Search results

1 – 10 of 137
Open Access
Article
Publication date: 4 September 2017

Yuanxing Zhang, Zhuqi Li, Kaigui Bian, Yichong Bai, Zhi Yang and Xiaoming Li

Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain…

Abstract

Purpose

Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN) apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks.

Design/methodology/approach

In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions.

Findings

By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time.

Originality/value

This paper tries to project population distribution by modeling geo-homophily in OSNs.

Details

International Journal of Crowd Science, vol. 1 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 6 March 2017

Zhuoxuan Jiang, Chunyan Miao and Xiaoming Li

Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by…

2155

Abstract

Purpose

Recent years have witnessed the rapid development of massive open online courses (MOOCs). With more and more courses being produced by instructors and being participated by learners all over the world, unprecedented massive educational resources are aggregated. The educational resources include videos, subtitles, lecture notes, quizzes, etc., on the teaching side, and forum contents, Wiki, log of learning behavior, log of homework, etc., on the learning side. However, the data are both unstructured and diverse. To facilitate knowledge management and mining on MOOCs, extracting keywords from the resources is important. This paper aims to adapt the state-of-the-art techniques to MOOC settings and evaluate the effectiveness on real data. In terms of practice, this paper also tries to answer the questions for the first time that to what extend can the MOOC resources support keyword extraction models, and how many human efforts are required to make the models work well.

Design/methodology/approach

Based on which side generates the data, i.e instructors or learners, the data are classified to teaching resources and learning resources, respectively. The approach used on teaching resources is based on machine learning models with labels, while the approach used on learning resources is based on graph model without labels.

Findings

From the teaching resources, the methods used by the authors can accurately extract keywords with only 10 per cent labeled data. The authors find a characteristic of the data that the resources of various forms, e.g. subtitles and PPTs, should be separately considered because they have the different model ability. From the learning resources, the keywords extracted from MOOC forums are not as domain-specific as those extracted from teaching resources, but they can reflect the topics which are lively discussed in forums. Then instructors can get feedback from the indication. The authors implement two applications with the extracted keywords: generating concept map and generating learning path. The visual demos show they have the potential to improve learning efficiency when they are integrated into a real MOOC platform.

Research limitations/implications

Conducting keyword extraction on MOOC resources is quite difficult because teaching resources are hard to be obtained due to copyrights. Also, getting labeled data is tough because usually expertise of the corresponding domain is required.

Practical implications

The experiment results support that MOOC resources are good enough for building models of keyword extraction, and an acceptable balance between human efforts and model accuracy can be achieved.

Originality/value

This paper presents a pioneer study on keyword extraction on MOOC resources and obtains some new findings.

Details

International Journal of Crowd Science, vol. 1 no. 1
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 3 June 2022

XiYue Deng, Xiaoming Li, Zhenzhen Chen, Mengli Zhu, Naixue Xiong and Li Shen

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points…

809

Abstract

Purpose

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points to construct urban security risk indicators. This paper combines traffic data and urban alarm data to analyze the safe travel characteristics of the urban population. The research results are helpful to explore the diversity of human group behavior, grasp the temporal and spatial laws and reveal regional security risks. It provides a reference for optimizing resource deployment and group intelligence analysis in emergency management.

Design/methodology/approach

Based on the dynamics index of group behavior, this paper mines the data of large shared bikes and ride-hailing in a big city of China. We integrate the urban interest points and travel dynamic characteristics, construct the urban traffic safety index based on alarm behavior and further calculate the urban safety index.

Findings

This study found significant differences in the travel power index among ride-sharing users. There is a positive correlation between user shared bike trips and the power-law bimodal phenomenon in the logarithmic coordinate system. It is closely related to the urban public security index.

Originality/value

Based on group-shared dynamic index integrated alarm, we innovatively constructed an urban public safety index and analyzed the correlation of travel alarm behavior. The research results fully reveal the internal mechanism of the group behavior safety index and provide a valuable supplement for the police intelligence analysis.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 30 April 2020

Conghu Wang, Yuhua Qiao and Xiaoming Li

This paper aims to identify important factors in green public procurement (GPP) implementation and then to clarify how these factors affect GPP implementation.

Abstract

Purpose

This paper aims to identify important factors in green public procurement (GPP) implementation and then to clarify how these factors affect GPP implementation.

Design/methodology/approach

The authors applied the Delphi method first and then conducted a focused and constrained multiple case study at 18 government procurement centers across China.

