CExp： secure and verifiable outsourcing of composite modular exponentiation with single untrusted server

Outsnurcing computing allows users with resource-constrained devices tn outsnurce their complex computation wnrkloads to cloud servers that may not be honest. In this paper, we propose a new algorithm for securing the outsourcing of composite modnlar exponentiation, which is one of the most complex computing tasks in discrete- log based cryptographic protocols. Unlike algorithms based on two untrusted servers, we outsnurce modular expnnentiation operation to only a single server, which eliminates the potential for a cnllusinn attack when using two servers. Moreover, our proposed algorithm can hide the base and exponent of the outsourced data, which prevents the exposure of sensitive information to clnud servers. In addition, compared with the state-of-the-art algorithms, our scheme has remarkably better checkability, The user could detect any misbehavior with a probability of one if the server returns a fault result.

An Optimized Cross Correlation Power Attack of Message Blinding Exponentiation Algorithms

The message blinding method is the most efficient and secure countermeasure against first-order differential power analysis(DPA).Although cross correlation attacks(CCAs) were given for defeating message blinding methods,however searching for correlation points is difficult for noise,misalignment in practical environment.In this paper,we propose an optimized cross correlation power attack for message blinding exponentiation algorithms.The attack method can select the more correlative power points of share one operation in the modular multiplication by comparing variances between correlation coefficients.Further we demonstrate that the attack method is more efficient in experiments with hardware implementation of RSA on a crypto chip card.In addition to the proposed CCA method can recovery all 1024 bits secret key and recognition rate increases to 100%even when the recorded signals are noisy.

基于改进YOLOv8-CEFG的垃圾检测算法研究

随着我国经济的高速发展和人口的急剧增加,生活垃圾污染问题日益突出。然而,传统的人工垃圾检测方法效率低且主观性强。为提高复杂场景下垃圾检测的准确率,文章提出了一种基于改进YOLOv8的垃圾检测模型。为提升检测精度和识别效果,引入了EMA(Exponential Moving Average)注意力机制。实验结果显示,YOLOv8-CEFG在垃圾检测数据集上表现优异,最终其mAP达到了88.8%,比原始YOLOv8模型提高了3.1%。YOLOv8-CEFG算法能较好地满足实时检测任务的需求,并展示了良好的检测效果。

A LOW-REGULARITY FOURIER INTEGRATOR FOR THE DAVEY-STEWARTSON II SYSTEM WITH ALMOST MASS CONSERVATION

In this work,we propose a low-regularity Fourier integrator with almost mass conservation to solve the Davey-StewartsonⅡsystem(hyperbolic-elliptic case).Arbitrary order mass convergence could be achieved by the suitable addition of correction terms,while keeping the first order accuracy in H~γ×H^(γ+1)for initial data in H^(γ+1)×H^(γ+1)withγ>1.The main theorem is that,up to some fixed time T,there exist constantsτ_(0)and C depending only on T and‖u‖_(L^(∞)((0,T);H^(γ+1)))such that,for any 0<τ≤τ_(0),we have that‖u(t_(n),·)-u^(n)‖H_γ≤C_(τ),‖v(t_(n),·)-v^(n)‖_(Hγ+1)≤C_(τ),where u^(n)and v^(n)denote the numerical solutions at t_(n)=nτ.Moreover,the mass of the numerical solution M(u^(n))satisfies that|M(u^(n))-M(u_0)|≤Cτ~5.

Efficiency of a Modular Cleanroom for Space Applications

A prototype cleanroom for hazardous testing and handling of satellites prior to launcher encapsulation,satisfying the ISO8 standard has been designed and analyzed in terms of performances.Unsteady Reynolds Averaged Navier-Stokes(URANS)models have been used to study the related flow field and particulate matter(PM)dispersion.The outcomes of the URANS models have been validated through comparison with equivalent large-eddy simulations.Special attention has been paid to the location and shape of the air intakes and their orientation in space,in order to balance the PM convection and diffusion inside the cleanroom.Forming a cyclone-type flow pattern inside the cleanroom is a key to maintaining a high ventilation efficiency.

Equivalence between the internal observability and equation

This paper is concerned with a third order in time linear Moore-Gibson-Thompson equation which describes the acoustic velocity potential in ultrasound wave program.Influenced by the work of Kaltenbacher,Lasiecka and Marchand(Control Cybernet.2011,40:971-988),we establish an observability inequality of the conservative problem,and then discuss the equivalence between the exponential stabilization of a dissipative system and the internal observational inequality of the corresponding conservative system.

