Search results

Affective states in learning have gained immense attention in education. The precise affective-states prediction can increase the learning gain by adapting targeted interventions that can adjust the changes in individual affective states of students. Several techniques are devised for predicting the affective states considering audio, video and biosensors. Still, the system that relies on analyzing audio and video cannot certify anonymity and is subjected to privacy problems.

A new strategy, termed rider squirrel search algorithm-based deep long short-term memory (RiderSSA-based deep LSTM) is devised for affective-state prediction. The deep LSTM training is done by the proposed RiderSSA. Here, RiderSSA-based deep LSTM effectively predicts the affective states like confusion, engagement, frustration, anger, happiness, disgust, boredom, surprise and so on. In addition, the learning styles are predicted based on the extracted features using rider neural network (RideNN), for which the Felder–Silverman learning-style model (FSLSM) is considered. Here, the RideNN classifies the learners. Finally, the course ID, student ID, affective state, learning style, exam score and course completion are taken as output data to determine the correlative study.

The proposed RiderSSA-based deep LSTM provided enhanced efficiency with elevated accuracy of 0.962 and the highest correlation of 0.406.

The proposed method based on affective prediction obtained maximal accuracy and the highest correlation. Thus, the method can be applied to the course recommendation system based on affect prediction.

The purpose of this paper is to explore which structures of academic articles referees would pay more attention to, what specific content referees focus on, and whether the distribution of PRC is related to the citations.

Firstly, utilizing the feature words of section title and hierarchical attention network model (HAN) to identify the academic article structures. Secondly, analyzing the distribution of PRC in different structures according to the position information extracted by rules in PRC. Thirdly, analyzing the distribution of feature words of PRC extracted by the Chi-square test and TF-IDF in different structures. Finally, four correlation analysis methods are used to analyze whether the distribution of PRC in different structures is correlated to the citations.

The count of PRC distributed in Materials and Methods and Results section is significantly more than that in the structure of Introduction and Discussion, indicating that referees pay more attention to the Material and Methods and Results. The distribution of feature words of PRC in different structures is obviously different, which can reflect the content of referees' concern. There is no correlation between the distribution of PRC in different structures and the citations.

Due to the differences in the way referees write peer review reports, the rules used to extract position information cannot cover all PRC.

The paper finds a pattern in the distribution of PRC in different academic article structures proving the long-term empirical understanding. It also provides insight into academic article writing: researchers should ensure the scientificity of methods and the reliability of results when writing academic article to obtain a high degree of recognition from referees.

The anticorrosion coatings used in marine and atmospheric environment are subjected to many environmental factors. And the aging failure has been puzzling researchers. The purpose of this study is to find the correlation between the initial aging of epoxy coatings and the typical marine atmospheric environmental factors.

The epoxy coatings were subjected to a one-year exposure in three typical marine atmospheres. Meanwhile, principal component analysis, linear regression and Spearman and gray correlation analysis were applied to quantify the environmental characteristics and establish correlations with the coating aging.

The results indicate that the coating will undergo macroscopic fading and chalking upon exposure to the marine atmosphere, while microscopic examination reveals holes, cracks and partial peeling. The adhesion performance and electrochemical properties of the coating deteriorated with prolonged exposure, coating aging mainly occurs with the generation of O-H bonds and the breakage of molecular chains such as C-N and C-O-C. The coating was most deeply aged after exposure to the Xisha, followed by Zhoushan and finally Qingdao. Environmental factors affect the photooxidative aging and hydrolytic degradation processes of coatings and thus coating aging. To further demonstrate the correlation between environmental factors and coating aging, principal component analysis was used. The correlation model between environmental factors and coating aging was subsequently obtained. The correlation model between the rate of coating adhesion loss (E) and the comprehensive evaluation parameter of environmental factors (Z) is expressed as E = 0.142 + 0.028Z. Meanwhile, the Spearman correlation analysis and gray correlation method were used to investigate the impact of each environmental factor on coating aging. Solar irradiation, relative humidity and wetting time have the highest correlation with coating aging, which are all above 0.8 and have the greatest influence on coating aging; wind speed and temperature have the smallest correlation with coating aging, which are about 0.6 and have the least influence on coating aging.

This paper establishes a correlation between typical marine environmental factors and coating aging performance, which is crucial for predicting the service life of other coatings in diverse environments.

This study aims to apply new modifications by changing the nonlinear logarithmic calculation steps in the method based on the removal effects of criteria (MEREC) method. Geometric and harmonic mean from multiplicative functions is used for the modifications made while extracting the effects of the criteria on the overall performance one by one. Instead of the nonlinear logarithmic measure used in the MEREC method, it is desired to obtain results that are closer to the mean and have a lower standard deviation.

The MEREC method is based on the removal effects of the criteria on the overall performance. The method uses a logarithmic measure with a nonlinear function. MEREC-G using geometric mean and MEREC-H using harmonic mean are introduced in this study. The authors compared the MEREC method, its modifications and some other objective weight determination methods.

