Quantitative Comparative Study of the Performance of Lossless Compression Methods Based on a Text Data Model

Data compression plays a key role in optimizing the use of memory storage space and also reducing latency in data transmission. In this paper, we are interested in lossless compression techniques because their performance is exploited with lossy compression techniques for images and videos generally using a mixed approach. To achieve our intended objective, which is to study the performance of lossless compression methods, we first carried out a literature review, a summary of which enabled us to select the most relevant, namely the following: arithmetic coding, LZW, Tunstall’s algorithm, RLE, BWT, Huffman coding and Shannon-Fano. Secondly, we designed a purposive text dataset with a repeating pattern in order to test the behavior and effectiveness of the selected compression techniques. Thirdly, we designed the compression algorithms and developed the programs (scripts) in Matlab in order to test their performance. Finally, following the tests conducted on relevant data that we constructed according to a deliberate model, the results show that these methods presented in order of performance are very satisfactory:- LZW- Arithmetic coding- Tunstall algorithm- BWT + RLELikewise, it appears that on the one hand, the performance of certain techniques relative to others is strongly linked to the sequencing and/or recurrence of symbols that make up the message, and on the other hand, to the cumulative time of encoding and decoding.

Simultaneous Compression of the Celiac Trunk, Superior Mesenteric Artery, and Renal Arteries by the Median Arcuate Ligament: About One Case

Median arcuate ligament syndrome (MALS), is a rare abdominal vascular compression syndrome caused by the compression of the proximal celiac trunk by the median arcuate ligament. According to many authors, a low insertion of the diaphragmatic crura or an abnormally high origin of the celiac trunk from the aorta can cause compression of the celiac artery. Usually, patients with MALS are asymptomatic. Computed tomography (CT) angiography of the abdomen is the main imaging modality to confirm the diagnosis. The coexistence of celiac trunk and superior mesenteric artery compression by the median arcuate ligament is rarely described in the literature. To our knowledge, until now, a simultaneous combination of three abdominal vascular compressions by the median arcuate ligament has never been described. From this case, we report a simultaneous compression of the celiac trunk, superior mesenteric artery, and renal arteries by the median arcuate ligament.

Nonlinear Study on the Mechanical Performance of Built-Up Cold-Formed Steel Concrete-Filled Columns under Compression

Given their numerous functional and architectural benefits,such as improved bearing capacity and increased resistance to elastic instability modes,cold-formed steel(CFS)built-up sections have become increasingly developed and used in recent years,particularly in the construction industry.This paper presents an analytical and numerical study of assembled CFS two single channel-shaped columns with different slenderness and configurations(backto-back,face-to-face,and box).These columns were joined by double-row rivets for the back-to-back and box configurations,whereas they were welded together for the face-to-face design.The built-up columns were filled with ordinary concrete of good strength.Finite element models were applied,using ABAQUS software,to assess mechanical performance and study the influence of assembly techniques on the behavior of cold-formed columns under axial compression.Analytical approaches based on Eurocode 3 and Eurocode 4 recommendations for un-filled and concrete-filled columns respectively were followed for the numerical analysis,and concrete confinement effects were also considered per American Concrete Institute(ACI)standards for face-to-face and box configurations.The obtained results indicated a good correlation between the numerical results and the proposed analytical methodology which did not exceed 8%.The failure modes showed that the columns failed due to instabilities such as local and global buckling.

A whole process damage constitutive model for layered sandstone under uniaxial compression based on Logistic function

