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This paper aims to investigate opportunities of the short- and long-run international portfolio diversification (IPD) benefits by investing in the Middle Eastern oil-producing countries. Over the past decades, IPD has been the integral feature of global capital markets. Several potential benefits like increasing returns and/or reducing risk have made investors to internationalize their portfolios. Solnik’s theory (1974) approved that gains can be achieved through IPD if returns in the different markets are not perfectly correlated. This may attribute to low correlations of equity returns among different economies. In this regards, there would be a large potential of diversification benefits for investors that diversify into new emerging group of economies such as equity markets of the main oil-producing countries. These markets are often segmented and they may ensure a superior return rate for a given risk level.

In most of the previous studies, Pearson’s correlation test is used to analyze the short-run relationship of market prices. However, recent empirical studies indicate that correlations between equity returns vary over the time. To examine the time-varying conditional correlation, this paper used the dynamic conditional correlation (DCC) model to investigate opportunities of the short-run IPD benefits. In addition, for the long-run linkage analysis, the autoregressive distributed lag (ADRL) approach introduced by Pesaran et al. (2001) is applied.

It is found that, the market returns of the sampled countries are not definitely correlated in the short- and long-term. So, international portfolio investors may get the short- and long-term diversification benefits by diversifying their portfolios among the Middle Eastern equity markets, namely, Iran, Bahrain, Qatar, Kuwait, Oman, Saudi Arabia and UAE.

This paper departs from earlier studies by focusing on the dynamic characteristics of correlation. Two main issues are pursued in this paper. First, instead of modeling the correlation by methods like Pearson correlation coefficient that consider the constant-correlation assumption, this paper directly uses the DCC model. Second, to empirically estimate the long-run relationship among stock markets in the Middle Eastern oil-producing countries, the ARDL approach is utilized. The ARDL approach is more robust and performs well for small sample sizes than other co-integration techniques.

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.

The purpose of this paper is to develop an equation for the synergistic corrosion of SRB and CO₂ based on the D-W model.

The bacterial types in the a and ß pipelines were studied by the most probable number method, and the corrosion morphology of L360 in pipeline water samples was studied by surface analysis. The corrosion rate of L360 was studied using the weight loss method. The gray correlation method was used to calculate the degree of correlation between the influencing factors of corrosion under the synergistic effect of CO₂ and SRB. The curve obtained from PIPESIM software and experiments data was then fitted using multiple non-linear regression method by MATLAB software.

The equation was used to predict the corrosion of the ß pipeline for verification, and it was found that seven out of ten excavation sites were within a 20% error range.

Using the gray correlation method, an equation that considers synergistic corrosion of SRB and CO₂ has been developed based on the D-W model. The equation could be used to predict the corrosion rate of shale gas gathering pipelines through SRB and CO₂ synergistic corrosion.

The purpose of this paper is to develop a maintenance decision support system (DSS) framework using in-service lubricant data for fault diagnosis. The DSS reveals embedded patterns in the data (knowledge discovery) and automatically quantifies the influence of lubricant parameters on the unhealthy state of the machine using alternative classifiers. The classifiers are compared for robustness from which decision-makers select an appropriate classifier given a specific lubricant data set.

The DSS embeds a framework integrating cluster and principal component analysis, for feature extraction, and eight classifiers among them extreme gradient boosting (XGB), random forest (RF), decision trees (DT) and logistic regression (LR). A qualitative and quantitative criterion is developed in conjunction with practitioners for comparing the classifier models.

The results show the importance of embedded knowledge, explored via a knowledge discovery approach. Moreover, the efficacy of the embedded knowledge on maintenance DSS is emphasized. Importantly, the proposed framework is demonstrated as plausible for decision support due to its high accuracy and consideration of practitioners needs.

The proposed framework will potentially assist maintenance managers in accurately exploiting lubricant data for maintenance DSS, while offering insights with reduced time and errors.

Advances in lubricant-based intelligent approach for fault diagnosis is seldom utilized in practice, however, may be incorporated in the information management systems offering high predictive accuracy. The classification models' comparison approach, will inevitably assist the industry in selecting amongst divergent models' for DSS.

Ranking relevant journals is very critical for researchers to choose their publication outlets, which can affect their research performance. In the management information systems (MIS) subject, many related studies conducted surveys as the subjective method for identifying MIS journal rankings. However, very few consider other objective methods, such as journals’ impact factors and h-indexes. The paper aims to discuss these issues.

In this paper, top 50 ranked journals identified by researchers’ perceptions are examined in terms of the correlation to the rankings by their impact factors and h-indexes. Moreover, a hybrid method to combine these different rankings based on Borda count is used to produce new MIS journal rankings.

The results show that there are low correlations between the subjective and objective based MIS journal rankings. In addition, the new MIS journal rankings by the Borda count approach can also be considered for future researches.

