Compression Function Research Articles

Quantum Free-Start Collision Attacks on Double Block Length Hashing with Round-Reduced AES-256

Recently, Hosoyamada and Sasaki (EUROCRYPT 2020), and Xiaoyang Dong et al. (ASIACRYPT 2020) proposed quantum collision attacks against AES-like hashing modes AES-MMO and AES-MP. Their collision attacks are based on the quantum version of the rebound attack technique exploiting the differential trails whose probabilities are too low to be useful in the classical setting but large enough in the quantum setting. In this work, we present dedicated quantum free-start collision attacks on Hirose’s double block length compression function instantiated with AES-256, namely HCF-AES-256. The best publicly known classical attack against HCF-AES-256 covers up to 9 out of 14 rounds. We present a new 10-round differential trail for HCF-AES-256 with probability 2−160, and use it to find collisions with a quantum version of the rebound attack. Our attack succeeds with a time complexity of 285.11 and requires 216 qRAM in the quantum-attack setting, where an attacker can make only classical queries to the oracle and perform offline computations. We also present a quantum free-start collision attack on HCF-AES-256 with a time complexity of 286.07 which outperforms Chailloux, Naya-Plasencia, and Schrottenloher’s generic quantum collision attack (ASIACRYPT 2017) in a model when large qRAM is not available.

High squint multichannel SAR imaging algorithm for high speed maneuvering platforms with small-aperture

For high speed maneuvering platforms, multichannel synthetic aperture radar (SAR) can realize wide-swath imaging more flexibly at a high squint. In this mode, the signal reconstruction and imaging is a challenging task because the direction of the channel array vector is time-variant and inconsistent with the radar velocity vector. In this paper, the properties of space time spectrum are analyzed in detail at first. It is found that the space time spectrum of the signal is irregular, in which the space time spectral lines are nonlinear and there is a massive Doppler spectrum shift. Therefore, a range-dependent signal reconstruction method based on space time spectrum correction is proposed to obtain the unambiguous Doppler spectrum. For wide-swath data processing, an improved Omega-K approach based on time domain spectrum compression is further proposed to obtain a well-focused image. A modified Stolt mapping is used to address the range variations of range cell migration (RCM). Subsequently, a time domain spectrum compression function is used to eliminate the time domain aliasing of small-aperture data without zero-padding. Simulation results and real data processing are presented to validate the proposed algorithm.

Singular vector sparse reconstruction for image compression

Generally, more than half of smaller singular values and corresponding singular vectors should be abandoned to achieve the image compression function for the compression method based on singular value decomposition (SVD). Although these discarded parts contain some noise and fuzzy factors, they also contain some detailed information to boost image reconstruction. To overcome this problem, we present a novel lossy image compression method named singular vector sparse reconstruction (SVSR) keeping the sparse representation data of more singular vector to boost the performance of SVD based image compression method in compression ratio and reconstruction quality. Specifically, we treat the singular vector as a signal and express it sparsely through sparse sampling based on the analysis of the characteristics of the singular vector. In particular, the compression ratio of the proposed method is about 70% higher than that of the traditional SVD method. Evaluation on several image data and the experimental results with different image compression algorithms clearly demonstrate the advantages of our proposed SVSR algorithm in compression ratio and reconstruction quality.

Volume-constrained deformation of a thin sheet as a route to harvest elastic energy.

Thin sheets exhibit rich morphological structures when subjected to external constraints. These structures store elastic energy that can be released on demand when one of the constraints is suddenly removed. Therefore, when adequately controlled, shape changes in thin bodies can be utilized to harvest elastic energy. In this paper, we propose a mechanical setup that converts the deformation of the thin body into a hydrodynamic pressure that potentially can induce a flow. We consider a closed chamber that is filled with an incompressible fluid and is partitioned symmetrically by a long and thin sheet. Then, we allow the fluid to exchange freely between the two parts of the chamber, such that its total volume is conserved. We characterize the slow, quasistatic, evolution of the sheet under this exchange of fluid, and derive an analytical model that predicts the subsequent pressure drop in the chamber. We show that this evolution is governed by two different branches of solutions. In the limit of a small lateral confinement we obtain approximated solutions for the two branches and characterize the transition between them. Notably, the transition occurs when the pressure drop in the chamber is maximized. Furthermore, we solve our model numerically and show that this maximum pressure behaves nonmonotonically as a function of the lateral compression.

