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Heart diseases have become one of the most causes of death among Egyptians. With 500 deaths per 100,000 occurring annually in Egypt, it has been noticed that medical data faces a high-dimensional problem that leads to a decrease in the classification accuracy of heart data. So the purpose of this study is to improve the classification accuracy of heart disease data for helping doctors efficiently diagnose heart disease by using a hybrid classification technique.

This paper used a new approach based on the integration between dimensionality reduction techniques as multiple correspondence analysis (MCA) and principal component analysis (PCA) with fuzzy c means (FCM) then with both of multilayer perceptron (MLP) and radial basis function networks (RBFN) which separate patients into different categories based on their diagnosis results in this paper, a comparative study of the performance performed including six structures such as MLP, RBFN, MLP via FCM–MCA, MLP via FCM–PCA, RBFN via FCM–MCA and RBFN via FCM–PCA to reach to the best classifier.

The results show that the MLP via FCM–MCA classifier structure has the highest ratio of classification accuracy and has the best performance superior to other methods; and that Smoking was the most factor causing heart disease.

This paper shows the importance of integrating statistical methods in increasing the classification accuracy of heart disease data.

The purpose of this paper is to present a procedure to design an experimental setup meant to validate an innovative approach for simulating, via computational fluid dynamics, a high-pressure gas release from a rupture (e.g. on an offshore oil and gas platform). The design is based on a series of scaling exercises, some of which are anything but trivial.

The experimental setup is composed of a wind tunnel, the instrumented scaled (1:10) mock-up of an offshore platform and a gas release system. A correct scaling approach is necessary to define the reference speed in the wind tunnel and the conditions of the gas release to maintain similarity with respect to the real-size phenomena. The scaling of the wind velocity and the scaling of the gas release were inspired by the approach proposed by Hall et al. (1997): a dimensionless group was chosen to link release parameters, wind velocity and geometric scaling factor.

The theoretical scaling approaches for each different part of the setup were applied to the design of the experiment and some criticalities were identified, such as the existence of a set of case studies with some release parameters laying outside the applicability range of the developed scaling methodology, which will be further discussed.

The resulting procedure is one of a kind because it involves a multi-scaling approach because of the different aspects of the design. Literature supports for the different scaling theories but, to the best of the authors’ knowledge, fails to provide an integrated approach that considers the combined effects of scaling.

With the European Union (EU) Directive 2014/95/UE, there is a growing interest in the corporate disclosure of “non-financial information” (NFI). However, no generally accepted definition of this term exists. This paper aims to reflect on the meaning and importance of the NFI definition by investigating how this term is defined in the literature and by exploring scholars’ cognitive perceptions of its meaning.

Two different research methods were used. A systematic literature review of NFI definitions was integrated with a survey to a sample of Italian scholars working on the NFI research topic.

This study demonstrates that the meaning of NFI is still ambiguous and multifaceted as neither a common understanding nor a single and generally accepted definition of the term exists. As the advent of the EU directive, this term has often referred to information about society and the environment, though most academics define and understand NFI differently, as corporate social responsibility (CSR) issues, intellectual capital information and information that are external to financial statements. These definitions pave the way for conceptualising NFI as a genus and its different understandings (i.e. CSR, ESG information, etc.) as species. Therefore, what constitutes NFI is open to interpretations.

This paper contributes to enriching the literature on the meaning of NFI and providing further insights into explaining the heterogeneity of the NFI definition.

This paper provides researchers, practitioners and regulators with some novel insights into the meaning and understanding of NFI. It provides regulators and standard setters with knowledge for building a commonly accepted definition of NFI. Meanwhile, policymakers, regulators, practitioners and academics can contribute to establishing a definition by following three approaches: regulative, open and adaptive. This can help to avoid the risk of an information gap among stakeholder expectations, regulator requests and NFI reporting in practice.

The literature focussing on the meaning of NFI is still scarce. This study contributes to extending the knowledge of how the term NFI is defined and understood by academics.

