三甘醇脱水填料塔计算方法适用性分析

塔径计算是进行三甘醇填料脱水塔设计的首要工作,为了选用准确适用的塔径计算方法,详细介绍了多种塔径计算方法。以两个实际项目的数据为计算案例,分别采用贝恩-霍根(Bain-Haugen)关联式、通用压降关联图法(GPDC)、塔负荷系数法、Aspen HYSYS软件等不同方法计算三甘醇填料脱水塔的塔径,并进行了计算结果偏差分析和计算方法适用性分析。结果分析表明,塔负荷系数法、通用压降关联图法(GPDC)、Aspen HYSYS软件计算结果相近,经圆整后的塔径一致。贝恩-霍根(Bain-Haugen)关联式算出的结果偏差较大,过于保守,分别为11.11%和8.73%。由于通用压降关联图法(GPDC)的计算结果受GPDC关联图内数据点影响准确度不易保证,建议选用塔负荷系数法和Aspen HYSYS软件进行三甘醇脱水填料塔塔径的计算。      

E?cient Video Cutout by Paint Selection

Video cutout refers to extracting moving objects from videos, which is an important step in many video editing tasks. Recent algorithms have limitations in terms of e?ciency, interaction style, and rob...     

Mathematical representation of radiality constraint in distribution system reconfiguration problem

Distribution systems are most commonly operated in a radial configuration for a number of reasons. In order to impose radiality constraint in the optimal network reconfiguration problem, an efficient algorithm is introduced in this paper based on graph theory. The paper shows that the normally followed methods of imposing radiality constraint within a mixed-integer programming formulation of the reconfiguration problem may not be sufficient. The minimum-loss network reconfiguration problem is formulated using different ways to impose radiality constraint. It is shown, through simulations, that the formulated problem using the proposed method for representing radiality constraint can be solved more efficiently, as opposed to the previously proposed formulations. This results in up to 30% reduction in CPU time for the test systems used in this study.     

SINA: Semantic interpretation of user queries for question answering on interlinked data

The architectural choices underlying Linked Data have led to a compendium of data sources which contain both duplicated and fragmented information on a large number of domains. One way to enable non-experts users to access this data compendium is to provide keyword search frameworks that can capitalize on the inherent characteristics of Linked Data. Developing such systems is challenging for three main reasons. First, resources across different datasets or even within the same dataset can be homonyms. Second, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain user query. Finally, constructing a federated formal query from keywords across different datasets requires exploiting links between the different datasets on both the schema and instance levels. We present Sina, a scalable keyword search system that can answer user queries by transforming user-supplied keywords or natural-languages queries into conjunctive SPARQL queries over a set of interlinked data sources. Sina uses a hidden Markov model to determine the most suitable resources for a user-supplied query from different datasets. Moreover, our framework is able to construct federated queries by using the disambiguated resources and leveraging the link structure underlying the datasets to query. We evaluate Sina over three different datasets. We can answer 25 queries from the QALD-1 correctly. Moreover, we perform as well as the best question answering system from the QALD-3 competition by answering 32 questions correctly while also being able to answer queries on distributed sources. We study the runtime of SINA in its mono-core and parallel implementations and draw preliminary conclusions on the scalability of keyword search on Linked Data.     

Robust skin detection in real-world images

Human skin detection in images is desirable in many practical applications, e.g., human–computer interaction and adult-content filtering. However, existing methods are mainly suffer from confusing backgrounds in real-world images. In this paper, we try to address this issue by exploring and combining several human skin properties, i.e. color property, texture property and region property. First, images are divided into superpixels, and robust skin seeds and background seeds are acquired through color property and texture property of skin. Then we combining color, region and texture properties of skin by proposing a novel skin color and texture based graph cuts (SCTGC) to acquire the final skin detection results. Comprehensive and comparative experiments show that the proposed method achieves promising performance and outperforms many state-of-the-art methods over publicly available challenging datasets with a great part of hard images.     

