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1.
A novel approach to aviation data links and data exchange between aircraft modules : doctoral dissertation
Ilija Subotić, 2023, doktorska disertacija

Opis: Aviation industry is a key driver of global economic development with over a third of all trade by value sent by air. It represents a highly significant global market with estimated revenue over 840 billion USD in 2023, while the industry directly and indirectly supports an estimated $3.5 trillion (4.1%) of the world's gross domestic product (GDP) through the jobs and services of air industry suppliers, employee spending and serving industries such as tourism. Due to increasing global air passenger demand, the global aviation industry is projected to grow by approximately 25% from 2022 to 2027. However, in some cases the operation of aircraft may still be reliant on outdated technology that could be years or even decades old. Due to safety concerns, the global system of civil aviation is one of the most regulated industries, and every new procedure, technological advancement or device is required to be thoroughly checked by licensed institutions, numerous experts and aviation regulatory authorities. This reasonable approach inevitably leads to difficulties when dealing with noticed problems in any particular field – whether these are flight operations, aircraft maintenance, corporate affairs or general compliance. One of these problems are aircraft communications and data transfers between aircraft and all other groundbased stations. Namely, apart from classical radio links for voice communications, digital radio links for data transmissions have been used for a few decades now. These are ACARS (Aircraft Communications, Addressing and Reporting System) and CPDLC (Controller-Pilot Data Link Communications). These aeronautical communications data links use HF/VHF links and, alternatively, over areas with no or with poor signal coverage, commercial data satellites. However, there are several fundamental problems with data link systems implemented this way. The first problem is that the authenticity of the messages being exchanged cannot be verified. Potential attackers can, without much effort, falsify messages or even pose as a legitimate air traffic control unit or an aircraft crew. Another problem lies in the available bandwidth for VHF data links and the possible maximum transmission speeds reachable: the data transmission speed of VHF channels is very low - usually around 15 Kbit/s, and the best achievable results barely exceed 30 Kbit/s. In addition, the third major problem is message delivery, which is not guaranteed to succeed. There were indeed cases when the sent message did not reach the desired destination or arrived after a long delay of even several minutes. Aside from the mentioned problems, there are still issues related to specific aspects of the used HF/VHF data transmission links, such as signal stability, switching between individual ground radio stations, signal coverage issues etc. Therefore, in this dissertation, the main motive is to explore alternatives and find ways to solve at least some of these problems. The research in this dissertation is based on the usage of the Internet for the transmission of messages, instead of the previous radio data links. During the research it was concluded that the cellular Internet connection, even in today's technically inadequate state in the means of aeronautical needs, meets the conditions to be used as a medium for CPDLC and ACARS connections at flight altitudes up to 10,000 ft. Another goal of the research is to consider and develop the possibility of integrating the CPDLC and ACARS systems into one platform, codenamed IACARP (Integrated Aeronautical Communications, Addressing and Reporting Platform), which would provide the possibility to increase the number of functions and capabilities of both systems. The third intention of the dissertation is to propose and develop a dedicated communication protocol, which will be based on the Internet as a medium for data transmission, which will allow the IACARP platform to use a protocol that is adapted for use in aeronautical operations. In addition to the communications protocol, the dissertation also provides a possible solution for the authentication problem of messages sent within the system, in a way that does not require encryption of those messages. The proposed solution represents a new algorithm for generating a special short code based on which the authenticity of the messages is confirmed. The possibilities of automatically sending individual reports from certain vital aircraft systems to the air traffic control units are also being considered, through the proposed IACARP system. This way of integrating the components yielded another possibility which is thoroughly considered, and that is the remote control of the aircraft by ATC units in cases of emergency situations. Remote control of the aircraft in this way can most likely be achieved since there is a significant number of aircraft equipped with systems that can land them automatically, without much human intervention. Hence, it would be enough to just remotely reprogram the FMC (Flight Management Computer), enter a new flight route that would initiate landing at a suitable airport, as well as to remotely monitor and control the state of vital aircraft systems by giving the appropriate command through the IACARP platform. As the final part of the dissertation, the conclusions and the decision to accept or reject the hypotheses are presented, along with some perspectives and ideas for further research in this area.
Ključne besede: aeronautical data links, cellular networks, CPDLC, ACARS, air traffic control, message authentication, dedicated communications protocol, doctoral dissertation
Objavljeno v ReVIS: 15.03.2024; Ogledov: 1142; Prenosov: 37
.pdf Celotno besedilo (13,29 MB)

