Frito-Lay - Supply Chain Impact Analysis

The snack food company Frito-Lay relies on Route Sales Representatives (RSRs) to stock and maintain shelves of snack foods in every store. Frito-Lay currently does not have a system which can accurately predict cannibalization, or the effects of a store opening or closing on other stores of the same chain in the area. The goal is to sort through 1900 stores in a given metropolitan area to see the effects of cannibalization. In order to tackle the problem, a Microsoft Access program was created to filter stores based on location or whether the store was open for the full three-year duration or not. The analysis of an opening or closing store is divided between the long-term and short-term effects. An examination of the long-term effects begins by focusing on eliminating seasonal and yearly trends. Seasonal trends are deemed to be insignificant due to the lack of a dominant oscillation within the year. Next, yearly trends are eliminated by performing an individual regression analysis between the introduced store and a nearby store and tracking the sales changes on control charts. A scatterplot is created using the distance between the neighboring store and the introduced store versus the sales changes. A trend line is fitted to the data, but little correlation can be seen. The long-term effects are inconclusive because the model does not incorporate different factors that could affect sales numbers. The short-term effects were analyzed using a combination of control charts, percentage changes, and sales averages before and after the store’s introduction. The most statistically significant interactions were same-store cannibalization for mass merchandisers and supermarkets. This supports the already-standing practices by Frito-Lay

Task-embedded control networks for few-shot imitation learning

Much like humans, robots should have the ability to leverage knowledge from previously learned tasks in order to learn new tasks quickly in new and unfamiliar environments. Despite this, most robot learning approaches have focused on learning a single task, from scratch, with a limited notion of generalisation, and no way of leveraging the knowledge to learn other tasks more efficiently. One possible solution is meta-learning, but many of the related approaches are limited in their ability to scale to a large number of tasks and to learn further tasks without forgetting previously learned ones. With this in mind, we introduce Task-Embedded Control Networks, which employ ideas from metric learning in order to create a task embedding that can be used by a robot to learn new tasks from one or more demonstrations. In the area of visually-guided manipulation, we present simulation results in which we surpass the performance of a state-of-the-art method when using only visual information from each demonstration. Additionally, we demonstrate that our approach can also be used in conjunction with domain randomisation to train our few-shot learning ability in simulation and then deploy in the real world without any additional training. Once deployed, the robot can learn new tasks from a single real-world demonstration

Air cooling vs. liquid immersion cooling: can liquid immersion cooling improve the energy and space efficiency of data centres?

The demand for cloud services is rising continuously, inflating the energy demand for data centres exponentially. The purpose of this literature review is to discover the positive impact liquid immersion cooling can have on data centre efficiency and density. Utilizing a systematic literature review, this paper illustrates the research already conducted on immersion cooling. The calculated results, using the available data, shows that by switching from air to liquid immersion cooling, about half the energy used by a data centre and two thirds of the space occupied by a data centre can be freed for additional hardware. This review succeeds in showing the capabilities of liquid immersion cooling in data centres. Further research can be conducted on the actual improvement when a data centre is converted to immersion cooling.Der Bedarf an Online-Diensten steigt kontinuierlich an, das lässt den Energieverbrauch von Rechenzentren exponentiell ansteigen. Die Absicht der Literaturrecherche ist es, zu entdecken, wie die Effizienz und Dichte von Rechenzentren durch Flüssigkeitstauchkühlung erhöht werden kann. Es wurde eine systematische Literaturrecherche gewählt, um die bisher geleistete Forschungsarbeit zum Thema aufzuzeigen. Die mit den gefundenen Daten berechneten Ergebnisse haben gezeigt, dass ein Umstieg von Luft zu Flüssigkeitstauchkühlung die verwendete Energie halbieren und den Platzverbrauch sogar auf ein Drittel reduzieren kann. Das ermöglicht eine Erweiterung der Rechenkapazität. Die Literaturrecherche hat die Möglichkeiten von Flüssigkeitstauchkühlung erfolgreich gezeigt. Weitere Forschungsarbeit könnte geleistet werden, indem man eine Umrüstung eines luftgekühlten Rechenzentrums begleitet und die Größe und den Energieverbrauch sowohl vorher als auch nachher misst

Quasi-dynamic pressure and temperature

The phase transformation of {beta}-HMX (< 0.5% RDX) to the {delta} phase has been studied for over twenty years and more recently with an optically sensitive second harmonic generation technique. Shock studies of the plastic binder composites of HMX have indicated that the transition is perhaps irreversible, a result that concurs with the static pressure results published by F. Goetz et al. [l] in 1978. However the stability field favors the {beta} polymorph over {delta} as pressure is increased (up to 5.4 GPa) along any sensible isotherm. In this experiment strict control of pressure and temperature is maintained while x-ray and optical diagnostics are applied to monitor the conformational dynamics of HMX. Unlike the temperature induced {beta} -> {delta} transition, the pressure induced is heterogeneous in nature. The room pressure and temperature {delta} -> {beta} transition is not immediate although it seems to occur over tens of hours. Transition points and kinetics are path dependent and so this paper describes our work in progress

The role of information systems in configuring organisational power

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN032294 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Scalability and performance of data-parallel pressure-based multigrid methods for viscous flows

A full-approximation storage multigrid method for solving the steady-state 2-d incompressible Navier-Stokes equations on staggered grids has been implemented in Fortran on the CM-5,using the array aliasing feature in CM-Fortran to avoid declaring fine-grid-sized arrays on all levels while still allowing a variable number of grid levels. Thus, the storage cost scales with the number of unknowns,allowing us to consider significantly larger problems than would otherwise be possible. Timings over a range of problem sizes and numbers of processors, up to 4096 X 4096 on 512 nodes, show that the smoothing procedure, a pressure-correction technique, is scalable and that the restriction and prolongation steps are nearly so. The performance obtained for the multigrid method is 333 Mflops out of the theoretical peak 4 Gflops on a 32-node CM-5. In comparison, a single-grid computation obtained 420 Mflops. The decrease is due to the inefficiency of the smoothing iterations on the coarse grid levels. W cycles cost much more and are much less efficient than V cycles, due to the increased contribution from the coarse grids. The convergence rate characteristics of the pressure-correction multigrid method are investigated in a Re - 5000 lid-driven cavity flow and a Re = 300 symmetric backward-facing step flow, using either a defect-correction scheme or a second-order upwind scheme. A heuristic technique relating the convergence tolerances for the coarse grids to the truncation error of the discretization has been found effective and robust. With second-order up-winding on all grid levels, a 5-level 320X 80 step flow solution was obtained in 20 V cycles, which corresponds to a smoothing rate of 0.7, and required 25 s on a 32-node CM-5. Overall, the convergence rates obtained in the present work are comparable to the most competitive findings reported in the literature, © 1996 Academic Press, Inc