36 research outputs found

    Mode-Seeking on Hypergraphs for Robust Geometric Model Fitting

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    In this paper, we propose a novel geometric model fitting method, called Mode-Seeking on Hypergraphs (MSH),to deal with multi-structure data even in the presence of severe outliers. The proposed method formulates geometric model fitting as a mode seeking problem on a hypergraph in which vertices represent model hypotheses and hyperedges denote data points. MSH intuitively detects model instances by a simple and effective mode seeking algorithm. In addition to the mode seeking algorithm, MSH includes a similarity measure between vertices on the hypergraph and a weight-aware sampling technique. The proposed method not only alleviates sensitivity to the data distribution, but also is scalable to large scale problems. Experimental results further demonstrate that the proposed method has significant superiority over the state-of-the-art fitting methods on both synthetic data and real images.Comment: Proceedings of the IEEE International Conference on Computer Vision, pp. 2902-2910, 201

    Hypergraph Modelling for Geometric Model Fitting

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    In this paper, we propose a novel hypergraph based method (called HF) to fit and segment multi-structural data. The proposed HF formulates the geometric model fitting problem as a hypergraph partition problem based on a novel hypergraph model. In the hypergraph model, vertices represent data points and hyperedges denote model hypotheses. The hypergraph, with large and "data-determined" degrees of hyperedges, can express the complex relationships between model hypotheses and data points. In addition, we develop a robust hypergraph partition algorithm to detect sub-hypergraphs for model fitting. HF can effectively and efficiently estimate the number of, and the parameters of, model instances in multi-structural data heavily corrupted with outliers simultaneously. Experimental results show the advantages of the proposed method over previous methods on both synthetic data and real images.Comment: Pattern Recognition, 201

    Intravascular large B-cell lymphoma of the kidney: A case report

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    We report a 41-year-old Chinese woman with intravascular large B-cell lymphoma diagnosed by percutaneous renal biopsy. The patient was admitted to Nanfang Hospital of Southern Medical University, Guangzhou, China with complaints of high spiking fever for a month and bilateral lower limb fatigue with difficulty ambulating for the past 5 months

    XMM-Newton and NICER Measurement of the Rms Spectrum of the Millihertz Quasiperiodic Oscillations in the Neutron-star Low-mass X-Ray Binary 4U 1636–53

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    We used two XMM-Newton and six Neutron Star Interior Composition Explorer observations to investigate the fractional rms amplitude of the millihertz quasiperiodic oscillations (mHz QPOs) in the neutron-star low-mass X-ray binary 4U 1636?53. We studied, for the first time, the fractional rms amplitude of the mHz QPOs versus energy in 4U 1636?53 down to 0.2 keV. We find that, as the energy increases from ∼0.2 to ∼3 keV, the rms amplitude of the mHz QPOs increases, different from the decreasing trend that has been previously observed above 3 keV. This finding has not yet been predicted by any current theoretical model; however, it provides an important observational feature to speculate whether a newly discovered mHz oscillation originates from the marginally stable nuclear burning process on the neutron-star surface.Fil: Lyu, Ming. Xiangtan University; ChinaFil: Zhang, Guobao. Chinese Academy Of Sciences; ChinaFil: Méndez, Mariano. University Of Groningen, Kapteyn Astronomical Institute; AlemaniaFil: Altamirano, D.. University of Southampton; Reino UnidoFil: Mancuso, Giulio Cesare. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; ArgentinaFil: Xiang, Fu-Yuan. Xiangtan University; ChinaFil: Xiao, Huaping. Xiangtan University; Chin

    Family-clinician shared decision making in intensive care units : cluster randomized trial in China

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    We thank the China Medical Board, which financially supported our study.Objective To investigate if a Family-Clinician Shared Decision-Making (FCSDM) intervention benefits patients, families and intensive care units (ICUs) clinicians.  Methods Six ICUs in China were allocated to intervention or usual care. 548 patients with critical illness, 548 family members and 387 ICU clinicians were included into the study. Structured FCSDM family meetings were held in the intervention group. Scales of SSDM, HADS, QoL2 and CSACD were used to assess families’ satisfaction and distress, patients’ quality of life, and clinicians’ collaboration respectively.  Results Comparing the intervention group with the control group at post-intervention, there were significant differences in the families’ satisfaction (P =0.0001), depression level (P =0.005), and patients’ quality of life (P =0.0007). The clinicians’ mean CSCAD score was more positive in the intervention group than controls (P < 0.05). There was no significant between-group differences on ICU daily medical cost, but the intervention group demonstrated shorter number of days’ stay in ICU (P=0.0004).  Conclusion The FCSDM intervention improved families’ satisfaction and depression, shortened patients’ duration of ICU stay, and enhanced ICU clinicians’ collaboration.  Practice implications Further improvement and promotion of the FCSDM model are needed to provide more evidence to this field in China.Publisher PDFPeer reviewe