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A decision support system for identity and access management : doktorska disertacija
Miljenko Hajnić, 2022, doktorska disertacija

Opis: Managing redeployment of employees is a complex and highly demanding process for a company’s decision-makers in the human resources department since it requires fast responsiveness, in particular when there is a huge amount of requests and activities required to answer the organizational needs. Redeployment requires multiple evaluations of employees and organizational units involving many attributes, such as education, skills, work experience, and distance from the workplace, to name a few. Consequently, every redeployment task causes a new cycle of granting new access rights to the company’s application software. Since the whole granting access procedure can take from several hours up to several days, depending on the number of IT administrators and the number of employees’ user accounts that have to be appropriately configured, the cost of employee redeployment is directly reflected through the overhead expense for employees while they wait for their user account to be updated, and in the meantime, the company’s income will be lower than the projected one. To address this problem, this doctoral thesis focuses on the importance of key service interoperability and the development of software components that enable the integration of the decision model with Human Resources Management software and Identity and Access Management software into the decision support system in order to increase the company’s efficiency and effectiveness. Key service interoperability was achieved by first developing a decision support model using the Decision EXpert (DEX) method. The developed DEX model was applied for a logical base in the development of the web-based application. We developed a custom web-based application that evaluates multiple entities at once and proposes several appropriate alternatives ranked by three novel algorithms that we developed for three different contexts of employee redeployments. Our web-based application is a software prototype designed for easy integration with other business applications involved in the process of employee redeployment. Finally, we performed several process simulations to conceptually test the possibility, feasibility and profitability of software improvements and integrations.
Ključne besede: decision support, decision expert, human resources, redeployment, identity and access management, doctoral dissertation
Objavljeno v ReVIS: 25.02.2022; Ogledov: 1818; Prenosov: 98
.pdf Celotno besedilo (2,31 MB)

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Automatic reconstruction of complex dynamical networks : doctoral dissertation
Marc Grau Leguia, 2019, doktorska disertacija

Opis: A foremost problem in network science is how to reconstruct (infer) the topology of a real network from signals measured from its internal units. Grasping the architecture of complex networks is key, not only to understand their functioning, but also to predict and control their behaviour. Currently available methods largely focus on the detection of links of undirected networks and often require strong assumptions about the system. However, many of these methods cannot be applied to networks with directional connections. To address this problem, in this doctoral work we focus at the inference of directed networks. Specifically, we develop a model-based network reconstruction method that combines statistics of derivative-variable correlations with simulated annealing. We furthermore develop a data-driven reconstruction method based on a nonlinear interdependence measure. This method allows one to infer the topology of directed networks of chaotic Lorenz oscillators for a subrange of the coupling strength and link density. Finally, we apply the data-driven method to multichannel electroencephalographic recordings from an epilepsy patient. The functional brain networks obtained from this approach are consistent with the available medical information.
Ključne besede: network reconstruction, simulated annealing, dynamical systems, nonlinear interdependence measure, EEG, doctoral dissertation
Objavljeno v ReVIS: 19.04.2019; Ogledov: 3348; Prenosov: 150
.pdf Celotno besedilo (6,96 MB)

5.
Improving governance in mandatory defined-contribution pension funds : case study of Croatia
Petar-Pierre Matek, 2018, doktorska disertacija

