Yuqin Wang, Bing Liang, Wen Ji, Shiwei Wang and Yiqiang Chen
In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors…
Abstract
Purpose
In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors, and learners all over the world can get access to these courses via the internet. However, faced with massive courses, learners often waste much time finding courses they like. This paper aims to explore the problem that how to make accurate personalized recommendations for MOOC users.
Design/methodology/approach
This paper proposes a multi-attribute weight algorithm based on collaborative filtering (CF) to select a recommendation set of courses for target MOOC users.
Findings
The recall of the proposed algorithm in this paper is higher than both the traditional CF and a CF-based algorithm – uncertain neighbors’ collaborative filtering recommendation algorithm. The higher the recall is, the more accurate the recommendation result is.
Originality/value
This paper reflects the target users’ preferences for the first time by calculating separately the weight of the attributes and the weight of attribute values of the courses.
Details
Keywords
Yonghong Jin, Meng Xu, Wei Wang and Yuqin Xi
The purpose of this paper is to discuss how venture capital institutions can use their syndicated investment network to help listed companies to achieve better performance in…
Abstract
Purpose
The purpose of this paper is to discuss how venture capital institutions can use their syndicated investment network to help listed companies to achieve better performance in mergers and acquisitions (M&A) activities.
Design/methodology/approach
This paper builds a fixed effect unbalanced panel regression model to study the impact of venture capital network on the M&A performance of listed companies.
Findings
Evidence indicated that the stronger the information resource acquisition ability of venture capital institutions in the network, the better the listed company's M&A performance supported; the stronger the information resource control ability of venture capital institutions in the network, the better the listed company's M&A performance supported; the higher the participation of venture capital institutions, the more significant the positive impact of information resource acquisition and information resource control abilities on M&A performance in the network.
Research limitations/implications
The data in this paper are from China's Growth Enterprise Market (GEM), other markets may be considered in the future research studies.
Practical implications
The research conclusions of this paper affirm the positive role played by venture capital institutions through syndicated investment in eliminating information asymmetry in M&A of invested companies. The information resource acquisition and control abilities and participation degree of the venture capital network have positively promoted the M&A performance of the invested enterprises.
Originality/value
The conclusions of this paper not only provide useful supplements to existing research literature on venture capital network functions and corporate M&A but also have certain guiding value for venture capital institutions and start-ups to better use venture capital practices to improve their capabilities and performance.
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Zilong Wang, JiaCheng Zhou, Fang Liu, Yuqin Wu and Nu Yan
The purpose of this paper is to study the microstructure and properties of Sn-3.5Ag and Sn-3.5Ag-0.5Sb lead-free solder alloys with and without a rotating magnetic field (RMF).
Abstract
Purpose
The purpose of this paper is to study the microstructure and properties of Sn-3.5Ag and Sn-3.5Ag-0.5Sb lead-free solder alloys with and without a rotating magnetic field (RMF).
Design/methodology/approach
Optical microscopy, scanning electron microscopy and X-ray diffraction were used to analyze the effect of an RMF on the microstructure of the solders. Differential scanning calorimetry was used to study the influence of the RMF on the thermal characteristics of the solders. The mechanical properties of the alloys were determined by tensile measurements at different strain rates.
Findings
The ß-Sn grains and intermetallic compounds for the Sn-3.5Ag and Sn-3.5Ag-0.5Sb lead-free solder alloys were refined under an RMF, and the morphology of the ß-Sn grains changed from dendritic to equiaxed. The pasty range was significantly reduced under an RMF. The ultimate tensile strength (UTS) of Sn-3.5Ag improved under the RMF, whereas the UTS of Sn-3.5Ag-0.5Sb decreased slightly. The addition of Sb to the Sn-3.5Ag alloy significantly enhanced the UTS and elongation (El.%) of the samples. The UTS of the solder increased with increasing strain rate.
