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1 – 5 of 5Guang Zhang and Jingyi Ge
This paper aims to study the establishment of cooperative supply game model considering transportation hub location, and design the profit allocation rule of the cooperative…
Abstract
Purpose
This paper aims to study the establishment of cooperative supply game model considering transportation hub location, and design the profit allocation rule of the cooperative supply coalition.
Design/methodology/approach
Based on the economic lost-sizing (ELS) game model and considering the location of transportation hub and the topology design of basic traffic network, we build a supply game model to maximize the profit of cooperative supply coalition. Based on the principle of proportion and the method of process allocation, we suppose the procedural proportional solution of the supplier cooperative supply game.
Findings
Through numerical examples, the validity and applicability of the proposed model and the procedural proportional solution were verified by comparing the procedural proportional solution with the weighted Shapley value, the equal division solution and the proportional rule.
Originality/value
This paper constructs a feasible mixed integer programming model for cooperative supply game. We also provide the algorithm of the allocation rule of cooperative supply game and the property analysis of the allocation rule.
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The purpose of this paper is to present a method that addresses the data sparsity problem in points of interest (POI) recommendation by introducing spatiotemporal context features…
Abstract
Purpose
The purpose of this paper is to present a method that addresses the data sparsity problem in points of interest (POI) recommendation by introducing spatiotemporal context features based on location-based social network (LBSN) data. The objective is to improve the accuracy and effectiveness of POI recommendations by considering both spatial and temporal aspects.
Design/methodology/approach
To achieve this, the paper introduces a model that integrates the spatiotemporal context of POI records and spatiotemporal transition learning. The model uses graph convolutional embedding to embed spatiotemporal context information into feature vectors. Additionally, a recurrent neural network is used to represent the transitions of spatiotemporal context, effectively capturing the user’s spatiotemporal context and its changing trends. The proposed method combines long-term user preferences modeling with spatiotemporal context modeling to achieve POI recommendations based on a joint representation and transition of spatiotemporal context.
Findings
Experimental results demonstrate that the proposed method outperforms existing methods. By incorporating spatiotemporal context features, the approach addresses the issue of incomplete modeling of spatiotemporal context features in POI recommendations. This leads to improved recommendation accuracy and alleviation of the data sparsity problem.
Practical implications
The research has practical implications for enhancing the recommendation systems used in various location-based applications. By incorporating spatiotemporal context, the proposed method can provide more relevant and personalized recommendations, improving the user experience and satisfaction.
Originality/value
The paper’s contribution lies in the incorporation of spatiotemporal context features into POI records, considering the joint representation and transition of spatiotemporal context. This novel approach fills the gap left by existing methods that typically separate spatial and temporal modeling. The research provides valuable insights into improving the effectiveness of POI recommendation systems by leveraging spatiotemporal information.
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Fuzhao Chen, Zhilei Chen, Qian Chen, Tianyang Gao, Mingyan Dai, Xiang Zhang and Lin Sun
The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production…
Abstract
Purpose
The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.
Design/methodology/approach
The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.
Findings
This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.
Originality/value
By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.
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Xiaobing Fan, Bingli Pan, Hongyu Liu, Shuang Zhao, Xiaofan Ding, Haoyu Gao, Bing Han and Hongbin Liu
This paper aims to prepare an oil-impregnated porous polytetrafluoroethylene (PTFE) composite with advanced tribological properties using citric acid as a novel pore-forming agent.
Abstract
Purpose
This paper aims to prepare an oil-impregnated porous polytetrafluoroethylene (PTFE) composite with advanced tribological properties using citric acid as a novel pore-forming agent.
Design/methodology/approach
Citric acid (CA) was used to form pores in PTFE, and then oil-impregnated PTFE composites were prepared. The pore-forming efficiency of CA was evaluated. The possible mechanism of lubrication was proposed according to the tribological properties.
Findings
The results show CA is an efficient pore-forming agent and completely removed, and the porosity of the PTFE increases with the increase of the CA content. The oil-impregnated porous PTFE exhibits an excellent tribological performance, an increased wear resistance of 77.29% was realized in comparison with neat PTFE.
Originality/value
This study enhances understanding of the lubrication mechanism of oil-impregnated porous polymers and guides for their tribological applications.
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Mark Pim-Wusu, Eric Kwame Simpeh and Mansfield Selasi Kortto
Bio-digester toilet handling in Ghana has become a modern trend, shadowing the traditional septic tank approach and other sewage methods. This practice raises environmental…
Abstract
Purpose
Bio-digester toilet handling in Ghana has become a modern trend, shadowing the traditional septic tank approach and other sewage methods. This practice raises environmental concerns that could affect human ageing. This study aims to investigate the effectiveness of bio-digester toilet facilities and their environmental effect on ageing in Accra, Ghana.
Design/methodology/approach
The study adopts quantitative and qualitative strategies. A purposive sampling technique was used to select households with bio-digester toilet facilities across the study area through a field survey questionnaire during Phase 1. A semi-structured interview was adopted for an in-depth perspective of the respondents, and laboratory analysis was performed on bio-digester effluent samples to validate phase one as a third stage. The quantitative data was analysed using descriptive statistics and laboratory analysis using standard methods for Escherichia coli, total coliform, dissolved oxygen, potential of hydrogen and temperature. The qualitative data was analysed using content analysis.
Findings
Laboratory analyses of effluent samples revealed that the bio-digester toilet facility could harm human health when its effluent is discharged into public drains. The study further discovered that only district and municipal assembly-certified technicians must construct the bio-digester toilet facilities, and households need regular education on the proper use and maintenance of the facility.
Originality/value
The revelation of this research means that it is essential for the country at large to make appropriate bylaws to regulate toilet waste handling and their environmental effect on ageing regarding households that discharge bio-digester toilet effluents into public drains for the betterment of the global agenda of sustainable development.
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