Characterization And Emulation Of Low Voltage Power Line Channels For Narrowband And Broadband Communication

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Characterization And Emulation Of Low Voltage Power Line Channels For Narrowband And Broadband Communication

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Author : Han, Bin
language : en
Publisher: KIT Scientific Publishing
Release Date : 2017-06-06

Characterization And Emulation Of Low Voltage Power Line Channels For Narrowband And Broadband Communication written by Han, Bin and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-06 with Technology (General) categories.

The demand for smart grid and smart home applications has raised the recent interest in power line communication (PLC) technologies, and has driven a broad set of deep surveys in low-voltage (LV) power line channels. This book proposes a set of novel approaches, to characterize and to emulate LV power line channels in the frequency range from0.15to 10 MHz, which closes gaps between the traditional narrowband (up to 500 kHz) and broadband (above1.8 MHz) ranges.

Characterization And Emulation Of Low Voltage Power Line Channels For Narrowband And Broadband Communication

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Author : Bin Han
language : en
Publisher:
Release Date : 2020-10-09

Characterization And Emulation Of Low Voltage Power Line Channels For Narrowband And Broadband Communication written by Bin Han and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-09 with Computers categories.

The demand for smart grid and smart home applications has raised the recent interest in power line communication (PLC) technologies, and has driven a broad set of deep surveys in low-voltage (LV) power line channels. This book proposes a set of novel approaches, to characterize and to emulate LV power line channels in the frequency range from0.15to 10 MHz, which closes gaps between the traditional narrowband (up to 500 kHz) and broadband (above1.8 MHz) ranges. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Design And Analysis Of A Content Based Image Retrieval System

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Author : Hernández Mesa, Pilar
language : en
Publisher: KIT Scientific Publishing
Release Date : 2017-10-18

Design And Analysis Of A Content Based Image Retrieval System written by Hernández Mesa, Pilar and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-18 with Technology (General) categories.

The automatic retrieval of images according to the similarity of their content is a challenging task with many application fields. In this book the automatic retrieval of images according to human spontaneous perception without further effort or knowledge is considered. A system is therefore designed and analyzed. Methods for the detection and extraction of regions and for the extraction and comparison of color, shape, and texture features are also investigated.

Driver Behavior Analysis And Decision Making For Autonomous Driving At Non Signalized Inner City Intersections

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Author : Weinreuter, Hannes
language : en
Publisher: KIT Scientific Publishing
Release Date : 2025-01-17

Driver Behavior Analysis And Decision Making For Autonomous Driving At Non Signalized Inner City Intersections written by Weinreuter, Hannes and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-17 with categories.

The focus of this work is on human driving behavior in road traffic. Two aspects of it are covered, the prediction of it, including the identification of relevant influencing factors, as well as the behavior generation for autonomous vehicles. The behavior prediction is based on a field study during which participants drove a measurement vehicle through inner-city traffic. Using the driven trajectories and lidar recordings complexity features to describe the surroundings at the intersection, the traffic there and the driving path are defined. The driving behavior is characterized by further features. Based on the complexity features regression models are trained to predict the behavior features. For that, linear regression, random forest and gradient boosting machine are utilized. Different complexity feature sets, including ones that are reduced with the help of an autoencoder, are used for prediction. The results show that the driving behavior can be predicted reliably. However, when using complexity feature sets with only few features the prediction performance is reduced. In order to obtain a complexity score that is in line with human perception of complexity, an online study using videos of approaches to intersections was conducted. In pairwise comparisons participants were asked to identify the more complex situation. From that data complexity scores for the intersection passes included in the study are calculated. Several methods are used to assign these scores to the runs of the original field study. Behavior regression models are trained using these assigned complexity scores. The results show that behavior prediction with the complexity scores is possible, however, most variants require to also consider the turning direction as a second feature. The behavior generation for decision-making at T-intersections is based on a discrete event system (DES). For it, several features are used to define events that describe the status of the decision-making process at the intersection. The events trigger the transitions between the states of the DES. All states are associated with either offensive or defensive driving behavior, which is implemented using the intelligent driver model. The algorithm is validated with a simulation framework. Using a generic map and several real maps, the decision-making model is simulated 14400 times while interacting with further cooperation vehicles. None of these runs resulted in a collision involving the vehicle running the algorithm and the times to pass the intersection can be explained by the numbers of cooperation vehicles and the intersection layouts. Further simulations are used to investigate the influence of limited visibility at the intersections on the model.

