Graph-based Multi-View Fusion and Local Adaptation: Mitigating Within-Household Confusability for Speaker Identification

Speaker identification (SID) in the household scenario (e.g., for smart speakers) is an important but challenging problem due to limited number of labeled (enrollment) utterances, confusable voices, and demographic imbalances. Conventional speaker recognition systems generalize from a large random sample of speakers, causing the recognition to underperform for households drawn from specific cohorts or otherwise exhibiting high confusability. In this work, we propose a graph-based semi-supervised learning approach to improve household-level SID accuracy and robustness with locally adapted graph normalization and multi-signal fusion with multi-view graphs. Unlike other work on household SID, fairness, and signal fusion, this work focuses on speaker label inference (scoring) and provides a simple solution to realize household-specific adaptation and multi-signal fusion without tuning the embeddings or training a fusion network. Experiments on the VoxCeleb dataset demonstrate that our approach consistently improves the performance across households with different customer cohorts and degrees of confusability.Comment: To appear in Interspeech 2022. arXiv admin note: text overlap with arXiv:2106.0820

Applying Bayesian Neural Networks to Event Reconstruction in Reactor Neutrino Experiments

A toy detector has been designed to simulate central detectors in reactor neutrino experiments in the paper. The electron samples from the Monte-Carlo simulation of the toy detector have been reconstructed by the method of Bayesian neural networks (BNN) and the standard algorithm, a maximum likelihood method (MLD), respectively. The result of the event reconstruction using BNN has been compared with the one using MLD. Compared to MLD, the uncertainties of the electron vertex are not improved, but the energy resolutions are significantly improved using BNN. And the improvement is more obvious for the high energy electrons than the low energy ones.Comment: 9 pages, 3 figures, Accepted by NIM

The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe

The preponderance of matter over antimatter in the early Universe, the dynamics of the supernova bursts that produced the heavy elements necessary for life and whether protons eventually decay --- these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our Universe, its current state and its eventual fate. The Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed plan for a world-class experiment dedicated to addressing these questions. LBNE is conceived around three central components: (1) a new, high-intensity neutrino source generated from a megawatt-class proton accelerator at Fermi National Accelerator Laboratory, (2) a near neutrino detector just downstream of the source, and (3) a massive liquid argon time-projection chamber deployed as a far detector deep underground at the Sanford Underground Research Facility. This facility, located at the site of the former Homestake Mine in Lead, South Dakota, is approximately 1,300 km from the neutrino source at Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino charge-parity symmetry violation and mass ordering effects. This ambitious yet cost-effective design incorporates scalability and flexibility and can accommodate a variety of upgrades and contributions. With its exceptional combination of experimental configuration, technical capabilities, and potential for transformative discoveries, LBNE promises to be a vital facility for the field of particle physics worldwide, providing physicists from around the globe with opportunities to collaborate in a twenty to thirty year program of exciting science. In this document we provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess.Comment: Major update of previous version. This is the reference document for LBNE science program and current status. Chapters 1, 3, and 9 provide a comprehensive overview of LBNE's scientific objectives, its place in the landscape of neutrino physics worldwide, the technologies it will incorporate and the capabilities it will possess. 288 pages, 116 figure

Direct Search for Dark Matter by Using Dual-phase Liquid Xenon Detector and Measurement of Nuclear Recoils in Liquid Argon

Cosmological and Astrophysical observations provide compelling evidences for the existence of dark matter in the universe. One class of dark matter candidates, the Weakly Interacting Massive Particles (WIMPs), has been predicted in many particle physics theories. Direct detection experiments using dual- phase liquid noble element detectors report the best sensitivities to the detection of the dark matter particles. The next generation direct detection experiments using the same technology, are actively been built and expected to give a factor of 100 improvement on the current best sensitivity.This thesis discusses the measurement of nuclear recoils in a dual-phase liquid argon detector using a bunched neutron beam generated by linear accelerator facility at accelerator laboratory in Notre Dame University. Nuclear recoils of en- ergy ranging from 10.8 keVnr to 49.9 keVnr are measured under different drift field configurations. An electric field quenching on nuclear recoils in liquid argon is dis- covered and quantified for the first time. This quenching effect is also found to be drift field and recoil energy dependent. By varying the drift field amplitude from 100 V/cm to 1000 V/cm for each nuclear recoil energy, the quenching effect are measured as a function of nuclear recoil energy and drift field amplitude. Results from this measurement is used in the direct dark matter detection experiment to calculate the final sensitivity of direct dark matter search.A separate work on the optimization of detector design for the XENON1T detector is also discussed in detail. Finite element simulation tool is used to design and optimize the electric field in XENON1T time projection chamber. As part of the design of XENON1T detector, electron transparency across metal grids of different geometrical configurations are also studied

