Compression Applications Research Articles

Research on the application of CNN algorithm based on chaotic recursive diagonal model in medical image processing

Abstract In this paper, the image processing capability of the CNN algorithm under the chaotic recursive diagonal model is explored from two aspects of medical image fusion and compression. By analyzing the structure of the chaotic recursive diagonal model, it is possible to combine it with a neural network. A convolutional neural network is used to automatically extract the focusing features of an image and output the probability of a pixel focusing. Combining the convolutional layer to extract image features with the activation function to nonlinearly map the feature map to achieve the effect of image fusion. Focusing on the exploration of the CNN algorithm for image fusion in image compression application processes. The results show that in the image fusion experiments, the CNN algorithm for image fusion data MI mean value is 6.1051, variance is 0.4418. QY mean value is 0.9859. The variance value is 0.0014. Compared to other algorithms, CNN in the image fusion effect has the effect of better distinguishing the edge details and making the appropriate decision. The CNN algorithm of the compression time is shorter. The time used in the compression of the X-chest image is 2.75s, which is 0.42 less than other algorithms. This study provides a new research perspective for medical image processing and is beneficial to improving the efficiency of medical image processing.

A Study of Disjoint Set Union in Programming Competitions

Disjoint Set Union (DSU) is a tree data structure, which is used to effectively deal with the problems of merging and querying disjoint sets. The DSU algorithm can be used to merge sets and query to which set the node belongs. The DSU algorithm is usually implemented using arrays and tree structures, but there are also methods that use hash tables. The DSU algorithm has a wide range of applications in the connectivity of graph theory, social network and image processing. It helps researchers better understand and analyze set operations, provides a basis for subsequent work, and promotes the solution and optimization of various problems in the field. At the same time, in the programming competition of college students, the use of DSU is more frequent, usually the use of set query is more, resulting in high time complexity and unable to solve the problem quickly. Therefore, path compression strategy is introduced to significantly improve the efficiency of set query. Finally, the application of path compression in union search is introduced in the form of programming competition.

F-Divergences and Their Applications in Lossy Compression and Bounding Generalization Error

In this paper, we provide three applications for f-divergences: (i) we introduce Sanov’s upper bound on the tail probability of the sum of independent random variables based on super-modular f-divergence and show that our generalized Sanov’s bound strictly improves over ordinary one, (ii) we consider the lossy compression problem which studies the set of achievable rates for a given distortion and code length. We extend the rate-distortion function using mutual f-information and provide new and strictly better bounds on achievable rates in the finite blocklength regime using super-modular f-divergences, and (iii) we provide a connection between the generalization error of algorithms with bounded input/output mutual f-information and a generalized rate-distortion problem. This connection allows us to bound the generalization error of learning algorithms using lower bounds on the f-rate-distortion function. Our bound is based on a new lower bound on the rate-distortion function that (for some examples) strictly improves over previously best-known bounds.

Enhancing Security in Database Grid Infrastructure for Storage Clusters

This research project primarily focused on improving security by addressing vulnerabilities and creating a cost-scalable storage cluster solution, for applications. The Oracle Grid Infrastructure for Storage Clusters (OGISC) represents cutting-edge advancements in this field. The research extensively explores the philosophy of OGISC. Explains its core methodology. Recognizing the weaknesses of existing security mechanisms, we propose a solution to enhance security measures. A key aspect of our investigation involves integrating Glusterfs, a system known for its ability to scale linearly. We delve into the architecture of the solution demystifying the storage scale-out processes to its operation. Our study goes beyond integration by developing an approach and metadata model specifically tailored for Glusterfs ensuring optimal performance and robustness. One noteworthy aspect of our research is the application of Glusterfs compression with OpenVPN. This exploration highlights the benefits derived from this integration emphasizing how OpenVPN enhances Glusterfs capabilities. Rigorous analysis stages serve as the foundation for our findings resulting in a forward-thinking solution. Finally, we conclude this research with an examination of avenues for future exploration in this dynamic field.

