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Despite the actual prevalence of diverse types of multimedia information, research on video news is still in an early stage. Improving the accessibility of video news seems worth investigating, therefore, the purpose of this paper is to present a new combination mode of video news text clustering and selection. This method is useful for sorting out and classifying various types of news videos and media texts based on sentiment analysis.

A novel system is proposed, whereby video news are identified and categorized into good or bad ones via the authors' suggested Hidden Markov Model (HMM) and Support Vector Machine (SVM) hybrid learning method. Actually, an exploratory video news sentiment analysis case study, conducted on various news databases, has proven that the feature‐selection‐combining method, encompassing the Information Gain (IG), Mutual Information (MI) and CHI‐statistic (CHI), performs the best classification, which testifies and highlights the designed framework's value.

In fact, the system turns out to be applicable to several areas, especially video news, where annotation and personal perspectives affect the accuracy aspect.

The present work shows the way for further research pertaining to the personal attitudes and the application of different linguistic techniques during the classification.

The achieved results are so promising, encouraging and satisfactory, that they highlight the originality and efficiency of the authors' approach as an effective tool enabling to secure an easy access to video news and multi‐media texts.

The purpose of this paper is to study the mechanical behavior in fatigue tensile mode of different cross-ply laminates constituted of unidirectional carbon fibers, hybrid fibers and glass fibers in an epoxy matrix; and to identify and characterize the local damage in the laminated materials with the use of the acoustic emission (AE) technique.

The tests in the fatigue mode permitted the determination of the effect of the stacking sequences, thickness of 90° oriented layers and reinforcement types on the fatigue mechanical behavior of the laminated materials. The damage investigation in those materials is reached with the analysis of AE signals collected from fatigue tensile tests.

The results show the effects of reinforcement type, stacking sequences and thicknesses ratio of 90° and 0° layers on the mechanical behavior. A cluster analysis of AE data is achieved and the resulting clusters are correlated with the damage mechanism of specimens under loading tests.

The analysis of AE signals collected from tensile tests of the fatigue failure load allows the damage investigation in different types of cross-ply laminates which are differentiated by the reinforcement type, stacking sequences and thicknesses ratio of 90° and 0° layers.

This paper treats the problem of scheduling seafaring staff inspired from a real case study, where the shipowner operates several vessel categories that require specific skills aiming to achieve a fair workload distribution and minimizing incompatibility between workers while meeting legal constraints, including requirements for days off and rest intervals between shifts.

A mixed integer linear problem (MILP) formulation has been built to address the seafaring staff scheduling problem by integrating multiple objectives and constraints. The model’s performance is tested through experimental results across varying parameter adjustments.

Our model was tested and validated using the XPRESS solver, and the results demonstrate its effectiveness in meeting the specified objectives and constraints. Notably, findings reveal that increasing the number of qualified workers leads to improved gains, until a certain threshold. Additionally, expanding the size of the workforce can result in longer execution times, specifically when incompatibility increases.

The originality of this study lies in proposing a generic novel model that deals with maritime staff scheduling, incorporating worker incompatibilities and workload fairness as key objectives.

This paper aims to enable the analysts of reliability and safety systems to evaluate the risk and prioritize failure modes ideally to prefer measures for reducing the risk of undesired events.

To address the constraints considered in the conventional failure mode and effects analysis (FMEA) method for criticality assessment, the authors propose a new hybrid model combining different multi-criteria decision-making (MCDM) methods. The analytical hierarchy process (AHP) is used to construct a criticality matrix and calculate the weights of different criteria based on five criticalities: personnel, equipment, time, cost and quality. In addition, a preference ranking organization method for enrichment evaluation (PROMETHEE) method is used to improve the prioritization of the failure modes. A comparative work in which the robust data envelopment analysis (RDEA)-FMEA approach was used to evaluate the validity and effectiveness of the suggested approach and simplify the comparative analysis.

This work aims to highlight the real case study of the automotive parts industry. Using this analysis enables assessing the risk efficiently and gives an alternative ranking to that acquired by the traditional FMEA method. The obtained findings offer that combining of two multi-criteria decision approaches and integrating their outcomes allow for instilling confidence in decision-makers concerning the risk assessment and the ranking of the different failure modes.

