Xiaohua Shi, Kaicheng Tang and Hongtao Lu
Book sorting system is one of specific application in smart library scenarios, and it now has been widely used in most libraries based on RFID (radio-frequency identification…
Abstract
Purpose
Book sorting system is one of specific application in smart library scenarios, and it now has been widely used in most libraries based on RFID (radio-frequency identification devices) technology. Book identification processing is one of the core parts of a book sorting system, and the efficiency and accuracy of book identification are extremely critical to all libraries. In this paper, the authors propose a new image recognition method to identify books in libraries based on barcode decoding together with deep learning optical character recognition (OCR) and describe its application in library book identification processing.
Design/methodology/approach
The identification process relies on recognition of the images or videos of the book cover moving on a conveyor belt. Barcode is printed on or attached to the surface of each book. Deep learning OCR program is applied to improve the accuracy of recognition, especially when the barcode is blurred or faded. The approach the authors proposed is robust with high accuracy and good performance, even though input pictures are not in high resolution and the book covers are not always vertical.
Findings
The proposed method with deep learning OCR achieves best accuracy in different vertical, skewed and blurred image conditions.
Research limitations/implications
Methods that the authors proposed need to cooperate and practice in different book sorting machine.
Social implications
The authors collected more than 500 books from a library. These photos display the cover of more than 100 randomly picked books with backgrounds in different colors, each of which has about five different pictures captured from variety angles. The proposed method combines traditional barcode identification algorithm with the authors’ modification to locate and deskew the image. And deep learning OCR is involved to enhance the accuracy when the barcode is blurred or partly faded. Book sorting system design based on this method will also be introduced.
Originality/value
Experiment demonstrates that the accuracy of the proposed method is high in real-time test and achieves good accuracy even when the barcode is blurred. Deep learning is very effective in analyzing image content, and a corresponding series of methods have been formed in video content understanding, which can be a greater advantage and play a role in the application scene of intelligent library.
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Xiaohua Shi, Chen Hao, Ding Yue and Hongtao Lu
Traditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of…
Abstract
Purpose
Traditional library book recommendation methods are mainly based on association rules and user profiles. They may help to learn about students' interest in different types of books, e.g., students majoring in science and engineering tend to pay more attention to computer books. Nevertheless, most of them still need to identify users' interests accurately. To solve the problem, the authors propose a novel embedding-driven model called InFo, which refers to users' intrinsic interests and academic preferences to provide personalized library book recommendations.
Design/methodology/approach
The authors analyze the characteristics and challenges in real library book recommendations and then propose a method considering feature interactions. Specifically, the authors leverage the attention unit to extract students' preferences for different categories of books from their borrowing history, after which we feed the unit into the Factorization Machine with other context-aware features to learn students' hybrid interests. The authors employ a convolution neural network to extract high-order correlations among feature maps which are obtained by the outer product between feature embeddings.
Findings
The authors evaluate the model by conducting experiments on a real-world dataset in one university. The results show that the model outperforms other state-of-the-art methods in terms of two metrics called Recall and NDCG.
Research limitations/implications
It requires a specific data size to prevent overfitting during model training, and the proposed method may face the user/item cold-start challenge.
Practical implications
The embedding-driven book recommendation model could be applied in real libraries to provide valuable recommendations based on readers' preferences.
Originality/value
The proposed method is a practical embedding-driven model that accurately captures diverse user preferences.
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Junwei Zheng, Yu Gu, Lan Luo, Yunhua Zhang, Hongtao Xie and Kai Chang
Project complexity is a critical issue that has increasingly attracted attention in both academic and practical circles. However, there are still many gaps in the research on…
Abstract
Purpose
Project complexity is a critical issue that has increasingly attracted attention in both academic and practical circles. However, there are still many gaps in the research on project complexity, such as the differentiated conceptualization of complexity and disjointed operationalization in the measurements. Therefore, this paper aims to conduct a systematic and detailed literature review on the concept, dimensions, assessment, and underlying mechanisms of project complexity.
Design/methodology/approach
A systematic literature review methodology was applied to search and synthesize the research on project complexity, and a final sample of 74 journal articles was identified.
Findings
This study first summarizes the concepts of project complexity from three different theoretical perspectives, and then identifies different approaches of measurement, evaluation, or simulation to assess project complexity. This paper finally establishes an integrative framework to synthesize the antecedents, mediators and moderators, and outcomes of project complexity, generating four suggestions for future research.
