Class Of Schemes Research Articles

Privacy-Preserving Range Query Quantum Scheme With Single Photons in Edge-Based Internet of Things

Range query in cloud-based outsourcing applications is an important data search service, but it can suffer from privacy disclosure. In this paper, we generalize and redefine privacy-preserving range query in edge-based Internet of Things (IoT). Furthermore, to enhance security and privacy of sensitive data, we introduce quantum cryptographic technologies and present a novel quantum approach to solve the problem. First, we present a feasible protocol for Quantum Secret Permutating (QSP) with single photons, which will be later utilized in the final scheme as a basic block. Second, we generalize traditional privacy-preserving range query to a secure one-sided two-party computation, i.e., specific dot product. Third, we present a synchronously grouping strategy based on Quantum Key Distribution (QKD) to reduce the complexity and improve the efficiency of solving this two-party computation, so that it can easily get the desired result by repeatedly using feasible quantum privacy query group by group. Finally, adopting our previously proposed quantum protocols, we design privacy-preserving range query quantum scheme in edge-based IoT. Compared with the classical related schemes, our proposed quantum scheme has higher security, because the security of our proposed protocols is based on the basic physical principles of quantum mechanics, instead of unproven computational difficulty assumptions.

Hyperbolic modeling of gradient damage and one-dimensional finite volume simulations

This study provides a new formulation of gradient damage model which allows an efficient explicit numerical solution of dynamics problems. The proposed methodology is based on an ”extended Lagrangian approach” developed by one of the authors for the nondissipative and dispersive shallow water equation. By using this strategy, the global minimization problem commonly derived for gradient damage models is recast as a purely local hyperbolic one with source terms that can be easily solved using finite volumes. The numerical solution of the governing system is then based on a fractional-step method consisting of a classical Godunov-type scheme and an implicit Ordinary Differential Equation solver for the local source terms. Numerical results are presented on one-dimensional multi-fragmentation and spalling tests for illustration purpose.

Fractional-order numerical modeling to study chloride ion transport in concrete with fly ash or slag additions.

To better study the chloride ion migration in concrete with fly ash or ground granulated blast furnace slag under low fatigue load, a Caputo time fractional-order chloride diffusion model is developed in this paper. The model, grounded in Fick's second law with a fractional-order derivative, employs an implicit numerical method for discretization, resulting in a fractional-order numerical scheme. The stability and convergence of the scheme are rigorously proven within the paper. The model's unknown parameters are estimated using genetic algorithm with a grid method. To validate the model's effectiveness, its numerical solution is juxtaposed with experimental results from chloride erosion studies. Furthermore, the fitting efficacy of the Caputo time fractional-order numerical scheme is compared with that of the classical Fick's second law numerical scheme and analytical solution. The research findings demonstrate that the fractional-order numerical scheme can more accurately simulate the chloride concentration in concrete containing fly ash or slag. Additionally, the model shows promise in predicting the service life of fly ash or slag concrete.

Attribute and User Trust Score-Based Zero Trust Access Control Model in IoV

The Internet of Vehicles (IoV) is an innovative area of interest in modern mobility that is rapidly evolving while facing complex challenges. Traditional IoV networks are susceptible to intrusion threats, which can lead to data leakage and seizure of vehicle control by attackers, thereby endangering vehicle users’ privacy and personal safety. An Attribute and User Trust Score-based Zero Trust Access Control Model (AU-ZTAC) is proposed, combining the zero-trust and attribute-based access control models to meet network protection requirements while achieving fine-grained dynamic access control and incorporating trust evaluation in the access control process to better reflect users’ intent. Experimental results demonstrate the effectiveness and feasibility of trust assessment through the proposed model. A comparison with the classical schemes illustrates that AU-ZTAC allows for more flexible and fine-grained access control in complex access control environments while improving IoV security.

A class of bound-preserving MUSCL-Hancock schemes in two dimensions

In this paper we discuss the MUSCL-Hancock scheme for the two-dimensional conservation laws and derive the bound-preserving conditions by a parameterized convex decomposition method which is proposed in [Journal of Computational Physics, 474:111805, 2023] for one-dimensional problems. The CFL number equals the half of the one-dimensional value and then ensures the speed-up compared with the classical two-stage MUSCL scheme. The bound-preserving slope limiter on the preliminary reconstruction becomes problem dependent. The maximum-minimum preserving slope limiter for the scalar problems becomes the same with its one-dimensional version. A positivity-preserving slope limiter for the Euler system is designed including a different parameter from the scalar problems and more efficient operators than the existing limiters. Numerical experiments are reported to demonstrate the robustness of the proposed scheme.