Wireless Data Transmission For The Battery Management System Of Electric And Hybrid Vehicles

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Author : Alonso, Damián Ezequiel
language : en
Publisher: KIT Scientific Publishing
Release Date : 2017-09-15

Wireless Data Transmission For The Battery Management System Of Electric And Hybrid Vehicles written by Alonso, Damián Ezequiel and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-15 with Technology (General) categories.

This work introduces a novel wireless approach for the data transmission within automotive battery management systems. The main target is the reduction of the wiring harness deployed in a battery. The characteristics of the wireless in-battery channel are investigated by means of measurements and software-based electromagnetic simulations. Different types of antennas and frequency bands are analyzed. The performance of the proposed system is evaluated by means of simulations and prototypes.

Reconstruction From Spatio Spectrally Coded Multispectral Light Fields

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Author : Schambach, Maximilian
language : en
Publisher: KIT Scientific Publishing
Release Date : 2022-10-17

Reconstruction From Spatio Spectrally Coded Multispectral Light Fields written by Schambach, Maximilian and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-17 with Technology & Engineering categories.

In dieser Arbeit werden spektral kodierte multispektrale Lichtfelder untersucht, wie sie von einer Lichtfeldkamera mit einem spektral kodierten Mikrolinsenarray aufgenommen werden. Für die Rekonstruktion der kodierten Lichtfelder werden zwei Methoden entwickelt, eine basierend auf den Prinzipien des Compressed Sensing sowie eine Deep Learning Methode. Anhand neuartiger synthetischer und realer Datensätze werden die vorgeschlagenen Rekonstruktionsansätze im Detail evaluiert. -In this work, spatio-spectrally coded multispectral light fields, as taken by a light field camera with a spectrally coded microlens array, are investigated. For the reconstruction of the coded light fields, two methods, one based on the principles of compressed sensing and one deep learning approach, are developed. Using novel synthetic as well as a real-world datasets, the proposed reconstruction approaches are evaluated in detail.

Machine Learning For Camera Based Monitoring Of Laser Welding Processes

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Author : Hartung, Julia
language : en
Publisher: KIT Scientific Publishing
Release Date : 2024-03-08

Machine Learning For Camera Based Monitoring Of Laser Welding Processes written by Hartung, Julia and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-08 with categories.

The increasing use of automated laser welding processes causes high demands on process monitoring. This work demonstrates methods that use a camera mounted on the focussing optics to perform pre-, in-, and post-process monitoring of welding processes. The implementation uses machine learning methods. All algorithms consider the integration into industrial processes. These challenges include a small database, limited industrial manufacturing inference hardware, and user acceptance.

Hyperspectral Image Unmixing Incorporating Adjacency Information

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Author : Bauer, Sebastian
language : en
Publisher: KIT Scientific Publishing
Release Date : 2018-07-18

Hyperspectral Image Unmixing Incorporating Adjacency Information written by Bauer, Sebastian and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-18 with Technology & Engineering categories.

While the spectral information contained in hyperspectral images is rich, the spatial resolution of such images is in many cases very low. Many pixel spectra are mixtures of pure materials' spectra and therefore need to be decomposed into their constituents. This work investigates new decomposition methods taking into account spectral, spatial and global 3D adjacency information. This allows for faster and more accurate decomposition results.

Light Field Imaging For Deflectometry

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Author : Uhlig, David
language : en
Publisher: KIT Scientific Publishing
Release Date : 2023-07-14

Light Field Imaging For Deflectometry written by Uhlig, David and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-14 with categories.

Optical measurement methods are becoming increasingly important for high-precision production of components and quality assurance. The increasing demand can be met by modern imaging systems with advanced optics, such as light field cameras. This work explores their use in the deflectometric measurement of specular surfaces. It presents improvements in phase unwrapping and calibration techniques, enabling high surface reconstruction accuracies using only a single monocular light field camera.

Probabilistic Models And Inference For Multi View People Detection In Overlapping Depth Images

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Author : Wetzel, Johannes
language : en
Publisher: KIT Scientific Publishing
Release Date : 2022-07-12

Probabilistic Models And Inference For Multi View People Detection In Overlapping Depth Images written by Wetzel, Johannes and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-12 with Technology & Engineering categories.

In this work, the task of wide-area indoor people detection in a network of depth sensors is examined. In particular, we investigate how the redundant and complementary multi-view information, including the temporal context, can be jointly leveraged to improve the detection performance. We recast the problem of multi-view people detection in overlapping depth images as an inverse problem and present a generative probabilistic framework to jointly exploit the temporal multi-view image evidence.