Integrated command, control, communications and computation system functional architecture

The functional architecture for an integrated command, control, communications, and computation system applicable to the command and control portion of the NASA End-to-End Data. System is described including the downlink data processing and analysis functions required to support the uplink processes. The functional architecture is composed of four elements: (1) the functional hierarchy which provides the decomposition and allocation of the command and control functions to the system elements; (2) the key system features which summarize the major system capabilities; (3) the operational activity threads which illustrate the interrelationahip between the system elements; and (4) the interfaces which illustrate those elements that originate or generate data and those elements that use the data. The interfaces also provide a description of the data and the data utilization and access techniques

Fracture toughness and fatigue-crack propagation in a Zr–Ti–Ni–Cu–Be bulk metallic glass

The recent development of metallic alloy systems which can be processed with an amorphous structure over large dimensions, specifically to form metallic glasses at low cooling rates (similar to 10 K/s), has permitted novel measurements of important mechanical properties. These include, for example, fatigue-crack growth and fracture toughness behavior, representing the conditions governing the subcritical and critical propagation of cracks in these structures. In the present study, bulk plates of a Zr41.2Ti13.8Cu12.5Ni10Be22.5 alloy, machined into 7 mm wide, 38 mm thick compact-tension specimens and fatigue precracked following standard procedures, revealed fracture toughnesses in the fully amorphous structure of K(lc)similar to 55 MPa root m, i.e., comparable with that of a high-strength steel or aluminum ahoy. However, partial and full crystallization, e.g., following thermal exposure at 633 K or more, was found to result in a drastic reduction in fracture toughness to similar to 1 MPa root m, i.e., comparable with silica glass. The fully amorphous alloy was also found to be susceptible to fatigue-crack growth under cyclic loading, with growth-rate properties comparable to that of ductile crystalline metallic alloys, such as high-strength steels or aluminum alloys; no such fatigue was seen in the partially or fully crystallized alloys which behaved like very brittle ceramics. Possible micromechanical mechanisms for such behavior are discussed

Did Neoliberalizing West African Forests Produce a New Niche for Ebola?

A recent study introduced a vaccine that controls Ebola Makona, the Zaire ebolavirus variant that has infected 28,000 people in West Africa. We propose that even such successful advances are insufficient for many emergent diseases. We review work hypothesizing that Makona, phenotypically similar to much smaller outbreaks, emerged out of shifts in land use brought about by neoliberal economics. The epidemiological consequences demand a new science that explicitly addresses the foundational processes underlying multispecies health, including the deep-time histories, cultural infrastructure, and global economic geographies driving disease emergence. The approach, for instance, reverses the standard public health practice of segregating emergency responses and the structural context from which outbreaks originate. In Ebola's case, regional neoliberalism may affix the stochastic "friction" of ecological relationships imposed by the forest across populations, which, when above a threshold, keeps the virus from lining up transmission above replacement. Export-led logging, mining, and intensive agriculture may depress such functional noise, permitting novel spillovers larger forces of infection. Mature outbreaks, meanwhile, can continue to circulate even in the face of efficient vaccines. More research on these integral explanations is required, but the narrow albeit welcome success of the vaccine may be used to limit support of such a program.SCOPUS: re.jinfo:eu-repo/semantics/publishe

Parity-Projected Shell Model Monte Carlo Level Densities for fp-shell Nuclei

We calculate parity-dependent level densities for the even-even isotopes 58,62,66 Fe and 58 Ni and the odd-A nuclei 59 Ni and 65 Fe using the Shell Model Monte Carlo method. We perform these calculations in the complete fp-gds shell-model space using a pairing+quadrupole residual interaction. We find that, due to pairing of identical nucleons, the low-energy spectrum is dominated by positive parity states. Although these pairs break at around the same excitation energy in all nuclei, the energy dependence of the ratio of negative-to-positive parity level densities depends strongly on the particular nucleus of interest. We find equilibration of both parities at noticeably lower excitation energies for the odd-A nuclei 59 Ni and 65 Fe than for the neighboring even-even nuclei 58 Ni and 66 Fe.Comment: 5 pages, 4 figures, submitted to Phys. Rev.

