Xiwang Xiang, Xin Ma, Minda Ma, Wenqing Wu and Lang Yu
PM10 is one of the most dangerous air pollutants which is harmful to the ecological system and human health. Accurate forecasting of PM10 concentration makes it easier for the…
Abstract
Purpose
PM10 is one of the most dangerous air pollutants which is harmful to the ecological system and human health. Accurate forecasting of PM10 concentration makes it easier for the government to make efficient decisions and policies. However, the PM10 concentration, particularly, the emerging short-term concentration has high uncertainties as it is often impacted by many factors and also time varying. Above all, a new methodology which can overcome such difficulties is needed.
Design/methodology/approach
The grey system theory is used to build the short-term PM10 forecasting model. The Euler polynomial is used as a driving term of the proposed grey model, and then the convolutional solution is applied to make the new model computationally feasible. The grey wolf optimizer is used to select the optimal nonlinear parameters of the proposed model.
Findings
The introduction of the Euler polynomial makes the new model more flexible and more general as it can yield several other conventional grey models under certain conditions. The new model presents significantly higher performance, is more accurate and also more stable, than the six existing grey models in three real-world cases and the case of short-term PM10 forecasting in Tianjin China.
Practical implications
With high performance in the real-world case in Tianjin China, the proposed model appears to have high potential to accurately forecast the PM10 concentration in big cities of China. Therefore, it can be considered as a decision-making support tool in the near future.
Originality/value
This is the first work introducing the Euler polynomial to the grey system models, and a more general formulation of existing grey models is also obtained. The modelling pattern used in this paper can be used as an example for building other similar nonlinear grey models. The practical example of short-term PM10 forecasting in Tianjin China is also presented for the first time.
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Yonghong Zhang, Shuhua Mao and Yuxiao Kang
With the massive use of fossil energy polluting the natural environment, clean energy has gradually become the focus of future energy development. The purpose of this article is…
Abstract
Purpose
With the massive use of fossil energy polluting the natural environment, clean energy has gradually become the focus of future energy development. The purpose of this article is to propose a new hybrid forecasting model to forecast the production and consumption of clean energy.
Design/methodology/approach
Firstly, the memory characteristics of the production and consumption of clean energy were analyzed by the rescaled range analysis (R/S) method. Secondly, the original series was decomposed into several components and residuals with different characteristics by the ensemble empirical mode decomposition (EEMD) algorithm, and the residuals were predicted by the fractional derivative grey Bernoulli model [FDGBM (p, 1)]. The other components were predicted using artificial intelligence (AI) models (least square support vector regression [LSSVR] and artificial neural network [ANN]). Finally, the fitting values of each part were added to get the predicted value of the original series.
Findings
This study found that clean energy had memory characteristics. The hybrid models EEMD–FDGBM (p, 1)–LSSVR and EEMD–FDGBM (p, 1)–ANN were significantly higher than other models in the prediction of clean energy production and consumption.
Originality/value
Consider that clean energy has complex nonlinear and memory characteristics. In this paper, the EEMD method combined the FDGBM (P, 1) and AI models to establish hybrid models to predict the consumption and output of clean energy.
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Ao Zhang, Jian Zhang, Mingjun Zhang, Junyi Liu and Ping Peng
This paper aims to investigate the effect and mechanism of O atom single doping, Ce and O atoms co-doping on the interfacial microscopic behavior of brazed Ni-Cr/diamond.
Abstract
Purpose
This paper aims to investigate the effect and mechanism of O atom single doping, Ce and O atoms co-doping on the interfacial microscopic behavior of brazed Ni-Cr/diamond.
Design/methodology/approach
Using first-principles calculations, the embedding energy, work of separation, interfacial energy and electronic structures of Ni-Cr-O/diamond and Ni-Cr-O-Ce/diamond interface models were calculated. Then, the effect of Ce and O co-doping was experimentally verified through brazed diamond with CeO2-added Ni-Cr filler alloy.
