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With the increasing abundance of network resources and big data, multi-modal information search (MMIS) has been paid more and more attention, but the research results of MMIS are relatively few. This paper attempts to put forward constructive suggestions for the design of multi-modal information system, so that the system can have a better user experience, help users improve the efficiency of obtaining information and optimize the information service mode.

A research model of influencing factors is established by using the TAM (technology acceptance model) theory. The influencing factors of users' multi-modal information search behavior (MMISB) are analyzed by using questionnaire, experiment and the structural equation model. On the basis of this, some suggestions are put forward to build the multi-modal search (MMS) system and improve the efficiency of MMIS.

The research shows that users' MMISB is directly related to their search intention, and the search intention can influence users' cognition of the usefulness and ease of MMIS through their own information search ability and system characteristics. The user's MMIS ability is affected by the demand expression ability and retrieval ability cognition; the user's cognition of system characteristics is affected by the system function and information quality. This shows that the user's MMISB is closely related to the user's cognitive situation, but due to the author's limited time and research ability, only the questionnaire survey method cannot be used to in-depth research and explore the influencing factors of MMIS. Therefore, in the future research, we should combine the interview method to further track the user's emotional factors and scene factors.

For the first time, TAM theory is combined with cross-modal retrieval behavior and the paper explores the influencing factors and evaluation indexes of users' MMISB. The second, the questionnaire was compiled to investigate the influencing factors of the MMISB of the university group, and the reliability analysis, validity analysis, correlation analysis and structural equation model analysis of the survey data are carried out . The survey data and analysis results are original, which can provide a theoretical basis for improving the service level of MMIS.

The purpose of this paper is to investigate the thermal elastohydrodynamic lubrication (TEHL) flash temperature of the helical gear pairs considering profile modification.

A flash temperature model of the helical gear pair considering the profile modification is proposed based on the TEHL and meshing theories. In doing so, the slicing, fast Fourier transform and chase-after methods are applied to accurately and rapidly obtain the flash temperature of the gear pair. Then, the effects of the modification, input torque and rotation speed on the flash temperature are studied.

With the increment of the tip relief amount, the flash temperature of the helical gear pair with the axial modification decreases first and then increases, and the meshing position of the maximum flash temperature moves toward the pitch point. Moreover, reducing the input torque or increasing the rotation speed can efficiently reduce the TEHL flash temperature.

This work is a valuable reference for the profile design and optimization of the helical gears to avoid the excessive flash temperature.

The purpose of this paper is to quantify the influence of alternating current (AC) interference on hydrogen evolution reaction of X80 steel.

The hydrogen evolution potential was obtained by cathodic potentiodynamic polarization curve. The instantaneous potential under AC interference was obtained by high-frequency acquisition with three-electrode system. Electrochemical impedance spectroscopy and Tafel polarization curves were used to study the influence mechanism of AC interference on instantaneous potential.

It was concluded that the hydrogen evolution reaction could occur on X80 steel under AC interference. There were critical AC current densities of about 100 to 200 A/m2, beyond which the cathode reaction of X80 steel changed from oxygen absorption to hydrogen evolution. Besides the pH value, the initial polarization potential EZ and impedance module of the steel/electrolyte interface under AC interference were also the factors that affected the critical AC densities in different solutions.

This research quantified the hydrogen evolution capacity of X80 steel under AC interference, which could be applied to clear the effect of AC interference on hydrogen evolution reaction.

In this paper, the smoothed point interpolation method (SPIM) is used to model the slope deformation. However, the computational efficiency of SPIM is not satisfying when modeling the large-scale nonlinear deformation problems of geological bodies.

In this paper, the SPIM is used to model the slope deformation. However, the computational efficiency of SPIM is not satisfying when modeling the large-scale nonlinear deformation problems of geological bodies.

A simple slope model with different mesh sizes is used to verify the performance of the efficient face-based SPIM. The first accelerating strategy greatly enhances the computational efficiency of solving the large-scale slope deformation. The second accelerating strategy effectively improves the convergence of nonlinear behavior that occurred in the slope deformation.

The designed efficient face-based SPIM can enhance the computational efficiency when analyzing large-scale nonlinear slope deformation problems, which can help to predict and prevent potential geological hazards.

The purpose of this paper is to solve the common problems that traditional optimization methods cannot fully improve the performance of electromagnetic linear actuators (EMLAs).