Exponentially Convergent Multiscale Finite Element Method

We provide a concise review of the exponentially convergent multiscale finite element method(ExpMsFEM)for efficient model reduction of PDEs in heterogeneous media without scale separation and in high-frequency wave propagation.The ExpMsFEM is built on the non-overlapped domain decomposition in the classical MsFEM while enriching the approximation space systematically to achieve a nearly exponential convergence rate regarding the number of basis functions.Unlike most generalizations of the MsFEM in the literature,the ExpMsFEM does not rely on any partition of unity functions.In general,it is necessary to use function representations dependent on the right-hand side to break the algebraic Kolmogorov n-width barrier to achieve exponential convergence.Indeed,there are online and offline parts in the function representation provided by the ExpMsFEM.The online part depends on the right-hand side locally and can be computed in parallel efficiently.The offline part contains basis functions that are used in the Galerkin method to assemble the stiffness matrix;they are all independent of the right-hand side,so the stiffness matrix can be used repeatedly in multi-query scenarios.

Approximation Properties of Vectorial Exponential Functions

This contribution is dedicated to the celebration of Rémi Abgrall’s accomplishments in Applied Mathematics and Scientific Computing during the conference“Essentially Hyperbolic Problems:Unconventional Numerics,and Applications”.With respect to classical Finite Elements Methods,Trefftz methods are unconventional methods because of the way the basis functions are generated.Trefftz discontinuous Galerkin(TDG)methods have recently shown potential for numerical approximation of transport equations[6,26]with vectorial exponential modes.This paper focuses on a proof of the approximation properties of these exponential solutions.We show that vectorial exponential functions can achieve high order convergence.The fundamental part of the proof consists in proving that a certain rectangular matrix has maximal rank.

Enhanced Differentiable Architecture Search Based on Asymptotic Regularization

In differentiable search architecture search methods,a more efficient search space design can significantly improve the performance of the searched architecture,thus requiring people to carefully define the search space with different complexity according to various operations.Meanwhile rationalizing the search strategies to explore the well-defined search space will further improve the speed and efficiency of architecture search.With this in mind,we propose a faster and more efficient differentiable architecture search method,AllegroNAS.Firstly,we introduce a more efficient search space enriched by the introduction of two redefined convolution modules.Secondly,we utilize a more efficient architectural parameter regularization method,mitigating the overfitting problem during the search process and reducing the error brought about by gradient approximation.Meanwhile,we introduce a natural exponential cosine annealing method to make the learning rate of the neural network training process more suitable for the search procedure.Moreover,group convolution and data augmentation are employed to reduce the computational cost.Finally,through extensive experiments on several public datasets,we demonstrate that our method can more swiftly search for better-performing neural network architectures in a more efficient search space,thus validating the effectiveness of our approach.

Charting the course:India's health expenditure projections for 2035

Objectives Understanding past trends and forecasting future changes in health spending is vital for planning and reducing reliance on out-of-pocket(OOP)expenses.The current study analyzed health expenditure patterns in India and forecasted future trends and patterns until 2035.Methods Data on health expenditure in India from 2000 to 2019 was collected from the Organisation for Economic Co-operation and Development(OECD)iLibrary and National Health Accounts 2019 databases.Gross domestic product(GDP)data from the World Bank was also utilized.Descriptive statistics analyzed the composition and pattern,while the exponential smoothing model forecasted future health expenditures.Results The findings revealed that expenditure made by OOP is the primary health financing source,followed by government and pre-paid private spending.The percentage of GDP allocated to total health expenditure remains stable,while the per capita health expenditure fluctuates.Variations in expenditure among states are observed,with Karnataka relying heavily on pre-paid private coverage.Future projections suggest a decline in per capita and total health expenditure as a share of GDP,with a slight increase in the government’s share.Pre-paid private expenditure per capita and OOP health expenditure as a share of the total is projected to remain relatively constant but still high in absolute terms.Conclusion The study highlights variations in health spending in India,characterized by high OOP spending,limited public coverage,and a need for investments,and reforms to improve healthcare access and equity.

