一种基于CFSFDP改进算法的重要地点识别方法研究

以LBSN用户位置数据为对象,针对数据偶发更新且数量稀疏的特点,围绕聚类算法的改进,研究了一种重要地点识别方法。首先,采用速度剪枝对数据进行预处理,剔除异常干扰点;其次,选用基于密度峰值的CFSFDP算法进行聚类。针对该算法无法自行选择簇中心点的问题,提出了CFSFDP改进算法。该算法采用簇中心点自动选择策略,将簇中心权值的变化趋势作为自动划分簇中心的依据,有效避免了通过决策图判决簇中心的方法所带来的误差;最后,对各簇中心点坐标进行逆向地理编码,完成重要地点识别。实验以Foursquare用户Check-in数据为例,结果表明CFSFDP改进算法相比于DBSCAN具有更高的准确率和较低的计算量,进一步证明了该重要地点识别方法的可行性和有效性。     

基于非参数核密度估计的密度峰值聚类算法*

针对密度峰值聚类算法CFSFDP(Clustering by fast search and find of density peaks)计算密度时人为判断截断距离和人工截取簇类中心的缺陷,提出了一种基于非参数核密度估计的密度峰值的聚类算法。首先,应用非参数核密度估计方法计算数据点的局部密度;其次,根据排序图采用簇中心点自动选择策略确定潜在簇类中心点,将其余数据点归并到相应的簇类中心;最后,依据簇类间的合并准则,对邻近相似子簇进行合并,并根据边界密度识别噪声点,得到聚类结果。在人工测试数据集和UCI真实数据集上的实验表明,新算法较之原CFSFDP算法,不仅有效避免了人为判断截断距离和截取簇类中心的主观因素,而且可以取得更高的准确度。     

基于密度峰值与密度聚类的集成算法

针对快速搜索和发现密度峰值聚类（CFSFDP）算法需人工在决策图上选择聚类中心的问题，提出一种基于密度峰值和密度聚类的集成算法。首先，借鉴CFSFDP思想，将局部密度最大的数据作为第一个中心；接着，从该中心点出发采用一种利用Warshall算法求解密度相连改进的基于密度的噪声应用空间聚类（DBSCAN）算法进行聚类，得到第一个簇；最后，在尚未被划分的数据中找出最大局部密度的数据，将它作为下一个簇的中心后再次采用上述算法进行聚类，直到所有数据被聚类或有部分数据被视为噪声。所提算法既解决了CFSFDP选择中心需人工干预的问题，又优化了DBSCAN算法，即每次迭代都是从当前最好的点（局部密度最大的点）出发寻找簇。通过可视化数据集和非可视化数据集与经典算法（CFSFDP、DBSCAN、模糊C均值（FCM）算法和K均值（K-means）算法）的对比实验结果表明，所提算法聚类效果更好，准确率更高，优于对比算法。     

结合遗传k均值改进的密度峰值聚类算法

针对密度峰值聚类(CFSFDP)算法处理多密度峰值数据集时,人工选择聚类中心易造成簇的误划分问题,提出一种结合遗传k均值改进的密度峰值聚类算法。在CFSFDP求得的可能簇中心中,利用基于可变染色体长度编码的遗传k均值的全局搜索能力自动搜索出最优聚类中心,同时自适应确定遗传k均值的交叉概率,避免早熟问题的出现。在UCI数据集上的实验结果表明,改进算法具有较好的聚类质量和较少的迭代次数,验证了所提算法的可行性和有效性。     

一种基于K近邻的比较密度峰值聚类算法

快速搜索与发现密度峰值聚类算法（Fast Search and Discovery Density Peak Clustering Algorithm，CFSFDP）的聚类效果十分依赖截断距离[dc]的主观选取，而最佳[dc]值的确定并不容易，并且当处理分布复杂、密度变化大的数据集时，算法生成的决策图中类簇中心点与非类簇中心点的区分不够明显，使类簇中心的选取变得困难。针对这些问题，对其算法进行了优化，并提出了基于K近邻的比较密度峰值聚类算法（Comparative Density Peak Clustering algorithm Based on K-Nearest Neighbors，CDPC-KNN）。算法结合K近邻概念重新定义了截断距离和局部密度的度量方法，对任意数据集能自适应地生成截断距离，并使局部密度的计算结果更符合数据的真实分布。同时在决策图中引入距离比较量代替原距离参数，使类簇中心在决策图上更加明显。通过实验验证，CDPC-KNN算法的聚类效果整体上优于CFSFDP算法与DBSCAN算法，分离度实验表明新算法使类簇中心与非类簇中心点的区分度得到有效提高。     

