The manned maneuvering unit flight controller arm

The Manned Maneuvering Unit (MMU) and its support equipment provide an extravehicular astronaut mobility, and the ability to work outside the confines of the Shuttle Orbiter payload bay. The MMU design requirements are based on the highly successful Skylab M-509 maneuvering unit. Design of the MMU was started as an R&D effort in April 1975 and Flight Hardware design was started in August 1979 to support a possible requirement for in-space inspection and repair of Orbiter thermal protection tiles. Subsequently, the qualification test and production activities were slowed, and the current projected earliest first flight is now STS-11 in January, 1984. The MMU propulsion subsystem provides complete redundancy with two identical "system". Each system contains a high pressure gaseous nitrogen tank, an isolation valve, a regulator, and twelve 1.7 lbf (7.5 N) thrusters. The thrusters are packaged to provide the crew member six-degree-of-freedom control in response to commands from translational and rotational hand controllers. This paper discusses the MMU control arm requirements, design, and developmental history

Addressing the challenges of a new digital technologies curriculum: MOOCs as a scalable solution for teacher professional development

England and Australia have introduced new learning areas, teaching computer science to children from the first year of school. This is a significant milestone that also raises a number of big challenges: the preparation of teachers and the development of resources at a national scale. Curriculum change is not easy for teachers, in any context, and to ensure teachers are supported, scaled solutions are required. One educational approach that has gained traction for delivering content to large-scale audiences are massively open online courses (MOOCs); however, little is known about what constitutes effective MOOC design, particularly within professional development contexts. To prepare teachers in Australia, we decided to ride the wave of MOOCs, developing a MOOC to deliver free computing content and pedagogy to teachers with the integration of social media to support knowledge exchange and resource building. The MOOC was designed to meet teacher needs, allowing for flexibility, ad-hoc interactions, support and the open sharing of resources. In this paper, we describe the process of developing our initiative, participant engagement and experiences, so that others encountering similar changes and reforms may learn from our experience.Rebecca Vivian, Katrina Falkner and Nickolas Falkne

Towards compliant distributed shared memory

Copyright © 2002 IEEEThere exists a wide spectrum of coherency models for use in distributed shared memory (DSM) systems. The choice of model for an application should ideally be based on the application's data access patterns and phase changes. However, in current systems, most, if not all of the parameters of the coherency model are fixed in the underlying DSM system. This forces the application either to structure its computations to suit the underlying model or to endure an inefficient coherency model. This paper introduces a unique approach to the provision of DSM based on the idea of compliance. Compliance allows an application to specify how the system should most effectively operate through a separation between mechanism, provided by the underlying system, and policy, pro-vided by the application. This is in direct contrast with the traditional view that an application must mold itself to the hard-wired choices that its operating platform has made. The contribution of this work is the definition and implementation of an architecture for compliant distributed coherency management. The efficacy of this architecture is illustrated through a worked example.Falkner, K. E.; Detmold, H.; Munro, D. S.; Olds, T

Spatial continuity of measured seawater and tracer fluxes through Nares Strait, a dynamically wide channel bordering the Canadian Archipelago

Freshwater delivered as precipitation and runoff to the North Pacific and Arctic oceans returns to the Atlantic principally via the Canadian polar shelf and Fram Strait. It is conveyed as ice or freshened seawater. Here we use detailed ship-based measurements to calculate a snap-shot of volume, freshwater, and tracer fluxes through Nares Strait, a 500-km long waterway separating Greenland and Ellesmere Island. We use quasi-synoptic observations of current by ship-mounted acoustic Doppler current profiler (ADCP), of salinity and temperature by CTD probe and of dissolved nutrients by rosette bottle sampler on four cross-sections between 82 and 78N latitude. Data were collected during the first half of August 2003. We partition the fluxes into components derived from Pacific and Atlantic inflows into the Arctic Ocean. During the time of the survey, there was a net southward 0.91±0.10 Sv (106 m3 s-1) flux of volume and a net southward 31±4 10-3 Sv (977±127 km3 y-1) flux of freshwater relative to a salinity of 34.8. Much of the volume flux was carried within a strong (40 cm s-1), narrow (10 km) subsurface jet hugging the western (Ellesmere Island) side of the strait. The presence of this jet in four sections spanning the 500-km length of the strait is evidence of a buoyant boundary current through the strait. The jet was coincident with elevated concentrations of phosphate (1.0 mmol m-3) and silicate (11 mmol m-3) which both indicate a Pacific Ocean source. We interpreted the ratio of dissolved total inorganic nitrogen to phosphate in terms of fractional dilution of Atlantic by Pacific waters. About 0.43±0.10 Sv (39%) of the southward flow was of Pacific origin. These results are a snapshot during the summer of 2003 following a prolonged period of northward directed wind stress when ice cover was mobile. Although long-term mean values are likely different, we determined that the major fraction of the through-flow is carried by a jet of scale determined by the internal Rossby radius (5-10 km)

