On a general theory for compressing process and aeroacoustics:linear analysis

Of the three mutually coupled fundamental processes （shearing, compressing, and thermal） in a general fluid motion, only the general formulation for the compress- ing process and a subprocess of it, the subject of aeroacous- tics, as well as their physical coupling with shearing and thermal processes, have so far not reached a consensus. This situation has caused difficulties for various in-depth complex multiprocess flow diagnosis, optimal configuration design, and flow/noise control. As the first step toward the desired formulation in fully nonlinear regime, this paper employs the operator factorization method to revisit the analytic linear theories of the fundamental processes and their decomposi- tion, especially the further splitting of compressing process into acoustic and entropy modes, developed in 1940s-1980s. The flow treated here is small disturbances of a compressible, viscous, and heat-conducting polytropic gas in an unbounded domain with arbitrary source of mass, external body force, and heat addition. Previous results are thereby revised and extended to a complete and unified theory. The theory pro- vides a necessary basis and valuable guidance for developing corresponding nonlinear theory by clarifying certain basic issues, such as the proper choice of characteristic variables of compressing process and the feature of their governing equations.

Parameters Compressing in Deep Learning

With the popularity of deep learning tools in image decomposition and natural language processing,how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem to be solved.These parameters are huge and can be as many as millions.At present,a feasible direction is to use the sparse representation technique to compress the parameter matrix to achieve the purpose of reducing parameters and reducing the storage pressure.These methods include matrix decomposition and tensor decomposition.To let vector take advance of the compressing performance of matrix decomposition and tensor decomposition,we use reshaping and unfolding to let vector be the input and output of Tensor-Factorized Neural Networks.We analyze how reshaping can get the best compress ratio.According to the relationship between the shape of tensor and the number of parameters,we get a lower bound of the number of parameters.We take some data sets to verify the lower bound.

Compressing Information of Target Tracking in Wireless Sensor Networks

Target tracking is a well studied topic in wireless sensor networks. It is a procedure that nodes in the network collaborate in detecting targets and transmitting their information to the base-station continuously, which leads to data implosion and redundancy. To reduce traffic load of the network, a data compressing based target tracking protocol is proposed in this work. It first incorporates a clustering based data gather method to group sensor nodes into clusters. Then a novel threshold technique with bounded error is proposed to exploit the spatial correlation of sensed data and compress the data in the same cluster. Finally, the compact data presentations are transmitted to the base-station for targets localization. We evaluate our approach with a comprehensive set of simulations. It can be concluded that the proposed method yields excellent performance in energy savings and tracking quality.

Compressing ultrafast electron pulse by radio frequency cavity

An ultrafast electron diffraction technique with both high temporal and spatial resolution has been shown to be a powerful tool to observe the material transient structural change on an atomic scale.The space charge forces in a multi-electron bunch will greatly broaden the electron pulse width,and therefore limit the temporal resolution of the high brightness electron pulse.Here in this work,we design an ultrafast electron diffraction system,and utilize a radio frequency cavity to realize the ultrafast electron pulse compression.We experimentally demonstrate that the stretched electron pulse width of14.98 ps with an electron energy of 40 keV and the electron number of 1.0 ×10;can be maximally compressed to about0.61 ps for single-pulse measurement and 2.48 ps for multi-pulse measurement by using a 3.2-GHz radiofrequency cavity.We also theoretically and experimentally analyze the parameters influencing the electron pulse compression efficiency for single-and multi-pulse measurements by considering radiofrequency field time jitter,electron pulse time jitter and their relative time jitter.We suggest that increasing the electron energy or shortening the distance between the compression cavity and the streak cavity can further improve the electron pulse compression efficiency.These experimental and theoretical results are very helpful for designing the ultrafast electron diffraction experiment equipment and compressing the ultrafast electron pulse width in a future study.