密度峰值快速聚类算法优化研究

密度峰值快速搜索聚类CFSFDP算法选择聚类中心时需要通过人工在决策图中选择,且最后进行簇核心与簇光晕划分时会将簇的一些边缘部分划入簇光晕中,导致划分结果不够合理。针对以上问题,提出一种聚类中心自动选择及簇核心与簇光晕分割优化的聚类算法。利用异常检测的思想,寻找簇中心权值的异常点,将异常点作为各簇的聚类中心;引入簇内局部密度,实现对簇核心与簇光晕更合理的分割。通过实验对比,本文提出的算法自动化效果优于CFSFDP算法且得到的聚类结果更为精确。     

基于多密度峰值的CFSFDP算法改进

CFSFDP(Clustering by Fast Search and Find of Density Peaks)算法在单个簇中存在多个密度峰值时,使用决策图难以确定聚类中心数量,导致聚类效果不佳的情况。对此提出将所有密度大于当前位置的数据点以及与当前位置的最小距离各归为一个集合,并对高斯核求得的局部密度排序。当存在多个密度峰值时,只选择第一个点作为聚类中心,同时利用归一化的γ值分布图确定聚类中心数。人工数据集和UCI数据集的数值模拟实验表明,改进CFSFDP算法在调整兰德系数、同质性、完整性、V-measure和标准互信息评分等各指标值均优于CFSFDP算法、DBSCAN算法和k-means算法。该算法弥补了CFSFDP算法对多密度峰值不能很好聚类的缺陷,适用于对较低维度的任意形数据集的聚类。     

一种基于相对密度和决策图的聚类算法

聚类是数据挖掘领域的一个重要研究方向,针对复杂数据集中存在的簇间密度不均匀、聚类形态多样、聚类中心的识别等问题,引入样本点k近邻信息计算样本点的相对密度,借鉴快速搜索和发现密度峰值聚类(CFSFDP)算法的簇中心点识别方法,提出一种基于相对密度和决策图的聚类算法,实现对任意分布形态数据集聚类中心快速、准确地识别和有效聚类.在7类典型测试数据集上的实验结果表明,所提出的聚类算法具有较好的适用性,与经典的DBSCAN算法和CFSFDP等算法相比,在没有显著提高时间复杂度的基础上,聚类效果更好,对不同类型数据集的适应性也更广.     

基于CFSFDP聚类算法的WSNs高能效分簇路由算法

为进一步降低无线传感器网络在周期性数据收集过程中的能量消耗,提出一种基于CFSFDP聚类算法的能量高效分簇路由算法。算法首先采用CFSFDP聚类算法对网络分簇进行集中控制,使网络各簇得到均衡分布的同时能够降低网络中的控制包开销;其次在簇头、副簇头及中继节点的选举公式中增加动态权重因子保证数据传输的可靠性;最后在选择下一跳中继节点时加入簇内能耗因子使各簇能耗能够更加均衡地下降。仿真结果显示,该算法网络生存周期较LEACH、KBECRA、CHTD-M算法均有显著提高,表明改进算法在降低和均衡网络能耗上具有优越性。     

罚处共享最近邻密度峰聚类算法

为解决传统密度峰聚类算法容易忽略低密度簇中心以及难以自动选择聚类中心的问题,提出罚处共享最近邻密度峰聚类算法.设计罚处系数,减少高密度簇中非中心点的共享最近邻局部密度值,降低低密度簇中心点被忽视的机率;采用迭代阈值法实现簇中心点的自动选择.在人工数据集、UCI真实数据集以及图像数据集上进行仿真实验,其结果表明,该算法能找到数据集的簇中心和簇数目,聚类精度优于相比较的其它算法,该算法是可行的、有效的.     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.