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

L'anhelat somni d'una nit d'hivern

Abstract not availabl

Un magnànim Alexandre

Abstract not availabl

Una feliç família de pingüins

Abstract not availabl

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 $\Theta(n^k)$, for some integer $k\leq d$, where $d$ is the dimension of the VASS. We present a polynomial-time algorithm computing the optimal $k$. 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 $k$ such that the termination complexity is $\Omega(n^k)$. 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