Multiple vocabulary coding for 3D shape retrieval using Bag of Covariances

Bag of Covariance matrices (BoC) have been recently introduced as an extension of the standard Bag of Words (BoW) to the space of positive semi-definite matrices, which has a Riemannian structure. BoC descriptors can be constructed with various Riemannian metrics and using various quantization approaches. Each construction results in some quantization errors, which are often reduced by increasing the vocabulary size. This, however, results in a signature that is not compact, increasing both the storage and computation complexity. This article demonstrates that a compact signature, with minimum distortion, can be constructed by using multiple vocabulary based coding. Each vocabulary is constructed from a different quantization method of the covariance feature space. The proposed method also extracts non-linear dependencies between the different BoC signatures to compose the final compact signature. Our experiments show that the proposed approach can boost the performance of the BoC descriptors in various 3D shape classification and retrieval tasks

Reducing Disparities by way of a Cancer Disparities Research Training Program

Background: For minority populations, there is a continuing disparity in the burden of death and illness from cancer. Research to address this disparity should be conducted by investigators who can best understand and address the needs of culturally diverse communities. However, minorities are under-represented in health-related research. The goal of this project was to develop and evaluate an approach to motivating and preparing master’s degree students for careers dedicated to cancer disparities research. Method: A Cancer Disparities Research Training Program (CDRTP) was initiated in 2010. The program consists of coursework, practicum experiences, and research opportunities. Assessment of the curriculum is based on monitoring achievement of evaluation indicators and includes a quantitative assessment and qualitative approach. Results: In its first three years, the program graduated 20 trainees, all of whom were minorities (18 African Americans and two Asians). When asked about career goals, two-thirds of the trainees indicated interest in pursuing careers in research on cancer prevention and control. The trainees expressed high satisfaction with the courses, instructor, materials, and curriculum. Although trainees had suggestions about course details, evaluations overall were positive. Across focus groups, three recurrent themes emerged regarding activities to enhance the student experience: having a wider variety of topics, more guest speakers, and field trips. Conclusion: The CDRTP was intended to recruit students – primarily African Americans – into research on prevention and control of cancer disparities. Although final evaluation of the program’s overall outcome will not be available for several years, a preliminary evaluation indicates the program is being successful

Deep Shape Matching

We cast shape matching as metric learning with convolutional networks. We break the end-to-end process of image representation into two parts. Firstly, well established efficient methods are chosen to turn the images into edge maps. Secondly, the network is trained with edge maps of landmark images, which are automatically obtained by a structure-from-motion pipeline. The learned representation is evaluated on a range of different tasks, providing improvements on challenging cases of domain generalization, generic sketch-based image retrieval or its fine-grained counterpart. In contrast to other methods that learn a different model per task, object category, or domain, we use the same network throughout all our experiments, achieving state-of-the-art results in multiple benchmarks.Comment: ECCV 201

SHREC'16 Track: 3D Sketch-Based 3D Shape Retrieval

Sketch-based 3D shape retrieval has unique representation availability of the queries and vast applications. Therefore, it has received more and more attentions in the research community of content-based 3D object retrieval. However, sketch-based 3D shape retrieval is a challenging research topic due to the semantic gap existing between the inaccurate representation of sketches and accurate representation of 3D models. In order to enrich and advance the study of sketch-based 3D shape retrieval, we initialize the research on 3D sketch-based 3D model retrieval and collect a 3D sketch dataset based on a developed 3D sketching interface which facilitates us to draw 3D sketches in the air while standing in front of a Microsoft Kinect. The objective of this track is to evaluate the performance of different 3D sketch-based 3D model retrieval algorithms using the hand-drawn 3D sketch query dataset and a generic 3D model target dataset. The benchmark contains 300 sketches that are evenly divided into 30 classes, as well as 1 258 3D models that are classified into 90 classes. In this track, nine runs have been submitted by five groups and their retrieval performance has been evaluated using seven commonly used retrieval performance metrics. We wish this benchmark, the comparative evaluation results and the corresponding evaluation code will further promote sketch-based 3D shape retrieval and its applications

Identifying Community-Engaged Translational Research Collaboration Experience and Health Interests of Community-Based Organizations Outside of Metropolitan Atlanta

