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Identifying and Harnessing Concurrency for Parallel and Distributed Network Simulation

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ISBN: 9783731505112 Year: Pages: XI, 147 p. DOI: 10.5445/KSP/1000054019 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:02:00
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Although computer networks are inherently parallel systems, the parallel execution of network simulations on interconnected processors frequently yields only limited benefits. In this thesis, methods are proposed to estimate and understand the parallelization potential of network simulations. Further, mechanisms and architectures for exploiting the massively parallel processing resources of modern graphics cards to accelerate network simulations are proposed and evaluated.

Real-time Biomechanical Modeling for Intraoperative Soft Tissue Registration

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ISBN: 9783731503736 Year: Pages: 239 p. DOI: 10.5445/KSP/1000046886 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:01:58
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Computer assisted surgery systems intraoperatively support the surgeon by providing information on the location of hidden risk and target structures during surgery. However, soft tissue deformations make intraoperative registration (and thus intraoperative navigation) difficult. In this work, a novel, biomechanics based approach for real-time soft tissue registration from sparse intraoperative sensor data such as stereo endoscopic images is presented to overcome this problem.

Dynamiksimulation in der Computergraphik

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ISBN: 9783731502043 Year: Pages: IV, 255 p. DOI: 10.5445/KSP/1000040123 Language: GERMAN
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:02:00
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Interactive physically-based simulation of rigid bodies and deformable solids is an important and active research topic in computer graphics as well as an essential part of many applications like virtual prototyping, computer games or training simulators. This work presents interactive simulation methods for multi-body systems, cloth and incompressible deformable solids. Furthermore, GPU-based methods are introduced which accelerate the simulation significantly.

Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)

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ISBN: 9783039213757 / 9783039213764 Year: Pages: 344 DOI: 10.3390/books978-3-03921-376-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
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This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR

Keywords

Vehicle-to-X communications --- Intelligent Transport Systems --- VANET --- DSRC --- Geobroadcast --- multi-sensor --- fusion --- deep learning --- LiDAR --- camera --- ADAS --- object tracking --- kernel based MIL algorithm --- Gaussian kernel --- adaptive classifier updating --- perception in challenging conditions --- obstacle detection and classification --- dynamic path-planning algorithms --- joystick --- two-wheeled --- terrestrial vehicle --- path planning --- infinity norm --- p-norm --- kinematic control --- navigation --- actuation systems --- maneuver algorithm --- automated driving --- cooperative systems --- communications --- interface --- automated-manual transition --- driver monitoring --- visual tracking --- discriminative correlation filter bank --- occlusion --- sub-region --- global region --- autonomous vehicles --- driving decision-making model --- the emergency situations --- red light-running behaviors --- ethical and legal factors --- T-S fuzzy neural network --- road lane detection --- map generation --- driving assistance --- autonomous driving --- real-time object detection --- autonomous driving assistance system --- urban object detector --- convolutional neural networks --- machine vision --- biological vision --- deep learning --- convolutional neural network --- Gabor convolution kernel --- recurrent neural network --- enhanced learning --- autonomous vehicle --- crash injury severity prediction --- support vector machine model --- emergency decisions --- relative speed --- total vehicle mass of the front vehicle --- perception in challenging conditions --- obstacle detection and classification --- dynamic path-planning algorithms --- drowsiness detection --- smart band --- electrocardiogram (ECG) --- photoplethysmogram (PPG) --- recurrence plot (RP) --- convolutional neural network (CNN) --- squeeze-and-excitation --- residual learning --- depthwise separable convolution --- blind spot detection --- machine learning --- neural networks --- predictive --- vehicle dynamics --- electric vehicles --- FPGA --- GPU --- parallel architectures --- optimization --- panoramic image dataset --- road scene --- object detection --- deep learning --- convolutional neural network --- driverless --- autopilot --- deep leaning --- object detection --- generative adversarial nets --- image inpainting --- n/a