A Coal Permeability Model with Variable Fracture Compressibility Considering Triaxial Strain Condition

Fracture compressibility and strain boundary conditions are key factors in the evolution of coal permeability. Previous research has shown that fracture compressibility of coal is variable. Generally, the uniaxial strain condition is adopted for field coalbed methane (CBM) recovery. In this study, we assumed that the coal samples were under triaxial strain conditions combined with McKee’s stress-dependent fracture compressibility function and the improved Shi-Durucan permeability model. A new permeability model, with variable fracture compressibility, was derived. Considering variable fracture compressibility, the calculated results of the model were closer to the experimental values than the model with constant fracture compressibility. Based on previous experimental data, the responses of fracture compressibility to effective stress, gas pressure, gas type, and coal rank were analyzed. Coal fracture compressibility generally decreased with increase in effective stress. With increasing pore pressure, coal fracture compressibility first decreased and then increased when the experimental gas was CO2, CH4, or N2; it first increased and then decreased when the experimental gas was He. The stronger the adsorption capacity of the gas, the greater the coal fracture compressibility under uniform pore pressure. Numerical results of CBM production can be more accurate when the uniaxial and triaxial strain conditions are assumed for a coal seam far away from and near a wellhead, respectively.

Large nonuniform bending of beams with compressible stored energy functions of polynomial-type

The large bending of beams made with complex materials finds application in many emerging fields. To describe the nonlinear behavior of these complex materials such as rubbers, polymers and biological tissues, stored energy functions of polynomial-type are commonly used. Using polyconvex and compressible stored energy functions of polynomial-type, in the present paper the equilibrium problem of slender beams in the fully nonlinear context of finite elasticity is formulated. In the analysis, the bending is considered nonuniform, the complete three-dimensional kinematics of the beam is taken into account and both deformation and displacement fields are deemed large. The governing equations take the form of a coupled system of three equations in integral form, which is solved numerically through an iterative procedure. Explicit formulae for displacements, stretches and stresses in every point of the beam, following both Lagrangian and Eulerian descriptions, are derived. By way of example, a complete analysis has been performed for the Euler beam.

Construction and Analysis of SHA-256 Compression Function Based on Chaos S-Box

To further improve the security of SHA-256, a compression function construction scheme based on chaotic S-box is proposed. Through the reasonable design of the iteration mode and using the nonlinearity, confusion, and anti-difference of chaotic S-box, the relationship between the plaintext and the hash value becomes more complicated and unpredictable, by the diffusion of the linear transformation P-box, the dependence between the plaintext and the hash value is further improved. The compression function is applied to the SHA-256 Hash Algorithm to test and analyze the distribution, sensitivity, confusion, diffusion, and collision resistance, and compared with the original SHA-256 and the mainstream Hash Algorithms. The results show that the proposed scheme can effectively improve the collision resistance of the SHA-256 Hash Algorithm and enhance the stability of confusion and diffusion with fewer cryptographic components and lower operational consumption to provide more reliable security guarantee for its application.