Assessment of compressive strength of jet grouting by machine learning

Jet grouting is one of the most popular soil improvement techniques,but its design usually involves great uncertainties that can lead to economic cost overruns in construction projects.The high dispersion in the properties of the improved material leads to designers assuming a conservative,arbitrary and unjustified strength,which is even sometimes subjected to the results of the test fields.The present paper presents an approach for prediction of the uniaxial compressive strength(UCS)of jet grouting columns based on the analysis of several machine learning algorithms on a database of 854 results mainly collected from different research papers.The selected machine learning model(extremely randomized trees)relates the soil type and various parameters of the technique to the value of the compressive strength.Despite the complex mechanism that surrounds the jet grouting process,evidenced by the high dispersion and low correlation of the variables studied,the trained model allows to optimally predict the values of compressive strength with a significant improvement with respect to the existing works.Consequently,this work proposes for the first time a reliable and easily applicable approach for estimation of the compressive strength of jet grouting columns.

Rheological properties and concentration evolution of thickened tailings under the coupling effect of compression and shear

Cemented paste backfill(CPB)is a key technology for green mining in metal mines,in which tailings thickening comprises the primary link of CPB technology.However,difficult flocculation and substandard concentrations of thickened tailings often occur.The rheological properties and concentration evolution in the thickened tailings remain unclear.Moreover,traditional indoor thickening experiments have yet to quantitatively characterize their rheological properties.An experiment of flocculation condition optimization based on the Box-Behnken design(BBD)was performed in the study,and the two response values were investigated:concentration and the mean weighted chord length(MWCL)of flocs.Thus,optimal flocculation conditions were obtained.In addition,the rheological properties and concentration evolution of different flocculant dosages and ultrafine tailing contents under shear,compression,and compression-shear coupling experimental conditions were tested and compared.The results show that the shear yield stress under compression and compression-shear coupling increases with the growth of compressive yield stress,while the shear yield stress increases slightly under shear.The order of shear yield stress from low to high under different thickening conditions is shear,compression,and compression-shear coupling.Under compression and compression-shear coupling,the concentration first rapidly increases with the growth of compressive yield stress and then slowly increases,while concentration increases slightly under shear.The order of concentration from low to high under different thickening conditions is shear,compression,and compression-shear coupling.Finally,the evolution mechanism of the flocs and drainage channels during the thickening of the thickened tailings under different experimental conditions was revealed.

Compressing and Coding Method of Seismic Data

Aiming at the characteristics of the seismic exploration signals, the paper studies the image coding technology, the coding standard and algorithm, brings forward a new scheme of admixing coding for seismic data compression. Based on it, a set of seismic data compression software has been developed.

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.

Superhard BC_2N:an Orthogonal Crystal Obtained by Transversely Compressing(3,0)-CNTs and(3,0)-BNNTs

By means of density functional theory calculations, an orthogonal boron-carbon-nitrogen compound called （3,0）- BC2N is predicted, which can be obtained by transversely compressing （3,03 carbon nanotubes （CNTs） and boron nitride nanotubes （BNNTs）. Its structural stability, elastic properties, mechanical properties and electronic structure are systematically investigated. The results show that （3,0）-BU2N is a superhard material with a direct bandgap. However, its similar structures, （3,0）-C and （3,0）-BN are indirect semiconductors. Strikingly, （3,0）-C is harder than diamond. We also simulate the x-ray diffraction of （3,0）-BC2N to support future experimental investigations. In addition, our study shows that the transition from （3,03 CNTS and BNNTs to （3,0）-BC2N is irreversible.

Protective effect of compressing arc extinguishing lightning protection device on superimposed lightning strikes

Traditional lightning protection measures can not solve the problem of superimposed lightning strikes.This paper presents a compressing arc extinguishing lightning protection device,which can solve the problem of superimposed lightning strikes.This device can extinguish the power frequency continuous current arc quickly in 1-2 ms.It is far less than the response time of relay protection,which can avoid lightning trips and improve the reliability of power supply.The computer simulation and engineering practice show that the compressing arc extinguishing device has good protection effect on superimposed lightning strikes.