Findings

The authors identified four clusters of factors for successful GPP implementation: more clear, consistent and operational policy goals; a nation-wide green procurement campaign to enhance social capital and cultural resources; promoting staff’s ethics, professionalism, capacity and knowledge; and establishing checks and balances among organizations involved in the whole purchasing process.

Social implications

GPP can significantly improve environmental protection and sustainable development.

Originality/value

Based on key insights from systems theory and agency theory, the authors emphasize that GPP implementation must take down its own functional silos and adopt a process approach across organizational tiers to synchronize human resource based and inter-organizational capabilities into a unified whole through information sharing, communications and collaboration.

Details

Journal of Public Procurement, vol. 20 no. 3
Type: Research Article
ISSN: 1535-0118

Keywords

Article
Publication date: 1 March 2021

Xiaoyan Zhang, Runtian Wang, Yingyu Zhao, Jun Zhang, Boyuan Zhang, Zhengcan Chen, Pu Liu, Zhenbin Chen, Chunli Liu and Xiaoming Li

This paper aims to evaluate the separation and purification characteristics of flavonoids from polygonum cuspidatum (PC) extracts by using macroporous adsorption resins (MAR…

Abstract

Purpose

This paper aims to evaluate the separation and purification characteristics of flavonoids from polygonum cuspidatum (PC) extracts by using macroporous adsorption resins (MAR) mixed bed to improve the utilization rate of flavonoids.

Design/methodology/approach

Taking the separation performance of flavonoids as an evaluation index, the best MAR were screened from 31 sorts of MAR and combined the best MAR to form a MAR mixed bed for adsorption and separation of flavonoids.

Findings

By studying the separation conditions that affect flavonoids, the results showed that resin LZ-72 has best separation and purification effect on flavonoids under the optimal adsorption and desorption conditions, the purity of the obtained flavonoid compound reaches 82.50%, 2.66 times of the initial extract, and the recovery rate reaches 89.70%. Theoretical research results have shown that the adsorption of flavonoids by MAR conforms to the pseudo-second-order kinetics and Freundlich models.

Practical implications

Because the flavonoids in PC have great medicinal value, the purpose of this work is to develop a method of separating and purifying flavonoids from PC, which will provide a certain foundation for the development of medicine.

Originality/value

This contribution provided a novel way to separate flavonoids from PC. Under the optimal conditions, the content of flavonoids in the product was increased 2.66-fold from 31.01% to 82.50%, and the recovery yield was 89.70%.

Details

Pigment & Resin Technology, vol. 50 no. 6
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 12 July 2024

Zhiqiang Zhang, Xiaoming Li, Xinyi Xu, Chengjie Lu, Yihe Yang and Zhiyong Shi

The purpose of this study is to explore the potential of trainable activation functions to enhance the performance of deep neural networks, specifically ResNet architectures, in…

Abstract

Purpose

The purpose of this study is to explore the potential of trainable activation functions to enhance the performance of deep neural networks, specifically ResNet architectures, in the task of image classification. By introducing activation functions that adapt during training, the authors aim to determine whether such flexibility can lead to improved learning outcomes and generalization capabilities compared to static activation functions like ReLU. This research seeks to provide insights into how dynamic nonlinearities might influence deep learning models' efficiency and accuracy in handling complex image data sets.

Design/methodology/approach

This research integrates three novel trainable activation functions – CosLU, DELU and ReLUN – into various ResNet-n architectures, where “n” denotes the number of convolutional layers. Using CIFAR-10 and CIFAR-100 data sets, the authors conducted a comparative study to assess the impact of these functions on image classification accuracy. The approach included modifying the traditional ResNet models by replacing their static activation functions with the trainable variants, allowing for dynamic adaptation during training. The performance was evaluated based on accuracy metrics and loss profiles across different network depths.

Findings

The findings indicate that trainable activation functions, particularly CosLU, can significantly enhance the performance of deep learning models, outperforming the traditional ReLU in deeper network configurations on the CIFAR-10 data set. CosLU showed the highest improvement in accuracy, whereas DELU and ReLUN offered varying levels of performance enhancements. These functions also demonstrated potential in reducing overfitting and improving model generalization across more complex data sets like CIFAR-100, suggesting that the adaptability of activation functions plays a crucial role in the training dynamics of deep neural networks.

Originality/value

This study contributes to the field of deep learning by introducing and evaluating the impact of three novel trainable activation functions within widely used ResNet architectures. Unlike previous works that primarily focused on static activation functions, this research demonstrates that incorporating trainable nonlinearities can lead to significant improvements in model performance and adaptability. The introduction of CosLU, DELU and ReLUN provides a new pathway for enhancing the flexibility and efficiency of neural networks, potentially setting a new standard for future deep learning applications in image classification and beyond.