A Novel Hash Function Based on a Chaotic Sponge and DNA Sequence

Many chaos-based hash functions have convoluted designs that are not based on proper design principles, complicating the verification of security claims. We address this problem by proposing a hash function based on a chaotic sponge construction and DNA sequence. DNA sequence is used to design state transition rules of a deterministic chaotic finite-state automata (DCFSA), a chaotic structure that enhances the chaoticity of digital chaotic maps. We use a DCFSA configuration consisting of four states associated with logistic maps. Analysis shows that the DCFSA configuration is efficient and has high chaotic complexity. Both DCFSA and DNA are used to design the sponge-based hash function. An input message is transformed into a DNA sequence and divided into fixed-length blocks. Each block is absorbed into a sponge structure via DNA-XOR. The sponge state is then updated with a new DNA sequence by iterating DCFSA as a compression function. Statistical evaluations indicate that the proposed hash function has near-ideal diffusion, confusion, collision resistance and distribution properties. The proposed hash can also extend the provably secure notions of the sponge construction, specifically the indifferentiability from random oracles. Furthermore, the hash function has a high level of performance as compared to other chaos-based hash functions.

Speed of random walks, isoperimetry and compression of finitely generated groups

We give a solution to the inverse problem (given a prescribed function, find a corresponding group) for large classes of speed, entropy, isoperimetric profile, return probability and $L_p$-compression functions of finitely generated groups. For smaller classes, we give solutions among solvable groups of exponential volume growth. As corollaries, we prove a recent conjecture of Amir on joint evaluation of speed and entropy exponents and we obtain a new proof of the existence of uncountably many pairwise non-quasi-isometric solvable groups, originally due to Cornulier and Tessera. We also obtain a formula relating the $L_p$-compression exponent of a group and its wreath product with the cyclic group for$p$ in $[1,2]$.

Extending Marlow’s general first-invariant constitutive model to compressible, isotropic hyperelastic materials

PurposeA general first-invariant constitutive model has been derived in literature for incompressible, isotropic hyperelastic materials, known as Marlow model, which reproduces test data exactly without the need of curve-fitting procedures. This paper aims to describe how to extend Marlow’s constitutive model to the more general case of compressible hyperelastic materials.Design/methodology/approachThe isotropic constitutive model is based on a strain energy function, whose isochoric part is solely dependent on the first modified strain invariant. Based on Marlow’s idea, a principle of energetically equivalent deformation states is derived for the compressible case, which is used to determine the underlying strain energy function directly from measured test data. No particular functional of the strain energy function is assumed. It is shown how to calibrate the volumetric and isochoric strain energy functions uniquely with uniaxial or biaxial test data only. The constitutive model is implemented into a finite element program to demonstrate its applicability.FindingsThe model is well suited for use in finite element analysis. Only one set of test data is required for calibration without any need for curve-fitting procedures. These test data are reproduced exactly, and the model prediction is reasonable for other deformation modes.Originality/valueMarlow’s basic concept is extended to the compressible case and applied to both the volumetric and isochoric part of the compressible strain energy function. Moreover, a novel approach is described on how both compressive and tensile test data can be used simultaneously to calibrate the model.

Thermodynamics, EOS, and heat capacity in molecular modeling of self-assembled molecular layers.

Self-assembled monolayers (SAMs) on solid surfaces represent a rapidly developed class of non-autonomous phases widely used in organic electronics, sensors, catalysis, and other applications. In many cases, the same organic molecules form various stable and metastable polymorphous structures that can transform to each other at certain parameters. A high rigidity of SAMs extremely complicates the evaluation of the chemical potential using standard methods based on thermodynamic integration. This study presents results of molecular modeling of two-dimensional structures of tripod-shaped molecules associated with the trimesic acid (TMA) molecules. A technique used here is based on a recently developed method of external fields imposed on an elongated simulation cell in the framework of a kinetic Monte Carlo algorithm. These fields are the external potential and a damping field that reduces the intermolecular potential and affects the system similar to the increase in temperature. Equations of state (EOS) for several TMA polymorphs have been obtained with the conventional Monte Carlo simulation. It was shown that, in each case, only one constant links the chemical potential obtained with the external field method and the EOS at any temperature and pressure. The heat capacities of SAMs at constant volume and pressure were also determined as functions of temperature and compressibility of the structure at given degrees of freedom. The approach can be used as a general tool for modeling and evaluation of thermodynamic properties of various rigid structures, including SAMs of functional organic molecules.

