Additive Scheme Research Articles

Enhancing Privacy in the Management of Library Resources: A Novel Approach Utilizing FRS and ABE-CP Algorithm for Improved Protection

Libraries contain sensitive resources that users can access. The vital challenges faced include unauthorized access, privacy violations, malicious attacks, etc. Researchers have explored several ways to curb these challenges including encryption, policies, anti-malware etc. An improved design to secure library resources based on Fragmentation Redundancy Scattering (FRS) and Attribute-Based Encryption Cipher text Policy (ABE-CP) was presented. The core idea of FRS is to fragment confidential information to produce insignificant fragments and then scatter the pieces across the distributed system. As such, the scheme provides a new technique to manage network components and exchange encryption keys. By comparing the proposed scheme with other schemes, the proposed scheme prevents unauthorized access to users’ data and protects user’s privacy. The scheme in addition becomes resistant to common attacks like replay and man in the middle. According to our findings, the scheme is safe, practicable, and comprehensive with high security for both encrypting and decrypting users’ data within the least possible time.

MAYO Key Recovery by Fixing Vinegar Seeds

As the industry prepares for the transition to post-quantum secure public key cryptographic algorithms, vulnerability analysis of their implementations is gaining importance. A theoretically secure cryptographic algorithm should also be able to withstand the challenges of physical attacks in real-world environments. MAYO is a candidate in the ongoing second round of the NIST post-quantum standardization process for selecting additional digital signature schemes. This paper demonstrates three first-order single-execution fault injection attacks on the official MAYO implementation on the ARM Cortex-M4. By using voltage glitching to disrupt the computation of the vinegar seed during the signature generation, we enable the recovery of the secret key directly from the faulty signatures. Our experimental results show that the success rates of the fault attacks in a single execution are 36%, 82%, and 99%, respectively. They emphasize the importance of developing countermeasures against fault attacks prior to the widespread deployment of post-quantum algorithms like MAYO.

Enterprise internal audit data encryption based on blockchain technology.

Internal auditing demands innovative and secure solutions in today's business environment, with increasing competitive pressure and frequent occurrences of risky and illegal behaviours. Blockchain along with secure databases like encryption improves internal audit security through immutability and transparency. Hence integrating blockchain with homomorphic encryption and multi-factor authentication improves privacy and mitigates computational overhead. Recently, blockchain applications for internal audits in the enterprise sector are still emerging. Thus, blockchain technology in auditing provides the benefits of enhanced transparency and immutability in data processing, which can establish new solutions for internal auditing but still lacks encryption techniques. The research proposed a framework called "BlockCryptoAudit" to enhance internal audit processes through cryptographic encryption methods and blockchain technology, ensuring secure and transparent audit operations. The proposed approach integrates an additive homomorphic Paillier encryption scheme with blockchain to create a safe and tamper-resident audit trail. Utilizing homomorphic Paillier encryption, BlockCryptoAudit ensures that computations may be performed on encrypted audit data while safeguarding data privacy. The applied blockchain hyperledger component guarantees the immutability and transparency of encrypted audit records, resulting in a decentralized and tamper-resistant record. By limiting data accessibility to authorized individuals based on specified responsibilities, role-based access restrictions handled using smart contracts further strengthen security. The study protects audit data's security and confidentiality by encrypting it and putting it on a blockchain. The study compares the proposed BlockCryptoAudit with models like B-OAP, BSE-DF, and EG-FLB regarding risk mitigation, audit quality, security overhead, and audit trail effectiveness. With little security overhead, BlockCryptoAudit beats out B-OAP, BSE-DF, and EG-FLB in terms of risk mitigation (98%) and audit quality (99%). It is an effective way to improve internal audit processes and guarantee data integrity due to its high performance.

