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In the big data era, image compression is of significant importance in today’s world. Importantly, compression of large sized images is required for everyday tasks; including electronic data communications and internet transactions. However, two important measures should be considered for any compression algorithm: the compression factor and the quality of the decompressed image. In this paper, we use Frei-Chen bases technique and the Modified Run Length Encoding (RLE) to compress images. The Frei-Chen bases technique is applied at the first stage in which the average subspace is applied to each 3 × 3 block. Those blocks with the highest energy are replaced by a single value that represents the average value of the pixels in the corresponding block. Even though Frei-Chen bases technique provides lossy compression, it maintains the main characteristics of the image. Additionally, the Frei-Chen bases technique enhances the compression factor, making it advantageous to use. In the second stage, RLE is applied to further increase the compression factor. The goal of using RLE is to enhance the compression factor without adding any distortion to the resultant decompressed image. Integrating RLE with Frei-Chen bases technique, as described in the proposed algorithm, ensures high quality decompressed images and high compression rate. The results of the proposed algorithms are shown to be comparable in quality and performance with other existing methods.

In the cold rolling process, friction coefficient, oil film thickness and other factors vary dramatically with the change in the rolling speed, which seriously affects the strip thickness deviation. This paper aims to improve the strip control precision with the forecast roll gap model based on CF-PSO-SVM approach in the rolling process.

In this paper, a novel forecasting model of the roll gap based on support vector machine (SVM) optimized by particle swarm optimization with compression factor (CF-PSO) is proposed. Based on lots of online data, the roll gap models regressed by PSO-SVM, genetic algorithm (GA)-SVM and CF-PSO-SVM are obtained and verified through evaluating the performances with the decision coefficient (R²), mean absolute error and root mean square error. In addition, with the good forecasting performances of CF-PSO-SVM, a roll gap compensation model is studied.

The results indicate that the proposed CF-PSO-SVM has excellent learning regression ability compared with other optimization algorithms. Meanwhile, a roll gap compensation model based on the rolling speed and plastic coefficient is obtained, which has been proved validated in product.

In this paper, the SVM algorithm is combined with traditional rolling technology to solve the problems in actual production, which has great supporting significance for the improvement of production efficiency.

Recently, the double joint photographic experts group (JPEG) compression detection tasks have been paid much more attention in the field of Web image forensics. Although there are several useful methods proposed for double JPEG compression detection when the quantization matrices are different in the primary and secondary compression processes, it is still a difficult problem when the quantization matrices are the same. Moreover, those methods for the different or the same quantization matrices are implemented in independent ways. The paper aims to build a new unified framework for detecting the doubly JPEG compression.

First, the Y channel of JPEG images is cut into 8 × 8 nonoverlapping blocks, and two groups of features that characterize the artifacts caused by doubly JPEG compression with the same and the different quantization matrices are extracted on those blocks. Then, the Riemannian manifold learning is applied for dimensionality reduction while preserving the local intrinsic structure of the features. Finally, a deep stack autoencoder network with seven layers is designed to detect the doubly JPEG compression.

Experimental results with different quality factors have shown that the proposed approach performs much better than the state-of-the-art approaches.

To verify the integrity and authenticity of Web images, the research of double JPEG compression detection is increasingly paid more attentions.

This paper aims to propose a unified framework to detect the double JPEG compression in the scenario whether the quantization matrix is different or not, which means this approach can be applied in more practical Web forensics tasks.

This paper aims to develop at sewing thread during the seam formation may lead to the compression of fabric under seam. In the present study, the model has been proposed to predict the seam compression and calculation of seam boldness, as well as thread consumption by considering seam compression.

The effect of sewing parameters on the fabric compression at the seam (Cf) for fabrics of varying bulk density was studied by the Taguchi method and also the multilinear regression equation is obtained to predict seam compression by considering these parameters. The framework has been set as per the single view metrology approach to measuring structural seam boldness (Bs). One of the basic geometrical models (Ghosh and Chavhan, 2014) for the prediction of thread consumption at lock stitch has been modified by considering fabric compression at the seam (Cf).

The multilinear regression model has been proposed which can predict the compression under seam using easily measurable fabric parameters and stitch density. The seam boldness is successfully calculated quantitatively using the proposed formula with a good correlation with the seam boldness rated subjectively. The thread consumption estimation from the proposed approach was found to be more accurate.

The compression under seam is found out using easily measurable parameters; fabric thickness, fabric weight and stitch density from the proposed model. The attempt has been made to calculate seam boldness quantitatively and the new approach to find out thread consumption by considering the seam compression has been proposed.

Polymer composite panels are widely used in aeronautic and aerospace structures due to the high strength-to-weight ratios of these structures. The purpose of this paper is to determine the strain fields and failure mechanisms during the failure of the impacted composite laminates when subjected to compression.

A series of compression-after-impact (CAI) tests was performed on composite plates 150×100×4 mm3 made of a carbon-fibre-reinforced epoxy resin matrix. A digital image correlation and fractographic analysis by means of optical and electron microscopy are used for this purpose.

The full-field strain measurements indicate a concentrated band of compressive strain near the impact, where buckling occurs. The results indicate that the strain concentration factor can be considered to be a failure criterion. The shear strain visualisation around the impact reveals an area of heterogeneous deformation that is comparable to the detected delamination area acquired by an ultrasonic technique. Fibre and inter-fibre fractures are described for the particular impact site regions.