Optical Hash function based on multiple scattering media

Hash functions, which can extract message digest from input messages as output, play an important role in digital signature and authentication. Meanwhile, Hash functions are essential in many cryptographic protocols and regimes. With the research becoming more and more in depth, a series of Hash functions is proposed, such as MD series and SHA series. At the same time, the security analysis and attacks against Hash functions are carried out. The security of Hash functions is threatened. In this case, how to improve the security of the Hash functions becomes the primary concern. In this paper, an optical Hash function based on the interaction between light and multiple scattering media is proposed. Unlike most of the traditional Hash functions which are based on mathematical transformations or complex logic operations, this method innovatively takes advantage of the natural random scattering effect of multiple scattering media on coherently modulated light, and realizes the “confusion” and “diffusion” of modulated light, which satisfies the core functional requirement of the Hash function: one-way encoding/encryption with strong security. The photoelectric hybrid system designed by this method can effectively simulate the "compression function" in the Hash function. Combined with the Sobel filter with feature extraction function, the input data of arbitrary length can be compressed and encrypted into the output with a fixed length of 256-bit (Hash value). The principle of the proposed optical Hash function can be described as follows. 1) Two 8-bit images with a size of 16×16 pixels are loaded in SLM<sub>1</sub> (amplitude-only spatial modulator) and SLM<sub>2</sub> (phase-only spatial modulator) respectively. 2) The coherent wavefront is modulated by SLM<sub>1</sub> and SLM<sub>2</sub>, and then propagates on multiple scattering media. 3) A speckle pattern is recorded by CCD because of the confusion of multiple scattering media. 4) The features of the speckle pattern, which is extracted by Sobel filter, serve as the input of the next compression function. For the unpredicted and non-duplicated disorder multiple scattering media, it is tremendously difficult to determine the internal state of the multiple scattering media. Therefore, the proposed optical Hash function is considered to have a high security. A series of simulation results shows that the proposed optical Hash function has a good “avalanche effect” and “collision resistance”, and its security performance is comparable to that of the most widely used traditional Hash functions (MD5 and SHA-1).

Design and Evaluation of the Performance of an Integrated Flux-Switching Motor–Compressor With Airfoil-Shaped Rotor

The objective of this article is to propose the concept of and evaluate the potential performance of an integrated flux-switching permanent magnet (FSPM) motor-compressor that has rotor poles designed as airfoils to perform compression functions. The airfoil-shaped rotor functions as the rotor of both an electric motor and an axial-flow compressor. As a result, the integrated motor-compressor increases the compressor system compactness by eliminating the separation between the motor and compressor. In this article, the electromagnetic and thermodynamic designs are developed using sizing equations and mean line analysis. Four design configurations of the integrated motor-compressor are carried out and evaluated, including the continuous-skewed versus step-skewed structure and laminated steels versus soft magnetic composite (SMC) materials. The thermodynamic performance is calculated by mean line analysis and computational fluid dynamics (CFD). The electromagnetic performance and structural analysis are evaluated by finite element analysis (FEA). The comparisons of the integrated motor-compressor with conventional motor-driven compressors are conducted. Results from FEA and CFD verify the integrated motor-compressor.

