3,287 research outputs found
Local Warming
Using 55 years of daily average temperatures from a local weather station, I
made a least-absolute-deviations (LAD) regression model that accounts for three
effects: seasonal variations, the 11-year solar cycle, and a linear trend. The
model was formulated as a linear programming problem and solved using widely
available optimization software. The solution indicates that temperatures have
gone up by about 2 degrees Fahrenheit over the 55 years covered by the data. It
also correctly identifies the known phase of the solar cycle; i.e., the date of
the last solar minimum. It turns out that the maximum slope of the solar cycle
sinusoid in the regression model is about the same size as the slope produced
by the linear trend. The fact that the solar cycle was correctly extracted by
the model is a strong indicator that effects of this size, in particular the
slope of the linear trend, can be accurately determined from the 55 years of
data analyzed.
The main purpose for doing this analysis is to demonstrate that it is easy to
find and analyze archived temperature data for oneself. In particular, this
problem makes a good class project for upper-level undergraduate courses in
optimization or in statistics.
It is worth noting that a similar least-squares model failed to characterize
the solar cycle correctly and hence even though it too indicates that
temperatures have been rising locally, one can be less confident in this
result.
The paper ends with a section presenting similar results from a few thousand
sites distributed world-wide, some results from a modification of the model
that includes both temperature and humidity, as well as a number of suggestions
for future work and/or ideas for enhancements that could be used as classroom
projects.Comment: 12 pages, 5 figures, to appear in SIAM Revie
Managing a Fleet of Autonomous Mobile Robots (AMR) using Cloud Robotics Platform
In this paper, we provide details of implementing a system for managing a
fleet of autonomous mobile robots (AMR) operating in a factory or a warehouse
premise. While the robots are themselves autonomous in its motion and obstacle
avoidance capability, the target destination for each robot is provided by a
global planner. The global planner and the ground vehicles (robots) constitute
a multi agent system (MAS) which communicate with each other over a wireless
network. Three different approaches are explored for implementation. The first
two approaches make use of the distributed computing based Networked Robotics
architecture and communication framework of Robot Operating System (ROS) itself
while the third approach uses Rapyuta Cloud Robotics framework for this
implementation. The comparative performance of these approaches are analyzed
through simulation as well as real world experiment with actual robots. These
analyses provide an in-depth understanding of the inner working of the Cloud
Robotics Platform in contrast to the usual ROS framework. The insight gained
through this exercise will be valuable for students as well as practicing
engineers interested in implementing similar systems else where. In the
process, we also identify few critical limitations of the current Rapyuta
platform and provide suggestions to overcome them.Comment: 14 pages, 15 figures, journal pape
Implementing Session Centered Calculi
Recently, specific attention has been devoted to the development of service oriented process calculi. Besides the foundational aspects, it is also interesting to have prototype implementations for them in order to assess usability and to minimize the gap between theory and practice. Typically, these implementations are done in Java taking advantage of its mechanisms supporting network applications. However, most of the recurrent features of service oriented applications are re-implemented from scratch. In this paper we show how to implement a service oriented calculus, CaSPiS (Calculus of Services with Pipelines and Sessions) using the Java framework IMC, where recurrent mechanisms for network applications are already provided. By using the session oriented and pattern matching communication mechanisms provided by IMC, it is relatively simple to implement in Java all CaSPiS abstractions and thus to easily write the implementation in Java of a CaSPiS process
The Grid[Way] Job Template Manager, a tool for parameter sweeping
Parameter sweeping is a widely used algorithmic technique in computational
science. It is specially suited for high-throughput computing since the jobs
evaluating the parameter space are loosely coupled or independent.
A tool that integrates the modeling of a parameter study with the control of
jobs in a distributed architecture is presented. The main task is to facilitate
the creation and deletion of job templates, which are the elements describing
the jobs to be run. Extra functionality relies upon the GridWay Metascheduler,
acting as the middleware layer for job submission and control. It supports
interesting features like multi-dimensional sweeping space, wildcarding of
parameters, functional evaluation of ranges, value-skipping and job template
automatic indexation.
The use of this tool increases the reliability of the parameter sweep study
thanks to the systematic bookkeping of job templates and respective job
statuses. Furthermore, it simplifies the porting of the target application to
the grid reducing the required amount of time and effort.Comment: 26 pages, 1 figure
Graph-based real-time fault diagnostics
A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components
Exposing errors related to weak memory in GPU applications
© 2016 ACM.We present the systematic design of a testing environment that uses stressing and fuzzing to reveal errors in GPU applications that arise due to weak memory effects. We evaluate our approach on seven GPUS spanning three NVIDIA architectures, across ten CUDA applications that use fine-grained concurrency. Our results show that applications that rarely or never exhibit errors related to weak memory when executed natively can readily exhibit these errors when executed in our testing environment. Our testing environment also provides a means to help identify the root causes of such errors, and automatically suggests how to insert fences that harden an application against weak memory bugs. To understand the cost of GPU fences, we benchmark applications with fences provided by the hardening strategy as well as a more conservative, sound fencing strategy
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