78 research outputs found
Generalized Sparse Convolutional Neural Networks for Semantic Segmentation of Point Clouds Derived from Tri-Stereo Satellite Imagery
We studied the applicability of point clouds derived from tri-stereo satellite imagery for
semantic segmentation for generalized sparse convolutional neural networks by the example of
an Austrian study area. We examined, in particular, if the distorted geometric information, in addition
to color, influences the performance of segmenting clutter, roads, buildings, trees, and vehicles. In this
regard, we trained a fully convolutional neural network that uses generalized sparse convolution
one time solely on 3D geometric information (i.e., 3D point cloud derived by dense image matching),
and twice on 3D geometric as well as color information. In the first experiment, we did not use
class weights, whereas in the second we did. We compared the results with a fully convolutional
neural network that was trained on a 2D orthophoto, and a decision tree that was once trained on
hand-crafted 3D geometric features, and once trained on hand-crafted 3D geometric as well as color
features. The decision tree using hand-crafted features has been successfully applied to aerial laser
scanning data in the literature. Hence, we compared our main interest of study, a representation
learning technique, with another representation learning technique, and a non-representation learning
technique. Our study area is located in Waldviertel, a region in Lower Austria. The territory is
a hilly region covered mainly by forests, agriculture, and grasslands. Our classes of interest are heavily
unbalanced. However, we did not use any data augmentation techniques to counter overfitting. For our
study area, we reported that geometric and color information only improves the performance of the
Generalized Sparse Convolutional Neural Network (GSCNN) on the dominant class, which leads to a
higher overall performance in our case. We also found that training the network with median class
weighting partially reverts the effects of adding color. The network also started to learn the classes
with lower occurrences. The fully convolutional neural network that was trained on the 2D orthophoto
generally outperforms the other two with a kappa score of over 90% and an average per class accuracy
of 61%. However, the decision tree trained on colors and hand-crafted geometric features has a 2%
higher accuracy for roads
原子力プラントのライフサイクル情報管理に基づく廃炉シミュレーションに関する研究
Tohoku University博士(情報科学)thesi
Advances in Grid Computing
This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems
Earth Observation Open Science and Innovation
geospatial analytics; social observatory; big earth data; open data; citizen science; open innovation; earth system science; crowdsourced geospatial data; citizen science; science in society; data scienc
Applying Hypervisor-Based Fault Tolerance Techniques to Safety-Critical Embedded Systems
This document details the work conducted through the development of this thesis, and it
is structured as follows:
• Chapter 1, Introduction, has briefly presented the motivation, objectives, and contributions
of this thesis.
• Chapter 2, Fundamentals, exposes a series of concepts that are necessary to correctly
understand the information presented in the rest of the thesis, such as the
concepts of virtualization, hypervisors, or software-based fault tolerance. In addition,
this chapter includes an exhaustive review and comparison between the different
hypervisors used in scientific studies dealing with safety-critical systems, and a
brief review of some works that try to improve fault tolerance in the hypervisor itself,
an area of research that is outside the scope of this work, but that complements
the mechanism presented and could be established as a line of future work.
• Chapter 3, Problem Statement and Related Work, explains the main reasons why
the concept of Hypervisor-Based Fault Tolerance was born and reviews the main
articles and research papers on the subject. This review includes both papers related
to safety-critical embedded systems (such as the research carried out in this thesis)
and papers related to cloud servers and cluster computing that, although not directly
applicable to embedded systems, may raise useful concepts that make our solution
more complete or allow us to establish future lines of work.
• Chapter 4, Proposed Solution, begins with a brief comparison of the work presented
in Chapter 3 to establish the requirements that our solution must meet in order to
be as complete and innovative as possible. It then sets out the architecture of the
proposed solution and explains in detail the two main elements of the solution: the
Voter and the Health Monitoring partition.
• Chapter 5, Prototype, explains in detail the prototyping of the proposed solution,
including the choice of the hypervisor, the processing board, and the critical functionality
to be redundant. With respect to the voter, it includes prototypes for both
the software version (the voter is implemented in a virtual machine) and the hardware
version (the voter is implemented as IP cores on the FPGA).
• Chapter 6, Evaluation, includes the evaluation of the prototype developed in Chapter
5. As a preliminary step and given that there is no evidence in this regard, an
exercise is carried out to measure the overhead involved in using the XtratuM hypervisor
versus not using it. Subsequently, qualitative tests are carried out to check that
Health Monitoring is working as expected and a fault injection campaign is carried
out to check the error detection and correction rate of our solution. Finally, a comparison
is made between the performance of the hardware and software versions of
Voter.
• Chapter 7, Conclusions and Future Work, is dedicated to collect the conclusions
obtained and the contributions made during the research (in the form of articles in
journals, conferences and contributions to projects and proposals in the industry).
In addition, it establishes some lines of future work that could complete and extend
the research carried out during this doctoral thesis.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: Katzalin Olcoz Herrero.- Secretario: Félix García Carballeira.- Vocal: Santiago Rodríguez de la Fuent
Space station data system analysis/architecture study. Task 2: Options development DR-5. Volume 1: Technology options
The second task in the Space Station Data System (SSDS) Analysis/Architecture Study is the development of an information base that will support the conduct of trade studies and provide sufficient data to make key design/programmatic decisions. This volume identifies the preferred options in the technology category and characterizes these options with respect to performance attributes, constraints, cost, and risk. The technology category includes advanced materials, processes, and techniques that can be used to enhance the implementation of SSDS design structures. The specific areas discussed are mass storage, including space and round on-line storage and off-line storage; man/machine interface; data processing hardware, including flight computers and advanced/fault tolerant computer architectures; and software, including data compression algorithms, on-board high level languages, and software tools. Also discussed are artificial intelligence applications and hard-wire communications
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