263 research outputs found

    Energy-Efficient Inference Accelerator for Memory-Augmented Neural Networks on an FPGA

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    Memory-augmented neural networks (MANNs) are designed for question-answering tasks. It is difficult to run a MANN effectively on accelerators designed for other neural networks (NNs), in particular on mobile devices, because MANNs require recurrent data paths and various types of operations related to external memory access. We implement an accelerator for MANNs on a field-programmable gate array (FPGA) based on a data flow architecture. Inference times are also reduced by inference thresholding, which is a data-based maximum inner-product search specialized for natural language tasks. Measurements on the bAbI data show that the energy efficiency of the accelerator (FLOPS/kJ) was higher than that of an NVIDIA TITAN V GPU by a factor of about 125, increasing to 140 with inference thresholdingComment: Accepted to DATE 201

    A method to identify differential expression profiles of time-course gene data with Fourier transformation

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    BACKGROUND: Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. RESULTS: This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization. The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. CONCLUSIONS: Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics

    Quantum circuit simulation of linear optics using fermion to qubit encoding

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    This work proposes a digital quantum simulation protocol for the linear scattering process of bosons, which provides a simple extension to partially distinguishable boson cases. Our protocol is achieved by combining the boson-fermion correspondence relation and fermion to qubit encoding protocols. As a proof of concept, we designed quantum circuits for generating the Hong-Ou-Mandel dip by varying particle distinguishability. The circuits were verified with the classical and quantum simulations using the IBM Quantum and IonQ cloud services.Comment: 10 pages, 7 figure

    Painsight: An Extendable Opinion Mining Framework for Detecting Pain Points Based on Online Customer Reviews

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    As the e-commerce market continues to expand and online transactions proliferate, customer reviews have emerged as a critical element in shaping the purchasing decisions of prospective buyers. Previous studies have endeavored to identify key aspects of customer reviews through the development of sentiment analysis models and topic models. However, extracting specific dissatisfaction factors remains a challenging task. In this study, we delineate the pain point detection problem and propose Painsight, an unsupervised framework for automatically extracting distinct dissatisfaction factors from customer reviews without relying on ground truth labels. Painsight employs pre-trained language models to construct sentiment analysis and topic models, leveraging attribution scores derived from model gradients to extract dissatisfaction factors. Upon application of the proposed methodology to customer review data spanning five product categories, we successfully identified and categorized dissatisfaction factors within each group, as well as isolated factors for each type. Notably, Painsight outperformed benchmark methods, achieving substantial performance enhancements and exceptional results in human evaluations.Comment: WASSA at ACL 202

    Enhanced overall efficiency of GaInN-based light-emitting diodes with reduced efficiency droop by Al-composition-graded AlGaN/GaN superlattice electron blocking layer

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    AlxGa1-xN/GaN superlattice electron blocking layers (EBLs) with gradually decreasing Al composition toward the p-type GaN layer are introduced to GaInN-based high-power light-emitting diodes (LEDs). GaInN/GaN multiple quantum well LEDs with 5- and 9-period Al-composition-graded AlxGa1-xN/GaN EBL show comparable operating voltage, higher efficiency as well as less efficiency droop than LEDs having conventional bulk AlGaN EBL, which is attributed to the superlattice doping effect, enhanced hole injection into the active region, and reduced potential drop in the EBL by grading Al compositions. Simulation results reveal a reduction in electron leakage for the superlattice EBL, in agreement with experimental results. (C) 2013 AIP Publishing LLC.open1133sciescopu

    Communication during the Pandemic: Use of videoconferencing in Audit Committee-Auditor Communication

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    Using Korean listed firms’ mandatory disclosure on the communication method for meetings between the Audit Committee and auditors from 2019 to 2020, we find that videoconferencing leads to weaker audit quality. We measure the degree of videoconferencing by the proportion of videoconferencing in the total number of meetings between the Audit Committee and auditors. We provide preliminary results on whether changes in communication methods affect audit quality. Our results are robust to change analyses, balanced sample analyses, including auditor fixed effects, and using an alternative measure of audit quality and videoconferencing. We find that Audit Committee independence or expertise does not affect the relationship between videoconferencing and audit quality but holding more formal Audit Committee meetings during the year mitigates the negative impact of videoconferencing on audit quality. Our paper contributes to the literature on information processing of Audit Committees

    The Effect of Imbalanced Carrier Transport on the Efficiency Droop in GaInN-Based Blue and Green Light-Emitting Diodes

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    The effect of strongly-imbalanced carrier concentration and mobility on efficiency droop is studied by comparing the onset voltage of high injection, the onset current density of the droop, and the magnitude of the droop, as well as their temperature dependence, of GaInN-based blue and green light-emitting diodes (LEDs). An n-to-p asymmetry factor is defined as sigma(n)/sigma(p), and was found to be 17.1 for blue LEDs and 50.1 for green LEDs. Green LEDs, when compared to blue LEDs, were shown to enter the high-injection regime at a lower voltage, which is attributed to their less favorable p-type transport characteristics. Green LEDs, with lower hole concentration and mobility, have a lower onset current density of the efficiency droop and a higher magnitude of the efficiency droop when compared to blue LEDs. The experimental results are in quantitative agreement with the imbalanced carrier transport causing the efficiency droop, thus providing guidance for alleviating the phenomenon of efficiency droop.114sciescopu

    Allergic Inflammatory Mediated Coronary Artery Vasospasm: A Case Report of Kounis Syndrome

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    INTRODUCTION Kounis syndrome is an acute coronary syndrome occurring secondary to an anaphylactic reaction. A wide variety of triggers such as drugs and environmental exposures have been described for the so-called allergic myocardial infarction. The pathophysiology of Kounis syndrome is thought to be due to the release of inflammatory mediators such as histamine and cytokines by mast cells and eosinophils resulting in either coronary vasospasm, myocardial infarction or stent thrombosis
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