983 resultados para Composite Dynamic Object
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Interactive ray tracing of non-trivial scenes is just becoming feasible on single graphics processing units (GPU). Recent work in this area focuses on building effective acceleration structures, which work well under the constraints of current GPUs. Most approaches are targeted at static scenes and only allow navigation in the virtual scene. So far support for dynamic scenes has not been considered for GPU implementations. We have developed a GPU-based ray tracing system for dynamic scenes consisting of a set of individual objects. Each object may independently move around, but its geometry and topology are static.
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Highly available software systems occasionally need to be updated while avoiding downtime. Dynamic software updates reduce down-time, but still require the system to reach a quiescent state in which a global update can be performed. This can be difficult for multi-threaded systems. We present a novel approach to dynamic updates using first-class contexts, called Theseus. First-class contexts make global updates unnecessary: existing threads run to termination in an old context, while new threads start in a new, updated context; consistency between contexts is ensured with the help of bidirectional transformations. We show that for multi-threaded systems with coherent memory, first-class contexts offer a practical and flexible approach to dynamic updates, with acceptable overhead.
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The present paper is an abridged version of the first chapter to the book EC Electronic Communications and Competition Law (London: Cameron May, 2007). It is intended to pinpoint the contours of the communications sector as an object of regulation - an exercise that is essential to any thoughts on appropriate regulatory design. The communications sector is defined through its salient features of being (i) network-bound; (ii) dynamic; (iii) converging; (iv) sensitive to regulation and society’s reactions; and as one (v) with special societal role and as (vi) part of the new economy.
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OBJECT The authors developed a new mapping technique to overcome the temporal and spatial limitations of classic subcortical mapping of the corticospinal tract (CST). The feasibility and safety of continuous (0.4-2 Hz) and dynamic (at the site of and synchronized with tissue resection) subcortical motor mapping was evaluated. METHODS The authors prospectively studied 69 patients who underwent tumor surgery adjacent to the CST (< 1 cm using diffusion tensor imaging and fiber tracking) with simultaneous subcortical monopolar motor mapping (short train, interstimulus interval 4 msec, pulse duration 500 μsec) and a new acoustic motor evoked potential alarm. Continuous (temporal coverage) and dynamic (spatial coverage) mapping was technically realized by integrating the mapping probe at the tip of a new suction device, with the concept that this device will be in contact with the tissue where the resection is performed. Motor function was assessed 1 day after surgery, at discharge, and at 3 months. RESULTS All procedures were technically successful. There was a 1:1 correlation of motor thresholds for stimulation sites simultaneously mapped with the new suction mapping device and the classic fingerstick probe (24 patients, 74 stimulation points; r(2) = 0.98, p < 0.001). The lowest individual motor thresholds were as follows: > 20 mA, 7 patients; 11-20 mA, 13 patients; 6-10 mA, 8 patients; 4-5 mA, 17 patients; and 1-3 mA, 24 patients. At 3 months, 2 patients (3%) had a persistent postoperative motor deficit, both of which were caused by a vascular injury. No patient had a permanent motor deficit caused by a mechanical injury of the CST. CONCLUSIONS Continuous dynamic mapping was found to be a feasible and ergonomic technique for localizing the exact site of the CST and distance to the motor fibers. The acoustic feedback and the ability to stimulate the tissue continuously and exactly at the site of tissue removal improves the accuracy of mapping, especially at low (< 5 mA) stimulation intensities. This new technique may increase the safety of motor eloquent tumor surgery.
