Digital technologies and tools - drivers of digitalization in construction

Construction is a structural sector that creates the infrastructure for the functioning of other sectors, which is why its development is essential for the national economy. For this reason, the digitalization of construction is paramount. It is characterized by great complexity of production processes and typical conservatism, which is why it is known for its difficulties in the transition to digitalization. Digital technologies and tools are the engines of digitalization in construction. The paper explores the importance of some key technologies and tools for its digitization– first, the role of building information modeling, along with the application of virtual, augmented, and mixed reality, mobile technologies, and cloud computing. Sensors and other tools and technologies belonging to the Internet of Things, as well as the use of drones, have great potential for revolutionizing the construction sector. Artificial Intelligence and Machine Learning help analyze large amounts of data in construction and help make timely, accurate and efficient decisions. The study highlights the importance of resources as basis for the digitalization of construction with focus on human resources

Performance evaluation of machine learning models for credit risk prediction

The purpose of this research paper is to propose an approach for calculating the optimal threshold for predictions generated by binomial classification models for credit risk prediction. Our approach is considering the cost matrix and cumulative profit chart for setting the threshold value. In the paper we examine the performance of several models trained with homogeneous (Random Forest, XGBoost, etc.) and heterogeneous (Stacked Ensemble) ensemble classifiers. Models are trained on data extracted from Lending Club website. Different evaluation measures are derived to compare and rank the fitted models. Further analysis reveals that application of trained models with the set according to the proposed approach threshold leads to significantly reduced default loans ratio and at the same time improves the credit portfolio structure of the Peer-to-Peer lending platform. We evaluate the models performance and demonstrate that with machine learning models Peer-to-Peer lending platform can decrease the default loan ratio by 8% and generate profit lift of 16%

Exploiting the knowledge engineering paradigms for designing smart learning systems

Knowledge engineering (KE) is a subarea of artificial intelligence (AI). Recently, KE paradigms have become more widespread within the fields of smart education and learning. Developing of Smart learning Systems (SLS) is very difficult from the technological perspective and a challenging task. In this paper, three KE paradigms, namely: case-based reasoning, data mining, and intelligent agents are discussed. This article demonstrates how SLS can take advantage of the innovative KE paradigms. Therefore, the paper addresses the pros of such smart computing approaches for the industry of SLS. Moreover, we concentrate our discussion on the challenges faced by knowledge engineers and software developers in developing and deploying efficient and robust SLS. Overall, this study introduces the reader the KE techniques, approaches and algorithms currently in use and the open research issues in designing the smart learning systems.Инженерия знаний (ИЗ) – это подобласть искусственного интеллекта (ИИ). В последнее время парадигмы ИЗ и умных вычислений получают все более широкое распространение в сфере умного образования и обучения. Разработка систем умного обучения (СУО) является очень трудной с технологической точки зрения и сложной задачей. В данной статье мы изучили три парадигмы ИЗ, а именно рассуждения на основе прецедентов, интеллектуальный анализ данных и интеллектуальные агенты. Наше исследование указывает на то, что такие парадигмы могут эффективно использоваться для СУОІнженерія знань (ІЗ) – це пiдобласть штучного інтелекту (ШІ). Останнім часом парадигми ШІ та розумних обчислень отримують все більш широке поширення в сферi розумної освіти i навчання. Розробка систем розумного навчання (СРН) є дуже важким з технологічної точки зору і складним завданням. У даній статті ми вивчили три парадигми ШІ, а саме міркування на основі прецедентів, інтелектуальний аналіз даних та інтелектуальні агенти. Наше дослідження вказує на те, що такі парадигми можуть ефективно використовуватися для СР

CARD-NOT-PRESENT FRAUD – CHALLENGES AND COUNTERACTIONS

Due to the rapid development of electronic commerce, the percentage of card-not-present payments over the Internet and fraud related to these, have increased. The relative importance of card-not-present fraud (CNPF) has increased permanently on a global and European scale mainly due to the gradual solution to problems connected with the protection of cardpresent transactions through the transition to the EMV chip standard and transfer of fraud to more vulnerable card-not-present transactions in which it is difficult to verify the identity of the cardholder in a reliable way. For the protection of card transactions it is necessary to take adequate measures by introducing common harmonized compulsory minimum security requirements across the EU. First, we propose these equirements to include methods for checking the authentication of users. We consider the 3-D Secure Protocol in a version with dynamic authentication the most suitable method because in the EU many steps towards its implementation have already been made. This is of great importance for the systems used by banks and merchants for the prevention of card-not-present fraud and for detecting and blocking of fraudulent transactions