Additive operator splitting scheme for a general mean curvature flow and application in edges enhancement

Many models that use non-linear partial differential equations (PDEs) have been extensively applied for different tasks in image processing. Among these PDE-based approaches, the mean curvature flow filtering has impressive results, for which feature directions in the image are important. In this paper, we explore a general model of mean curvature flow, as proposed in [4, 5]. The modelcan be re-arranged to a reaction-diffusion form, facilitating the creation of an unconditionally stable semi-implicit scheme for image filtering. The method employs the Additive Operator Split (AOS) technique. Experiments demonstrated that the modified general model of mean curvature flow is highly effective for reducing noise and has a superior job of preserving edges.

Polarizability of exohedral lithium derivatives of fullerene C60

We have calculated mean polarizabilities of lithium–C60 exohedral derivatives and found that the depression of polarizability is typical for them as for covalent adducts of C60. This phenomenon implies the decreasing growth of the mean polarizability with the increasing number of the addends, attached to the fullerene core. Our previously developed model of the additive scheme, accounting this depression, works for lithium compounds only qualitatively, as the C60…Li contacts are non-covalent. Anisotropy of polarizability of C60Li n correlates with Li…Li distances in the molecules and almost independent of their symmetry.

Employment and deployment of additional staff roles in general practice: a realist evaluation of what works for whom, how, and why.

The Additional Roles Reimbursement Scheme (ARRS) was introduced in England in 2019 to alleviate workforce pressures in general practice by funding additional staff such as clinical pharmacists, paramedics, first-contact physiotherapists, and from 1 October 2024 the scheme funds recently qualified GPs. However, the employment and deployment models of ARRS staff present ongoing complexities and challenges that require further exploration. To explore the decision-making processes behind primary care networks (PCNs) and general practice staffing choices, and how these choices influence the operationalisation of ARRS. This was a qualitative case study across four PCNs in England using a realist evaluation framework. Data collection took place between September 2022 and November 2023. Semi-structured interviews were conducted with PCN clinical directors, GPs, practice managers, and ARRS staff (n = 42). Transcripts were analysed using a realist evaluation framework to identify the context-mechanism-outcome configurations. Direct employment models fostered staff development and retention, contingent on established trust among practices. Subcontracting was favoured to mitigate employment risks but could lead to unintended consequences such as conflicting accountabilities and less integration with existing GP practice staff. The optimal deployment model involved rotations across a limited number of GP practices, ideally two, with one serving as a base, ensuring consistency in training and management. This study provides novel insights into the complexities of different employment and deployment models of ARRS staff. These findings will be invaluable for creating a sustainable GP practice workforce and informing future workforce strategies as the scheme expands to include recently qualified GPs.

Contraction rate estimates of stochastic gradient kinetic Langevin integrators

In previous work, we introduced a method for determining convergence rates for integration methods for the kinetic Langevin equation for M-▽Lipschitz m-log-concave densities [Leimkuhler et al., SIAM J. Numer. Anal. 62 (2024) 1226–1258]. In this article, we exploit this method to treat several additional schemes including the method of Brunger, Brooks and Karplus (BBK) and stochastic position/velocity Verlet. We introduce a randomized midpoint scheme for kinetic Langevin dynamics, inspired by the recent scheme of Bou-Rabee and Marsden [arXiv:2211.11003, 2022]. We also extend our approach to stochastic gradient variants of these schemes under minimal extra assumptions. We provide convergence rates of O(m/M), with explicit stepsize restriction, which are of the same order as the stability thresholds for Gaussian targets and are valid for a large interval of the friction parameter. We compare the contraction rate estimates of many kinetic Langevin integrators from molecular dynamics and machine learning. Finally, we present numerical experiments for a Bayesian logistic regression example.

Convergence analysis of non-matching finite elements for a linear monotone additive Schwarz scheme for semi-linear elliptic problems

Abstract In this article, we are interested in the standard finite element approximation method of linear additive Schwarz iterations for a class of semi-linear elliptic problems, for two subdomains, in the context of non-matching grids. More precisely, by means of a uniform convergence result from the study by Lui and a fundamental lemma consisting of estimating, at each iteration, the gap between the continuous and the finite element Schwarz iterates, we prove that the discrete Schwarz sequences converge, in the maximum norm, to the true solution. Moreover, we also give numerical results to support the theoretical findings.

