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