3,240 research outputs found
Secure and Privacy Preserving Consensus for Second-order Systems Based on Paillier Encryption
This paper aims at secure and privacy preserving consensus algorithms of
networked systems. Due to the technical challenges behind decentralized design
of such algorithms, the existing results are mainly restricted to a network of
systems with simplest first-order dynamics. Like many other control problems,
breakthrough of the gap between first-order dynamics and higher-order ones
demands for more advanced technical developments. In this paper, we explore a
Paillier encryption based average consensus algorithm for a network of systems
with second-order dynamics, with randomness added to network weights. The
conditions for privacy preserving, especially depending on consensus rate, are
thoroughly studied with theoretical analysis and numerical verification
Nonlinear saturation of toroidal Alfven eigenmodes via nonlinear mode couplings
Gyrokinetic theory of nonlinear mode coupling as a mechanism for toroidal
Alfven eigenmode (TAE) saturation in the fusion plasma related parameter regime
is presented, including 1) para- metric decay of TAE into lower kinetic TAE
(LKTAE) and geodesic acoustic mode (GAM), and 2) enhanced TAE coupling to shear
Alfven wave (SAW) continuum via ion induced scattering. Our theory shows that,
for TAE saturation in the parameter range of practical interest, several
processes with comparable scattering cross sections can be equally important.Comment: Proceeding of 27th IAEA-Fusion Energy Conferenc
Kinetic theory of geodesic acoustic modes in toroidal plasmas: a brief review
Geodesic acoustic modes (GAM) are oscillating zonal structures unique to
toroidal plasmas, and have been extensively studied in the past decades due to
their potential capabilities of regulating microscopic turbulences and
associated anomalous transport. This article reviews linear and nonlinear
theories of GAM; with emphases on kinetic treatment, system nonuniformity and
realistic magnetic geometry, in order to reflect the realistic experimental
conditions. Specifically, in the linear physics, the resonant wave-particle
interactions are discussed, with the application to resonant excitation by
energetic particles (EPs). The theory of EP-induced GAM (EGAM) is applied to
realistic devices for the interpretation of experimental observations, and
global effects due to coupling to GAM continuum are also discussed. Meanwhile,
in the nonlinear physics, the spontaneous GAM excitation by microscale
turbulences is reviewed, including the effects of various system
nonuniformities. A unified theoretical framework of GAM/EGAM is then
constructed based on our present understandings. The first-principle-based
GAM/EGAM theories reviewed here, thus, provide the tools needed for the
understanding and interpretation of experimental/numerical results.Comment: Submitted to Plasma Science and Technology. 27 pages, 19 figure
Design and Optimization of VoD schemes with Client Caching in Wireless Multicast Networks
Due to the explosive growth in multimedia traffic, the scalability of
video-on-demand (VoD) services becomes increasingly important. By exploiting
the potential cache ability at the client side, the performance of VoD
multicast delivery can be improved through video segment pre-caching. In this
paper, we address the performance limits of client caching enabled VoD schemes
in wireless multicast networks with asynchronous requests. Both reactive and
proactive systems are investigated. Specifically, for the reactive system where
videos are transmitted on demand, we propose a joint cache allocation and
multicast delivery scheme to minimize the average bandwidth consumption under
the zero-delay constraint. For the proactive system where videos are
periodically broadcasted, a joint design of the cache-bandwidth allocation
algorithm and the delivery mechanism is developed to minimize the average
waiting time under the total bandwidth constraint. In addition to the full
access pattern where clients view videos in their entirety, we further consider
the access patterns with random endpoints, fixed-size intervals and downloading
demand, respectively. The impacts of different access patterns on the
resource-allocation algorithm and the delivery mechanism are elaborated.
