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The purpose of this paper is to report on the global practical uniform h-stabilization for certain classes of nonlinear time-varying systems and its application in a separately excited DC motor circuit.

Based on Lyapunov theory, the practical h-stabilization result is derived to guarantee practical h-stability and applicated in a separately excited DC motor.

A controller is designed and added to the nonlinear time-varying system. The practical h-stability of the nonlinear control systems is guaranteed by applying the appropriate controller based on Lyapunov second method. Another effective controller is also designed for the global practical uniform h-stability on the separately excited DC motor with load. Numerical simulations are demonstrated to verify the effectiveness of the proposed controller scheme.

The introduced approach is interesting for practical h-stabilization of nonlinear time-varying systems and its application in a separately excited DC motor. The original results generalize well-known fundamental result: practical exponential stabilization for nonlinear time-varying systems.

The purpose of this paper is to analyze cloud reviews according to the end-user context and requirements.

propose a comprehensive knowledge base composed of interconnected Web Ontology Language, namely, modular ontology for cloud service opinion analysis (SOPA). The SOPA knowledge base will be the basis of context-aware cloud service analysis using consumers' reviews. Moreover, the authors provide a framework to evaluate cloud services based on consumers' reviews opinions.

The findings show that there is a positive impact of personalizing the cloud service analysis by considering the reviewers' contexts in the performance of the framework. The authors also proved that the SOPA-based framework outperforms the available cloud review sites in term of precision, recall and F-measure.

Limited information has been provided in the semantic web literature about the relationships between the different domains and the details on how that can be used to evaluate cloud service through consumer reviews and latent opinions. Furthermore, existing approaches are lacking lightweight and modular mechanisms which can be utilized to effectively exploit information existing in social media.

The SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.

The SOPA ontology is capable of representing the content of a product/service as well as its related opinions, which are extracted from the customer's reviews written in a specific context. Furthermore, the SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.

Along with the ever growingWeb is the proliferation of objectionable content, such as sex, violence, racism, etc. We need efficient tools for classifying and filtering undesirable web content. In this paper, we investigate this problem through WebGuard, our automatic machine learning based pornographic website classification and filtering system. Facing the Internet more and more visual and multimedia as exemplified by pornographic websites, we focus here our attention on the use of skin color related visual content based analysis along with textual and structural content based analysis for improving pornographic website filtering. While the most commercial filtering products on the marketplace are mainly based on textual content‐based analysis such as indicative keywords detection or manually collected black list checking, the originality of our work resides on the addition of structural and visual content‐based analysis to the classical textual content‐based analysis along with several major‐data mining techniques for learning and classifying. Experimented on a testbed of 400 websites including 200 adult sites and 200 non pornographic ones, WebGuard, our Web filtering engine scored a 96.1% classification accuracy rate when only textual and structural content based analysis are used, and 97.4% classification accuracy rate when skin color related visual content based analysis is driven in addition. Further experiments on a black list of 12 311 adult websites manually collected and classified by the French Ministry of Education showed that WebGuard scored 87.82% classification accuracy rate when using only textual and structural content‐based analysis, and 95.62% classification accuracy rate when the visual content‐based analysis is driven in addition. The basic framework of WebGuard can apply to other categorization problems of websites which combine, as most of them do today, textual and visual content.

The growth of the web and the increasing number of documents electronically available has been paralleled by the emergence of harmful web pages content such as pornography, violence, racism, etc. This emergence involved the necessity of providing filtering systems designed to secure the internet access. Most of them process mainly the adult content and focus on blocking pornography, marginalizing violence. The purpose of this paper is to propose a violent web content detection and filtering system, which uses textual and structural content‐based analysis.

The violent web content detection and filtering system uses textual and structural content‐based analysis based on a violent keyword dictionary. The paper focuses on the keyword dictionary preparation, and presents a comparative study of different data mining techniques to block violent content web pages.

The solution presented in this paper showed its effectiveness by scoring a 89 per cent classification accuracy rate on its test data set.

Many future work directions can be considered. This paper analyzed only the web page, and an additional analysis of the visual content can be one of the directions of future work. Future research is underway to develop effective filtering tools for other types of harmful web pages, such as racist, etc.

The paper's major contributions are first, the study and comparison of several decision tree building algorithms to build a violent web classifier based on a textual and structural content‐based analysis for improving web filtering. Second, showing laborious dictionary building by finding automatically discriminative indicative keywords.

The purpose of this paper is to build a class model to confirm the authenticity of olives from Bi'r al Malluli, Tunisian region, in order to obtain the Designation of Origin (DO).

In total, ten orchards of Chemlali olive oil variety were chosen, in Sfax region, characterized by the same applied cultural techniques. Pomological characters of olives, fatty acids composition and organoleptic analysis of olive oil were conducted.

Results showed that the pomological characters were specific of the Chemlali variety: the olive weight ranged from 0.9 to 1.10 g in all studied orchards and the water content (WC) ranged from 41.45 to 57.68 per cent. All analysed oils showed good fatty acids balance. Chemlali olive oil contains high amounts of oleic acid and a smaller amount of linoleic acid. The oleic acid content ranged from 57.96 to 63.52 per cent according to the orchards. All oils having oleic acid higher than 55 per cent are categorized as extra virgin olive oil based on International Olive Oil Council (IOOC) Norma. Based on the organoleptic analysis, all the analysed oils were classified as an extra virgin olive oil. The principal component analysis applied separately on olive characters and fatty acids contents do not indicate any group's structure.

