In Vehicular Ad Hoc Networks (VANETs), content distribution directly relies on the fleeting and dynamic contacts between moving vehicles, which often leads to prolonged downloading delay and terrible user experience. ...
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ISBN:
(纸本)9781467307734;9781467307758
In Vehicular Ad Hoc Networks (VANETs), content distribution directly relies on the fleeting and dynamic contacts between moving vehicles, which often leads to prolonged downloading delay and terrible user experience. Deploying Wifi-based Access Points (APs) could relieve this problem, but it often requires a large amount of investment, especially at the city scale. In this paper, we propose the idea of ParkCast, which doesn't need investment, but leverages roadside parking to distribute contents in urban VANETs. With wireless device and rechargable battery, parked vehicles can communicate with any vehicles driving through them. Owing to the extensive parking in cities, available resources and contact opportunities for sharing are largely increased. To each road, parked vehicles at roadside are grouped into a line cluster as far as possible, which is locally coordinated for node selection and data transmission. Such a collaborative design paradigm exploits the sequential contacts between moving vehicles and parked ones, implements sequential file transfer, reduces unnecessary messages and collisions, and then expedites content distribution greatly. We investigate ParkCast through theoretic analysis and realistic survey and simulation. The results prove that our scheme achieve high performance in distribution of contents with different sizes, especially in sparse traffic conditions.
In this paper, cross-corpora evaluations are used to analyze the bias of spontaneous facial expression databases. Local binary pattern, Gabor, eigenface and fisherface features are extracted and applied to the four sp...
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ISBN:
(纸本)9781467322164
In this paper, cross-corpora evaluations are used to analyze the bias of spontaneous facial expression databases. Local binary pattern, Gabor, eigenface and fisherface features are extracted and applied to the four spontaneous expression databases: USTC-NVIE, VAM, Belfast Naturalistic and SEMAINE to recognize arousal (high/low) and valance (positive/negative) respectively. Experimental results indicate that there exists bias among different spontaneous expression databases. The emotion-induction methods, the variety of subjects and the quantity of raters may have caused such a bias.
In this study, we investigate the break index labeling problem with a syntactic-to-prosodic structure conversion. The statistical relationship between the mapped syntactic tree structure and prosodic tree structure of...
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In this study, we investigate the break index labeling problem with a syntactic-to-prosodic structure conversion. The statistical relationship between the mapped syntactic tree structure and prosodic tree structure of sentences in the training set is used to generate a Synchronous Tree Substitution Grammar (STSG) which can describe the probabilistic mapping (substitution) rules between them. For a given test sentence and the corresponding parsed syntactic tree structure, thus generated STSG can convert the syntactic tree to a prosodic tree statistically. We compare the labeling results with other approaches and show the probabilistic mapping can indeed benefit break index labeling performance.
The research of metamaterial is one of most important global activity that promises to change the lives in many different ways. Flexibly controlling the properties of metamaterials by tunable designs makes metamateria...
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The research of metamaterial is one of most important global activity that promises to change the lives in many different ways. Flexibly controlling the properties of metamaterials by tunable designs makes metamaterials more colorful and thus enables a family of new electromagnetic devices. In this paper, the use of ferrites on design of tunable metamaterials has been reviewed. Owing to the novel properties of ferrites, including broadband negative permeability and tunability of permeability, a great many researchers have focused on investigating ferrites based metamaterials and the relevant applications. This paper reviews the design, theoretical analysis, numerical and experimental demonstrations, and the potential applications of the ferrite based metamaterials.
Traditional temporal logics such as LTL (Linear Temporal Logic) and CTL (Computation Tree Logic) have shown tremendous success in specifying and verifying hardware and software systems. However, this kind of logic can...
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We present a tunable triple-band μ-negative metamaterial composed of loop resonator and ferrite. The tunable triple-band-stop transmission spectrum of such metamaterial is investigated numerically by full wave simula...
We present a tunable triple-band μ-negative metamaterial composed of loop resonator and ferrite. The tunable triple-band-stop transmission spectrum of such metamaterial is investigated numerically by full wave simulations. Moreover, the corresponding effective parameters are retrieved to illustrate the tunable μ-negative characteristic.
Multi-task sparse feature learning aims to improve the generalization performance by exploiting the shared features among tasks. It has been successfully applied to many applications including computer vision and biom...
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ISBN:
(纸本)9781627480031
Multi-task sparse feature learning aims to improve the generalization performance by exploiting the shared features among tasks. It has been successfully applied to many applications including computer vision and biomedical informatics. Most of the existing multi-task sparse feature learning algorithms are formulated as a convex sparse regularization problem, which is usually suboptimal, due to its looseness for approximating an ?_0o-type regularizer. In this paper, we propose a non-convex formulation for multi-task sparse feature learning based on a novel regularizer. To solve the non-convex optimization problem, we propose a Multistage Multi-Task Feature Learning (MSMTFL) algorithm. Moreover, we present a detailed theoretical analysis showing that MSMTFL achieves a better parameter estimation error bound than the convex formulation. Empirical studies on both synthetic and real-world data sets demonstrate the effectiveness of MSMTFL in comparison with the state of the art multi-task sparse feature learning algorithms.
The future power grid is expected to further expand with highly distributed energy sources and smart loads. The increased size and complexity lead to increased burden on existing computational resources in energy cont...
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ISBN:
(纸本)9781467309745
The future power grid is expected to further expand with highly distributed energy sources and smart loads. The increased size and complexity lead to increased burden on existing computational resources in energy control centers. Thus the need to perform real-time assessment on such systems entails efficient means to distribute centralized functions such as state estimation in the power system. In this paper, we present our experience of prototyping a system architecture that connects distributed state estimators individually running parallel programs to solve non-linear estimation procedure. Through our experience, we highlight the needs of integrating the distributed state estimation algorithm with efficient partition and data communication tools so that distributed state estimation has low overhead compared to the centralized solution. We build a test case based on the IEEE 118 bus system and partition the state estimation of the whole system model to available HPC clusters. The measurement from the test bed demonstrates the low overhead of our solution.
In this work, we propose a recursive local linear estimator (RLLE) for identification of nonlinear autoregressive systems with exogenous inputs, along with an analysis of its strong consistency and asymptotical mean s...
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In this work, we propose a recursive local linear estimator (RLLE) for identification of nonlinear autoregressive systems with exogenous inputs, along with an analysis of its strong consistency and asymptotical mean square error properties. The performance of the proposed RLLE is verified by a simulation example.
This paper proposes key SaaS (Software-as-a-Service) design strategies for those SaaS systems that run on top of a commercial PaaS (Platform-as-a-Service) system such as GAE (Google App Engine)[1]. Specifically, this ...
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This paper proposes key SaaS (Software-as-a-Service) design strategies for those SaaS systems that run on top of a commercial PaaS (Platform-as-a-Service) system such as GAE (Google App Engine)[1]. Specifically, this paper proposes a model-based approach for customization, multi-tenancy architecture, scalability, and redundancy & recovery techniques for GAE. The ACDATER (Actors, Conditions, Data, Actions, Timing, Events, and Relationship) model is used for various features, and then automated code generation is used to generate code based on the model specified. Simulation can be performed to ensure correctness before deployment.
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