Opis: Demographic changes and other socio-economic factors put a strain on pension systems around the world. Developed countries are particularly affected by population aging and generous existing pay-as-you-go schemes. To achieve a more sustainable pension system, many countries introduced defined-contribution pension plans. The World Bank, which took a leading role in conceptual and operational aspects of pension reforms worldwide, provided support to many countries, including Croatia, in the implementation of its three-pillar model. At the same time, Anglo-Saxon countries witnessed a dramatic shift from defined-benefit to defined-contribution pension schemes. As a result, employees are bearing investment risk, meaning that their pension benefits directly depend on the investment performance of pension plans invested in capital markets. Consequently, issues related to the governance of defined-contribution pension plans have become a matter of concern for researchers and regulators worldwide. The main questions are: (1) whether a governance system can be created that will work for the benefit of fund members and (2) where should policy makers and pension supervisors focus their efforts. Because asset management is characterised by significant conflicts of interest and low observability of money managers% actions, agency theory provides an excellent theoretical framework for the research of governance issues in second pillar pension funds. It helps in identifying the stakeholders, describing their relationships and identifying where their interests are not aligned. Most importantly, it provides a framework for identifying the most suitable control mechanisms to curb conflicts of interest. Theory suggests that behaviour-based control mechanisms will be best adapted in the case of pension funds. Of importance are: (1) internal governance structure and mechanisms, including third-party monitors, (2) regulation and supervision and (3) duties and liabilities of the governing body. The definition of investment performance benchmarks is the most obvious outcome-based control mechanism. Information systems have an important role in increasing the monitoring capacity of stakeholders. Theory suggests that third-party monitoring, such as supervision by public agencies, is particularly important, because pension funds are characterised by a failure of market control mechanisms. In addition, the interpretation of money managers% fiduciary duties by courts of justice will have an extremely important impact on the credibility of regulatory and supervisory efforts. Legislation plays a leading role in the design of control-mechanisms. This is particularly the case in civil law jurisdictions that opted for a highly prescriptive approach to regulation. The case study of the Croatian second pillar pension funds is based on an analysis of the Croatian Act on Mandatory Pension Funds and its comparative analysis with the OECD Core Principles of Private Pension Regulation, the UCITS Directive and the IORP II Directive. It breaks down the provisions of these legislative acts and standards along the lines of the framework provided by the agency theory - namely, the information available to fund members, internal governance mechanisms, political pressures and tools available to the regulator (including liability of the managing body). Evidence from the research supports the hypothesis that the Croatian Act on Mandatory Pension Funds addresses in an adequate manner most of the governance issues related to the management of second pillar mandatory pension funds. Nevertheless, some deficiencies were revealed, and a list of recommendations was outlined. The application of agency theory to pension funds and the comparative analysis of legislative documents adds to the body of literature on second pillar pension funds by providing an innovative approach to the issue. It also provides guidelines for regulators introducing defined-contribution pension schemes or trying to improve existing ones.
Ključne besede: pension funds, governance, agency theory, World Bank, pension system, Croatia, doctoral dissertation
Objavljeno v ReVIS: 12.03.2019; Ogledov: 2522; Prenosov: 123
.pdf Celotno besedilo (1,41 MB)

6.
Multilevel complex systems approaches to computational linguistics : doctoral dissertation
Kristina Ban, 2018, doktorska disertacija