Originality/value
This study summarizes the definition and operationalization of project complexity to reduce the discrepancies in the existing research and offers an integrative framework to offer a broad overview of the current understanding of project complexity, providing a potential way forward for addressing project complexity.
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Jayanti Bandyopadhyay, Hongtao Guo, Miranda Lam and Jinying Liu
We obtained information on China Gerui from secondary published sources, including annual reports downloaded from the Securities and Exchange Commission’s (SEC) EDGAR database…
Abstract
Research methodology
We obtained information on China Gerui from secondary published sources, including annual reports downloaded from the Securities and Exchange Commission’s (SEC) EDGAR database, news sites and newspapers, the company’s website and journal articles. One of the authors visited the China Gerui plant in Henan, China.
Case overview/synopsis
China Gerui, a Chinese metal fabrication company, enjoyed exponential growth because of its location, product innovation and ability to move up the value chain. At the height of its success, the company listed on the Nasdaq and had plans to raise capital to fund ambitious expansion plans. Unfortunately, four years after listing on Nasdaq, the company received a letter from the listing qualifications department notifying China Gerui that they were not in compliance with Nasdaq’s filing requirements because it had not filed its Form 20-F. Now, the company had only five days to decide whether to request an appeal of the letter.
Complexity academic level
This case is best suited for higher-level undergraduate accounting and finance courses such as intermediate accounting, auditing, international accounting, financial statement analysis, corporate finance and investments analysis. It is especially appropriate for graduate-level global accounting and advanced financial statement analysis courses. In these courses, the best placement is after coverage of SEC regulations and requirements for financial statement reporting and disclosure. Moreover, the case may be used as a tool to demonstrate the step-by-step process for searching and retrieving information from a public company’s filings through the SEC’s EDGAR database.
Supplementary materials
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Yanqiu Xia, Wenhao Chen, Yi Zhang, Kuo Yang and Hongtao Yang
The purpose of this study is to investigate the effectiveness of a composite lubrication system combining polytetrafluoroethylene (PTFE) film and oil lubrication in steel–steel…
Abstract
Purpose
The purpose of this study is to investigate the effectiveness of a composite lubrication system combining polytetrafluoroethylene (PTFE) film and oil lubrication in steel–steel friction pairs.
Design/methodology/approach
A PTFE layer was sintered on the surface of a steel disk, and a lubricant with additives was applied to the surface of the steel disk. A friction and wear tester was used to evaluate the tribological properties and insulation capacity. Fourier transform infrared spectrometer was used to analyze the changes in the composition of the lubricant, and X-ray photoelectron spectroscopy was used to analyze the chemical composition of the worn surface.
Findings
It was found that incorporating the PTFE film with PSAIL 2280 significantly enhanced both the friction reduction and insulation capabilities at the electrical contact interface during sliding. The system consistently achieved ultra-low friction coefficients (COF < 0.01) under loads of 2–4 N and elucidated the underlying lubrication mechanisms.
Originality/value
This work not only confirm the potential of PTFE films in insulating electrical contact lubrication but also offer a viable approach for maintaining efficient and stable low-friction wear conditions.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0222/
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Hong Jiang, Hongtao Xu, Shukuan Zhao and Yong Chen
Internet of Things (IoT), a strategic emerging industry, has brought a new driving force to the global economic growth, as well as an effective solution to break the barrier of…
Abstract
Purpose
Internet of Things (IoT), a strategic emerging industry, has brought a new driving force to the global economic growth, as well as an effective solution to break the barrier of economic development. However, standards system of IoT is not yet mature, existing obvious overlapping and even conflicting standards, and enterprises lack mature technology standardization model, which severely restricts the structural upgrading and development of IoT. The paper aims to discuss these issues.
Design/methodology/approach
In this regard, this study combs the research context of the IoT, technology standardization and competition behavior, and analyze technology standardization models of IoT by combining theory with practice. Using game theory and profit function, this paper analyzes the selection mechanism of standardization model of IoT enterprises, and explores practical application of these models using competitive behavior theory.
