43,657 research outputs found
Eigenvalue spectrum for single particle in a spheroidal cavity: A Semiclassical approach
Following the semiclassical formalism of Strutinsky et al., we have obtained
the complete eigenvalue spectrum for a particle enclosed in an infinitely high
spheroidal cavity. Our spheroidal trace formula also reproduces the results of
a spherical billiard in the limit . Inclusion of repetition of each
family of the orbits with reference to the largest one significantly improves
the eigenvalues of sphere and an exact comparison with the quantum mechanical
results is observed upto the second decimal place for . The
contributions of the equatorial, the planar (in the axis of symmetry plane) and
the non-planar(3-Dimensional) orbits are obtained from the same trace formula
by using the appropriate conditions. The resulting eigenvalues compare very
well with the quantum mechanical eigenvalues at normal deformation. It is
interesting that the partial sum of equatorial orbits leads to eigenvalues with
maximum angular momentum projection, while the summing of planar orbits leads
to eigenvalues with except for L=1. The remaining quantum mechanical
eigenvalues are observed to arise from the 3-dimensional(3D) orbits. Very few
spurious eigenvalues arise in these partial sums. This result establishes the
important role of 3D orbits even at normal deformations.Comment: 17 pages, 7 ps figure
Knowledge representation system for assembly using robots
Assembly robots combine the benefits of speed and accuracy with the capability of adaptation to changes in the work environment. However, an impediment to the use of robots is the complexity of the man-machine interface. This interface can be improved by providing a means of using a priori-knowledge and reasoning capabilities for controlling and monitoring the tasks performed by robots. Robots ought to be able to perform complex assembly tasks with the help of only supervisory guidance from human operators. For such supervisory quidance, it is important to express the commands in terms of the effects desired, rather than in terms of the motion the robot must undertake in order to achieve these effects. A suitable knowledge representation can facilitate the conversion of task level descriptions into explicit instructions to the robot. Such a system would use symbolic relationships describing the a priori information about the robot, its environment, and the tasks specified by the operator to generate the commands for the robot
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Automatic Detection of Clear-Sky Periods From Irradiance Data
Recent degradation studies have highlighted the importance of considering cloud cover when calculating degradation rates, finding more reliable values when the data are restricted to clear sky periods. Several automated methods of determining clear sky periods have been previously developed, but parameterizing and testing the models has been difficult. In this paper, we use clear sky classifications determined from satellite data to develop an algorithm that determines clear sky periods using only measured irradiance values and modeled clear sky irradiance as inputs. This method is tested on global horizontal irradiance (GHI) data from ground collectors at six sites across the United States and compared against independent satellite-based classifications. First, 30 separate models were optimized on each individual site at GHI data intervals of 1, 5, 10, 15, and 30 min (sampled on the first minute of the interval). The models had an average F0.5 score of 0.949 ± 0.035 on a holdout test set. Next, optimizations were performed by aggregating data from different locations at the same interval, yielding one model per data interval. This paper yielded an average F0.5 of 0.946 ± 0.037. A final, 'universal' optimization that was trained on data from all sites at all intervals provided an F0.5 score of 0.943 ± 0.040. The optimizations all provide improvements on a prior, unoptimized clear sky detection algorithm that produces F0.5 scores that average to 0.903 ± 0.067. Our paper indicates that a single algorithm can accurately classify clear sky periods across locations and data sampling intervals
Decision Sheet and Learning Diary: New Tools for Improved Learning Through the Case Method
Of the three phases of learning through the case method, instructors have focused on the in-class phase in training of both teachers and participants. The other two phases, pre-class preparation and post class-reflection, have not received much attention leading to lack of exploitation of the full learning potential from the method. This paper shares continued efforts to conceptualize and develop two tools, decision sheet and learning diary, to strengthen the two phases. These were designed and tested in three executive development programmes. The results and our reflections suggest that the tools enhance the process of learning and the learning itself.
Nonuniversal exponents in sandpiles with stochastic particle number transfer
We study fixed density sandpiles in which the number of particles transferred
to a neighbor on relaxing an active site is determined stochastically by a
parameter . Using an argument, the critical density at which an
active-absorbing transition occurs is found exactly. We study the critical
behavior numerically and find that the exponents associated with both static
and time-dependent quantities vary continuously with .Comment: Some parts rewritten, results unchanged. To appear in Europhys. Let
Synchronization in Networks of Identical Systems via Pinning: Application to Distributed Secondary Control of Microgrids
Motivated by the need for fast synchronized operation of power microgrids, we
analyze the problem of single and multiple pinning in networked systems. We
derive lower and upper bounds on the algebraic connectivity of the network with
respect to the reference signal. These bounds are utilized to devise a
suboptimal algorithm with polynomial complexity to find a suitable set of nodes
to pin the network effectively and efficiently. The results are applied to
secondary voltage pinning control design for a microgrid in islanded operation
mode. Comparisons with existing single and multiple pinning strategies clearly
demonstrates the efficacy of the obtained results.Comment: 11 pages, 9 figures, submitted to Transactions on Control Systems
Technolog
Dark Energy and the Statistical Study of the Observed Image Separations of the Multiply Imaged Systems in the CLASS Statistical Sample
The present day observations favour a universe which is flat, accelerated and
composed of matter (baryonic + dark) and of a negative
pressure component, usually referred to as dark energy or quintessence. The
Cosmic Lens All Sky Survey (CLASS), the largest radio-selected galactic mass
scale gravitational lens search project to date, has resulted in the largest
sample suitable for statistical analyses. In the work presented here, we
exploit observed image separations of the multiply imaged lensed radio sources
in the sample. We use two different tests: (1) image separation distribution
function of the lensed radio sources and (2)
{\dtheta}_{\mathrm{pred}} vs {\dtheta}_{\mathrm{obs}} as observational
tools to constrain the cosmological parameters and \Om. The results are
in concordance with the bounds imposed by other cosmological tests.Comment: 20 pages latex; Modified " Results and Discussion " section, new
references adde
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