Institutional Repository of Academic Research University of Macedonia
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Between Salafism, Colonialism and Nationalism; the making of an anti-Sufi discourse in Interwar Algeria
No full textThis article examines the intricate dialectics between colonialism, Salafism and the first glimpses of an Algerian nation throughout the interwar period. Founded in 1931, the Association of the Muslim Algerian Ulama (AMAU) embarked on defining the – French dominated – ummah [nation] on cultural and religious terms. By the same token, it aspired to reform the intellectual conditions of the Sunni populace via schools and weekly journals for the steadily growing Arabic-speaking readership. It is against such backdrop, that an old/new fault line was brought in the foreground of the Algerian salafī/iṣlāḥī discourse: the ‘authenticity’ of the scripts as opposed to the ‘heterodox’ ritualism and superstitions of Sufism. By applying the lens of postcolonial theory, it is suggested that the anti-Sufi content of the Association’s journals, reflected the cultural re-codifications of the French ‘Mission Civilisatrice’, albeit in the shape of a restored Islamic orthodoxy coupled with the ambitious ethnoreligious reconstruction of Algeria.121718
Empirical Model for Estimating Sustainable Entrepreneurship’s Growth Potential and Positive Outlook
No full textIn recent years, the expanding concern of environmental, innovative, and sustainable development has advanced sustainable entrepreneurship. Hence, sustainable innovative entrepreneurship can be considered as a running space for business development, auditing, data analytics, and validation practices with modern, positive, and competitive initiatives. The main aim of this paper was to consider the role of Pearson’s ρ as a quality measure initiative on sustainable entrepreneurship growth dynamics, reflecting the strength in and direction of the linear relationship between the corporate’s EBIT profit and several quality corporate factors related to the sustainable growth potential with a positive outlook. A new ρ-based empirical econometric model was proposed, tested on a Western Balkans case study, and validated. Applications and implications of the model are considered in the context of corporate sustainable profitability with a social footprint.11118120
Technical Debt Management: The Road Ahead for Successful Software Delivery
No full textTechnical Debt, considered by many to be the 'silent killer' of software projects, has undeniably become part of the everyday vocabulary of software engineers. We know it compromises the internal quality of a system, either deliberately or inadvertently. We understand Technical Debt is not all derogatory, often serving the purpose of expediency. But, it is associated with a clear risk, especially for large and complex systems with extended service life: if we do not properly manage Technical Debt, it threatens to 'bankrupt' those systems. Software engineers and organizations that develop software-intensive systems are facing an increasingly more dire future state of those systems if they do not start incorporating Technical Debt management into their day to day practice. But how? What have the wins and losses of the past decade of research and practice in managing Technical Debt taught us and where should we focus next? In this paper, we examine the state of the art in both industry and research communities in managing Technical Debt; we subsequently distill the gaps in industrial practice and the research shortcomings, and synthesize them to define and articulate a vision for what Technical Debt management looks like five years hence.15302023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE
Equity premium prediction: The role of information from the options market
No full textWe examine the role of information from the options market in forecasting the equity premium. We provide evidence that the equity premium is predictable out-of-sample using a set of CBOE strategy benchmark indices as predictors. We use a range of econometric approaches to generate point, quantile, and density forecasts of the equity premium. We find that models based on option variables consistently outperform the historical average benchmark. In addition to statistical gains, using option predictors results in substantial economic benefits for a mean–variance investor, delivering up to a fivefold increase in certainty equivalent returns over the benchmark during the 1996–2021 sample period.6410080
BPR Assessment Framework: Staging Business Processes for Redesign Using Cluster Analysis
No full textIn response to increasingly competing environments, organizations are examining how their core business processes (BPs) may be redesigned to improve performance and responsiveness. However, there is a lack of approaches for evaluating Business Process Redesign (BPR) at design time and systematically applying BPR in the case of eligible models. The aim of this research is to demonstrate in practice how the BPR Assessment Framework evaluates the redesign capacity of process models prior to implementation. From the two discrete operation modes of the framework, the paper focuses on the Staging Mode that accounts for the classification of sets of organizational processes. The staging is supported with a clearly defined methodology that is based on partitional clustering and is demonstrated by using a process model repository from literature, initially containing 1000 process models. Based on the findings, the models have varying BPR capacity and the results are consistent to the rational claim that a rising structural complexity denotes a low capacity for BPR. The framework proved to be a convenient and straightforward method for classifying the process models of the repository to categories of low, moderate, and high plasticity and external quality. The contribution of the approach lies to the fact that it can be readily used by practitioners in the course of BPR decision making.47497110Decision Support Systems XIII. Decision Support Systems in An Uncertain World: The Contribution of Digital Twin
Development and validation of the teachers’ augmented reality competences (TARC) scale
