Leonidas Theodorakopoulos

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• Doctor of Philosophy
• Adjunt Professor at University of Patras

In this study, we analyze the performance of the machine learning operators in Apache Spark MLlib for K-Means, Random Forest Regression, and Word2Vec. We used a multi-node Spark cluster along with collected detailed execution metrics computed from the data of diverse datasets and parameter settings. The data were used to train predictive models tha...

The accounting division plays a crucial role in providing accurate financial data and insights, which are instrumental to informed decision-making and strategic planning. Organizational financial transparency and effective support for resource management depend on accounting. This paper presents a deep neural network (DNN)-based accounting analytic...

Systems for graph processing are a key enabler for insights from large-scale graphs that are critical to many new advanced technologies such as Artificial Intelligence, Internet of Things, and blockchain. In this study, we benchmark another two widely utilized graph processing systems, Apache Spark GraphX and Apache Fink, concerning the key perform...

The integration of big data analytics in digital marketing has fundamentally transformed how organizations understand and influence consumer behavior. This systematic review explores the potential of big data to offer deep insights into consumer preferences and behaviors. The current literature on big data and consumer behavior showcases its potent...

Big data and blockchain technology are coming together to revolutionize how decisions are made in a decentralized way across various industries. This review looks at how these technologies , along with distributed systems, can improve data security, transparency, and real-time processing , making decision-making more efficient and informed. The int...

Objectives: This study discusses work performed within the context of the SAINT R&D project concerning the correlation of the prices of cybercrime services with the costs of investing in cyber security technologies. The main goal is to investigate how various financial and business-related cybercrime parameters relate to cybersecurity costs. In thi...

The mode is a fundamental descriptive statistic in data analysis, signifying the most frequent element within a dataset. The range mode query (RMQ) problem expands upon this concept by preprocessing an array A containing n natural numbers. This allows for the swift determination of the mode within any subarray A[a..b], thus optimizing the computati...

Big Data and blockchain technology are coming together to revolutionize how decisions are made in a decentralized way across various industries. This review looks at how these technologies, along with distributed systems, can improve data security, transparency, and real-time processing, making decision-making more efficient and informed. The integ...

The explosion of data volume in the digital age has completely changed the corporate and industrial environments. In-depth analysis of large datasets to support strategic decision-making and innovation is the main focus of this paper’s exploration of big data management engineering. A thorough examination of the basic elements and approaches necess...

This paper presents a comprehensive study on applying machine learning (ML) techniques for real-time credit card fraud detection. With the increasing prevalence of credit card fraud, financial institutions face the challenge of detecting fraudulent transactions promptly and accurately. This research evaluates various ML models, including Logistic R...

Objectives: This paper aims to comprehensively explore the implications of Big Data within the realm of accounting, dissecting both its potential advantages and the hurdles it presents. The primary goal is to introduce and delineate the potential benefits of Big Data integration in accounting practices. Additionally, it seeks to identify and thorou...

In the context of the Internet of Things (IoT), Tiny Machine Learning (TinyML) and Big Data, enhanced by Edge Artificial Intelligence, are essential for effectively managing the extensive data produced by numerous connected devices. Our study introduces a set of TinyML algorithms designed and developed to improve Big Data management in large-scale...

In this work, we present a Distributed Bayesian Inference Classifier for Large-Scale Systems, where we assess its performance and scalability on distributed environments such as PySpark. The presented classifier consistently showcases efficient inference time, irrespective of the variations in the size of the test set, implying a robust ability to...

The increasing volume, velocity, and variety of data generated in today’s digital economy have given rise to new opportunities and challenges for the field of accounting. Big data has the potential to revolutionize accounting practices by providing a wealth of information that was previously unavailable. However, to fully realize the potential of b...

In this study, we introduce FLIBD, a novel strategy for managing Internet of Things (IoT) Big Data, intricately designed to ensure privacy preservation across extensive system networks. By utilising Federated Learning (FL), Apache Spark, and Federated AI Technology Enabler (FATE), we skilfully investigated the complicated area of IoT data managemen...

Autonomous vehicles (AVs), defined as vehicles capable of navigation and decision-making independent of human intervention, represent a revolutionary advancement in transportation technology. These vehicles operate by synthesizing an array of sophisticated technologies, including sensors, cameras, GPS, radar, light imaging detection and ranging (Li...

The COVID-19 pandemic prompted higher education institutions to develop new strategies for conducting examinations alongside other learning activities. The Hellenic Open University (HOU) adopted Remote Electronic Examinations (REE) as a one-way solution due to physical presence restrictions. This study presents the perceptions of HOU faculty member...

The advent of big data has transformed the way in which businesses interact with consumers. With the ability to collect and analyze vast amounts of data from multiple sources, companies are now able to gain insights into consumer behavior that were previously impossible. This paper explores the relationship between big data, consumer behavior, digi...

This paper explores the role of Big Data Analytics (BDA) in e-Government and how it can act as a catalyst for digital transformation. The paper begins by defining e-Government and digital transformation, and then moves on to explain the concept of BDA. The benefits of using BDA in e-Government are then discussed, such as data-driven decision-making...

The advent of digital technology has transformed the way businesses interact with consumers, providing an abundance of data that can be harnessed to improve the customer experience. Big data analysis offers businesses the tools to gain insight into consumer behavior and preferences, optimize the customer journey, and create personalized experiences...

