Zhijie Chen, Qile Chen, Weizhen Chen and Yinao Wang
This paper describes the use of grey system theory in mathematical programming problems. In particular, the linear programming problem, which is one of the most widely used…
Abstract
This paper describes the use of grey system theory in mathematical programming problems. In particular, the linear programming problem, which is one of the most widely used mathematical programming problems, with grey interval and grey forecasting are developed. The adaptability of both these linear programming problems is rather satisfactory.
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Zhijie Chen, Weizhen Chen and Qile Chen
The purpose of this paper is to propose a new group decision‐making approach, which can only use simple mathematical calculations to perform a group decision‐making task.
Abstract
Purpose
The purpose of this paper is to propose a new group decision‐making approach, which can only use simple mathematical calculations to perform a group decision‐making task.
Design/methodology/approach
The large column and large row (LCLR) method is designed and applied.
Findings
The paper finds four propositions to support LCLR methods to be a simple and effectual means for group decision making.
Research limitations/implications
The aggregated matrix constructed in LCLR methods should be generated from non‐contradictory circles.
Practical implications
Effective group decision‐making results can be obtained by easily used methods, not necessarily by using complex mathematics technology to conduct the task.
Originality/value
The new approach based on LCLR methods proposed in this paper may be one of the most easily used and effective means for group decision making.
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Hao Zhan, Qinhan Fang and Weizhen Chen
Bridge plans are a complicated grey system. It depends on various natural and social factors. The purpose of this paper is to provide a scientific method for optimization of…
Abstract
Purpose
Bridge plans are a complicated grey system. It depends on various natural and social factors. The purpose of this paper is to provide a scientific method for optimization of bridge construction plan.
Design/methodology/approach
Grey relational analysis (GRA) is completely new analysis method has been proposed in the grey system theory. Grey relational order can be used to describe the relation between the related factors based on data series rather than linear relation and typical distribution. First, this paper describes the basic steps and formulae of GRA. Then provides an example to show how to select best bridge construction plan with the method. Specially discusses significant influence of weight selection on decision making for a bridge plan.
Findings
The optimization of bridge construction plan will be selected more reasonable and more objective with the method GRA.
Research limitations/implications
This paper will be further studied on how to quantify indicators more objectively and how to decide weight factor more reasonably.
Practical implications
It has significant practical value to apply GRA to optimization of bridge plans and other engineering projects.
Originality/value
A scientific method‐GRA has been applied to the selection of bridge plans for seeking the best comprehensive result.
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Weizhen Chen, Bingwen Wang, Hao Zhan and Long Zhou
Denoising of the vibration signal is crucial to identify a structure's damage. Based on noise frequency character, the “real” vibration signal can be gotten. The purpose of this…
Abstract
Purpose
Denoising of the vibration signal is crucial to identify a structure's damage. Based on noise frequency character, the “real” vibration signal can be gotten. The purpose of this paper is to propose a novel method for denoising a signal based on the wavelet transform.
Design/methodology/approach
The vibration signal with noise which can be collected by wireless network is decomposed by wavelet transform. In order to select optimal level of wavelet decomposition, based on noise's frequency, power spectral density is used. A soft thresholding method based on minimum mean‐variance is used for vibration signal de‐noising with Gaussian noise.
Findings
A novel method has been described in his paper. Based on the relationship between vibration signal's character and noise frequency, the way to get rid of noise is combined wavelet transform with power spectral density.
Originality/value
In order to select optimal level of wavelet decomposition, based on noise's frequency, power spectral density is used. A soft thresholding method based on minimum mean‐variance is used for vibration signal denoising with Gaussian noise.
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Björn Berggren and Lars Silver
The purpose of this paper is to analyse the role of social capital and bridging networks on entrepreneurial activity in three different regions in Sweden.
Abstract
Purpose
The purpose of this paper is to analyse the role of social capital and bridging networks on entrepreneurial activity in three different regions in Sweden.
Design/methodology/approach
The empirical base of the paper comprises 120 in‐depth interviews with entrepreneurs and other stakeholders in three municipalities in Sweden, statistical data from Statistics Sweden and a large postal survey conducted by the Confederation of Swedish Enterprises.
Findings
The bridging networks between local civil servants and local politicians on the one hand and entrepreneurs on the other are pivotal for the development of an entrepreneurial community.
Research limitations/implications
Despite the same rational‐legal framework, this paper shows how the cognitive dimension of social capital influences the level of entrepreneurship in three municipalities. The importance of bridging networks is also highlighted.
Practical implications
An open channel of communication between politicians and entrepreneurs allows the former to gain legitimacy in the eyes of the latter. By widening the network, more actors are involved in local and regional development, thereby raising the level of competence and resources.
Originality/value
Using three different sets of data, this paper offers a deeper understanding into the complex nature of bridging networks between politics and business.
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Hongming Gao, Hongwei Liu, Weizhen Lin and Chunfeng Chen
Purchase conversion prediction aims to improve user experience and convert visitors into real buyers to drive sales of firms; however, the total conversion rate is low, especially…
Abstract
Purpose
Purchase conversion prediction aims to improve user experience and convert visitors into real buyers to drive sales of firms; however, the total conversion rate is low, especially for e-retailers. To date, little is known about how e-retailers can scientifically detect users' intents within a purchase conversion funnel during their ongoing sessions and strategically optimize real-time marketing tactics corresponding to dynamic intent states. This study mainly aims to detect a real-time state of the conversion funnel based on graph theory, which refers to a five-class classification problem in the overt real-time choice decisions (RTCDs)—click, tag-to-wishlist, add-to-cart, remove-from-cart and purchase—during an ongoing session.