Bedding structural planes significantly influence the mechanical properties and stability of engineering rock masses.This study conducts uniaxial compression tests on layered sandstone with various bedding angles(0°,15°,30°,45°,60°,75°and 90°)to explore the impact of bedding angle on the deformational mechanical response,failure mode,and damage evolution processes of rocks.It develops a damage model based on the Logistic equation derived from the modulus’s degradation considering the combined effect of the sandstone bedding dip angle and load.This model is employed to study the damage accumulation state and its evolution within the layered rock mass.This research also introduces a piecewise constitutive model that considers the initial compaction characteristics to simulate the whole deformation process of layered sandstone under uniaxial compression.The results revealed that as the bedding angle increases from 0°to 90°,the uniaxial compressive strength and elastic modulus of layered sandstone significantly decrease,slightly increase,and then decline again.The corresponding failure modes transition from splitting tensile failure to slipping shear failure and back to splitting tensile failure.As indicated by the modulus’s degradation,the damage characteristics can be categorized into four stages:initial no damage,damage initiation,damage acceleration,and damage deceleration termination.The theoretical damage model based on the Logistic equation effectively simulates and predicts the entire damage evolution process.Moreover,the theoretical constitutive model curves closely align with the actual stress−strain curves of layered sandstone under uniaxial compression.The introduced constitutive model is concise,with fewer parameters,a straightforward parameter determination process,and a clear physical interpretation.This study offers valuable insights into the theory of layered rock mechanics and holds implications for ensuring the safety of rock engineering.

Atomistic evaluation of tension–compression asymmetry in nanoscale body-centered-cubic AlCrFeCoNi high-entropy alloy

The tension and compression of face-centered-cubic high-entropy alloy(HEA) nanowires are significantly asymmetric, but the tension–compression asymmetry in nanoscale body-centered-cubic(BCC) HEAs is still unclear. In this study,the tension–compression asymmetry of the BCC Al Cr Fe Co Ni HEA nanowire is investigated using molecular dynamics simulations. The results show a significant asymmetry in both the yield and flow stresses, with BCC HEA nanowire stronger under compression than under tension. The strength asymmetry originates from the completely different deformation mechanisms in tension and compression. In compression, atomic amorphization dominates plastic deformation and contributes to the strengthening, while in tension, deformation twinning prevails and weakens the HEA nanowire.The tension–compression asymmetry exhibits a clear trend of increasing with the increasing nanowire cross-sectional edge length and decreasing temperature. In particular, the compressive strengths along the [001] and [111] crystallographic orientations are stronger than the tensile counterparts, while the [110] crystallographic orientation shows the exactly opposite trend. The dependences of tension–compression asymmetry on the cross-sectional edge length, crystallographic orientation,and temperature are explained in terms of the deformation behavior of HEA nanowire as well as its variations caused by the change in these influential factors. These findings may deepen our understanding of the tension–compression asymmetry of the BCC HEA nanowires.

Experimental crushing behavior and energy absorption of angular gradient honeycomb structures under quasi-static and dynamic compression

The high variability of shock in terrorist attacks poses a threat to people's lives and properties,necessitating the development of more effective protective structures.This study focuses on the angle gradient and proposes four different configurations of concave hexagonal honeycomb structures.The structures'macroscopic deformation behavior,stress-strain relationship,and energy dissipation characteristics are evaluated through quasi-static compression and Hopkinson pressure bar impact experiments.The study reveals that,under varying strain rates,the structures deform starting from the weak layer and exhibit significant interlayer separation.Additionally,interlayer shear slip becomes more pronounced with increasing strain rate.In terms of quasi-static compression,symmetric gradient structures demonstrate superior energy absorption,particularly the symmetric negative gradient structure(SNG-SMS)with a specific energy absorption of 13.77 J/cm~3.For dynamic impact,unidirectional gradient structures exhibit exceptional energy absorption,particularly the unidirectional positive gradient honeycomb structure(UPG-SML)with outstanding mechanical properties.The angle gradient design plays a crucial role in determining the structure's stability and deformation mode during impact.Fewer interlayer separations result in a more pronounced negative Poisson's ratio effect and enhance the structure's energy absorption capacity.These findings provide a foundation for the rational design and selection of seismic protection structures in different strain rate impact environments.