Findings
The results show that O single-doping reduces the interfacial bonding strength between Ni-Cr filler alloy and diamond but enhances its interfacial stability to some extent. However, the Ce and O co-doping simultaneously enhances the interfacial bonding strength and stability between Ni-Cr filler alloy and diamond. The in-situ formed Ce-O oxide at interface impedes the direct contact between diamond and Ni-Cr filler alloy, which weakens the catalytic effect of Ni element on diamond graphitization. It is experimentally found that the fine rod-shaped Cr3C2 and Cr7C3 carbides are generated on diamond surface brazed with CeO2-added Ni-Cr filler alloy. After grinding, the brazed diamond grits, brazed with CeO2-added Ni-Cr filler alloy, present few fracture and the percentage of intact diamond reaches 67.8%. Compared to pure Ni-Cr filler alloy, the brazed diamond with CeO2-added Ni-Cr filler alloy exhibit the better wear resistance and the slighter thermal damage.
Originality/value
Using first-principles calculations, the effect of Ce and O atoms co-doping on the brazed diamond with Ni-Cr filler alloy is investigated, and the calculation results are verified experimentally. Through the first-principles calculations, the interface behavior and reaction mechanism between diamond and filler alloy can be well disclosed, and the composition of filler alloy can be optimized, which will be beneficial for synergistically realizing the enhanced interface bonding and reduced thermal damage of brazed diamond.
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Irina V. Gashenko, Elena N. Makarenko, Yuliya S. Zima and Tatyana V. Makarenko
The purpose of the chapter is to study the possibilities of systemic intellectual support for managerial decisions in modern business systems and perspectives of authomatization…
Abstract
Purpose
The purpose of the chapter is to study the possibilities of systemic intellectual support for managerial decisions in modern business systems and perspectives of authomatization of this process on the basis of intellectual technologies.
Methodology
The methodology of the chapter includes the methods of systemic and problem analysis, analysis of causal connections, modeling, and formalization.
Conclusions
Advantages of usage of technologies of intellectual support for decisions in modern business systems are substantiated; they are connected to multitask character, full determination of possibilities and problems of the business system regardless of employees’ involvement in this process, and “scale effect” during making of managerial decisions. Also, drawbacks of intellectual support for decision-making in modern business systems are determined: incompleteness of authomatization of the process of making of managerial decision, foundation primarily on digital data, necessity for complex digitization of the business system, and the problem of security of digital data and intellectual technologies.
Originality/Value
Large opportunities of systemic intellectual support for managerial decisions in modern business systems and wide perspectives of almost full authomatization of this process on the basis of intellectual technologies, accessible at all stages of the process of decision-making, are determined. For this, an algorithm of complex intellectual support for decisions in a modern business system is offered. The obtained results allow determining intellectual technologies of support for managerial decisions in modern business systems as a perspective direction of improving this process.
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Qiuhui Xiao, Xiaotong Xu and Panpan Liu
Recently, increasing importance has been given to electronic records in China, despite the lack of understanding that institutions and organizations have regarding the security…
Abstract
Purpose
Recently, increasing importance has been given to electronic records in China, despite the lack of understanding that institutions and organizations have regarding the security status of electronic records preservation. Wuhan, the largest city in central China, serves as a case to investigate the preservation security of electronic records. Challenges to security are summarized, and solutions are proposed to support policy-developing and operational guidance. The paper aims to discuss these issues.
Design/methodology/approach
The Delphi method is applied to analyze the advice of nine experts, select survey items and design questionnaires. Data are collected from 34 archives in Wuhan through field surveys, oral interviews and e-mails, which are analyzed and illustrated with three representative cases.
Findings
Main achievements of electronic records preservation are concluded in the electronic records management system, carrier types and storage formats, and data backup. Problems are summarized as a lack of awareness and capability of defending against security risks, disaster recovery capability, and understanding of electronic record characteristics. Solutions are proposed as follows: carrying out regular security risk evaluation, adopting new technologies, implementing application-level backup, strengthening technology-related education and attracting more IT talent to join the archive discipline. In addition, it is critical to promote an understanding of the characteristics of electronic records.
Originality/value
This paper investigates the security status of electronic records in central China by surveys and case studies. Critical problems and corresponding solutions are raised to support policy-developing and operational guidance for the research and practice of all kinds of institutions that implement electronic records preservation.
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Strategic group has been intensively studied since this term emerged in 1970s, but previous studies have been limited to the comparisons between groups such as performance…
Abstract
Purpose
Strategic group has been intensively studied since this term emerged in 1970s, but previous studies have been limited to the comparisons between groups such as performance comparison. The purpose of this paper is to explore the internal structure of strategic groups by examining the effect of strategic distance from a firm to the center of its strategic group on firm performance.