Influencing Factors and Prediction of Risk of Returning to Ecological Poverty in Liupan Mountain Region,China

China has resolved its overall regional poverty in 2020 by attaining moderate societal prosperity.The country has entered a new development stage designed to achieve its second centenary goal.However,ecological fragility and risk susceptibility have increased the risk of returning to ecological poverty.In this paper,the Liupan Mountain Region of China was used as a case study,and the counties were used as the scale to reveal the spatiotempora differentiation and influcing factors of the risk of returning to poverty in study area.The indicator data for returning to ecological poverty from 2011-2020 were collected and summarized in three dimensions:ecological,economic and social.The autoregressive integrated moving average model(ARIMA)time series and exponential smoothing method(ES)were used to predict the multidimensional indicators of returning to ecological poverty for 61 counties(districts)in the Liupan Mountain Region for 2021-2030.The back propagation neural network(BPNN)and geographic information system(GIS)were used to generate the spatial distribution and time variation for the index of the risk of returning to ecological poverty(RREP index).The results show that 1)ecological factors were the main factors in the risk of returning to ecological poverty in Liupan Mountain Region.2)The RREP index for the 61 counties(districts)exhibited a downward trend from 2021-2030.The RREP index declined more in medium-and high-risk areas than in low-risk areas.From 2021 to 2025,the RREP index exhibited a slight downward trend.From 2026 to2030,the RREP index was expected to decline faster,especially from 2029-2030.3)Based on the RREP index,it can be roughly divided into three types,namely,the high-risk areas,the medium-risk areas,and the low-risk areas.The natural resource conditions in lowrisk areas of returning to ecological poverty,were better than those in medium-and high-risk areas.

Mixed convectional and chemical reactive flow of nanofluid with slanted MHD on moving permeable stretching/shrinking sheet through nonlinear radiation,energy omission

Hybrid nanofluids are remarkable functioning liquids that are intended to reduce the energy loss while maximizing the heat transmission.In the involvement of suction and nonlinear thermal radiation effects,this study attempted to explore the energy transmission features of the inclined magnetohydrodynamic(MHD)stagnation flow of CNTs-hybrid nanofluid across the nonlinear permeable stretching or shrinking sheet.This work also included some noteworthy features like chemical reactions,variable molecular diffusivity,quadratic convection,viscous dissipation,velocity slip and heat omission assessment.Employing appropriate similarity components,the model equations were modified to ODEs and computed by using the HAM technique.The impact of various relevant flow characteristics on movement,heat and concentration profiles was investigated and plotted on a graph.Considering various model factors,the significance of drag friction,heat and mass transfer rate were also computed in tabular and graphical form.This leads to the conclusion that such factors have a considerable impact on the dynamics of fluid as well as other engineering measurements of interest.Furthermore,viscous forces are dominated by increasing the values ofλ_(p),δ_(m)andδ_(q),and as a result,F(ξ)accelerates while the opposite trend is observed for M andφ.The drag friction is boosted by the augmentation M,λ_(p)andφ,but the rate of heat transfer declined.According to our findings,hybrid nanoliquid effects dominate that of ordinary nanofluid in terms of F(ξ),Θ(ξ)andφ(ξ)profiles.The HAM and the numerical technique(shooting method)were found to be in good agreement.

Reviewing Stability Criteria for Positive Homogeneous Systems and Adding One for Discrete-Time Cases with Degree Less Than One

The article synthesizes and presents the results regarding the stability of positive homogeneous systems that have been researched and published in recent years. Next, we provide a sufficient condition for global exponential stability in the case of discrete-time positive homogeneous systems with an order less than one with time-varying delays.

The Maximum and Minimum Value of Exponential RandićIndices of Quasi-Tree Graph

The exponential Randić index has important applications in the fields of biology and chemistry. The exponential Randić index of a graph G is defined as the sum of the weights e 1 d( u )d( v ) of all edges uv of G, where d( u ) denotes the degree of a vertex u in G. The paper mainly provides the upper and lower bounds of the exponential Randić index in quasi-tree graphs, and characterizes the extremal graphs when the bounds are achieved.

THE GROWTH OF SOLUTIONS TO HIGHER ORDER DIFFERENTIAL EQUATIONS WITH EXPONENTIAL POLYNOMIALS AS ITS COEFFICIENTS

By looking at the situation when the coefficients Pj(z)(j=1,2,…,n-1)(or most of them) are exponential polynomials,we investigate the fact that all nontrivial solutions to higher order differential equations f((n))+Pn-1(z)f((n-1))+…+P0(z)f=0 are of infinite order.An exponential polynomial coefficient plays a key role in these results.

Optimal Quota-Share and Excess-of-Loss Reinsurance and Investment with Heston’s Stochastic Volatility Model

An optimal quota-share and excess-of-loss reinsurance and investment problem is studied for an insurer who is allowed to invest in a risk-free asset and a risky asset.Especially the price process of the risky asset is governed by Heston's stochastic volatility(SV)model.With the objective of maximizing the expected index utility of the terminal wealth of the insurance company,by using the classical tools of stochastic optimal control,the explicit expressions for optimal strategies and optimal value functions are derived.An interesting conclusion is found that it is better to buy one reinsurance than two under the assumption of this paper.Moreover,some numerical simulations and sensitivity analysis are provided.