Quasi-plastic deformation mechanisms and inverse Hall-Petch relationship in nanocrystalline boron carbide under compression

Grain boundaries(GBs)play a significant role in the deformation behaviors of nanocrystalline ceramics.Here,we investigate the compression behaviors of nanocrystalline boron carbide(nB_(4)C)with varying grain sizes using molecular dynamics simulations with a machine-learning force field.The results reveal quasi-plastic deformation mechanisms in nB_(4)C:GB sliding,intergranular amorphization and intragranular amorphization.GB sliding arises from the presence of soft GBs,leading to intergranular amorphization.Intragranular amorphization arises from the interaction between grains with unfavorable orientations and the softened amorphous GBs,and finally causes structural failure.Furthermore,nB_(4)C models with varying grain sizes from 4.07 nm to 10.86 nm display an inverse Hall-Petch relationship due to the GB sliding mechanism.A higher strain rate in nB_(4)C often leads to a higher yield strength,following a 2/3 power relationship.These deformation mechanisms are critical for the design of ceramics with superior mechanical properties.

Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression

Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues,particularly in the field of lung disease diagnosis.One promising avenue involves the use of chest X-Rays,which are commonly utilized in radiology.To fully exploit their potential,researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems.However,constructing and compressing these systems presents a significant challenge,as it relies heavily on the expertise of data scientists.To tackle this issue,we propose an automated approach that utilizes an evolutionary algorithm(EA)to optimize the design and compression of a convolutional neural network(CNN)for X-Ray image classification.Our approach accurately classifies radiography images and detects potential chest abnormalities and infections,including COVID-19.Furthermore,our approach incorporates transfer learning,where a pre-trainedCNNmodel on a vast dataset of chest X-Ray images is fine-tuned for the specific task of detecting COVID-19.This method can help reduce the amount of labeled data required for the task and enhance the overall performance of the model.We have validated our method via a series of experiments against state-of-the-art architectures.

Optimization of tracheoesophageal fistula model established with Tshaped magnet system based on magnetic compression technique

BACKGROUND The magnetic compression technique has been used to establish an animal model of tracheoesophageal fistula(TEF),but the commonly shaped magnets present limitations of poor homogeneity of TEF and poor model control.We designed a Tshaped magnet system to overcome these problems and verified its effectiveness via animal experiments.AIM To investigate the effectiveness of a T-shaped magnet system for establishing a TEF model in beagle dogs.METHODS Twelve beagles were randomly assigned to groups in which magnets of the Tshaped scheme(study group,n=6)or normal magnets(control group,n=6)were implanted into the trachea and esophagus separately under gastroscopy.Operation time,operation success rate,and accidental injury were recorded.After operation,the presence and timing of cough and the time of magnet shedding were observed.Dogs in the control group were euthanized after X-ray and gastroscopy to confirm establishment of TEFs after coughing,and gross specimens of TEFs were obtained.Dogs in the study group were euthanized after X-ray and gastroscopy 2 wk after surgery,and gross specimens were obtained.Fistula size was measured in all animals,and then harvested fistula specimens were examined by hematoxylin and eosin(HE)and Masson trichrome staining.RESULTS The operation success rate was 100%for both groups.Operation time did not differ between the study group(5.25 min±1.29 min)and the control group(4.75 min±1.70 min;P=0.331).No bleeding,perforation,or unplanned magnet attraction occurred in any animal during the operation.In the early postoperative period,all dogs ate freely and were generally in good condition.Dogs in the control group had severe cough after drinking water at 6-9 d after surgery.X-ray indicated that the magnets had entered the stomach,and gastroscopy showed TEF formation.Gross specimens of TEFs from the control group showed the formation of fistulas with a diameter of 4.94 mm±1.29 mm(range,3.52-6.56 mm).HE and Masson trichrome staining showed scar tissue formation and hierarchical structural disorder at the fistulas.Dogs in the study group did not exhibit obvious coughing after surgery.X-ray examination 2 wk after surgery indicated fixed magnet positioning,and gastroscopy showed no change in magnet positioning.The magnets were removed using a snare under endoscopy,and TEF was observed.Gross specimens showed well-formed fistulas with a diameter of 6.11 mm±0.16 mm(range,5.92-6.36 mm),which exceeded that in the control group(P<0.001).Scar formation was observed on the internal surface of fistulas by HE and Masson trichrome staining,and the structure was more regular than that in the control group.CONCLUSION Use of the modified T-shaped magnet scheme is safe and feasible for establishing TEF and can achieve a more stable and uniform fistula size compared with ordinary magnets.Most importantly,this model offers better controllability,which improves the flexibility of follow-up studies.