Design/methodology/approach
The research is based on data acquired from the annual reports of listed companies and some Chinese domestic databases, including CSMAR Solution, WIND financial database, and China Core Newspapers Full-text Database. After grouping listed pharmaceutical companies in China over the period 2010-2011, the authors test three hypotheses by using fixed effect regressions.
Findings
The paper finds that the strategic distance from a firm to the center of its strategic group has a significant negative effect on the firm's financial performance. Two factors are discovered to influence that effect: corporate diversification strengthens the negative effect of strategic distance on performance, while firm's media visibility weakens that negative effect.
Originality/value
The findings reveal the relationship between intra-group strategic positioning and firm performance, and specify how firms can gain competitive advantage through positioning choices and strategic actions. This study promotes the establishment of a more comprehensive strategic group theory by revealing the structure within strategic groups.
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Rahul Jain, Kunj Bihari Rana and Makkhan Lal Meena
The COVID-19 pandemic is spreading in India and different parts of the world. The outbreak delivered not only the condition of dying from infection but also forced people…
Abstract
Purpose
The COVID-19 pandemic is spreading in India and different parts of the world. The outbreak delivered not only the condition of dying from infection but also forced people (especially office workers and students) to perform all working (office work, classes, assignments, etc.) and non-working activities (leisure activities such as social media, gaming, etc.) at home using handheld devices (HHDs). In this situation, HHD usage for longer durations is mainly responsible for work-related health issues. Therefore, the paper aims to explore HHD usage patterns and musculoskeletal disorders (MSDs) amongst HHD users during homestay and the impact of individual and HHD usage–related factors on MSDs.
Design/methodology/approach
From different states of India, 651 people (especially HHD users from universities and industries) were sampled by using systematic cluster random sampling. In addition, an online questionnaire was used to collect data on the prevalence and risk factors of MSDs. Finally, mean comparisons and chi-square analysis was used to analyse the collected data.
Findings
The prevalence rate of MSDs was higher in upper body parts as compared to the lower body parts. The association of gender with MSDs in various body parts was substantial. The time spent on various working and non-working activities using HHDs was significantly associated with MSDs in upper body parts.
Practical implications
Homestay work may be used as an alternative working arrangement, and the risk factors that have the most significant impact on the health of HHD users may be identified by organizations. The findings suggest the proper use of HHDs as per their essential need with intermediate recreational activities.
Originality/value
It is observed that the musculoskeletal health of office workers and university students is a cause for concern during homestay. The current study provides the prevalence of MSDs experienced by HHD users and the association of individual and HHD usage factors with MSDs.
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Xiaomei Liu, Bin Ma, Meina Gao and Lin Chen
A time-varying grey Fourier model (TVGFM(1,1,N)) is proposed for the simulation of variable amplitude seasonal fluctuation time series, as the performance of traditional grey…
Abstract
Purpose
A time-varying grey Fourier model (TVGFM(1,1,N)) is proposed for the simulation of variable amplitude seasonal fluctuation time series, as the performance of traditional grey models can't catch the time-varying trend well.
Design/methodology/approach
The proposed model couples Fourier series and linear time-varying terms as the grey action, to describe the characteristics of variable amplitude and seasonality. The truncated Fourier order N is preselected from the alternative order set by Nyquist-Shannon sampling theorem and the principle of simplicity, then the optimal Fourier order is determined by hold-out method to improve the robustness of the proposed model. Initial value correction and the multiple transformation are also studied to improve the precision.
Findings
The new model has a broader applicability range as a result of the new grey action, attaining higher fitting and forecasting accuracy. The numerical experiment of a generated monthly time series indicates the proposed model can accurately fit the variable amplitude seasonal sequence, in which the mean absolute percentage error (MAPE) is only 0.01%, and the complex simulations based on Monte-Carlo method testify the validity of the proposed model. The results of monthly electricity consumption in China's primary industry, demonstrate the proposed model catches the time-varying trend and has good performances, where MAPEF and MAPET are below 5%. Moreover, the proposed TVGFM(1,1,N) model is superior to the benchmark models, grey polynomial model (GMP(1,1,N)), grey Fourier model (GFM(1,1,N)), seasonal grey model (SGM(1,1)), seasonal ARIMA model seasonal autoregressive integrated moving average model (SARIMA) and support vector regression (SVR).
