Plasma current tomography for HL-2A based on Bayesian inference

An accurate plasma current profile has irreplaceable value for the steady-state operation of the plasma.In this study,plasma current tomography based on Bayesian inference is applied to an HL-2A device and used to reconstruct the plasma current profile.Two different Bayesian probability priors are tried,namely the Conditional Auto Regressive(CAR)prior and the Advanced Squared Exponential(ASE)kernel prior.Compared to the CAR prior,the ASE kernel prior adopts nonstationary hyperparameters and introduces the current profile of the reference discharge into the hyperparameters,which can make the shape of the current profile more flexible in space.The results indicate that the ASE prior couples more information,reduces the probability of unreasonable solutions,and achieves higher reconstruction accuracy.

LDA-ID:An LDA-Based Framework for Real-Time Network Intrusion Detection

Network intrusion poses a severe threat to the Internet.However,existing intrusion detection models cannot effectively distinguish different intrusions with high-degree feature overlap.In addition,efficient real-time detection is an urgent problem.To address the two above problems,we propose a Latent Dirichlet Allocation topic model-based framework for real-time network Intrusion Detection(LDA-ID),consisting of static and online LDA-ID.The problem of feature overlap is transformed into static LDA-ID topic number optimization and topic selection.Thus,the detection is based on the latent topic features.To achieve efficient real-time detection,we design an online computing mode for static LDA-ID,in which a parameter iteration method based on momentum is proposed to balance the contribution of prior knowledge and new information.Furthermore,we design two matching mechanisms to accommodate the static and online LDA-ID,respectively.Experimental results on the public NSL-KDD and UNSW-NB15 datasets show that our framework gets higher accuracy than the others.

Tomography of emissivity for Doppler coherence imaging spectroscopy diagnostic in HL-2A

A newly developed Doppler coherence imaging spectroscopy(CIS)technique has been implemented in the HL-2 A tokamak for carbon impurity emissivity and flow measurement.In CIS diagnostics,the emissivity and flow profiles inside the plasma are measured by a camera from the line-integrated emissivity and line-averaged flow,respectively.A standard inference method,called tomographic inversion,is necessary.Such an inversion is relatively challenging due to the ill-conditioned nature.In this article,we report the recent application and comparison of two different tomography algorithms,Gaussian process tomography and Tikhonov tomography,on light intensity measured by CIS,including feasibility and benchmark studies.Finally,the tomographic results for real measurement data in HL-2A are presented.

Gaussian process tomography based on Bayesian data analysis for soft x-ray and AXUV diagnostics on EAST

This work presents the Gaussian process tomography(GPT)based on Bayesian data analysis and its applications in soft x-ray(SXR)and absolute extreme ultraviolet spectroscopy(AXUV)diagnostics on experimental advanced superconducting tokamak(EAST).This is the first application of the GPT method in the AXUV diagnostic system in fusion devices.It is found that even if only horizontal detector arrays are used to reconstruct the two-dimensional(2D)distribution of SXR and AXUV emissivity fields,the GPT method performs robustly and extremely fast,which enables the GPT method to provide real-time feedback on impurity transport and fast magnetohydrodynamics(MHD)events.By reconstructing SXR emissivity in the poloidal cross section on EAST,an m/n=1/1 internal kink mode has been observed,and the plasma redistribution due to the kink mode is clearly visible in the reconstructions,where m is the poloidal mode number and n is the toroidal mode number.Sawtooth-like internal disruptions extended throughout the entire plasma core and mainly driven by the m/n=2/1 mode have been acquired.During the sawtooth-like internal disruption crash phase,the conversion from an m=2 mode to an m=1 mode is observed.Using the reconstructed AXUV emissivity field we were able to observe the process of impurity accumulated in the plasma core and the mitigation of core impurity due to neon injection in the plasma edge.The data from all other diagnostics involved in the analysis shows that the reconstructions from AXUV measurements are reliable.

Integrated data analysis on the electron temperature profile of HL-2A with the Bayesian probability inference method

Data analysis on tokamak plasmas is mainly based on various diagnostic systems,which are usually modularized and independent of each other.This leads to a large amount of data not being fully and effectively exploited so that it is not conducive to revealing the deep physical mechanism.In this work,Bayesian probability inference with machine learning methods have been applied to the electron cyclotron emission and Thomson scattering diagnostic systems on HL-2A/2M,and the effects of integrated data analysis(IDA)on the electron temperature of HL-2A with Bayesian probability inference are demonstrated.A program is developed to infer the whole electron temperature profile with a confidence interval,and the program can be applied in online analysis.The IDA results show that the full profile of the electron temperature can be obtained and the diagnostic information is more comprehensive and abundant with IDA.The inference models for electron temperature analysis are established and the developed programs will serve as an experimental data analysis tool for HL-2A/2M in the near future.

An elementary proof for the representation theorem of analytic isotropic tensor functions of a second-order tensor

Based on the Cayley-Hamilton theorem and fixed-point method,we provide an elementary proof for the representation theorem of analytic isotropic tensor functions of a second-order tensor in a three-dimensional(3D)inner-product space,which avoids introducing the generating function and Taylor series expansion.The proof is also extended to any finite-dimensional inner-product space.