MEREC-G and MEREC-H variants, which are modifications of the MEREC method, are shown to be effective in determining the objective weights of the criteria. Findings of the MEREC-G and MEREC-H variants are more convenient, simpler, more reasonable, closer to the mean and have fewer deviations. It was determined that the MEREC-G variant gave more compatible findings with the entropy method.

Decision-making can occur at any time in any area of life. There are various criteria and alternatives for decision-making. In multi-criteria decision-making (MCDM) models, it is a very important distinction to determine the criteria weights for the selection/ranking of the alternatives. The MEREC method can be used to find more reasonable or average results than other weight determination methods such as entropy. It can be expected that the MEREC method will be more used in daily life problems and various areas.

Objective weight determination methods evaluate the weights of the criteria according to the scores of the determined alternatives. In this study, the MEREC method, which is an objective weight determination method, has been expanded. Although a nonlinear measurement model is used in the literature, the contribution was made in this study by using multiplicative functions. As an important originality, the authors demonstrated the effect of removing criteria in the MEREC method in a sensitivity analysis by actually removing the alternatives one by one from the model.

This study aims to investigate the possibilities of cryptocurrencies as hedges and diversifiers in the Indian stock market before and during financial crisis due to the pandemic and the Russia–Ukraine war.

Researchers have used daily data on cryptocurrencies and Indian stock prices from March 10, 2015 to August 26, 2022. The researchers have used the dynamic conditional correlations (DCC)-GARCH model to determine the volatility spillover and dynamic correlation between stocks and digital currencies. Further, researchers have explored hedge ratio, portfolio weight and hedging effectiveness using the estimates of the DCC-GARCH model.

The findings indicate a negative conditional correlation between equities and cryptocurrencies before the crisis and a positive conditional correlation except for Tether during the crisis. Which implies that cryptocurrencies serve as a hedging asset in the stock market before a crisis but are not more than a diversifier during the crisis, except for Tether. Notably, Tether serves as a safe haven during times of crisis. Finally, the study suggests that Bitcoin, Ethereum, Binance Coin and Ripple are the most effective diversifiers for Indian stocks during the crisis.

This study makes several contributions to the existing literature. First, it compares the hedge and diversification roles of cryptocurrencies in the Indian stock market before and during crisis. Second, the study findings provide insights on risk hedging and can serve as a guide for investors. Third, it may help rational investors avoid underestimating risk while constructing portfolios, particularly in times of financial turmoil.

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

This study aims to investigate the influence of resource slack on the decline of Brazilian companies, with a particular focus on the moderating role of environmental dynamism. The authors specifically examine three types of resource slack: available, potential and recoverable. These represent surplus resources that exceed what is necessary for the organization’s basic operations. The role of environmental dynamism, characterized by rapid changes in customer preferences, technologies and competitive dynamics, is considered as a moderating factor in this relationship.

The authors used data from Brazilian companies spanning from 1997 to 2008. The research sample was composed using the matching-pairs method, which included a group of publicly traded companies that experienced decline (43 companies) and a group that did not (40 companies) within the specified timeframe.

Findings of this study indicate that the presence of available slack, being more liquid resources, decreases the likelihood of organizational decline. Furthermore, the moderation effect of potential resource slack can mitigate decline in companies operating in dynamic industries.

This research provides valuable insights into the impact of slack resources on potential organizational turnarounds. Given the relative scarcity of resources in these companies compared to those in developed countries, whether they be financial, human or technological, the study highlights the unique influence of slack in a less explored institutional environment. This research underscores the importance of examining the decline of Brazilian companies from a broader perspective, emphasizing that decisions regarding resource use can have significant implications on a company’s trajectory, either amplifying or mitigating its decline.

¿Cuál es el impacto del slack de recursos en el declive de grandes empresas brasileñas? Para responder a esta pregunta, hemos probado hipótesis por separado para tres tipos de salck de recursos: disponible, potencial y recuperable. Estos excedentes consisten en recursos en exceso más allá de lo necesario para mantener la organización funcionando.

Desarrollamos un estudio empírico cuantitativo y longitudinal con datos de empresas brasileñas de 1997 a 2008. Adoptamos el método de pares emparejados, componiendo la muestra de investigación con un grupo de empresas cotizadas en bolsa que declinaron (43 empresas) y otro que no declinó (40 empresas) en el período de tiempo.

Encontramos que la disponibilidad de recursos más líquidos reduce la posibilidad de declive. El efecto de moderación en el slack de recursos potenciales para empresas en industrias dinámicas puede mitigar el declive.

Esta investigación contribuye a una mejor comprensión del efecto del excedente en posibles recuperaciones. Extender los estudios de recursos excedentes al contexto de empresas brasileñas mostró la influencia que el excedente ejerce en un ambiente institucional relativamente menos explorado. Ya sea financiero, humano o tecnológico, la escasez de recursos es más pronunciada que en empresas de países desarrollados. Esta investigación llama la atención sobre el hecho de que la declinación de empresas brasileñas se analiza desde una perspectiva más amplia. Las decisiones sobre cómo la empresa usa sus recursos pueden afectar positiva o negativamente la declinación de las empresas, reforzando la importancia de discutir esta relación.

