Language independent search in MediaEval's Spoken Web Search task

In this paper, we describe several approaches to language-independent spoken term detection and compare their performance on a common task, namely “Spoken Web Search”. The goal of this part of the MediaEval initiative is to perform low-resource language-independent audio search using audio as input. The data was taken from “spoken web” material collected over mobile phone connections by IBM India as well as from the LWAZI corpus of African languages. As part of the 2011 and 2012 MediaEval benchmark campaigns, a number of diverse systems were implemented by independent teams, and submitted to the “Spoken Web Search” task. This paper presents the 2011 and 2012 results, and compares the relative merits and weaknesses of approaches developed by participants, providing analysis and directions for future research, in order to improve voice access to spoken information in low resource settings.     

Cloud based intelligent system for delivering health care as a service

The promising potential of cloud computing and its convergence with technologies such as mobile computing, wireless networks, sensor technologies allows for creation and delivery of newer type of cloud services. In this paper, we advocate the use of cloud computing for the creation and management of cloud based health care services. As a representative case study, we design a Cloud Based Intelligent Health Care Service (CBIHCS) that performs real time monitoring of user health data for diagnosis of chronic illness such as diabetes. Advance body sensor components are utilized to gather user specific health data and store in cloud based storage repositories for subsequent analysis and classification. In addition, infrastructure level mechanisms are proposed to provide dynamic resource elasticity for CBIHCS. Experimental results demonstrate that classification accuracy of 92.59% is achieved with our prototype system and the predicted patterns of CPU usage offer better opportunities for adaptive resource elasticity.     

Fall detection for multiple pedestrians using depth image processing technique

A fall detection method based on depth image analysis is proposed in this paper. As different from the conventional methods, if the pedestrians are partially overlapped or partially occluded, the proposed method is still able to detect fall events and has the following advantages: (1) single or multiple pedestrian detection; (2) recognition of human and non-human objects; (3) compensation for illumination, which is applicable in scenarios using indoor light sources of different colors; (4) using the central line of a human silhouette to obtain the pedestrian tilt angle; and (5) avoiding misrecognition of a squat or stoop as a fall. According to the experimental results, the precision of the proposed fall detection method is 94.31% and the recall is 85.57%. The proposed method is verified to be robust and specifically suitable for applying in family homes, corridors and other public places.     

Detecting symmetries of rational plane and space curves

This paper addresses the problem of determining the symmetries of a plane or space curve defined by a rational parametrization. We provide effective methods to compute the involution and rotation symmetries for the planar case. As for space curves, our method finds the involutions in all cases, and all the rotation symmetries in the particular case of Pythagorean-hodograph curves. Our algorithms solve these problems without converting to implicit form. Instead, we make use of a relationship between two proper parametrizations of the same curve, which leads to algorithms that involve only univariate polynomials. These algorithms have been implemented and tested in the Sage system.     

Detecting criminal organizations in mobile phone networks

The study of criminal networks using traces from heterogeneous communication media is acquiring increasing importance in nowadays society. The usage of communication media such as mobile phones and online social networks leaves digital traces in the form of metadata that can be used for this type of analysis. The goal of this work is twofold: first we provide a theoretical framework for the problem of detecting and characterizing criminal organizations in networks reconstructed from phone call records. Then, we introduce an expert system to support law enforcement agencies in the task of unveiling the underlying structure of criminal networks hidden in communication data. This platform allows for statistical network analysis, community detection and visual exploration of mobile phone network data. It enables forensic investigators to deeply understand hierarchies within criminal organizations, discovering members who play central role and provide connection among sub-groups. Our work concludes illustrating the adoption of our computational framework for a real-word criminal investigation.     

基于多决策树的RFID入侵检测模型

为了能够有效对RFID系统的已知攻击和未知攻击进行检测和预警,在分析大量RFID安全协议的基础上,提出了利用构建多决策树的方法对RFID系统的入侵行为进行检测。通过分析,得到所构造出的多决策树能够发现针对RFID系统的攻击之间的关系,并且具有可扩展性和高效性,使之能够适用于各种实际的RFID系统的应用。     

基于边缘信息车流量检测方法的研究

针对边缘检测中阈值很难确定导致不能准确提取背景边缘信息的问题,提出一种改进的基于边缘信息车流量检测方法。该方法预先对路况边缘图像作削顶处理获取一个恰当的阈值,从而可以准确地提取背景边缘信息;且在车辆计数过程中,结合固定窗法和浮动窗法二者的优点,设计一种新的浮动窗法进行车辆计数。实验结果表明,该方法在实时性、检测速度、正确率等方面得到很大的改进,能够在不同环境下进行正确有效地车流量检测。     

云数据中心心跳检测与故障评估

为提高云数据中心的抗毁能力,针对软硬件日趋复杂化带来的诸多故障问题,以传统的服务器心跳检测机制为基础,结合云计算的特点,提出一种保证云数据中心有效运行的心跳检测与故障评估方案。在实验室搭建仿真平台进行实验,实验结果表明,该方案能够及时检测到节点故障,依据预先制定的故障等级评估标准,采用模糊综合法进行评估,为云数据中心的管理与运作提供参考依据与保障。     

基于CPLD的光电编码器角位移拟合测速法

针对常用的M法和T法无法满足增量式光电编码器整个测速范围内误差要求的问题,提出了对码盘信号进行角位移拟合求采样时刻即时速度的新方法,在匀加速条件下对这3种方法进行了仿真实验,比较了测速误差。实验结果表明,角位移拟合法在整个速度范围内都能获得很高的测速精度和误差一致性。最后用CPLD对该方法加以实现,给出了Verilog硬件描述语言的设计程序和3种方法的实验结果比较。基于CPLD的实现方法电路简单,运行稳定可靠,处理速度快,为角位移拟合法提供了一种非常好的实现方法。