Xin Rui, Junying Wu, Jianbin Zhao and Maryam Sadat Khamesinia
Based on the positive features of the shark smell optimization (SSO) algorithm, the purpose of this paper is to propose a method based on this algorithm, dynamic voltage and…
Abstract
Purpose
Based on the positive features of the shark smell optimization (SSO) algorithm, the purpose of this paper is to propose a method based on this algorithm, dynamic voltage and frequency scaling (DVFS) model and fuzzy logic to minimize the energy consumption of integrated circuits of internet of things (IoT) nodes and maximize the load-balancing among them.
Design/methodology/approach
Load balancing is a key problem in any distributed environment such as cloud and IoT. It is useful when a few nodes are overloaded, a few are under-loaded and the remainders are idle without interrupting the functioning. As this problem is known as an NP-hard one and SSO is a powerful meta-hybrid method that inspires shark hunting behavior and their skill to detect and feel the smell of the bait even from far away, in this research, this study have provided a new method to solve this problem using the SSO algorithm. Also, the study have synthesized the fuzzy logic to counterbalance the load distribution. Furthermore, DVFS, as a powerful energy management method, is used to reduce the energy consumption of integrated circuits of IoT nodes such as processor and circuit bus by reducing the frequency.
Findings
The outcomes of the simulation have indicated that the proposed method has outperformed the hybrid ant colony optimization – particle swarm optimization and PSO regarding energy consumption. Similarly, it has enhanced the load balance better than the moth flame optimization approach and task execution node assignment algorithm.
Research limitations/implications
There are many aspects and features of IoT load-balancing that are beyond the scope of this paper. Also, given that the environment was considered static, future research can be in a dynamic environment.
Practical implications
The introduced method is useful for improving the performance of IoT-based applications. We can use these systems to jointly and collaboratively check, handle and control the networks in real-time. Also, the platform can be applied to monitor and control various IoT applications in manufacturing environments such as transportation systems, automated work cells, storage systems and logistics.
Originality/value
This study have proposed a novel load balancing technique for decreasing energy consumption using the SSO algorithm and fuzzy logic.
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Yingying Zhou, Jianbin Chen and Baodong Cheng
The purpose of this paper is to analyze the effect and mechanism of platform incentives on users’ knowledge collaboration performance (KCP) and the configuration leading to high…
Abstract
Purpose
The purpose of this paper is to analyze the effect and mechanism of platform incentives on users’ knowledge collaboration performance (KCP) and the configuration leading to high KCP in online knowledge communities (OKCs) in the post-COVID-19 pandemic era from a cross-culture perspective.
Design/methodology/approach
A survey method and a standard questionnaire were applied. The data was analyzed using multiple regression and fuzzy set qualitative comparative analysis.
Findings
The results indicate that, for both kinds of users, self-enhancement and communication positively affect the KCP. User engagement significantly mediates the relationship between communication and KCP and knowledge absorptive capacity moderates the relationship between user engagement and KCP. In contrast, material incentive positively affects the KCP of Chinese users, while hurting the cross-cultural sample. And the promotion of KCP for cross-cultural samples does not require a higher engagement and knowledge absorptive capacity, while paying more attention to short-term interests, such as communication and self-enhancement.
Research limitations/implications
The study only divides users into Chinese and cross-cultural foreign users, without a distinction between foreign users in different countries. In addition, the research is based on cross-sectional data and failed to try to explore the long-term effects of these incentives from the time dimension.
Originality/value
This study explores the incentive mechanism and configuration of OKC platforms to achieve high KCP for different users from a cross-cultural perspective. It provides new ideas and solutions for precise incentives for users of OKC platforms.
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Zhanfu Li, Jianbin Liang, Peiyu Jia, Shaoqi Zheng, Hongzhi Zhou and Xin Tong
The purpose of this paper is to study the screen surface parameters of the double deck vibrating screen, in sections, to determine the influence of each part of the screen surface…
Abstract
Purpose
The purpose of this paper is to study the screen surface parameters of the double deck vibrating screen, in sections, to determine the influence of each part of the screen surface on the screening efficiency of the vibrating screen. Finally, the best screening parameters were calculated to obtain the best screening performance.
Design/methodology/approach
In this paper, the discrete element method is used to simulate the process of two-layer subsection screening. Response surface test was used to analyze the influence of various factors and their interactions on screening results. Finally, based on the binomial regression model of screening efficiency, the optimal combination of vibration parameters is calculated.
Findings
In the screening process of vibrating screen, due to the different screening environments in each area of the screen surface, the single-layer linear vibrating screen with equal screen surface parameters cannot obtain the best screening performance. Among the single factors, the effect of vibration frequency is the most significant.
Originality/value
To address the issue of single layer linear vibrating screens with equal screen surface parameters being unable to maintain optimal screening performance when handling large amounts of materials. This article proposes a double layer vibrating screen with different screen surface grids and screen surface angles to address the problem of low screening performance of traditional single layer linear vibrating screens.
