基于FLUENT计算的LNG真空管道泄漏安全分析

LNG （液化天然气Liquefied Natural Gas）具有低温特性,在LNG站内常用真空管道以减少LNG的气化损耗。真空管道的真空度是保证管道绝热的重要因素,一旦LNG管道发生泄漏、真空丧失,管道的绝热性能降低,LNG受热大量气化将造成火灾、爆炸等安全隐患。传统的判断往往利用经验观察或通过现场数据及公式计算对LNG管道泄漏做出判断,具有局限性。本文利用FLUENT数值模拟软件,将LNG管道转化为数学模型,对LNG管道泄漏的温度场进行模拟,分析出真空丧失后管道热量分布,研究管道泄漏后热量变化规律,识别出管道重点危险部位,能科学发现问题,对事故预防、控制具有重要的现实意义,同时为LNG站内的科学管理提供理论依据。     

基于小样本学习的图像分类技术综述

图像分类的应用场景非常广泛, 很多场景下难以收集到足够多的数据来训练模型, 利用小样本学习进行图像分类可解决训练数据量小的问题. 本文对近年来的小样本图像分类算法进行了详细综述, 根据不同的建模方式, 将现有算法分为卷积神经网络模型和图神经网络模型两大类, 其中基于卷积神经网络模型的算法包括四种学习范式: 迁移学习、元学习、对偶学习和贝叶斯学习; 基于图神经网络模型的算法原本适用于非欧几里得结构数据, 但有部分学者将其应用于解决小样本下欧几里得数据的图像分类任务, 有关的研究成果目前相对较少. 此外, 本文汇总了现有文献中出现的数据集并通过实验结果对现有算法的性能进行了比较. 最后, 讨论了小样本图像分类技术的难点及未来研究趋势.     

基于差分的图像感知哈希算法

现有图像感知算法侧重于减少相似图像感知哈希值间的差异性,较少关注增大不同图像感知哈希值间的差异性问题.针对这一局限性,提出并实现循环贯序差分和拉普拉斯算子两种基于差分的图像感知哈希算法,并分别在小规模相似图像集合和大规模不同图像集合上进行测试.与现有图像感知哈希算法相比,所提算法体现了图像像素点间的局部关联性,增加了不...     

基于节点运动的机会网络路由算法

机会网络利用节点移动带来的接触机会传输数据,数据在节点运动过程中捎带转发,保证了节点独立性,但会给数据传输带来影响.以节点的运动特性为切入点设计了基于运动的机会网络路由算法.综合考虑数据传输、数据内容以及应用需求等因素,设计了数据转发优先级评价模型,结合节点活动区间划分方案制定数据传输规则;设计了差异化副本传输策略,在...     

肉苁蓉低聚糖提取工艺的研究

以内蒙古阿拉善盟出产的肉苁蓉为实验材料,对肉苁蓉低聚糖的提取工艺进行了研究,通过L9(34)正交实验,确定最佳工艺参数为浸提液pH为11,时间为90min,温度60℃,料液比为1∶25,浸提次数为2次。      

基于LPCMCC的音频数据检索方法

LPC美尔倒频谱系数（LPCMCC）根据人耳听觉特性将LPC倒谱系数（LPCC）用非线性美尔尺度进行变换,从而更接近人耳的听觉系统。基于此提出一种采用LPCMCC为特征参数,通过动态时间规整算法进行音频数据的分类与检索方法。实验结果表明,该方法的检索精度高于LPCC,检索效率高于美尔倒谱系数（MFCC）。     

An improved selective attention model considering orientation preferences

An improved selective attention model is proposed in this paper, which is designed as a network of spiking neurons of Hodgkin--Huxley type with star-like connections between the central units and peripheral neurons. In this model, peripheral neurons represent the neurons located in the primary visual cortex. Since orientation preference is an important property of neurons in primary visual cortex, it should be considered except for external stimuli intensity. Simulation results show that the improved model can sequentially select objects with different orientation preferences and has a reliable shift of attention from one object to another, which are consistent with the experimental results that the neurons with different orientation preferences are laid out in pinwheel patterns.     

An effective hybrid learning system for telecommunication churn prediction

Customer churn has emerged as a critical issue for Customer Relationship Management and customer retention in the telecommunications industry, thus churn prediction is necessary and valuable to retain the customers and reduce the losses. Moreover, high predictive accuracy and good interpretability of the results are two key measures of a classification model. More studies have shown that single model-based classification methods may not be good enough to achieve a satisfactory result. To obtain more accurate predictive results, we present a novel hybrid model-based learning system, which integrates the supervised and unsupervised techniques for predicting customer behaviour. The system combines a modified k-means clustering algorithm and a classic rule inductive technique (FOIL).Three sets of experiments were carried out on telecom datasets. One set of the experiments is for verifying that the weighted k-means clustering can lead to a better data partitioning results; the second set of experiments is for evaluating the classification results, and comparing it to other well-known modelling techniques; the last set of experiment compares the proposed hybrid-model system with several other recently proposed hybrid classification approaches. We also performed a comparative study on a set of benchmarks obtained from the UCI repository. All the results show that the hybrid model-based learning system is very promising and outperform the existing models.     

The general theory of three-party quantum secret sharing protocols over phase-damping channels

The general theory of three-party QSS protocols with the noisy quantum channels is discussed. When the particles are transmitted through the noisy quantum channels, the initial pure three-qubit tripartite entangled states would be changed into mixed states. We analyze the security of QSS protocols with the different kinds of three-qubit tripartite entangled states under phase-damping channels and figure out, for different kinds of initial states, the successful probabilities that Alice’s secret can be recovered by legal agents are different. Comparing with one recent QSS protocol based on GHZ states, our scheme is secure, and has a little smaller key rate than that of the recent protocol.     

Expansible quantum secret sharing network

In the practical applications, member expansion is a usual demand during the development of a secret sharing network. However, there are few consideration and discussion on network expansibility in the existing quantum secret sharing schemes. We propose an expansible quantum secret sharing scheme with relatively simple and economical quantum resources and show how to split and reconstruct the quantum secret among an expansible user group in our scheme. Its trait, no requirement of any agent’s assistant during the process of member expansion, can help to prevent potential menaces of insider cheating. We also give a discussion on the security of this scheme from three aspects.