Fatigue life of plain concrete subjected to low frequency uniaxial stress reversal loading

Most concrete structures sustain cyclic loading conditions during their service life. The accumulated damage caused by this type of loading can be regarded as fatigue and leads to sudden failures. Therefore, knowledge regarding the behavior of concrete under repeated loading is critical in structural design. It becomes even more critical when the fatigue stresses range from tension to compression. Since the fatigue behavior of plain concrete under cyclic sequential application of tension and compression, known as stress reversal, could differ from the behavior under pure tensile or compressive fatigue, concrete fatigue analysis under different cases of stress reversal is pursued in this study. A low frequency of 0.1 Hz is chosen for this study to replicate the slow recurring nature of certain loading conditions. Analysis indicates that stress reversal generally causes more severe deterioration and reduces the number of cycles to failure when compared to tensile fatigue. Results also indicate that adding some level of compression largely contributes to the energy that is required to fail the specimens under stress reversal fatigue. A macroscopic cross-section failure analysis is also followed in this research, revealing that specimens with highest concentration of fractured aggregates achieved longer fatigue lives.

Thermo-mechanical properties and internal architecture of PI composites for high-pressure hydrogen applications

The efficient transport of Hydrogen is pivotal to the wide scale adaption of energy produced from renewable sources. Reciprocating piston compressors with high strength non-lubricated sealing solutions for piston and rod packing rings will be a key technology to fulfill gas purity and high-pressure gradients demands set by hydrogen applications. Polyimide polymer matrix composites have seen use in tribological applications and promise high mechanical strength and temperature resistance. The presented work describes carbon fiber reinforced Polyimide blends in comparison, characterized by complementary advanced methods to investigate their properties and potential for reciprocating compressor applications. Thermo-mechanical and tribological testing was supported by microstructure analysis utilizing synchrotron tomography and electron microscopy, pinpointing the necessity of dry lubricating additives such as PTFE. New insights in micromechanical deformation behavior of fiber reinforced polymers are given and promising fiber-reinforced polyimide compositions suitable for high-pressure hydrogen compression applications were identified.

General Image Manipulation Detection Using Feature Engineering and a Deep Feed-Forward Neural Network

Within digital forensics, a notable emphasis is placed on the detection of the application of fundamental image-editing operators, including but not limited to median filters, average filters, contrast enhancement, resampling, and various other operations closely associated with these techniques. When conducting a historical analysis of an image that has potentially undergone various modifications in the past, it is a logical initial approach to search for alterations made by fundamental operators. This paper presents the development of a deep-learning-based system designed for the purpose of detecting fundamental manipulation operations. The research involved training a multilayer perceptron using a feature set of 36 dimensions derived from the gray-level co-occurrence matrix, gray-level run-length matrix, and normalized streak area. The system detected median filtering, mean filtering, the introduction of additive white Gaussian noise, and the application of JPEG compression in digital Images. Our system, which utilizes a multilayer perceptron trained with a 36-feature set, achieved an accuracy of 99.46% and outperformed state-of-the-art deep-learning-based solutions, which achieved an accuracy of 97.89%.

Bioinspired High-Strength Borate Cross-Linked Microfibrillated Cellulose Composite Laminate with Self-Extinguishing Flame Retardance and Superhydrophobicity for Self-Cleaning.

The cross-linking of borates enhances the intercellular structural connection, resulting in the creation of a mechanically superior structural material composed of lignocellulose and borate. This is accomplished by employing a mechanical pretreatment procedure and a binder-free hot-pressing method. Nevertheless, these materials frequently encounter constraints in humid environments, making it challenging to simultaneously achieve the desired performance objectives. Here, the prepressed bulk of microfibrillated cellulose is modified and subjected to hot pressing, while ensuring that the enhanced physical and mechanical properties of lignocellulosic recombinant materials are maintained. This modified material is termed the microfibrillated cellulose composite laminate (MCCL). These findings indicate that the application of compression, shear, and friction forces during hot-pressing results in the formation of a compact laminated structure using pine lignocellulose. The self-cleaning MCCL exhibits significantly improved mechanical properties compared with untreated lignocellulose materials (ULM). Specifically, the flexural strength (MOR), modulus of elasticity (MOE), and internal bonding strength (IB) of self-cleaning MCCL are found to be 5 times, 2.5 times, and 4.1 times higher, respectively, than those of ULM. This improvement in the pine lignocellulose can be attributed to the enhanced layering and branching that occurs during mechanical milling. This results in a higher proportion of ester and hydrogen bonds, as well as an increased exposure of hydroxyl groups. As a result, the modified MCCL exhibits self-cleaning properties, as evidenced by its surface water contact angle (WCA) of 152°. The rolling/jumping water droplets, which contain pollutants, effectively remove graphite powder from the surface, leaving it clean. Moreover, MCCL demonstrates exceptional dimensional stability and flame-retardant self-extinguishing properties, making it highly promising as a structural material in engineering technology.

