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1 – 10 of 49
Article
Publication date: 1 July 2003

Xiaolong Wu, Dinghe Guo, Jinghong Pan and Xuemou Wu

In this paper, we will introduce charm pansystems and provide mathematical models for panweighted field‐network. Various mathematical models of pansystems will be discussed. Some…

Abstract

In this paper, we will introduce charm pansystems and provide mathematical models for panweighted field‐network. Various mathematical models of pansystems will be discussed. Some traditional mathematical concepts such as topology space and rough sets theory will be analyzed within this framework.

Details

Kybernetes, vol. 32 no. 5/6
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 7 July 2023

Xiaojie Xu and Yun Zhang

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important…

Abstract

Purpose

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

Design/methodology/approach

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

Findings

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

Originality/value

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

Details

Journal of Financial Management of Property and Construction , vol. 29 no. 1
Type: Research Article
ISSN: 1366-4387

Keywords

Article
Publication date: 7 June 2021

Sixian Chan, Jian Tao, Xiaolong Zhou, Binghui Wu, Hongqiang Wang and Shengyong Chen

Visual tracking technology enables industrial robots interacting with human beings intelligently. However, due to the complexity of the tracking problem, the accuracy of visual…

Abstract

Purpose

Visual tracking technology enables industrial robots interacting with human beings intelligently. However, due to the complexity of the tracking problem, the accuracy of visual target tracking still has great space for improvement. This paper aims to propose an accurate visual target tracking method based on standard hedging and feature fusion.

Design/methodology/approach

For this study, the authors first learn the discriminative information between targets and similar objects in the histogram of oriented gradients by feature optimization method, and then use standard hedging algorithms to dynamically balance the weights between different feature optimization components. Moreover, they penalize the filter coefficients by incorporating spatial regularization coefficient and extend the Kernelized Correlation Filter for robust tracking. Finally, a model update mechanism to improve the effectiveness of the tracking is proposed.

Findings

Extensive experimental results demonstrate the superior performance of the proposed method comparing to the state-of-the-art tracking methods.

Originality/value

Improvements to existing visual target tracking algorithms are achieved through feature fusion and standard hedging algorithms to further improve the tracking accuracy of robots on targets in reality.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 15 December 2020

Desheng Wu, Jingxiu Song, Yuan Bian, Xiaolong Zheng and Zhu Zhang

The increase of turbulence sources and risk points under the complex social information network has brought severe challenges. This paper discusses risk perception and intelligent…

Abstract

Purpose

The increase of turbulence sources and risk points under the complex social information network has brought severe challenges. This paper discusses risk perception and intelligent decision-making under the complex social information network to maintain social security and financial security.

Design/methodology/approach

Cross-modal semantic fusion and social risk perception, temporal knowledge graph and analysis, complex social network intelligent decision-making methods have been studied. A big data computing platform of software and hardware integration for security combat is constructed based on the technical support.

Findings

The software and hardware integration platform driven by big data can realize joint identification of significant risks, intelligent analysis and large-scale group decision-making.

Practical implications

The integrated platform can monitor the abnormal operation and potential associated risks of Listed Companies in real-time, reduce information asymmetry and accounting costs and improve the capital market's ability to serve the real economy. It can also provide critical technical support and decision support in necessary public opinion monitoring and control business.

Originality/value

In this paper, the theory of knowledge-enhanced multi-modal multi-granularity dynamic risk analysis and intelligent group decision-making and the idea of an inference think tank (I-aid-S) is proposed. New technologies and methods, such as association analysis, time series evolution and super large-scale group decision-making, have been established. It's also applied in behavior and situation deduction, public opinion and finance and provides real-time, dynamic, fast and high-quality think tank services.

Details

Industrial Management & Data Systems, vol. 121 no. 1
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 9 November 2022

Zhicheng Song, Xiang Li, Xiaolong Yang, Yao Li, Linkang Wang and Hongtao Wu

This paper aims to improve the kinematic modeling accuracy of a spatial three-degrees-of-freedom compliant micro-motion parallel mechanism by proposing a modified modeling method…

183

Abstract

Purpose

This paper aims to improve the kinematic modeling accuracy of a spatial three-degrees-of-freedom compliant micro-motion parallel mechanism by proposing a modified modeling method based on the structural matrix method (SMM).