A Qual é o impacto da folga de recursos no declínio de grandes empresas brasileiras? Para responder a essa pergunta, testamos hipóteses separadamente para três tipos de folga de recursos: disponível, potencial e recuperável. Essas folgas consistem em recursos além do necessário para manter a organização funcionando.

Desenvolvemos um estudo empírico quantitativo e longitudinal com dados de empresas brasileiras de 1997 a 2008. Adotamos o método de pares combinados, compondo a amostra de pesquisa com um grupo de empresas de capital aberto que declinaram (43 empresas) e outro que não declinou (40 empresas) no período.

Descobrimos que a disponibilidade de recursos mais líquidos reduz a possibilidade de declínio. O efeito moderador na folga de recursos potenciais para empresas em indústrias dinâmicas pode mitigar o declínio.

Esta pesquisa contribui para uma melhor compreensão do efeito da folga sobre possíveis recuperações. A extensão dos estudos de folgas de recursos para o contexto de empresas brasileiras mostrou a influência que a folga exerce em um ambiente institucional relativamente menos explorado. Seja financeiro, humano ou tecnológico, a escassez de recursos é mais pronunciada do que em empresas de países desenvolvidos. Esta pesquisa chama a atenção para o fato de que o declínio de empresas brasileiras é analisado sob uma perspectiva mais ampla. Decisões sobre como a empresa usa seus recursos podem afetar positiva ou negativamente o declínio das empresas, reforçando a importância de discutir essa relação.

This study investigates the relationship between stakeholders and implementing environmentally sustainable practices (ESPs) by Thai restaurant chains.

A survey method using the questionnaire was used to collect data from 400 owners/managers of Thai restaurant chains. The structural equation modeling (SEM) was used to determine the relationship between stakeholders and the implementation of ESPs by Thai restaurant chains.

The finding revealed that both primary and secondary stakeholders significantly influence implementing ESPs, with no moderating effect of environmental knowledge on primary stakeholders regarding implementing ESPs.

The results can help restaurant chain businesses understand how stakeholder power, in response to their regular interactions and societal expectations, affects the implementation of ESPs.

This study is among the first study to investigate the effects of stakeholder pressure on the implementation of ESPs in Thai restaurant chains in Thailand. By looking at restaurant chains, the authors add to the body of knowledge on ESPs in the hospitality sector and offer insights on the role of stakeholders and the moderating role of environmental knowledge.

Academics and businesses alike have begun to recognise sustainability as a vital component of supply chain competitive advantage in recent years. Inconclusive results have been found in empirical studies of sustainable supply chain management (SSCM) that have ignored contextual variables concerning the dynamic role of firm capability in favour of testing alternative assumptions about the effect of various elements of the triple bottom line (TBL) on firm performance outcomes. The present study examines whether and how firm capabilities mediate the connection between SSCM, from a TBL standpoint, and firm financial performance outcomes.

Using the stakeholder theory, the study employed 325 survey responses from firms operating in different industries in Ghana (a less-researched context but one that plays a key role regarding SSCM practices) and the partial least squares structural equation model (PLS-SEM) technique to simultaneously assess the relationships amongst the variables.

It was discovered that the connections between all the TBL facets of SSCM practices and firm performance are positive and significant, and these relationships are mediated by firm capabilities.

By examining the underlying variables and relationships that contribute to the establishment of the rather complex relationship between SSCM practices from a TBL perspective and the performance of a firm, the research contributes to current knowledge on SSCM practices, firm capabilities and firm performance.

This paper presents the findings from the assessment of the determinants of cloud computing (CC) deployment by construction organisations. Using the technology-organisation-environment (TOE) framework, the study strives to improve construction organisations' project delivery and digital transformation by adopting beneficial technologies like CC.

This study adopted a post-positivism philosophical stance using a deductive approach with a questionnaire administered to construction organisations in South Africa. The data gathered were analysed using descriptive and inferential statistics. Also, the fusion of structural equation modelling (SEM) and machine learning (ML) regression models helped to gain a robust understanding of the key determinants of using CC.

The study found that the use of CC by construction organisations in South Africa is still slow. SEM indicated that this slow usage is influenced by six technology and environmental factors, namely (1) cost-effectiveness, (2) availability, (3) compatibility, (4) client demand, (5) competitors' pressure and (6) trust in cloud service providers. ML models developed affirmed that these variables have high predictive power. However, sensitivity analysis revealed that the availability of CC and CC's ancillary technologies and the pressure from competitors are the most important predictors of CC usage in construction organisations.

The paper offers a theoretical backdrop for future works on CC in construction, particularly in developing countries where such a study has not been explored.