Testing the risk and return trade-off in the Athens stock exchange

The present thesis is focused on the examination of the relationship between specific variables with the application of asset pricing models as well as the employment of (G)ARCH models, unit root and cointegration analysis. A theoretical and empirical review on the models is presented and, more specifically, there is an empirical examination of the validity of the Capital Asset Pricing Model (CAPM) and the two main forms of the Arbitrage Pricing Theory (APT) in the Athens Stock Exchange (ASE) during the period 1989-2006. Furthermore, there is an empirical application of specific (G)ARCH models on the variables under examination and an investigation of whether there are long-run relationships between different sets of financial and macroeconomic variables – whether the variables are cointegrated. The results of the tests show the inability of the CAPM to explain the behaviour of stocks for the period under examination, as well as for the sub-periods (1984-1994, 1995-2000, and 2001-2006 respectively). This means that the (optimal) market portfolio used in the CAPM presents a poor explanatory power on the returns of stocks. On the contrary, the results of the statistical APT model show that there may be factors other than the market portfolio that can explain the behaviour of stocks. Similarly, the results from the application of the macroeconomic APT model show that specific macroeconomic variables can partially explain stocks’ behaviour. Finally, the existence of long-run relationships between macroeconomic and financial variables, based on a series of cointegration tests, is evidence that there are different factors that can affect stocks, leading to a possible weak-form inefficiency of the Greek market

Intraclass Clustering-Based CNN Approach for Detection of Malignant Melanoma

This paper describes the process of developing a classification model for the effective detection of malignant melanoma, an aggressive type of cancer in skin lesions. Primary focus is given on fine-tuning and improving a state-of-the-art convolutional neural network (CNN) to obtain the optimal ROC-AUC score. The study investigates a variety of artificial intelligence (AI) clustering techniques to train the developed models on a combined dataset of images across data from the 2019 and 2020 IIM-ISIC Melanoma Classification Challenges. The models were evaluated using varying cross-fold validations, with the highest ROC-AUC reaching a score of 99.48%

An AI-Assisted Skincare Routine Recommendation System in XR

In recent years, there has been an increasing interest in the use of artificial intelligence (AI) and extended reality (XR) in the beauty industry. In this paper, we present an AI-assisted skin care recommendation system integrated into an XR platform. The system uses a convolutional neural network (CNN) to analyse an individual's skin type and recommend personalised skin care products in an immersive and interactive manner. Our methodology involves collecting data from individuals through a questionnaire and conducting skin analysis using a provided facial image in an immersive environment. This data is then used to train the CNN model, which recognises the skin type and existing issues and allows the recommendation engine to suggest personalised skin care products. We evaluate our system in terms of the accuracy of the CNN model, which achieves an average score of 93% in correctly classifying existing skin issues. Being integrated into an XR system, this approach has the potential to significantly enhance the beauty industry by providing immersive and engaging experiences to users, leading to more efficient and consistent skincare routines

Statistical interpretation of tunnel project characteristics and their influence on technical risks – current and future challenges

Tunnels are an increasingly significant part of our built infrastructure. Simultaneously, they are subject to a diversity of inherent uncertainties associated with the geotechnical, hydro-geological, and physical environment surrounding them. The associated risks can materialize on many occasions, leading to disasters with substantially high reinstatement costs, incurred delays, and damage to adjacent third-party assets and the environment. Such disasters can occur due to extreme natural events and unforeseen and unforeseeable ground conditions or accidents. but also, human-driven issues, such as substandard design, poor project management, aggressive project timelines leading to safety shortcuts, compressed budgets and application of innovative techniques not yet fully tested and validated, are some factors contributing to an increased probability of risk materialization and disastrous events. This paper aims to provide a statistical interpretation of tunnel project characteristics and their influence on technical risks based on a database with approximately 400 tunnel failure cases. A further goal of the study is to support decision-makers in the risk management process, such as owners, engineers, and insurers by improving their understanding of project sensitivities. The results indicate the significance of technical characteristics (such as tunnel dimensions, construction type, and ground formations). Still, they also reveal some dependence between lower project risks and the application of current project and risk management practices

Simplified numerical models to simulate hollow monopile wind turbine foundations

The majority of wind turbine foundations consist of hollow monopiles inserted in the soil, requiring high computational effort to be numerically simulated. Alternative simplified models are very often employed instead. Three-dimensional solid models, in which the hollow structure and pile are substituted by solid cylinders with equivalent properties, are the most extended simplifications. Very few 2D models can be found in the literature due to the challenge of finding suitable equivalent properties and loads to fully represent the 3D nature of the problem. So far, very limited attention has been devoted to the accuracy of both 3D and 2D simplified models under dynamic and even static actions. Thus, in this paper, simplified 3D and 2D solid models are proposed and justified. An elasto-plastic constitutive model with accumulative degradation is used to simulate the soil behaviour, and frictional contact elements are implemented between the soil and pile to model their interaction. These simplified approaches are compared with the full 3D hollow model, under static and cyclic loads. The results demonstrate that the proposed simplified approaches are a reasonable alternative to the 3D hollow model, which allows researchers and designers to drastically reduce the computational effort in the simulations under long term conditions

Symbiosis of life-cycle structural design and asset management based on Building Information Modeling: Application for industrial facility equipment

In the last few years, particular focus has been devoted to the life cycle performance of fastening systems, which is reflected in increasing numbers of publications, standards and large-scale research efforts. Simultaneously, experience shows that in many cases, where fastening systems are implemented – such as industrial facilities – the design of fasteners is governed by fatigue loading under dynamic characteristics. In order to perform an adequate design and to specify the most efficient and appropriate fastening product, the engineer needs to access and process a broad range of technical and commercial information. Building information modelling (BIM), as a data management method in the construction industry, can supply such information and accommodate a comprehensive design and specification process. Furthermore, the application of BIM-based processes, such as the generation of a BIM-model, allows to use the important information for the construction as well as the life cycle management with different actions and time dependencies of the asset and its components. As a consequence, the BIM model offers the potential to correlate different data relevant for achieving the goals of the respective application, in order to ensure a more effective and correct design of the fastening. This paper demonstrates such a BIMbased design framework for an Industry 4.0 case, and in particular, the installation of a factory robot through post-installed anchors under fatigue-relevant loading in concrete