The paper aims to investigate the comfort-related performances of an innovative solar shading solution based on a new composite patented material that consists of a cement-based matrix coupled with a stretchable three-dimensional textile. The paper’s aim is, through a performance-based generative design approach, to develop a high-performance static shading system able to guarantee adequate daylit spaces, a connection with the outdoors and a glare-free environment in the view of a holistic and occupant-centric daylight assessment.

The paper describes the design and simulation process of a complex static shading system for digital manufacturing purposes. Initially, the optical material properties were characterized to calibrate radiance-based simulations. The developed models were then implemented in a multi-objective genetic optimization algorithm to improve the shading geometries, and their performance was assessed and compared with traditional external louvres and overhangs.

The system developed demonstrates, for a reference office space located in Milan (Italy), the potential of increasing useful daylight illuminance by 35% with a reduced glare of up to 70%–80% while providing better uniformity and connection with the outdoors as a result of a topological optimization of the shape and position of the openings.

The paper presents the innovative nature of a new composite material that, coupled with the proposed performance-based optimization process, enables the fabrication of optimized shading/cladding surfaces with complex geometries whose formability does not require ad hoc formworks, making the process fast and economic.

Classifying moving objects in video sequences has been extensively studied, yet it is still an ongoing problem. In this paper, we propose to solve moving objects classification problem via an extended version of two-dimensional principal component analysis (2DPCA), named as category-wise 2DPCA (CW2DPCA). A key component of the CW2DPCA is to independently construct optimal projection matrices from object-specific training datasets and produce category-wise feature spaces, wherein each feature space uniquely captures the invariant characteristics of the underlying intra-category samples. Consequently, on one hand, CW2DPCA enables early separation among the different object categories and, on the other hand, extracts effective discriminative features for representing both training datasets and test objects samples in the classification model, which is a nearest neighbor classifier. For ease of exposition, we consider human/vehicle classification, although the proposed CW2DPCA-based classification framework can be easily generalized to handle multiple objects classification. The experimental results prove the effectiveness of CW2DPCA features in discriminating between humans and vehicles in two publicly available video datasets.

Status of fiscal health of local governments helps in determining planned budget and realistic action plan for citizens’ wellbeing. This paper aims to assess the fiscal health of local governments in Bangladesh.

Using data from 18 south-western municipalities of Bangladesh during the fiscal year 2018–19, this research measures fiscal health by applying Wang, Dennis and Tu’s solvency test and Brown’s Ten-Point Test.

The result shows that one-tenth of the entire municipalities are endowed with better position, whereas almost 39 percent of municipalities are in the worst situation and nearly 50 percent of municipalities are in the average category. Because of having limited liabilities, the municipalities are endowed with more than enough cash solvency and reasonable level of long-run solvency. The key problems are that budgetary solvency of all municipalities is not satisfactory, and service expenses are more than their revenue generation. This study suggests improving the financial capabilities of the municipalities through properly using their resources, generating loans, and claiming a need-based budget from the central government.

The paper investigates the status of fiscal solvency of local governments in Bangladesh in a new dimension. The findings might be helpful to policymakers in budgeting for development initiatives of local governments in Bangladesh so that citizens’ better wellbeing is ensured.

Access to finance, especially by the poor and marginalized section of the population, is a prerequisite for creating employment opportunities, economic growth, poverty reduction and social cohesion. Access to finance makes transactions quicker, cheaper and safer. Most people around the world having an account in a formal financial institution serve as an entry point into formal financial sector. This study aims to analyze the status of financial inclusion in Assam with respect to demographic penetration, geographic penetration and usage ratio, i.e. credit–deposit ratio.

The study covers a period of 12 years from 2007–08 to 2018–19. Both the parametric and non-parametric statistical tools have been used to analyze the various dimensions of financial inclusion.

The study clearly indicates that there is a significant difference between Assam and aggregate India in financial inclusion and the status of Assam is somewhat lower as compared to the aggregate financial inclusion status of India. To achieve a satisfactory level of financial inclusion, it is not enough to open a bank account for the excluded people, but banks must look at flexibility and timeliness in services to offer a complete package to this segment of the population.