This research gives encouraging outcomes concerning the risk assessment and failure modes ranking in order to reduce the frequency of occurrence and gravity of the undesired events by handling different forms of uncertainty and divergent judgments of experts.

The food supply chain (FSC) challenges coupled with global disruptions, such as the recent coronavirus disease 2019 (COVID-19) pandemic outbreak, exacerbate its vulnerability. The Internet of things (IoT) is one of the disruptive technologies being adopted in food supply chain management (FSCM). This study aims to address the challenges of IoT adoption in the FSC by systematically analyzing the prior pertinent literature.

A structured literature review was used to collate a list of peer-reviewed and relevant publications. A total of 72 out of 210 articles were selected for the final evaluation.

The literature review findings suggest five themes: technical, financial, social, operational, educational and governmental related challenges. A total of 15 challenges were devised from the review related literature of IoT adoption. The study concludes with future research recommendations for scholars and practical implications for practitioners.

While this study focuses on the overall FSC, further research should address other domains in the FSC such as cold supply chain, agriculture and perishable food to gain a better contextual understanding of the specific case.

The topic of IoT adoption in the FSCM is still considered emerging. Therefore, the present work contributes to the limited studies and documentation on the level of IoT implementation in the FSCM. This study should help organizations to assimilate how to adopt and manage the IoT application by addressing the factors and challenges presented in this research.

The purpose of this paper is to discover the most important productivity determinants of Yemeni microfinance institutions. In addition, this study tests the most appropriate tool to measure productivity in such unique industry.

The authors applied data envelopment analysis (DEA) with the variable return to scale after testing the technology return to scale assumption. Then, they used DEA with bootstrapping technique to overcome the borne biasness in the conventional DEA analysis. Finally, the authors presented the Hicks–Moorsteen (total factor productivity [TFP]) as the most suitable tool for the technology presented in this study.

In this paper, the authors found a prolonged deterioration in the productivity scores of microfinance institutions in Yemen. This study highlights the importance of operating in rural areas to improve micro finance institutions’ (MFIs’) productivity. In contrast, they found no significant differences in productivity, neither between microfinance banks and non-governmental organizations nor between Islamic and non-Islamic MFIs.

This study extends previous research in the area of productivity and its determinants. It also adds to the body of productivity knowledge and methodology within the context of the microfinance industry in Yemen.

The study discovered new productivity determinants and re-assessed the importance of some already known ones. These determinants have been studied for the first time in Yemen’s microfinance industry and have contributed to answer the question of what is the most suitable productivity method that should be used. This study proved that the Hicks–Moorsteen TFP and the variable return to scale assumption are the only suitable methods to study productivity in the microfinance industry.

This paper aims to enable the analysts of reliability and safety system to assess the criticality and prioritize failure modes perfectly to prefer actions for controlling the risks of undesirable scenarios.

To resolve the challenge of uncertainty and ambiguous related to the parameters, frequency, non-detection and severity considered in the traditional approach failure mode effect and criticality analysis (FMECA) for risk evaluation, the authors used fuzzy logic where these parameters are shown as members of a fuzzy set, which fuzzified by using appropriate membership functions. The adaptive neuro-fuzzy inference system process is suggested as a dynamic, intelligently chosen model to ameliorate and validate the results obtained by the fuzzy inference system and effectively predict the criticality evaluation of failure modes. A new hybrid model is proposed that combines the grey relational approach and fuzzy analytic hierarchy process to improve the exploitation of the FMECA conventional method.

This research project aims to reflect the real case study of the gas turbine system. Using this analysis allows evaluating the criticality effectively and provides an alternate prioritizing to that obtained by the conventional method. The obtained results show that the integration of two multi-criteria decision methods and incorporating their results enable to instill confidence in decision-makers regarding the criticality prioritizations of failure modes and the shortcoming concerning the lack of established rules of inference system which necessitate a lot of experience and shows the weightage or importance to the three parameters severity, detection and frequency, which are considered to have equal importance in the traditional method.