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Until today, most of the documentation of forensic relevant medical findings is limited to traditional 2D photography, 2D conventional radiographs, sketches and verbal description. There are still some limitations of the classic documentation in forensic science especially if a 3D documentation is necessary. The goal of this paper is to demonstrate new 3D real data based geo-metric technology approaches. This paper present approaches to a 3D geo-metric documentation of injuries on the body surface and internal injuries in the living and deceased cases. Using modern imaging methods such as photogrammetry, optical surface and radiological CT/MRI scanning in combination it could be demonstrated that a real, full 3D data based individual documentation of the body surface and internal structures is possible in a non-invasive and non-destructive manner. Using the data merging/fusing and animation possibilities, it is possible to answer reconstructive questions of the dynamic development of patterned injuries (morphologic imprints) and to evaluate the possibility, that they are matchable or linkable to suspected injury-causing instruments. For the first time, to our knowledge, the method of optical and radiological 3D scanning was used to document the forensic relevant injuries of human body in combination with vehicle damages. By this complementary documentation approach, individual forensic real data based analysis and animation were possible linking body injuries to vehicle deformations or damages. These data allow conclusions to be drawn for automobile accident research, optimization of vehicle safety (pedestrian and passenger) and for further development of crash dummies. Real 3D data based documentation opens a new horizon for scientific reconstruction and animation by bringing added value and a real quality improvement in forensic science.
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The effect of MWCNT introduction in a polycarbosilane based ceramic on its electrical properties is presented. The electrical conductivity of two MWCNT powders was measured under dynamic compaction up to 20 MPa when it reached 3–5 S/cm. The compaction behavior was also analyzed and modeled. A composite was then realized using allylhydridopolycarbosilane SMP10® and divinylbenzene as matrix. Intact 10 mm MWCNT-SiC ceramic discs samples with 2 wt.% filler load were produced pressure-less via liquid route despite the linear shrinkage of about 30%. Nanotubes microstructure and distribution in the matrix were confirmed after pyrolysis with TEM and SEM analysis. Anyhow similar electrical conductivity values after pyrolysis between the loaded and unloaded samples were measured. The microstructure analysis via XRD and TEM revealed that the percolative carbon network formed through the use of divinylbenzene improves the electric conductivity more than that of MWCNT addition and also simplifies the whole process.
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The contribution of this article demonstrates how to identify context-aware types of e-Learning objects (eLOs) derived from the subject domains. This perspective is taken from an engineering point of view and is applied during requirements elicitation and analysis relating to present work in constructing an object-oriented (OO), dynamic, and adaptive model to build and deliver packaged e-Learning courses. Consequently, three preliminary subject domains are presented and, as a result, three primitive types of eLOs are posited. These types educed from the subject domains are of structural, conceptual, and granular nature. Structural objects are responsible for the course itself, conceptual objects incorporate adaptive and logical interoperability, while granular objects congregate granular assets. Their differences, interrelationships, and responsibilities are discussed. A major design challenge relates to adaptive behaviour. Future research addresses refinement on the subject domains and adaptive hypermedia systems.
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Abstract Information-centric networking (ICN) offers new perspectives on mobile ad-hoc communication because routing is based on names but not on endpoint identifiers. Since every content object has a unique name and is signed, authentic content can be stored and cached by any node. If connectivity to a content source breaks, it is not necessarily required to build a new path to the same source but content can also be retrieved from a closer node that provides the same content copy. For example, in case of collisions, retransmissions do not need to be performed over the entire path but due to caching only over the link where the collision occurred. Furthermore, multiple requests can be aggregated to improve scalability of wireless multi-hop communication. In this work, we base our investigations on Content-Centric Networking (CCN), which is a popular {ICN} architecture. While related works in wireless {CCN} communication are based on broadcast communication exclusively, we show that this is not needed for efficient mobile ad-hoc communication. With Dynamic Unicast requesters can build unicast paths to content sources after they have been identified via broadcast. We have implemented Dynamic Unicast in CCNx, which provides a reference implementation of the {CCN} concepts, and performed extensive evaluations in diverse mobile scenarios using NS3-DCE, the direct code execution framework for the {NS3} network simulator. Our evaluations show that Dynamic Unicast can result in more efficient communication than broadcast communication, but still supports all {CCN} advantages such as caching, scalability and implicit content discovery.