Electronic Banking in Bulgaria – State and Perspectives

The aim of this publication is making analyses and evaluation of the current situation of the electronic banking, offered by the commercial banks in Bulgaria, and to draw the perspectives of its future development. A detailed inquiry was made of the basic forms of the electronic banking – telephone, PC-, Internet and GSM-banking, offered by the commercial banks. The distribution of electronic channels was evaluated according to several criteria: type of clients, subject of the definite channel (juridical and physical persons); operations (informational or active), to which access is allowed and level of expenses for getting the service; way of stimulating the consumers of electronic channels in comparison with those of the classic channel (i.e. banking on a desk), level of security and protection, guaranteed by the systems for electronic banking. As a result of the analyses some conclusions were reached regarding the situation on the Bulgarian banks’ market in regard of offering of different forms of electronic banking and were shown the perspectives for their future development. The Internet banking, offered by 56% of the banks, and the GSM-banking, the access to which for the moment is hardly reachable prove to be with the biggest potential.

Social Media Usage Patterns in Higher Education Institutions – An Empirical Study

The main goal of this research is to identify some notable trends, opportunities and limitations regarding the application of social media in higher education based on studying the way students use social media during their education. The re-search is focused on the impact of social media on the process of learning, creation and distribution of education related content, as well as on education related communication. The target groups of the research are students in University of Economics Varna enrolled in different bachelor and master programs. An association analysis was implemented to identify the most common pat-terns regarding the application of social media in the education process. Statistical methods for testing hypothesis were used to assess the relationship between students’ specialty and derived social media patterns. The findings show that Facebook groups are а preferable social media tool for communication with colleagues, content sharing and distribution, while wikis and university Learning Management Systems (LMSs) are most used for content creation and additional learning. Some social media channels are more preferable for content creation and additional learning compared to scientific databases and e-books. Following the research results a conclusion can be drawn regarding the leading part of the students in initiating the use of social media compared to the relatively smaller role of the academic staff in this process. A medium to small relationships were discovered between students’ specialty and the application of con-tent sharing communities and forums in knowledge process with students in computer science more likely to use these social media types compared to students in economics

Use of Social Media in Higher Education Institutions – an Empirical Study Based on Bulgarian Learning Experience

Social media have enormous power and trigger changes in whole spectrum of businesses, as well as learning and education. A study of students’ adoption of social media at the University of Economics – Varna (UE-Varna), Bulgaria, has proven its significant impact on young people. Using online questionnaire among 378 students, the high popularity of social media has been confirmed. An important research question is whether higher education institutions teaching students mainly in the fields of social, economic and legal sciences use the benefits of the social media in the context of Learning Management Systems (LMSs) and integrated social media tools. The majority of the examined 24 universities use two LMSs - Moodle and Blackboard Learn. Both possess tools like forums, chat, wikis, internal messaging, blogs, learning groups, collaboration tools. The study of the two Moodle platforms implemented at the UE-Varna shows use of discussion forums, chat, and internal messaging

Exploiting the Knowledge Engineering Paradigms for Designing Smart Learning Systems

Knowledge engineering (KE) is a subarea of artificial intelligence (AI). Recently, KE paradigms have become more widespread within the fields of smart education and learning. Developing of Smart learning Systems (SLS) is very difficult from the technological perspective and a challenging task. In this paper, three KE paradigms, namely: case-based reasoning, data mining, and intelligent agents are discussed. This article demonstrates how SLS can take advantage of the innovative KE paradigms. Therefore, the paper addresses the pros of such smart computing approaches for the industry of SLS. Moreover, we concentrate our discussion on the challenges faced by knowledge engineers and software developers in developing and deploying efficient and robust SLS. Overall, this study introduces the reader the KE techniques, approaches and algorithms currently in use and the open research issues in designing the smart learning systems

Attractiveness of Collaborative Platforms for Sustainable E-Learning in Business Studies

E-learning platforms have become more and more complex. Their functionality included in learning management systems is extended with collaborative platforms, which allow better communication, group collaboration, and face-to-face lectures. Universities are facing the challenge of advanced use of these platforms to fulfil sustainable learning goals. Better usability and attractiveness became essential in successful e-learning platforms, especially due to the more intensive interactivity expected from students. In the study, we researched the user experience of students who have used Moodle, Microsoft Teams, and Google Meet. User experience is, in most cases, connected with a person’s perception, person’s feelings, and satisfaction with the platform used. Data were collected using a standard UEQ questionnaire. With this research, we examined whether user experience factors: perceived efficiency, perceived perspicuity, perceived dependability, perceived stimulation, and perceived novelty affect perceived attractiveness, which is an important factor in the sustainability of e-learning tools. The collected data were processed using SmartPLS. The research study showed that all studied factors have a statistically significant impact on perceived attractiveness. Factor perceived stimulation has the strongest statistically significant impact on the perceived attractiveness of e-learning platforms, followed by perceived efficiency, perceived perspicuity, perceived novelty, and perceived dependability