A Review of GAN-Based Super-Resolution Reconstruction for Optical Remote Sensing Images

High-resolution images have a wide range of applications in image compression, remote sensing, medical imaging, public safety, and other fields. The primary objective of super-resolution reconstruction of images is to reconstruct a given low-resolution image into a corresponding high-resolution image by a specific algorithm. With the emergence and swift advancement of generative adversarial networks (GANs), image super-resolution reconstruction is experiencing a new era of progress. Unfortunately, there has been a lack of comprehensive efforts to bring together the advancements made in the field of super-resolution reconstruction using generative adversarial networks. Hence, this paper presents a comprehensive overview of the super-resolution image reconstruction technique that utilizes generative adversarial networks. Initially, we examine the operational principles of generative adversarial networks, followed by an overview of the relevant research and background information on reconstructing remote sensing images through super-resolution techniques. Next, we discuss significant research on generative adversarial networks in high-resolution image reconstruction. We cover various aspects, such as datasets, evaluation criteria, and conventional models used for image reconstruction. Subsequently, the super-resolution reconstruction models based on generative adversarial networks are categorized based on whether the kernel blurring function is recognized and utilized during training. We provide a brief overview of the utilization of generative adversarial network models in analyzing remote sensing imagery. In conclusion, we present a prospective analysis of forthcoming research directions pertaining to super-resolution reconstruction methods that rely on generative adversarial networks.

Compression Characteristics of Liquid Ring Compressors With Fixed and Freely Rotating Casings

Abstract Liquid ring compressors (LRC) are used for a wide range of compression and vacuum applications, including corrosive or flammable gases for which other compression technologies may not be feasible. The presence of a surrounding liquid ring may offer the possibility of polytropic compression due to incremental heat loss to the liquid. This aspect may play a critical role in compression (and expansion) processes of heat engine cycles toward approaching the targeted Carnot efficiencies. To date, published research addressing the physical phenomena behind LRC is highly limited. Experimentally studying these machines will result in a demonstration of aggregate performance. In order to improve our understanding of LRC with and without freely rotating casings and to be able to analyze the complex inner workings, a numerical approach using computational fluid dynamics (CFD) tools, supported by available experimental data for validation purposes, has been established. Physical parameters such as water–air interface, temperature, pressure, entropy production, vorticity, and shear strain rate are presented for a baseline geometry taken from the open literature. Finally, temperature-entropy paths and isothermal and isentropic efficiencies are presented. The significant performance gain from the freely rotating casing is highlighted. Detailed results present insights into work addition processes of such machines.

A new chaotic jerk system with hidden heart-shaped attractor: dynamical analysis, multistability, connecting curves and its application in image encryption

Application of chaos in modeling natural phenomena and encryption encourages researchers to design new chaotic systems with exciting features. Here a chaotic jerk oscillator with different properties is proposed. Previous studies mainly used non-polynomial and piecewise linear terms to design the attractors’ shape. In the paper, the heart-shaped attractor is designed using just polynomial terms. This system is studied by considering its bifurcation diagram, Lyapunov exponent, and basin of attraction. These tools show that the proposed system has chaotic and periodic attractors that coexist in some parameter intervals. The oscillator does not have an equilibrium and has a heart-shaped attractor. Moreover, the connecting curves of the oscillator are considered to explore other structural properties. Numerical results confirm the analytical solutions for the system’s connecting curves. The interesting dynamics of the oscillator are used in an encryption and compression application.

Effect of Physical Therapy on Circumference Measurement and Extremity Volume in Patients Suffering from Lipedema with Secondary Lymphedema.

Background: Lipedema is a chronic and progressive disease. Many complications can occur if the disease is not treated. The most important of these complications is lipedema with secondary lymphedema. There are very few publications about lipedema with secondary lymphedema. The aim of this study is to investigate the effect of physical therapy on lower extremity circumference and volume in patients suffering from lipedema with secondary lymphedema. Methods and Results: All patients received pneumatic compression and complex decongestive therapy (CDT). Perometer measurement was made at five distinct points. Fifteen patients were included in the study. It was seen that significant reduction was found in the circumference of three of the five points of measurements performed in the left leg, whereas significant reduction was found in the circumference of four of the five points of measurements performed in the right leg. Also, there was a decrease in the extremity volume in both legs. Conclusion: Combined application of CDT and pneumatic compression in patients suffering from lipedema with secondary lymphedema is an effective treatment method in reducing lower extremity volume and circumference measurement.

