New neighborhood based rough sets

Neighborhood based rough sets are important generalizations of the classical rough sets of Pawlak, as neighborhood operators generalize equivalence classes. In this article, we introduce nine neighborhood based operators and we study the partial order relations between twenty-two different neighborhood operators obtained from one covering. Seven neighborhood operators result in new rough set approximation operators. We study how these operators are related to the other fifteen neighborhood based approximation operators in terms of partial order relations, as well as to seven non-neighborhood-based rough set approximation operators

Next Generation NASA Hazard Detection System Development

The SPLICE project is continuing NASAs efforts to develop precision landing GN&C technologies for future lander missions. One of those technologies is the next generation Hazard Detection (HD) System, which consists of a new HD Lidar and HD Algorithms. The HD System is a modular system that will be adapted to meet specific mission needs in the future. This paper presents the design approach, the nominal concept of operations for which the first prototype is being designed, and the expected performance of the system

Stochastic Stokes' drift of a flexible dumbbell

We consider the stochastic Stokes drift of a flexible dumbbell. The dumbbell consists of two isotropic Brownian particles connected by a linear spring with zero natural length, and is advected by a sinusoidal wave. We find an asymptotic approximation for the Stokes drift in the limit of a weak wave, and find good agreement with the results of a Monte Carlo simulation. We show that it is possible to use this effect to sort particles by their flexibility even when all the particles have the same diffusivity.Comment: 12 pages, 1 figur

Open-Loop Flight Testing of COBALT GN&C Technologies for Precise Soft Landing

A terrestrial, open-loop (OL) flight test campaign of the NASA COBALT (CoOperative Blending of Autonomous Landing Technologies) platform was conducted onboard the Masten Xodiac suborbital rocket testbed, with support through the NASA Advanced Exploration Systems (AES), Game Changing Development (GCD), and Flight Opportunities (FO) Programs. The COBALT platform integrates NASA Guidance, Navigation and Control (GN&C) sensing technologies for autonomous, precise soft landing, including the Navigation Doppler Lidar (NDL) velocity and range sensor and the Lander Vision System (LVS) Terrain Relative Navigation (TRN) system. A specialized navigation filter running onboard COBALT fuzes the NDL and LVS data in real time to produce a precise navigation solution that is independent of the Global Positioning System (GPS) and suitable for future, autonomous planetary landing systems. The OL campaign tested COBALT as a passive payload, with COBALT data collection and filter execution, but with the Xodiac vehicle Guidance and Control (G&C) loops closed on a Masten GPS-based navigation solution. The OL test was performed as a risk reduction activity in preparation for an upcoming 2017 closed-loop (CL) flight campaign in which Xodiac G&C will act on the COBALT navigation solution and the GPS-based navigation will serve only as a backup monitor

NASA SPLICE Project: Development and Testing of Precision Landing GN&C Technologies

NASA's technology advancement needs for entry, descent and landing call for high-precision, high-rate sensors that can improve navigation accuracy and vehicle control performance. Higher landing accuracy is required for any future human lander missions, and likely, for most robotic missions 1,2. Sensors and algorithms that significantly reduce navigation errors and can image the local terrain will enable landing at locations of high scientific interest that would otherwise pose significant risk to the vehicle. The Safe and Precise Landing-Integrated Capabilities Evolution project, or SPLICE, is developing precision landing and hazard avoidance (PL&HA) technologies for NASA and for potential commercial space flight missions. SPLICE technologies include sensors, algorithms, advanced space flight computing capabilities, and simulation tools used to integrate and study guidance, navigation, and control (GN&C) system performance. SPLICE efforts include hardware-in-the-loop (HWIL) simulation testing, ground testing, and flight testing, including reuse of hardware from the CoOperative Blending of Autonomous Landing Technologies (COBALT) suborbital flight-test payload3,4. Two of the precise navigation sensors that are being developed and matured within SPLICE are LiDARs. Since 2006, NASA Langley has been developing a Navigation Doppler LiDAR (NDL) for precise velocity measurements, and SPLICE is building an NDL engineering test unit (ETU) that will be brought up to TRL 6 following environmental and high-speed1,2 testing. NASA Goddard is developing a Hazard Detection LiDAR (HD LiDAR) engineering development unit (EDU) for SPLICE that has relevance to future human and robotic lander missions. The HD LiDAR will be flight test and matured to TRL 5

COBALT CoOperative Blending of Autonomous Landing Technology

COBALT is a terrestrial test platform for development and maturation of GN&C (Guidance, Navigation and Control) technologies for PL&HA (Precision Landing and Hazard Avoidance). The project is developing a third generation, Langley Navigation Doppler Lidar (NDL) for ultra-precise velocity and range measurements, which will be integrated and tested with the JPL Lander Vision System (LVS) for Terrain Relative Navigation (TRN) position estimates. These technologies together provide navigation that enables controlled precision landing. The COBALT hardware will be integrated in 2017 into the GN&C subsystem of the Xodiac rocket-propulsive Vertical Test Bed (VTB) developed by Masten Space Systems (MSS), and two terrestrial flight campaigns will be conducted: one open-loop (i.e., passive) and one closed-loop (i.e., active)