Tourism is the “heavy industry” of our country, as confirmed by the statistical data of many surveys. With the help of new technologies, the goal of attracting quality tourism and increasing per capita spending on products and services provided by the tourism industry is becoming more and more achievable. In the present work, the adoption of big da...

Objectives: Accurate prediction of stock market returns is a very challenging task due to the volatile and non-linear nature of the financial stock markets. In this work, we consider conventional time series analysis techniques with additional information from the Google Trend website to predict stock price returns. We further utilize a machine lea...

In the modern era where data is produced from multivariate sources, there is an urge to handle such data in an efficient yet effective manner. Therefore, applications that necessitate such capabilities shall make use of data structures and indexing mechanisms that can perform fast index operations along with low complexity as per insertion, deletio...

Visualization is a critical component across every software as it enables users to familiarize themselves with the environment and perform certain tasks with ease. Therefore, straightforward yet interactive and easy-to-understand tools let users’ complex demands be satisfied within minutes. The objective of this work is to give an optimized graphic...

This research examines the educational challenges encountered by second-chance school students in the correctional facility during the pandemic. The opportunity to utilise a specialised digital interconnection facility with the eLearning Platform deprived offenders of the right to equal access to education. Using open-source software, a unique encr...

In this paper, an investigation is conducted to estimate the effect of economic uncertainty on volume volatility, focusing on four systemic Greek banking institutions, including (i) Alpha Bank, (ii) Eurobank, (iii) National Bank of Greece, and (iv) Piraeus Bank. The purpose of this study is to explain in detail if the EPU is linked with volume vola...

The employment of various language modelling techniques in the area of information retrieval is gaining wide adoption in the state of the art methods. The precision of the language model enables the solution of the issue of information retrieval in a huge corpus of texts. To accomplish this, these techniques begin by estimating a probabilistic ling...

Background/Objectives: Accurate prediction of stock prices is an extremely challenging task because of factors such as political conditions, global economy, unexpected events, market anomalies, and relevant companies’ features. In this work, the random forest has been used to forecast the prices of the four major Greek systemic banks Methods/Analys...

The growing volume, complexity and diversity of data available on the internet that can be used in marketing is a real challenge. In this work, the main goal is to determine the degree of opportunities, challenges and research questions that arise with the emergence of Big Data. It also concludes that Big Data processing enables the marketing secto...

The research aims to study the effects of economic policy uncertainty on the return volatility of stocks with data from the largest banking institutions in Greece. Volatility is constructed using intraday data, whereas the research period extends over a period of about thirteen years, more specifically from January 5, 2001, to June 30, 2014. This p...

In this research paper we focus on the problems concerning inmates' access to education through Second Chance Schools operating within penitentiaries due to the Covid-19 pandemic. A specially encrypted platform has been created through open-source software that can provide distance learning and does not allow access to any part of the internet othe...

The purpose of this research paper is to investigate the challenges of education that arose among learnersof second chance schools, Greek inmates during the pandemic. Offenders lost their right to equal access toeducation because they could not even use a specialized digital interconnection facility with the eLearningPlatform. Through open-source s...

The effects of the 2008 financial crisis undoubtedly caused problems not only to the banking sector but also to the real economy of the developed and the developing countries in almost all around the globe. Besides, as is widely known, every banking crisis entails the corresponding cost to the economy of each country affected by it, which results f...

Instagram, a social networking application for sharing multimedia files, started in 2010. Today, it has 800 million active monthly users, resulting in 70 million Postswith Photos and Videos every day. People interact with each of these posts by commenting using text/symbols andhashtags. All this activity generates a huge amount of data, called them...

The Cloud Computing is a technology that will totally dominate in the future. Companies such as Google, Microsoft, Amazon and others have invested heavily in new technological structure while increasingly focus their services to take advantage of the revolutionary Cloud Computing capabilities. There are many ways of how cloud computing is changing...

Nowadays there is a growing need for collecting and processing data from different sources in heterogeneous and semi-structured formats. Developing an intelligent recommendation system is a good way to overcome the problem of overloaded products information provided by the e-commerce enterprises. As there are a great number of products on the Inter...

The Pattern Recognition through Data Mining Techniques of the Historical Advertisements is an essential task within the digital documentation of cultural heritage. The classification is a tedious task and habitually consumes a lot of time if implements in a large number of advertising images stored in aKnowledge Data Base. The existence of automate...

Sentiment Analysis has been extensively investigated in recent years as a method of human emotions' classification to specific events, products, services etc. It is considered as a very important problem, especially for organizations or companies who want to know the consumers' view about their products and services. In combination with the evoluti...

We have suggested the creation of a Small Efficient Energy Production Systems with reduced cost. The idea was to integrate machining technology; microcontrollers and software in order to create Efficient Electricity Production with reduced cost. The machining technology permitted us to construct a teeterboard that could (turn / move and) follow the...

Not only in the field of education but also in many other forms of social expression and action, a period of fundamental changes can be observed due to the incorporation of new data imposed by the technological revolution. However, the process of integrating Information and Communication Technologies (ICT) in the learning process requires coordinat...

In this paper, we will explore some of the exciting use cases for IoT in logistics and cluster these within the bounds of warehousing operations and freight transportation. The Internet of Things (IoT) is a term coined to describe the communication between machine to machine through Internet connectivity. Utilizing this network infrastructure, logi...