温州产业集群发展中的政府职能及效果分析

从政府参与产业集群的角度将温州产业集群划分为3个阶段,讨论了温州市政府在产业集群发展过程中的职能,并采用产业集群集聚地区的数据对温州市政府参与产业集群的效果进行了分析,为温州市政府促进产业集群的升级和发展提供了建议.     

Preparation and characterization of nano-hydroxy apatite/konjac glucomannan composite scaffolds

A novel nano-hydroxyapatite (HA)/konjac glucomannan composite scaffold with high porosity was developed by blending nano-HA particles with konjac glucomannan in alkaline solution. The scanning electron microscopy, porosity measurement, X-ray diffraction(XRD), and Fourier transformed infrared(FTIR) spectroscopy were used to analyze the physical and chemical properties of the composite scaffolds. The pure konjac glucomannan scaffolds and composite scaffolds were similar in their macroscopic morphology, however, the microscopic morphology on porewall surfaces was quite different. The diffraction patterns of XRD revealed the presence of konjac glucomannan and HA in the composite scaffolds. In addition, the results of FTIR also showed the existence of the functional group of HA. These results reveal that the newly developed nano-HA/konjac glucomannan composite scaffold may serve as a good three-dimensional substrate in bone tissue engineering.     

基于混沌粒子群和模糊聚类的图像分割算法*

模糊C-均值聚类算法(FCM)是一种结合模糊集合概念和无监督聚类的图像分割技术,适合灰度图像中存在着模糊和不确定的特点;但该算法受初始聚类中心和隶属度矩阵的影响,易陷入局部极小.利用混沌非线性动力学具有遍历性、随机性等特点,结合粒子群的寻优特性,提出了一种基于混沌粒子群模糊C-均值聚类(CPSO-FCM)的图像分割算法.实验证明,该方法不仅具有防止粒子因停顿而收敛到局部极值的能力,而且具有更快的收敛速度和更高的分割精度.     

量子竞争决策算法及其在旅行商问题中的应用*

提出一种新型优化算法——量子竞争决策算法,在竞争决策的基础上,将进化博弈论中博弈者不断学习和调整来提高竞争力的思想引入到优化中,使竞争者具有自进化能力,同时充分利用量子进化计算中量子比特、叠加态等理论,增加竞争群体的多样性,缩小群体规模。通过对典型的TSP实验计算和与其他算法比较,均取得了较好的效果,算法具有较强的全局优化能力。     

A multi-view attention-based deep learning system for online deviant content detection

With the exponential growth of user-generated content, policies and guidelines are not always enforced in social media, resulting in the prevalence of deviant content violating policies and guidelines. The adverse effects of deviant content are devastating and far-reaching. However, the detection of deviant content from sparse and imbalanced textual data is challenging, as a large number of stakeholders are involved with different stands and the subtle linguistic cues are highly dependent on complex context. To address this problem, we propose a multi-view attention-based deep learning system, which combines random subspace and binary particle swarm optimization (RS-BPSO) to distill content of interest (candidates) from imbalanced data, and applies the context and view attention mechanisms in convolutional neural network (dubbed as SSCNN) for the extraction of structural and semantic features. We evaluate the proposed approach on a large-scale dataset collected from Facebook, and find that RS-BPSO is able to detect whether the content is associated with marijuana with an accuracy of 87.55%, and SSCNN outperforms baselines with an accuracy of 94.50%.

     

基于深度卷积神经网络的心音分类算法

针对现有心音分类算法普适性差、依赖于对基本心音的精确分割、分类模型结构单一等问题,提出采用大量未经过精确分割的心音二维特征图训练深度卷积神经网络(CNN)的方法;首先采用滑动窗口方法和梅尔频率系数对心音信号进行预处理,得到大量未经过精确分割的心音特征图;然后利用深度CNN模型对心音特征图进行训练和测试;根据卷积层间连接方式的不同,设计了 3种深度CNN模型:基于单一连接的卷积神经网络、基于跳跃连接的卷积神经网络、基于密集连接的卷积神经网络;实验结果表明,基于密集连接的卷积神经网络比其他两种网络具备更大的潜力;与其他心音分类算法相比,该算法不依赖于对基本心音的精确分割,且在分类准确率、敏感性和特异性方面均有提升.     