Originality/value
The results revealed that the application of RMF in the molten alloy had a significant effect on its microstructure and mechanical properties. The thermal characteristics of the Sn-3.5Ag and Sn-3.5Ag-0.5Sb solder alloys were improved under the RMF. This research is expected to fill a knowledge gap regarding the behaviour of Sn-Ag solder alloys under RMF.
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Keywords
Fang Liu, Zilong Wang, JiaCheng Zhou, Yuqin Wu and Zhen Wang
The purpose of this study is to investigate the effects of Ce and Sb doping on the microstructure and thermal mechanical properties of Sn-1.0Ag-0.5Cu lead-free solder. The effects…
Abstract
Purpose
The purpose of this study is to investigate the effects of Ce and Sb doping on the microstructure and thermal mechanical properties of Sn-1.0Ag-0.5Cu lead-free solder. The effects of 0.5%Sb and 0.07%Ce doping on microstructure, thermal properties and mechanical properties of Sn-1.0Ag-0.5Cu lead-free solder were investigated.
Design/methodology/approach
According to the mass ratio, the solder alloys were prepared from tin ingot, antimony ingot, silver ingot and copper ingot with purity of 99.99% at 400°C. X-ray diffractometer was adopted for phase analysis of the alloys. Optical microscopy, scanning electron microscopy and energy dispersive spectrometer were used to study the effect of the Sb and Ce doping on the microstructure of the solder. Then, the thermal characteristics of alloys were characterized by a differential scanning calorimeter (DSC). Finally, the ultimate tensile strength (UTS), elongation (EL.%) and yield strength (YS) of solder alloys were measured by tensile testing machine.
Findings
With the addition of Sb and Ce, the ß-Sn and intermetallic compounds of solders were refined and distributed more evenly. With the addition of Sb, the UTS, EL.% and YS of Sn-1.0Ag-0.5Cu increased by 15.3%, 46.8% and 16.5%, respectively. The EL.% of Sn-1.0Ag-0.5Cu increased by 56.5% due to Ce doping. When both Sb and Ce elements are added, the EL.% of Sn-1.0Ag-0.5Cu increased by 93.3%.
Originality/value
The addition of 0.5% Sb and 0.07% Ce can obtain better comprehensive performance, which provides a helpful reference for the development of Sn-Ag-Cu lead-free solder.
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Lei Wang, Xinming Wang, Liang Li, Chuang Yang and Yuqin Zhu
With respect to severe working conditions such as heavy load and impact, this paper aims to investigate the friction reduction and anti-wear performance of kaolin and molybdenum…
Abstract
Purpose
With respect to severe working conditions such as heavy load and impact, this paper aims to investigate the friction reduction and anti-wear performance of kaolin and molybdenum dialkyl dithiophosphate (MoDDP) composite lubricant additives to improve the lubrication effect of a single additive.
Design/methodology/approach
A four-ball friction test was carried out to determine the optimal concentration of kaolin and organic molybdenum additives and the tribological properties of the kaolin/MoDDP composite lubricant additives. A ring block test of composite lubricant additives was designed to investigate its lubrication performance under the severe working conditions of low speed, heavy load and impact.
Findings
The results showed that the optimal addition mass fractions of kaolin and MoDDP were 4.0 and 1.5 Wt.%, respectively, when kaolin and MoDDP were used as single lubricant additives. Compared with the single additive, the 4.0 Wt.% kaolin/1.5 Wt.% MoDDP composite lubricant additive showed excellent friction reduction and anti-wear effects under heavy load and impact conditions. Physicochemical analysis of the wear surface revealed that the lamellar kaolin additive and MoDDP had excellent synergistic effects, and the friction process promoted the generation of lubricant films containing a chemically reactive layer of MoS2, MoO2, FeS2 and Fe2O3 and a physically adsorbent layer containing SiO2 and Al2O3, which play important roles in anti-wear and friction reduction.
Originality/value
The excellent friction reduction and anti-wear effects of lamellar silicate minerals and the excellent antioxidant properties and good synergistic effects of molybdenum were comprehensively used to develop the composite additives with great lubricating properties.
