5,793 research outputs found
USEM: A ubiquitous smart energy management system for residential homes
With the ever-increasing worldwide demand for energy, and the limited available energy resources, there is a growing need to reduce our energy consumption whenever possible. Therefore, over the past few decades a range of technologies have been proposed to assist consumers with reducing their energy use. Most of these have focused on decreasing energy consumption in the industry, transport, and services sectors. In more recent years, however, growing attention has been given to energy use in the residential sector, which accounts for nearly 30% of total energy consumption in the developed countries. Here we present one such system, which aims to assist residential users with monitoring their energy usage and provides mechanisms for setting up and controlling their home appliances to conserve energy. We also describe a user study we have conducted to evaluate the effectiveness of this system in supporting its users with a range of tools and visualizations developed for ubiquitous devices such as mobile phones and tablets. The findings of this study have shown the potential benefits of our system, and have identified areas of improvement that need to be addressed in the future
Operations of and Future Plans for the Pierre Auger Observatory
Technical reports on operations and features of the Pierre Auger Observatory,
including ongoing and planned enhancements and the status of the future
northern hemisphere portion of the Observatory. Contributions to the 31st
International Cosmic Ray Conference, Lodz, Poland, July 2009.Comment: Contributions to the 31st ICRC, Lodz, Poland, July 200
ROBAST: Development of a ROOT-Based Ray-Tracing Library for Cosmic-Ray Telescopes and its Applications in the Cherenkov Telescope Array
We have developed a non-sequential ray-tracing simulation library, ROOT-based
simulator for ray tracing (ROBAST), which is aimed to be widely used in optical
simulations of cosmic-ray (CR) and gamma-ray telescopes. The library is written
in C++, and fully utilizes the geometry library of the ROOT framework. Despite
the importance of optics simulations in CR experiments, no open-source software
for ray-tracing simulations that can be widely used in the community has
existed. To reduce the dispensable effort needed to develop multiple
ray-tracing simulators by different research groups, we have successfully used
ROBAST for many years to perform optics simulations for the Cherenkov Telescope
Array (CTA). Among the six proposed telescope designs for CTA, ROBAST is
currently used for three telescopes: a Schwarzschild-Couder (SC) medium-sized
telescope, one of SC small-sized telescopes, and a large-sized telescope (LST).
ROBAST is also used for the simulation and development of hexagonal light
concentrators proposed for the LST focal plane. Making full use of the ROOT
geometry library with additional ROBAST classes, we are able to build the
complex optics geometries typically used in CR experiments and ground-based
gamma-ray telescopes. We introduce ROBAST and its features developed for CR
experiments, and show several successful applications for CTA.Comment: Accepted for publication in Astroparticle Physics. 11 pages, 10
figures, 4 table
GEANT4 : a simulation toolkit
Abstract Geant4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics. PACS: 07.05.Tp; 13; 2
CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks
The precise modeling of subatomic particle interactions and propagation
through matter is paramount for the advancement of nuclear and particle physics
searches and precision measurements. The most computationally expensive step in
the simulation pipeline of a typical experiment at the Large Hadron Collider
(LHC) is the detailed modeling of the full complexity of physics processes that
govern the motion and evolution of particle showers inside calorimeters. We
introduce \textsc{CaloGAN}, a new fast simulation technique based on generative
adversarial networks (GANs). We apply these neural networks to the modeling of
electromagnetic showers in a longitudinally segmented calorimeter, and achieve
speedup factors comparable to or better than existing full simulation
techniques on CPU (-) and even faster on GPU (up to
). There are still challenges for achieving precision across
the entire phase space, but our solution can reproduce a variety of geometric
shower shape properties of photons, positrons and charged pions. This
represents a significant stepping stone toward a full neural network-based
detector simulation that could save significant computing time and enable many
analyses now and in the future.Comment: 14 pages, 4 tables, 13 figures; version accepted by Physical Review D
(PRD
ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization
ROOT is an object-oriented C++ framework conceived in the high-energy physics
(HEP) community, designed for storing and analyzing petabytes of data in an
efficient way. Any instance of a C++ class can be stored into a ROOT file in a
machine-independent compressed binary format. In ROOT the TTree object
container is optimized for statistical data analysis over very large data sets
by using vertical data storage techniques. These containers can span a large
number of files on local disks, the web, or a number of different shared file
systems. In order to analyze this data, the user can chose out of a wide set of
mathematical and statistical functions, including linear algebra classes,
numerical algorithms such as integration and minimization, and various methods
for performing regression analysis (fitting). In particular, ROOT offers
packages for complex data modeling and fitting, as well as multivariate
classification based on machine learning techniques. A central piece in these
analysis tools are the histogram classes which provide binning of one- and
multi-dimensional data. Results can be saved in high-quality graphical formats
like Postscript and PDF or in bitmap formats like JPG or GIF. The result can
also be stored into ROOT macros that allow a full recreation and rework of the
graphics. Users typically create their analysis macros step by step, making use
of the interactive C++ interpreter CINT, while running over small data samples.
Once the development is finished, they can run these macros at full compiled
speed over large data sets, using on-the-fly compilation, or by creating a
stand-alone batch program. Finally, if processing farms are available, the user
can reduce the execution time of intrinsically parallel tasks - e.g. data
mining in HEP - by using PROOF, which will take care of optimally distributing
the work over the available resources in a transparent way
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