Statistical Validation of a Physical Prime Random Number Generator Based on Quantum Noise

Random prime numbers are an essential resource for many asymmetric cryptographic protocols. However, despite the emerging popularity of quantum random number generators (QRNGs) as sources of secure randomness, physical prime number generators have not yet been explored. In this work, we experimentally implement and characterize a vacuum-based probabilistic prime number generation scheme with an error probability of 3.5×10−15. By removing the quantum source (QS), an additional scheme based on electronic noise is derived, and a comparative analysis for increasing prime lengths is made. We observed that the QS significantly outperforms the classical scheme for small prime generation, where increases up to 585.0% in the diversity of unique primes obtained are seen. Moreover, we propose a length-agnostic statistical test for prime number sequences and apply it to the output of the uniformized randomness source, which was successful in revealing underlying biases in the output prime distributions. The resultant sequences were subsequently submitted to the NIST statistical test suite, where the quantum and classical sources passed, respectively, 86.96% and 45.34% of the total test set applied.

Stuart Hall and the Introduction of Althusser in Cultural Studies: A Thinker of Difference

This article focuses on Stuart Hall’s reading of Louis Althusser’s main theoretical works. Since the early 1970s, Hall has undertaken a critical confrontation with Althusser’s ‘structural Marxism’, rescuing those useful concepts to think cultural difference and identity, without failing to criticize his ‘superstructuralist’ interpretation of Marx. However, what Hall will retain as Althusser’s most important contribution is, above all, his theory of ideology. In this context, I follow an idea formulated by Hall that could be read as summarizing the theoretical and political scope of Althusser’s contribution to Cultural Studies: ‘he enabled me to live in and with difference’. By complicating classical interpretations schemes in the Marxist tradition, Hall’s Althusser may be read as a ‘thinker of difference’ who opens up a whole research program to reconsider class conflicts as traversed (or ‘overdetermined’) by gender, racial or colonial conflicts.

High-order adaptive multiresolution wavelet upwind schemes for hyperbolic conservation laws

We present a novel system of high-order adaptive multiresolution wavelet collocation upwind schemes, implemented in a meshfree framework, for solving hyperbolic conservation laws. Our approach constructs asymmetrical wavelet bases with interpolation properties to achieve the upwind property and address nonlinearities in hyperbolic problems. An adaptive algorithm based on multiresolution analysis in wavelet theory is designed to capture moving shock waves and identify new localized steep regions. To suppress the Gibbs phenomenon, we propose an integration average reconstruction method based on the Lebesgue differentiation theorem. These numerical techniques enable the wavelet collocation upwind scheme to provide a general framework for devising satisfactory adaptive wavelet upwind methods with high-order accuracy. We perform several benchmark tests for 1D hyperbolic problems to verify the accuracy and efficiency of the proposed wavelet schemes. Notably, our wavelet collocation upwind schemes successfully solve the two interacting blast waves problem when discretizing the spatial derivatives in the physical space directly. This is in contrast to classical high-order schemes that usually involve transforming variables back and forth between physical and characteristic spaces with many local projections. Our results indicate the robustness, stability, and efficiency of our proposed schemes for strong shock wave interaction problems.

Iterative Equalization and Decoding over an Additive White Gaussian Noise Channel with ISI Using Low-Density Parity-Check Codes

In this article we present an iterative system of equalization and decoding to manage the intersymbol interference over an additive white Gaussian noise (AWGN) channel. Following the classic turbo equalization scheme, the proposed system consists of low-density parity-check (LDPC) coding at the transmitter side; we applied a Log maximum a posteriori probability (Log-MAP) equalizer and min-sum LDPC decoding at the receiver side. The equalizer and decoder, linked through interleaving and deinterleaving, iteratively update each other’s information. We performed the performance analysis of the proposed system, bit error rate (BER) vs. signal-to-noise ratio (SNR), considering three different impulse responses of the channel (h). Our experimental results indicated that increasing the number of iterations performed by the LDPC decoder from 10 to 20 during the iterative process of equalization and decoding leads to better outcomes. The proposed system was compared with turbo equalization and separate equalization, performed before the decoding process with minimum mean-square error (MMSE) and LDPC decoding, in terms of BER vs. SNR, considering the three different h. Based on the analyzed results, it can be concluded that the equalization performance depends on both the impulse responses of the channel and the chosen decoding and equalization method; therefore, the equalization method does not always offer good results for any h.

