The Experts below are selected from a list of 3504 Experts worldwide ranked by ideXlab platform
Sung Wook Baik - One of the best experts on this subject based on the ideXlab platform.
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mobile cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors
Sensors, 2014Co-Authors: Irfan Mehmood, Muhammad Sajjad, Sung Wook BaikAbstract:Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For Redundancy Elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.
Chen Yang - One of the best experts on this subject based on the ideXlab platform.
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sensor placement algorithm for structural health monitoring with Redundancy Elimination model based on sub clustering strategy
Mechanical Systems and Signal Processing, 2019Co-Authors: Chen Yang, Ke Liang, Xuepan Zhang, Xinyu GengAbstract:Abstract Considering the limitation of selecting several neighbor sensors in a local region similar to just single one, namely redundant information, a sensor placement algorithm for structural health monitoring is proposed based on sub-clustering strategy, in order to improve the performance of sensor configuration with less Redundancy. According to the significance of Redundancy, the proposed novel Redundancy Elimination model considers global and local effect to overcome the previous limitations in sensor distribution. Based on the sub-clustering strategy, the Redundancy Elimination model reflects the sensor configuration in each sub-clustering and overall structural field. The presented sub-clustering strategy for sensor placement includes three main procedures: sub-clustering algorithm, its check step and smallest enclosing circle method, thus the accuracy can be guaranteed. Combining the effective independence method with normalization and weighting factor, the proposed sensor placement algorithm can balance performance and Redundancy by using genetic algorithm, which is more competitive to reduce the order difference between the two objectives. Finally, the effectiveness of the proposed Redundancy Elimination model is verified by a simple example, and another two engineering numerical examples including space solar power satellite and re-usable launch vehicle are applied to demonstrate the validity of the proposed sensor placement algorithm respectively.
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optimal sensor placement for spatial lattice structure based on three dimensional Redundancy Elimination model
Applied Mathematical Modelling, 2019Co-Authors: Chen Yang, Wanzheng Zheng, Xuepan ZhangAbstract:Abstract Spatial lattice structures are widely applied in engineering fields attributed to their superiorities in weight and reasonable stress. It is essential to select the best sensor placement layout for structural health monitoring and safety purposes, yet it is neither realistic nor efficient to place sensors in every location possible on the structure. To meet the strong requirements for optimal sensor placement in spatial lattice structure, this paper aims to investigate a combined objective function based on effective independence method and three dimensional Redundancy Elimination model to balance between optimal sensor placement performance and Elimination in Redundancy. To eliminate redundant information and resource waste caused by the clustered sensor distribution, the three-dimensional Redundancy Elimination model is constructed with the consideration of nearer nodes and overall sensor distribution ranges in three-dimensional cases. In addition, the combined function is constructed by giving the two component functions equal significance using weighting factors and normalization, and solved by genetic algorithm. Finally, the proposed method for spatial lattice structure is supported by three numerical examples including a simple lattice structure, a ground spatial truss structure and a space docking modular in space solar power satellite.
Konstantin Korovin - One of the best experts on this subject based on the ideXlab platform.
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inst gen a modular approach to instantiation based automated reasoning
In: Programming Logics - Essays in Memory of Harald Ganzinger; 2013. p. 239-270., 2013Co-Authors: Konstantin KorovinAbstract:Inst-Gen is an instantiation-based reasoning method for first-order logic introduced in [18]. One of the distinctive features of Inst-Gen is a modular combination of first-order reasoning with efficient ground reasoning. Thus, Inst-Gen provides a framework for utilising efficient off-the-shelf propositional SAT and SMT solvers as part of general first-order reasoning. In this paper we present a unified view on the developments of the Inst-Gen method: (i) completeness proofs; (ii) abstract and concrete criteria for Redundancy Elimination, including dismatching constraints and global subsumption; (iii) implementation details and evaluation.
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iprover eq an instantiation based theorem prover with equality
International Joint Conference on Automated Reasoning, 2010Co-Authors: Konstantin Korovin, Christoph StickselAbstract:iProver-Eq is an implementation of an instantiation-based calculus Inst-Gen-Eq which is complete for first-order logic with equality. iProver-Eq extends the iProver system with superposition-based equational reasoning and maintains the distinctive features of the Inst-Gen method. In particular, first-order reasoning is combined with efficient ground satisfiability checking where the latter is delegated in a modular way to any state-of-the-art SMT solver. The first-order reasoning employs a saturation algorithm making use of Redundancy Elimination in form of blocking and simplification inferences. We describe the equational reasoning as it is implemented in iProver-Eq, the main challenges and techniques that are essential for efficiency.