The contribution of this paper is to apply the Borda count approach to combine different MIS journal rankings produced by subjective and objective methods. The new MIS journal rankings and previous studies can be complementary to allow researchers to determine the top-ranked journals for their publication outlets.

Criteria importance through intercriteria correlation (CRITIC) is a multicriteria decision-making method that helps compute the weights of decision criteria by considering the contrast intensity and conflicting relationships inherent in each criterion. This study aims to conduct a bibliometric analysis to provide quantitative insights into the research trends concerning the CRITIC method.

The study assembled bibliographic data from 220 CRITIC-based publications retrieved from the Scopus database. Subsequently, the gathered data were processed using Tableau software, using specific functions within the software to format them to suit the analysis requirements. Following data preparation, a visual analysis was then conducted based on five parameters that can characterize the research evolutions in CRITIC. These parameters include research productivity across years, dominant countries, dominant researchers, dominant publication outlets and popular research topics. Various visualization techniques, such as combined charts, geographical maps and word clouds, were used to draw conclusions for each parameter.

The study discovered a burgeoning trend in CRITIC research in recent years, particularly from 2019 onwards. The COVID-19 pandemic unexpectedly contributed to this upward trend, prompting remarkable collaboration among researchers who used diverse decision-making methods, such as CRITIC, to provide data-driven solutions for addressing COVID-19 challenges. Additionally, the study identified China and Iran as the leading countries in CRITIC research, with notable researchers such as Xindong Peng and Mehdi Keshavarz-Ghorabaee predominantly affiliated with institutions in these countries. Keyword analysis indicated the application of CRITIC across various trending topics, including Industry 4.0 and environmental sustainability.

No bibliometric analyses have been conducted on the CRITIC method in the literature since its inception in 1995, leaving the scientific community clueless about its research trends. To the best of the author’s knowledge, this study serves as the first bibliometric analysis, providing quantitative evidence on the research trends associated with the CRITIC method. By shedding light on these trends, this study enables the scientific community, including researchers and funding agencies, to make informed decisions regarding future research endeavors involving the CRITIC method.

Ciliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed.

Based on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference.

The three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized.

This algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

The state‐of‐the‐art of existing methods of tear resistance (static and dynamic) of clothing has been described, also presented are the parameters of static tear resistance for protective and work clothing depending on its application.

For chosen group of fabrics the introduction of a new parameter of dynamic tear resistance was proposed. For research, five static tear test methods and the dynamic one were chosen. In order to find the relationship between the results of mean tear forces for the six described methods Kendall's agreement coefficient was calculated. The comparative measurements for results of static tear resistance and dynamic tear resistance for protective and work clothing were carried out. On the basis of this, the value of tear dynamic force for these fabrics was established.

When establishing the criteria for the tear strength for protective and work clothing, the most significant was fabric end‐use and the minimal value of tear strength associated.

The value of dynamic tear resistance can be the criterion for assessment of fabrics with regard to textiles exposed to tearing during application. It was the first comparative analysis of the measurement of tear resistance methods.

Investigating test methods for the assessment of clear resistance.

The purpose of this paper is to examine information and volatility linkages among real estate, equity, bond and money markets in Australia.

A novel rational expectations framework of financial contagion (Kodres and Pritsker, 2002), along with a combination of robust statistical methods including simple and dynamic correlations and generalized impulse response (Fereidouni et al., 2014) have been employed using data covering three dynamic pre-pandemic economic cycles, namely, global financial crisis (GFC) period, pre-pandemic housing boom and pre-pandemic housing downturn from 2008 (February) to 2019 (December).

Results reveal information linkages across real estate, equity, bond and money markets through correlations in return and volatilities of these series. Finding indicates that the three financial markets (equity, bond and money markets) are interdependent and integrated through information and volatility linkages during the GFC period and pre-pandemic housing downturn period. Financial markets have stronger associations with real estate market during pre-pandemic housing boom. The findings contribute to the general notion that the performances of three financial markets are closely related to the “boom” phase of the real estate cycle.

This research provides an extension of existing literature regarding the information and volatility contagion of the expanded set of core investment markets in Australia. The findings could assist household buyers and investors in designing strategic investment portfolios/hedging strategies and minimizing asset specific risks through diversification over short-term and long-term. In addition, results could support the maintenance, growth and development of a combination of competitive balanced investment markets including real estate, equity, bond and money markets in post-pandemic economy.

This paper verifies the adequacy of perceived quality measurement instruments by comparing the SERVPERF and EP methods. After a discussion of the differences between the two methods, a quality perception measurement instrument for the company is developed and applied to a sample of ceramic company clients. The methods are compared by analyzing the multitrait‐multimethod matrix using the structural equation model methodology. Results indicate that SERVPERF has greater reliability, greater convergent and discriminant validity, explains variance more completely, and consequently introduces less bias.