The study is a significant attempt to meet the shortcomings and improve banking coverage for achieving financial inclusion.

This paper investigates the effect of entrepreneurial orientation (EO) on small- and medium-sized enterprises' (SMEs) access to credit. Starting with the idea that SMEs' strategy-making process, structures and behaviour can favour credit access, the authors also explore the moderating role of bank lending technologies in shaping this relationship.

This study relies on a unique survey of Austrian and Italian SMEs which contains detailed information on access to credit, EO dimensions, relationship lending and firm-level characteristics. The authors perform stepwise logistic regressions to assess whether EO interacts with SME's access to finance, and how relationship lending enhances this relationship.

Proactiveness, autonomy and competitive aggressiveness are important constructs for improving access to bank financing. Those dimensions became more important when a relationship bank is involved, suggesting a role for relationship lending in overcoming SMEs' opaqueness. In addition, relationship lending is crucial for innovative SMEs in overcoming credit denial rates.

The small sample did not allow to analyse the effect of EO on discouraged borrowers. Furthermore, alternative measures of relationship lending (such as geographical proximity or the length of the relationship) and the share of credit granted by the relationship bank would have been interesting to further validate our results.

This study shows that EO dimensions and the type of lending technology are relevant for the financial success of SMEs. More precisely, the authors show that diversity within the banking system helps innovative, autonomous, proactive and competitive SMEs. These important pieces of soft information are injected into the final lending decision when a relationship bank is involved. The evidence suggests the need for SMEs to interact with local banks to fully exploit their EO posture.

To the authors' knowledge, this paper is the first attempt to analyse whether relationship lending can affect the EO–credit access relation.

This study aims to investigate the impact of environmental performance, social responsibility and corporate governance (ESG) on bank performance (BP) in the Italian banking sector. It analyzes the relationships between 10 dimensions of ESG pillars and BP indicators during the period 2016–2020.

This study examines a sample of 105 Italian banks and develops three econometric models to verify the effect of ESG initiatives on BP indicators. The independent variables are the ESG dimensions collected from the Refinitiv database, whereas the explanatory variables are performance indicators measured through accounting and market variables.

The findings show that ESG policies negatively affect operational and market performance in the banking sector, suggesting that Italian banks have not fully embraced strong sustainability procedures. However, the relationships between ESG dimensions are mixed if measured individually. The results show a significant positive impact of emission and waste reductions on financial and operating performance, but regarding social aspects, it is proved that better product responsibility decreases accounting performance.

This study offers an in-depth examination of ESG practices in relation to current and future performance. In particular, the findings provide practitioners and academics with an actual set of predictors in the ESG area to improve BP.

To the best of the authors’ knowledge, this is the only study that has investigated the impact of ESG issues on BP in Italy. Few prior studies have used all dimensions of ESG policies at a disaggregated level to investigate their effect on various performance indicators.

This paper aims to elaborate a set of characteristics that conceptualize and qualify a disruptive business model.

The literature on disruptive business models will be analyzed using the latent semantic analysis (LSA) technique, complemented by content analysis, to obtain a more precise qualification and conceptualization regarding disruptive business models.

The results found described concepts already described in the theory. However, such findings, highlighted by the LSA, bring new perspectives to the analysis of the disruptive business models, little discussed in the literature and which reveal important considerations to be made on this subject.

It should be noted, about the technique used, a limitation on the choice of the number of singular values. For this to be a problem in the open literature, the authors tried to work not just with the cost-benefit ratio given the addition of each new dimension in the analysis, as well as a criterion of saturation of the terms presented.

The presentation of this set of characteristics can be used as a validation tool to identify if a business is or is not a disruptive business model by managers.

The originality of this paper is the achievement of a consolidated set of characteristics that conceptualize and qualify the disruptive business models by conducting an in-depth analysis of the literature on disruptive business models through the LSA technique, considering the difficulty of obtaining precise concepts on this subject in the literature.