Effects of Low-Light Environments on the Growth and Physiological and Biochemical Parameters of <i>Indocalamus</i> and Seasonal Variations in Leaf Active Substance Contents

Indocalamus, characterized by its expansive leaves, low height, strong reproductive capacity, and abundant bioactive compounds, has extensive utility in the realms of food processing, the manufacturing of packaging materials, and the advancement of novel pharmaceuticals. Two light environments, CK (100% full light) and ST (50% full light), were established to explore the effects of low-light environments on the reproductive ability, morphological characteristics, photosynthetic properties, and leaf active substances of 14 Indocalamus species. The findings revealed that in comparison to the CK treatment, for 14 species of Indocalamus under the ST treatment, (1) the diameter, single leaf area, and leaf area index increased by 8.27%, 8.14%, and 17.88%, respectively; (2) the net photosynthetic rate decreased by 15.14%, and the total chlorophyll contents increased by 20.25%; and (3) the total flavonoid contents increased by 18.28% in autumn, the total polyphenol contents increased by 48.96% in spring, and the total polysaccharide contents increased by 31.44% and 30.81% in summer and winter, respectively. In summary, Indocalamus are adapted to survive in low-light environments; the growth and physiological indices differ significantly between the two light environments, and the low-light environment can effectively promote the growth and development of the leaves. Furthermore, the leaves are rich in flavonoids, polyphenols, polysaccharides, and active substances, which are affected by the light intensity and the season to varying degrees, and autumn and winter are the best times for harvesting the leaves. The leaves of I. hunanensis and I. lacunosus are richest in flavonoids and polyphenols, while the leaves of I. kunmingensis cv. fuminer are richest in polysaccharides. The main findings of this study demonstrate that Indocalamus has strong shade tolerance and tremendous leaf value, laying the foundation for broadening the application of their leaves and for their industrial development in understory composite planting systems

A deep learning–based fully automated program for choroidal structure analysis within the region of interest in myopic children

Purpose: To develop and validate a fully automated program for choroidal structure analysis within a 1500-μm-wide region of interest centered on the fovea (deep learning– based choroidal structure assessment program [DCAP]). Methods: A total of 2162 fovea-centered radial swept-source optical coherence tomog-raphy (SS-OCT) B-scans from 162 myopic children with cycloplegic spherical equiva-lent refraction ranging from −1.00 to −5.00 diopters were collected to develop the DCAP. Medical Transformer network and Small Attention U-Net were used to automatically segment the choroid boundaries and the nulla (the deepest point within the fovea). Automatic denoising based on choroidal vessel luminance and binarization were applied to isolate choroidal luminal/stromal areas. To further compare the DCAP with the traditional handcrafted method, the luminal/stromal areas and choroidal vascular-ity index (CVI) values for 20 OCT images were measured by three graders and the DCAP separately. Intraclass correlation coefficients (ICCs) and limits of agreement were used for agreement analysis. Results: The mean ± SD pixel-wise distances from the predicted choroidal inner, outer boundary, and nulla to the ground truth were 1.40 ± 1.23, 5.40 ± 2.24, and 1.92 ± 1.13 pixels, respectively. The mean times required for choroidal structure analysis were 1.00, 438.00 ± 75.88, 393.25 ± 78.77, and 410.10 ± 56.03 seconds per image for the DCAP and three graders, respectively. Agreement between the automatic and manual area measurements was excellent (ICCs &gt; 0.900) but poor for the CVI (0.627; 95% confidence interval, 0.279–0.832). Additionally, the DCAP demonstrated better intersession repeata-bility. Conclusions: The DCAP is faster than manual methods. Also, it was able to reduce the intra-/intergrader and intersession variations to a small extent. Translational Relevance: The DCAP could aid in choroidal structure assessment.</p