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The purpose of this paper is to propose a new indicator-gray porosity that can objectively evaluate real porosities of electromagnetic shielding (EMS) fabric based on computer image analysis, which aims to address current porosity evaluation by tightness.

A method for the fabric image acquisition is determined and a gray digital model is established. The porosity membership region of true porosity is judged according to the total gray wave. A bi-directional judgment method based on horizontal and vertical single gray waves is proposed to automatically identify the gray porosity in the porosity membership region. After experiments, the differences between the gray porosity indicator and the tightness indicator are analyzed, the influence of the gray porosity on the shielding effectiveness (SE) is discussed, and the advantages of the gray porosity indicator are detailed.

Results show that the proposed indicator can accurately represent the real porosity size of the EMS fabric without pre-acquiring the structure parameters of the fabric, which provides a reference for the study of the electromagnetic characteristic of the EMS fabric.

The gray porosity presented in this paper is a new method to objectively evaluate real porosities of the EMS fabric, and can be applied to the research and evaluation of the electromagnetic characteristic for the EMS fabric.

International harmonization of accounting standards and the move toward convergence have revived an increasing interest in the influence of culture in accounting and auditing. The growing number of countries adopting IFRS and the increasing acceptance of International Standards on Auditing (ISA) has further raised researchers’ attention. For example, more than 100 countries require or permit the use of IFRS, with more countries, such as Canada, India, and Korea, planning to adopt IFRS by 2011 (Deloitte Touche Tohmatsu, 2007; IASB, 2007a, 2007b). This move toward convergence is driven largely on assumptions and assertions based on enhancing international comparability of accounting and auditing information.

The authors measure the impact of culture on Sharia; Social and Financial Disclosure (SSFD) of Islamic Banks (IBs) around the world.

Content analysis is used to measure levels of disclosure for a sample of 136 IBs of 25 countries for years 2013 and 2014. Different cultural measures are used. These include secrecy/transparency as suggested by Gray (1988) and Hofstede (1980, 1983, 2001, 2010)’s culture dimensions which include: Power Distance; Individualism; Masculinity; Uncertainty Avoidance; Long-Term Ordination and Indulgence. Ordinary least square (OLS) regression is used to test the research hypotheses.

After controlling bank-specific, corporate governance and country characteristics, the authors found that Hofstede’s culture dimensions have a significant impact on SSFD. They also found that Gray's transparency dimension positively influence levels of sharia, social and aggregated disclosure. Therefore, they conclude that culture influences levels of disclosure in IBs.

This study has policy implications for managers and regulators of Islamic banking industry.

This study is the first to use both Gray and Hofstede models in the context of IBs around the world. It also the first to explore the impact of culture on three different disclosure levels for IBs.

This study aims to use gray models to predict abnormal stock returns.

Data are collected from listed companies in the Tehran Stock Exchange during 2005-2015. The analyses portray three models, namely, the gray model, the nonlinear gray Bernoulli model and the Nash nonlinear gray Bernoulli model.

Results show that the Nash nonlinear gray Bernoulli model can predict abnormal stock returns that are defined by conditions other than gray models which predict increases, and then after checking regression models, the Bernoulli regression model is defined, which gives higher accuracy and fewer errors than the other two models.

The stock market is one of the most important markets, which is influenced by several factors. Thus, accurate and reliable techniques are necessary to help investors and consumers find detailed and exact ways to predict the stock market.

The purpose of this study is to investigate the impact of parallel importation on brand equity in high and low product involvement arrangements.

A 2 × 2 (authorized goods/gray‐marketed goods)×(high involvement/low involvement) between‐subjects experimental design is utilized; consumer electronics and ballpoint pens are examined.

The results of this empirical study show that source channel (authorized goods versus gray goods) has a significant impact on brand equity; among the five brand equity dimensions, consumers are most concerned about the difference in “perceived quality” between gray goods and authorized goods; given the levels of stimuli, sourcing channel stimuli are found to have more powerful effects than product involvement on consumer evaluations of brand equity.

Marketing implications of the study are as follows. For authorized agents: they could emphasize the “perceived quality” of their products in order to prevent market “squatting” from gray marketers. For manufacturers: authorized goods have a stronger effect on brand equity than gray goods; therefore, manufacturers could adapt the contents and packaging of their products to match consumption behavior in each different country to achieve the purpose of market segmentation and to prevent the products from being diverted. For gray marketers: they should not only emphasize the lower prices of their products, but also highlight their brand knowledge and the brand recognition and provide a valid and sensitive reflection of the brand's standing to their customers.

The most notable finding from this study may be that given the levels of stimuli, sourcing channel stimuli were found to have more powerful effects than product involvement on consumer evaluations of brand equity.

This paper aims to quantify atmospheric corrosion by image analyses. The corrosion extent, form and distribution of corrosion product on Q235B and T91 steels exposed to a Zhoushan marine atmosphere over one year are characterized by image analysis.

Image analysis of corrosion images were achieved using the gray value, wavelet analysis and fuzzy Kolmogorov–Sinai (K–S) entropy.

As corrosion becomes extensive, the gray value of corrosion images decreases, and the energy value of nine subimages after wavelength decomposition decreases. Fuzzy K–S entropy increases as localized corrosion propagates but decreases as uniform corrosion spreads.

The methods proposed in this work open a new way for fast corrosion evaluation of metallic materials exposed to atmospheric conditions.

The purpose of this paper is to develop a system to analyse the characteristics of infrared objects.

According to the gray scale of image pixel by the image entropy, gray scale estimating is carries on to construct the neural networks. And then the grey relational analysis and grey clustering methods are applied to filter the possible object. The target is predicted through image segmentation pretreatment based on the forecasting value by grey system and assigned corresponding mark. The forecasting precision is greatly elevated by GM (1, 1) model.

