Hongxing Han, Wei Chen, Bin Huang and Xudong Fu
This paper aims to propose a shape factor for granular materials based on particle shape. The scientific goal is to investigate the influence of particle shape on the mechanical…
Abstract
Purpose
This paper aims to propose a shape factor for granular materials based on particle shape. The scientific goal is to investigate the influence of particle shape on the mechanical properties of rockfill materials.
Design/methodology/approach
The method of generating four regular-shaped particles is based on the observation that most rockfill grains are regarded as like-triangle, like-rhombus, like-square and like-hexagon. A shape factor F that is developed using the Blaschke coefficient and a concave–convex degree is proposed. A biaxial compression test on rockfill materials under stress path is numerically simulated by discrete element method. The evolution of the shape factor F under the simulated stress paths is analyzed, and particle breakage rate, peak intensity and peak-related internal friction angle for rockfill materials are derived. A method of determining the shape factor F involved in the two functions is proposed.
Findings
A new micro-parameter is calibrated using the test data of one rockfill material. Particle shape greatly affects the particle breakage rate, peak intensity and peak-related internal friction angle for rockfill materials. The final experimental grading curves all approach the particle breakage grading curve proposed by Einav (the fractal dimension is 2.7).
Originality/value
This study proposes a shape factor F, which describes the geometric features of natural rockfill particles. The proposed shape factor F has a simple structure, and its parameters are easy to determine. The method provides an opportunity for a quantitative study on the particle shape of granular materials, and this study helps to better understand the influence of particle shape on the mechanical characteristics of rockfill materials.
Details
Keywords
Hongxing Wang, LianZheng Ge, Ruifeng Li, Yunfeng Gao and Chuqing Cao
An optimal solution method based on 2-norm is proposed in this study to solve the inverse kinematics multiple-solution problem caused by a high redundancy. The current research…
Abstract
Purpose
An optimal solution method based on 2-norm is proposed in this study to solve the inverse kinematics multiple-solution problem caused by a high redundancy. The current research also presents a motion optimization based on the 2-Norm of high-redundant mobile humanoid robots, in which a kinematic model is designed through the entire modeling.
Design/methodology/approach
The current study designs a highly redundant humanoid mobile robot with a differential mobile platform. The high-redundancy mobile humanoid robot consists of three modular parts (differential driving platform with two degrees of freedom (DOF), namely, left and right arms with seven DOF, respectively) and has total of 14 DOFs. Given the high redundancy of humanoid mobile robot, a kinematic model is designed through the entire modeling and an optimal solution extraction method based on 2-norm is proposed to solve the inverse kinematics multiple solutions problem. That is, the 2-norm of the angle difference before and after rotation is used as the shortest stroke index to select the optimal solution. The optimal solution of the inverse kinematics equation in the step is obtained by solving the minimum value of the objective function of a step. Through the step-by-step cycle in the entire tracking process, the kinematic optimization of the highly redundant humanoid robot in the entire tracking process is realized.
Findings
Compared with the before and after motion optimizations based on the 2-norm algorithm of the robot, its motion after optimization shows minimal fluctuation, improved smoothness, limited energy consumption and short path during the entire mobile tracking and operating process.
Research limitations/implications
In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.
Practical implications
In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.
Social implications
In this paper, the whole kinematics model of the highly redundant humanoid mobile robot is established and its motion is optimized based on 2-norm, which provides a theoretical basis for the follow-up research of the service robot.
Originality/value
Motion optimization based on the 2-norm of a highly redundant humanoid mobile robot with the entire modeling is performed on the basis of the entire modeling. This motion optimization can make the highly redundant humanoid mobile robot’s motion path considerably short, minimize energy loss and shorten time. These researches provide a theoretical basis for the follow-up research of the service robot, including tracking and operating target, etc. Finally, the motion optimization algorithm is verified by the tracking and operating behaviors of the robot and an example.
Details
Keywords
Jianjin Yue, Wenrui Li, Jian Cheng, Hongxing Xiong, Yu Xue, Xiang Deng and Tinghui Zheng
The calculation of buildings’ carbon footprint (CFP) is an important basis for formulating energy-saving and emission-reduction plans for building. As an important building type…
Abstract
Purpose
The calculation of buildings’ carbon footprint (CFP) is an important basis for formulating energy-saving and emission-reduction plans for building. As an important building type, there is currently no model that considers the time factor to accurately calculate the CFP of hospital building throughout their life cycle. This paper aims to establish a CFP calculation model that covers the life cycle of hospital building and considers time factor.
