Regression and Classification for Direction-of-Arrival Estimation with Convolutional Recurrent Neural Networks

We present a novel learning-based approach to estimate the direction-of-arrival (DOA) of a sound source using a convolutional recurrent neural network (CRNN) trained via regression on synthetic data and Cartesian labels. We also describe an improved method to generate synthetic data to train the neural network using state-of-the-art sound propagation algorithms that model specular as well as diffuse reflections of sound. We compare our model against three other CRNNs trained using different formulations of the same problem: classification on categorical labels, and regression on spherical coordinate labels. In practice, our model achieves up to 43% decrease in angular error over prior methods. The use of diffuse reflection results in 34% and 41% reduction in angular prediction errors on LOCATA and SOFA datasets, respectively, over prior methods based on image-source methods. Our method results in an additional 3% error reduction over prior schemes that use classification based networks, and we use 36% fewer network parameters

A Randomized, Controlled Trial of Meditation for Work Stress, Anxiety and Depressed Mood in Full-Time Workers

Objective. To assess the effect of meditation on work stress, anxiety and mood in full-time workers. Methods. 178 adult workers participated in an 8-week, 3-arm randomized controlled trial comparing a “mental silence” approach to meditation (n = 59) to a “relaxation” active control (n = 56) and a wait-list control (n = 63). Participants were assessed before and after using Psychological Strain Questionnaire (PSQ), a subscale of the larger Occupational Stress Inventory (OSI), the State component of the State/Trait Anxiety Inventory for Adults (STAI), and the depression-dejection (DD) subscale of the Profile of Mood States (POMS). Results. There was a significant improvement for the meditation group compared to both the relaxation control and the wait-list groups the PSQ (P = .026), and DD (P = .019). Conclusions. Mental silence-orientated meditation, in this case Sahaja Yoga meditation, is a safe and effective strategy for dealing with work stress and depressive feelings. The findings suggest that “thought reduction” or “mental silence” may have specific effects relevant to work stress and hence occupational health

Change Vector Analysis using Enhanced PCA and Inverse Triangular Function-based Thresholding

Change vector analysis is a very sophisticated method to evaluate land-use/land-cover changes meaningfully. By making proper choice of input data in the form of bands (for instance, red, NIR etc) or features (for instance, greenness, brightness, wetness etc), information about both the magnitude as well as the type/nature of changes can be extracted. However, improper selection of thresholds is always a hindrance to a good change detection algorithm. The paper has proposed an improved technique to select threshold appropriately by means of principal component difference and inverse triangular function. The changes have been represented using class-based circular wheel representation. Results have been shown to further testify the performance of proposed algorithm.Defence Science Journal, 2012, 62(4), pp.236-242, DOI:http://dx.doi.org/10.14429/dsj.62.107

Defence Electronics Applications Laboratoty, Dehradun

A system has been built and tested for automated change detection between multi-temporal panchromatic images. This paper discusses the implementation issues, associated tools, and finally summarises initial tests on IRS IC/ID and other high-resolution images. Key characteristics of this system are integration of technologies having high degree of registration, normalisation of the effects of radiometry; selectivity to specific type of changes, refinement of changes by thresholding, and assignment of presence and absence of object and tools for updation/deletion of change mask. A semi-automatic technique for selection of control points in an image having affine distortion has been implemented. Linear regression is used for normalisation of the images. Two change detection techniques, namely image subtraction and image ratioing have been used to find the global change mask. Selective threshold is used to generate target mask. Target mask is shown in two colours to depict presence and absence of the object. Method based on ratioing has been found to be more sensitive to spectral variations and provides better detection of changes

Knowledge, attitude and practice of pharmacovigilance among community pharmacists in Delhi, India

