This paper discusses the role of casual attributions and positive emotion in trust repair of *** equation modeling(SEM) was used in our study to analyze 517 valid online *** empirical results indicate that casual attr...
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This paper discusses the role of casual attributions and positive emotion in trust repair of *** equation modeling(SEM) was used in our study to analyze 517 valid online *** empirical results indicate that casual attributions(locus and stability) have a negative impact on positive emotion;however,controllability opposing our initial expectation has a positive impact on positive *** the same time,positive emotion not only influences trust but also mediates the effect of casual attributions on trust.
In this research we investigate that user's stickiness of virtual community would affect the trust and the stickiness is mediator between trust repair and *** questionnaire through"Happy Farm"from the Fa...
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In this research we investigate that user's stickiness of virtual community would affect the trust and the stickiness is mediator between trust repair and *** questionnaire through"Happy Farm"from the Facebook,we used the Structural equation modeling(SEM) to analyze the data,in order to understand repair methods and the community trust the persons concerned after the stickiness of the impact of *** result shows that functional and informational of trust repair has positive relationship with stickiness.
We propose and experimentally evaluate a new method for clustering human behaviors that is suitable for bootstrapping an anomaly detection module for intelligent video surveillance systems. The method uses dynamic tim...
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ISBN:
(纸本)9789746724913
We propose and experimentally evaluate a new method for clustering human behaviors that is suitable for bootstrapping an anomaly detection module for intelligent video surveillance systems. The method uses dynamic time warping, agglomerative hierarchical clustering, and hidden Markov models to provide an initial partitioning of a set of observation sequences then automatically identifies where to cut off the hierarchical clustering dendrogram. We show that the method is extremely effective, providing 100% accuracy in separating anomalous from typical behaviors on real-world testbed video surveillance data.
We research the multimedia information hiding (MIH) which is a technology to overlay digital information on multimedia contents such as picture, sound, document, etc. As application to disaster management of MIH, we h...
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We research the multimedia information hiding (MIH) which is a technology to overlay digital information on multimedia contents such as picture, sound, document, etc. As application to disaster management of MIH, we have developed a new technology called "PAIH" (Public Address information Hiding) which is a technology to overlay information such as position or destination on siren sound of urgent vehicles. Siren sound is allowed to degrade of sound quality, but PAIH is required to decode correct information from siren sound with pitch shift (Doppler effect) or under noisy environment.
On-demand resource provision is one of the key features of cloud computing, allowing applications to grow or shrink on the basis of dynamic workloads. Thus far, most of the research on leveraging on-demand resource pr...
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ISBN:
(纸本)9789746724913
On-demand resource provision is one of the key features of cloud computing, allowing applications to grow or shrink on the basis of dynamic workloads. Thus far, most of the research on leveraging on-demand resource provision has focused on batch style applications for scientific computation or Web-centric applications, especially n-tier e-commerce applications. Very little research, however, has focused on leveraging the benefits of cloud computing for applications with alternative architectures. In this paper, we focus on Back-end Mashup applications that have resource-intensive back ends responsible for continuous collection and analysis of real-time data from external services or applications. We present a working prototype back-end mashup application, BuddyMonitor, that allows users of instant messaging services to monitor and analyze the online presence of their "buddies." The prototype exploits adaptive allocation of cloud resources to scale gracefully in the presence of rapid increases in workload. We demonstrate the feasibility of the approach in an experimental evaluation with a testbed cloud and a realistic simulation of a large scale external XMPP chat service. We conclude that cloud computing with adaptive resource allocation has the potential to increase the usability, stability, and performance of large-scale back-end mashup applications.
Current service-level agreements (SLAs) offered by cloud providers do not make guarantees about response time of Web applications hosted on the cloud. Satisfying a maximum average response time guarantee for Web appli...
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A simple and intuitive model to mine an email transactions log for significant messages and users is presented. No use is made of NLP or semantic analysis. The model is based only on scoring messages and users from a ...
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ISBN:
(纸本)9788988678312
A simple and intuitive model to mine an email transactions log for significant messages and users is presented. No use is made of NLP or semantic analysis. The model is based only on scoring messages and users from a graphtheoretic analysis of the communication pattern represented in the transaction log. Practical experiments indicate the potential of the model.
We propose and experimentally evaluate a new method for clustering human behaviors that is suitable for bootstrapping an anomaly detection module for intelligent video surveillance systems. The method uses dynamic tim...
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ISBN:
(纸本)9781424456062
We propose and experimentally evaluate a new method for clustering human behaviors that is suitable for bootstrapping an anomaly detection module for intelligent video surveillance systems. The method uses dynamic time warping, agglomerative hierarchical clustering, and hidden Markov models to provide an initial partitioning of a set of observation sequences then automatically identifies where to cut off the hierarchical clustering dendrogram. We show that the method is extremely effective, providing 100% accuracy in separating anomalous from typical behaviors on real-world testbed video surveillance data.
A simple and intuitive model to mine an email transactions log for significant messages and users is presented. No use is made of NLP or semantic analysis. The model is based only on scoring messages and users from a ...
详细信息
A simple and intuitive model to mine an email transactions log for significant messages and users is presented. No use is made of NLP or semantic analysis. The model is based only on scoring messages and users from a graph-theoretic analysis of the communication pattern represented in the transaction log. Practical experiments indicate the potential of the model.
Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. Because of high levels of occlusion, ...
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ISBN:
(纸本)9781424478149
Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. Because of high levels of occlusion, dense features, and shadows, object detectors tend to produce large numbers of false detections. We introduce a new method based on 3D head plane estimation that reduces these false detections while preserving high detection rates. Our algorithm learns the head plane from observations of human heads, without any a priori extrinsic camera calibration information. In an experimental evaluation, we show that the head plane estimation technique dramatically improves the performance of a pedestrian tracker for dense crowds based on a Viola and Jones AdaBoost cascade classifier for head detection, a particle filter for tracking, and color histograms for appearance modeling.
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