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The missing travel time data for roads is a common problem encountered by traffic management departments. Tensor decomposition, as one of the most widely used method for…
Abstract
Purpose
The missing travel time data for roads is a common problem encountered by traffic management departments. Tensor decomposition, as one of the most widely used method for completing missing traffic data, plays a significant role in the intelligent transportation system (ITS). However, existing methods of tensor decomposition focus on the global data structure, resulting in relatively low accuracy in fibrosis missing scenarios. Therefore, this paper aims to propose a novel tensor decomposition model which further considers the local spatiotemporal similarity for fibrosis missing to improve travel time completion accuracy.
Design/methodology/approach
The proposed model can aggregate road sections with similar physical attributes by spatial clustering, and then it calculates the temporal association of road sections by the dynamic longest common subsequence. A similarity relationship matrix in the temporal dimension is constructed and incorporated into the tensor completion model, which can enhance the local spatiotemporal relationship of the missing parts of the fibrosis type.
Findings
The experiment shows that this method is superior and robust. Compared with other baseline models, this method has the smallest error and maintains good completion results despite high missing rates.
Originality/value
This model has higher accuracy for the fibrosis missing and performs good convergence effects in the case of the high missing rate.
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Jianbin Luo, Yuanhao Tie, Ke Mi, Yajuan Pan, Lifei Tang, Yuan Li, Hongxiang Xu, Zhonghang Liu, Mingsen Li and Chunmei Jiang
The purpose of this paper is to investigate the optimal average drag coefficient of the Ahmed body for mixed platoon driving under crosswind and no crosswind conditions using the…
Abstract
Purpose
The purpose of this paper is to investigate the optimal average drag coefficient of the Ahmed body for mixed platoon driving under crosswind and no crosswind conditions using the response surface optimization method. This study has extraordinary implications for the planning of future intelligent transportation.
Design/methodology/approach
First, the single vehicle and vehicle platoon models are validated. Second, the configuration with the lowest average drag coefficient under the two conditions is obtained by response surface optimization. At the same time, the aerodynamic characteristics of the mixed platoon driving under different conditions are also analyzed.
Findings
The configuration with the lowest average drag coefficient under no crosswind conditions is 0.3 L for longitudinal spacing and 0.8 W for lateral spacing, with an average drag coefficient of 0.1931. The configuration with the lowest average drag coefficient under crosswind conditions is 10° for yaw angle, 0.25 L for longitudinal spacing, and 0.8 W for lateral spacing, with an average drag coefficient of 0.2251. Compared to the single vehicle, the average drag coefficients for the two conditions are reduced by 25.1% and 41.3%, respectively.
Originality/value
This paper investigates the lowest average drag coefficient for mixed platoon driving under no crosswind and crosswind conditions using a response surface optimization method. The computational fluid dynamics (CFD) results of single vehicle and vehicle platoon are compared and verified with the experimental results to ensure the reliability of this study. The research results provide theoretical reference and guidance for the planning of intelligent transportation.
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Urban MICE competitiveness research consists of two clusters, one that is public-statistics-based and another that is questionnaire-based. Supply-side research on urban MICE…
Abstract
Purpose
Urban MICE competitiveness research consists of two clusters, one that is public-statistics-based and another that is questionnaire-based. Supply-side research on urban MICE competitiveness is rare. Based on the findings of Chen (2014) and other scholars, the purpose of this paper is to design counterpart statistical indicators to empirically analyze CMCA member cities.
Design/methodology/approach
After calculating the standardized Z value of the original statistical data for 17 CMCA member cities, the authors conducted confirmatory factor analysis for the first-level principal components, based on which hierarchical clustering was performed; then, regression analysis was conducted with the MICE profit factor as the dependent variable and the cost factor, tight support factor and facilitating factor as the independent variables to support publishing articles.
Findings
The confirmatory factor analysis showed that the urban MICE competitiveness indicators from the supply-side perspective include the profit factor, cost factor, tight support factor and facilitating factor.
Research limitations/implications
On the basis of research findings from the demand perspective and the literature review, the authors constructed an urban MICE competitiveness indicator system from the perspective of the supply side and conducted principal component analysis. However, because of the inaccessibility of panel data, the current data were only sufficient to conduct the research. If panel data could be acquired, further research could be conducted to perfect the current indicator system for urban MICE competitiveness.
Practical implications
The findings suggest that tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.
Social implications
The tight support factor exerts a significant positive influence on urban MICE competitiveness from the supply-side perspective, while the cost factor exerts a significant negative influence. The findings suggest that the tourism total income, tourism foreign exchange income, inbound tourist number, number of exhibitions, exhibition area, number of UFI member cities and number of ICCA member cities were the main reason for the gap between different cities’ competitiveness and the reform focus for improving urban MICE competitiveness. The cost factor had a significantly negative influence on urban MICE competitiveness, implying that the higher the average hotel room price and revenue per available room, the less competitive the MICE host city is.