Background: Lack of knowledge of Pharmacovigilance (PhV) and Adverse Drug Reactions (ADRs) reporting culture among the prescribers have been identified as major factors for under reporting of ADRs. In an attempt to increase the reporting many countries have allowed pharmacists to report ADRs. This study was planned to assess the knowledge, attitude and practices of PhV among community pharmacist in Delhi, India.Methods: Cross sectional, questionnaire based study was conducted to evaluate the knowledge, attitude and practice of PhV among 200 community pharmacists of Delhi (west Delhi) India.Results: Majority (74%) of the respondents felt that ADR reporting is necessary but only 9% were aware of existing PhV Program of India. Only 5% of pharmacists knew about elements of PhV. Forty percent (40%) of pharmacists did not know where to report ADRs and 26% felt that there is no need to report ADRs. Significant number (77%) of pharmacists felt that ADRs reporting will damage their image. 96% never try to find ADRs and in case if they get ADRs from patients, majority (95%) of them never report to anybody. Almost all (96%) of respondents cited busy schedule as the main reason for non-reporting and 86% said that it will be very convenient if ADRs are collected by someone from them.Conclusions: Community pharmacists had positive attitude towards ADRs reporting but their knowledge and practice regarding PhV need to be improved. There is a need of regular training to increase their role in PhV

Architectural Support for Optimizing Huge Page Selection Within the OS

© 2023 Copyright held by the owner/author(s). This document is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Accepted version of a Published Work that appeared in final form in 56th ACM/IEEE International Symposium on Microarchitecture (MICRO), Toronto, Canada. To access the final edited and published work see https://doi.org/10.1145/3613424.3614296Irregular, memory-intensive applications often incur high translation lookaside buffer (TLB) miss rates that result in significant address translation overheads. Employing huge pages is an effective way to reduce these overheads, however in real systems the number of available huge pages can be limited when system memory is nearly full and/or fragmented. Thus, huge pages must be used selectively to back application memory. This work demonstrates that choosing memory regions that incur the most TLB misses for huge page promotion best reduces address translation overheads. We call these regions High reUse TLB-sensitive data (HUBs). Unlike prior work which relies on expensive per-page software counters to identify promotion regions, we propose new architectural support to identify these regions dynamically at application runtime. We propose a promotion candidate cache (PCC) that identifies HUB candidates based on hardware page table walks after a lastlevel TLB miss. This small, fixed-size structure tracks huge pagealigned regions (consisting of base pages), ranks them based on observed page table walk frequency, and only keeps the most frequently accessed ones. Evaluated on applications of various memory intensity, our approach successfully identifies application pages incurring the highest address translation overheads. Our approach demonstrates that with the help of a PCC, the OS only needs to promote 4% of the application footprint to achieve more than 75% of the peak achievable performance, yielding 1.19-1.33× speedups over 4KB base pages alone. In real systems where memory is typically fragmented, the PCC outperforms Linux’s page promotion policy by 14% (when 50% of total memory is fragmented) and 16% (when 90% of total memory is fragmented) respectively

Acoustic pulse propagation in an urban environment using a three-dimensional numerical simulation

Acoustic pulse propagation in outdoor urban environments is a physically complex phenomenon due to the predominance of reflection, diffraction, and scattering. This is especially true in non-line-of-sight cases, where edge diffraction and high-order scattering are major components of acoustic energy transport. Past work by Albert and Liu [J. Acoust. Soc. Am. 127, 1335-1346 (2010)] has shown that many of these effects can be captured using a two-dimensional finite-difference time-domain method, which was compared to the measured data recorded in an army training village. In this paper, a full three-dimensional analysis of acoustic pulse propagation is presented. This analysis is enabled by the adaptive rectangular decomposition method by Raghuvanshi, Narain and Lin [IEEE Trans. Visual. Comput. Graphics 15, 789-801 (2009)], which models sound propagation in the same scene in three dimensions. The simulation is run at a much higher usable bandwidth (nearly 450 Hz) and took only a few minutes on a desktop computer. It is shown that a three-dimensional solution provides better agreement with measured data than two-dimensional modeling, especially in cases where propagation over rooftops is important. In general, the predicted acoustic responses match well with measured results for the source/sensor locations