Design/methodology/approach

This paper analyzes the problem that the torsional compliance equation of the circular notched hinge is no longer applicable because it is subject to bilateral restrained torsion. The torsional compliance equation is modified by introducing the relative length coefficient. The input coupling effect, which is often neglected, is considered in kinematic modeling. The symbolic expression of the input coupling matrix is obtained. Theory, simulation and experimentation are presented to show the validity of the proposed kinematic model.

Findings

The results show that the proposed kinematics model can improve the modeling accuracy by comparing the theoretical, finite element method (FEM) and experimental method.

Originality/value

This work provides a feasible scheme for CMPM kinematics modeling. It can be better applied to the optimization design based on the kinematic model in the future.

Details

Industrial Robot: the international journal of robotics research and application, vol. 50 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 29 October 2020

Ting Luo, Xiaolong Xue, Yongtao Tan, Yuna Wang and Yuanxin Zhang

This paper aimed to introduce a systematic body of knowledge via a scientometric review, guiding the sustainable transition from conventional construction to prefabricated…

1596

Abstract

Purpose

This paper aimed to introduce a systematic body of knowledge via a scientometric review, guiding the sustainable transition from conventional construction to prefabricated construction. The construction industry currently faces a challenge to balance sustainable development and the construction of new buildings. In this context, one of the most recent debates is prefabricated construction. As an emerging construction approach, although existing knowledge makes contributions to the implementation of prefabricated construction, there is a lack of a comprehensive and in-depth overview of the critical knowledge themes and gaps.

Design/methodology/approach

This study uses the scientometric analysis to review the state-of-the-art knowledge of prefabricated construction. It retrieved data from the Web of Science core collection database. CiteSpace software was used to conduct the analysis and visualization; three analysis methods identify the knowledge hotspots, knowledge domains and knowledge topics. Finally, according to integrating the hidden connections among results, a body of knowledge for prefabricated construction application can be inferred.

Findings

The results show that 120 knowledge hotspots, five critical knowledge domains and five prominent knowledge topics are vital for promoting implementation of prefabricated construction. Based on the afore analysis, a body of knowledge for prefabricated construction that can systematically cover a broad knowledge of prefabricated construction-related research and activities are integrated and proposed in this paper.

Originality/value

Body of knowledge systematically covers a broad knowledge of prefabricated construction applications and is vital to guide researchers and practitioners to conduct related research and activities, thereby promoting the sustainable transition to prefabricated construction implementation.

Details

Engineering, Construction and Architectural Management, vol. 28 no. 9
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 12 September 2023

Yang Zhou, Long Wang, Yongbin Lai and Xiaolong Wang

The coupling process between the loading mechanism and the tank car mouth is a crucial step in the tank car loading process. The purpose of this paper is to design a method to…

Abstract

Purpose

The coupling process between the loading mechanism and the tank car mouth is a crucial step in the tank car loading process. The purpose of this paper is to design a method to accurately measure the pose of the tanker car.

Design/methodology/approach

The collected image is first subjected to a gray enhancement operation, and the black parts of the image are extracted using Otsu’s threshold segmentation and morphological processing. The edge pixels are then filtered to remove outliers and noise, and the remaining effective points are used to fit the contour information of the tank car mouth. Using the successfully extracted contour information, the pose information of the tank car mouth in the camera coordinate system is obtained by establishing a binocular projection elliptical cone model, and the pixel position of the real circle center is obtained through the projection section. Finally, the binocular triangulation method is used to determine the position information of the tank car mouth in space.

Findings

Experimental results have shown that this method for measuring the position and orientation of the tank car mouth is highly accurate and can meet the requirements for industrial loading accuracy.

Originality/value

A method for extracting the contours of various types of complex tanker mouth is proposed. This method can accurately extract the contour of the tanker mouth when the contour is occluded or disturbed. Based on the binocular elliptic conical model and perspective projection theory, an innovative method for measuring the pose of the tanker mouth is proposed, and according to the space characteristics of the tanker mouth itself, the ambiguity of understanding is removed. This provides a new idea for the automatic loading of ash tank cars.