Self-powered supercapacitor-mode tactile sensor based on polygonal litchi–like nanospheres decorated three-dimensional reduced graphene oxide aerogel for wearable electronics device

Rapidly growing improvement of portable and wearable devices stimulates requirements for multifunction tactile electronics. Herein, we report a novel electrochemical-driving supercapacitor-mode self-powered tactile sensor based on polygonal litchi–like nanospheres embedded 3D reduced graphene oxide aerogel framework, which displays outstanding compressibility to accommodate complex external conditions such as large-scale mechanical deformations. The sensor has the power to realize function of both strain compression sensing and energy storage capabilities simultaneously. The porosity of aerogels and pseudocapacitance property of polygonal litchi–like CoV2O6 nanospheres endows the composite aerogel with superior electrochemical performance with energy density of 139.18 Wh kg−1 at 500.0 W kg−1. Taking advantage of splendid elasticity of aerogel structure, self-powered supercapacitor-mode sensor response to external pressure signal sensitively. The self-powered sensor not only presents promising potentials in wireless charging system, but also expands the practical application areas of electrochemical energy storage device greatly.

Customised Selection of the Haptic Design in C-Loop Intraocular Lenses Based on Deep Learning.

In order to increase the probability of having a successful cataract post-surgery, the customisation of the haptic design of the intraocular lens (IOL) according to the characteristics of the patient is recommended. In this study, we present two prediction models based on deep neural networks (DNNs). One is capable of predicting the biomechanical stability of any C-loop IOL, whereas the other can predict the haptic design that fits a desired biomechanical response, enabling the selection of the optimal IOL as a function of the IOL diameter compression. The data used to feed the networks has been obtained from a validated finite element model in which multitude of geometries are tested according to the ISO 11979-3 compression test, a standard for the mechanical properties of the IOLs. The biomechanical response model provides a very high accurate response (Pearson's r = 0.995), whilst the IOL haptic design model shows that several IOL designs can provide the same biomechanical response (Pearson's r = 0.992). This study might help manufacturers and ophthalmologists both analyse any IOL design and select the best IOL for each patient. In order to facilitate its application, a graphical user interface (GUI) was created to show the potential of deep learning methods in cataract surgery.

Ultra-Lightweight EPS Concrete: Mixing Procedure and Predictive Models for Compressive Strength

Expanded polystyrene (EPS) lightweight concrete is increasingly used in various applications due to its lightweight, excellent heat preservation, sound insulation and energy absorbing characteristics. However, due to the hydrophobic nature and very low density of EPS beads, EPS concretes are prone to segregation, poor bonding, and homogeneity issues. The properties of EPS concrete are highly dependent on the mixture proportions and mixing procedure. This study involves the development of a quality mixing procedure for Ultra-lightweight EPS concrete and the development of two predictive compressive strength models function of concrete mixture and density, respectively. An experimental program is developed to implement the mixing procedure and to calibrate and evaluate the accuracy of the models. The proposed models were found to accurately predict the strength of concrete mixtures. The corresponding standard error for the models is less than 0.3 MPa and the corresponding correlation coefficient is greater than 0.93. To ensure quality control before concrete is cast, a link between the plastic density of fresh concrete and the compressive strength was established. Furthermore, to accommodate tight construction schedules, the effects of concrete age on the compressive strength development were studied and the 28-day strength was related to strengths at early ages.

Green Communications for Future Vehicular Networks: Data Compression Approaches, Opportunities, and Challenges

Cellular vehicular networks constitute an important part of future vehicular communication systems. However, they pose challenges to fulfill vehicles with demands for the transmission rates of various network services while achieving satisfactory costs and energy consumption. The cloud radio access network architecture is considered as a green wireless access network framework that reduces the deployment costs of base stations while achieving resource sharing and dynamic scheduling to lower energy consumption, and thus will greatly improve spectrum efficiency. in this article, we first propose a cloud vehicular radio access network (C-VRAN) architecture to enable rapid network innovation for green vehicular communications. Specifically, we propose a vehicular network framework consisting of centralized processing, collaborative radio, real-time cloud computing, and data compression functions. Then, the design and the potential benefits of C-VRAN are presented in detail. Moreover, an effective data compression approach for the proposed architecture is proposed to meet low-distortion compression for cellular vehicular network data, thereby improving fiber resource utilization. Finally, we briefly discuss key challenges and solutions for future green vehicular communications.