No full textWhile augmented reality (AR) can offer many advantages in education, one reason for the difficulty of integrating it in instructional practices is the lack of teachers’ AR competences. Therefore, there is an increasing need to address the required competences needed by teachers to effectively integrate augmented reality (AR) in their teaching. This study develops and validates a comprehensive augmented reality competences scale for teachers. The suggested instrument encompasses skills related to the creation, use and management of augment reality resources for teaching. The scale was validated on a sample of 150 educators from 45 countries teaching in primary, secondary or tertiary levels. Confirmatory factor analysis demonstrated valid results in terms of model fit criteria, factor loadings, validity, and reliability. The final scale is composed of 11 items and 4 competence components. Teaching subject, general digital skills and previous AR class experience revealed significant differences across the scale components, while gender and age did not reveal any significant associations. Educators in higher education institutions self-reported higher competence level for designing, developing, and modifying AR resources compared to secondary and primary levels. The scale can be used by educators to self-assess their AR competences, teacher professional development institutions and policy makers to develop training programs in AR and software companies to develop AR experiences that can empower educators
Identifying patients with paroxysmal atrial fibrillation from sinus rhythm ECG using random forests
No full textParoxysmal atrial fibrillation (PAF) is a cardiac arrhythmia which is often challenging to diagnose because patients may be asymptomatic, and episodes are usually intermittent. In this paper we describe a method for identifying patients with a history of PAF using electrocardiogram (ECG) recordings during sinus rhythm. We analyzed, on a beat-to-beat basis, the P-waves in the sinus rhythm ECGs of 69 patients with a history of PAF and 59 healthy individuals. From each subject’s P-waves, we calculated key electrocardiographic metrics, including some which are proposed here for the first time. Using means testing and feature selection methods, we discerned the features which were most useful for classification, and trained a Random Forest which identified PAF patients. Our approach achieved a 93.45% accuracy, sensitivity of 95.21%, and specificity of 91.40% using P-wave integral and novel amplitude and slope-based features which ranked highest in importance compared to other metrics from the literature. In particular, descriptive statistics of P-wave amplitudes, slopes, and integrals, were effective for identifying subjects with PAF history vs. healthy individuals. Our method has a high sensitivity and discrimination ability, with an AUC=0.9669 which is superior to others’, and can thus be potentially valuable for the early identification of patients who are prone to episodes of PAF, even as part of the standard cardiological checkup that most adults undergo periodically.213A11894
Mathematical modeling for further improving task scheduling on Big Data systems
No full textIn the big data era which we have entered, the development of smart scheduler has become a necessity. A Distributed Stream Processing System (DSPS) has the role of assigning processing tasks to the available resources (dynamically or not) and route streaming data between them. Smart and efficient task scheduling can reduce latencies and eliminate network congestions. The most commonly used scheduler is the default Storm scheduler, which has proven to have certain disadvantages, like the inability to handle system changes in a dynamic environment. In such cases, rescheduling is necessary. This paper is an extension of a previous work on dynamic task scheduling. In such a scenario, some type of rescheduling is necessary to have the system working in the most efficient way. In this paper, we extend our previous works Souravlas and Anastasiadou (Appl Sci 10(14):4796, 2020); Souravlas et al. (Appl Sci 11(1):61, 2021) and present a mathematical model that offers better balance and produces fewer communication steps. The scheduler is based on the idea of generating larger sets of communication steps among the system nodes, which we call superclasses. Our experiments have shown that this scheme achieves better balancing and reduces the overall latency.2014
Moderating Role of Cost Accounting Information Quality on the Relationship Between the COVID‐19 Pandemic and Budgeting in Public Hospitals
No full textBased on new public management, information processing theory and contingency theory, this study investigates the impact of the COVID-19 pandemic on budgeting in public hospitals, focusing on budget use. The research hypotheses were tested using a survey of 82 responses from hospital CFOs. The results show that the organisations that were most affected by the pandemic increased their use of budgets for planning, resource allocation and control, compared to those that were less affected. This study also highlights the moderating role of cost accounting information quality in the relationship between crises and budget use. We find that public hospitals that have been most affected by the pandemic and have simultaneously better cost accounting information have increased their use of budgets for planning, resource allocation and cost control more than those whose costing system does not provide superior cost data.331143
Oil shocks and investor attention
No full textIn this paper, we examine the existence of sentiment exposure in oil price returns. We augment the SVAR model of Kilian and Park (International Economic Review, 2009, 50, 1267–1287) by including the effects of (1) investors sentiment proxied by Google’s search volume index, (2) economic policy uncertainty (EPU) and (3) time variation in both coefficients and the variance-covariance matrix. Our empirical results show that changes in investor attention do exhibit a significant long-lasting impact on oil and stock market returns. Aggregate oil demand and supply shocks have a transitory effect on investor sentiment. We reveal that the impact of EPU is temporary and significant, while EPU responds strongly to shocks on oil prices and stock market returns. In all cases, the magnitude and sign of responses are affected by the timing of the shock. Our findings are robust to an alternative sentiment indicator and once the role of oil inventories is considered.87688