Fast magnetization switching of Stoner particles: A nonlinear dynamics picture

The magnetization reversal of Stoner particles is investigated from the point of view of nonlinear dynamics within the Landau-Lifshitz-Gilbert formulation. The following results are obtained. 1) We clarify that the so-called Stoner-Wohlfarth (SW) limit becomes exact when damping constant is infinitely large. Under the limit, the magnetization moves along the steepest energy descent path. The minimal switching field is the one at which there is only one stable fixed point in the system. 2) For a given magnetic anisotropy, there is a critical value for the damping constant, above which the minimal switching field is the same as that of the SW-limit. 3) We illustrate how fixed points and their basins change under a field along different directions. This change explains well why a non-parallel field gives a smaller minimal switching field and a short switching time. 4) The field of a ballistic magnetization reversal should be along certain direction window in the presence of energy dissipation. The width of the window depends on both of the damping constant and the magnetic anisotropy. The upper and lower bounds of the direction window increase with the damping constant. The window width oscillates with the damping constant for a given magnetic anisotropy. It is zero for both zero and infinite damping. Thus, the perpendicular field configuration widely employed in the current experiments is not the best one since the damping constant in a real system is far from zero.Comment: 10 pages, 9 figures. submitted to PR

A Web/Grid Services Approach for Integration of Virtual Clinical & Research Environments

Clinicans have responsibilities for audit and research, often participating in projects with basic scientist colleagues. Our work in a regional teaching hospital setting involves collaboration with the medical school computer services and builds upon work developed in computer science department as part of the Collaborative Orthopaedic Research Environment (CORE) project[1]. This has established a pilot study for proof of concept work. Users are mapped to a personal profile implemented using XML and a service oriented architecture (SOA)[2,3]. This bridges the e-Health and e-Science domains, addressing some of the basic questions of security and uptake

An immune system based genetic algorithm using permutation-based dualism for dynamic traveling salesman problems

Copyright @ Springer-Verlag Berlin Heidelberg 2009.In recent years, optimization in dynamic environments has attracted a growing interest from the genetic algorithm community due to the importance and practicability in real world applications. This paper proposes a new genetic algorithm, based on the inspiration from biological immune systems, to address dynamic traveling salesman problems. Within the proposed algorithm, a permutation-based dualism is introduced in the course of clone process to promote the population diversity. In addition, a memory-based vaccination scheme is presented to further improve its tracking ability in dynamic environments. The experimental results show that the proposed diversification and memory enhancement methods can greatly improve the adaptability of genetic algorithms for dynamic traveling salesman problems.This work was supported by the Key Program of National Natural Science Foundation (NNSF) of China under Grant No. 70431003 and Grant No. 70671020, the Science Fund for Creative Research Group of NNSF of China under GrantNo. 60521003, the National Science and Technology Support Plan of China under Grant No. 2006BAH02A09 and the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant No. EP/E060722/1

Fuzzy State Aggregation and Off-Policy Reinforcement Learning for Stochastic Environments

Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the environment it is operating in changes. This ability to learn in an unsupervised manner in a changing environment is applicable in complex domains through the use of function approximation of the domain’s policy. The function approximation presented here is that of fuzzy state aggregation. This article presents the use of fuzzy state aggregation with the current policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF (PD-WoLF), exceeding the learning rate and performance of the combined fuzzy state aggregation and Q-learning reinforcement learning. Results of testing using the TileWorld domain demonstrate the policy hill climbing performs better than the existing Q-learning implementations

Fuzzy State Aggregation and Policy Hill Climbing for Stochastic Environments

Reinforcement learning is one of the more attractive machine learning technologies, due to its unsupervised learning structure and ability to continually learn even as the operating environment changes. Additionally, by applying reinforcement learning to multiple cooperative software agents (a multi-agent system) not only allows each individual agent to learn from its own experience, but also opens up the opportunity for the individual agents to learn from the other agents in the system, thus accelerating the rate of learning. This research presents the novel use of fuzzy state aggregation, as the means of function approximation, combined with the fastest policy hill climbing methods of Win or Lose Fast (WoLF) and policy-dynamics based WoLF (PD-WoLF). The combination of fast policy hill climbing and fuzzy state aggregation function approximation is tested in two stochastic environments: Tileworld and the simulated robot soccer domain, RoboCup. The Tileworld results demonstrate that a single agent using the combination of FSA and PHC learns quicker and performs better than combined fuzzy state aggregation and Q-learning reinforcement learning alone. Results from the multi-agent RoboCup domain again illustrate that the policy hill climbing algorithms perform better than Q-learning alone in a multi-agent environment. The learning is further enhanced by allowing the agents to share their experience through a weighted strategy sharing

Activity Pattern Discovery from Network Captures

Investigating insider threat cases is challenging because activities are conducted with legitimate access that makes distinguishing malicious activities from normal activities difficult. To assist with identifying non-normal activities, we propose using two types of pattern discovery to identify a person\u27s behavioral patterns in network data. The behavioral patterns serve to deemphasize normal behavior so that insider threat investigations can focus attention on potentially more relevant. Results from a controlled experiment demonstrate the highlighting of a suspicious event through the reduction of events belonging to discovered patterns. Abstract © 2016 IEEE