Post-Quantum Secure ID-Based (Threshold) Linkable Dual-Ring Signature and Its Application in Blockchain Transactions

Ring signatures are widely used in e-voting, anonymous whistle-blowing systems, and blockchain transactions. However, due to the anonymity of ring signatures, a signer can sign the same message multiple times, potentially leading to repeated voting or double spending in blockchain transactions. To address these issues in blockchain transactions, this work constructs an identity-based linkable ring signature scheme based on the hardness of the lattice-based Module Small Integer Solution (M-SIS) assumption, which is hard even for quantum attackers. The proposed scheme is proven to be anonymous, unforgeable, linkable, and nonslanderable in the random oracle model. Compared to existing identity-based linkable ring signature (IBLRS) schemes of linear size, our signature size is relatively smaller, and this advantage is more pronounced when the number of ring members is small. We provide approximate signature size data for ring members ranging from 2 to 2048. When the number of ring members is 16 (or 512. resp.), the signature size of our scheme is 11.40 KB (or 24.68 KB, respectively). Finally, a threshold extension is given as an additional scheme with specifications and security analysis.

Ablation Study of Diffusion Model with Transformer Backbone for Low-count PET Denoising.

Diffusion models (DM) built from a hierarchy of denoising autoencoders have achieved remarkable progress in image generation, and are increasingly influential in the field of image restoration (IR) tasks. In the meantime, its backbone of autoencoders also evolved from UNet to vision transformer, e.g. Restormer. Therefore, it is important to disentangle the contribution of backbone networks and the additional generative learning scheme. Notably, DM shows varied performance across IR tasks, and the performance of recent advanced transformer-based DM on PET denoising is under-explored. In this study, we further raise an intuitive question, "{if we have a sufficiently powerful backbone, whether DM can be a general add-on generative learning scheme to further boost PET denoising}". Specifically, we investigate one of the best-in-class IR models, i.e., DiffIR, which is a latent DM based on the Restormer backbone. We provide a qualitative and quantitative comparison with UNet, SR3 (UNet+pixel DM), and Restormer, on the 25% low dose 18F-FDG whole-body PET denoising task, aiming to identify the best practices. We trained and tested on 93 and 12 subjects, and each subject has 644 slices. It appears that Restormer outperforms UNet in terms of PSNR and MSE. However, additional latent DM over Restormer does not contribute to better MSE, SSIM, or PSNR in our task, which is even inferior to the conventional UNet. In addition, SR3 with pixel space DM is not stable to synthesize satisfactory results. The results are consistent with the natural image super-resolution tasks, which also suffer from limited spatial information. A possible reason would be the denoising iteration at latent feature space cannot well support detailed structure and texture restoration. This issue is more crucial in the IR tasks taking inputs with limited details, e.g., SR and PET denoising.

Power increase potential of coal-fired power plant assisted by the heat release of the thermal energy storage system: Restrictions and thermodynamic performance

The integration of a thermal energy storage (TES) system is an effective way to improve the load cycling rate of coal-fired power plants (CFPPs). To evaluate the power increase potential and thermodynamic performance of CFPP supplied by heat release of the molten salt TES system, eight discharging modes for CFPP integrated with the TES system including steam injection, heater bypass, and additional turbine schemes were comparatively evaluated. The system simulation models of the integrated systems were developed and the thermodynamic performance of the proposed system were evaluated. Results show that the mode SI-HPT (high-pressure turbine steam injection) has the largest output power increase of 25.00 % under the benchmark condition of 75%THA, but the mode HB-LPH (low-pressure heater bypass) shows a very low output power increase of 2.08 %. Moreover, the power generation efficiency is changed by the external heat source through a change in the average heat absorption temperature of the Rankine cycle and the internal irreversibility of the steam/water cycle. Under the typical benchmark discharging condition of 75%THA, the power generation efficiency of the turbine in mode SI-LPT (low-pressure turbine steam injection) can be reduced from 47.41 % to 44.15 %, but it can be increased from 47.41 % to 48.86 % in mode SI-HPT. When the temperature ranges of the TES system are above 600 °C and below 450 °C, the modes SI-HPT and SI-LPT obtain the optimal comprehensive performance, respectively. This study can provide the scientific guidance for retrofit for CFPP to achieve efficient and flexible design.

