Dialogue Act Recognition via CRF-Attentive Structured Network

Dialogue Act Recognition (DAR) is a challenging problem in dialogue interpretation, which aims to attach semantic labels to utterances and characterize the speaker's intention. Currently, many existing approaches formulate the DAR problem ranging from multi-classification to structured prediction, which suffer from handcrafted feature extensions and attentive contextual structural dependencies. In this paper, we consider the problem of DAR from the viewpoint of extending richer Conditional Random Field (CRF) structural dependencies without abandoning end-to-end training. We incorporate hierarchical semantic inference with memory mechanism on the utterance modeling. We then extend structured attention network to the linear-chain conditional random field layer which takes into account both contextual utterances and corresponding dialogue acts. The extensive experiments on two major benchmark datasets Switchboard Dialogue Act (SWDA) and Meeting Recorder Dialogue Act (MRDA) datasets show that our method achieves better performance than other state-of-the-art solutions to the problem. It is a remarkable fact that our method is nearly close to the human annotator's performance on SWDA within 2% gap.Comment: 10 pages, 4figure

CashGrab

Undergraduate Engineering Science students are required to complete a group-based, two-course capstone sequence: ENSC 405W and ENSC 440. Groups form company structures and create an innovative product that potentially acts as a solution to a real-life problem. This collection archives the following assignments: proposal, design specifications, requirements specifications, and proof of concept

Conflict-related environmental damages on health: lessons learned from the past wars and ongoing Russian invasion of Ukraine

On 24 February 2022, Russian military forces invaded Ukraine. The fighting has already caused unimaginable conditions and millions of people were forced to flee their homes. For decades, conflicts have been linked to environmental pollution, exposure to radioactivity and heavy metals as well as infectious diseases. The invasion may cause specific environmental risks, like the release of radioactive substances from nuclear power plants and contaminated soils. Because international collaboration is one of the most effective ways to address environmental problems, it is critical to establish scientific bodies within a global framework to identify concrete actions and tangible measures to provide immediate assistance to citizens. This commentary discusses the above issues from lessons learned from the past wars and the way forward in the Russian invasion of Ukraine

Hydrostatic Mass Profiles of Galaxy Clusters in the eROSITA Survey

To assume hydrostatic equilibrium between the intracluster medium and the gravitational potential of galaxy clusters is an extensively used method to investigate their total masses. We want to test hydrostatic masses obtained with an observational code in the context of the SRG/eROSITA survey. We use the hydrostatic modeling code MBProj2 to fit surface-brightness profiles to simulated clusters with idealized properties as well as to a sample of 93 clusters taken from the Magneticum Pathfinder simulations. We investigate the latter under the assumption of idealized observational conditions and also for realistic eROSITA data quality. The comparison of the fitted cumulative total mass profiles and the true mass profiles provided by the simulations allows to gain knowledge about the reliability of our approach. Furthermore, we use the true profiles for gas density and pressure to compute hydrostatic mass profiles based on theory for every cluster. For an idealized cluster that was simulated to fulfill perfect hydrostatic equilibrium, we find that the cumulative total mass at the true $r_{500}$ and $r_{200}$ can be reproduced with deviations of less than 7%. For the clusters from the Magneticum Pathfinder simulations under idealized observational conditions, the median values of the fitted cumulative total masses at the true $r_{500}$ and $r_{200}$ are in agreement with our expectations, taking into account the hydrostatic mass bias. Nevertheless, we find a tendency towards a too high steepness of the cumulative total mass profiles in the outskirts. For realistic eROSITA data quality, this steepness problem intensifies for clusters with high redshifts and thus leads to too high cumulative total masses at $r_{200}$. For the hydrostatic masses based on the true profiles known from the simulations, we find a good agreement with our expectations concerning the hydrostatic mass

Accelerating Approximate Nonnegative Canonical Polyadic Decomposition using Extrapolation

peer reviewedConstrained Low-Rank Matrix Approximations : Theorical and Algorithmic Developments for Practitioners - Sources publiques européenne

Binary Neural Networks in FPGAs: Architectures, Tool Flows and Hardware Comparisons.

Binary neural networks (BNNs) are variations of artificial/deep neural network (ANN/DNN) architectures that constrain the real values of weights to the binary set of numbers {-1,1}. By using binary values, BNNs can convert matrix multiplications into bitwise operations, which accelerates both training and inference and reduces hardware complexity and model sizes for implementation. Compared to traditional deep learning architectures, BNNs are a good choice for implementation in resource-constrained devices like FPGAs and ASICs. However, BNNs have the disadvantage of reduced performance and accuracy because of the tradeoff due to binarization. Over the years, this has attracted the attention of the research community to overcome the performance gap of BNNs, and several architectures have been proposed. In this paper, we provide a comprehensive review of BNNs for implementation in FPGA hardware. The survey covers different aspects, such as BNN architectures and variants, design and tool flows for FPGAs, and various applications for BNNs. The final part of the paper gives some benchmark works and design tools for implementing BNNs in FPGAs based on established datasets used by the research community

Extrapolated Alternating Algorithms for Approximate Canonical Polyadic Decomposition

peer reviewe

Accelerating Block Coordinate Descent for Nonnegative Tensor Factorization

peer reviewe

The SRG/eROSITA All-Sky Survey: Large-scale view of the Centaurus cluster

Methods. We utilized the combined five SRG/eROSITA All-Sky Survey data (eRASS:5) to perform X-ray imaging and spectral analyses of the Centaurus cluster in various directions to large radii. Surface brightness (SB) profiles out to $2R_{200}$ were constructed. We acquired gas temperature, metallicity, and normalization per area profiles out to $R_{200}$. We compared our results with previous Centaurus studies, cluster outskirts measurements, and simulations. Comprehensive sky background analysis was done across the FoV, in particular, to assess the variation of the eROSITA Bubble emission that partially contaminates the field. Results. The processed X-ray images show the known sloshing-induced structures in the core. The core ($r\leq11~\mathrm{kpc}$) is better described with a 2T model than a 1T model. Here, we measured lower T from the cooler component (~1.0 keV) and higher Z ($\sim\!1.6Z_\odot$), signifying an iron bias. In the intermediate radial range, we observed prominent SB and normalization per area excesses in the eastern sector (Cen 45 location), reaching out to $R_{500}$. Temperature enhancements near the location of Cen 45 imply that the gas is shock-heated due to the interaction with Cen 30, the significant excess behind Cen 45 center might be the tail/ram-pressure-stripped gas. We found good agreement between the outskirt temperatures with the profile from simulations and fit from Suzaku outskirts measurements. We detected significant SB emission to the sky background level out to $R_{200}$ with a $3.5\sigma$ and followed by $2.9\sigma$ at $1.1R_{200}$. The metallicity at $R_{500}-R_{200}$ is low but within the ranges of other outskirts studies. Conclusions. We present the first measurement of ICM morphology and properties of Centaurus cluster sampling the whole azimuth beyond $30'$, increasing the probed volume by a factor of almost 30.Comment: Submitted to the Astronomy & Astrophysics journal: 19 pages, 10 figures (main text), 2 figure (appendix