A Comprehensive Method for Assessing Meat Freshness Using Fusing Electronic Nose, Computer Vision, and Artificial Tactile Technologies

The traditional methods cannot be used to meet the requirements of rapid and objective detection of meat freshness. Electronic nose (E-Nose), computer vision (CV), and artificial tactile (AT) sensory technologies can be used to mimic humans’ compressive sensory functions of smell, look, and touch when making judgement of meat quality (freshness). Though individual E-Nose, CV, and AT sensory technologies have been used to detect the meat freshness, the detection results vary and are not reliable. In this paper, a new method has been proposed through the integration of E-Nose, CV, and AT sensory technologies for capturing comprehensive meat freshness parameters and the data fusion method for analysing the complicated data with different dimensions and units of six odour parameters of E-Nose, 9 colour parameters of CV, and 4 rubbery parameters of AT for effective meat freshness detection. The pork and chicken meats have been selected for a validation test. The total volatile base nitrogen (TVB-N) assays are used to define meat freshness as the standard criteria for validating the effectiveness of the proposed method. The principal component analysis (PCA) and support vector machine (SVM) are used as unsupervised and supervised pattern recognition methods to analyse the source data and the fusion data of the three instruments, respectively. The experimental and data analysis results show that compared to a single technology, the fusion of E-Nose, CV, and AT technologies significantly improves the detection performance of various freshness meat products. In addition, partial least squares (PLS) is used to construct TVB-N value prediction models, in which the fusion data is input. The root mean square error predictions (RMSEP) for the sample pork and chicken meats are 1.21 and 0.98, respectively, in which the coefficient of determination (R2) is 0.91 and 0.94. This means that the proposed method can be used to effectively detect meat freshness and the storage time (days).

Classical flutter analysis of composite wind turbine blades including compressibility

AbstractFor wind turbine blades with the increased slenderness ratio, flutter instability may occur at lower wind and rotational speeds. For long blades, at the flutter condition, relative velocities at blade sections away from the hub center are usually in the subsonic compressible range. In this study, for the first time for composite wind turbine blades, a frequency domain classical flutter analysis methodology has been presented including the compressibility effect only for the outboard blade sections, which are in the compressible flow regime exceeding Mach 0.3. Flutter analyses have been performed for the baseline blade designed for the 5‐MW wind turbine of NREL. Beam‐blade model has been generated by making analogy with the structural model of the prewisted rotating thin‐walled beam (TWB) and variational asymptotic beam section (VABS) method has been utilized for the calculation of the sectional properties of the blade. To investigate the compressibility effect on the flutter characteristics of the blade, frequency and time domain aeroelastic analyses have been conducted by utilizing unsteady aerodynamics via incompressible and compressible indicial functions. This study shows that with use of compressible indicial functions, the effect of compressibility can be taken into account effectively in the frequency domain aeroelastic stability analysis of long blades whose outboard sections are inevitably in the compressible flow regime at the onset of flutter.

Pressure effects on the EXAFS Debye-Waller factor of iron.

The pressure effects on atomic mean-square relative displacement characterizing the extended X-ray absorption fine structure (EXAFS) Debye-Waller factor of iron metal have been investigated based on the Debye model. The analytical expressions of the Debye frequency and EXAFS Debye-Waller factor have been derived as functions of crystal volume compressibility. Based on the well established equation-of-state including the contributions of the anharmonic and electronic thermal pressures, numerical calculations have been performed for iron up to a pressure of 220 GPa and compared with experimental data when possible. These results show that the Debye frequency increases rapidly with compression, and beyond 150 GPa it behaves as a linear function of pressure. Meanwhile the mean-square relative displacement curve drops robustly with pressure, especially at pressures smaller than 100 GPa. This phenomenon causes the enhancement of EXAFS signals at high pressure. Reversely, the increasing of temperature will reduce the amplitude of EXAFS spectra.