Design/methodology/approach
On the basis of field and literature research, the basic framework is built using dynamic life cycle assessment (DLCA), and the gray prediction model is used to predict the future value. Finally, a CFP model covering the whole life cycle has been constructed and applied to a hospital building in China.
Findings
The results applied to the case show that the CO2 emission in the operation stage of the hospital building is much higher than that in other stages, and the total CO2 emission in the dynamic and static analysis operation stage accounts for 83.66% and 79.03%, respectively; the difference of annual average emission of CO2 reached 28.33%. The research results show that DLCA is more accurate than traditional static life cycle assessment (LCA) when measuring long-term objects such as carbon emissions in the whole life cycle of hospital building.
Originality/value
This research established a carbon emission calculation model that covers the life cycle of hospital building and considered time factor, which enriches the research on carbon emission of hospital building, a special and extensive public building, and dynamically quantifies the resource consumption of hospital building in the life cycle. This paper provided a certain reference for the green design, energy saving, emission reduction and efficient use of hospital building, obviously, the limitation is that this model is only applicable to hospital building.
Details
Keywords
Yong Liu, Chang-Xue Lin and Gang Zhao
The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on…
Abstract
Purpose
The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.
Design/methodology/approach
To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.
Findings
The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.
Originality/value
The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.
Details
Keywords
Drawing on social capital theory, this study aims to explore the effect of corporate social responsibility (CSR) on organizational resilience. The research investigates the…
Abstract
Purpose
Drawing on social capital theory, this study aims to explore the effect of corporate social responsibility (CSR) on organizational resilience. The research investigates the mediating role of relationship quality in the association of CSR with organizational resilience, and the moderating role of data-driven culture in the association between CSR and relationship quality.
Design/methodology/approach
Data were collected from Chinese agricultural firms with a sample of 241 senior or middle executives and structural equation modeling was used to test the research model and hypotheses.
Findings
The results indicate that CSR positively affects the relationship quality between agribusinesses and farmers, which in turn positively affects both proactive resilience and reactive resilience. Relationship quality has a partial mediating role in the association of CSR with proactive resilience and reactive resilience. Data-driven culture has a positive moderating effect on the relationship between CSR and relationship quality.
Originality/value
By arguing for CSR toward organizational resilience and analyzing its underlying mechanism, this study enriches the literature on CSR and organizational resilience and expands the existing knowledge on the roles of relationship quality and data-driven culture. This study also provides practical insights into how to improve organizational resilience.
Details
Keywords
Shenlong Wang, Kaixin Han and Jiafeng Jin
In the past few decades, the content-based image retrieval (CBIR), which focuses on the exploration of image feature extraction methods, has been widely investigated. The term of…
Abstract
Purpose
In the past few decades, the content-based image retrieval (CBIR), which focuses on the exploration of image feature extraction methods, has been widely investigated. The term of feature extraction is used in two cases: application-based feature expression and mathematical approaches for dimensionality reduction. Feature expression is a technique of describing the image color, texture and shape information with feature descriptors; thus, obtaining effective image features expression is the key to extracting high-level semantic information. However, most of the previous studies regarding image feature extraction and expression methods in the CBIR have not performed systematic research. This paper aims to introduce the basic image low-level feature expression techniques for color, texture and shape features that have been developed in recent years.
Design/methodology/approach
First, this review outlines the development process and expounds the principle of various image feature extraction methods, such as color, texture and shape feature expression. Second, some of the most commonly used image low-level expression algorithms are implemented, and the benefits and drawbacks are summarized. Third, the effectiveness of the global and local features in image retrieval, including some classical models and their illustrations provided by part of our experiment, are analyzed. Fourth, the sparse representation and similarity measurement methods are introduced, and the retrieval performance of statistical methods is evaluated and compared.
Findings
The core of this survey is to review the state of the image low-level expression methods and study the pros and cons of each method, their applicable occasions and certain implementation measures. This review notes that image peculiarities of single-feature descriptions may lead to unsatisfactory image retrieval capabilities, which have significant singularity and considerable limitations and challenges in the CBIR.
Originality/value
A comprehensive review of the latest developments in image retrieval using low-level feature expression techniques is provided in this paper. This review not only introduces the major approaches for image low-level feature expression but also supplies a pertinent reference for those engaging in research regarding image feature extraction.