Quantum-resistant Transport Layer Security

The reliance on asymmetric public key cryptography (PKC) and symmetric encryption for cyber-security in current telecommunication networks is threatened by the emergence of powerful quantum computing technology. This is due to the ability of quantum computers to efficiently solve problems such as factorization or discrete logarithms, which are the basis for classical PKC schemes. Thus, the assumption that communications networks are secure no longer holds true. Quantum Key Distribution (QKD) and post-quantum cryptography (PQC) are the first cyber-security technologies that allow communications to resist the attacks of a quantum computer. To achieve quantum-resistant communications, the aforementioned technologies need to be incorporated into a network security protocol such as Transport Layer Security (TLS). In this paper, we describe and implement two novel, hybrid solutions in which QKD and PQC are combined inside TLS for achieving quantum-resistant authenticated key exchange: Concatenation and Exclusively-OR (XOR). We present the results, in terms of complexity and security enhancement, of integrating state-of-the-art QKD and PQC technologies into a practical, industry-ready TLS implementation. Our findings demonstrate that the adoption of a PQC-only approach enhances the TLS handshake performance by approximately 9% compared to classical methods. Furthermore, our hybrid PQC-QKD quantum-resistant TLS comes at a performance cost of approximately 117% during the key establishment process. In return, we substantially augment the security of the handshake, paving the road for the development of future-proof quantum-resistant communication systems based on QKD and PQC.

Finite element numerical schemes for a chemo-attraction and consumption model

This work is devoted to design and study efficient and accurate numerical schemes to approximate a chemo-attraction model with consumption effects, which is a nonlinear parabolic system for two variables; the cell density and the concentration of the chemical signal that the cell feel attracted to.We present several finite element schemes to approximate the system, detailing the main properties of each of them, such as conservation of cells, energy-stability and approximated positivity. Moreover, we carry out several numerical simulations to study the efficiency of each of the schemes and to compare them with others classical schemes.

Security analysis of the Classic McEliece, HQC and BIKE schemes in low memory

With the advancement of NIST PQC standardization, three of the four candidates in Round 4 are code-based schemes, namely Classic McEliece, HQC and BIKE. Currently, one of the most important tasks is to further analyze their security levels for the suggested parameter sets. At PKC 2022, Esser and Bellini restated the major information set decoding (ISD) algorithms by using nearest neighbor technique and then applied these ISD algorithms to estimate the bit security of Classic McEliece, HQC and BIKE under the suggested parameter sets. However, all major ISD algorithms consume a large amount of memory, which in turn affects their time complexities. In this paper, we theoretically reestimate the security levels of the parameter sets suggested by these three schemes in low memory by applying K-list sum algorithms to ISD framework. Compared with Esser–Bellini’s algorithms, our results achieve the best gains for Classic McEliece, HQC, and BIKE, with reductions in security levels of 11.09, 12.64, and 12.19 bits, respectively.

New simple local smoothness indicators for fifth-order WENO schemes simulating compressible flows

For the WENO-Z scheme, the structure of the local smoothness indicators has a significant impact on the computational performance of the weighted essentially non-oscillatory scheme with a given global smoothness indicator. In this paper, a new class of two-parameter local smoothness indicators is constructed by combining the classical fifth-order WENO-JS and WENO-UD5 schemes and locally appending the coefficients of the higher-order terms of the new local smoothness indicators. A new WENO scheme, WENO-NSLI, is constructed using the global smoothness indicators of WENO-UD5. Numerical experiments show that the new scheme can achieve optimal accuracy at the critical point when the parameter (λ,μ)=(0.5,10) is taken and has a higher resolution than WENO-JS, WENO-Z, and WENO-UD5.