Methods of high voltage generation by cascading amplifiers

The purpose of this study was to create a new model of a high-voltage measuring amplifier that would include several stages of operational amplifiers to increase the operating voltage range by sequentially “virtual” connecting the output voltages of each stage. The research methodology included the use of cascaded amplifier coupling, an additive error correction scheme, as well as modelling and computational studies to optimise the design of high-voltage operational amplifiers. The study results showed that the use of high-voltage operational amplifiers RA94 provides high stability and accuracy of the output signal even under variable loads. The cascaded connection of the amplifiers helped to expand the frequency range and increase the operating voltage, which increased their efficiency. The use of an additive error correction scheme significantly reduced signal distortion, improving its quality. Modelling and computational studies optimised the design of the amplifiers, which contributed to the achievement of high technical characteristics. By combining these methods, a reliable system with improved parameters was created. The amplifiers have shown promise for a wide range of industrial and scientific applications. They can operate in difficult conditions with high accuracy. The study confirmed the importance of integrating modern technologies into the development of electronic systems. Computational studies of a new model of a high-voltage measuring amplifier demonstrate that the use of several stages of operational amplifiers together with an additive error correction scheme can significantly expand the frequency range of the amplifier and increase the operating voltage range, which leads to improved measurement quality

An improved implicit direct-forcing immersed boundary method (DF-IBM) around arbitrarily moving rigid structures

An improved implicit direct-forcing immersed boundary method (DF-IBM) is presented for simulating incompressible flows around complex rigid structures undergoing arbitrary motion. The current approach harnesses the pressure implicit with splitting of operators algorithm to handle the fluid–solid system's dual constraints in a segregated manner. As a result, the divergence-free condition is preserved throughout the Eulerian domain, and the no-slip velocity boundary condition is exactly enforced on the immersed boundary. A new pressure Poisson equation (PPE) is derived, incorporating the boundary force where the no-slip condition is already met, enabling the use of fast iterative PPE solvers without modifications. The improvement involves integrating Lagrangian weight methods having better reciprocity over the IBM-related linear operators with the implicit formulation. An additional force initialization scheme is introduced to further boost the algorithm's performance. The method's accuracy, efficiency, and capability are verified through various stationary and moving immersed boundary cases. The results are validated against experimental and numerical data from the literature. The proposed improvements seamlessly integrate into existing incompressible fluid solvers with minimal adjustments to the original system equations, highlighting their ease of implementation.

Optimizing HAWK Signature Scheme Performance on ARMv8

This study proposes an optimized implementation of the HAWK Signature algorithm, one of the candidates in the first evaluation round for additional digital signature schemes in the NIST Post-Quantum Cryptography competition. The core motivation of this research is to improve the performance of HAWK algorithm. By conducting profiling analysis to identify, we identified the most resource-intensive functions. And then we optimized the functions. The optimization techniques through profiling analysis are not limited to HAWK but can be applied to other algorithms as well. Additionally, the study demonstrates how efficient optimization can be achieved using fewer instructions by leveraging lesser-known ARMv8 instructions. By targeting the functions with the highest overhead and utilizing fewer instructions, a performance improvement of approximately 2.5% for Hawk512 and 4% for Hawk1024 was achieved, respectively. These results confirm that combining profiling analysis with efficient instruction usage can lead to significant performance improvements.

Effect of Additional Roles Reimbursement Scheme roles on prescription patterns and patient satisfaction in England: a retrospective panel data analysis.

