Abstract-In this work, a decision support system for early breast cancer detection is presented. In hard to diagnose cases, different examinations (i.e. mammography, ultrasonography and magnetic resonance imaging) provide contradictory findings and patient is guided to biopsy for definite results. The proposed method employs a Correlation Feature Selection procedure and an Artificial Immune Recognition System (AIRS) and is evaluated using real data collected from 53 subjects with contradictory diagnoses. Comparative results with commonly used artificial intelligence classifiers verify the suitability of the AIRS classifier. The application of such an approach can reduce the number of unnecessary biopsies.
Rapid developments in digital innovation and technology in recent decades have marked a transition into the fourth industrial revolution (and the fifth social revolution), causing a significant impact on all areas of human activity. Moreover, these developments have been strongly felt with the advent of the COVID pandemic. The COVID pandemic has acted as a catalyst for imminent changes within the operational models of banks and their digitization, both locally and internationally, dealing with this peculiar crisis as an opportunity rather than a threat. In this study, after conducting a bibliographic overview of the key literature, an analysis of the digital development that took place in the banking sector in Greece was conducted, comparing the views of bank customers to those of bank employees and investigating the key factors that are believed to have a positive and/or negative effect on the use of new digital banking products and services, as well as the influence of factors determining digital banking expansion (gender, age, educational level, pandemic, etc.). The results revealed that bank customers were quite satisfied and familiar with digital transactions and wished to expand their use, while they considered the possibility of 24/7 service as an important factor in choosing to use digital banking, and the factors for expanding their use were transaction speed, transaction security, and information security. However, bank employees accept digital transformation positively and believe that for it to be successful, additional and ongoing training is required to upgrade their digital skills, which will also contribute to culture change and adaptation to the digital era. Furthermore, the age and educational level of bank customers had a statistically significant effect on the growing acceptance and expansion of the banking sector’s digital transformation. A comparison of the correlations of the demographic data with answers given by bank employees did not reveal any significant variations regarding the findings given by bank customers. These findings can be useful for bank management policy-making issues, for banks and their supervising authorities to build KPIs to monitor and assess the digitalization progress, and for academics for further research, especially as the COVID pandemic ensues and the need for digital solutions is all the more urgent, marking the digital competition between banks as one of increasing intensity.
Purpose: This study is an attempt to capture the concept of tax evasion, to distinguish it from tax avoidance and to illustrate the magnitude of the problem in Greece. Design/Methodology/Approach: Time series analysis and regression analysis were performed to determine which factors affect tax compliance in Greece. Data were collected from three different directorates of the Greek Independent Authority for Public Revenue (IAPR), K.E.ME.EP. (Audit Authority for Large Enterprises), K.E.F.O.ME.P. (Audit Authority for Taxpayers with Great Wealth) and Y.E.D.D.E. (Services for Investigations & Safeguarding of Public Revenue). Findings:The results of the research showed that the amount of fines and taxes (related to tax compliance) imposed are statistically significant and positively dependent on both the number of audits and the amounts of money imposed as fines for each audit carried out by K.E.ME.EP. and K.E.F.O.ME.P., while for Y.E.D.D.E. the identified revenue foregone depends only on the number of completed audits. Practical Implications: Tax evasion is a phenomenon that has been of concern to the governments of all countries since ancient times, because it results in both the loss of state revenues and an unequal and unfair distribution of tax burdens. However, tackling tax evasion is a particularly difficult task, mainly because it cannot be easily detected and measured. Originality/Value: This research points out that frequent and effective audits, combined with high fines, are a tool to reduce tax evasion and increase tax compliance.
<abstract><p>We consider dynamical systems that have emerged in financial studies and exhibit chaotic behaviour. The main purpose is to develop a data-based method for reconstruction of the trajectories of these systems. This methodology can then be used for prediction and control and it can also be utilized even if the dynamics of the system are unknown. To this end, we combine merits from Koopman operator theory, Extended Dynamic Mode Decomposition and Takens' embedding theorem. The result is a linear autoregressive model whose trajectories approximate the orbits of the original system. Finally, we enrich this method with machine learning techniques that can be used to train the autoregressive model.</p></abstract>
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