Complexity and algorithm of setting optimal location for data sink in real-time NOMA-based IIoTs

Real-time performance is one of the most vital metrics in Non-Orthogonal Multiple Access (NOMA) based Industrial Internet of Things (IIoTs) applications. Since the relative geographic relationship between data sink and wireless sensors affects the transmission parallelism and thus the real-time performance, setting a reasonable location for the data sink is thus a feasible way to high real-time performance for applications where the locations of wireless sensors are fixed. In this paper, we consider how to find an optimal location for the data sink to minimize average access delay. We first formulate the problem and prove it to be NP-Complete by presenting an original reduction proof from classic set partition problem. Second, by tightening the NOMA decoding constraint of the original problem, a heuristic algorithm, which is designed based on Apollonian Circle Theorem and Dilworth Theorem, obtains a feasible location for the data sink. Simulation results reveal that the real-time performance loss of the heuristic algorithm is no more than 50% of the best one. Compared with the classic TDMA scheme, the real-time performance increases by more than 60% for some typical settings, and it can even reach 70% for the linear network topology, owing to the full exploitation of NOMA parallelism.

Analysis of rotational Doppler shift with multi-ring vortex beams.

Vortex beams (VBs) with orbital angular momentum have shown great potential in the detection of transverse rotational motion of spatial targets which is undetectable in the classical radar scheme. However, most of the reported rotational Doppler measurements based on VBs can only be realized under ideal experimental conditions. The long-range detection is still a challenge. The detection distance based on rotational Doppler effect (RDE) is mainly limited by the scattered signal's signal-to-noise ratio (SNR). In this work, we investigated the influence of multi-ring vortex beams (MVBs) on the rotational Doppler frequency spectrum of scattered light from an object based on RDE and proposed a method of SNR enhancement of RDE signal. Firstly, different types of MVBs composed of a set of single-ring VBs with the same topological charge and different radii are designed, including multi-ring Laguerre Gaussian beam (MLGB), multi-ring perfect vortex beams (MPVB), and high-order Laguerre Gaussian beam (HLGB). Then, the influence of the number of rings and radial radius interval on the intensity profiles of MVBs and rotational Doppler frequency spectra under aligned and misaligned conditions is studied in detail. And the reasons why different types of MVBs lead to different SNR enhancement effectiveness with the increase of rings are also analyzed theoretically. Finally, proof-of-concept experiments were conducted to verify the effectiveness of the SNR enhancement method for RDE signals. The results showed that the amplitudes of the Doppler spectra generated by the MLGB and MPVB are improved substantially with the increase of rings, but the enhancement effect caused by the former is superior to the latter. The gain of HLGB on the RDE signal is the lowest. This study provides a useful reference for the optimization of rotational Doppler detection systems and may be of great application value in telemetry, long-range communication and optical imaging.

Terrestrial heat flow and subsidence of the Eastern Mediterranean Sea

We analysed the bathymetry and both marine and continental heat-flow data of the Eastern Mediterranean Sea basins. Bathymetry was corrected for the subsidence caused by sediment deposition to obtain the water-loaded seafloor depth. The thermal measurements were critically reviewed and corrected for sedimentation by 1–13 mW m−2 and for climatic changes by 4–5 mW m−2 to infer the purely conductive terrestrial heat flow. The seafloor depths and thermal data of the Ionian, Herodotus and Levantine basins were compared to reference models of continental lithosphere stretching and ocean plate cooling. In the Levantine Basin, the seafloor depth of 5.0 km argues for a continental crust that thinned ∼100 Ma ago by a factor of 2.7. The seafloor depth of the Herodotus and Ionian basins (7.5 and 6.3 km, respectively) does not match the continental stretching model predictions, suggesting they are floored by oceanic lithosphere. The reference models for the plate cooling and subsidence only partly account for the seafloor depth of the Eastern Mediterranean Sea basins. The seafloor of the Ionian agrees or is slightly deeper than the reference models, while in the Herodotus, it may exceed the expected subsidence of about 1 km. Compared to the reference models of plate cooling, the heat flow of the Herodotus and Ionian basins is lower by about 10 mW m−2. Together with the seafloor depth and gravity anomaly pattern, this argues for a cold and thick lithosphere beneath the Ionian and Herodotus basins. The lower heat flow may suggest that the basins escape from classical schemes of oceanic lithosphere cooling or that the reference models cannot be used for such old seafloors.