In 2019, the Additional Roles Reimbursement Scheme (ARRS) was introduced in England as a crucial component of the government's manifesto pledge to enhance access to general practice. The primary objective was to recruit 26 000 extra personnel through new roles into general practice. To analyse the effects of ARRS staff on prescription rates and patient satisfaction. A retrospective panel data analysis combining data from the General Workforce Minimum Dataset and NHS Digital datasets about primary care practices and their activity from 2018 to 2022. The study included data from >6000 general practices. A linear regression analysis was conducted to determine the association between ARRS staff and prescription rates and patient satisfaction, controlling for patient and practice characteristics. The results showed that ARRS roles tend to be more frequent in larger general practices, with fewer full-time GPs per patient, and with more overseas trained GPs. The use of ARRS staff was significantly associated with lower prescription rates (β = -0.52, P<0.001) and higher patient satisfaction (β = 3.2, P<0.001), after controlling for patient and practice characteristics. This study suggests that the ARRS has the potential to have a positive role in primary care, notably through reduced prescription rates and improved patient satisfaction. Further research is needed to explore the long-term effects of the ARRS on primary care, including patient outcomes and healthcare costs, and the potential barriers to its implementation.

Enabling PERK and other MPC-in-the-Head Signatures on Resource-Constrained Devices

One category of the digital signatures submitted to the NIST Post-Quantum Cryptography Standardization Process for Additional Digital Signature Schemes comprises proposals constructed leveraging the MPC-in-the-Head (MPCitH) paradigm. Typically, this framework is characterized by the computation and storage in sequence of large data structures both in signing and verification algorithms, resulting in heavy memory consumption. While some research on the efficiency of these schemes on high-performance machines has been done, studying their performance and optimization on resource-constrained ones still needs to be explored. In this work, we aim to address this gap by (1) introducing a general method to reduce the memory footprint of MPCitH schemes and analyzing its application to several MPCitH proposed schemes in the NIST Standardization Process. Additionally, (2) we conduct a detailed examination of potential memory optimizations in PERK, resulting in a streamlined version of the signing and verification algorithms with a reduced memory footprint ranging from 22 to 85 KB, down from the original 0.3 to 6 MB. Finally, (3) we introduce the first implementation of PERK tailored for Arm Cortex M4 alongside extensive experiments and comparisons against reference implementations.

Updating the radiation infrastructure in MESSy (based on MESSy version 2.55)

Abstract. The calculation of the radiative transfer is a key component of global circulation models. In this article, we describe the most recent updates of the radiation infrastructure in the Modular Earth Submodel System (MESSy). These updates include the implementation of the PSrad radiation scheme within the RAD submodel. Furthermore, the radiation-related submodels CLOUDOPT (for the calculation of cloud optical properties) and AEROPT (for the calculation of aerosol optical properties) have been updated and are now more flexible in order to deal with different sets of shortwave and longwave bands of radiation schemes. In the wake of these updates, a new submodel (ALBEDO), which features solar-zenith-angle-dependent albedos and a new satellite-based background (white sky) albedo, was created. All of these developments are backward compatible, and previous features of the MESSy radiation infrastructure remain available. Moreover, these developments mark an important step in the use of the ECHAM/MESSy Atmospheric Chemistry (EMAC) model, as the update of the radiation scheme was a key aspect in the development of the sixth generation of the European Centre for Medium-Range Weather Forecasts – HAMburg (ECHAM6) model from ECHAM5. The developments presented here are also aimed towards using the MESSy infrastructure with the ICOsahedral Non-hydrostatic (ICON) model as a base model. The improved infrastructure will also aid in the implementation of additional radiation schemes once this should be needed. We have optimized the set of free parameters for two general circulation model-type (GCM-type) setups for pre-industrial and present-day conditions: one with the radiation scheme that was used to date (i.e. the radiation scheme of ECHAM5) and one with the newly implemented PSrad radiation scheme. After this parameter optimization, we performed four model simulations and evaluated the corresponding model results using reanalysis and observational data. The most apparent improvements related to the updated radiation scheme are the reduced cold biases in the tropical upper troposphere and lower stratosphere and the extratropical lower stratosphere and a strengthened polar vortex. The former is also related to improved stratospheric humidity and its variability if the new radiation scheme is employed. Using the multiple radiation call capability of MESSy, we have applied the two model configurations to calculate instantaneous and stratospheric-adjusted radiative forcings related to changes in greenhouse gases. Overall, we find that for many forcing experiments the simulations with the new radiation scheme show improved radiative forcing values. This is in particular the case for methane radiative forcings, which are considerably higher when assessed with the new radiation scheme and thus in better agreement with reference values.

