2,376 research outputs found

    Sampled Weighted Min-Hashing for Large-Scale Topic Mining

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    We present Sampled Weighted Min-Hashing (SWMH), a randomized approach to automatically mine topics from large-scale corpora. SWMH generates multiple random partitions of the corpus vocabulary based on term co-occurrence and agglomerates highly overlapping inter-partition cells to produce the mined topics. While other approaches define a topic as a probabilistic distribution over a vocabulary, SWMH topics are ordered subsets of such vocabulary. Interestingly, the topics mined by SWMH underlie themes from the corpus at different levels of granularity. We extensively evaluate the meaningfulness of the mined topics both qualitatively and quantitatively on the NIPS (1.7 K documents), 20 Newsgroups (20 K), Reuters (800 K) and Wikipedia (4 M) corpora. Additionally, we compare the quality of SWMH with Online LDA topics for document representation in classification.Comment: 10 pages, Proceedings of the Mexican Conference on Pattern Recognition 201

    Frequency Control of Multi-Pulse 2-micron Laser Transmitter for Atmospheric Carbon Dioxide Measurement

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    Laser sources with highly stabilized emission wavelength is of paramount importance for a long term atmospheric carbon dioxide (CO2) measurement from a space platform. Integrated Path Differential Absorption (IPDA) lidar is a promising instrument for such a task. The design of a laser transmitter, with emphasis on the method used to control and select several wavelengths, is presented. This multi-pulsed, injection seeded, 2-m transmitter uses a Ho:Tm:YLF laser crystal which has matching emission to the absorption of CO2 in the R30 spectroscopic area. The injection seeded laser produces triple single longitudinal mode transform limited line width pulses with a total of 80 mJ at a repetition rate of 50 Hz

    Multi-sensor fusion based on multiple classifier systems for human activity identification

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    Multimodal sensors in healthcare applications have been increasingly researched because it facilitates automatic and comprehensive monitoring of human behaviors, high-intensity sports management, energy expenditure estimation, and postural detection. Recent studies have shown the importance of multi-sensor fusion to achieve robustness, high-performance generalization, provide diversity and tackle challenging issue that maybe difficult with single sensor values. The aim of this study is to propose an innovative multi-sensor fusion framework to improve human activity detection performances and reduce misrecognition rate. The study proposes a multi-view ensemble algorithm to integrate predicted values of different motion sensors. To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection systems. To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. Furthermore, we utilized Synthetic Over-sampling minority Techniques (SMOTE) algorithm to reduce the impact of class imbalance and improve performance results. With the above methods, this paper provides unified framework to resolve major challenges in human activity identification. The performance results obtained using two publicly available datasets showed significant improvement over baseline methods in the detection of specific activity details and reduced error rate. The performance results of our evaluation showed 3% to 24% improvement in accuracy, recall, precision, F-measure and detection ability (AUC) compared to single sensors and feature-level fusion. The benefit of the proposed multi-sensor fusion is the ability to utilize distinct feature characteristics of individual sensor and multiple classifier systems to improve recognition accuracy. In addition, the study suggests a promising potential of hybrid feature selection approach, diversity-based multiple classifier systems to improve mobile and wearable sensor-based human activity detection and health monitoring system. - 2019, The Author(s).This research is supported by University of Malaya BKP Special Grant no vote BKS006-2018.Scopu

    Cross-aisle seismic performance of selective storage racks

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    © 2020 A series of single-axis shaking table tests were conducted on three full-scale selective storage racks in the cross-aisle direction. The uplifting and rocking behaviour of the racks was examined under three baseplate types: ductile, heavy duty, and unanchored. Each rack was subjected to a sequence of ground motions of increasing intensity up to failure, with a total of 29 tests conducted. At 1.5 times the respective design level ground motions, the heavy duty baseplates caused a foundation failure while the unanchored rack failed by overturning. The rack with ductile baseplates survived all tests up to 2.3 times the design level. For a given ground motion, the unanchored rack upright always had the smallest peak axial load. However, the unanchored rack had much larger sways under the Northbridge and Kobe ground motions. The NZS 1170.5 equivalent static method design loading was found to be overly conservative for racks with ductile and heavy duty baseplates, of which the upright design axial forces were better predicted using the refined equivalent static method

    NADH- and NAD(P)H-Nitrate Reductases in Rice Seedlings

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    Decay and coherence of two-photon excited yellow ortho-excitons in Cu2O

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    Photoluminescence excitation spectroscopy has revealed a novel, highly efficient two-photon excitation method to produce a cold, uniformly distributed high density excitonic gas in bulk cuprous oxide. A study of the time evolution of the density, temperature and chemical potential of the exciton gas shows that the so called quantum saturation effect that prevents Bose-Einstein condensation of the ortho-exciton gas originates from an unfavorable ratio between the cooling and recombination rates. Oscillations observed in the temporal decay of the ortho-excitonic luminescence intensity are discussed in terms of polaritonic beating. We present the semiclassical description of polaritonic oscillations in linear and non-linear optical processes.Comment: 14 pages, 12 figure

    Pancreatic Head Mass from Metastatic Meningeal Hemangiopericytoma

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    Purpose. To illustrate the propensity of meningeal hemangiopericytoma to spread extraneurally, as a distinction to the ordinary meningioma
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