In this paper, a multidisciplinary optimization (MDO) method based on the non-dominated sorting genetic algorithm-II (NSGA-II) algorithm was proposed. An electromagnetic-mechanical coupled actuator analysis model of EMLAs was established, and the coupling relationship between static/dynamic performance of the actuator was analyzed. Suitable optimization variables were designed based on fuzzy grayscale theory to address the incompleteness of the actuator data and the uncertainty of the coupling relationship. A multiobjective genetic algorithm was used to obtain the optimal solution set of Pareto with the maximum electromagnetic force, electromagnetic force fluctuation rate, time constant and efficiency as the optimization objectives, the final optimization results were then obtained through a multicriteria decision-making method.

The experimental results show that the maximum electromagnetic force, electromagnetic force fluctuation rate, time constants and efficiency are improved by 18.1%, 38.5%, 8.5% and 12%, respectively. Compared with single-discipline optimization, the effectiveness of the multidiscipline optimization method was verified.

This paper proposes a MDO method for EMLAs that takes into account static/dynamic performance, the proposed method is also applicable to the design and analysis of various electromagnetic actuators.

This study explores how collaborative cost sharing between the buyer and the supplier in cold chain equipment and marketing and advertising affects the performance of a fresh agricultural produce supply chain (FAP-SC).

We use a contingency approach to modeling different scenarios and analyzing how fairness perception, interplaying with corporative–retailer cost sharing., influences the performance of fresh agricultural produce cold chains.

The findings of the research highlight the crucial role of the retailer's fairness concern. When the retailer's fairness concern is absent, cost sharing (in cold chain equipment and marketing and advertising) is found to help boost demand and enhance the profits of members of the supply chain; bilateral cost sharing is found to have a more significant impact than unilateral cost sharing. When the retailer's fairness concern is taken into account, however, cost sharing is found to reduce demand at a lower level of fairness coefficient but increases demand at a higher level of fairness coefficient; bilateral cost sharing boosts both demand and profit of the supply chain when the retailer is in a “high concern, high anger” state.

The findings of the research highlight the important role of the buyer's farness perception when supply chain partners adopt collaborative cost sharing programs. This study contributes significantly to research and practice in supply chain collaboration and agricultural cold chain performance.

Effective farmer participation in the rural land consolidation process has become increasingly important because it improves results in rural land consolidation and land use efficiency. The purpose of this paper is to examine the mechanism of farmers’ effective participation in Chinese rural land consolidation.

The authors empirically assess farmers’ effective participation in the rural land consolidation process in ten counties of China’s Hubei province. Focusing on an effective decision-making model, the authors comprehensively evaluated farmer participation using surveys that incorporated an index system and analyzed survey results using a structural equation model to examine factors that influenced farmer’s effective participation.

The results of the study suggest that the correlations between farmers’ effective participation and the impacting factors the authors proposed were particularly strong. In addition, participation ability, participation opportunity and participation incentive are strongly associated with effective farmer participation. Thus, the authors highlight that incentives should be provided to encourage farmers’ effective participation in rural land consolidation.

Because of the chosen approach and the set of the research object, the geographic context of the empirical survey work was limited; furthermore, the authors only studied the influencing factors at the individual level, leaving the interaction effects between governmental factors and farmer individual factors inadequately explained.

Despite those limitations, these results serve as an important reference for government agencies and stakeholder groups in rural land consolidation decision making.

In recent years, it is imperative to establish the structure of manufacturing industry in the context of smart factory. Due to rising demand for exchange of information with various devices, and huge number of sensor nodes, the industrial wireless networks (IWNs) face network congestion and inefficient task scheduling. For this purpose, software-defined network (SDN) is the emerging technology for IWNs, which is integrated into cognitive industrial Internet of things for dynamic task scheduling in the context of industry 4.0.

In this paper, the authors present SDN based dynamic resource management and scheduling (DRMS) for effective devising of the resource utilization, scheduling, and hence successful transmission in a congested medium. Moreover, the earliest deadline first (EDF) algorithm is introduced in authors’ proposed work for the following criteria’s to reduce the congestion in the network and to optimize the packet loss.

The result shows that the proposed work improves the success ratio versus resource usage probability and number of nodes versus successful joint ratio. At last, the proposed method outperforms the existing myopic algorithms in terms of query response time, energy consumption and success ratio (packet delivery) versus number of increasing nodes, respectively.

The authors proposed a priority based scheduling between the devices and it is done by the EDF approach. Therefore, the proposed work reduces the network delay time and minimizes the overall energy efficiency.