Findings
First, in the process of standardization, technology standardization model n enterprises is not single, nor is it immutable. Second, the trend of internationalization of technical standards is becoming more and more obvious. Third, if LoT enterprises want to achieve their own technology standardization, the corresponding competitive behavior is essential. Fourth, with the change of innovation capability and market forces, the competitive behavior of enterprises should be improved accordingly to better adapt to the changes of internal and external environment and ensure the realization of the standardization of enterprises. Fifth, if IoT attempts to achieve the same globalization as the internet, there must be a set of support systems.
Originality/value
Finally, some suggestions are given for the future development in the field of IoT. This study will provide some theoretical support for promoting the development of standards and enhancing the competitiveness of IoT enterprises.
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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…
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.
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Hongtao Liu and Jin Shang
The purpose of this paper is to use an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015.
Abstract
Purpose
The purpose of this paper is to use an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015.
Design/methodology/approach
This paper uses an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO2 emissions is also presented.
Findings
The results suggest that the amount of CO2 emissions related to fixed asset investments increased during the entire period. The social and economic effect played a major role in promoting carbon emissions, followed by the fixed asset effect. Therefore, the activity factor was the dominant positive factor, followed by the construction factor. The negative element was the energy effect, in which the energy intensity factor played an important role in reducing emissions, followed by the structural factor. Moreover, the carbon intensity factor might be a potential inhibitory force in reducing carbon emissions.
Research/limitations/implications
A steady financial policy, relaxed family planning, sustainable urbanization, strategy of innovation-driven development, reform of scientific and technological structures, development of science and technology and exploration of new energy sources are proposed to mitigate carbon emissions from fixed asset investments. The conclusion also provides a reference for developing countries in similar situations.
Originality/value
This paper uses an index decomposition analysis to investigate the driving forces of China’s CO2 emissions related to fixed asset investments from 2003 to 2015. To make policy recommendations, this paper identifies three effects. An approach to calculating energy-relevant CO2 emissions is also presented.
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Ye Liu and Changjiang Lyu
The performance of the first batch of listed companies since the restart of new initial public offerings (IPOs) in January 2014 and their accounting information face repeated and…
Abstract
Purpose
The performance of the first batch of listed companies since the restart of new initial public offerings (IPOs) in January 2014 and their accounting information face repeated and volatile questioning from different sides. This paper aims to take Guirenniao (China) Co. Ltd. (GRN for short), one of the first batch of listed companies in 2014 that suffered performance decline, as an example to analyze how it managed earnings before IPO.
Design/methodology/approach
This paper examines earnings management signs that exist in GRN through analysis of its financial statements compared to those of its industry peers. This paper then uses the modified Jones model to detect its accrual earnings management and build three models, which are abnormal levels of cash flows from operations, abnormal production costs and abnormal discretionary expenses, to detect real earnings management.
Findings
This paper finds that GRN managed earnings through accrual and real activities in 2012 and 2013. Finally, this paper provides evidence on the specific methods of earnings management, which are easing credit policy to recognize revenue in advance, abnormal expansion, decreasing costs and connected transactions.
Originality/value
This paper examines earnings management signs exist in GRN through analysis of its financial statements comparing to those of its industry peers. This paper then uses the modified Jones Model to detect its accrual earnings management and build three models which are abnormal levels of cash flows from operations, abnormal production costs and abnormal discretionary expenses to detect real earnings management.
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Md Jahidur Rahman, Hongtao Zhu and Sihe Chen
This study aims to investigate the relationship between corporate social responsibility (CSR) and financial distress and the moderating effect of firm characteristics, auditor…
Abstract
Purpose
This study aims to investigate the relationship between corporate social responsibility (CSR) and financial distress and the moderating effect of firm characteristics, auditor characteristics and the Coronavirus disease 2019 (Covid-19) in China.
Design/methodology/approach
The research question is empirically examined on the basis of a data set of 1,257 Chinese-listed firms from 2011 to 2021. The dependent variable is financial distress risk, which is measured mainly by Z-score. CSR score is used as a proxy for CSR. Propensity score matching, two-stage least square and generalized method of moments are adopted to mitigate the potential endogeneity issue.
Findings
This study reveals that CSR can reduce financial distress. Specifically, results show an inverse relationship between CSR and financial distress, more significantly in non-state-owned enterprises, firms with non-BigN auditor and during Covid-19. The results are consistent and robust to endogeneity tests and sensitivity analyses.
Originality/value
This study enriches the literature on CSR and financial distress, resulting in a more attractive corporate environment, improved financial stability and more crisis-resistant economies in China.