The paper illustrates that, based on the analysis and its experimental results, this system has a good recognition rate for infrared target.

This paper provides a way to grasp the minutial feature of the image. The filtering operation based on pixel level provided auto‐adapted filtering with a new stage.

Applications of grey theory deepened the content of detecting infrared targets and enriched technology of image processing.

This system introduces an effective method for detecting infrared targets.

The effect of culture, through the accounting values of conservatism and secrecy, on accounting judgments is an area of research extensively studied in developed countries. However, little research has focused on this issue in developing countries, specifically Arab countries. Thus, this study aims to fill this gap by investigating the impact of the combined effect of the culture/accounting dimensions on the interpretation of the probability expressions used in the international accounting standards/international financial reporting standards (IFRSs) in two North African/Arab countries: Tunisia and Egypt.

In the first place, this study determines Hofstede’s cultural index scores for Tunisia, ignored in his original model and updates those related to Egypt, which provides a more relevant understanding of the cultural effect. Then, the study relies on the Hofstede/Gray cultural accounting model to examine the extent to which the accounting values of conservatism and secrecy may affect the recognition of the increase and the decrease of income and the disclosure of this information in the financial statements by postgraduate accounting student in both countries.

The results provide evidence of the generalizability of Gray’s conservatism hypothesis in the North African/Arab countries (i.e. Tunisia and Egypt), at least in the context of income recognition. Moreover, the findings demonstrate that culture, through its influence on the accounting value of secrecy, affects the interpretation of probability expressions used in the IFRSs to establish disclosures.

This study calls for more attention from the standard setters to provide further guidance related to the consistent and accurate numerical value that needs to be assigned to the probability expressions to reduce the ambiguity related to their interpretation. The international accounting standards board (IASB) should pay greater attention to the use of vague probability expressions in developing the IFRSs to promote the true comparability of financial reporting worldwide. Like with any research, this study implies certain limitations specifically related to the sample selection, a sample size, which may affect the generalizability of the results. Thus, future research may rely on a larger sample combining and cover other cultural areas.

The results of this study may give insights into the practical issues faced by the accounting practitioners and which are related to the interpretation and the application of the IFRS including probability expressions. This may trigger their attention toward this issue to reduce the occurrence of these expressions in the revised and newly released standards to guarantee homogeneous financial reporting practices across countries and enhance the IASB’s objective of international accounting harmonization.

This study might be the first one that investigates the issue of the IFRS interpretation in two North African and Arab countries: Tunisia and Egypt. It also provides an original investigation of the cultural effect on accounting judgments based on the actualized Hofstede’s cultural indexes, especially for Tunisia which is ignored in the original country classification.

The purpose of this paper is to explore cultural impact on the harmonisation of Russian Accounting Standards with International Financial Reporting Standards (IFRS).

A theoretical review established that differences still exist between the two sets of accounting standards. For decades, Russia was a socialist state of planned economy. Accounting was a tool of centralised control, and accountants had a job of gathering information for statistical purposes of the government and tax authorities. This led to the development of a “Soviet culture” mindset. Accountants saw their jobs as following prescribed rules. Accounting is seen by Hofstede as a field in which historically developed practices are more important than laws of nature. It is therefore expected that accounting rules and the way they are applied will vary among different national cultures. Hence, Gray tried to explore how Hofstede's national cultural dimensions may explain international differences in accounting. With respect to past research in this area, Nobes argued that “national accounting traditions are likely to continue into consolidated reporting where scope for this exists within IFRS rules”. Ding et al. investigated the role of a country's culture and legal origin as an explanation for the differences between local Generally Accepted Accounting Principles (GAAP) and IAS as they were in 2001. The study gathered 53 Russian accountants' attitudes towards reporting under harmonised Russian Accounting Standards through semi structured interviews.

The findings supported the theoretical view of a “Soviet culture” which has an impact on harmonisation of Russian Accounting Standards with the IFRS. Russia's high rankings in such cultural dimensions as power distance, uncertainty avoidance and collectivism have contributed to the development of certain preferences among Russian accountants. Those preferences were for statutory control, uniformity, conservatism and secrecy. Further findings indicate that accountants in Russia display reluctance to disclose financial information to the external users. One of the main reasons was found to be fear of disclosing too much information to competitors. Based on these findings, accountants in Russia display clear signs of preference for secrecy as opposed to transparency, as identified by Gray.

One of the contributions of this study is to examine current perceptions of Russian accountants towards financial reporting under new harmonised Russian Accounting Standards based on Rozhnova's study.

The purpose of this paper is to find an efficient fabric defect detection algorithm by means of exploring the sparsity characteristics of main local binary pattern (MLBP) extracted from the original fabric texture.

In the proposed algorithm, original LBP features are extracted from the fabric texture to be detected, and MLBP are selected by occurrence probability. Second, a dictionary is established with MLBP atoms which can sparsely represent all the LBP. Then, the value of the gray-scale difference between gray level of neighborhood pixels and the central pixel, and the mean of the difference which has the same MLBP feature are calculated. And then, the defect-contained image is reconstructed as normal texture image. Finally, the residual is calculated between reconstructed and original images, and a simple threshold segmentation method can divide the residual image, and the defective region is detected.

The experiment result shows that the fabric texture can be more efficiently reconstructed, and the proposed method achieves better defect detection performance. Moreover, it offers empirical insights about how to exploit the sparsity of one certain feature, e.g. LBP.

Because of the selected research approach, the results may lack generalizability in chambray. Therefore, researchers are encouraged to test the proposed propositions further.

In this paper, a novel fabric defect detection method which extracts the sparsity of MLBP features is proposed.