Context based configuration management system

A computer-based system for configuring and displaying information on changes in, and present status of, a collection of events associated with a project. Classes of icons for decision events, configurations and feedback mechanisms, and time lines (sequential and/or simultaneous) for related events are displayed. Metadata for each icon in each class is displayed by choosing and activating the corresponding icon. Access control (viewing, reading, writing, editing, deleting, etc.) is optionally imposed for metadata and other displayed information

The Force Balance of Electrons During Kinetic Anti-parallel Magnetic Reconnection

Fully kinetic simulations are applied to the study of 2D anti-parallel reconnection, elucidating the dynamics by which the electron fluid maintains force balance within both the electron diffusion region (EDR) and the ion diffusion region (IDR). Inside the IDR, magnetic field-aligned electron pressure anisotropy ($p_{e\parallel}\gg p_{e\perp})$ develops upstream of the EDR. Compared to previous investigations, the use of modern computer facilities allows for simulations at the natural proton to electron mass ratio $m_i/m_e=1836$. In this high-$m_i/m_e$-limit the electron dynamics changes qualitatively, as the electron inflow to the EDR is enhanced and mainly driven by the anisotropic pressure. Using a coordinate system with the $x$-direction aligned with the reconnecting magnetic field and the $y$-direction aligned with the central current layer, it is well-known that for the much studied 2D laminar anti-parallel and symmetric scenario the reconnection electric field at the $X$-line must be balanced by the $\partial p_{exy}/ \partial x$ and $\partial p_{eyz}/ \partial z$ off-diagonal electron pressure stress components. We find that the electron anisotropy upstream of the EDR imposes large values of $\partial p_{exy}/ \partial x$ within the EDR, and along the direction of the reconnection $X$-line this stress cancels with the stress of a previously determined theoretical form for $\partial p_{eyz}/ \partial z$. The electron frozen-in law is instead broken by pressure tensor gradients related to the direct heating of the electrons by the reconnection electric field. The reconnection rate is free to adjust to the value imposed externally by the plasma dynamics at larger scales.Comment: Submitted to Physics of Plasmas, 11 October 202

Spin Relaxation in Graphene with self-assembled Cobalt Porphyrin Molecules

In graphene spintronics, interaction of localized magnetic moments with the electron spins paves a new way to explore the underlying spin relaxation mechanism. A self-assembled layer of organic cobalt-porphyrin (CoPP) molecules on graphene provides a desired platform for such studies via the magnetic moments of porphyrin-bound cobalt atoms. In this work a study of spin transport properties of graphene spin-valve devices functionalized with such CoPP molecules as a function of temperature via non-local spin-valve and Hanle spin precession measurements is reported. For the functionalized (molecular) devices, we observe a slight decrease in the spin relaxation time ({\tau}s), which could be an indication of enhanced spin-flip scattering of the electron spins in graphene in the presence of the molecular magnetic moments. The effect of the molecular layer is masked for low quality samples (low mobility), possibly due to dominance of Elliot-Yafet (EY) type spin relaxation mechanisms

Bias dependent spin injection into graphene on YIG through bilayer hBN tunnel barriers

We study the spin injection efficiency into single and bilayer graphene on the ferrimagnetic insulator Yttrium-Iron-Garnet (YIG) through an exfoliated tunnel barrier of bilayer hexagonal boron nitride (hBN). The contacts of two samples yield a resistance-area product between 5 and 30 k$\Omega\mu$m$^2$. Depending on an applied DC bias current, the magnitude of the non-local spin signal can be increased or suppressed below the noise level. The spin injection efficiency reaches values from -60% to +25%. The results are confirmed with both spin valve and spin precession measurements. The proximity induced exchange field is found in sample A to be (85 $\pm$ 30) mT and in sample B close to the detection limit. Our results show that the exceptional spin injection properties of bilayer hBN tunnel barriers reported by Gurram et al. are not limited to fully encapsulated graphene systems but are also valid in graphene/YIG devices. This further emphasizes the versatility of bilayer hBN as an efficient and reliable tunnel barrier for graphene spintronics.Comment: 9 pages, 6 figures, 5 supplementary figure