Gain Scheduling for the Orion Launch Abort Vehicle Controller

One of NASAs challenges for the Orion vehicle is the control system design for the Launch Abort Vehicle (LAV), which is required to abort safely at any time during the atmospheric ascent portion of ight. The focus of this paper is the gain design and scheduling process for a controller that covers the wide range of vehicle configurations and flight conditions experienced during the full envelope of potential abort trajectories from the pad to exo-atmospheric flight. Several factors are taken into account in the automation process for tuning the gains including the abort effectors, the environmental changes and the autopilot modes. Gain scheduling is accomplished using a linear quadratic regulator (LQR) approach for the decoupled, simplified linear model throughout the operational envelope in time, altitude and Mach number. The derived gains are then implemented into the full linear model for controller requirement validation. Finally, the gains are tested and evaluated in a non-linear simulation using the vehicles ight software to ensure performance requirements are met. An overview of the LAV controller design and a description of the linear plant models are presented. Examples of the most significant challenges with the automation of the gain tuning process are then discussed. In conclusion, the paper will consider the lessons learned through out the process, especially in regards to automation, and examine the usefulness of the gain scheduling tool and process developed as applicable to non-Orion vehicles

Broken R-parity, stop decays, and neutrino physics

We discuss the phenomenology of the lightest stop in models where R-parity is broken by bilinear superpotential terms. In this class of models we consider scenarios where the R-parity breaking two-body decay ~t_1->\tau^+b competes with the leading three-body decays such as ~t_1->W^+b~\chi^0_1. We demonstrate that the R-parity violating decay can be sizable and in some parts of the parameter space even the dominant one. Moreover we discuss the expectations for \~t_1->\mu^+b and ~t_1->e^+b. The recent results from solar and atmospheric neutrinos suggest that these are as important as the tau bottom mode. The \~t_1->l^+b decays are of particular interest for hadron colliders, as they may allow a full mass reconstruction of the lighter stop. Moreover these decay modes allow cross checks on the neutrino mixing angle involved in the solar neutrino puzzle complementary to those possible using neutralino decays. For the so--called small mixing angle or SMA solution ~t_1->e^+b should be negligible, while for the large mixing angle type solutions all ~t_1->l^+b decays should have comparable magnitude.Comment: 51 pages, 6 figures, LaTeX2e and RevTeX4, published versio

Genome size and ploidy of Paracoccidioides brasiliensis reveals a haploid DNA content: Flow cytometry and GP43 sequence analysis

The aim of this study was to evaluate genome size and ploidy of the dimorphic pathogenic fungus Paracoccidioides brasiliensis. The cell cycle analysis of 10 P. brasiliensis isolates by flow cytometry (FCM) revealed a genome size ranging from 26.3+/-0.1Mb (26.9+/-0.1fg) to 35.5+/-0.2Mb (36.3+/-0.2fg) per uninucleated yeast cell. The DNA content of conidia from P. brasiliensis ATCC 60855-30.2+/-0.8Mb (30.9+/-0.8fg) -showed no significant differences with the yeast form, possibly excluding the occurrence of ploidy shift during morphogenesis. The ploidy of several P. brasiliensis isolates was assessed by comparing genome sizing by FCM with the previously described average haploid size obtained from electrophoretic karyotyping. The analysis of intra-individual variability of a highly polymorphic P. brasiliensis gene, GP43, indicated that only one allele seems to be present. Overall, the results showed that all analysed isolates presented a haploid, or at least aneuploid, DNA content and no association was detected between genome size/ploidy and the clinical-epidemiological features of the studied isolates. This work provides new knowledge on P. brasiliensis genetics/genomics, important for future research in basic cellular/molecular mechanisms and for the development/design of molecular techniques in this fungus

Network centrality: an introduction

Centrality is a key property of complex networks that influences the behavior of dynamical processes, like synchronization and epidemic spreading, and can bring important information about the organization of complex systems, like our brain and society. There are many metrics to quantify the node centrality in networks. Here, we review the main centrality measures and discuss their main features and limitations. The influence of network centrality on epidemic spreading and synchronization is also pointed out in this chapter. Moreover, we present the application of centrality measures to understand the function of complex systems, including biological and cortical networks. Finally, we discuss some perspectives and challenges to generalize centrality measures for multilayer and temporal networks.Comment: Book Chapter in "From nonlinear dynamics to complex systems: A Mathematical modeling approach" by Springe