Evaluation of concept importance in concept maps mined from lecture notes: computer vs human

Concept maps are commonly used tools for organising and representing knowledge in order to assist meaningful learning. Although the process of constructing concept maps improves learners’ cognitive structures, novice students typically need substantial assistance from experts. Alternatively, expert-constructed maps may be given to students, which increase the workload of academics. To overcome this issue, automated concept map extraction has been introduced. One of the key limitations is the lack of an evaluation framework to measure the quality of machine-extracted concept maps. At present, researchers in this area utilise human experts’ judgement or expert-constructed maps as the gold standard to measure the relevancy of extracted knowledge components. However, in the educational context, particularly in course materials, the majority of knowledge presented is relevant to the learner, resulting in a large amount of information that has to be organised. Therefore, this paper introduces a machine-based approach which studies the relative importance of knowledge components and organises them hierarchically. We compare machine-extracted maps with human judgment, based on expert knowledge and perception. This paper describes three ranking models to organise domain concepts. The results show that the auto-generated map positively correlates with human judgment (rs~1) for well-structured courses with rich grammar (well-fitted contents).Thushari Atapattu, Katrina Falkner and Nickolas Falkne

Attention, Filling in The Gaps for Generalization in Routing Problems

Machine Learning (ML) methods have become a useful tool for tackling vehicle routing problems, either in combination with popular heuristics or as standalone models. However, current methods suffer from poor generalization when tackling problems of different sizes or different distributions. As a result, ML in vehicle routing has witnessed an expansion phase with new methodologies being created for particular problem instances that become infeasible at larger problem sizes. This paper aims at encouraging the consolidation of the field through understanding and improving current existing models, namely the attention model by Kool et al. We identify two discrepancy categories for VRP generalization. The first is based on the differences that are inherent to the problems themselves, and the second relates to architectural weaknesses that limit the model's ability to generalize. Our contribution becomes threefold: We first target model discrepancies by adapting the Kool et al. method and its loss function for Sparse Dynamic Attention based on the alpha-entmax activation. We then target inherent differences through the use of a mixed instance training method that has been shown to outperform single instance training in certain scenarios. Finally, we introduce a framework for inference level data augmentation that improves performance by leveraging the model's lack of invariance to rotation and dilation changes.Comment: Accepted at ECML-PKDD 202

Multiple cyclotron line-forming regions in GX 301-2

We present two observations of the high-mass X-ray binary GX 301-2 with NuSTAR, taken at different orbital phases and different luminosities. We find that the continuum is well described by typical phenomenological models, like a very strongly absorbed NPEX model. However, for a statistically acceptable description of the hard X-ray spectrum we require two cyclotron resonant scattering features (CRSF), one at ~35 keV and the other at ~50 keV. Even though both features strongly overlap, the good resolution and sensitivity of NuSTAR allows us to disentangle them at >=99.9% significance. This is the first time that two CRSFs are seen in GX 301-2. We find that the CRSFs are very likely independently formed, as their energies are not harmonically related and, if it were a single line, the deviation from a Gaussian shape would be very large. We compare our results to archival Suzaku data and find that our model also provides a good fit to those data. We study the behavior of the continuum as well as the CRSF parameters as function of pulse phase in seven phase bins. We find that the energy of the 35 keV CRSF varies smoothly as function of phase, between 30-38 keV. To explain this variation, we apply a simple model of the accretion column, taking the altitude of the line-forming region, the velocity of the in-falling material, and the resulting relativistic effects into account. We find that in this model the observed energy variation can be explained simply due to a variation of the projected velocity and beaming factor of the line forming region towards us.Comment: 18 pages, 10 figures, accepted for publication in A&

Routing Arena: A Benchmark Suite for Neural Routing Solvers

Neural Combinatorial Optimization has been researched actively in the last eight years. Even though many of the proposed Machine Learning based approaches are compared on the same datasets, the evaluation protocol exhibits essential flaws and the selection of baselines often neglects State-of-the-Art Operations Research approaches. To improve on both of these shortcomings, we propose the Routing Arena, a benchmark suite for Routing Problems that provides a seamless integration of consistent evaluation and the provision of baselines and benchmarks prevalent in the Machine Learning- and Operations Research field. The proposed evaluation protocol considers the two most important evaluation cases for different applications: First, the solution quality for an a priori fixed time budget and secondly the anytime performance of the respective methods. By setting the solution trajectory in perspective to a Best Known Solution and a Base Solver's solutions trajectory, we furthermore propose the Weighted Relative Average Performance (WRAP), a novel evaluation metric that quantifies the often claimed runtime efficiency of Neural Routing Solvers. A comprehensive first experimental evaluation demonstrates that the most recent Operations Research solvers generate state-of-the-art results in terms of solution quality and runtime efficiency when it comes to the vehicle routing problem. Nevertheless, some findings highlight the advantages of neural approaches and motivate a shift in how neural solvers should be conceptualized