ACMICS: an agent communication model for interacting crowd simulation

Behavioral plausibility is one of the major aims of crowd simulation research. We present a novel approach that simulates communication between the agents and assess its influence on overall crowd behavior. Our formulation uses a communication model that tends to simulate human-like communication capability. The underlying formulation is based on a message structure that corresponds to a simplified version of Foundation for Intelligent Physical Agents Agent Communication Language Message Structure Specification. Our algorithm distinguishes between low- and high-level communication tasks so that ACMICS can be easily extended and employed in new simulation scenarios. We highlight the performance of our communication model on different crowd simulation scenarios. We also extend our approach to model evacuation behavior in unknown environments. Overall, our communication model has a small runtime overhead and can be used for interactive simulation with tens or hundreds of agents. © 2017, The Author(s)

NFATc2 Modulates Microglial Activation in the AβPP/PS1 Mouse Model of Alzheimer\u27s Disease

Alzheimer’s disease (AD) brains are characterized by fibrillar amyloid-β (Aβ) peptide containing plaques and associated reactive microglia. The proinflammatory phenotype of the microglia suggests that they may negatively affect disease course and contribute to behavioral decline. This hypothesis predicts that attenuating microglial activation may provide benefit against disease. Prior work from our laboratory and others has characterized a role for the transcription factor, nuclear factor of activated T cells (NFAT), in regulating microglial phenotype in response to different stimuli, including Aβ peptide. We observed that the NFATc2 isoform was the most highly expressed in murine microglia cultures, and inhibition or deletion of NFATc2 was sufficient to attenuate the ability of the microglia to secrete cytokines. In order to determine whether the NFATc2 isoform, in particular, was a valid immunomodulatory target in vivo, we crossed an NFATc2–/– line to a well-known AD mouse model, an AβPP/PS1 mouse line. As expected, the AβPP/PS1 x NFATc2–/– mice had attenuated cytokine levels compared to AβPP/PS1 mice as well as reduced microgliosis and astrogliosis with no effect on plaque load. Although some species differences in relative isoform expression may exist between murine and human microglia, it appears that microglial NFAT activity is a viable target for modulating the proinflammatory changes that occur during AD

Tiny but Mighty: Designing and Realizing Scalable Latency Tolerance for Manycore SoCs

Modern computing systems employ significant heterogeneity and specialization to meet performance targets at manageable power. However, memory latency bottlenecks remain problematic, particularly for sparse neural network and graph analytic applications where indirect memory accesses (IMAs) challenge the memory hierarchy. Decades of prior art have proposed hardware and software mechanisms to mitigate IMA latency, but they fail to analyze real-chip considerations, especially when used in SoCs and manycores. In this paper, we revisit many of these techniques while taking into account manycore integration and verification. We present the first system implementation of latency tolerance hardware that provides significant speedups without requiring any memory hierarchy or processor tile modifications. This is achieved through a Memory Access Parallel-Load Engine (MAPLE), integrated through the Network-on-Chip (NoC) in a scalable manner. Our hardware-software co-design allows programs to perform long-latency memory accesses asynchronously from the core, avoiding pipeline stalls, and enabling greater memory parallelism (MLP). In April 2021 we taped out a manycore chip that includes tens of MAPLE instances for efficient data supply. MAPLE demonstrates a full RTL implementation of out-of-core latency-mitigation hardware, with virtual memory support and automated compilation targetting it. This paper evaluates MAPLE integrated with a dual-core FPGA prototype running applications with full SMP Linux, and demonstrates geomean speedups of 2.35× and 2.27× over software-based prefetching and decoupling, respectively. Compared to state-of-the-art hardware, it provides geomean speedups of 1.82× and 1.72× over prefetching and decoupling techniques