The Experts below are selected from a list of 1051317 Experts worldwide ranked by ideXlab platform
Hongqi Wang - One of the best experts on this subject based on the ideXlab platform.
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a new method on inshore ship detection in high resolution satellite images using shape and Context Information
IEEE Geoscience and Remote Sensing Letters, 2014Co-Authors: Ge Liu, Yasen Zhang, Xinwei Zheng, Xian Sun, Hongqi WangAbstract:In this letter, we present a new method to detect inshore ships using shape and Context Information. We first propose a new energy function based on an active contour model to segment water and land and minimize it with an iterative global optimization method. The proposed energy performs well on the different intensity distributions between water and land and produces a result that can be well used in shape and Context analyses. In the segmented image, ships are detected with successive shape analysis, including shape analysis in the localization of ship head and region growing in computing the width and length of ship. Finally, to locate ships accurately and remove the false alarms, we unify them with a binary linear programming problem by utilizing the Context Information. Experiments on QuickBird images show the robustness and precision of our method.
Alan Colman - One of the best experts on this subject based on the ideXlab platform.
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ontcaac an ontology based approach to Context aware access control for software services
The Computer Journal, 2015Co-Authors: A S M Kayes, Jun Han, Alan ColmanAbstract:In modern communication environments, the ability to provide access control to services in a Context-aware manner is crucial. By leveraging the dynamically changing Context Information, we can achieve Context-specific control over access to services, better satisfying the security and privacy requirements of the stakeholders. In this paper, we introduce a new Context-Aware Access Control (CAAC) Framework that adopts an ontological approach in modelling dynamic Context Information and the corresponding CAAC policies. It includes a Context model specific to access control, capturing the relevant low-level Context Information and inferring the high-level implicit Context Information. Using the Context model, the policy model of the framework provides support for specifying and enforcing CAAC policies. We have developed a prototype and presented a healthcare case study to realise the framework.
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user centric social Context Information management an ontology based approach and platform
Ubiquitous Computing, 2014Co-Authors: Muhammad Ashad Kabir, Jian Yu, Alan ColmanAbstract:Social Context Information has been used with encouraging results in developing socially aware applications in different domains. However, users' social Context Information is distributed over the Web and managed by many different proprietary applications, which is a challenge for application developers as they must collect Information from different sources and wade through a lot of irrelevant Information to obtain the social Context Information of interest. On the other hand, it is extremely hard for Information owners to control how their Information should be exposed to different users and applications. Combining the social Context Information from the diverse sources, incorporating richer semantics and preserving Information owners' privacy could greatly assist the developers and as well as the Information owners. In this paper, we introduce a social Context Information management system (SCIMS). It includes the ability to acquire raw social data from multiple sources; an ontology-based model for classifying, inferring and storing social Context Information, in particular, social relationships and status; an ontology-based policy model and language for owners to control access to their Information; a query interface for accessing and utilizing social Context Information. We evaluate the performance of SCIMS using real data from Facebook, LinkedIn, Twitter, and Google Calendar and demonstrate its applicability through a socially aware phone call application.
Muhammad Ashad Kabir - One of the best experts on this subject based on the ideXlab platform.
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user centric social Context Information management an ontology based approach and platform
Ubiquitous Computing, 2014Co-Authors: Muhammad Ashad Kabir, Jian Yu, Alan ColmanAbstract:Social Context Information has been used with encouraging results in developing socially aware applications in different domains. However, users' social Context Information is distributed over the Web and managed by many different proprietary applications, which is a challenge for application developers as they must collect Information from different sources and wade through a lot of irrelevant Information to obtain the social Context Information of interest. On the other hand, it is extremely hard for Information owners to control how their Information should be exposed to different users and applications. Combining the social Context Information from the diverse sources, incorporating richer semantics and preserving Information owners' privacy could greatly assist the developers and as well as the Information owners. In this paper, we introduce a social Context Information management system (SCIMS). It includes the ability to acquire raw social data from multiple sources; an ontology-based model for classifying, inferring and storing social Context Information, in particular, social relationships and status; an ontology-based policy model and language for owners to control access to their Information; a query interface for accessing and utilizing social Context Information. We evaluate the performance of SCIMS using real data from Facebook, LinkedIn, Twitter, and Google Calendar and demonstrate its applicability through a socially aware phone call application.
Antonio Capone - One of the best experts on this subject based on the ideXlab platform.
