Evaluating Visual Properties via Robust HodgeRank

International Journal of Computer Vision - Nowadays, how to effectively evaluate visual properties has become a popular topic for fine-grained visual comprehension. In this paper we study the...     

LabVIEW机械故障诊断系统的Web实现

本文针对机械设备远程故障诊断的振动数据分析问题,设计了一种在Web浏览器中进行机械设备振动数据实时显示和频谱分析的方法。首先,LabVIEW程序通过以太网从工业现场采集实时振动数据并以网络共享变量发布;然后,LabVIEW Web Service服务程序根据用户请求获取实时振动波形数据或对数据进行频谱分析,将数据以XML方式返回;最后,客户端的浏览器中分别采用Flex和Ajax对XML进行解析并显示实时波形和特征参数。该方法快速、稳定、可靠,很好地解决了远程故障诊断的问题。     

Enhancing collaborative filtering by user interest expansion via personalized ranking

Recommender systems suggest a few items from many possible choices to the users by understanding their past behaviors. In these systems, the user behaviors are influenced by the hidden interests of the users. Learning to leverage the information about user interests is often critical for making better recommendations. However, existing collaborative-filtering-based recommender systems are usually focused on exploiting the information about the user's interaction with the systems; the information about latent user interests is largely underexplored. To that end, inspired by the topic models, in this paper, we propose a novel collaborative-filtering-based recommender system by user interest expansion via personalized ranking, named iExpand. The goal is to build an item-oriented model-based collaborative-filtering framework. The iExpand method introduces a three-layer, user-interests-item, representation scheme, which leads to more accurate ranking recommendation results with less computation cost and helps the understanding of the interactions among users, items, and user interests. Moreover, iExpand strategically deals with many issues that exist in traditional collaborative-filtering approaches, such as the overspecialization problem and the cold-start problem. Finally, we evaluate iExpand on three benchmark data sets, and experimental results show that iExpand can lead to better ranking performance than state-of-the-art methods with a significant margin.     

A low distortion image enhancement scheme based on multi-resolutions analysis in next generation network

With the advent of Next Generation Network (NGN), services that are currently provided by multiple specific network-centric architectures. NGN provides AAA (Anytime, Anywhere and Always on) access to users from different service providers with consistent and ubiquitous provision of services as necessary. This special issue of NGN includes pervasive, grid, and peer-to-peer computing to provide computing and communication services at anytime and anywhere. In fact, the application of NGN includes digital image processing, multimedia systems/services, and so on. Here we focus on the digital image processing technology in NGN environments. Low-contrast structure and heavy noise in NGN environments can be found in many kinds of digital images, which makes the images vague and uncertainly, especially in x-ray images. As result, some useful tiny characteristic are weakened—which are difficult to distinguish even by naked eyes. Based on the combination of no-linear grad-contrast operator and multi-resolution wavelet analysis, a kind of image enhancement processing algorithm for useful tiny characters is presented. The algorithm can enhance the tiny characters while confine amplifying noise. The analysis of the results shows that local regions of the image are enhanced by using the concept of the grad contrast to make image clearer adaptively. Experiments were conducted on real pictures, and the results show that the algorithm is flexible and convenient.     

Mining blackhole and volcano patterns in directed graphs: a general approach

Given a directed graph, the problem of blackhole mining is to identify groups of nodes, called blackhole patterns, in a way such that the average in-weight of this group is significantly larger than the average out-weight of the same group. The problem of finding volcano patterns is a dual problem of mining blackhole patterns. Therefore, we focus on discovering the blackhole patterns. Indeed, in this article, we develop a generalized blackhole mining framework. Specifically, we first design two pruning schemes for reducing the computational cost by reducing both the number of candidate patterns and the average computation cost for each candidate pattern. The first pruning scheme is to exploit the concept of combination dominance to reduce the exponential growth search space. Based on this pruning approach, we develop the gBlackhole algorithm. Instead, the second pruning scheme is an approximate approach, named approxBlackhole, which can strike a balance between the efficiency and the completeness of blackhole mining. Finally, experimental results on real-world data show that the performance of approxBlackhole can be several orders of magnitude faster than gBlackhole, and both of them have huge computational advantages over the brute-force approach. Also, we show that the blackhole mining algorithm can be used to capture some suspicious financial fraud patterns.     

电流密度对声电沉积生物活性透钙磷石涂层结构和形貌的影响

通过声电沉积工艺在碳／碳复合材料表面制备了生物活性透钙磷石涂层，采用SEM、FFIR、XRD研究了超声场中电流密度对涂层组成结构和形貌的影响。发现在一定工艺条件下，随电流密度增加，涂层的平均晶粒尺寸减小，致密度增加；当电流密度小于l0mA／cm^2时涂层形貌为片状，l0mA／cm^2-26mA／cm^2时为粒状，32mA／cm^2时为花菜心状。且涂层中透钙磷石晶体的择优取向也发生变化，择优晶面依次为(021)、(111)、(220)。同时还讨论了涂层微观结构变化机理。     

Enhanced Photoelectrochemical Performance of Hematite Photoanode by Decorating NiCoP Nanoparticles Through a Facile Spin Coating Method

Catalysis Letters - Hematite (α-Fe2O3) is a potential photoanode material for photoelectrochemical (PEC) water splitting, but its short hole diffusion length and low water oxidation kinetics...     

旅游管理专业研究生《地理信息系统》课程教学改革探讨

在智慧旅游时代,掌握GIS基础理论知识和技术技能对于旅游专业学生来说非常重要.本文从旅游管理研究生GIS课程目标发出,结合实践教学经验,分析了该课程在教学过程中存在的一些问题,从教学内容、教学方法和考核方式三个方面提出切实可行的GIS课程教学改革建议,以提升课程教学质量和研究生的科研素质.     

高温水环境对复合材料绝缘横担性能的影响研究

为更好地指导配网用复合材料绝缘横担应用,依据GB/T 20142—2006要求对密封处理及未密封处理的两类复合材料绝缘横担进行了42 h水煮(0.1％NaCl)试验,研究高温水环境对两种处理方式绝缘横担性能的影响.对水煮前后吸水率、额定弯曲负荷、拉伸强度、弯曲强度、干工频电压、干雷电冲击电压及电气强度等性能进行对比测试,同时采用SEM进行断口微观形貌分析.结果表明:在高温水环境下,密封处理绝缘横担性能优于未密封处理绝缘横担,但两种处理方式的绝缘横担额定弯曲负荷均大于6.5 kN,雷电冲击耐受电压均大于350 kV,拉伸强度和弯曲强度分别大于680 MPa和1000 MPa,表现出良好的力学及电气性能.