基于Citespace的我国稀土出口研究进展与热点分析

随着战略性新兴产业的兴起发展，稀土作为战略资源的重要地位不断凸显，作为公共产品供给，稀土出口问题备受国内外关注。文章运用CiteSpace软件并基于文献计量与知识图谱分析方法，以CNKI文献资料为数据源，对1993~2019年稀土出口研究相关文献从发文量、作者群体、发文机构、关键词、突现词及时间线方面进行分析，以探讨国内稀土出口领域研究的演进趋势与发展热点。结果表明：近年来稀土出口领域文献整体呈增长趋势，但是文献发表具有明显的波动性和政策关联性。作者群体和发文机构主要集中在具有科研优势或资源优势地区的高校，研究团队之间合作程度较低。稀土产业、出口管制、出口配额、出口定价、出口政策等成为文献关键词和高频词。未来的稀土出口领域的研究方向主要集中在出口定价、可持续发展、本土稀土产业链发展和稀土产业资本出口四个方面。     

Estimating posterior inference quality of the relational infinite latent feature model for overlapping community detection

Overlapping community detection has become a very hot research topic in recent decades, and a plethora of methods have been proposed. But, a common challenge in many existing overlapping community detection approaches is that the number of communities K must be predefinedmanually. We propose a flexible nonparametric Bayesian generative model for count-value networks, which can allow K to increase as more and more data are encountered instead of to be fixed in advance. The Indian buffet process was used to model the community assignment matrix Z, and an uncollapsed Gibbs sampler has been derived.However, as the community assignment matrix Z is a structured multi-variable parameter, how to summarize the posterior inference results and estimate the inference quality about Z, is still a considerable challenge in the literature. In this paper, a graph convolutional neural network based graph classifier was utilized to help to summarize the results and to estimate the inference quality about Z. We conduct extensive experiments on synthetic data and real data, and find that empirically, the traditional posterior summarization strategy is reliable.     

基于双向位图的CSR大规模图存储优化

大数据时代,Graph500是评测超级计算机处理数据密集型应用能力的重要工具,E级验证系统的图遍历处理能力主要受限于内存空间和访存带宽,尤其是内存空间利用率直接决定了图的测试规模和测试性能.针对天河E级验证系统小内存特征,提出了基于双向位图的大规模图数据压缩存储方法(bidirectional-bitmap based CSR,Bi-CSR),Bi-CSR在CSR矩阵压缩的基础上引入行方向位图和列方向位图协同完成稀疏矩阵压缩存储,行方向位图主要负责行方向位图的压缩存储与索引,列方向位图除了进一步压缩图存储空间,还负责为顶点遍历向量并行优化提供加速空间.Bi-CSR大幅度减少了稀疏矩阵存储空间.面向天河E级验证系统,当图输入规模为237时,Graph500的图存储空间节约效率接近70%,全系统稳定测试性能为2.131E+12TEPS,性能最大加速比超过100倍.     

Dynamic modelling of PEM fuel cell system for simulation and sizing of marine power systems

This article presents a model of a proton exchange membrane fuel cell (PEMFC) system for marine power systems. PEMFC in marine hybrid power sources can have various power ranges and capacities in contrast with vehicle applications. Investigating PEMFCs behaviour and performance for various conditions and configurations is demanded for proper sizing and feasibility studies. Hence, modelling and simulation facilitate understanding the performance of the PEMFC behaviour with various sizes and configurations in power systems. The developed model in this work has a system level fidelity with real time capabilities, which can be utilized for simulator approaches besides quasi-static studies with a power-efficiency curve. Moreover, the model can be used for scaling the PEMFC power range by considering transient responses and corresponding efficiencies. The Bond graph approach as a multi-disciplinary energy based modelling strategy is employed for the PEMFC as a multi domains system. In the end, various PEMFC cell numbers and compressor sizes have been compared with power-efficiency curves and transient responses in a benchmark.     

基于节点1-邻居图相似性的社会网络匿名技术

利用传统的k匿名技术在社会网络中进行隐私保护时会存在聚类准则单一、图中数据信息利用不足等问题. 针对该问题, 提出了一种利用Kullback-Leibler (KL)散度衡量节点1-邻居图相似性的匿名技术(anonymization techniques for measuring the similarity of node 1-neighbor graph based on Kullback-Leibler divergence, SNKL). 根据节点1-邻居图分布的相似性对原始图节点集进行划分, 按照划分好的类进行图修改, 使修改后的图满足k匿名, 完成图的匿名发布. 实验结果表明, SNKL方法与HIGA方法相比在聚类系数上的改变量平均降低了17.3%, 同时生成的匿名图与原始图重要性节点重合度保持在95%以上. 所提方法在有效保证隐私的基础上, 可以显著的降低对原始图结构信息的改变.