Discussion of Classical Phosphate Extraction Schemes to Identify Speciation in (Hydro-) Thermochemically Treated Sewage Sludge

Discussion of Classical Phosphate Extraction Schemes to Identify Speciation in (Hydro-) Thermochemically Treated Sewage Sludge

Numerical Solution of Advection–Diffusion Equation of Fractional Order Using Chebyshev Collocation Method

This work presents a highly accurate method for the numerical solution of the advection–diffusion equation of fractional order. In our proposed method, we apply the Laplace transform to handle the time-fractional derivative and utilize the Chebyshev spectral collocation method for spatial discretization. The primary motivation for using the Laplace transform is its ability to avoid the classical time-stepping scheme and overcome the adverse effects of time steps on numerical accuracy and stability. Our method comprises three primary steps: (i) reducing the time-dependent equation to a time-independent equation via the Laplace transform, (ii) employing the Chebyshev spectral collocation method to approximate the solution of the transformed equation, and (iii) numerically inverting the Laplace transform. We discuss the convergence and stability of the method and assess its accuracy and efficiency by solving various problems in two dimensions.

Three dimensional meshfree analysis for time-Caputo and space-Laplacian fractional diffusion equation

Numerical exploration of spatial fractional differential equations in three dimensions is not trivial due to their complexity, especially for complicated problem domains. In this work, the time-Caputo and space-Laplacian fractional diffusion equations in three dimensions are analyzed using a meshfree technique. In the temporal dimension, the classical L1 finite difference scheme is used to approach the Caputo fractional derivative. The spatial discretization is realized by a three dimensional reproducing kernel particle method (RKPM), which can eliminate the dependence of shape functions on certain meshes. Therefore RKPM is very suitable to approximate the field variable in complicated three dimensional domains compared with other mesh-dependent methods. For the purpose of increasing the computational efficiency, the stabilized conforming nodal integration (SCNI) and lumped mass matrix techniques are adopted in the Galerkin meshfree formulation. In the proposed method, the tedious derivatives computing for meshfree shape functions, numerical integration for Galerkin weak form and time-consuming inverse calculating for the large size mass matrix are all realized by more efficient approaches comparing with the conventional Galerkin RKPM. Several numerical examples in various domains with structured and unstructured discretization are studied to demonstrate the proposed methodology, and the results show very favorable performance of the proposed method regarding the accuracy and effectiveness.

Coupled estimation of global 500m daily aerodynamic roughness length, zero-plane displacement height and canopy height

Aerodynamic roughness length (z0m) and zero-plane displacement height (d), highly related to canopy height (h), are pivotal parameters to characterize the exchange of momentum, heat and water between the land and atmosphere and widely used in many remotely sensed evapotranspiration models, hydrological models and land surface models. In this study, we developed a practical method for coupled estimates of global 500 m daily z0m, d and h by combining the measurements over 2000–2019 at 271 sites worldwide, collocated remote sensing and reanalysis datasets, an optimized scheme, balanced random forest (BRF) and wind profile equation. The h estimated by the optimization (Opt) scheme, in comparison to that by five classical schemes, was in the highest agreement with the dynamic observations at 109 of 271 sites, with a root mean square error (RMSE) of 1.14 m (varying between 0.17 m and 2.58 m over different vegetated surfaces) and a coefficient of determination (R2) of 0.99. Meanwhile, the validation of h estimated by the BRF model against the inferred h at 271 sites and the Lidar-based observations showed an RMSE of 0.13 m - 4.84 m and an R2 of 0.79 - 0.95 over different vegetated land cover types. The z0m estimated by combining the BRF model and the Opt scheme presented a similar global spatial distribution compared to the CFSv2 and ERA5 products in 2019, with the estimated z0m exhibiting the greatest temporal-spatial variability. Moreover, the estimated z0m was more similar in magnitude to the ERA5 product but lower than the CFSv2 product. The generated d product showed similar spatial distribution and temporal-spatial variability to the z0m estimates, but was about 4 to 15 times larger than z0m in magnitude. This study could benefit the improvement of simulation of turbulent flux transfer between the land and atmosphere.