Color Image Compression and Encryption Algorithm Based on 2D Compressed Sensing and Hyperchaotic System

With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of pictures.This study presents a new approach to the encryption and compression of color images.It is predicated on 2D compressed sensing(CS)and the hyperchaotic system.First,an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong security.Then,the processed images are con-currently encrypted and compressed using 2D CS.Among them,chaotic sequences replace traditional random measurement matrices to increase the system’s security.Third,the processed images are re-encrypted using a combination of permutation and diffusion algorithms.In addition,the 2D projected gradient with an embedding decryption(2DPG-ED)algorithm is used to reconstruct images.Compared with the traditional reconstruction algorithm,the 2DPG-ED algorithm can improve security and reduce computational complexity.Furthermore,it has better robustness.The experimental outcome and the performance analysis indicate that this algorithm can withstand malicious attacks and prove the method is effective.

Lateral ring compression test applied to a small caliber steel jacket:Identification of a constitutive model

The evolution of threats and scenarios requires continuous performance improvements of ballistic protections for armed forces.From a modeling point of view,it is necessary to use sufficiently precise material behavior models to accurately describe the phenomena observed during the impact of a projectile on a protective equipment.In this context,the goal of this paper is to characterize the behavior of a small caliber steel jacket by combining experimental and numerical approaches.The experimental method is based on the lateral compression of ring specimens directly machined from the thin and small ammunition.Various speeds and temperatures are considered in a quasi-static regime in order to reveal the strain rate and temperature dependencies of the tested material.The Finite Element Updating Method(FEMU)is used.Experimental results are coupled with an inverse optimization method and a finite element numerical model in order to determine the parameters of a constitutive model representative of the jacket material.Predictions of the present model are verified against experimental results and a parametric study as well as a discussion on the identified material parameters are proposed.The results indicate that the strain hardening parameter can be neglected and the behavior of the thin steel jacket can be described by a modeling without strain hardening sensitivity.

Experimental and numerical study on dynamic mechanical behaviors of shale under true triaxial compression at high strain rate

High-energy gas fracturing of shale is a novel,high efficacy and eco-friendly mining technique,which is a typical dynamic perturbing behavior.To effectively extract shale gas,it is important to understand the dynamic mechanical properties of shale.Dynamic experiments on shale subjected to true triaxial compression at different strain rates are first conducted in this research.The dynamic stress-strain curves,peak strain,peak stress and failure modes of shale are investigated.The results of the study indicate that the intermediate principal stress and the minor principal stress have the significant influence on the dynamic mechanical behaviors,although this effect decreases as the strain rate increases.The characteristics of compression-shear failure primarily occur in shale subjected to triaxial compression at high strain rates,which distinguishes it from the fragmentation characteristics observed in shale under dynamic uniaxial compression.Additionally,a numerical three-dimensional Split Hopkinson Pressure Bar(3D-SHPB),which is established by coupling PFC3D and FLAC3D methods,is validated to replicate the laboratory characteristics of shale.The dynamic mechanical characteristics of shale subjected to different confining stresses are systematically investigated by the coupling PFC3D and FLAC3D method.The numerical results are in good agreement with the experimental data.

A Novel Quantization and Model Compression Approach for Hardware Accelerators in Edge Computing

Massive computational complexity and memory requirement of artificial intelligence models impede their deploy-ability on edge computing devices of the Internet of Things(IoT).While Power-of-Two(PoT)quantization is pro-posed to improve the efficiency for edge inference of Deep Neural Networks(DNNs),existing PoT schemes require a huge amount of bit-wise manipulation and have large memory overhead,and their efficiency is bounded by the bottleneck of computation latency and memory footprint.To tackle this challenge,we present an efficient inference approach on the basis of PoT quantization and model compression.An integer-only scalar PoT quantization(IOS-PoT)is designed jointly with a distribution loss regularizer,wherein the regularizer minimizes quantization errors and training disturbances.Additionally,two-stage model compression is developed to effectively reduce memory requirement,and alleviate bandwidth usage in communications of networked heterogenous learning systems.The product look-up table(P-LUT)inference scheme is leveraged to replace bit-shifting with only indexing and addition operations for achieving low-latency computation and implementing efficient edge accelerators.Finally,comprehensive experiments on Residual Networks(ResNets)and efficient architectures with Canadian Institute for Advanced Research(CIFAR),ImageNet,and Real-world Affective Faces Database(RAF-DB)datasets,indicate that our approach achieves 2×∼10×improvement in the reduction of both weight size and computation cost in comparison to state-of-the-art methods.A P-LUT accelerator prototype is implemented on the Xilinx KV260 Field Programmable Gate Array(FPGA)platform for accelerating convolution operations,with performance results showing that P-LUT reduces memory footprint by 1.45×,achieves more than 3×power efficiency and 2×resource efficiency,compared to the conventional bit-shifting scheme.

