Wei Yang and Yongxin Gao
This paper aims to describe typical regional document supply networks in China through detailed discussion of their framework, service mode and influence on the nationwide…
Abstract
Purpose
This paper aims to describe typical regional document supply networks in China through detailed discussion of their framework, service mode and influence on the nationwide document supply networks.
Design/methodology/approach
This paper highlights various kinds of regional document supply networks in China that serve as document resource sharing cooperation networks within provinces, cities and university towns. Their framework, service mode and influence on the nationwide document supply networks are discussed, followed by suggestions for improvement.
Findings
Regional document supply networks have their natural advantages in local financial support and extensive local coverage and are capable of providing fine service to meet various user needs timely and economically. They become an important part and beneficial supplement to nationwide document supply networks.
Originality/value
This paper studies regional document supply networks in China which has rarely been addressed in the international library literature.
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Gang Li, Zhihuang Zhao, Lan Li, Yuanbo Li, Mengjiao Zhu and Yongxin Jiao
This study investigates the influence of artificial intelligence (AI) stimuli on customer stickiness (CS), the mediation effects of social presence (SP) and the moderating impacts…
Abstract
Purpose
This study investigates the influence of artificial intelligence (AI) stimuli on customer stickiness (CS), the mediation effects of social presence (SP) and the moderating impacts of customer traits in this influencing process.
Design/methodology/approach
Drawing on the arousal theory and social response theory, a conceptual model was established and tested by a data set of 268 customers in the catering industry.
Findings
The results indicate that AI stimuli, such as perceived personalization and perceived interactivity, positively affect CS. SP partially mediates the influence of AI stimuli on CS. Customer traits such as customers' need for interaction (NFI) and novelty seeking (NS) actively moderate the mediating effects of SP.
Originality/value
This study advances the interactive marketing literature from three aspects. Firstly, instead of focusing on the functional aspects of AI stimuli, it extends our understanding of AI-enabled interactive marketing by examining the effects of social and emotional aspects of AI stimuli on customer response. Secondly, it extends our understanding of social response by illuminating the mediating effects of SP between AI stimuli and CS. Finally, it provides new insights and empirical evidence for the research focus on customer traits in AI-enabled interactive marketing.
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Haojia Su, Zhengchun Cai, Zhengwei lv, Yongkang Chen and Yongxin Ji
In this work, the authors used reversible addition-fragmentation transfer (RAFT) polymerization to develop a new cationic acrylate modified epoxy resin emulsion for water-borne…
Abstract
Purpose
In this work, the authors used reversible addition-fragmentation transfer (RAFT) polymerization to develop a new cationic acrylate modified epoxy resin emulsion for water-borne inkjet which have the advantages of both polyacrylate and epoxy resin. The emulsion was successfully used in the canvas coating for inkjet printing. This paper aims to contribute to the development of novel cationic emulsions for inkjet printing industry.
Design/methodology/approach
In this work, the epoxy acrylate was synthesized from RAFT agent and epoxy resin firstly. Cationic macromolecular emulsifier was prepared by RAFT polymerization, using 2,2’-Azobisisobutyronitrile as initiator, 2-(dimethylamino)ethyl methacrylate and styrene as monomer, which was directly used to prepare the emulsion. The influences of the amount of 2-(dimethylamino)ethyl methacrylate on particle size, zeta potential and water contact angle were studied. Finally, the cationic emulsion was used to print images by inkjet printing.
Findings
The emulsion has the smallest particle size, the highest potential and the highest water contact angle when the DM content is 13 Wt.%. The transmission electron microscopy analysis reveals the latex particles is core-shell sphere with the diameters in the range 120–200 nm. The emulsion was successfully used in the canvas coating for inkjet printing. This work will contribute to the development of novel cationic emulsions for inkjet printing industry.
Originality/value
The emulsion was successfully used in the canvas coating for inkjet printing. This work will contribute to the development of novel cationic emulsions for inkjet printing industry.
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Yongxin Zhou, Qian Li, Zhiguo Xing, Renze Zhou, Zhenhua Huang, Yanfei Huang and Weiling Guo
This paper aims to investigate the effect of aluminum addition on the microstructure and mechanical properties of Mg-8Gd-4Y-1Zn alloy.
Abstract
Purpose
This paper aims to investigate the effect of aluminum addition on the microstructure and mechanical properties of Mg-8Gd-4Y-1Zn alloy.
Design/methodology/approach
Mg-8Gd-4Y-1Zn-xAl (x = 0, 0.5, 1.0, 1.5, 2.0 Wt.%) alloys were prepared by the conventional gravity casting technology, and then microstructures, phase composition and mechanical properties were investigated by material characterization method, systematically.
Findings
Results show that the as-cast microstructure of Mg-8Gd-4Y-1Zn alloy mainly consists of a-Mg matrix as well as Mg12REZn (18 R LPSO structure), and island-like Mg3(RE, Zn) phase is distributed at the grain boundary. The addition of a small amount of Al (0.5 Wt.%) can decrease the content of island-like Mg3(RE, Zn) phase, but significantly increase the content of long-period stacking ordered (LPSO) structure, resulting in the improvement of both tensile strength and elongation of Mg-8Gd-4Y-1Zn alloy. However, the addition of excessive Al will consume Re element and decrease the amount of LPSO structure, leading to the decrease of tensile properties. When the content of Al is 0.5 Wt.%, the tensile strength and elongation are 225 MPa and 9.0% of Mg-8Gd-4Y-1Zn alloy, which are 14% and 29% higher than that of Mg-8Gd-4Y-1Zn alloy, respectively.