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A high-resolution stratigraphy is essential toward deciphering climate variability in detail and understanding causality arguments of events in earth history. Because the highly dynamic middle to late Eocene provides a suitable testing ground for carbon cycle models for a waning warm world, an accurate time scale is needed to decode climate-driving mechanisms. Here we present new results from ODP Site 1260 (Leg 207) which covers a unique expanded middle Eocene section (magnetochrons C18r to C20r, late Lutetian to early Bartonian) of the tropical western Atlantic including the chron C19r transient hyperthermal event and the Middle Eocene Climate Optimum (MECO). To establish a detailed cyclostratigraphy we acquired a distinctive iron intensity records by XRF scanning Site 1260 cores. We revise the shipboard composite section, establish a cyclostratigraphy and use the exceptional eccentricity modulated precession cycles for orbital tuning. The new astrochronology revises the age of magnetic polarity chrons C19n to C20n, validates the position of very long eccentricity minima at 40.2 and 43.0 Ma in the orbital solutions, and extends the Astronomically Tuned Geological Time Scale back to 44 Ma. For the first time the new data provide clear evidence for an orbital pacing of the chron C19r event and a likely involvement of the very long eccentricity cycle contributing to the evolution of the MECO.
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AUTOFLY-Aid Project aims to develop and demonstrate novel automation support algorithms and tools to the flight crew for flight critical collision avoidance using “dynamic 4D trajectory management”. The automation support system is envisioned to improve the primary shortcomings of TCAS, and to aid the pilot through add-on avionics/head-up displays and reality augmentation devices in dynamically evolving collision avoidance scenarios. The main theoretical innovative and novel concepts to be developed by AUTOFLY-Aid project are a) design and development of the mathematical models of the full composite airspace picture from the flight deck’s perspective, as seen/measured/informed by the aircraft flying in SESAR 2020, b) design and development of a dynamic trajectory planning algorithm that can generate at real-time (on the order of seconds) flyable (i.e. dynamically and performance-wise feasible) alternative trajectories across the evolving stochastic composite airspace picture (which includes new conflicts, blunder risks, terrain and weather limitations) and c) development and testing of the Collision Avoidance Automation Support System on a Boeing 737 NG FNPT II Flight Simulator with synthetic vision and reality augmentation while providing the flight crew with quantified and visual understanding of collision risks in terms of time and directions and countermeasures.
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Despite that Critical Infrastructures (CIs) security and surveillance are a growing concern for many countries and companies, Multi Robot Systems (MRSs) have not been yet broadly used in this type of facilities. This dissertation presents a novel study of the challenges arisen by the implementation of this type of systems and proposes solutions to specific problems. First, a comprehensive analysis of different types of CIs has been carried out, emphasizing the influence of the different characteristics of the facilities in the design of a security and surveillance MRS. One of the most important needs for the surveillance of a CI is the detection of intruders. From a technical point of view this problem can be abstracted as equivalent to the Detection and Tracking of Mobile Objects (DATMO). This dissertation proposes algorithms to solve this specific problem in a CI environment. Using 3D range images of the environment as input data, two detection algorithms for ground robots have been developed. These detection algorithms provide a list of moving objects in the robot detection area. Direct image differentiation and computer vision techniques are used when the robot is static. Alternatively, multi-layer ground reconstructions are compared to detect the dynamic objects when the robot is moving. Since CIs usually spread over large areas, it is very useful to incorporate aerial vehicles in the surveillance MRS. Therefore, a moving object detection algorithm for aerial vehicles has been also developed. This algorithm compares the real optical flow obtained from a down-face oriented camera with an artificial optical flow computed using a RANSAC based homography matrix. Two tracking algorithms have been developed to follow the moving objects trajectories. These algorithms can efficiently handle occlusions and crossings, as well as exchange information among robots. The multirobot tracking can be applied to any type of communication structure: centralized, decentralized or a combination of both. Even more, the developed tracking algorithms are independent of the detection algorithms and could be potentially used with other detection procedures or even with static sensors, such as cameras. In addition, using the 3D point clouds available to the robots, a relative localization algorithm has been developed to improve the position estimation of a given robot with observations from other robots. All the developed algorithms have been extensively tested in different simulated CIs using the Webots robotics simulator. Furthermore, the algorithms have also been validated with real robots operating in real scenarios. In conclusion, this dissertation presents a multirobot approach to Critical Infrastructure Surveillance, mainly focusing on Detecting and Tracking Dynamic Objects.
