27,108 research outputs found
An isogeometric analysis for elliptic homogenization problems
A novel and efficient approach which is based on the framework of
isogeometric analysis for elliptic homogenization problems is proposed. These
problems possess highly oscillating coefficients leading to extremely high
computational expenses while using traditional finite element methods. The
isogeometric analysis heterogeneous multiscale method (IGA-HMM) investigated in
this paper is regarded as an alternative approach to the standard Finite
Element Heterogeneous Multiscale Method (FE-HMM) which is currently an
effective framework to solve these problems. The method utilizes non-uniform
rational B-splines (NURBS) in both macro and micro levels instead of standard
Lagrange basis. Beside the ability to describe exactly the geometry, it
tremendously facilitates high-order macroscopic/microscopic discretizations
thanks to the flexibility of refinement and degree elevation with an arbitrary
continuity level provided by NURBS basis functions. A priori error estimates of
the discretization error coming from macro and micro meshes and optimal micro
refinement strategies for macro/micro NURBS basis functions of arbitrary orders
are derived. Numerical results show the excellent performance of the proposed
method
Aubry sets for weakly coupled systems of Hamilton--Jacobi equations
We introduce a notion of Aubry set for weakly coupled systems of
Hamilton--Jacobi equations on the torus and characterize it as the region where
the obstruction to the existence of globally strict critical subsolutions
concentrates. As in the case of a single equation, we prove the existence of
critical subsolutions which are strict and smooth outside the Aubry set. This
allows us to derive in a simple way a comparison result among critical sub and
supersolutions with respect to their boundary data on the Aubry set, showing in
particular that the latter is a uniqueness set for the critical system. We also
highlight some rigidity phenomena taking place on the Aubry set.Comment: 35 pages v.2 the introduction has been rewritten and shortened. Some
proofs simplified. Corrections and references added. Corollary 5.3 added
stating antisymmetry of the Ma\~n\'e matrix on points of the Aubry set.
Section 6 contains a new example
An Efficient Solution to the Mixed Shop Scheduling Problem Using a Modified Genetic Algorithm
The mixed job shop scheduling problem is one in which some jobs have fixed machine orders and other jobs may be processed in arbitrary orders. In past literature, optimal solutions have been proposed based on adaptations of classical solutions such as by Johnson, Thompson and Giffler among many others, by pseudopolynomial algorithms, by simulation, and by Genetic Algorithms (GA). GA based solutions have been proposed for flexible Job shops. This paper proposes a GA algorithm for the mixed job shop scheduling problem. The paper starts with an analysis of the characteristics of the so-called mixed shop problem. Based on those properties, a modified GA is proposed to minimize the makespan of the mixed shop schedule. In this approach, sample instances used as test data are generated under the constraints of shop scheduling problems. A comparison of our results based on benchmark data indicate that our modified GA provides an efficient solution for the mixed shop scheduling problem
APMEC: An Automated Provisioning Framework for Multi-access Edge Computing
Novel use cases and verticals such as connected cars and human-robot
cooperation in the areas of 5G and Tactile Internet can significantly benefit
from the flexibility and reduced latency provided by Network Function
Virtualization (NFV) and Multi-Access Edge Computing (MEC). Existing frameworks
managing and orchestrating MEC and NFV are either tightly coupled or completely
separated. The former design is inflexible and increases the complexity of one
framework. Whereas, the latter leads to inefficient use of computation
resources because information are not shared. We introduce APMEC, a dedicated
framework for MEC while enabling the collaboration with the management and
orchestration (MANO) frameworks for NFV. The new design allows to reuse
allocated network services, thus maximizing resource utilization. Measurement
results have shown that APMEC can allocate up to 60% more number of network
services. Being developed on top of OpenStack, APMEC is an open source project,
available for collaboration and facilitating further research activities
Insights into Pharmacotherapy Management for Parkinson's Disease Patients Using Wearables Activity Data.
We investigate what supervised classification models using clinical and wearables data are best suited to address two important questions about the management of Parkinson's Disease (PD) patients: 1) does a PD patient require pharmacotherapy or not, and 2) whether therapies are having an effect. Currently, patient management is suboptimal due to using subjective patient reported episodes to answer these questions. METHODOLOGY: Clinical and real environment sensor data (memory, tapping, walking) was provided by the mPower study (6805 participants). From the data, we derived relevant clinical scenarios: S1) before vs. after initiating pharmacotherapy, and S2) before vs. after taking medication. For each scenario we designed and tested 6 methods of supervised classification. Precision, Accuracy and Area Under the Curve (AUC) were computed using 10-fold cross-validation. RESULTS: The best classification models were: S1) Decision Trees on Tapping activity data (AUC 0.95, 95% CI 0.05); and S2) K-Nearest Neighbours on Gait data (mean AUC 0.70, 95% CI 0.07, 46% participants with AUC > 0.70). CONCLUSIONS: Automatic patient classification based on sensor activity data can objectively inform PD medication management, with significant potential for improving patient care
Exploiting resource contention in highly mobile environments and its application to vehicular ad-hoc networks
As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. However, mobile environments also need to consider handover issues. Furthermore, in a highly mobile environment, traditional reactive approaches to handover are inadequate and thus proactive techniques have been investigated. Recent research in proactive handover techniques, defined two key parameters: Time Before Handover and Network Dwell Time for a mobile node in any given networking topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. This proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This paper therefore presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments
High Energy Scattering in the Quasi-Potential Approach
Asymptotic behavior of the scattering amplitude for two scalar particles by
scalar, vector and tensor exchanges at high energy and fixed momentum transfers
is reconsidered in quantum field theory. In the framework of the
quasi-potential approach and the modified perturbation theory a systematic
scheme of finding the leading eikonal scattering amplitudes and its corrections
are developed and constructed.The connection between the solutions obtained by
quasi-potential and functional approaches is also discussed.The first
correction to leading eikonal amplitude is found. Keywords: Eikonal scattering
theory, Quantum gravity.Comment: 18 pages. arXiv admin note: substantial text overlap with
arXiv:0804.343
Negative Magnetoresistance in the Nearest-neighbor Hopping Conduction
We propose a size effect which leads to the negative magnetoresistance in
granular metal-insulator materials in which the hopping between two nearest
neighbor clusters is the main transport mechanism. We show that the hopping
probability increases with magnetic field. This is originated from the level
crossing in a few-electron cluster. Thus, the overlap of electronic states of
two neighboring clusters increases, and the negative magnetoresistance is
resulted.Comment: Latex file, no figur
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