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Visual tracking integrates the technology of image processing and pattern recognition, etc., which has a lot of potential applications, such as automatic driving, safety monitoring, etc. This paper analyzes the advantages and disadvantages of the Kernelized Correlation Filter (KCF) and Tracking-Learning-Detection (TLD), which are two kinds of trackers. TLD tracker has correcting capability whereas...
Traditionally, distributed computing concentrates on computation understood at the level of information exchange and sets aside human and organizational concerns as largely to be handled in an ad hoc manner. Increasingly, however, distributed applications involve multiple loci of autonomy. Research in multiagent systems (MAS) addresses autonomy by drawing on concepts and techniques from artificial...
The assessment methods used in the vast majority of virtual learning environments are not satisfactory for measuring student learning, many of which provide only tools that allow for summative assessment, thus providing incorrect information about learning. Many of these environments are not able to provide responses about student learning and do not provide activities that can be monitored by verifying...
The paradigm of health care delivery is slowly aligning with the needs and habits of modern patients. Mobile computing may be a solution to respond to the growing trend and need for health care sharing and collaboration, enabling the redesign of processes giving rise to new models of health care delivery. Seeking to determine the situation in Portugal regarding mobile computing initiatives in this...
In this paper we propose a model of the dynamic heart system, as a necessary and important element of the non-invasive ECG diagnostic system. It was shown that the conceptual and detailed models of heart electrical activity are the link for all the subsystems of the cardiovascular system. In this case the ECG provides information of the status and autowave processes in a dynamic heart system. To control...
People are suffering from a range of risks in the ubiquitous networks of current world, such as rumours spreading in social networks, computer viruses propagating throughout the Internet and unexpected failures happened in Smart grids. We usually monitor only a few users of detecting various risks due to the resource constraints and privacy protection. This leads to a critical problem to detect compromised...
Computerized systems employed for the analysis of cardiotocographic signals have become almost indispensable tools in fetal monitoring, for which evaluation of fetal heart rate signals plays a key role. Consequently to the diffusion of these systems, new software and complex signal processing methodologies are spreading and are gaining more and more interest. For testing the performances of new software...
The inference of the network traffic matrix from partial measurement data becomes increasingly critical for various network engineering tasks, such as capacity planning, load balancing, path setup, network provisioning, anomaly detection, and failure recovery. The recent study shows it is promising to more accurately interpolate the missing data with a three-dimensional tensor as compared to interpolation...
In this paper, we address the problem of nonlinear fault detection of chemical processes. The objective is to extend our previous work [1] to provide a better performance in terms of fault detection accuracies by developing a pre-image kernel PCA (KPCA)-based Generalized Likelihood Ratio Test (GLRT) technique. The benefit of the pre-image kPCA technique lies in its ability to compute the residual...
Hospital inpatients often fall during an exit from the bed or in the ensuing seconds and minutes. Existing fall prevention technologies fail to provide adequate lead time to a patient bed exit or exhibit high rates of false alarms. To address these limitations and reduce risk of falls for patients and hospitals, we have developed a 3D camera-based system, named Ocuvera, for monitoring patients at...
The objective of this paper is to extend the applicability of the GLR method to a wide range of practical systems. Most real systems are nonlinear, multivariate, and are best represented by input-output type of models. Kernel partial least squares (KPLS) models have been widely used to represent such systems. Therefore, in this paper, kernel PLS-based GLR method will be utilized in practice to improve...
In this paper we present a system architecture for trust management inspired by a human model for the evaluation of trust. We focus on large-scale marketplaces for diverse software resources and services. In such marketplaces, user agents (consumer, provider and broker) are largely autonomous with vastly diverse requirements, capabilities, and trust preferences. We hypothesize the need for personalized...
With cloud computing, efficient resource management is of great importance, as it has a direct impact on the scalability of the cloud application, and can result in significant energy and cost reductions. In recent years, a lot of research has been done regarding the management of cloud resources, resulting in multiple novel resource allocation strategies. Validation of these strategies however is...
How the brain maintains the stability of visual perception across saccade is a central question in systems neuroscience; accurately characterizing visual responses in the perisaccadic period is an important step towards understanding how the visual world is represented during saccades. Here, we develop a probabilistic model in the Generalized Linear Model framework to characterize and predict the...
This paper introduces an approach that handleswith the trustworthy cloud service selection issue in Cloudcomputing environments. Despite the fact that most of theexisting trust systems consider several QoS attributes for trustcomputing, none of them did consider the correlation that mayexist among these attributes. However, we demonstrate in thispaper that the integration of correlation between QoS...
The problem of monitoring ongoing technical condition of various vehicle subsystems from operational data is a subject matter for many modern armies. Due to the requirements on reliability of military vehicles and its failure-free operation during a mission; it would be advantageous to have a tool that enables a quick diagnostics of vehicles most important components. Present article shows one of...
At 28nm technology and below, hot spot prediction and process window control on production wafers have become increasingly critical to prevent sensitive pattern geometries from becoming yield limiting defects as a result of process variation. We previously established a systematic approach to identify focus-sensitive hotspots, characterize their process window margins, use a focus variation map to...
The use of counterfeit smart grid devices throughout the smart grid communication infrastructure represents a real problem. Hence, monitoring and early detection of counterfeit smart grid devices is critical for protecting smart grid's components and data. To address these concerns, in this paper, we introduce a novel system level approach to identify counterfeit smart grid devices. Specifically,...
Performance monitoring is essential for all subsystems, especially high performance computing systems. These systems are sensitive to errors and failures which lead to data losses and then severely impact on the organizations. Consequently, resource information in the systems (e.g., CPU usage, memory usage, disk I/O usage, etc.) during the operations must be collected through the system monitoring...
The following is a very common question in numerous theoretical and application-related domains: given a graph G, does it satisfy some given property? For example, is G connected? Is its diameter smaller than a given threshold? Is its average degree larger than a certain threshold? Traditionally, algorithms to quickly answer such questions were developed for static and centralized graphs (i.e. G is...
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