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The performance of oil-filled pressure cores is very much affected by the corrugated diaphragm and the oil filling volume. The purpose of this paper is to show the effects of different corrugated diaphragms, different oil filling volumes and different treatments of the corrugated diaphragms on the performance of pressure sensors.

Pressure-sensitive cores with different diaphragm diameters, different diaphragm ripple numbers and different oil filling volumes are produced, and thermal cycling is introduced to improve the diaphragm performance, and finally the performance of each pressure-sensitive core is tested and the test data are analyzed and compared.

The experimental results show that the larger the diameter of the corrugated diaphragm used for encapsulation, the better the performance. For pressure-sensitive cores using smaller diameter corrugated diaphragms, the performance of one corrugation is better than that of two corrugations. When the number of corrugations and the diameter are the same size, the performance of the outer ring of the diaphragm with concave corrugations is better than that with convex corrugations. At the same time, the diaphragm after thermal cycling treatment and appropriate reduction of encapsulated oil filling can improve the performance of the pressure-sensitive core.

By exploring the effects of corrugated diaphragm and oil filling volume on the performance of oil-filled pressure cores, the design of oil-filled pressure sensors can be guided to improve sensor performance.

Due to its inexpensive production costs, low stress concentration and maintenance-friendliness, the adhesive bonded pipe joint is frequently utilized for pipe connection. However, further theoretical analysis is needed to understand the debonding failure mechanism of such bonded pipe joints under axial tension.

In this study, based on the bi-linear cohesive zone model, the integrated closed-form solutions were derived by considering the axial stiffness ratio and failure stage to determine the relative interfacial slip, interfacial shear stress and relationship of tension–displacement in the bonded pipe joint.

Additionally, solutions for the critical bonded length and the ultimate load capacity were put forth. Besides, the numerical study was conducted to verify the theoretical solutions regarding the load–displacement relationship. The interfacial shear stress distribution at different failure stages was presented to understand the interfacial shear stress transmission and debonding process. The effect of bonded length on the ultimate load and ductility of pipe joints was also discussed.

The findings in this study can give a reference for the design of bonded pipe joints in their actual engineering applications.

Business process models, while primarily intended for process documentation, communication, and improvement, are often also used as input for developing process-oriented software systems (Ouyang et al., 2009). Ensuring correctness, handling complexity, and improving reusability and maintainability of business process models are important for all these goals. The purpose of this paper is to propose an aspect-oriented business process modeling and correctness controlling method based on Petri nets to satisfy these goals.

The aspect-oriented paradigm provides a proper mechanism to modularization, and thus reduces the complexity of models, and also improves reusability and maintainability. However, weaving aspects into base processes may bring in mistakes or errors. To ensure correctness of modeling, this paper presents a formal approach to modeling aspect-oriented business processes and a method to ensure modeling correctness. Petri net is used as the process modeling language and its analysis techniques are applied to analyze the correctness of modeling. Two types of correctness, specifically, aspect-aspect correctness and base-aspect correctness are analyzed. A real banking process model is studied systematically in the case study to evaluate the approach and the performance assessments are conducted to show the cost and effect of the approach.

Designing aspect-oriented business process models help organizations reusing the model elements to reduce redundancy of their model repository, improving their maintainability, and supporting them to adapt to the changes of business requirements with flexible modeling. It is important to stress that the correctness of business process modeling is important in ensuring the quality of the models, especially in the safety-critical business domains, such as financial business domain.

In this paper, separation of concerns is used to separate the cross-cutting activities and core activities in accordance with the different functions of these activities, and an approach to modeling aspect-oriented business processes is proposed. First, the cross-cutting activities are encapsulated as aspects, while core business activities are modeled as base processes. Then, according to the correctness requirements of business process models, based on the weaving mechanisms of aspect-oriented approach, weaving correctness is defined. Weaving correctness controlling methods between multi-aspects and between aspects and base processes are designed. Errors or mistakes of aspect-oriented business process modeling are prevented during the procedure of modeling to ensure error-free business process modeling.

