The Web is overcrowded with news articles, an overwhelming information source both with its amount and diversity. Assigning news articles to similar groups, on the other hand, provides a very powerful data mining and ...
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The paper presents a novel automatic early warning system to remotely monitor areas of archaeological and cultural interest from the risk of fire. Since these areas have been treasured and tended for very long periods...
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The paper presents a novel automatic early warning system to remotely monitor areas of archaeological and cultural interest from the risk of fire. Since these areas have been treasured and tended for very long periods of time, they are usually surrounded by old and valuable vegetation or situated close to forest regions, which exposes them to an increased risk of fire. The proposed system takes advantage of recent advances in multi-sensor surveillance technologies, using optical and infrared cameras, wireless sensor networks capable of monitoring different modalities (e.g. temperature and humidity) as well as local weather stations on the deployment site. The signals collected from these sensors are transmitted to a monitoring centre, which employs intelligent computer vision and pattern recognition algorithms as well as data fusion techniques to automatically analyze sensor information. The system is capable of generating automatic warning signals for local authorities whenever a dangerous situation arises, as well as estimating the propagation of the fire based on the fuel model of the area and other important parameters such as wind speed, slope, and aspect of the ground surface.
Collection, processing, storage and maintenance of samples to facilitate long-term cohort studies in biobanks, requires a system to manage samples in an effective way to prevent sample mix up and loss. Sample identifi...
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Collection, processing, storage and maintenance of samples to facilitate long-term cohort studies in biobanks, requires a system to manage samples in an effective way to prevent sample mix up and loss. Sample identification and tracking system aims to reserve data on the samples at all the times, hence RFID technology is employed. This technology allows information to be stored on the tags attached to tubes containing samples. A system is proposed, designed and prototype in the Prostate Cancer research Consortium biobank.
We present the dynamic web personalization and document grouping infrastructure for meta-portals and the evaluation of the mechanism on peRSSonal, a system that collects articles from news portals and blogs worldwide....
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We propose a novel optimization-based paradigm for designing enhanced classifiers. The proposed paradigm allows us to incorporate available prior process knowledge into classifier design, thereby improving the perform...
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We propose a novel optimization-based paradigm for designing enhanced classifiers. The proposed paradigm allows us to incorporate available prior process knowledge into classifier design, thereby improving the performance of the resulting classifiers. In this work, we focus on dynamical systems that can be represented as finite-state multi-dimensional stochastic processes that possess labeled steady-state distributions. Given prior operational knowledge of the process, our goal is to build a classifier that can accurately label future observations obtained from the steady-state, by utilizing both the available prior knowledge and the training data. Simulation results show that the proposed paradigm yields improved classifiers that outperform traditional classifiers that use only training data.
This paper deals with the problem of deploying a team of flying robots to perform surveillance coverage missions over a terrain of arbitrary morphology. In such missions, a key factor for the successful completion is ...
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This paper deals with the problem of deploying a team of flying robots to perform surveillance coverage missions over a terrain of arbitrary morphology. In such missions, a key factor for the successful completion is the knowledge of the terrain's morphology. In this paper, we introduce a two-step centralized procedure to align optimally a swarm of flying vehicles for the aforementioned task. Initially, a single robot constructs a map of the area of interest using a novel monocular-vision-based approach. A state-of-the-art visual-SLAM algorithm tracks the pose of the camera while, simultaneously, building an incremental map of the surrounding environment. The map generated is processed and serves as an input in an optimization procedure using the cognitive adaptive methodology initially introduced in [1], [2]. The output of this procedure is the optimal arrangement of the robot team, which maximizes the monitored area. The efficiency of our approach is demonstrated using real data collected from aerial robots in different outdoor areas.
Scheduling in traditional distributed systems has been mainly studied for system performance parameters without data transmission requirements. With the emergence of Data Grids (DGs) and Data Centers, data-aware sched...
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Scheduling in traditional distributed systems has been mainly studied for system performance parameters without data transmission requirements. With the emergence of Data Grids (DGs) and Data Centers, data-aware scheduling has become a major research issue. DGs arise quite naturally to support needs of scientific communities to share, access, process, and manage large data collections geographically distributed. In fact, DGs can be seen as precursors of Data Centers of Cloud Computing platforms, which serve as basis for collaboration at large scale. In such computational infrastructures, the large amount of data to be efficiently processed is a real challenge. One of the key issues contributing to the efficiency of massive processing is the scheduling with data transmission requirements. Data-aware scheduling, although similar in nature with Grid scheduling, is giving rise to the definition of a new family of optimization problems. New requirements such as data transmission, decoupling of data from processing, data replication, data access and security are the basis for the definition of a whole taxonomy of data scheduling problems from an optimization perspective. In this work we present the modelling of such requirements and define data scheduling problems. We exemplify the methodology for the case of data-ware independent batch task scheduling and present several heuristic resolution methods for the problem.
The use of Numerical Control and computers in manufacturing has enabled the development of new sheet forming processes. One of these flexible processes is called Incremental Sheet Forming (ISF) in which deformation is...
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ISBN:
(纸本)9781457708381
The use of Numerical Control and computers in manufacturing has enabled the development of new sheet forming processes. One of these flexible processes is called Incremental Sheet Forming (ISF) in which deformation is localized by the movement of a spherical or flat forming tool. ISF is carried out regularly by a CNC machine tool or by a Robot, which follows a tool-path generated by CAM programs, without the need for costly dies. Despite research progresses in understanding the deformation mechanism in ISF the process still needs a further optimization to guarantee the reliability required for industrial applications. This paper deals with the design of a new smart forming tool, applying FEM modeling and simulation, which is able to measure one of the key process parameters: the sheet thickness during the forming process. The authors analyze the possibility to use a Hall-effect sensor integrated into the forming tool for more precise on-line thickness measurement than what can be found in the literature and first results are reported.
FEC is an error control method that can be used to augment or replace other methods for reliable data transmission. Such schemes inevitably add a constant overhead in the transmitted data. However, they are so simple ...
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