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Fast Cell Discovery in mm-wave 5G Networks with Context Information
IEEE Transactions on Mobile Computing, 2017Co-Authors: Ilario Filippini, Francesco Devoti, Vincenzo Sciancalepore, Antonio CaponeAbstract:The exploitation of mm-wave bands is one of the key-enabler for 5G mobile radio networks. However, the introduction of mm-wave technologies in cellular networks is not straightforward due to harsh propagation conditions that limit the mm-wave access availability. Mm-wave technologies require high-gain antenna systems to compensate for high path loss and limited power. As a consequence, directional transmissions must be used for cell discovery and synchronization processes: this can lead to a non-negligible access delay caused by the exploration of the cell area with multiple transmissions along different directions. The integration of mm-wave technologies and conventional wireless access networks with the objective of speeding up the cell search process requires new 5G network architectural solutions. Such architectures introduce a functional split between C-plane and U-plane, thereby guaranteeing the availability of a reliable signaling channel through conventional wireless technologies that provides the opportunity to collect useful Context Information from the network edge. In this article, we leverage the Context Information related to user positions to improve the directional cell discovery process. We investigate fundamental trade-offs of this process and the effects of the Context Information accuracy on the overall system performance. We also cope with obstacle obstructions in the cell area and propose an approach based on a geo-located Context database where Information gathered over time is stored to guide future searches. Analytic models and numerical results are provided to validate proposed strategies.
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Context Information for Fast Cell Discovery in mm-wave 5G Networks
Proceedings of European Wireless 2015; 21th European Wireless Conference, 2015Co-Authors: Antonio Capone, Ilario Filippini, Vincenzo SciancaleporeAbstract:The exploitation of the mm-wave bands is one of the most promising solutions for 5G mobile radio networks. However, the use of mm-wave technologies in cellular networks is not straightforward due to mm-wave harsh propagation conditions that limit access availability. In order to overcome this obstacle, hybrid network architectures are being considered where mmwave small cells can exploit an overlay coverage layer based on legacy technology. The additional mm-wave layer can also take advantage of a functional split between control and user plane, that allows to delegate most of the signaling functions to legacy base stations and to gather Context Information from users for resource optimization. However, mm-wave technology requires high gain antenna systems to compensate for high path loss and limited power, e.g., through the use of multiple antennas for high directivity. Directional transmissions must be also used for the cell discovery and synchronization process, and this can lead to a non-negligible delay due to the need to scan the cell area with multiple transmissions at different directions. In this paper, we propose to exploit the Context Information related to user position, provided by the separated control plane, to improve the cell discovery procedure and minimize delay. We investigate the fundamental trade-offs of the cell discovery process with directional antennas and the effects of the Context Information accuracy on its performance. Numerical results are provided to validate our observations.
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Context Information for Fast Cell Discovery in mm-wave 5G Networks
2015Co-Authors: Antonio Capone, Ilario Filippini, Vincenzo SciancaleporeAbstract:The exploitation of the mm-wave bands is one of the most promising solutions for 5G mobile radio networks. However, the use of mm-wave technologies in cellular networks is not straightforward due to mm-wave severe propagation conditions that limit access availability. In order to overcome this obstacle, hybrid network architectures are being considered where mm-wave small cells can exploit an overlay coverage layer based on legacy technology. The additional mm-wave layer can also take advantage of a functional split between control and user plane, that allows to delegate most of the signaling functions to legacy base stations and to gather Context Information from users for resource optimization. However, mm-wave technology requires multiple antennas and highly directional transmissions to compensate for high path loss and limited power. Directional transmissions must be also used for the cell discovery and synchronization process, and this can lead to a non negligible delay due to need to scan the cell area with multiple transmissions in different angles. In this paper, we propose to exploit the Context Information related to user position, provided by the separated control plane, to improve the cell discovery procedure and minimize delay. We investigate the fundamental trade-offs of the cell discovery process with directional antennas and the effects of the Context Information accuracy on its performance. Numerical results are provided to validate our observations.
Ge Liu - One of the best experts on this subject based on the ideXlab platform.
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a new method on inshore ship detection in high resolution satellite images using shape and Context Information
IEEE Geoscience and Remote Sensing Letters, 2014Co-Authors: Ge Liu, Yasen Zhang, Xinwei Zheng, Xian Sun, Hongqi WangAbstract:In this letter, we present a new method to detect inshore ships using shape and Context Information. We first propose a new energy function based on an active contour model to segment water and land and minimize it with an iterative global optimization method. The proposed energy performs well on the different intensity distributions between water and land and produces a result that can be well used in shape and Context analyses. In the segmented image, ships are detected with successive shape analysis, including shape analysis in the localization of ship head and region growing in computing the width and length of ship. Finally, to locate ships accurately and remove the false alarms, we unify them with a binary linear programming problem by utilizing the Context Information. Experiments on QuickBird images show the robustness and precision of our method.