The purpose of this study is to provide a novel multi-fingered hand made of hyperelastic material. This kind of hand has the advantage of less mechanical parts, simpler control system. It can greatly cut down the complexity and cost of the hands under conditions of ensuring enough flexibility of grasping.

Based on the principle of virtual work, the equations of pulling force and grasping force are derived. To get the max grasping force, the optimal structural dimensions of the hand are obtained by finite element simulations. Hand’s grasping experiment is conducted.

The factors influencing grasping force and grasping stability are identified, and they are the length between short poles around the knuckles and the height of short poles. Experimental results show that the max strain of knuckles is less than the elastic limit of hyperelastic material, and the presented hand is practicable. The adaptive ability and grasping stability of the presented hand are demonstrated.

A novel multi-fingered hand made of hyperelastic material is presented in this paper. By designing the thickness of every section of a hyperelastic plate, the knuckle sections will bend and other sections of the plate will remain straight, and thus, the multi-fingered hand will grasp.

The purpose of this paper is to analyze and forecast the Chinese term structure of interest rates using functional principal component analysis (FPCA).

The authors propose an FPCA-K model using FPCA. The forecasting of the yield curve is based on modeling functional principal component (FPC) scores as standard scalar time series models. The authors evaluate the out-of-sample forecast performance using the root mean square and mean absolute errors.

Monthly yield data from January 2002 to December 2016 are used in this paper. The authors find that in the full sample, the first two FPCs account for 98.68 percent of the total variation in the yield curve. The authors then construct an FPCA-K model using the leading principal components. The authors find that the FPCA-K model compares favorably with the functional signal plus noise model, the dynamic Nelson-Siegel models and the random walk model in the out-of-sample forecasting.

The authors propose a functional approach to analyzing and forecasting the yield curve, which effectively utilizes the smoothness assumption and conveniently addresses the missing-data issue.

To the best knowledge, the authors are the first to use FPCA in the modeling and forecasting of yield curves.

This study examined how marketer- and user-generated photographs jointly influence consumers' online hotel booking.

Viewing photographs as stimuli that influence consumers' online hotel booking, this study proposes a research model and validates that using one quasi-experiment.

The findings of this study provide some empirical insights. Marketers can release room- and scene-related photographs. Users can release product- and social-related photographs. The interaction between room-related photographs by marketers and product-related photographs by users can promote energetic arousal and dominance and then promote online booking intention. The interaction between scene-related photographs by marketers and social-related photographs by users can promote energetic arousal and dominance and then promote online booking intention. Pleasure, energetic arousal and dominance can positively influence the attitude toward photographs. Pleasure and energetic arousal can positively influence the attitude toward photographs and then positively influence booking intention. Dominance can positively influence booking intention.

The findings of this study reveal significant interaction effects between marketer- and user-generated photographs on consumers' online booking. The findings will help researchers and marketers better understand the impact of photographs on consumers' online hotel booking.

Exponential growth in online video content makes viewing choice and video promotion increasingly challenging. While explicit recommendation systems have value, they inherently distract the user from normal behaviour and are open to numerous biases. To enhance user interest evaluation accuracy, the purpose of this paper is to comprehensively examine the relationship between implicit feedback and online video content, and reviews gender differentials in the interest indicated by a comprehensive set of viewer responses.

This paper includes 200 useable observations based on an experiment of user interaction with the Youku platform (one of the largest video-hosting websites in China). Logistic regression was employed for its simple interpretation to test the proposed hypotheses.

The findings demonstrate gender differentials in cursor movement behaviour, explainable via well-studied splits in personality, biological factors, primitive behaviour and emotion management. This work offers a solution to the sparsity of work on implicit feedback, contributing to the literature that combines explicit and implicit feedback.

This study offers a launch point for further work on human–computer interaction, and highlights the importance of looking beyond individual metrics to embrace wider human traits in video site design and implementation.

This paper links implicit feedback to online video content for the first time, and demonstrates its value as an interest capturing tool. By reviewing gender differentials in the interest indicated by a comprehensive set of viewer responses, this paper indicates how user characteristics remain critical. Consequently, this work signposts highly fruitful directions for both practitioners and researchers.