Simulation results validate the accuracy of the analytical results and also
provide useful insights in designing VoD networks with client caching.Comment: accepted by IEEE Transactions on Vehicular Technolog
Fine Structure Zonal Flow Excitation by Beta-induced Alfven Eigenmode
Nonlinear excitation of low frequency zonal structure (LFZS) by beta-induced
Alfven eigenmode (BAE) is investigated using nonlinear gyrokinetic theory. It
is found that electrostatic zonal flow (ZF), rather than zonal current, is
preferentially excited by finite amplitude BAE. In addition to the well-known
meso-scale radial envelope structure, ZF is also found to exhibit fine radial
structure due to the localization of BAE with respect to mode rational
surfaces. Specifically, the zonal electric field has an even mode structure at
the rational surface where radial envelope peaks.Comment: to be submitted to Nuclear Fusio
Exploiting Computation Replication for Mobile Edge Computing: A Fundamental Computation-Communication Tradeoff Study
Existing works on task offloading in mobile edge computing (MEC) networks
often assume a task is executed once at a single edge node (EN). Downloading
the computed result from the EN back to the mobile user may suffer long delay
if the downlink channel experiences strong interference or deep fading. This
paper exploits the idea of computation replication in MEC networks to speed up
the downloading phase. Computation replication allows each user to offload its
task to multiple ENs for repetitive execution so as to create multiple copies
of the computed result at different ENs which can then enable transmission
cooperation and hence reduce the communication latency for result downloading.
Yet, computation replication may also increase the communication latency for
task uploading, despite the obvious increase in computation load. The main
contribution of this work is to characterize asymptotically an order-optimal
upload-download communication latency pair for a given computation load in a
multi-user multi-server MEC network. Analysis shows when the computation load
increases within a certain range, the downloading time decreases in an
inversely proportional way if it is binary offloading or decreases linearly if
it is partial offloading, both at the expense of linear increase in the
uploading time.Comment: To appear in IEEE Transactions on Wireless Communication
Gyrokinetic theory of the nonlinear saturation of toroidal Alfven eigenmode
Nonlinear saturation of toroidal Alfven eigenmode (TAE) via ion induced
scatterings is investigated in the short-wavelength gyrokinetic regime. It is
found that the nonlinear evolution depends on the thermal ion \b{eta} value.
Here, \b{eta} is the plasma thermal to magnetic pressure ratio. Both the
saturation levels and associated energetic-particle transport coefficients are
derived and estimated correspondingly
An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining
Multi-task learning (MTL) has achieved remarkable success in natural language
processing applications. In this work, we study a multi-task learning model
with multiple decoders on varieties of biomedical and clinical natural language
processing tasks such as text similarity, relation extraction, named entity
recognition, and text inference. Our empirical results demonstrate that the MTL
fine-tuned models outperform state-of-the-art transformer models (e.g., BERT
and its variants) by 2.0% and 1.3% in biomedical and clinical domains,
respectively. Pairwise MTL further demonstrates more details about which tasks
can improve or decrease others. This is particularly helpful in the context
that researchers are in the hassle of choosing a suitable model for new
problems. The code and models are publicly available at
https://github.com/ncbi-nlp/bluebertComment: Accepted by BioNLP 202
BioSentVec: creating sentence embeddings for biomedical texts
Sentence embeddings have become an essential part of today's natural language
processing (NLP) systems, especially together advanced deep learning methods.
Although pre-trained sentence encoders are available in the general domain,
none exists for biomedical texts to date. In this work, we introduce
BioSentVec: the first open set of sentence embeddings trained with over 30
million documents from both scholarly articles in PubMed and clinical notes in
the MIMIC-III Clinical Database. We evaluate BioSentVec embeddings in two
sentence pair similarity tasks in different text genres. Our benchmarking
results demonstrate that the BioSentVec embeddings can better capture sentence
semantics compared to the other competitive alternatives and achieve
state-of-the-art performance in both tasks. We expect BioSentVec to facilitate
the research and development in biomedical text mining and to complement the
existing resources in biomedical word embeddings. BioSentVec is publicly
available at https://github.com/ncbi-nlp/BioSentVecComment: 5 pages, 3 tables and 2 figures accepted by The Seventh IEEE
International Conference on Healthcare Informatics (ICHI 2019
Short Wavelength Geodesic Acoustic Mode Excitation by Energetic Particles
Taking the collisionless damping of geodesic acoustic mode (GAM) as an
example, the physics processes underlying wave particle resonances in the short
wavelength limit are clarified. As illus- trative application, GAM excitation
by energetic particles in short wavelength limit is investigated assuming a
single pitch angle slowing-down fast ion equilibrium distribution function.
Conditions for this energetic particle-induced GAM (EGAM) to be unstable are
discussed.Comment: 4 pages, 2 figures. submitted to Physics of Plasma
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