This paper addresses the problem of localization and tracking multiple non-cooperative objects using only passive bearing sensor data. The challenges in this context lie in an unknown number of objects, false alarms a...
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ISBN:
(纸本)9780982443811
This paper addresses the problem of localization and tracking multiple non-cooperative objects using only passive bearing sensor data. The challenges in this context lie in an unknown number of objects, false alarms and clutter measurements. To avoid the time consuming data association and data storage, an iterative approach, which only considers the sensor data from the actual timestep for an update of every object state, is preferable. Our approach to perform this is a Monte Carlo realization of a probability hypothesis density filter. In this context we use bearing data gained from an antenna or optical camera mounted on an airborne observer. Tests on simulated and real world scenarios show that our approach leads to a stable localization and tracking of multiple targets, even in the presence of clutter and misleading bearing measurements.
Cyber security continues to be an increasingly important topic when considering Homeland Security issues. This area however is often overlooked during a disaster or emergency situation. Emergency management within the...
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We present JAWS, a job-aware, data-driven batch scheduler that improves query throughput for data-intensive scientific database clusters. As datasets reach petabyte-scale, workloads that scan through vast amounts of d...
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A Top-k aggregate query, which is a powerful technique when dealing with large quantity of data, ranks groups of tuples by their aggregate values and returns k groups with the highest aggregate values. However, compar...
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Several reports have linked food poisoning with the consumption of raw vegetables and fruits contaminated by Salmonella. Most studies suggested an extracellular lifestyle of Salmonella on plants. However, more recent ...
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ISBN:
(纸本)9783885792703
Several reports have linked food poisoning with the consumption of raw vegetables and fruits contaminated by Salmonella. Most studies suggested an extracellular lifestyle of Salmonella on plants. However, more recent studies show that Salmonella are also able to colonize the intracellular compartment of various plant tissues causing chlorosis and eventually death of infected organs. The aim of this work is to present a probabilistic classification algorithm for disease symptoms on Arabidopsis thaliana plant in order to improve the current biological research. The algorithm itself uses images of Arabidopsis thaliana leaves as input and consists of two steps. The first step is the detection of pixels belonging to a leaf. This is done with a globally optimal color segmentation method. The second step is realized with a probabilistic framework to classify each pixel. Finally a morbidity rate is computed based on the classification result.
Ubiquitous knowledge discovery systems must be captured from many different perspectives. In earlier chapters, aspects like machine learning, underlying network technologies etc. were described. An essential component...
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We have demonstrated a heterogeneously integrated Si/III-V laser based on an ultra-large-angle super-compact curved diffraction grating suitable for WDM applications in EPICs The lasing threshold is 150mA giving a max...
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We report the design and experimental results of an electrically pumped Silicon/AlGaInAs evanescent laser with right-angled-wedge reflector defined in the silicon layer. A continuous-wave laser with a lasing threshold...
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In this paper, we present an approach to automate the planning of an endovascular stent graft for abdominal aortic aneurysms (AAAs), which are treated with bifurcated prosthesis (Y-stents) when located close to the il...
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We present an interactive visualization system for the analysis of Gaussian mixture speaker models. The system exhibits the inner workings of the model intuitively by visualizing graphical representations of its param...
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We present an interactive visualization system for the analysis of Gaussian mixture speaker models. The system exhibits the inner workings of the model intuitively by visualizing graphical representations of its parameters and of the underlying acoustical data at the same time. This enables the exploration of new modeling possibilities in the context of speaker clustering tasks.
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