Project management tool

A system for managing a project that includes multiple tasks and a plurality of workers. Input information includes characterizations based upon a human model, a team model and a product model. Periodic reports, such as a monthly report, a task plan report, a budget report and a risk management report, are generated and made available for display or further analysis. An extensible database allows searching for information based upon context and upon content

Searching Across the International Space Station Databases

Data access in the enterprise generally requires us to combine data from different sources and different formats. It is advantageous thus to focus on the intersection of the knowledge across sources and domains; keeping irrelevant knowledge around only serves to make the integration more unwieldy and more complicated than necessary. A context search over multiple domain is proposed in this paper to use context sensitive queries to support disciplined manipulation of domain knowledge resources. The objective of a context search is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The search supports formally the tasks of selecting, combining, extending, specializing, and modifying components from a diverse set of domains. This paper demonstrates a new paradigm in composition of information for enterprise applications. In particular, it discusses an approach to achieving data integration across multiple sources, in a manner that does not require heavy investment in database and middleware maintenance. This lean approach to integration leads to cost-effectiveness and scalability of data integration with an underlying schemaless object-relational database management system. This highly scalable, information on demand system framework, called NX-Search, which is an implementation of an information system built on NETMARK. NETMARK is a flexible, high-throughput open database integration framework for managing, storing, and searching unstructured or semi-structured arbitrary XML and HTML used widely at the National Aeronautics Space Administration (NASA) and industry

Large-scale Nonlinear Variable Selection via Kernel Random Features

We propose a new method for input variable selection in nonlinear regression. The method is embedded into a kernel regression machine that can model general nonlinear functions, not being a priori limited to additive models. This is the first kernel-based variable selection method applicable to large datasets. It sidesteps the typical poor scaling properties of kernel methods by mapping the inputs into a relatively low-dimensional space of random features. The algorithm discovers the variables relevant for the regression task together with learning the prediction model through learning the appropriate nonlinear random feature maps. We demonstrate the outstanding performance of our method on a set of large-scale synthetic and real datasets.Comment: Final version for proceedings of ECML/PKDD 201

System for Performing Single Query Searches of Heterogeneous and Dispersed Databases

The present invention is a distributed computer system of heterogeneous databases joined in an information grid and configured with an Application Programming Interface hardware which includes a search engine component for performing user-structured queries on multiple heterogeneous databases in real time. This invention reduces overhead associated with the impedance mismatch that commonly occurs in heterogeneous database queries

Thermoelectric spin voltage in graphene

In recent years, new spin-dependent thermal effects have been discovered in ferromagnets, stimulating a growing interest in spin caloritronics, a field that exploits the interaction between spin and heat currents. Amongst the most intriguing phenomena is the spin Seebeck effect, in which a thermal gradient gives rise to spin currents that are detected through the inverse spin Hall effect. Non-magnetic materials such as graphene are also relevant for spin caloritronics, thanks to efficient spin transport, energy-dependent carrier mobility and unique density of states. Here, we propose and demonstrate that a carrier thermal gradient in a graphene lateral spin valve can lead to a large increase of the spin voltage near to the graphene charge neutrality point. Such an increase results from a thermoelectric spin voltage, which is analogous to the voltage in a thermocouple and that can be enhanced by the presence of hot carriers generated by an applied current. These results could prove crucial to drive graphene spintronic devices and, in particular, to sustain pure spin signals with thermal gradients and to tune the remote spin accumulation by varying the spin-injection bias

Why the Failure? How Adversarial Examples Can Provide Insights for Interpretable Machine Learning

Recent advances in Machine Learning (ML) have profoundly changed many detection, classification, recognition and inference tasks. Given the complexity of the battlespace, ML has the potential to revolutionise how Coalition Situation Understanding is synthesised and revised. However, many issues must be overcome before its widespread adoption. In this paper we consider two - interpretability and adversarial attacks. Interpretability is needed because military decision-makers must be able to justify their decisions. Adversarial attacks arise because many ML algorithms are very sensitive to certain kinds of input perturbations. In this paper, we argue that these two issues are conceptually linked, and insights in one can provide insights in the other. We illustrate these ideas with relevant examples from the literature and our own experiments