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Keywords
Wei Feng, Yuqin Wu and Yexian Fan
The purpose of this paper is to solve the shortage of the existing methods for the prediction of network security situations (NSS). Because the conventional methods for the…
Abstract
Purpose
The purpose of this paper is to solve the shortage of the existing methods for the prediction of network security situations (NSS). Because the conventional methods for the prediction of NSS, such as support vector machine, particle swarm optimization, etc., lack accuracy, robustness and efficiency, in this study, the authors propose a new method for the prediction of NSS based on recurrent neural network (RNN) with gated recurrent unit.
Design/methodology/approach
This method extracts internal and external information features from the original time-series network data for the first time. Then, the extracted features are applied to the deep RNN model for training and validation. After iteration and optimization, the accuracy of predictions of NSS will be obtained by the well-trained model, and the model is robust for the unstable network data.
Findings
Experiments on bench marked data set show that the proposed method obtains more accurate and robust prediction results than conventional models. Although the deep RNN models need more time consumption for training, they guarantee the accuracy and robustness of prediction in return for validation.
Originality/value
In the prediction of NSS time-series data, the proposed internal and external information features are well described the original data, and the employment of deep RNN model will outperform the state-of-the-arts models.
Details
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Libiao Bai, Shiyi Liu, Yuqin An and Qi Xie
Project portfolio benefit (PPB) evaluation is crucial for project portfolio management decisions. However, PPB is complex in composition and affected by synergy and ambidexterity…
Abstract
Purpose
Project portfolio benefit (PPB) evaluation is crucial for project portfolio management decisions. However, PPB is complex in composition and affected by synergy and ambidexterity. Ignoring these characteristics can result in inaccurate assessments, impeding the management and optimization of benefit. Considering the above complexity of PPB evaluation, this study aims to propose a refined PPB evaluation model to provide decision support for organizations.
Design/methodology/approach
A back propagation neural network optimized via genetic algorithm and pruning algorithm (P-GA-BPNN) is constructed for PPB evaluation. First, the benefit evaluation criteria are established. Second, the inputs and expected outputs for model training and testing are determined. Then, based on the optimization of BPNN via genetic algorithm and pruning algorithm, a PPB evaluation model is constructed considering the impacts of ambidexterity and synergy on PPB. Finally, a numerical example was applied to validate the model.
Findings
The results indicate that the proposed model can be used for effective PPB evaluation. Moreover, it shows superiority in terms of MSE and fitting effect through extensive comparative experiments with BPNN, GA-BPNN, and SVM models. The robustness of the model is also demonstrated via data random disturbance experiment and 10-cross-validation. Therefore, the proposed model could serve as a valuable decision-making tool for PPB management.
Originality/value
This study extends prior research by integrating the impacts of synergy and ambidexterity on PPB when conducting PPB evaluation, which facilitates to manage and enhance PPB. Besides, the structural redundancy of existing assessment methods is solved through the dynamic optimization of the network structure via the pruning algorithm, enhancing the effectiveness of PPB decision-making tools.
Details
Keywords
Xianmiao Li, Zhenting Xu and Yuqin Hu
This study aims to explore the dual-path effects of challenge (CTP) and hindrance time pressure (HTP) on knowledge sharing, which provides theoretical reference for knowledge…
Abstract
Purpose
This study aims to explore the dual-path effects of challenge (CTP) and hindrance time pressure (HTP) on knowledge sharing, which provides theoretical reference for knowledge teams to carry out knowledge sharing smoothly.
Design/methodology/approach
This study collected two waves of data and surveyed 416 employees in China. Regression analysis, bootstrapping and structure equitation modeling was adopted to test the hypotheses.
Findings
CTP has a positive impact on employee knowledge sharing, while HTP has a negative impact on employee knowledge sharing. Self-efficacy plays a mediating role between CTP and knowledge sharing, and emotional exhaustion plays a mediating role between HTP and knowledge sharing. The perceived organizational support can moderate the relationship between CTP and self-efficacy and between HTP and emotional exhaustion.
