10,229 research outputs found
Simulator verification techniques study. Integrated simulator self test system concepts
Software and hardware requirements for implementing hardware self tests are presented in support of the development of training and procedures development simulators for the space shuttle program. Self test techniques for simulation hardware and the validation of simulation performance are stipulated. The requirements of an integrated simulator self system are analyzed. Readiness tests, fault isolation tests, and incipient fault detection tests are covered
Breaking a secure communication scheme based on the phase synchronization of chaotic systems
A security analysis of a recently proposed secure communication scheme based
on the phase synchronization of chaotic systems is presented. It is shown that
the system parameters directly determine the ciphertext waveform, hence it can
be readily broken by parameter estimation of the ciphertext signal.Comment: 4 pages, 6 figure
Life As I Know It: My Story Told Through Poetry
This is a collection of poems and prose pieces, that cover love, loss, and everything in between
Deep Projective 3D Semantic Segmentation
Semantic segmentation of 3D point clouds is a challenging problem with
numerous real-world applications. While deep learning has revolutionized the
field of image semantic segmentation, its impact on point cloud data has been
limited so far. Recent attempts, based on 3D deep learning approaches
(3D-CNNs), have achieved below-expected results. Such methods require
voxelizations of the underlying point cloud data, leading to decreased spatial
resolution and increased memory consumption. Additionally, 3D-CNNs greatly
suffer from the limited availability of annotated datasets.
In this paper, we propose an alternative framework that avoids the
limitations of 3D-CNNs. Instead of directly solving the problem in 3D, we first
project the point cloud onto a set of synthetic 2D-images. These images are
then used as input to a 2D-CNN, designed for semantic segmentation. Finally,
the obtained prediction scores are re-projected to the point cloud to obtain
the segmentation results. We further investigate the impact of multiple
modalities, such as color, depth and surface normals, in a multi-stream network
architecture. Experiments are performed on the recent Semantic3D dataset. Our
approach sets a new state-of-the-art by achieving a relative gain of 7.9 %,
compared to the previous best approach.Comment: Submitted to CAIP 201
Efficient Algorithms for Asymptotic Bounds on Termination Time in VASS
Vector Addition Systems with States (VASS) provide a well-known and
fundamental model for the analysis of concurrent processes, parameterized
systems, and are also used as abstract models of programs in resource bound
analysis. In this paper we study the problem of obtaining asymptotic bounds on
the termination time of a given VASS. In particular, we focus on the
practically important case of obtaining polynomial bounds on termination time.
Our main contributions are as follows: First, we present a polynomial-time
algorithm for deciding whether a given VASS has a linear asymptotic complexity.
We also show that if the complexity of a VASS is not linear, it is at least
quadratic. Second, we classify VASS according to quantitative properties of
their cycles. We show that certain singularities in these properties are the
key reason for non-polynomial asymptotic complexity of VASS. In absence of
singularities, we show that the asymptotic complexity is always polynomial and
of the form , for some integer , where is the
dimension of the VASS. We present a polynomial-time algorithm computing the
optimal . For general VASS, the same algorithm, which is based on a complete
technique for the construction of ranking functions in VASS, produces a valid
lower bound, i.e., a such that the termination complexity is .
Our results are based on new insights into the geometry of VASS dynamics, which
hold the potential for further applicability to VASS analysis.Comment: arXiv admin note: text overlap with arXiv:1708.0925
South Dakota Low Income Families and Migration
Generally, a high proportion of out-migrants are believed to be persons who leave because of limited economic opportunities in the State for the skilled, the educated, underemployed or the employed members of the labor force. Often, underemployed and the unemployed are members of disadvantaged families; that is, families characterized by income levels not adequate to provide minimum living standards. Consequently, it is believed that areas of a rural state with extensive concentrations of poverty level families may be areas of low employment opportunities, and consequently areas of high out-migration. For this study, poverty level families are those households with incomes below poverty level, as defined by the United States Bureau of the Census. Primarily, income is the major determinant of poverty status; however, the specified income minimums vary according to rural-urban residency, marital status, and number of dependents. Table 1 shows typical poverty levels by household and residence. Poverty level families are of ten referred to as disadvantaged families, and counties or households with high levels of poverty are referred to as areas or units of disadvantagement
Restructurable Controls
Restructurable control system theory, robust reconfiguration for high reliability and survivability for advanced aircraft, restructurable controls problem definition and research, experimentation, system identification methods applied to aircraft, a self-repairing digital flight control system, and state-of-the-art theory application are addressed
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