Simultaneous laparoscopic and arthroscopic excision of a huge juxta-articular ganglionic cyst compressing the sciatic nerve:A case report

BACKGROUND A large ganglionic cyst extending from the hip joint to the intrapelvic cavity through the sciatic notch is a rare space-occupying lesion associated with compressive lower-extremity neuropathy.A cyst in the pelvic cavity compressing the intrapelvic-sciatic nerve is easily missed in the diagnostic process because it usually presents as atypical symptoms of an extraperitoneal-intrapelvic tumor.We present a case of a huge ganglionic cyst that was successfully excised laparoscopically and endoscopically by a gynecologist and an orthopedic surgeon.CASE SUMMARY A 52-year-old woman visited our hospital complaining of pain and numbness in her left buttock while sitting.The pain began 3 years ago and worsened,while the numbness in the left lower extremity lasted 1 mo.She was diagnosed and unsuccessfully treated at several tertiary referral centers many years ago.Magnetic resonance imaging revealed a suspected paralabral cyst(5 cm×5 cm×4.6 cm)in the left hip joint,extending to the pelvic cavity through the greater sciatic notch.The CA-125 and CA19-9 tumor marker levels were within normal limits.However,the cyst was compressing the sciatic nerve.Accordingly,endoscopic and laparoscopic neural decompression and mass excision were performed simultaneously.A laparoscopic examination revealed a tennis-ball-sized cyst filled with gelatinous liquid,stretching deep into the hip joint.An excisional biopsy performed in the pelvic cavity and deep gluteal space confirmed the accumulation of ganglionic cysts from the hip joint into the extrapelvic intraperitoneal cavity.CONCLUSION Intra-or extra-sciatic nerve-compressing lesion should be considered in cases of sitting pain radiating down the ipsilateral lower extremity.This large juxta-articular ganglionic cyst was successfully treated simultaneously using laparoscopy and arthroscopy.

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.

Restoration of the JPEG Maximum Lossy Compressed Face Images with Hourglass Block-GAN

In the context of high compression rates applied to Joint Photographic Experts Group(JPEG)images through lossy compression techniques,image-blocking artifacts may manifest.This necessitates the restoration of the image to its original quality.The challenge lies in regenerating significantly compressed images into a state in which these become identifiable.Therefore,this study focuses on the restoration of JPEG images subjected to substantial degradation caused by maximum lossy compression using Generative Adversarial Networks(GAN).The generator in this network is based on theU-Net architecture.It features a newhourglass structure that preserves the characteristics of the deep layers.In addition,the network incorporates two loss functions to generate natural and high-quality images:Low Frequency(LF)loss and High Frequency(HF)loss.HF loss uses a pretrained VGG-16 network and is configured using a specific layer that best represents features.This can enhance the performance in the high-frequency region.In contrast,LF loss is used to handle the low-frequency region.The two loss functions facilitate the generation of images by the generator,which can mislead the discriminator while accurately generating high-and low-frequency regions.Consequently,by removing the blocking effects frommaximum lossy compressed images,images inwhich identities could be recognized are generated.This study represents a significant improvement over previous research in terms of the image resolution performance.

Chaotic CS Encryption:An Efficient Image Encryption Algorithm Based on Chebyshev Chaotic System and Compressive Sensing

Images are the most important carrier of human information. Moreover, how to safely transmit digital imagesthrough public channels has become an urgent problem. In this paper, we propose a novel image encryptionalgorithm, called chaotic compressive sensing (CS) encryption (CCSE), which can not only improve the efficiencyof image transmission but also introduce the high security of the chaotic system. Specifically, the proposed CCSEcan fully leverage the advantages of the Chebyshev chaotic system and CS, enabling it to withstand various attacks,such as differential attacks, and exhibit robustness. First, we use a sparse trans-form to sparse the plaintext imageand then use theArnold transformto perturb the image pixels. After that,we elaborate aChebyshev Toeplitz chaoticsensing matrix for CCSE. By using this Toeplitz matrix, the perturbed image is compressed and sampled to reducethe transmission bandwidth and the amount of data. Finally, a bilateral diffusion operator and a chaotic encryptionoperator are used to perturb and expand the image pixels to change the pixel position and value of the compressedimage, and ultimately obtain an encrypted image. Experimental results show that our method can be resistant tovarious attacks, such as the statistical attack and noise attack, and can outperform its current competitors.