Originality/value
The parameter estimates and forecasting of the new proposed TVGFM are studied, and the good fitting and forecasting accuracy of time-varying amplitude seasonal fluctuation series are testified by numerical simulations and a case study.
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Weiliang Zhang, Sifeng Liu, Lianyi Liu, R.M. Kapila Tharanga Rathnayaka, Naiming Xie and Junliang Du
China's population aging is gradually deepening and needs to be actively addressed. The purpose of this paper is to construct a novel model for analyzing the population aging.
Abstract
Purpose
China's population aging is gradually deepening and needs to be actively addressed. The purpose of this paper is to construct a novel model for analyzing the population aging.
Design/methodology/approach
To analyze the aging status of a region, this study has considered three major indicators: total population, aged population and the proportion of the aged population. Additionally, the authors have developed a novel grey population prediction model that incorporates the fractional-order accumulation operator and Gompertz model (GM). By combining these techniques, the authors' model provides a comprehensive and accurate prediction of population aging trends in Jiangsu Province. This research methodology has the potential to contribute to the development of effective policy solutions to address the challenges posed by the population aging.
Findings
The fractional-order discrete grey GM is suitable for predicting the aging population and has good performance. The population aging of Jiangsu Province will continue to deepen in the next few years.
Practical implications
The proposed model can be used to predict and analyze aging differences in Jiangsu Province. Based on the prediction and analysis results, identified some corresponding countermeasures are suggested to address the challenges of Jiangsu's future aging problem.
Originality/value
The fractional-order discrete grey GM is firstly proposed in this paper and this model is a novel grey population prediction model with good performance.
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Simple Arora, Priya Chaudhary and Reetesh Kr Singh
The novel coronavirus pandemic is projected to cause an elevation in anxiety levels across the globe. With everything shifting to online mode, the teaching-learning has also gone…
Abstract
Purpose
The novel coronavirus pandemic is projected to cause an elevation in anxiety levels across the globe. With everything shifting to online mode, the teaching-learning has also gone virtual. This study aims to analyze the impact of novel coronavirus and online education on student’s anxiety and self-efficacy, investigate the role of coping strategies as a moderator between anxiety and self-efficacy. Also, develop and validate an online exam anxiety scale.
Design/methodology/approach
The data is collected by undertaking a cross-sectional survey of 434 higher education students from various universities. For conceptualization of the construct of online exam anxiety, the principal component analysis is carried out. Thereafter, the conceptual model is validated and tested using confirmatory factor analysis and hierarchical regression analysis.
Findings
The hypothesized model demonstrated good reliability and validity. The results showed that students’ anxiety has an adverse impact on their self-efficacy. Findings indicate that the sample in this study reported more anxiety owing to online examinations in comparison to coronavirus induced anxiety. Also, it was found that the relationship between anxiety and self-efficacy was stronger at low levels of coping strategy whereas it got considerably weakened at high levels of coping strategy.
Research limitations/implications
The study is limited to students who belong at other levels of education. Further studies can attempt to capture the impact of COVID on student anxiety. This study was restricted to students in the age group of 18–25. The impact of COVID can be studied in a different age group in the future.
Practical implications
This study offers important implications for educators, practitioners and policymakers working in the education sector. It presents an interesting insight into how the sudden change in pedagogical delivery to online mode is preventing a smooth transition for students and becoming a cause of anxiety. It recommends higher education institutions to develop an innovative and robust approach to promote and address mental health issues among students. It also stresses the need for ensuring that the process of conducting online examinations are streamlined and adequate guidance is given to students.
Social implications
The study proposes the need for training students and teachers on the application of an blended learning approach and efficient adoption of information and communication technology resources in teaching-learning.
Originality/value
The current study contributes to the existing body of knowledge by stressing that adaptive-behavioral and emotion-focused coping strategies are significantly helpful in tackling coronavirus related anxiety. It also recommends the need for Higher education institutions to play an active role in strengthening their preparedness strategies for effective management of outbreaks and pandemics.