The purpose of this paper is to explore the impact of peer-to-peer (P2P) supply chain financing on companies' innovation efficiency.

This study takes the core companies that invest in the P2P platform as the research background and uses data for Chinese companies and the systematic Generalised Method of Moments (the systematic GMM) to explore the relationship between the improvement of supply chain efficiency, research and development (R&D) investment, and innovation efficiency.

This study indicates that core enterprise investment in P2P can cause a significant improvement in the efficiency of the supply chain and that this improvement can significantly motivate enterprises to increase R&D investment. Although the improvement of supply chain efficiency has no significant effect on improving companies' innovation efficiency, it can have a positive impact on innovation efficiency through the regulating role of R&D investment.

This research shows several limitations such as single industry and few companies involved, but it analyses the impact of P2P supply chain financing on R&D investment, and companies' innovation efficiency and broadens the research field of P2P supply chain financing.

This article provides a theoretical direction for listed companies to invest in P2P platforms and achieve supply chain management. The research on the regulating role of this article provides a new way of thinking for the study of enterprise innovation.

This paper analyses the impact of the core enterprise investment in P2P on R&D investment and its subsequent impact on the companies' innovation efficiency, thus broadening the research field of P2P supply chain financing.

With the continuous development of aerospace technology, space exploration missions have been increasing year by year, and higher requirements have been placed on the upper level rocket. The purpose of this paper is to improve the ability to identify and detect potential targets for upper level rocket.

Aiming at the upper-level recognition of space satellites and core components, this paper proposes a deep learning-based spatial multi-target recognition method, which can simultaneously recognize space satellites and core components. First, the implementation framework of spatial multi-target recognition is given. Second, by comparing and analyzing convolutional neural networks, a convolutional neural network model based on YOLOv3 is designed. Finally, seven satellite scale models are constructed based on systems tool kit (STK) and Solidworks. Multi targets, such as nozzle, star sensor, solar,etc., are selected as the recognition objects.

By labeling, training and testing the image data set, the accuracy of the proposed method for spatial multi-target recognition is 90.17%, which is improved compared with the recognition accuracy and rate based on the YOLOv1 model, thereby effectively verifying the correctness of the proposed method.

This paper only recognizes space multi-targets under ideal simulation conditions, but has not fully considered the space multi-target recognition under the more complex space lighting environment, nutation, precession, roll and other motion laws. In the later period, training and detection can be performed by simulating more realistic space lighting environment images or multi-target images taken by upper-level rocket to further verify the feasibility of multi-target recognition algorithms in complex space environments.

The research in this paper validates that the deep learning-based algorithm to recognize multiple targets in the space environment is feasible in terms of accuracy and rate.

The paper helps to set up an image data set containing six satellite models in STK and one digital satellite model that simulates spatial illumination changes and spins in Solidworks, and use the characteristics of spatial targets (such as rectangles, circles and lines) to provide prior values to the network convolutional layer.

The purpose of this paper is to improve the efficiency of on-orbit operations through the top-level task design based on DoDAF. Based on the existing upper stage rocket technology, orbit transfer vehicles (OTVs) have developed rapidly in recent years. However, the lack of decision guidance based on overall task analysis requires integrating top-level analysis and bottom-level execution to achieve the smooth development of full-process tasks.

Using the Department of Defense Architecture Framework (DoDAF) as a reference, this paper performs the top-level mission analysis modeling of the on-orbit rendezvous and capture of the OTV. Moreover, the typical operational view products are obtained, and the cooperative relations among the mission requirements, the system requirements, and the functional requirements are also analyzed.

The results show that the attitude of the OTV changes violently during the maneuver and rendezvous phases. In addition, the view products can be optimized based on the results.

The proposed DoDAF-based on-orbit task integration analysis method achieves the effective fusion of high-level analysis and bottom-level execution of OTV on-orbit rendezvous and capture task through the top-level task modeling, operation view generation and task relationship analysis. According to the requirements and constraints of the on-orbit rendezvous and capture task, the control instructions of the vehicle are efficiently generated under the DoDAF framework.