension, and perceived sleep quality in health care shift workers. Larger studies are needed to determine this interventions’ effect on other populations of shift workers, post-night shift alertness, users long-term physical and mental health, and on patient outcomes.

Vocal plasticity in harbour seal pups

ABSTRACTVocal plasticity can occur in response to environmental and biological factors, including conspecifics’ vocalisations and noise. Pinnipeds are one of the few mammalian groups capable of vocal learning, and are therefore relevant to understanding the evolution of vocal plasticity in humans and other animals. Here, we investigate the vocal plasticity of harbour seals (Phoca vitulina), a species with vocal learning abilities attested in adulthood but not puppyhood. To zoom into early mammalian vocal development, we tested 1-3 weeks old seal pups. We tailored noise playbacks to this species and age to induce seal pups to shift their fundamental frequency (F0), rather than adapt call amplitude or temporal characteristics. We exposed individual pups to bandpass-filtered noise, which purposely spanned – and masked – their typical range of F0s, and simultaneously recorded pups’ spontaneous calls. Seals were able to modify their vocalisations quite unlike most mammals: They lowered their F0 in response to increased noise. This modulation was punctual and adapted to the particular noise condition. In addition, higher noise induced less dispersion around the mean F0, suggesting that pups may have been actively focusing their phonatory efforts to target lower frequencies. Noise masking did not seem to affect call amplitude. However, one seal showed two characteristics of the Lombard effect known for human speech in noise: significant increase in call amplitude and flattening of spectral tilt. Our relatively low noise levels may have favoured F0 shifts while inhibiting amplitude adjustments. This lowering of F0 is quite unusual, as other animals commonly display no F0 shift independently of noise amplitude. Our data represents a relatively rare case in mammalian neonates, and may have implications for the evolution of vocal plasticity across species, including humans.

A notched-noise precursor affects both diotic and dichotic notched-noise masking

The present study investigates how diotic and dichotic masked thresholds, in a notched-noise masking paradigm, are affected by activation of the Medial OlivoCochlear (MOC) reflex. Thresholds were obtained for a 500-Hz pure tone diotic or a dichotic signal, S (S0 or Sπ respectively), in the presence of a simultaneous or forward diotic masker (bandpass noise with no notch or a 400-Hz notch). A diotic precursor sound (bandpass noise with a 400- or 800-Hz notch) was presented prior to the signal and masker to activate the MOC reflex. For simultaneous- and forward-masking conditions, the decrease in masked thresholds as a notch was introduced in the masker was larger for the diotic than for the dichotic condition. This resulted in a reduced binaural masking level difference (BMLD) for the masker with a notch. The precursor augmented these two effects. The results indicate that the effect of the precursor, eliciting the MOC reflex, is less pronounced when binaural cues are processed.

The Effects of Normal Aging, Subjective Cognitive Decline, Mild Cognitive Impairment, or Alzheimer's Disease on Visual Search

Background: To examine the progressively developed visual-search deficiency associated with Alzheimer's disease (AD).Methods: Healthy-younger adults (34), healthy-older adults (normal-aging control, NC, 30), adults with subjective cognitive decline (SCD, 14), amnestic mild cognitive impairment (aMCI, 20), or mild AD (15) participated in this study. To determine whether 1 of 4 letters presented at 4 symmetrically-located positions differed from the other 3, when the 4 letters were masked by either other randomly positioned and oriented letters or random-pixel noise. Meanwhile, eye movements were tracked.Results: In all the participants, with the stimulus-presentation time being longer, the visual-search performance improved, and both the eye interest-area first fixation duration (IFFD) and the interest-area-fixation count (IFC) increased. Particularly under the noise-masking condition, the AD group performed the worst at stimulus-presentation times between 300 and 900 ms. The aMCI group, but not the SCD group, performed worse than the NC group at the stimulus-presentation time of either 300 or 500 ms. The IFC was higher in all the patient groups than that in the NC group, and distinguishable between participants with AD and those with SCD or aMCI. Conclusions: The visual-search performance combined with eye-moment tracking under the noise-masking condition can be used for distinguishing AD from normal aging, SCD, and aMCI.