Originality/value
Adding aluminum to Mg-8Gd-4Y-1Zn alloy strengthens its mechanical properties. And the effect of Al content on the alloy strengthening. The formation mechanism of LPSO structure with different aluminum content was revealed.
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Deepak Kumar, Yongxin Liu, Houbing Song and Sirish Namilae
The purpose of this study is to develop a deep learning framework for additive manufacturing (AM), that can detect different defect types without being trained on specific defect…
Abstract
Purpose
The purpose of this study is to develop a deep learning framework for additive manufacturing (AM), that can detect different defect types without being trained on specific defect data sets and can be applied for real-time process control.
Design/methodology/approach
This study develops an explainable artificial intelligence (AI) framework, a zero-bias deep neural network (DNN) model for real-time defect detection during the AM process. In this method, the last dense layer of the DNN is replaced by two consecutive parts, a regular dense layer denoted (L1) for dimensional reduction, and a similarity matching layer (L2) for equal weight and non-biased cosine similarity matching. Grayscale images of 3D printed samples acquired during printing were used as the input to the zero-bias DNN.
Findings
This study demonstrates that the approach is capable of successfully detecting multiple types of defects such as cracks, stringing and warping with high accuracy without any prior training on defective data sets, with an accuracy of 99.5%.
Practical implications
Once the model is set up, the computational time for anomaly detection is lower than the speed of image acquisition indicating the potential for real-time process control. It can also be used to minimize manual processing in AI-enabled AM.
Originality/value
To the best of the authors’ knowledge, this is the first study to use zero-bias DNN, an explainable AI approach for defect detection in AM.
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Muhammad Yazrin Yasin, Muhammad Azmi Bin Mohd Zain and Muhammad Haniff Bin Hassan
This paper discusses the urban management challenges in the Greater Kuala Lumpur area. Before examining Greater Kuala Lumpur's economic and social environment, we will look at the…
Abstract
This paper discusses the urban management challenges in the Greater Kuala Lumpur area. Before examining Greater Kuala Lumpur's economic and social environment, we will look at the factors that make it a competitive and fiscally sound entity. When considering urban development and redevelopment, we consider how proposed and ongoing projects, as well as plans, hierarchical links, and road networks, contributed to the increase. Because there is no urban growth boundary, land use change and rural encroachment, as well as environmental degradation and the impact of national economic projects on urban expansion, are both rapid and linear in the analysis. This paper also considers how to manage linear development that results in the creation of new suburbs. Finally, we propose strategies for achieving sustainable urban expansion and management by balancing the financial and governance capacities of Greater Kuala Lumpur local governments.
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Ana Camila Ferreira Mamede, José Roberto Camacho, Rui Esteves Araújo and Igor Santos Peretta
The purpose of this paper is to present the Moore-Penrose pseudoinverse (PI) modeling and compare with artificial neural network (ANN) modeling for switched reluctance machine…
Abstract
Purpose
The purpose of this paper is to present the Moore-Penrose pseudoinverse (PI) modeling and compare with artificial neural network (ANN) modeling for switched reluctance machine (SRM) performance.
Design/methodology/approach
In a design of an SRM, there are a number of parameters that are chosen empirically inside a certain interval, therefore, to find an optimal geometry it is necessary to define a good model for SRM. The proposed modeling uses the Moore-Penrose PI for the resolution of linear systems and finite element simulation data. To attest to the quality of PI modeling, a model using ANN is established and the two models are compared with the values determined by simulations of finite elements.
Findings
The proposed PI model showed better accuracy, generalization capacity and lower computational cost than the ANN model.
Originality/value
The proposed approach can be applied to any problem as long as experimental/computational results can be obtained and will deliver the best approximation model to the available data set.
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Mohammad Farhan Shaikh and Nallasivam K
In this study, a finite element model of a box-girder bridge along with the railway sub-track system is developed to predict the static behavior due to different combinations of…
Abstract
Purpose
In this study, a finite element model of a box-girder bridge along with the railway sub-track system is developed to predict the static behavior due to different combinations of the Indian railway system and free vibration responses resulting in different natural frequencies and their corresponding mode shapes.
Design/methodology/approach
The modeling and evaluation of the bridge and sub-track system were performed using non-closed form finite element method (FEM)-based ANSYS software.
Findings
From the analysis, the worst possible cases of deformation and stress due to different static load combinations were determined in the static analysis, while different natural frequencies were determined in the free vibrational analysis that can be used for further analysis because of the dynamic effect of the train vehicle.
Research limitations/implications
The scope of the current investigation is confined to the structure's static and free vibration analysis. However, this study will help the designers obtain relevant information for further analysis of the dynamic behavior of the bridge model.
Originality/value
In static analysis, the maximum deformation of the bridge deck was found to be 10.70E-03m due to load combination 5, whereas the maximum natural frequency for free vibration analysis is found to be 4.7626 Hz.