Machining—Recent Advances, Applications and Challenges

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ISBN: 9783039213771 / 9783039213788 Year: Pages: 554 DOI: 10.3390/books978-3-03921-378-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 16:10:12
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The Special Issue Machining—Recent Advances, Applications and Challenges is intended as a humble collection of some of the hottest topics in machining. The manufacturing industry is a varying and challenging environment where new advances emerge from one day to another. In recent years, new manufacturing procedures have retained increasing attention from the industrial and scientific community. However, machining still remains the key operation to achieve high productivity and precision for high-added value parts. Continuous research is performed, and new ideas are constantly considered. This Special Issue summarizes selected high-quality papers which were submitted, peer-reviewed, and recommended by experts. It covers some (but not only) of the following topics: High performance operations for difficult-to-cut alloys, wrought and cast materials, light alloys, ceramics, etc.; Cutting tools, grades, substrates and coatings. Wear damage; Advanced cooling in machining: Minimum quantity of lubricant, dry or cryogenics; Modelling, focused on the reduction of risks, the process outcome, and to maintain surface integrity; Vibration problems in machines: Active and passive/predictive methods, sources, diagnosis and avoidance; Influence of machining in new concepts of machine–tool, and machine static and dynamic behaviors; Machinability of new composites, brittle and emerging materials; Assisted machining processes by high-pressure, laser, US, and others; Introduction of new analytics and decision making into machining programming. We wish to thank the reviewers and staff from Materials for their comments, advice, suggestions and invaluable support during the development of this Special Issue.

Keywords

dry-cutting --- concrete --- segmented diamond blade --- topography --- diameter variation --- weight loss --- in situ estimation --- SACE-drilled hole depth --- spark-assisted chemical engraving --- glass machining --- computer vision --- electrochemical discharge machining --- butt weld joint --- fatigue --- crack growth rate --- weld reinforcement --- cooling rate --- artificial neutral network --- cutting parameters --- magnesium alloys --- optimization --- prime machining costs --- surface roughness --- electropulsing --- machinability --- chip compression ratio --- current density --- specific cutting energy --- cutting edge microgeometry --- residual stress --- finite element model --- cutting edge preparation --- Inconel 718 --- stiffness properties --- parameter identification --- connections --- machine tool --- response surface methodology --- design of experiments --- modal testing --- plastic zone --- fracture mechanism --- steel sheet --- cutting process --- Huber–Mises stress --- finite element method --- microscopic analysis --- PVD Ti0.41Al0.59N/Ti0.55Al0.45N coating --- cutting temperature --- Inconel 718 --- cutting tool wear --- secondary adhesion wear --- turning --- machining --- aluminium --- flank super abrasive machining (SAM) --- flank milling --- Inconel® 718 --- roughness --- residual stress --- machine vision --- on-machine monitoring --- tool insert condition --- computer numerical control --- turning machine tools --- multi-beam laser --- heat transfer analysis --- fast simulation --- GPU --- analytic solution --- minimum quantity lubrication --- surface grinding --- multi-objective optimization --- grey relational analysis --- surface topography --- sustainable machining --- Gamma-TiAl --- superalloys --- slight materials --- drilling --- titanium aluminides --- additive manufacturing --- single point incremental sheet forming --- residual stresses --- X-ray diffraction --- ultra-precision machining --- slow tool servo --- surface topography --- simulation --- microlens array --- sinusoidal grid --- Milling stability --- variable pitch --- chatter --- self-excitation --- milling --- ceramics --- ductile machining --- PCD --- corner radius --- material removal rate --- adhesive --- machining --- modelling --- dry --- CFRP/UNS A92024 --- induction assisted milling --- tool wear --- taguchi method --- cutting tool --- machining temperatures at two deformation zones --- force–temperature correlation through analytical modeling --- high computational efficiency --- real-time prediction --- hybrid stacks drilling --- minimum quantity lubrication --- hole quality --- tool wear --- WEDM --- EN 31 steel --- surface roughness --- fractal dimension --- ANN --- GA --- cryogenic machining --- cutting tool --- cutting geometry --- titanium --- power consumption --- material-removal rate --- specific energy consumption --- grain density --- modeling --- shape memory alloy --- superelastic nitinol --- WEDM --- heat transfer search algorithm --- DSC test --- shape memory effect --- dish angle --- trochoidal step --- response surface methodology --- surface roughness --- desirability approach --- tool wear --- trochoidal milling --- titanium alloy --- chip morphology --- thin-wall machining --- chatter --- vibration --- deflection --- damping --- prediction --- workholding --- fixture --- dynamic --- stability --- titanium alloys --- machining --- turning --- machinability --- tool wear --- laser-assisted machining --- Taguchi method --- optimal machining conditions --- machining characteristic --- milling --- the cutting force components --- vibrations --- magnesium alloys --- artificial neural networks

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