Reprogrammable Nonlinear Transmission Controls Using an Information Metasurface

AbstractNonlinearity manipulation based on electromagnetic (EM) metasurfaces has always been a hot topic, which is an important part of communication and radar systems. However, most of the existing transmission metasurfaces are mainly focused on linear processing on the incident EM waves. In this article, a reprogrammable nonlinear transmission metasurface is proposed for spatial waves using active power amplifiers. An ultrathin and compact metasurface is designed, fabricated, and measured, to achieve reprogrammable functions on the nonlinear transmissions. For EM incidence, the metasurface can not only amplify the magnification of small signals, but also control high‐energy signals nonlinearly, whose magnification is determined by different bias voltages. The simulation and experimental results show good consistency, which verifies the feasibility of the proposed method. This work can find potential applications in signal gain compression and construction of nonlinear units of diffractive deep neural networks.

Four-Leg Sustained Dynamic Compression Staple and Screw Generates Superior Lapidus Construct as Compared to Plate and Screw: A Biomechanical Study

Category: Ankle; Basic Sciences/Biologics Introduction/Purpose: Lapidus procedures are frequently used to treat moderate to severe hallux valgus in the setting of first tarsometatarsal instability or arthritis. The push for early weightbearing can lead to nonunion rates reaching 12%. A growing number of surgeons are utilizing orthopedic staples manufactured from NiTiNOL in foot and ankle arthrodesis procedures. These staples are inserted in an “open expanded” state which enables application of sustained dynamic compression (SDC) between bony segments, which can persist even when challenged with joint settling / bony resorption. The biomechanical performance of these devices has not been quantified in the setting of Lapidus procedures. This study determined the optimum SDC staple construct during Lapidus procedures, and to compare their performance to traditional plate and screw construct in an established model. Methods: Lapidus procedures were performed on synthetic bone replicates (Sawbones) using three SDC staple constructs and one static device construct: (1) dorsal four-leg inline SDC staple, (2) dorsal four-leg inline SDC staple with medial two-leg SDC staple (3) dorsal four-leg inline SDC staple with plantar medial-distal to lateral-proximal cannulated screw and (4) dorsomedial plate and distal dorsal to proximal plantar cannulated screw (FigA). Samples underwent four-point bending with calibrated servo- hydraulic machine (MTS). Max load and construct stiffness was calculated. Interfragmentary contact force, area, and pressure was measured with pressure sensor (Tekscan) and joint plantar gap measurements were completed with 3D motion capture system (Motion Analysis). Testing consisted of stepwise loading to 1, 2, and 3mm of crosshead displacement. For brevity, only data from 3mm displacement test are included herein. Data were analyzed with one-way ANOVA with Dunnett’s post hoc test (N=5/group). Results: The four-leg inline staple + two-leg staple and the four-leg inline staple + screw groups exhibited a 2.5x (p=0.03) and 7.5x (p <.001) increase in joint contact force as compared to the plate + screw group, respectively (FigB). The four-leg inline staple + two-leg staple and the four-leg inline staple + screw groups demonstrated a 3.5x (p=0.002) and 6.6x (p <.001) increase in joint contact area as compared to the plate + screw group, respectively (FigC). The four-leg inline staple + screw group exhibited a 65.1% reduction in plantar gap as compared to the plate + screw group (p=.039, FigD). Conclusion: The four-leg inline staple + screw group exhibited the optimal Lapidus construct biomechanical properties (greatest joint contact force, greatest joint contact area, and least plantar gap). The biomechanical testing performed herein was undertaken to simulate loading akin to early post-operative weight bearing. These data highlight the ability of the four-leg SDC NiTiNOL staple in combination with a static screw to provide meaningfully increased joint compression, uniformity of joint compression, and decreased construct motion as compared to the standard plate + screw construct that is frequently used clinically.

Pilot Study on Effect of Warm Compress Application using Optic Care Wear Vs Conventional Method on Level of Symptom Complex among Elderly Clients with Dry Eye Syndrome at Selected Old Age Home, Puducherry

Pilot Study on Effect of Warm Compress Application using Optic Care Wear Vs Conventional Method on Level of Symptom Complex among Elderly Clients with Dry Eye Syndrome at Selected Old Age Home, Puducherry

High quality factor unidirectional guided resonances of a silicon-on-lithium niobate photonic crystal slab for a tunable Gires-Tournois interferometer.