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iprover an instantiation based theorem prover for first order logic system description
International Joint Conference on Automated Reasoning, 2008Co-Authors: Konstantin KorovinAbstract:iProver is an instantiation-based theorem prover which is based on Inst-Gen calculus, complete for first-order logic. One of the distinctive features of iProver is a modular combination of instantiation and propositional reasoning. In particular, any state-of-the art SAT solver can be integrated into our framework. iProver incorporates state-of-the-art implementation techniques such as indexing, Redundancy Elimination, semantic selection and saturation algorithms. Redundancy Elimination implemented in iProver include: dismatching constraints, blocking non-proper instantiations and propositional-based simplifications. In addition to instantiation, iProver implements ordered resolution calculus and a combination of instantiation and ordered resolution. In this paper we discuss the design of iProver and related implementation issues.
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Integrating equational reasoning intoinstantiation-based theorem proving
2008Co-Authors: Harald Ganzinger, Konstantin KorovinAbstract:Abstract. In this paper we present a method for integrating equational reason-ing into instantiation-based theorem proving. The method employs a satisfiability solver for ground equational clauses together with an instance generation processbased on an ordered paramodulation type calculus for literals. The completeness of the procedure is proved using the the model generation technique, which al-lows us to justify Redundancy Elimination based on appropriate orderings
Irfan Mehmood - One of the best experts on this subject based on the ideXlab platform.
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mobile cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors
Sensors, 2014Co-Authors: Irfan Mehmood, Muhammad Sajjad, Sung Wook BaikAbstract:Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For Redundancy Elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.
Xuepan Zhang - One of the best experts on this subject based on the ideXlab platform.
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sensor placement algorithm for structural health monitoring with Redundancy Elimination model based on sub clustering strategy
Mechanical Systems and Signal Processing, 2019Co-Authors: Chen Yang, Ke Liang, Xuepan Zhang, Xinyu GengAbstract:Abstract Considering the limitation of selecting several neighbor sensors in a local region similar to just single one, namely redundant information, a sensor placement algorithm for structural health monitoring is proposed based on sub-clustering strategy, in order to improve the performance of sensor configuration with less Redundancy. According to the significance of Redundancy, the proposed novel Redundancy Elimination model considers global and local effect to overcome the previous limitations in sensor distribution. Based on the sub-clustering strategy, the Redundancy Elimination model reflects the sensor configuration in each sub-clustering and overall structural field. The presented sub-clustering strategy for sensor placement includes three main procedures: sub-clustering algorithm, its check step and smallest enclosing circle method, thus the accuracy can be guaranteed. Combining the effective independence method with normalization and weighting factor, the proposed sensor placement algorithm can balance performance and Redundancy by using genetic algorithm, which is more competitive to reduce the order difference between the two objectives. Finally, the effectiveness of the proposed Redundancy Elimination model is verified by a simple example, and another two engineering numerical examples including space solar power satellite and re-usable launch vehicle are applied to demonstrate the validity of the proposed sensor placement algorithm respectively.
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optimal sensor placement for spatial lattice structure based on three dimensional Redundancy Elimination model
Applied Mathematical Modelling, 2019Co-Authors: Chen Yang, Wanzheng Zheng, Xuepan ZhangAbstract:Abstract Spatial lattice structures are widely applied in engineering fields attributed to their superiorities in weight and reasonable stress. It is essential to select the best sensor placement layout for structural health monitoring and safety purposes, yet it is neither realistic nor efficient to place sensors in every location possible on the structure. To meet the strong requirements for optimal sensor placement in spatial lattice structure, this paper aims to investigate a combined objective function based on effective independence method and three dimensional Redundancy Elimination model to balance between optimal sensor placement performance and Elimination in Redundancy. To eliminate redundant information and resource waste caused by the clustered sensor distribution, the three-dimensional Redundancy Elimination model is constructed with the consideration of nearer nodes and overall sensor distribution ranges in three-dimensional cases. In addition, the combined function is constructed by giving the two component functions equal significance using weighting factors and normalization, and solved by genetic algorithm. Finally, the proposed method for spatial lattice structure is supported by three numerical examples including a simple lattice structure, a ground spatial truss structure and a space docking modular in space solar power satellite.