These experiments could improve numerical models for the CAI analyses and help to build a new criterion for this severe failure mode.

Talent compression is the labor market phenomenon where the average productivity differential between participants declines and has been used to explain the overall increase in competition within some professional sports markets. A finding that competitiveness is uniquely driven by talent compression is consistent with Rottenberg (1956), who argued that resource distribution is independent of factors that are invariant to labor productivity.

Rather than incorporate MLB team roster turnover as many of the past studies have done, we prefer to measure of all-star turnover in membership. Problematically, movement from an MLB team to an MLB team is limited by rule, finances and the fact that there are very few teams competing for player services. In contrast, All-Star membership is typically costlessly chosen by many millions of fans, league players and managers. In this way, All-Star voting should be invariant to many of the factors that affect movement from an MLB team to an MLB team.

In the end, we find that a close association between all-star turnover rates and the makeup of MLB’s labor pool.

The paper offers a new measure of player mobility.

Recycled concrete is an economical and environmentally friendly green material. The shear performance of recycled concrete load-bearing masonry is studied, which is great of significance for its promotion and application and also has great significance for the sustainable development of energy materials.

In total, 30 new load-bearing block masonry samples of self-insulating recycled concrete are subjected to pure shear tests, and 42 samples are tested subjected to shear-compression composite shear tests. According to the axial design compression ratio, the test is separated into seven working conditions (0.1–0.8).

According to the test results, the recommended formula for the average shear strength along the joint section of recycled concrete block masonry is given, which can be used as a reference for engineering design. The measured shear-compression correlation curves of recycled concrete block masonry are drawn, and the proposed limits of three shear-compression failure characteristics are given. The recommended formula for the average shear strength of masonry under the theory of shear-friction with variable friction coefficient is given, providing a valuable reference for the formulation of relevant specifications and practical engineering design.

Simulated elastoplastic analysis and finite element modeling on the specimens are performed to verify the test results.

Chief executive officer (CEO) ability may have an effect on various corporate reporting decisions, and consequently, the CEO ability is subject to scrutiny by regulatory reviewers. However, theoretical literature provides mixed evidence on how the CEO ability affects the regulatory review risk. Thus, this study aims to empirically examine the effect of CEO ability on regulatory review risk.

To measure CEO ability, this study uses the CEO ability-score developed by Demerjian et al. (2012). Further, to measure regulatory review risk, the study uses the probability of receiving a comment letter from the Securities and Exchange Organization of Iran.

This study finds that the relationship between CEO ability and regulatory review risk is generally negative and statistically significant but not economically significant, i.e. the relationship is very small. In this regard, the study shows that the relationship is negative and also statistically and economically significant for firms with low levels of agency conflicts and high levels of corporate governance quality; and is positive and also statistically and economically significant for firms with high levels of agency conflicts and low levels of corporate governance quality. In addition, while the study finds no evidence that the regulatory reviewers’ workload compression influences the general relationship between CEO ability and regulatory review risk, it documents that low (high) regulatory reviewers’ workload compression weakens (strengthens) both the relationships stated above.

Collectively, the results suggest that the agency conflicts/corporate governance quality and regulatory reviewers’ workload compression are important factors in the analysis of the relationship between the CEO ability and regulatory review risk. The results offer insights into the opposing theoretical viewpoints about the relationship between CEO ability and regulatory review risk. Thus, the results will be of interest to boards of directors and other stakeholders involved in the regulatory review process.

The purpose of this paper is to investigate the potential design advantage in terms of resistance factors for normal weight concrete beams containing moderate-dose randomly dispersed short fibers and reinforced with glass fiber reinforced polymer (GFRP) bars.

An analytical model based on the current code specifications is used to calculate the moment capacity of over-reinforced sections. The vast majority of the considered beams are over-reinforced, compression-controlled. The data of the fiber-reinforced concrete (FRC) reinforced with GFRP bars are collected from three published research studies which are based on experimentally tested results. Three different types of short fibers with four volume fractions are considered. Probabilistic model is established to conduct reliability-based calibration using Monte-Carlo Simulation. Limit state function, relevant load and resistance random variables are identified, and adequate statistical parameters are selected. Target reliability index consistent with the one used to develop current design code specifications is used.

Reliability analysis and calibration process are carried out with the intention of estimating the flexural resistance factors for FRC beams reinforced with GFRP bars.

The predicted flexural resistance factors ranged from 0.72 to 0.95, giving the resistance factors the potential to be increased above the currently specified value of 0.65 for compression-controlled members reinforced with FRP bars.

The joint photographic experts group (JPEG) 2000 image compression system is being used for cultural heritage preservation. The authors are aware of over a dozen of big memory institutions worldwide using this format. This paper aims to review and explain choices for end users to help resolve trade-offs that these users are likely to encounter in practice.

The JPEG 2000 format is quite complex and therefore sometimes considered as a preservation risk. A lossy compression is governed by a number of parameters that control compression speed and rate-distortion trade-off. Their inappropriate adjustment may fairly easily lead to sub-optimal compression performance. This paper provides general guidelines for selecting the most appropriate parameters for a specific application.

This paper serves as a guide for the preservation of digital heritage in cultural heritage institutions, including libraries, archives and museums.

This paper serves as a guide for the preservation of digital heritage in cultural heritage institutions, including libraries, archives and museums.