The networked integration of military systems can enable timely exploitation of intelligence and offer strategic advantages in the battlefield. Despite operating under harsh, hostile conditions, tactical networks have...
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A system for interpretation of complex scenes is presented. The main characteristics of the system are: virtual multisensor input, knowledge based and multilevel architecture, and intensional approach. The specific ap...
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Nowadays, security has become an important topic of interest to researchers. Different types of cryptography algorithms have been developed in order to improve the performance of these information-protecting procedure...
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This paper presents a modified approach to design multilevel controllers using structural perturbation technique for large-scale systems based on genetic algorithms. The powerful capabilities of genetic algorithms in ...
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Automated detection of anomalous trajectories is an important problem with considerable applications in intelligent transportation systems. Many existing studies have focused on distinguishing anomalous trajectories f...
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ISBN:
(数字)9781665490429
ISBN:
(纸本)9781665490429
Automated detection of anomalous trajectories is an important problem with considerable applications in intelligent transportation systems. Many existing studies have focused on distinguishing anomalous trajectories from normal trajectories, ignoring the large differences between anomalous trajectories. A recent study has made great progress in identifying abnormal trajectory patterns and proposed a two-stage algorithm for anomalous trajectory detection and classification (ATDC). This algorithm has excellent performance but suffers from a few limitations, such as high time complexity and poor interpretation. Here, we present a careful theoretical and empirical analysis of the ATDC algorithm, showing that the calculation of anomaly scores in both stages can be simplified, and that the second stage of the algorithm is much more important than the first stage. Hence, we develop a FastATDC algorithm that introduces a random sampling strategy in both stages. Experimental results show that FastATDC is 10 to 20 times faster than ATDC on real datasets. Moreover, FastATDC outperforms the baseline algorithms and is comparable to the ATDC algorithm.
This paper presents a new set of sensor fusion algorithms for mapping the environment of mobile robots using grid maps. The algorithms use the adaptive weighted average method and consider as weights the number of tim...
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Targeting enhanced navigational speed and autonomy for the space exploration rovers, researchers are gradually turning to reconfigurable computing and FPGAs. High-density space-grade FPGAs will enable the acceleration...
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A large number of multi-objective optimization evolutionary algorithms(MOEAs) have been developed in the past two decades. To compare these methods rigorously, or to measure the performance of a particular MOEA quanti...
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ISBN:
(纸本)9781424421961
A large number of multi-objective optimization evolutionary algorithms(MOEAs) have been developed in the past two decades. To compare these methods rigorously, or to measure the performance of a particular MOEA quantitatively, a variety of performance measures have been proposed. In this paper, some existing widely-used performance measures are briefly reviewed and compared according different properties. Two new performance measures computing the convergence towards the Pareto front and the solution diversity on the Pareto front are proposed And an outlook on how to further deepen insight in performance measures of MOEAs is given.
The evaluation model used in underlining intelligent manufacturing systems (IMS) and prospects based on improved algorithms and Machine Learning (ML) provides a systematized model for the optimization of production op...
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Numerous monitoring applications such as traffic control systems, border patrol monitoring, and person locater services generate a large number of multimedia data streams that need to be analyzed and processed using i...
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