An objective approach based on pomologic, sensory and acidic composition analyses would be used to delimitate Protected Designation of Origin (PDOs) in olive oil from the Bi'r al Malluli area and better protect their markets.

The research aims to addresses the limitations of previous literature regarding choosing the appropriate conceptualization of trust (i.e. interpersonal trust or system trust) and the role of design aesthetics in generating system trust and intention to adopt mobile banking.

The research conducts two studies. Study 1 determines the degree of humanness in a mobile banking application. Study 2 tests the research model. A total of 261 respondents participate in Study 1 and 491 in Study 2. Statistical Package for the Social Sciences (SPSS) (study 1) and SmartPLS (PLS software) (study 2) are used to test the hypotheses.

Study 1 establishes that the mobile banking application is perceived to have low humanness. Thus, it is expected that system trust is more appropriate to use than interpersonal trust. Study 2 demonstrates that (i) system trust is more useful than interpersonal trust in the mobile banking context and (ii) design aesthetics positively influences consumer system trust and intention to adopt.

To the best of the authors' knowledge, the current research is the first to distinguish empirically between system trust and interpersonal trust and identify the best choice of mobile banking trust type. Specifically, the study determined the choice of system trust for mobile banking through a priori humanness measures and validated this choice by measuring both system trust and interpersonal trust, which has not been done before. In addition, retail banking should consider the influence of design aesthetics on consumer trust and incorporate elements that enhance consumers' opinions about the mobile banking application's functionality, reliability and helpfulness.

The purpose of this paper is to identify the factors affecting firm voluntary disclosure policy adopted by a sample of 25 UAE companies listed on the Abu Dhabi Securities Exchange (ADX) for the period 2010-2014.

The author computes a weighted disclosure index (Botosan, 1997) for three-factor voluntary disclosure items and uses a multivariate regression analysis between disclosure index and a set of explanatory variables identified by previous research. The author also controls for endogeneity problem and uses panel data estimation.

It has been found that listing history, governmental sector, firm profitability and foreign listing positively affect the level of voluntary disclosure adopted by ADX listed companies. By contrast, the percentage of shares owned by block holders and industrial sector negatively affect the level of voluntary disclosure by ADX listed companies. Finally, the board and firm size, managers’ stock options and the leverage ratio do not have any impact on the level of voluntary disclosure adopted by ADX firms. The results remain unchanged to additional sensitivity checks.

The research presents some limitations: first, the author does not take into account all voluntary disclosure items such as human resources and environmental data disclosed by ADX listed firms. Second, other voluntary disclosure determinants remain unexplored for UAE firms such as culture and tax incentives in the light of the new tax rules including corporate tax and value-added tax.

The study has many implications: first, it can help investors in their decision making and lead to fair allocation of resources. Second, it gives helpful directives to UAE accounting authorities to enhance the quality of financial reporting in the light of the New Commercial Company Law 2015 for mandatory adoption of IFRS by all listed companies. The paper also presents helpful directives for tax authorities planning for both company and value-added taxes. It also sheds light on factors driving corporate social responsibility disclosures as a crucial component of voluntary disclosure policy

The paper explores the new determinants of voluntary disclosure such as foreign listing, governmental status and block holding for an emerging relatively unexplored stock market: ADX.

The purpose of this paper is to present the extension of plane wave based method.

The mixed functional are discretized using enriched finite elements. The fluid is discretized by enriched acoustic element, the structure by enriched structural finite element and the interface fluid‐structure by fluid‐structure interaction element.

Results obtained show the potentialities of the proposed method to solve a much larger class of wave problems in mid‐ and high‐frequency ranges.

The plane wave based method has previously been applied successfully to finite element and boundary element models for the Helmholtz equation and elastodynamic problems. This paper describes the extension of this method to the vibro‐acoustic problem.

The purpose of this study is to examine the impact of firm financial and operational characteristics on the level of forward-looking information disclosure (FLID) by Egyptian-listed non-financial companies. The present research also aims to investigate the moderating role of gender diversity on the board of directors.

The sample incorporates the non-financial companies included in the EGX 100 of the Egyptian Stock Exchange (ESE), whose reports were available during the study period from 2013 to 2018. The final sample comprises 49 companies with 294 observations. Statistical analysis is performed using multiple regression analysis.

This study found a significant positive impact of return on assets, leverage, company size and age on the level FLID, while external audit firm type and industry were found to impact the level of FLID negatively. Further, the board gender diversity (BGD) is found to have a moderating impact as it strengthens the effect of financial and operational characteristics on the level of FLID.

The present study has some implications for Egyptian companies, investors in the Egyptian market and regulators in emerging economies, which include paying more attention to BGD when selecting the board members by companies as well as following up the female representation in all the listed companies by regulators.

To the best of the authors’ knowledge, this is the first study to investigate the moderating role of BGD and its impact on the level of FLID in emerging markets. This extends the disclosure literature as the present study brings new evidence from an emerging market regarding BGD moderating role as early research concentrated on the direct impact of BGD on the level of FLID.