Originality/value
This study explains the reasons for the academic controversy about the effect of time pressure, enhances the scholars’ attention and understanding of the dual-path mechanism between time pressure and knowledge sharing and augments the theoretical research of time pressure and knowledge sharing.
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This paper aims to study the contact between rough cylindrical surfaces considering the elastic-plastic deformation of asperities.
Abstract
Purpose
This paper aims to study the contact between rough cylindrical surfaces considering the elastic-plastic deformation of asperities.
Design/methodology/approach
The elastic deformation of the nominal surface of the curved surface is considered, the contact area is discretized by the calculus thought and then the nominal distance between two surfaces is obtained by iteration after the pressure distribution is assumed. On the basis of the Zhao, Maietta and Chang elastic-plastic model, the contact area and the contact pressure of the rough cylindrical surfaces are calculated by the integral method, and then the solution for the contact between rough cylindrical surfaces is obtained.
Findings
The contact characteristic parameters of smooth surface Hertz contact, elastic contact and elastic-plastic contact between rough cylindrical surfaces are calculated under different plastic indexes and loads, and the calculation results are compared and analyzed. The analysis shows that the solution considering the elastic-plastic deformation of asperities for the contact between rough cylindrical surfaces is scientific and rational.
Originality/value
This paper provides a new effective method for the calculation of the contact between rough cylindrical surfaces.
Details
Keywords
Fei Sun, Haisang Liu, Yuqin Din, Honglian Cong and Zhijia Dong
The purpose of this research is to propose a flexible sensor with a weft-knitted float stitch structure and to explore knitting techniques that allow conductive yarns to be…
Abstract
Purpose
The purpose of this research is to propose a flexible sensor with a weft-knitted float stitch structure and to explore knitting techniques that allow conductive yarns to be skin-tight and less exposed, reducing production processes and increasing productivity. Study its electrical conductivity in different yarn materials, knit processes and deformation ranges. The analysis is compared to provide some basis for the design of the electrodes.
Design/methodology/approach
The method includes five operations: (1) Analysis of the morphological appearance, tensile variation, fiber material properties and electrical conductivity of high-elastic and filament silver-plated conductive yarns. (2) Based on the knitting process of the floating yarn structure, three-dimensional modeling of the flexible sensor was carried out to explore the influence of knitting process changes on appearance characteristics. (3) The fabric samples are knitted by different silver-plated conductive yarns with different structures. Processing of experimental samples to finished size by advance shrinkage. (4) Measure the resistance of the experimental sample after the machine has been lowered and after pre-shrinking. Use the stretching machine to simulate a wearing experiment and measure the change in resistance of the sample in the 0–15% stretching range. (5) Analyze the influence factors on the conductive performance of the flexible sensor to determine whether it is suitable for textile flexible sensors.
Findings
For the float knitted flexible sensors, the floating wire projection is influenced by the elasticity of the fabric and the length of the floating wire. Compared to the plain knitted flexible sensors, it has less resistance variation and better electrical properties, making it suitable for making electrodes for textile structures. In addition, the knitting method is integrated with the intelligent monitoring clothing, which saves the process for the integration of the flexible sensor, realizes positioning and fixed-point knitting.
Practical implications
The sensor technology of the designed weft-knitted float structure is varied and can be freely combined and designed in a wide range. Within the good electrical conductivity, the flexible sensor can realize integrated knitting, positioning monitoring, integrating into the appearance of clothing. It can also focus on the wearing experience of wearable products so that the appearance of the monitoring clothing is close to the clothes we wear in our daily life.
Originality/value
In this paper, an integrated positioning knitting flexible sensor based on the weft knitting float structure is studied. The improved knitting process allows the sensing contact surface to be close to the skin and reduces the integration process. The relationship between the exposure of the silver-plated yarn on the clothing surface and the electrical conductivity is analyzed. Within a certain conductive performance, reduces the exposed area of the conductive yarn on the clothing surface and proposes a design reference for the flexible sensor appearance.