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 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.

Fluid-Related Performances and Compressive Strength of Clinker-Free Cementitious Backfill Material Based on Phosphate Tailings

Phosphate tailings are usually used as backfill material in order to recycle tailings resources.This study considers the effect of the mix proportions of clinker-free binders on the fluidity,compressive strength and other key performances of cementitious backfill materials based on phosphate tailings.In particular,three solid wastes,phosphogypsum(PG),semi-aqueous phosphogypsum(HPG)and calcium carbide slag(CS),were selected to activate wet ground granulated blast furnace slag(WGGBS)and three different phosphate tailings backfill materials were prepared.Fluidity,rheology,settling ratio,compressive strength,water resistance and ion leaching behavior of backfill materials were determined.According to the results,when either PG or HPG is used as the sole activator,the fluidity properties of the materials are enhanced.Phosphate tailings backfill material activated with PG present the largest fluidity and the lowest yield stress.Furthermore,the backfill material’s compressive strength is considerably increased to 2.9 MPa at 28 days after WGGBS activation using a mix of HPG and CS,all with a settling ratio of only 1.15 percent.Additionally,all the three ratios of binder have obvious solidification effects on heavy metal ions Cu and Zn,and P in phosphate tailings.

An Investigation into the Compressive Strength,Permeability and Microstructure of Quartzite-Rock-Sand Mortar

River sand is an essential component used as a fine aggregate in mortar and concrete.Due to unrestrained exploitation,river sand resources are gradually being exhausted.This requires alternative solutions.This study deals with the properties of cement mortar containing different levels of manufactured sand(MS)based on quartzite,used to replace river sand.The river sand was replaced at 20%,40%,60%and 80%with MS(by weight or volume).The mechanical properties,transfer properties,and microstructure were examined and compared to a control group to study the impact of the replacement level.The results indicate that the compressive strength can be improved by increasing such a level.The strength was improved by 35.1%and 45.5%over that of the control mortar at replacement levels of 60%and 80%,respectively.Although there was a weak link between porosity and gas permeability in the mortars with manufactured sand,the gas permeability decreased with growing the replacement level.The microstructure of the MS mortar was denser,and the cement paste had fewer microcracks with increasing the replacement level.

Compressive performance of innovative reinforced pillars in closed/abandoned mines

Pillar is closely related to the stability and reliability of underground spaces in closed/abandoned mines.The present research introduced a new technique to strengthen square cement mortar columns via fiber-reinforced polymer(FRP)strips to verify the strengthening effect of FRP on pillars.Compared to a fully wrapped FRP jacket,the advantages of FRP strip are cost-effective and easy-to-construct.A series of compression tests as well as theoretical analysis were carried out to explore the mechanical behavior of square cement mortar specimens partially strengthened with FRP strips.The results verified the effectiveness of FRP strips in enhancing the stress and strain of cement mortar.Different from unconfined cement mortar specimens,these FRP-strengthened cement mortar specimens are featured with the double-peaked behaviors,mainly attributed to the stress state transformation from a one-dimensional to a three-dimensional stress state.It also indicated that the enhancement of stress increased with the FRP strip width.Moreover,the brittle-ductile transition ductile failure characteristics were also observed in FRP-confined cement mortar specimens.The ultimate ductility of the cement mortar specimen decreases gradually with the growth of the FRP strip width.The main contribution of this research is to enrich the strengthening techniques for residual pillars.

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.