High quality (Q) factor, tunable unidirectional guided resonances (UGRs) based on a silicon-on-lithium niobate (Si-on-LN) photonic crystal (PhC) slab are proposed and numerically investigated. The Q factors of UGRs decay quadratically with respect to the distance from the Γ point to the wave vector along the Γ-X direction, and high Q factor UGRs are obtained by moving UGR close to the Γ point. Also, a Gires-Tournois interferometer (GTI) based on a UGR with a Q factor of 9465 is numerically demonstrated, which produces a maximum group delay of 30 ps around 1.55 μm with unitary reflectance. The group delay and operation wavelengths of the GTI can be adjusted effectively by tuning the refractive index of lithium niobate (LN) and the periods of the silicon bars. Our study may find applications in PhC surface-emitting lasers, dispersion compensation, and compression of light pulses.

High-power laser beam shaping using a metasurface for shock excitation and focusing at the microscale.

Achieving high repeatability and efficiency in laser-induced strong shock wave excitation remains a significant technical challenge, as evidenced by the extensive efforts undertaken at large-scale national laboratories to optimize the compression of light element pellets. In this study, we propose and model a novel optical design for generating strong shocks at a tabletop scale. Our approach leverages the spatial and temporal shaping of multiple laser pulses to form concentric laser rings on condensed matter samples. Each laser ring initiates a two-dimensional focusing shock wave that overlaps and converges with preceding shock waves at a central point within the ring. We present preliminary experimental results for a single ring configuration. To enable high-power laser focusing at the micron scale, we demonstrate experimentally the feasibility of employing dielectric metasurfaces with exceptional damage threshold, experimentally determined to be 1.1 J/cm2, as replacements for conventional optics. These metasurfaces enable the creation of pristine, high-fluence laser rings essential for launching stable shock waves in materials. Herein, we showcase results obtained using a water sample, achieving shock pressures in the gigapascal (GPa) range. Our findings provide a promising pathway towards the application of laser-induced strong shock compression in condensed matter at the microscale.

Correlations of sensations of hardness and springiness of agar and gelatin gels with mechanical properties in human participants

ObjectivesIt is unclear which mechanical properties of foods cause the texture sensation in humans. This study aimed to investigate the relationship between unilateral compression measurements and the sensations of hardness and springiness in gels. MethodsThree different concentrations of agar and gelatin gels were prepared by the addition of agar (1%, 2%, and 3%) and gelatin (4%, 8%, and 16%) to water or apple juice. In a stress-rupture test, stress–strain curves were obtained by the application of uniaxial compression with a disc plunger at a compression rate of 10 mm/s. The hardness, springiness, and palatability of the gels were evaluated by 12 healthy volunteers using a visual analog scale. ResultsThe sensation of hardness was positively correlated with the sensation of springiness for the agar and gelatin gels. Palatability decreased as hardness increased for both gels. In terms of mechanical properties, the sensation of hardness was only significantly correlated with the initial elastic modulus, while the sensation of springiness was correlated with the late elastic modulus and other mechanical properties such as fracture strain, time, and stress. ConclusionsThese results suggest that sensations of hardness and springiness are produced in the initial and late stages, respectively, during the food-crushing process using the tongue, palate, and teeth.

Characterization of a polypropylene and polyethylene compound for the production of bricks in non-structural walls

This paper investigates the feasibility of using recycled plastic composed of polypropylene (PP) and high-density polyethylene (HDPE), as a basis for the fabrication of plastic bricks for non-structural walls starting from the material characterization. The deformation properties of plastic bricks were evaluated under the application of compression, flexural and traction forces; the thermal analysis of the material was carried out by means of the ignition test, differential scanning calorimeter (DSC) and its water ab-sorption capacity was also tested. Satisfactory results were obtained in the tests carried out; It was found that the compressive strength of the material complies with the requirements of standard specifications for conventional bricks (clay - concrete), and the physicochemical properties of the composite meet specifications of material for use in non-structural walls; which makes it an innovative material with enormous potential for use in the construction sector.

The Advance of Dialogue System with Neural Network

With the rapid reform of artificial intelligence, the dialogue system as an important branch of artificial intelligence has also developed greatly in recent years. However, dialogue systems also face many challenges, and accurate and well-sampled training data in dialogue systems is often not readily available. How to use the relationship extraction model based on meta-learning from a small number of samples to improve the accuracy of the relationship prediction method on few-shot learning training data. In addition, this article also explores methods of data compression, summarizing previous compression methods in different ways and related work. At the same time, the application of data compression in the dialogue chat model is also studied. The comparison before and after data compression is carried out to make the dialogue chat model maintain the original answer quality when the data part is reduced, and how to use knowledge graph and reinforcement learning to improve the answer quality of the dialogue system after data compression.