Charge Transfer Mechanism in Guanine-Based Self-Assembled Monolayers on a Gold Surface.

In this work, we have theoretically determined the one-electron oxidation potentials and charge transfer mechanisms in complex systems based on a self-assembled monolayer of guanine molecules adsorbed on a gold surface through different organic linkers. Classical molecular dynamics simulations were carried out to sample the conformational space of both the neutral and the cationic species. Thus, the redox potentials were determined for the ensembles of geometries through multiscale quantum-mechanics/molecular-mechanics/continuum solvation model calculations in the framework of the Marcus theory and in combination with an additive scheme previously developed. In this context, conformational sampling, description of the environment, and effects caused by the linker have been considered. Applying this methodology, we unravel the phenomena of electric current transport by evaluating the different stages in which charge transfer could occur. The results revealed how the positive charge migrates from the organic layer to the gold surface. Specifically, the transport mechanism seems to take place mainly along a single ligand and driven with the help of the electrostatic interactions of the surrounding molecules. Aside, several self-assembled monolayers with different linkers have been analyzed to understand how the nature of that moiety can tune the redox properties and the efficiency of the transport. We have found that the conjugation between the guanine and the linker, at the same time conjugated to the gold surface, gives rise to a more efficient transport. In conclusion, the established computational protocol sheds light on the mechanism behind charge transport in electrochemical DNA-based biosensor nanodevices.

Multi-Modality Ensemble Distortion for Spatial Steganography With Dynamic Cost Correction

This paper tackles a recent challenge in designing an efficient steganographic distortion model, whose goal is to accurately measure the modification cost of a pixel and help design steganographic schemes with high undetectability. Existing distortion models mostly assume that different modification directions of a pixel have an identical cost value and that pixel modifications are independent. These assumptions, however, may not lead to good steganography design because the modification direction of neighbouring pixels may affect the cost measurement of the current pixel. To address this problem, we propose a new distortion calculation method using dynamic cost correction and multi-modality distortion ensemble. The proposed scheme first employs a given distortion model to generate the original cost map. The cost of each pixel is then dynamically adjusted with majority voting according to the modification directions of its neighbouring pixels. Furthermore, different distortion calculation models are integrated to make the final decision on the distortion of each pixel. Experimental results show that compared to existing additive distortion-based steganographic schemes and deep learning-based steganographic schemes, steganography using our proposed distortion model performs better when tested against state-of-the-art steganalysis methods.

Jerk Chaotic System: Analysis, Circuit Simulation, Control and Synchronization with Application to Secure Communication

Dynamical behaviors of 3D Jerk system were examined in terms of equilibrium, stability, dissipative, and phase space attractor in this study. The system’s practical applications were demonstrated through circuit realization and synchronization scheme via active backstepping control with its effectiveness demonstrated in secure communication. The viability of the theoretical model of 3D Jerk system was confirmed using electronic circuit workbench designed in MultiSIM enviroment. A nonlinear feedback controller was designed using the recursive backstepping technique to control and track a desire function. For secure communication application, active backstepping method was adopted to synchronize two identical chaotic systems evolving from different initial conditions. It was demonstrated that when the controller was activated, the systems synchronize successfully. The results of the active backstepping designed controllers were numerically applied in the area of secure communication, with the variable of the drive being encrypted information transmitted through a coupling channel. Using an additive encryption masking scheme, the encrypted signal was a superposition of sinusoidal information specified by period function and chaotic carrier generated from a variable of the Jerk system. The transmitted information signal was successfully retrieved from the chaotic response signal using an inverse function decryption algorithm, thereby confirming the effectiveness and robustness of the designed controller.