Three dimensional discrete element modelling of the conventional compression behavior of gas hydrate bearing coal

To analyze the relationship between macro and meso parameters of the gas hydrate bearing coal(GHBC)and to calibrate the meso-parameters,the numerical tests were conducted to simulate the laboratory triaxial compression tests by PFC3D,with the parallel bond model employed as the particle contact constitutive model.First,twenty simulation tests were conducted to quantify the relationship between the macro–meso parameters.Then,nine orthogonal simulation tests were performed using four meso-mechanical parameters in a three-level to evaluate the sensitivity of the meso-mechanical parameters.Furthermore,the calibration method of the meso-parameters were then proposed.Finally,the contact force chain,the contact force and the contact number were examined to investigate the saturation effect on the meso-mechanical behavior of GHBC.The results show that:(1)The elastic modulus linearly increases with the bonding stiffness ratio and the friction coefficient while exponentially increasing with the normal bonding strength and the bonding radius coefficient.The failure strength increases exponentially with the increase of the friction coefficient,the normal bonding strength and the bonding radius coefficient,and remains constant with the increase of bond stiffness ratio;(2)The friction coefficient and the bond radius coefficient are most sensitive to the elastic modulus and the failure strength;(3)The number of the force chains,the contact force,and the bond strength between particles will increase with the increase of the hydrate saturation,which leads to the larger failure strength.

Anisotropic strength,deformation and failure of gneiss granite under high stress and temperature coupled true triaxial compression

The anisotropic mechanical behavior of rocks under high-stress and high-temperature coupled conditions is crucial for analyzing the stability of surrounding rocks in deep underground engineering.This paper is devoted to studying the anisotropic strength,deformation and failure behavior of gneiss granite from the deep boreholes of a railway tunnel that suffers from high tectonic stress and ground temperature in the eastern tectonic knot in the Tibet Plateau.High-temperature true triaxial compression tests are performed on the samples using a self-developed testing device with five different loading directions and three temperature values that are representative of the geological conditions of the deep underground tunnels in the region.Effect of temperature and loading direction on the strength,elastic modulus,Poisson’s ratio,and failure mode are analyzed.The method for quantitative identification of anisotropic failure is also proposed.The anisotropic mechanical behaviors of the gneiss granite are very sensitive to the changes in loading direction and temperature under true triaxial compression,and the high temperature seems to weaken the inherent anisotropy and stress-induced deformation anisotropy.The strength and deformation show obvious thermal degradation at 200℃due to the weakening of friction between failure surfaces and the transition of the failure pattern in rock grains.In the range of 25℃ 200℃,the failure is mainly governed by the loading direction due to the inherent anisotropy.This study is helpful to the in-depth understanding of the thermal-mechanical behavior of anisotropic rocks in deep underground projects.

Target acquisition performance in the presence of JPEG image compression

This paper presents an investigation on the effect of JPEG compression on the similarity between the target image and the background,where the similarity is further used to determine the degree of clutter in the image.Four new clutter metrics based on image quality assessment are introduced,among which the Haar wavelet-based perceptual similarity index,known as HaarPSI,provides the best target acquisition prediction results.It is shown that the similarity between the target and the background at the boundary between visually lossless and visually lossy compression does not change significantly compared to the case when an uncompressed image is used.In future work,through subjective tests,it is necessary to check whether this presence of compression at the threshold of just noticeable differences will affect the human target acquisition performance.Similarity values are compared with the results of subjective tests of the well-known target Search_2 database,where the degree of agreement between objective and subjective scores,measured through linear correlation,reached a value of 90%.