A Numerical Investigation Based on Exponential Collocation Method for Nonlinear SITR Model of COVID-19

In this work,the exponential approximation is used for the numerical simulation of a nonlinear SITR model as a system of differential equations that shows the dynamics of the new coronavirus(COVID-19).The SITR mathematical model is divided into four classes using fractal parameters for COVID-19 dynamics,namely,susceptible(S),infected(I),treatment(T),and recovered(R).The main idea of the presented method is based on the matrix representations of the exponential functions and their derivatives using collocation points.To indicate the usefulness of this method,we employ it in some cases.For error analysis of the method,the residual of the solutions is reviewed.The reported examples show that the method is reasonably efficient and accurate.

Low-field, high-gradient NMR shows diffusion contrast consistent with localization or motional averaging of water near surfaces

Nuclear magnetic resonance(NMR)measurements of water diffusion have been extensively used to probe microstructure in porous materials,such as biological tissue,however primarily using pulsed gradient spin echo(PGSE)methods.Low-field single-sided NMR systems have built-in static gradients(SG)much stronger than typical PGSE maximum gradient strengths,which allows for the signal attenuation at extremely high b-values to be explored.Here,we perform SG spin echo(SGSE)and SG stimulated echo(SGSTE)diffusion measurements on biological cells,tissues,and gels.Measurements on fixed and live neonatal mouse spinal cord,lobster ventral nerve cord,and starved yeast cells all show multiexponential signal attenuation on a scale of b with significant signal fractions observed at b×Do>1 with b as high as 400 ms/um2.These persistent signal fractions trend with surface-to-volume ratios for these systems,as expected from porous media theory.An exception found for the case of fixed vs.live spinal cords was attributed to faster exchange or permeability in live spinal cords than in fixed spinal cords on the millisecond timescale.Data suggests the existence of multiple exchange processes in neural tissue,which may be relevant to the modeling of time-dependent diffusion in gray matter.The observed multi-exponential attenuation is from protons on water and not macromolecules because it remains proportional to the normalized signal when a specimen is washed with D20.The signal that persists to b×Do>1 is also drastically reduced after delipidation,indicating that it originates from lipid membranes that restrict water diffusion.The multiexponential or stretched exponential character of the signal attenuation at b×Do>1 appears mono-exponential when viewed on a scale of(b×Do)/3,suggesting it may originate from localization or motional averaging of water near membranes on sub-micron length scales.To try to disambiguate these two contributions,signal attenuation curves were compared at varying temperatures.While the curves align when normalizing them using the localization length scale,they separate on a motional averaging length scale.This supports localization as the source of non-Gaussian displacements,but this interpretation is still provisional due to the possible confounds of heterogeneity,exchange,and relaxation.Measurements on two types of gel phantoms designed to mimic extracellular matrix.one with charged functional groups synthesized from polyacrylic acid(PAC)and another with uncharged functional groups synthesized from polyacrylamide(PAM),both exhibit signal at b×Do>1,potentially due to water interacting with macromolecules.These preliminary finding motivate future research into contrast and attenuation mechanisms in tissue with low-field,high-gradient NMR。

Forecasting Stock Prices with an Integrated Approach Combining ARIMA and Machine Learning Techniques ARIMAML

Stock market prediction has long been an area of interest for investors, traders, and researchers alike. Accurate forecasting of stock prices is crucial for financial decision-making and risk management. This paper presents a novel approach to predict stock prices by integrating Autoregressive Integrated Moving Average (ARIMA) and Exponential smoothing and Machine Learning (ML) techniques. Our study aims to enhance the predictive accuracy of stock price forecasting, which can significantly impact investment strategies and economic growth in this research paper implement the ARIMAML proposed method to predict the stock prices for Investment Bank of Iraq.

Vertical deformation model on postseismic phase using exponential and logarithmic function based on InSAR

The Palu MW7.4 earthquake occurred on September 28, 2018, with the epicenter at 119.86°, 0.72°. The severe shaking caused severe damage in Central Sulawesi, especially in Palu. We conducted a postseismic deformation study to determine the deformation pattern and reduce future earthquakes’ impact.Interferometric Synthetic Aperture Radar(In SAR) data were processed using Li CSBAS to get the time series. The time series data were fitted to exponential and logarithmic functions to determine the mechanism of postseismic deformation. The exponential model identified the influence of the viscoelastic mechanism, and the logarithm identified the afterslip mechanism. The Palu earthquake was fitted to logarithmic and exponential, but the logarithmic was more significant than an exponential function.Afterslip mechanism predominates, and viscoelastic mechanisms play a minor role in this postseismic deformation.