Design/methodology/approach
The authors propose a novel graph-theoretic framework to detect different states of the conversion funnel by identifying a user's unobserved mindset revealed from their navigation process graph, namely clickstream graph. First, the raw clickstream data are identified into individual sessions based on a 30-min time-out heuristic approach. Then, the authors convert each session into a sequence of temporal item-level clickstream graphs and conduct a temporal graph feature engineering according to the basic, single-, dyadic- and triadic-node and global characteristics. Furthermore, the synthetic minority oversampling technique is adopted to address with the problem of classifying imbalanced data. Finally, the authors train and test the proposed approach with several popular artificial intelligence algorithms.
Findings
The graph-theoretic approach validates that users' latent intent states within the conversion funnel can be interpreted as time-varying natures of their online graph footprints. In particular, the experimental results indicate that the graph-theoretic feature-oriented models achieve a substantial improvement of over 27% in line with the macro-average and micro-average area under the precision-recall curve, as compared to the conventional ones. In addition, the top five informative graph features for RTCDs are found to be Transitivity, Edge, Node, Degree and Reciprocity. In view of interpretability, the basic, single-, dyadic- and triadic-node and global characteristics of clickstream graphs have their specific advantages.
Practical implications
The findings suggest that the temporal graph-theoretic approach can form an efficient and powerful AI-based real-time intent detecting decision-support system. Different levels of graph features have their specific interpretability on RTCDs from the perspectives of consumer behavior and psychology, which provides a theoretical basis for the design of computer information systems and the optimization of the ongoing session intervention or recommendation in e-commerce.
Originality/value
To the best of the authors' knowledge, this is the first study to apply clickstream graphs and real-time decision choices in conversion prediction and detection. Most studies have only meditated on a binary classification problem, while this study applies a graph-theoretic approach in a five-class classification problem. In addition, this study constructs temporal item-level graphs to represent the original structure of clickstream session data based on graph theory. The time-varying characteristics of the proposed approach enhance the performance of purchase conversion detection during an ongoing session.
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Weizhen Wang, Yukari Nagai, Yuan Fang and Masami Maekawa
The purpose of this paper is to bridge the gap between human emotions and wearable technologies for interactive fashion innovation. To consider the reasons why smart clothing…
Abstract
Purpose
The purpose of this paper is to bridge the gap between human emotions and wearable technologies for interactive fashion innovation. To consider the reasons why smart clothing should satisfy the internet of things (IoT) technical functions and human emotional expression simultaneously, to investigate the manner in which artistic design perspectives and engineering methods combined effectively, to explore the R&D elements of future smart clothing based on the IoT technology.
Design/methodology/approach
This study combines artistic design perspectives with information-sensing engineering methods as well as kansei evaluation method. Micro-sensors and light-emitting diodes (LEDs) embedded in couples clothing prototype. The first experiment step in the design and production of prototype clothing, and do the initial emotional evaluation. The second experiment is the comparative evaluation of the prototype and other typical smart clothing.
Findings
The interactive clothing prototype was proven to correlate well with human emotional expressive patterns. The evaluation I indicated the prototype can stimulate the emotional response of the participants to achieve a higher score in the activate sensor state. Evaluation II revealed that in the process of interactive clothing design, the technical functionality should synchronize with the requirements of human emotional expression.
Originality/value
This study builds the research and development theoretical model of interactive clothing that can be integrated into daily smart clothing life design, and analyze the methods and means of blending IoT smart information-sensing technology with emotional design. By means of this experimental demonstration of human-centered interactive clothing design, the authors provide smart clothing 3.0 evolutionary roadmap and propose a new concept of internet of clothes (IoC) for further research reference.
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Fengxia Lu, Meng Wang, Weizhen Liu, Heyun Bao and Rupeng Zhu
This paper aims to propose a numerical method to calculate the convective heat transfer coefficient of spiral bevel gears under the condition of splash lubrication and to reveal…
Abstract
Purpose
This paper aims to propose a numerical method to calculate the convective heat transfer coefficient of spiral bevel gears under the condition of splash lubrication and to reveal the lubrication and temperature characteristics between the gears and the oil-air two-phase flow.
Design/methodology/approach
Based on computational fluid dynamics, the multiple reference frames (MRF) method was used to simulate the rotational characteristics of gears and the motions of their surrounding fluid. The lubrication and temperature characteristics of gears were studied by combining the MRF method with the volume of the fluid multiphase flow model.
Findings
The convective heat transfer coefficient can be improved by increasing the rotational speed and the oil immersion depth. Moreover, the temperature of the tooth surface having a large convective heat transfer coefficient is also found to be low. A large convection heat transfer coefficient could lead to a good cooling effect.
Originality/value
This method can be used to obtain the convective heat transfer coefficient values at different meshing positions, different radii and different tooth surface positions. It also can provide research methods for improving the cooling effect of gears under the condition of splash lubrication.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0233/