Details

International Journal of Web Information Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 28 September 2010

Festus O. Olorunniwo and Xiaoming Li

The purpose of this study is to investigate how the use of information technology (IT) and supply chain management initiatives (information sharing and collaboration) impact a…

6357

Abstract

Purpose

The purpose of this study is to investigate how the use of information technology (IT) and supply chain management initiatives (information sharing and collaboration) impact a company's performance in reverse logistics (RL).

Design/methodology/approach

A survey based on a previous exploratory research and literature review was sent out to 600 US companies having substantial activities in RL. Issues addressed in the survey, such as IT types deployed, IT operational attributes, information sharing, and collaboration, involve multiple parties in multi‐tier RL networks, extending beyond a simple buyer‐supplier dyad.

Findings

The results revealed that the type of IT used per se did not have a differential impact on a company's performance in RL. However, IT operational attributes positively affected RL performance and information sharing and collaboration are critical to RL performance.

Practical implications

Investment in IT alone cannot improve a company's performance; managers should take full account of IT attributes when deciding IT in RL. IT operational attributes tend to support one another – an improvement in one would lead to improvements in the others. With no exception in RL, companies need to share information and collaborate with their partners.

Originality/value

The paper reports an empirical survey of the IT use and collaboration practices in RL, and provides insights into the relationships and impacts of IT, RL operational attributes, information sharing, and collaboration on one another as well as on RL performance.

Details

Supply Chain Management: An International Journal, vol. 15 no. 6
Type: Research Article
ISSN: 1359-8546

Keywords

Content available
Article
Publication date: 1 November 2000

Xiaoming Li

542

Abstract

Details

International Journal of Social Economics, vol. 27 no. 11
Type: Research Article
ISSN: 0306-8293

Keywords

Article
Publication date: 22 February 2008

Liying Zhang, Xiaoming Li, Rong Mao, Bonita Stanton, Qun Zhao, Bo Wang and Ambika Mathur

The purpose of this paper is to show that HIV/AIDS‐related stigma has persisted world‐wide for decades. However, studies on the linkage between stigmatizing attitudes towards…

1704

Abstract

Purpose

The purpose of this paper is to show that HIV/AIDS‐related stigma has persisted world‐wide for decades. However, studies on the linkage between stigmatizing attitudes towards people living with HIV/AIDS (PLWHA) and misconceptions about HIV transmission routes in the general population, especially among youth in China, are sparse – a gap this study is intended to fill.

Design/methodology/approach

Cross‐sectional data from 1,839 students from 19 colleges were collected by trained interviewers using a structured questionnaire in Jiangsu province of China.

Findings

This study reveals that there is a high proportion of college students having both stigmatizing attitudes toward PLWHA and misconceptions about HIV/AIDS transmission routes. Multilevel logistic regression analysis results show that having stigmatizing attitudes towards PLWHA is positively associated with having misconceptions about HIV transmission routes. Participants with high misconception scores were more likely to possess stigmatizing attitudes towards PLWHA.

Originality/value

To reduce stigmatizing attitudes towards PLWHA, HIV/AIDS education should be strengthened among the general population, especially among youth.

Details

Health Education, vol. 108 no. 2
Type: Research Article
ISSN: 0965-4283

Keywords

Article
Publication date: 8 August 2008

Xiaoming Li and Festus Olorunniwo

This paper seeks to report a case study that focuses on identifying what may be considered a typical or generic RL process flow as well as the key strategic issues that a firm may…

5927

Abstract

Purpose

This paper seeks to report a case study that focuses on identifying what may be considered a typical or generic RL process flow as well as the key strategic issues that a firm may use for competitive advantage.

Design/methodology/approach

The research involves mainly interviews and plant visits to three companies, all of which manage some RL activities.

Findings

Highlighted are what type of RL process flow can be considered as generic, the type of technology innovation and IT a firm needs in order to operate an effective RL system and how these are integrated across the supply chain, the resource commitment (personnel, financial, upper‐level management) that a company needs to make to support successful RL efforts, and finally, the values firms derive from RL and the key performance indicators to measure these values for the RL operations.

Originality/value

A typical returns flow process is provided that can guide managers efficiently on their RL activities. Strategic activities are also presented that characterize successful practices in the RL industry.

Details

Supply Chain Management: An International Journal, vol. 13 no. 5
Type: Research Article
ISSN: 1359-8546

Keywords

1 – 10 of 137