Women in Artificial intelligence (AI)

This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI

Credit risk modeling for multilateral lenders

Financial crashes, bubbles, panic in the banking industry, currency crises and even sovereign defaults continue to occur periodically. Therefore, when international or multilateral lenders contemplate on lending credit to customers who are located in different countries, they require a meticulous method of analyzing every aspect to select the best customers, amongst numerous credit proposals from different countries. Moreover, while lending to selected customers, multilateral lenders need to take into account and consider the risk premium in their pricing methodology. Even after having selected sound customers, one should not neglect adequate loan loss provisions in order to safeguard themselves against unexpected changes in financial situations of customers. This may result in credit default. Although several credit scoring methodologies exist for calculating the risk of individuals and corporate customers, most of these methodologies are based on default history and there appears to be a lack of an appropriate methodology when faced with minimal credit default history. Usually, financial institutions and very large corporations are characterized by nil or a very low default history. Following this introduction, this dissertation aims to contribute towards these aspects in the form of three self-contained essays. The first chapter is concerned with determining the main factors, which affect the financial health of financial institutions. More specifically, this is undertaken by employing the two-way panel model and data from financial institutions in several Asian countries. The study attempts to determine bank specific and macro level factors affecting the financial soundness of these financial institutions. In the second chapter by following a similar approach of analysis, this study attempts to detect the main determinants of financial health for very large corporations. These corporations are another group of customers for multilateral lenders. In this case, data from very large corporations in Eastern European countries, which are characterized by their in-transition economies, are employed. Considering the dissertation's findings that are supportive of existing literature, the third chapter addresses the design of two credit scoring/rating models employing fuzzy logic methodology and based upon results from previous chapters. The scoring/rating results of the two models are then analyzed in comparison with the Capital Intelligence rating agency and stock exchange market performance results to assess robustness. This proves the relative robustness of our designed models. Overall, this thesis not only combines and investigates topical issues; moreover, it does so employing various techniques with the intention to contribute on the methodological level. The study is concluded by highlighting policy implications by providing direction for future research

Tradition and Innovation in Construction Project Management

This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

Dynamic data driven investigation of petrophysical and geomechanical properties for reservoir formation evaluation

Petrophysical and geomechanical properties of the formation such as Young’s modulus, bulk modulus, shear modulus, Poisson’s ratio, and porosity provide characteristic description of the hydrocarbon reservoir. It is well-established that static geomechanical properties are good representatives of reservoir formations; however, they are non-continuous along the wellbore, expensive and determining these properties may lead to formation damage. Dynamic geomechanical formation properties from acoustic measurements offer a continuous and non-destructive means to provide a characteristic description of the reservoir formation. In the absence of reliable acoustic measurements of the formation, such as sonic logs, the estimation of the dynamic geomechanical properties becomes challenging. Several techniques like empirical, analytical and intelligent systems have been used to approximate the property estimates. These techniques can also be used to approximate acoustic measurements thus enable dynamic estimation of geomechanical properties. This study intends to explore methodologies and models to dynamically estimate geomechanical properties in the absence of some or all acoustic measurements of the formation. The present work focused on developing empirical and intelligent systems like artificial neural networks (ANN), Gaussian processes (GP), and recurrent neural networks (RNN) to determine the dynamic geomechanical properties. The developed models serve as a cost-effective, reliable, efficient, and robust methods, offering dyanmic geomechanical analysis of the formation. This thesis has five main contributions: (a) a new data-driven empirical model of estimating static Young’s modulus from dynamic Young’s modulus, (b) a new data-driven ANN model for sonic well log prediction, (c) a new data-driven GP model for shear wave transit time prediction, (d) a new dynamic data-driven RNN model for sonic well log reproduction, and (e) an assessment on the ANN as a reliable sonic logging tool

ICTERI 2020: ІКТ в освіті, дослідженнях та промислових застосуваннях. Інтеграція, гармонізація та передача знань 2020: Матеріали 16-ї Міжнародної конференції. Том II: Семінари. Харків, Україна, 06-10 жовтня 2020 р.

This volume represents the proceedings of the Workshops co-located with the 16th International Conference on ICT in Education, Research, and Industrial Applications, held in Kharkiv, Ukraine, in October 2020. It comprises 101 contributed papers that were carefully peer-reviewed and selected from 233 submissions for the five workshops: RMSEBT, TheRMIT, ITER, 3L-Person, CoSinE, MROL. The volume is structured in six parts, each presenting the contributions for a particular workshop. The topical scope of the volume is aligned with the thematic tracks of ICTERI 2020: (I) Advances in ICT Research; (II) Information Systems: Technology and Applications; (III) Academia/Industry ICT Cooperation; and (IV) ICT in Education.Цей збірник представляє матеріали семінарів, які були проведені в рамках 16-ї Міжнародної конференції з ІКТ в освіті, наукових дослідженнях та промислових застосуваннях, що відбулася в Харкові, Україна, у жовтні 2020 року. Він містить 101 доповідь, які були ретельно рецензовані та відібрані з 233 заявок на участь у п'яти воркшопах: RMSEBT, TheRMIT, ITER, 3L-Person, CoSinE, MROL. Збірник складається з шести частин, кожна з яких представляє матеріали для певного семінару. Тематична спрямованість збірника узгоджена з тематичними напрямками ICTERI 2020: (I) Досягнення в галузі досліджень ІКТ; (II) Інформаційні системи: Технології і застосування; (ІІІ) Співпраця в галузі ІКТ між академічними і промисловими колами; і (IV) ІКТ в освіті