229 research outputs found

    Report on the Ninth Edition of the Sino-Japanese Academic Trilateral Forum held in Beijing on 5th November 2011

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    This paper is an overview of the proceedings of the Ninth Edition of the Sino-Japanese Academic Trilateral Forum held in Beijing on November 5th, 2011. 要旨本稿は2011年11月5日に北京で開催された「第9回日中三大学合同フォーラム」の概要を報告する

    Study on Leading Vehicle Detection at Night Based on Multisensor and Image Enhancement Method

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    Low visibility is one of the reasons for rear accident at night. In this paper, we propose a method to detect the leading vehicle based on multisensor to decrease rear accidents at night. Then, we use image enhancement algorithm to improve the human vision. First, by millimeter wave radar to get the world coordinate of the preceding vehicles and establish the transformation of the relationship between the world coordinate and image pixels coordinate, we can convert the world coordinates of the radar target to image coordinate in order to form the region of interesting image. And then, by using the image processing method, we can reduce interference from the outside environment. Depending on D-S evidence theory, we can achieve a general value of reliability to test vehicles of interest. The experimental results show that the method can effectively eliminate the influence of illumination condition at night, accurately detect leading vehicles, and determine their location and accurate positioning. In order to improve nighttime driving, the driver shortage vision, reduce rear-end accident. Enhancing nighttime color image by three algorithms, a comparative study and evaluation by three algorithms are presented. The evaluation demonstrates that results after image enhancement satisfy the human visual habits

    Reform of the interantional economic order: Uncertainty and economic policy coordination

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    This special issue contains a selection of articles on globalization and fintech. The contributions provide new insights on reform of the international economic order, paying special attention to uncertainty and economic policy coordination. They will certainly help improve our understanding of these topics

    Comprehensive thermal energy storage analysis of ceramic foam-enhanced molten salt in a shell-and-tube unit

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    Ceramic foam can be used to enhance the energy storage efficiency of molten salt for high-temperature solar thermal applications. However, its performance in a shell-and-tube unit is not fully understood. In this study, the energy storage performance of ceramic foam-enhanced molten salt in a shell-and-tube unit is investigated. The effects of ceramic foam configurations such as the filling height, porosity and outer diameter are studied. The results show that when the ceramic foam reaches the inner tube, the enhancement performance is remarkable, while it is insignificant in the case of below the inner tube. Although the total stored energy of the full foam-filled case is decreased by 13.6% compared to the no foam-filled case, the energy storage rate is improved by 54.9%. The variation of energy storage rate with porosity is generally regular. Ceramic foam with a small outer diameter has great enhancement performance; as the outer diameter increases, the difference in the enhancement gets less remarkable. The three factors are compared through a normalised effective porosity and the ceramic foam with varying outer diameters shows the best performance including the shortest melting time, the largest total stored energy and the highest energy storage rate. It is attributed that the ceramic foam surrounds the tube completely and concentrates around the tube, so its performance of conducting the heat of the tube is the best. The corrosion resistance of ceramic foams and the cost advantage make it a suitable thermal enhancer for molten salt in high-temperature solar thermal energy storage applications

    Single-Cell Multimodal Prediction via Transformers

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    The recent development of multimodal single-cell technology has made the possibility of acquiring multiple omics data from individual cells, thereby enabling a deeper understanding of cellular states and dynamics. Nevertheless, the proliferation of multimodal single-cell data also introduces tremendous challenges in modeling the complex interactions among different modalities. The recently advanced methods focus on constructing static interaction graphs and applying graph neural networks (GNNs) to learn from multimodal data. However, such static graphs can be suboptimal as they do not take advantage of the downstream task information; meanwhile GNNs also have some inherent limitations when deeply stacking GNN layers. To tackle these issues, in this work, we investigate how to leverage transformers for multimodal single-cell data in an end-to-end manner while exploiting downstream task information. In particular, we propose a scMoFormer framework which can readily incorporate external domain knowledge and model the interactions within each modality and cross modalities. Extensive experiments demonstrate that scMoFormer achieves superior performance on various benchmark datasets. Remarkably, scMoFormer won a Kaggle silver medal with the rank of 24/1221 (Top 2%) without ensemble in a NeurIPS 2022 competition. Our implementation is publicly available at Github.Comment: CIKM 202

    Bioassessment of a Drinking Water Reservoir Using Plankton: High Throughput Sequencing vs. Traditional Morphological Method

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    Drinking water safety is increasingly perceived as one of the top global environmental issues. Plankton has been commonly used as a bioindicator for water quality in lakes and reservoirs. Recently, DNA sequencing technology has been applied to bioassessment. In this study, we compared the effectiveness of the 16S and 18S rRNA high throughput sequencing method (HTS) and the traditional optical microscopy method (TOM) in the bioassessment of drinking water quality. Five stations reflecting different habitats and hydrological conditions in Danjiangkou Reservoir, one of the largest drinking water reservoirs in Asia, were sampled May 2016. Non-metric multi-dimensional scaling (NMDS) analysis showed that plankton assemblages varied among the stations and the spatial patterns revealed by the two methods were consistent. The correlation between TOM and HTS in a symmetric Procrustes analysis was 0.61, revealing overall good concordance between the two methods. Procrustes analysis also showed that site-specific differences between the two methods varied among the stations. Station Heijizui (H), a site heavily influenced by two tributaries, had the largest difference while station Qushou (Q), a confluence site close to the outlet dam, had the smallest difference between the two methods. Our results show that DNA sequencing has the potential to provide consistent identification of taxa, and reliable bioassessment in a long-term biomonitoring and assessment program for drinking water reservoirs
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