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Dynamic measurements will become a standard for bridge monitoring in the near future. This fact will produce an important cost reduction for maintenance. US Administration has a long term intensive research program in order to diminish the estimated current maintenance cost of US$7 billion per year over 20 years. An optimal intervention maintenance program demands a historical dynamical record, as well as an updated mathematical model of the structure to be monitored. In case that a model of the structure is not actually available it is possible to produce it, however this possibility does not exist for missing measurement records from the past. Current acquisition systems to monitor structures can be made more efficient by introducing the following improvements, under development in the Spanish research Project “Low cost bridge health monitoring by ambient vibration tests using wireless sensors”: (a) a complete wireless system to acquire sensor data, (b) a wireless system that permits the localization and the hardware identification of the whole sensor system. The applied localization system has been object of a recent patent, and (c) automatization of the modal identification process, aimed to diminish human intervention. This system is assembled with cheap components and allows the simultaneous use of a large number of sensors at a low placement cost. The engineer’s intervention is limited to the selection of sensor positions, probably based on a preliminary FE analysis. In case of multiple setups, also the position of a number of fixed reference sensors has to be decided. The wireless localization system will obtain the exact coordinates of all these sensors positions. When the selection of optimal positions is difficult, for example because of the lack of a proper FE model, this can be compensated by using a higher number of measuring (also reference) points. The described low cost acquisition system allows the responsible bridge administration to obtain historical dynamic identification records at reasonable costs that will be used in future maintenance programs. Therefore, due to the importance of the baseline monitoring record of a new bridge, a monitoring test just after its construction should be highly recommended, if not compulsory.
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The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.
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This paper is part of a set of publications related with the development of mathematical models aimed to simulate the dynamic input and output of experimental nondestructive tests in order to detect structural imperfections. The structures to be considered are composed by steel plates of thin thickness. The imperfections in these cases are cracks and they can penetrate either a significant part of the plate thickness or be micro cracks or superficial imperfections. The first class of cracks is related with structural safety and the second one is more connected to the structural protection to the environment, particularly if protective paintings can be deteriorated. Two mathematical groups of models have been developed. The first group tries to locate the position and extension of the imperfection of the first class of imperfections, i.e. cracks and it is the object of the present paper. Bending Kirchoff thin plate models belong to this first group and they are used to this respect. The another group of models is dealt with membrane structures under the superficial Rayleigh waves excitation. With this group of models the micro cracks detection is intended. In the application of the first group of models to the detection of cracks, it has been observed that the differences between the natural frequencies of the non cracked and the cracked structures are very small. However, geometry and crack position can be identified quite accurately if this comparison is carried out between first derivatives (mode rotations) of the natural modes are used instead. Finally, in relation with the analysis of the superficial crack existence the use of Rayleigh waves is very promising. The geometry and the penetration of the micro crack can be detected very accurately. The mathematical and numerical treatment of the generation of these Rayleigh waves present and a numerical application has been shown.
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Tactile sensors play an important role in robotics manipulation to perform dexterous and complex tasks. This paper presents a novel control framework to perform dexterous manipulation with multi-fingered robotic hands using feedback data from tactile and visual sensors. This control framework permits the definition of new visual controllers which allow the path tracking of the object motion taking into account both the dynamics model of the robot hand and the grasping force of the fingertips under a hybrid control scheme. In addition, the proposed general method employs optimal control to obtain the desired behaviour in the joint space of the fingers based on an indicated cost function which determines how the control effort is distributed over the joints of the robotic hand. Finally, authors show experimental verifications on a real robotic manipulation system for some of the controllers derived from the control framework.