    Applying CS and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics

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    Wireless Sensor Network (WSN) is applied widely in food cold chain logistics. However, traditional monitoring systems require significant real-time sensor data transmission which will result in heavy data traffic and communication systems overloading, and thus reduce the data collection and transmission efficiency. This research aims to develop a temperature Monitoring System for Frozen and Chilled Aquatic Products (MS-FCAP) based on WSN integrated with Compressed Sending (CS) to improve the efficiency of MS-FCAP. Through understanding the temperature and related information requirements of frozen and chilled aquatic products cold chain logistics, this paper illustrates the design of the CS model which consists of sparse sampling and data reconstruction, and shelf-life prediction. The system was implemented and evaluated in cold chain logistics between Hainan and Beijing in China. The evaluation result suggests that MS-FCAP has a high accuracy in reconstructing temperature data under variable temperature condition as well as under constant temperature condition. The result shows that MS-FCAP is capable of recovering the sampled sensor data accurately and efficiently, reflecting the real-time temperature change in the refrigerated truck during cold chain logistics, and providing effective decision support traceability for quality and safety assurance of frozen and chilled aquatic products.Agro-scientific Researc

    Methodology and experiences of rapid advice guideline development for children with COVID-19: responding to the COVID-19 outbreak quickly and efficiently

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    BACKGROUND: Rapid Advice Guidelines (RAG) provide decision makers with guidance to respond to public health emergencies by developing evidence-based recommendations in a short period of time with a scientific and standardized approach. However, the experience from the development process of a RAG has so far not been systematically summarized. Therefore, our working group will take the experience of the development of the RAG for children with COVID-19 as an example to systematically explore the methodology, advantages, and challenges in the development of the RAG. We shall propose suggestions and reflections for future research, in order to provide a more detailed reference for future development of RAGs. RESULT: The development of the RAG by a group of 67 researchers from 11 countries took 50 days from the official commencement of the work (January 28, 2020) to submission (March 17, 2020). A total of 21 meetings were held with a total duration of 48 h (average 2.3 h per meeting) and an average of 16.5 participants attending. Only two of the ten recommendations were fully supported by direct evidence for COVID-19, three recommendations were supported by indirect evidence only, and the proportion of COVID-19 studies among the body of evidence in the remaining five recommendations ranged between 10 and 83%. Six of the ten recommendations used COVID-19 preprints as evidence support, and up to 50% of the studies with direct evidence on COVID-19 were preprints. CONCLUSIONS: In order to respond to public health emergencies, the development of RAG also requires a clear and transparent formulation process, usually using a large amount of indirect and non-peer-reviewed evidence to support the formation of recommendations. Strict following of the WHO RAG handbook does not only enhance the transparency and clarity of the guideline, but also can speed up the guideline development process, thereby saving time and labor costs

    Methodology and experiences of rapid advice guideline development for children with COVID-19: responding to the COVID-19 outbreak quickly and efficiently.

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    BACKGROUND Rapid Advice Guidelines (RAG) provide decision makers with guidance to respond to public health emergencies by developing evidence-based recommendations in a short period of time with a scientific and standardized approach. However, the experience from the development process of a RAG has so far not been systematically summarized. Therefore, our working group will take the experience of the development of the RAG for children with COVID-19 as an example to systematically explore the methodology, advantages, and challenges in the development of the RAG. We shall propose suggestions and reflections for future research, in order to provide a more detailed reference for future development of RAGs. RESULT The development of the RAG by a group of 67 researchers from 11 countries took 50 days from the official commencement of the work (January 28, 2020) to submission (March 17, 2020). A total of 21 meetings were held with a total duration of 48 h (average 2.3 h per meeting) and an average of 16.5 participants attending. Only two of the ten recommendations were fully supported by direct evidence for COVID-19, three recommendations were supported by indirect evidence only, and the proportion of COVID-19 studies among the body of evidence in the remaining five recommendations ranged between 10 and 83%. Six of the ten recommendations used COVID-19 preprints as evidence support, and up to 50% of the studies with direct evidence on COVID-19 were preprints. CONCLUSIONS In order to respond to public health emergencies, the development of RAG also requires a clear and transparent formulation process, usually using a large amount of indirect and non-peer-reviewed evidence to support the formation of recommendations. Strict following of the WHO RAG handbook does not only enhance the transparency and clarity of the guideline, but also can speed up the guideline development process, thereby saving time and labor costs
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