Abstract: Image-based three-dimensional (3D) reconstruction can be used in many emerging applications like AR and disaster recovery. Most 3D reconstruction methods require mobile users to walk around the target area and reconstruct objectives with a…
Abstract: Before a smartphone user can access nearby devices’ services, her device must discover them. Service visibility scoping in large-scale, heterogeneous enterprise environments has many unique features, such as proximity-based interactions, differentiated visibility by device…
Abstract: Software-defined vehicle networks (SDVN) have introduced new VANET paradigms. Analytical and simulation models are needed to evaluate these new proposals and architectures. We present an analytical model for ON-OFF queueing networks under exponential and…
Abstract: 60GHz channels have few dominant paths due to sparsity. We can use dominant path angular information to predict link performance and track 802.11ad devices. 802.11ad devices have phased arrays, but their limited RF chains…
Abstract: UASNs are used in offshore exploration, auxiliary navigation, and marine military. Underwater sensor nodes’ communication, computation, and storage limitations preclude traditional security mechanisms. Trust models have been investigated as effective tools for UASN security…
Abstract: Recent smartphone sensors make identifying a locomotion mode easy. Locomomotion mode information improves trip planning, travel time estimation, and traffic management. Locomotion mode recognition work depends on labeled training instances and is not relevant….
Abstract: Network-based indoor positioning with WiFi access point (AP) RSS measurements uses channel modeling, position estimation, and error analysis. A novel sparse Bayesian learning algorithm models the radio power map (RPM) in indoor space to…
Abstract: Indoor positioning using Wi-Fi fingerprinting is common. It uses a similarity function to compare the operational fingerprint to a radio map of reference samples. In large deployments with a high fingerprint density and a…
Abstract: Unsupervised spectral feature selection (USFS) methods can produce interpretable and discriminative results by embedding a Laplacian regularizer in sparse feature selection to maintain training sample local similarity. USFS methods use a general-graph or hyper-graph…
Abstract: Social neighborhoods influence people’s social decisions. Structural diversity in the contact neighborhood predicts social contagion. Existing models have limited decomposability for large-scale networks and inaccurately reflect social context diversity. This paper proposes a truss-based…
Abstract: We study an automatic hypothesis generation (HG) problem, which involves discovering meaningful implicit connections between scientific terms like diseases, chemicals, drugs, and genes extracted from biomedical publication databases. Most previous studies of this problem…
Abstract: Recently, social media research has grown. This article predicts active users in online social events, which is rarely done. Previous work focused on emerging topics. This prediction task is a binary classification problem based…
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