Fuzzy adaptive networks in machining process modeling: surface roughness prediction for turning operations

Due to the complexity of the machine tool structure and the cutting process, the dynamics of machining processes are still not completely understood. This is especially true due to the demand of high-speed machining to increase productivity. In order to model and control these complex processes, new approaches, which can represent complex phenomenon combined with learning ability, are needed. The combined neural–fuzzy approach appears to be ideally suited for this purpose. In this paper, the recently developed fuzzy adaptive network (FAN) is used to model surface roughness in turning operations. The FAN network has both the learning ability of neural network and linguistic representation of complex, not well-understood, vague phenomenon. Furthermore, it can continuously improve the initially obtained rough model based on the daily operating data. To illustrate this approach, a model representing the influences of machining parameters on surface roughness is established and then the model is verified by the use of the results of pilot experiments. Finally, a comparison with the results based on statistical regression is provided.     

Recover Fault Services via Complex Service-to-Node Mappings in Wireless Sensor Networks

With the motivation of seamlessly extending wireless sensor networks to the external environment, service-oriented architecture comes up as a promising solution. However, as sensor nodes are failure prone, this consequently renders the whole wireless sensor network to seriously faulty. When a particular node is faulty, the service on it should be migrated into those substitute sensor nodes that are in a normal status. Currently, two kinds of approaches exist to identify the substitute sensor nodes: the most common approach is to prepare redundancy nodes, though the involved tasks such as maintaining redundancy nodes, i.e., relocating the new node, lead to an extra burden on the wireless sensor networks. More recently, other approaches without using redundancy nodes are emerging, and they merely select the substitute nodes in a sensor node’s perspective i.e., migrating the service of faulty node to it’s nearest sensor node, though usually neglecting the requirements of the application level. Even a few work consider the need of the application level, they perform at packets granularity and don’t fit well at service granularity. In this paper, we aim to remove these limitations in the wireless sensor network with the service-oriented architecture. Instead of deploying redundancy nodes, the proposed mechanism replaces the faulty sensor node with consideration of the similarity on the application level, as well as on the sensor level. On the application level, we apply the Bloom Filter for its high efficiency and low space costs. While on the sensor level, we design an objective solution via the coefficient of a variation as an evaluation for choosing the substitute on the sensor level.     

Optimizing content placement in a peer-assisted VoD architecture

Recently, a new peer-assisted architecture to build content delivery systems has been presented. This architecture is based on the use of the storage capacity of end-users’ set-top boxes (STBs), connected in a peer-to-peer (P2P) manner in order to help the content servers in the delivery process. In these systems, the contents are usually split into a set of smaller pieces, called sub-streams, which are randomly injected at the STBs. The present paper is focused on Video on Demand (VoD) streaming and it is assumed that the STB-based content delivery system is deployed over the global Internet, where the clients are distributed over different ISP networks. In this scenario, three different strategies are studied for increasing the percentage of data uploaded by peers, in order to offload the content servers as much as possible. First of all, a new mechanism is presented which determines which sub-stream has to be placed at which STB by a Non-Linear Programming (NLP) formulation. A different strategy for reducing the content server load is to take advantage of the available bandwidth in the different ISP networks. In this sense, two new mechanisms for forwarding the VoD requests to different ISP networks are presented. Finally, the present paper also shows that in some situations the available uplink bandwidth is associated with STBs that do not have the required sub-streams. Regarding this concern, a new mechanism has been designed that dynamically re-allocates some streams, which are being transmitted from specific STBs, to different STBs, in order to find the necessary resources to start new streaming sessions.     

A kernel-based framework for image collection exploration

While search engines have been a successful tool to search text information, image search systems still face challenges. The keyword-based query paradigm used to search in image collection systems, which has been successful in text retrieval, may not be useful in scenarios where the user does not have the precise way to express a visual query. Image collection exploration is a new paradigm where users interact with the image collection to discover useful and relevant pictures. This paper proposes a framework for the construction of an image collection exploration system based on kernel methods, which offers a mathematically strong basis to address each stage of an image collection exploration system: image representation, summarization, visualization and interaction. In particular, our approach emphasizes a semantic representation of images using kernel functions, which can be seamlessly harnessed across all system components. Experiments were conducted with real users to verify the effectiveness and efficiency of the proposed strategy.     

Extension of the gap statistics index to fuzzy clustering

The well-known gap statistic index proposed by Tibshirani et al. has successfully applied in many clustering evaluations. However, the gap statistic index cannot evaluate the clustering partitions from any fuzzy clustering algorithm. This is because fuzzy clustering cannot provide the within-cluster similarity measure that is used in the gas statistic index. Thus, the applicable range of the gap statistic index is very limited. In this paper, we present a new method that extends the gap statistic index to fuzzy clustering by using fuzzy membership notations. Our proposed method can extend the applicability of the gap statistic index, and outperform other existing fuzzy indices in several aspects. Experiments on eight sets of synthetic and real datasets are used to verify the applicability and efficiency of the proposed method.     

淮北平原主要农作物涝渍灾害 损失评估研究

针对淮北平原除涝减灾综合治理与规划中缺乏主要农作物受涝损失调查与评估基础资料的实 际问题,于2010年9月初区域降雨成灾之际,对受涝区进行主要农作物受涝经济损失调查。依据实 地调研成果,通过综合统计分析推求了不同耕地类型不同暴雨强度下的受涝损失率,在此基础上实现 了对淮北平原受涝经济损失的合理评估。     

高压切割喷嘴冲击磨损的数值分析

以复用矿井含煤颗粒的水对高压切割喷嘴的磨损物理问题为研究对象,采用计算流体力学理论进行数值计算,分析讨论了质量浓度为10、15、20、25、30、40 mg/L条件下速度、剪应力、磨损的分布以及变化关系。计算、分析结果表明:磨损主要发生在出口部位和锥体的后半部份,入口部份和锥体前半部份磨损较小;入口部位、锥体部位磨损量、剪应力随质量浓度增加变化较小;出口部位磨损量在质量浓度为10～20 mg/L减小较快,超过20 mg/L后变化不大;出口部位流体速度、磨损量、剪应力与质量浓度间存在对应关系。煤粒入口速度与混合物速度相同、锥体部位煤粒流体速度低于锥体部位混合物速度(平均值)约79.4%;煤粒出口部位速度随质量浓度的增大而呈现先增加后减小的趋势,速度最大值发生在浓度20 mg/L。     

浅析电子商务中的安全问题

随着现今社会互联网、个人终端技术的飞越发展,电子商务越来越多的出现在人们的生活与工作中,这种全新的商务模式具有便捷、高效率、低成本的特点.同时,这种全新的商务模式对管理水平、信息传递技术都提出了更高的要求,其中安全的重要性尤为突出.     

浅谈我国网络数据库的发展及对策

从网络数据库的概念、特点、发展趋势等方面论述了我国网络数据库的发展情况,针对我国网络数据库存在的问题提出了发展我国网络数据库的对策.     

一种完整的汉字识别系统设计

数字图像处理是计算机视觉技术的在交通管理领域的一个重要课题.它是指将图像信号转换成数字信号并利用计算机对其进行处理的过程.字符及汉字识别技术的成功运用,节省了大量的人力,而不影响正常的车辆行驶,并且可以快速的记录车辆的违章情况,它是交通管理自动化中的一项有效手段.本文将介绍一种完整的汉字识别系统设计,实现对36号宋体汉字的辨识.