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This paper aims to propose a fast machine compression scheme, which can solve the problem of low-bandwidth transmission for underwater images.

This fast machine compression scheme mainly consists of three stages. Firstly, raw images are fed into the image pre-processing module, which is specially designed for underwater color images. Secondly, a divide-and-conquer (D&C) image compression framework is developed to divide the problem of image compression into a manageable size. And extreme learning machine (ELM) is introduced to substitute for principal component analysis (PCA), which is a traditional transform-based lossy compression algorithm. The execution time of ELM is very short, thus the authors can compress the images at a much faster speed. Finally, underwater color images can be recovered from the compressed images.

Experiment results show that the proposed scheme can not only compress the images at a much faster speed but also maintain the acceptable perceptual quality of reconstructed images.

This paper proposes a fast machine compression scheme, which combines the traditional PCA compression algorithm with the ELM algorithm. Moreover, a pre-processing module and a D&C image compression framework are specially designed for underwater images.

The purpose of this paper is to obtain a theoretical model to analyze the effective modulus of cement paste in early age, including the setting and hardening periods, which has a great impact on mechanical properties of concrete structure.

Based on a power law approximation, a generalized mixture rule is used to construct the relationship between the effective modulus and hydration degree. In addition, a new model of the dependence of the Poisson's ratio on the hydration degree and water cement ratio is proposed for cement paste in early age.

The effective Young's modulus, storage shear modulus and Poisson's ratio of cement pastes with different water cement ratios and hydration degrees are studied by the presented model. The model can be applied to simulate the behavior of early-age cement paste at both the setting and the hardening periods. Compared with the experimental results, the correctness of the model is validated.

This work presents a mathematical model that can effectively estimate the effective Young's modulus and Poisson's ratio in the hardening period, and the storage shear modulus in the setting period of cement pastes.

Current measurement methods for fabric comfort attributes generally suffer from either complicated testing processes and intricate measuring equipment or partial evaluation objectives and thus are difficult for effectively evaluating multidimensional human perceptions towards the comprehensive comfort of fabrics. The purpose of this paper is to develop a facile test device, namely fabric comfort tester, to achieve a comprehensive evaluation of human sensations in terms of sensorial, thermal and acoustic comfort in clothing.

The prototype of the designed device was introduced, which enables a simultaneous test for multiple physical and mechanical properties of fabrics based on a force sensor and a set of infrared sensors via constructing multi-deformation states of the measured fabrics. Eleven measurement indices extracted from the measurement curves are defined and interpreted based on correlation analysis. A series of regression models are developed by relating the measurement indices with subjective evaluation results and validated by a set of independent samples.

Human perceptions of sensorial, thermal and acoustic comfort in clothing can be predicted by the measured physical indices and the designed test device with the developed regression models provides an alternative method to characterize the fabric comfort attributes effectively.

The work develops a novel device for objective evaluation of fabric comfort properties by a simultaneous test, integrating the mechanical measurement with thermal test and thereby filling the gap between the existing evaluation methods and practical requirements for the digitalization of fabric comfort in present textile and garment trade.

This paper aims to determine whether application of graphene layers to cuprammonium filaments affords the latter with excellent mechanical properties and improves their electrical properties. At the same time, a circuit model was established to explore the conductive mechanism of the filament. The actual model is used to verify the correctness of the model.

The cuprammonium filaments were desizing, the graphene oxide layer-by-layer sizing and reduction integration process by a continuous sizing machine. The electrical properties of mono- and multifilaments in the static condition, as well as the dynamic–mechanical properties of multifilaments, were analysed, and the related conductive mechanism of the filaments was deduced.

Cuprammonium filaments coated with graphene layers showed good electrical conductivity, and their volume resistance decreased to 4.35 O·cm with increasing number of graphene coats. The X-ray diffraction and thermogravimetric analysis results showed that the graphene layer treatment changed the crystallinity of the copperammonia filaments and improved the thermal stability of the filaments. In the dynamic case, filament resistance was calculated using the equivalent resistance model, and the fitting difference observed was small. This result confirmed the high fit of this circuit model.

Up to the knowledge from literature review, there are no reports on theoretical research on the relation between the electro-mechanical property and structure of conductive filaments.

This paper aims to examine the effect of dividend regulation on cost stickiness (i.e. the asymmetric change in firm expense between sales increase and sales decrease) and explore the underlying mechanism.

Based on the quasi-natural experiment of the Guideline for Dividend Policy of Listed Companies issued by the Shanghai Stock Exchange (SSE) in 2013, the authors employ a difference-in-difference model to investigate the impact of dividend regulation on cost stickiness.

