In a previous paper, fast PCA implementation for face detection based on cross-correlation in the frequency domain between the input image and eigenvectors was presented. Here, this approach is developed to reduce the...
详细信息
In a previous paper, fast PCA implementation for face detection based on cross-correlation in the frequency domain between the input image and eigenvectors was presented. Here, this approach is developed to reduce the computation steps required by fast PCA. The principle of divide and conquer strategy is applied through image decomposition. Each image is divided into small in size sub-images and then each one is tested separately by using a single fast PCA processor. In contrast to using only fast PCA, the speed up ratio is increased with the size of the input image when using fast PCA and image decomposition. Simulation results demonstrate that our proposal is faster than the conventional and fast PCA. Moreover, experimental results for different images show good performance.
Media streaming in mobile environments is becoming more and more important with the proliferation of 3G technologies and the popularity of online media services such as news clips, live sports, and hot movies. To avoi...
详细信息
Group Decision Making (GDM) refers to the selection of an alternative from a set of feasible alternatives that better satisfies some criteria according to a group of individuals (experts). There exist several differen...
详细信息
Group Decision Making (GDM) refers to the selection of an alternative from a set of feasible alternatives that better satisfies some criteria according to a group of individuals (experts). There exist several different models to simulate GDM processes, but many of those models do not usually take into account some dynamical aspects of real decision processes. For example, those models normally do not allow the experts set to change during the process (adding or removing experts), the alternatives to change (incorporating or discarding alternatives) or even to change the criteria. In this work we present a new model which allows to undertake GDM situations in which a large number of individuals (for example an on-line community) has to choose among different alternatives. To be able to obtain a good solution of consensus, the group of experts will be firstly simplified into a smaller group (using a simple clustering technique and a kind of trust network) which can then discuss about best solution to be selected.
Collaborative localization and discrimination of acoustic sources is an important problem for monitoring urban environments. Acoustic source localization typically is performed using either signal-based approaches tha...
详细信息
ISBN:
(纸本)9780982443804
Collaborative localization and discrimination of acoustic sources is an important problem for monitoring urban environments. Acoustic source localization typically is performed using either signal-based approaches that rely on transmission of raw acoustic data and are not suitable for resource-constrained wireless sensor networks or feature-based methods that result in degraded accuracy, especially for multiple targets. In this paper, we present a feature-based localization and discrimination approach for multiple acoustic sources using wireless sensor networks that fuses beamform and power spectral density data from each sensor. Our approach utilizes a graphical model for estimating the position of the sources as well as their fundamental and dominant harmonic frequencies. We present simulation and experimental results that show improvement in the localization accuracy and target discrimination. Our experimental results are obtained using motes equipped with microphone arrays and an onboard FPGA for computing the beamform and the power spectral density.
Metaschedulers can distribute parts of a bag-of-tasks (BoT) application among various resource providers in order to speed up its execution. When providers cannot disclose private information such as their load and co...
详细信息
Metaschedulers can distribute parts of a bag-of-tasks (BoT) application among various resource providers in order to speed up its execution. When providers cannot disclose private information such as their load and computing power, which are usually heterogeneous, the metascheduler needs to make blind scheduling decisions. We propose three policies for composing resource offers to schedule deadline-constrained BoT applications. Offers act as a mechanism in which resource providers expose their interest in executing an entire BoT or only part of it without revealing their load and total computing power. We also evaluate the amount of information resource providers need to expose to the metascheduler and its impact on the scheduling. Our main findings are: (i) offer-based scheduling produces less delay for jobs that cannot meet deadlines in comparison to scheduling based on load availability (i.e. free time slots); thus it is possible to keep providers' load private when scheduling multi-site BoTs; and (ii) if providers publish their total computing power they can have more local jobs meeting deadlines.
Radio Frequency IDentification (RFID) is a technology of automatic object identification. Retailers and manufacturers have created compelling business cases for deploying RFID in their supply chains. Yet, the uniquely...
详细信息
ISBN:
(纸本)9781605581668
Radio Frequency IDentification (RFID) is a technology of automatic object identification. Retailers and manufacturers have created compelling business cases for deploying RFID in their supply chains. Yet, the uniquely identifiable objects pose a privacy threat to individuals. In this paper, we study the privacy threats caused by publishing RFID data. Even if the explicit identifying information, such as name and social security number, has been removed from the published RFID data, an adversary may identify a target victim's record or infer her sensitive value by matching a priori known visited locations and timestamps. RFID data by default is high-dimensional and sparse, so applying traditional K-anonymity to RFID data suffers from the curse of high dimensionality, and would result in poor data usefulness. We define a new privacy model, develop an anonymization algorithm to accommodate special challenges on RFID data, and evaluate its performance in terms of data quality, efficiency, and scalability. To the best of our knowledge, this is the first work on anonymizing high-dimensional RFID data. Copyright 2009 ACM.
In this article, we survey the history of studies of computational creativity, following the development of the International Conference on Computational Creativity pom its beginnings, a decade ago, in two parallel wo...
详细信息
The purpose of this paper is to identify the threats that exist in Healthcare Information systems (HIS). The study has been carried out in three different departments namely, Information Technology department (ITD), M...
详细信息
ISBN:
(纸本)9781424451012
The purpose of this paper is to identify the threats that exist in Healthcare Information systems (HIS). The study has been carried out in three different departments namely, Information Technology department (ITD), Medical Record department (MRD) and X-Ray department in one of the leading government supported hospital in Malaysia. The hospital was equipped with Total Hospital Information System (THIS) environment. The data were collected using in-depth structured interviews. The study identified 22 types of threats according to major threat categories based on ISO/IEC 27002 (ISO 27799:2008). The result shows the most critical threat for the THIS is the power failure. In addition, acts of human error or failure threat also show high frequency of occurrence. The contribution of the paper will be categorization of threats in HIS and can be used to design and implement effective security systems and policies in healthcare setting.
暂无评论