Lensless polarimetric coded ptychography for high-resolution,high-throughput gigapixel birefringence imaging on a chip

Polarimetric imaging provides valuable insights into the polarization state of light interacting with a sample.It can infer crucial birefringence properties of specimens without using labels,thereby facilitating the diagnosis of diseases such as cancer and osteoarthritis.In this study,we present a novel polarimetric coded ptychography(pol-CP)approach that enables high-resolution,high-throughput gigapixel birefringence imaging on a chip.Our platform deviates from traditional lens-based systems by employing an integrated polarimetric coded sensor for lensless coherent diffraction imaging.Utilizing Jones calculus,we quantitatively determine the birefringence retardance and orientation information of biospecimens from the recovered images.Our portable pol-CP prototype can resolve the 435 nm linewidth on the resolution target,and the imaging field of view for a single acquisition is limited only by the detector size of 41 mm2.The prototype allows for the acquisition of gigapixel birefringence images with a 180 mm^(2) field of view in~3.5 min,a performance that rivals high-end whole slide scanner but at a small fraction of the cost.To demonstrate its biomedical applications,we perform high-throughput imaging of malaria-infected blood smears,locating parasites using birefringence contrast.We also generate birefringence maps of label-free thyroid smears to identify thyroid follicles.Notably,the recovered birefringence maps emphasize the same regions as autofluorescence images,underscoring the potential for rapid on-site evaluation of label-free biopsies.Our approach provides a turnkey and portable solution for lensless polarimetric analysis on a chip,with promising applications in disease diagnosis,crystal screening,and label-free chemical imaging,particularly in resource-constrained environments.

Synthetic aperture ptychography:coded sensor translation for joint spatial-Fourier bandwidth expansion

Conventional ptychography translates an object through a localized probe beam to widen the field of view in real space.Fourier ptychography translates the object spectrum through a pupil aperture to expand the Fourier bandwidth in reciprocal space.Here we report an imaging modality,termed synthetic aperture ptychography(SAP),to get the best of both techniques.In SAP,we illuminate a stationary object using an extended plane wave and translate a coded image sensor at the far field for data acquisition.The coded layer attached on the sensor modulates the object exit waves and serves as an effective ptychographic probe for phase retrieval.The sensor translation process in SAP synthesizes a large complex-valued wavefront at the intermediate aperture plane.By propagating this wavefront back to the object plane,we can widen the field of view in real space and expand the Fourier bandwidth in reciprocal space simultaneously.We validate the SAP approach with transmission targets and reflection silicon microchips.A 20-mm aperture was synthesized using a 5-mm sensor,achieving a fourfold gain in resolution and 16-fold gain in field of view for object recovery.In addition,the thin sample requirement in ptychography is no longer required in SAP.One can digitally propagate the recovered exit wave to any axial position for post-acquisition refocusing.The SAP scheme offers a solution for far-field sub-diffraction imaging without using lenses.It can be adopted in coherent diffraction imaging setups with radiation sources from visible light,extreme ultraviolet,and X-ray,to electron.

Recent advances in high-β_(N) experiments and magnetohydrodynamic instabilities with hybrid scenarios in the HL-2A Tokamak

Over the past several years,high-β_(N) experiments have been carried out on HL-2A.The high-β_(N) is realized using double transport barriers(DTBs)with hybrid scenarios.A stationary high-β_(N) (>2)scenario was obtained by pure neutral-beam injection(NBI)heating.Transient high performance was also achieved,corresponding to β_(N)≥3,ne/ne_(G)∼0.6,H_(98)∼1.5,f_(bs)∼30%,q_(95)∼4.0,and𝐺∼0.4.The high-β_(N) scenario was successfully modeled using integrated simulation codes,that is,the one modeling framework for integrated tasks(OMFIT).In high-𝛽𝑁plasmas,magnetohydrodynamic(MHD)instabilities are abundant,including low-frequency global MHD oscilla-tion with n=1,high-frequency coherent mode(HCM)at the edge,and neoclassical tearing mode(NTM)and Alfvénic modes in the core.In some high-β_(N) discharges,it is observed that the NTMs with m/n=3/2 limit the growth of the plasma energy and decrease β_(N).The low-n global MHD oscillation is consistent with the coupling of destabilized internal(m/n=1/1)and external(m/n=3/1 or 4/1)modes,and plays a crucial role in triggering the onset of ELMs.Achieving high-β_(N) on HL-2A suggests that core-edge interplay is key to the plasma confinement enhancement mechanism.Experiments to enhance β_(N) will contribute to future plasma operation,such as international thermonuclear experimental reactor.

A behavior-aware SLA-based framework for guaranteeing the security conformance of cloud service

As cloud computing technology turning to mature,cloud services have become a trust-based service.Users'distrust of the security and performance of cloud services will hinder the rapid deployment and development of cloud services.So cloud service providers(CSPs)urgently need a way to prove that the infrastructure and the behavior of cloud services they provided can be trusted.The challenge here is how to construct a novel framework that can effective verify the security conformance of cloud services,which focuses on fine-grained descriptions of cloud service behavior and security service level aggreements(SLAs).In this paper,we propose a novel approach to verify cloud service security conformance,which reduces the description gap between the CSP and users through modeling cloud service behavior and security SLA,these models enable a systematic integration of security constraints and service behavior into cloud while using UPPAAL to check the performance and security conformance.The proposed approach is validated through case study and experiments with real cloud service based on Open-Stack,which illustrates CloudSec approach effectiveness and can be applied on realistic cloud scenario.