Originality/value
The research bridge the empirical statistics and the questionnaire-based perception study on urban MICE tourism image, and advance to construct an empirical statistics based indicator system for urban MICE tourism image.
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Jianbin Xiong, Jinji Nie and Jiehao Li
This paper primarily aims to focus on a review of convolutional neural network (CNN)-based eye control systems. The performance of CNNs in big data has led to the development of…
Abstract
Purpose
This paper primarily aims to focus on a review of convolutional neural network (CNN)-based eye control systems. The performance of CNNs in big data has led to the development of eye control systems. Therefore, a review of eye control systems based on CNNs is helpful for future research.
Design/methodology/approach
In this paper, first, it covers the fundamentals of the eye control system as well as the fundamentals of CNNs. Second, the standard CNN model and the target detection model are summarized. The eye control system’s CNN gaze estimation approach and model are next described and summarized. Finally, the progress of the gaze estimation of the eye control system is discussed and anticipated.
Findings
The eye control system accomplishes the control effect using gaze estimation technology, which focuses on the features and information of the eyeball, eye movement and gaze, among other things. The traditional eye control system adopts pupil monitoring, pupil positioning, Hough algorithm and other methods. This study will focus on a CNN-based eye control system. First of all, the authors present the CNN model, which is effective in image identification, target detection and tracking. Furthermore, the CNN-based eye control system is separated into three categories: semantic information, monocular/binocular and full-face. Finally, three challenges linked to the development of an eye control system based on a CNN are discussed, along with possible solutions.
Originality/value
This research can provide theoretical and engineering basis for the eye control system platform. In addition, it also summarizes the ideas of predecessors to support the development of future research.
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Ming-Hui Liu, Jianbin Xiong, Chun-Lin Li, Weijun Sun, Qinghua Zhang and Yuyu Zhang
The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to…
Abstract
Purpose
The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.
Design/methodology/approach
This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.
Findings
According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.
Research limitations/implications
In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.
Originality/value
Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.
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Jianbin Luo, Mingsen Li, Ke Mi, Zhida Liang, Xiaofeng Chen, Lei Ye, Yuanhao Tie, Song Xu, Haiguo Zhang, Guiguang Chen and Chunmei Jiang
The purpose of this paper is to study the aerodynamic characteristics of Ahmed body in longitudinal and lateral platoons under crosswind by computational fluid dynamics…
Abstract
Purpose
The purpose of this paper is to study the aerodynamic characteristics of Ahmed body in longitudinal and lateral platoons under crosswind by computational fluid dynamics simulation. It helps to improve the aerodynamic characteristics of vehicles by providing theoretical basis and engineering direction for the development and progress of intelligent transportation.
Design/methodology/approach
A two-car platoon model is used to compare with the experiment to prove the accuracy of the simulation method. The simplified Ahmed body model and the Reynolds Averaged N-S equation method are used to study the aerodynamic characteristics of vehicles at different distances under cross-winds.
Findings
When the longitudinal distance x/L = 0.25, the drag coefficients of the middle and trailing cars at β = 30° are improved by about 272% and 160% compared with β = 10°. The side force coefficients of the middle and trailing cars are increased by 50% and 62%. When the lateral distance y/W = 0.25, the side force coefficients of left and middle cars at β = 30° are reduced by 38% and 37.5% compared with β = 10°. However, the side force coefficient of the right car are increased by about 84.3%.
Originality/value
Most of the researches focus on the overtaking process, and there are few researches on the neat lateral platoon. The innovation of this paper is that in addition to studying the aerodynamic characteristics of longitudinal driving, the aerodynamic characteristics of neat lateral driving are also studied, and crosswind conditions are added. The authors hope to contribute to the development of intelligent transportation.
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Wei Wang, Yongyong He, Yang Li, Bin Wei, Yutong Hu and Jianbin Luo
The purpose of this study is to investigate the inner flow field characteristics of groove textures in thrust bearings. Cavitation and vortex are studied simultaneously to enrich…
Abstract
Purpose
The purpose of this study is to investigate the inner flow field characteristics of groove textures in thrust bearings. Cavitation and vortex are studied simultaneously to enrich the theories of surface texture.
Design/methodology/approach
Navier–Stokes equations are solved using computational fluid dynamics. The MIXTURE model is adopted to study the gas–liquid mixture flow under the cavitation condition.
Findings
Re number, the depth ratio as well as the area ratio of the groove texture and the bottom shape are all influencing factors of the inner flow field characteristics. When cavitation region and vortex region occupy the bottom of the groove texture, these do not overlap because of the pressure gradient. The positive pressure gradient in the non-cavitation region introduces nonlinearity into the velocity profiles, which affects the load-carrying capacity and friction.
Originality/value
Cavitation and vortex are studied simultaneously only in this study. The characteristics of the textured thrust bearing can be analyzed and explained with the combined effect of cavitation and vortex.