The mass,fake news,and cognition security

The widespread fake news in social networks is posing threats to social stability, economic development, and political democracy, etc. Numerous studies have explored the effective detection approaches of online fake news, while few works study the intrinsic propagation and cognition mechanisms of fake news. Since the development of cognitive science paves a promising way for the prevention of fake news, we present a new research area called Cognition Security (CogSec), which studies the potential impacts of fake news on human cognition, ranging from misperception, untrusted knowledge acquisition, targeted opinion/attitude formation, to biased decision making, and investigates the effective ways for fake news debunking. CogSec is a multidisciplinary research field that leverages the knowledge from social science, psychology, cognition science, neuroscience, AI and computer science. We first propose related definitions to characterize CogSec and review the literature history. We further investigate the key research challenges and techniques of CogSec, including humancontent cognition mechanism, social influence and opinion diffusion, fake news detection, and malicious bot detection. Finally, we summarize the open issues and future research directions, such as the cognition mechanism of fake news, influence maximization of fact-checking information, early detection of fake news, fast refutation of fake news, and so on.     

不同温度条件下水工沥青混凝土抗压特性及防渗性能试验研究

为研究水工沥青混凝土在不同温度条件下的力学特性和经荷载作用后的防渗性能,在-30℃～30℃条件下对其进行了抗压试验研究,并对荷载和温度作用后的试件进行了渗透试验分析。试验结果表明:温度对水工沥青混凝土的应力-应变全曲线、抗压强度、弹性模量、峰值应变以及破坏模式等力学特性有显著影响。对比水工沥青混凝土在-30℃～30℃条件下应力-应变全曲线特点,可推断-10℃～0℃为其应力-应变特性变化的过渡温度区间。水工沥青混凝土的抗压强度和弹性模量随温度的升高而降低,峰值应变随温度的升高而增大。基于试验结果,本文提出的经验公式较好地反映了抗压强度、弹性模量以及峰值应变随温度变化的规律。在-30℃～0℃条件下,水工沥青混凝土的破坏模式主要为骨料开裂和沥青胶浆与骨料的黏结破坏;在10℃～30℃条件下,破坏模式主要为黏结破坏。此外,水工沥青混凝土经荷载作用后的防渗性能与温度环境有关。在10℃～30℃温度环境中,水工沥青混凝土承受7%的轴向压应变后,其渗透系数仍在10-7～10-6cm/s量级,防渗性能良好。     

预应力纤维布加固混凝土梁冻融特性试验

为了研究预应力碳纤维布对受冻融作用影响的混凝土梁的加固效果,从而进一步认识混凝土与碳纤维布共同工作的行为,研究了加固梁中碳纤维布和混凝土的各自力学性能以及碳纤维布加固混凝土梁的整体力学性能.结果表明,冻融后的试验梁开裂荷载和极限承载力有所下降;初始预应力水平越高,试验梁的开裂荷载和极限荷载下降速度越快;在冻融循环和预应力耦合作用下混凝土内部损伤严重,碳纤维布-混凝土界面的粘结力退化明显.     

霍尔推力器加速通道-空心阴极耦合区物理研究进展

重点介绍霍尔推力器耦合区物理过程的研究现状.霍尔推力器的耦合区连接阴极与通道内等离子体,控制通道入口电子参数,也通过耦合环境影响阴极自身的电子发射特性.由于耦合区处于推力器外部的负梯度弱磁场区,导致耦合区发生的物理过程十分复杂.分别从种子电子向通道内传导、羽流中和过程、等离子体桥电子的E×B漂移和耦合环境中的阴极放电等方面讨论了耦合区的参数分布和影响因素,总结了耦合区的特点,指出了目前研究的难点与不足,并对后续研究给出了建议.