The authors find that the cost stickiness of treatment group firms has decreased significantly when compared with control group firms after the dividend regulation. Moreover, this effect is more pronounced among firms in lower marketization regions, in lower competition industries and those with less analyst coverage and lower cash flow levels. Further analyses show that dividend regulation reduces the cost stickiness of firms by mitigating agency problems. Finally, the conclusion holds after several robust tests, including controlling for firm fixed effect, propensity score matching (PSM), placebo test and reconstruction of expense variable.

This paper confirms that dividend regulation serves an important role in corporate governance, which reduces firms' agency costs and thereby decreases cost stickiness. The conclusions shed light on the dividend policies of listed companies and capital market regulation in the future.

The purpose of this paper is to construct an information ecology factor-TAM model to explore how information, people, and information environment impact mobile library users’ behavioral intention.

An empirical study based on an information ecology factor-TAM model.

The results of model test indicate that information, people, and information environment affect users’ behavioral intention to use mobile library in the information ecology environment. This paper provides a new theoretical perspective to understand users’ behavior of mobile library. It also provides practical guidelines to promote the usage of mobile library.

Internet of Things makes digital library one important channel for people to obtain information. Mobile internet makes it possible to access a variety of information anytime and anywhere. With the rapid grow of the number of mobile internet users, the usage of mobile library does not grow correspondingly. This paper explores the reasons.

The purpose of this paper is to understand the process of failure of scale and the corrosion resistance of scale to the substrate in an atmospheric environment.

The corrosion behaviour of X65 pipeline steel with different types of oxide scale was analysed using the natural environment exposure corrosion test, scanning electron microscopy analysis, electrochemical corrosion polarization curve test and other methods in a warehouse environment.

The results of this research show that one type of oxide scale, which is rough, has an uneven microstructure, and exhibits weak adhesion to the matrix, does not protect the substrate from corrosion. Conversely, the uniform, dense oxide scale, which exhibits strong adhesion to the matrix, provides effective protection to the steel. However, as the corrosion develops, the corrosion rate of the substrate tends to accelerate, especially when the structure of the oxide scale is damaged to a certain extent.

The corrosion mechanism of the oxide scale on hot rolled steel in an atmospheric environment has been proposed.

The purpose of this paper is to obtain a constitutive model of cement-based material in the rheological stage, which owns the different water-cement ratio (w/c) and temperature and have a significant impact on the workability of concrete materials.

It is introduced a modified Arrhenius equation into the Herschel–Bulkley model, which is widely applied in rheological analysis and constructed an ordinary differential equation (ODE) of w/c from the Navier–Stokes equation. By solving the ODE, an approximate constitutive relation of cement-based materials included w/c and temperature is derived. Compared with the experimental results, the present model is validated.

The shear stress and shear rate curves with different w/c and temperature are simulated by the present method, and the present model can be applied to analyze the changes of apparent viscosity in cement-based material slurry as the w/c and temperature varying.

This work gives a mathematical model, which can effectively approximate the shear stress–shear rate relation with different w/c and temperature in the rheological stage of cement-based material.

This study established and examined a moderated mediation model connecting family motivation with proactive career behavior (PCB). Drawing on social cognitive career theory model of career self-management and person-environment fit theory, the authors posit that the influence of family motivation on PCB is mediated by career goal setting (CGS) and moderated by career support climate (CSC).

Using multilevel modeling techniques, data were collected from 98 leaders and 416 employees at two-time points.

Results show that family motivation has a positive direct and indirect effect on PCB through CGS. Additionally, CSC strengthens the positive effect of family motivation on PCB through CGS.

For employees, proactive career management and the establishment of clear career goals are vital for fulfilling family responsibilities. Simultaneously, for managers and organizations, creating a supportive work environment is crucial to encourage employees in career management.

While existing research highlights the detrimental effect of fulfilling family caregiving responsibilities on employees' career development, the comprehension of this relationship remains limited. Taking a family motivation perspective, this study explores the mechanisms through which family motivation stimulates employees to engage in PCB, with a specific focus on the moderating influence of CSC. The findings offer fresh insights into the role of family motivation in career development, contributing significantly to the broader literature on the intersection of family and careers.

To enhance the pleasure experience of clothes shopping online, finding satisfactory clothing and similar clothing recommendations to customers should be available and accurate. The purpose of this paper is to present a method for automatically computing the similarity between two apparels and giving an effective recommendation.

Based on a tabular layout of article characteristics the authors built a clothing information model to describe clothing. The clothing attributes are classified according to excavating features of the model. After the proposal of the computation algorithm for various attributes, an efficient similarity computation method is developed to obtain similar clothes with the given cloth. To prevent error and information omission during the computation, the analytic hierarchy process method and entropy method are adopted by the integrated weights as a control.

Clothing is a non‐rigid product which has a lot of crossover and complicated attributes and features. This paper found a tabular layout of article characteristics can explain the clothing clearly. Through experiments the authors found the weight of attributes to have a great influence on similar results during the similarity computation.

This paper presents a new way to describe clothing information, and present the algorithm for attributes computation.