Stochastic Gradient Compression for Federated Learning over Wireless Network

As a mature distributed machine learning paradigm,federated learning enables wireless edge devices to collaboratively train a shared AI-model by stochastic gradient descent(SGD).However,devices need to upload high-dimensional stochastic gradients to edge server in training,which cause severe communication bottleneck.To address this problem,we compress the communication by sparsifying and quantizing the stochastic gradients of edge devices.We first derive a closed form of the communication compression in terms of sparsification and quantization factors.Then,the convergence rate of this communicationcompressed system is analyzed and several insights are obtained.Finally,we formulate and deal with the quantization resource allocation problem for the goal of minimizing the convergence upper bound,under the constraint of multiple-access channel capacity.Simulations show that the proposed scheme outperforms the benchmarks.

Information-Theoretic Limits on Compression of Semantic Information

As conventional communication systems based on classic information theory have closely approached Shannon capacity,semantic communication is emerging as a key enabling technology for the further improvement of communication performance.However,it is still unsettled on how to represent semantic information and characterise the theoretical limits of semantic-oriented compression and transmission.In this paper,we consider a semantic source which is characterised by a set of correlated random variables whose joint probabilistic distribution can be described by a Bayesian network.We give the information-theoretic limit on the lossless compression of the semantic source and introduce a low complexity encoding method by exploiting the conditional independence.We further characterise the limits on lossy compression of the semantic source and the upper and lower bounds of the rate-distortion function.We also investigate the lossy compression of the semantic source with two-sided information at the encoder and decoder,and obtain the corresponding rate distortion function.We prove that the optimal code of the semantic source is the combination of the optimal codes of each conditional independent set given the side information.

A numerical survey of parameters to reach ignition condition for axial compression of a large-sized field reversed configuration

Field reversed configuration(FRC)is widely considered as an ideal target plasma for magnetoinertial fusion.However,its confinement and stability,both proportional to the radius,will deteriorate inevitably during radial compression.Hence,we propose a new fusion approach based on axial compression of a large-sized FRC.The axial compression can be made by plasma jets or plasmoids converging onto the axial ends of the FRC.The parameter space that can reach the ignition condition while preserving the FRC's overall quality is studied using a numerical model based on different FRC confinement scalings.It is found that ignition is possible for a large FRC that can be achieved with the current FRC formation techniques if compression ratio is greater than 50.A more realistic compression is to combine axial with moderate radial compression,which is also presented and calculated in this work.

Distributed Stochastic Optimization with Compression for Non-Strongly Convex Objectives

We are investigating the distributed optimization problem,where a network of nodes works together to minimize a global objective that is a finite sum of their stored local functions.Since nodes exchange optimization parameters through the wireless network,large-scale training models can create communication bottlenecks,resulting in slower training times.To address this issue,CHOCO-SGD was proposed,which allows compressing information with arbitrary precision without reducing the convergence rate for strongly convex objective functions.Nevertheless,most convex functions are not strongly convex(such as logistic regression or Lasso),which raises the question of whether this algorithm can be applied to non-strongly convex functions.In this paper,we provide the first theoretical analysis of the convergence rate of CHOCO-SGD on non-strongly convex objectives.We derive a sufficient condition,which limits the fidelity of compression,to guarantee convergence.Moreover,our analysis demonstrates that within the fidelity threshold,this algorithm can significantly reduce transmission burden while maintaining the same convergence rate order as its no-compression equivalent.Numerical experiments further validate the theoretical findings by demonstrating that CHOCO-SGD improves communication efficiency and keeps the same convergence rate order simultaneously.And experiments also show that the algorithm fails to converge with low compression fidelity and in time-varying topologies.Overall,our study offers valuable insights into the potential applicability of CHOCO-SGD for non-strongly convex objectives.Additionally,we provide practical guidelines for researchers seeking to utilize this algorithm in real-world scenarios.