Details

Robotic Intelligence and Automation, vol. 43 no. 6
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 11 June 2021

Xiaolong Zhou, Pinghao Wang, Sixian Chan, Kai Fang and Jianwen Fang

Visual object tracking plays a significant role in intelligent robot systems. This study aims to focus on unlocking the tracking performance potential of the deep network and…

Abstract

Purpose

Visual object tracking plays a significant role in intelligent robot systems. This study aims to focus on unlocking the tracking performance potential of the deep network and presenting a dynamic template update strategy for the Siamese trackers.

Design/methodology/approach

This paper presents a novel and efficient Siamese architecture for visual object tracking which introduces densely connected convolutional layers and a dynamic template update strategy into Siamese tracker.

Findings

The most advanced performance can be achieved by introducing densely connected convolutional neural networks that have not yet been applied to the tracking task into SiamRPN. By using the proposed architecture, the experimental results demonstrate that the performance of the proposed tracker is 5.8% (area under curve), 5.4% expected average overlap (EAO) and 3.5% (EAO) higher than the baseline on the OTB100, VOT2016 and VOT2018 data sets and achieves an excellent EAO score of 0.292 on the VOT2019 data set.

Originality/value

This study explores a deeper backbone network with each convolutional network layer densely connected. In response to tracking errors caused by templates that are not updated, this study proposes a dynamic template update strategy.

Details

Industrial Robot: the international journal of robotics research and application, vol. 48 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 7 March 2024

Fei Xu, Zheng Wang, Wei Hu, Caihao Yang, Xiaolong Li, Yaning Zhang, Bingxi Li and Gongnan Xie

The purpose of this paper is to develop a coupled lattice Boltzmann model for the simulation of the freezing process in unsaturated porous media.

Abstract

Purpose

The purpose of this paper is to develop a coupled lattice Boltzmann model for the simulation of the freezing process in unsaturated porous media.

Design/methodology/approach

In the developed model, the porous structure with complexity and disorder was generated by using a stochastic growth method, and then the Shan-Chen multiphase model and enthalpy-based phase change model were coupled by introducing a freezing interface force to describe the variation of phase interface. The pore size of porous media in freezing process was considered as an influential factor to phase transition temperature, and the variation of the interfacial force formed with phase change on the interface was described.

Findings

The larger porosity (0.2 and 0.8) will enlarge the unfrozen area from 42 mm to 70 mm, and the rest space of porous medium was occupied by the solid particles. The larger specific surface area (0.168 and 0.315) has a more fluctuated volume fraction distribution.

Originality/value

The concept of interfacial force was first introduced in the solid–liquid phase transition to describe the freezing process of frozen soil, enabling the formulation of a distribution equation based on enthalpy to depict the changes in the water film. The increased interfacial force serves to diminish ice formation and effectively absorb air during the freezing process. A greater surface area enhances the ability to counteract liquid migration.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 34 no. 4
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 6 March 2020

Xiaolong Tian and Tom Christensen

Compared with the worldwide reform trend of transcending new public management (NPM) during the past two decades, China's service-oriented government (SOG) reforms are a…

Abstract

Purpose

Compared with the worldwide reform trend of transcending new public management (NPM) during the past two decades, China's service-oriented government (SOG) reforms are a relatively different reform approach. After building an SOG was politically identified in 2004, China launched three rounds of SOG reforms in 2008, 2013 and 2018. The purpose of this article is to examine what is meant by China's SOG approach and analyze the reasons behind its emergence. In particular, it explores how this approach might be interpreted in NPM, and particularly post-NPM terms.

Design/methodology/approach

The main theoretical basis of the paper is three theoretical perspectives from organizational theory – the instrumental, cultural and myth perspectives, but more specifically, the concepts complexity and hybridity. The empirical examples are selected from the SOG reforms of 2008, 2013 and 2018. The data used are a combination of public documents and scholarly secondary literature.

Findings

This paper discusses the SOG approach in China as a response to the negative effects of NPM-related reforms and informed by the western post-NPM reforms. It contends that China's SOG is a complex and hybrid approach in which NPM and post-NPM elements coexist and their balance is different from the west.

Originality/value

Few authors have considered China's SOG approach in NPM and post-NPM terms. This paper contributes not only to a wider understanding of the ongoing SOG reform process in China, but also to the understanding of the relevance of public administration theories in a comparative perspective.

Details

International Journal of Public Sector Management, vol. 33 no. 4
Type: Research Article
ISSN: 0951-3558

Keywords

1 – 10 of 49