Background: While rural health research has increased over the last two decades, there is limited understanding of the self-reported health priorities and research interests of rural and suburban community-based representatives and residents. These insights can be used to inform more successful intervention strategies that are responsive to the lived experiences of local residents and leaders who are the gatekeepers to buy-in and sustainability of community engaged research. The Georgia Clinical and Translational Science Alliance, a collaboration between four academic institutions includes a Community Engagement Program (CE) designed to facilitate community-academic research partnerships. This study aimed to assess the health priorities, community-academic research experience, and interests of community respondents outside of Metropolitan Atlanta through the Community Engagement Facilitation Survey (CEFS). Methods: CE Program and Community Steering Board created the CEFS to assess the health topic priorities, research experience, and interests of community-based representatives and community members across the state of Georgia. The 11-item survey was administered (paper and electronic surveys) statewide at community events and professional organization meetings. Descriptive statistics were analyzed, and geospatial mapping was conducted. Data were analyzed in SPSS and Microsoft Excel software systems to clean data and to calculate data counts and percentages. Three maps were created in Tableau Version 19.2 depicting all counties represented by the survey sample superimposed with the counties from which at least one respondent indicated each of the top three health priorities for this sample. Results: Four-hundred six (406) surveys were analyzed, representing 83.6% of rural and suburban Georgia counties. The most frequently identified health priorities and research interests were diabetes, cancer, high blood pressure, and mental health

Overview of JET results for optimising ITER operation

The JET 2019–2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major neutral beam injection upgrade providing record power in 2019–2020, and tested the technical and procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle (α) physics in the coming D–T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed shattered pellet injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design and operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D–T benefited from the highest D–D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER

The role of ETG modes in JET-ILW pedestals with varying levels of power and fuelling

We present the results of GENE gyrokinetic calculations based on a series of JET-ITER-like-wall (ILW) type I ELMy H-mode discharges operating with similar experimental inputs but at different levels of power and gas fuelling. We show that turbulence due to electron-temperature-gradient (ETGs) modes produces a significant amount of heat flux in four JET-ILW discharges, and, when combined with neoclassical simulations, is able to reproduce the experimental heat flux for the two low gas pulses. The simulations plausibly reproduce the high-gas heat fluxes as well, although power balance analysis is complicated by short ELM cycles. By independently varying the normalised temperature gradients (omega(T)(e)) and normalised density gradients (omega(ne )) around their experimental values, we demonstrate that it is the ratio of these two quantities eta(e) = omega(Te)/omega(ne) that determines the location of the peak in the ETG growth rate and heat flux spectra. The heat flux increases rapidly as eta(e) increases above the experimental point, suggesting that ETGs limit the temperature gradient in these pulses. When quantities are normalised using the minor radius, only increases in omega(Te) produce appreciable increases in the ETG growth rates, as well as the largest increases in turbulent heat flux which follow scalings similar to that of critical balance theory. However, when the heat flux is normalised to the electron gyro-Bohm heat flux using the temperature gradient scale length L-Te, it follows a linear trend in correspondence with previous work by different authors

Spectroscopic camera analysis of the roles of molecularly assisted reaction chains during detachment in JET L-mode plasmas

The roles of the molecularly assisted ionization (MAI), recombination (MAR) and dissociation (MAD) reaction chains with respect to the purely atomic ionization and recombination processes were studied experimentally during detachment in low-confinement mode (L-mode) plasmas in JET with the help of experimentally inferred divertor plasma and neutral conditions, extracted previously from filtered camera observations of deuterium Balmer emission, and the reaction coefficients provided by the ADAS, AMJUEL and H2VIBR atomic and molecular databases. The direct contribution of MAI and MAR in the outer divertor particle balance was found to be inferior to the electron-atom ionization (EAI) and electron-ion recombination (EIR). Near the outer strike point, a strong atom source due to the D+2-driven MAD was, however, observed to correlate with the onset of detachment at outer strike point temperatures of Te,osp = 0.9-2.0 eV via increased plasma-neutral interactions before the increasing dominance of EIR at Te,osp < 0.9 eV, followed by increasing degree of detachment. The analysis was supported by predictions from EDGE2D-EIRENE simulations which were in qualitative agreement with the experimental observations

Shattered pellet injection experiments at JET in support of the ITER disruption mitigation system design

A series of experiments have been executed at JET to assess the efficacy of the newly installed shattered pellet injection (SPI) system in mitigating the effects of disruptions. Issues, important for the ITER disruption mitigation system, such as thermal load mitigation, avoidance of runaway electron (RE) formation, radiation asymmetries during thermal quench mitigation, electromagnetic load control and RE energy dissipation have been addressed over a large parameter range. The efficiency of the mitigation has been examined for the various SPI injection strategies. The paper summarises the results from these JET SPI experiments and discusses their implications for the ITER disruption mitigation scheme