This paper is providing encouraging results regarding the risk evaluation and prioritizing failures mode and decision-makers guidance to refine the relevance of decision-making to reduce the probability of occurrence and the severity of the undesirable scenarios with handling different forms of ambiguity, uncertainty and divergent judgments of experts.

This study aims to examine the triple relationship between capital regulation, banking lending and economic growth in a dual markets. Specifically, the author seeks to explore how changes in capital regulation can impact banking lending practices and subsequently influence economic growth, while also investigating the reciprocal effects of banking lending on economic growth.

The author follows several previous studies such as Shrieves and Dahl (1992), Beck and Levine (2002), Altunbas et al. (2007), Saeed et al. (2020) and Stewart et al. (2021) to identify a system of three equations, regarding economic growth, capital and banking financing growth, respectively. The author estimates the parameters of all equations simultaneously using the seemingly unrelated regression method (Zellner, 1962) for a sample of 46 Islamic banks and 113 conventional banks during 2002–2022. These banks operate in 13 Muslim countries from Middle East and North Africa and Southeast Asia.

The author’s findings demonstrate that in the case of Islamic banking, an increase in loan growth stimulates economic growth, while an increasing capital ratio positively influences economic growth but is accompanied by a reduction in loan growth. This result corroborates the findings of Stewart et al. (2021), which indicate that regulatory capital reduces unstable credit while improving gross domestic product growth. However, in the case of conventional banks, the response to an increase in loan growth on Gross Domestic Product Per Capita Growth (GDPCG) is ambiguous, while the capital ratio improves GDPCG and promotes LOANG, which, in turn, increases risk.

The Islamic banks can continue to significantly contribute to economic growth by effectively directing their available capital toward viable investment opportunities and supporting sustainable financial practices, even in the presence of potential constraints on loan growth. As for conventional banks, they are invited to increase their capital levels to ensure a strong and resilient financial system that can support lending and facilitate economic growth.

To the best of the author’s knowledge, this paper is the first to explore the triple relationship between capital requirements, Islamic bank lending and economic growth.

We investigate the relationship between gender diversity on corporate boards and environmental performances of firms. Our central focus is the extent to which a country's economic status (developed, developing) can shape such a relationship. We find evidence that gender diversity is positively correlated to environmental performances of firms. Interestingly, this correlation is not only stronger in developing countries but also increasing in gender diversity. These findings have considerable importance in terms of policy.

Promotion of gender diversity in developing countries, where abatement costs are the lowest, would improve global environmental quality in a cost-effective way. This is best achieved through building institutions and strengthening them. The benefits of such policy go beyond developing countries frontiers, particularly when global environmental problems (pollution, global warming, ozone layer depletion, loss of biodiversity, etc.) are concerned. These benefits can be a leverage for an efficient implementation of the United Nations Sustainable Development Goals (UN-SDGs) both as gender diversity stands as a goal by itself and also because it facilitates achieving other environmental-related SDGs.

The purpose of this paper is to explore the motivations and inhibitions linked to the entrepreneurial act in Tunisia, a country belonging to the Middle East and North Africa (MENA) region. The findings of such a study help to better understand why new graduates are reluctant to create their own firms in spite of the political efforts made by the government.

A qualitative approach is adopted. It is based on 38 semi-directive in-depth interviews conducted with new graduates in entrepreneurship, some of them being young entrepreneurs, and others who did not go through the entrepreneurial process. On the basis of the data collected, a thematic content analysis has been carried out.

A set of contextual and cultural factors has been highlighted by the analysis. When the context is characterised by poverty, mafia, corruption, or even by a popular revolution or a war in a neighbouring country, these factors may significantly affect new graduates’ decision to create their own firm. Besides, the entrepreneurial decision may be affected by cultural factors: the bureaucratic system, autocracy, and the existence of entrepreneurial milieus such as social class, region, and geographical regions.

The inductive qualitative approach adopted in a research study affects the generalisable character of the results. This study is also geographically limited to the great Tunis area (the capital and its suburbs).

This study has been carried out in a context of an emergent country from the MENA region. This special setting leads to the valorisation of an understudied set of contextual and cultural motivations and inhibitors of entrepreneurship.