Opis: Complex systems are omnipresent in nature, society as well as in human culture. Last few decades saw an increase of interest for their study, particularly by using graph-theoretic methodologies. By identifying systems' units as nodes and modelling interactions between the units as links, the study of complex networks spread to a number of disciplines including sociology, biology and linguistics, to just mention a few. The research done in this doctoral dissertation falls in this context. The core of this doctoral work is the data-driven multilevel analysis of major human languages, which was done in two stages. First, we looked at the speed of growth of Wikipedias in 26 different languages over the span of 15 years. This involved creating and analysing a dataset with 14962 articles, each of which exists in all 26 languages. We found six well-defined clusters of Wikipedias that share common growth patterns, with their make-up robust against the method used for their determination. Interestingly, the identified clusters were found to have little correlation with the respective language families. Rather, our results suggest that growth of Wikipedias is primarily governed by an intricate set of other factors, from culture to information literacy. Second, to approach human languages at another independent level, we gathered a dataset comprising a list of syllables and a list of syllables words in 10 different languages, specifically: English, Dutch, German, Russian, Slovenian, Croatian, French, Spanish, Latin and Basque. These datasets were obtained from recognized repositories for each language and benchmarked in the same way. Syllable networks were created by looking at pairs of syllables that jointly compose at least one word. We then carried out a systematic network analysis, relying on both standard network analysis methods and more recent techniques, such as K-core analysis and graphlet statistics. Research revealed striking similarities between the architectures of syllable networks that belong to the same language family, along with expected differences between the families. Indeed, structures of syllable networks were found to well quantify the linguistic similarities among these 10 languages, exactly as known from classical linguistics. Most interestingly, we found that Basque language, whose classification is as of today still unknown, bares a strong resemblance to Latin, at least when syllable network representation is concerned. Earlier stages of this doctoral work involved comparing the performance of network alignment algorithms, used in bioinformatics for studying protein networks. Several alignment algorithms were compared by scoring their performance on standard protein datasets. It was found that three algorithms, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. Due to the change of doctoral adviser, this research topic was abandoned in favour of language/syllable networks. In sum, this doctoral work involved two distinct directions of research in network science, one related to developing the methodology of network analysis (alignment algorithms), and the other devoted to extracting new information from specifically designed datasets (syllable networks). Therefore, the original contribution of this work to science includes both theory and methodology. Future research avenues include advancement along both directions, most interesting being the application of network alignment methods to syllable datasets, which could reveal more precise quantification of structural differences among syllable networks.
Ključne besede: computational statistics, biostatistics, bioinformatics, machine learning, computational linguistics, doctoral dissertation
Objavljeno v ReVIS: 21.12.2018; Ogledov: 4235; Prenosov: 140
.pdf Celotno besedilo (17,51 MB)

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Sentiment based classification of the web texts : doctoral dissertation
Jože Bučar, 2017, doktorska disertacija

Opis: It has always been a challenging task to predict events in the near or distant future. People are interested in forecasting weather, earthquakes, floods, predicting economic, political and social changes, as well as the development of technology, sales products and sports outcomes. On the web, an enormous quantity of data is generated daily. We are practically deluged by all kinds of data - scientific, medical, financial, historical, health care, demographic, business, and other. Usually, there are not enough human resources to examine this data. However, from this chaotic cluster of data we strive to obtain valuable information, which may significantly impact strategic decisions of both business and individuals in the future. Predicting future trends and events has become easier and more efficient especially with the collaboration among scientists from various fields. Sentiment analysis of web texts is an interesting and relevant research topic in this field. The aim of research described in this dissertation was to create specific language resources for sentiment analysis in Slovene, evaluate performance of sentiment based classification techniques and monitor the dynamics of sentiment, especially for the purpose of improving and contributing to computational analysis of texts in Slovene. Here, we introduce the construction of Slovene web-crawled news corpora and a lexicon for sentiment analysis in Slovene. Besides their availability, we describe the methodology and the tools that were required for their construction. The corpora contain more than 250,000 documents with political, business, economic and financial content from five Slovenian media resources on the web that were published between 1st of September 2007 and 31st of January 2016. They include sentiment annotation on three levels of granularity: sentence, paragraph and document level. More than 10,000 of them were manually annotated as positive, negative or neutral. A Slovene sentiment lexicon, which is based on the annotated documents, contains more than 25,000 words with sentiment ratings, and is the first of this kind for Slovene. In detail, we describe the construction of these language resources, the manual annotation process and its characteristics. All developed resources are publicly available under Creative Commons copyright license. We used the annotated documents to assess the sentiment classification approaches. Experimental performance evaluation of sentiment based classification techniques gives encouraging results. When classifying documents, in terms of time consumption and performance, the Multinational Naive Bayes and the Support Vector Machines approaches outperform the other classifiers. Also, consideration of smaller text segments, such as sentences, improves the performance. Models achieve F1-score value of 97,85 % within the two-class (positive and negative) and 77,76 % within the three-class (positive, negative and neutral) document-level sentiment based classification. The sentiment analysis methodology was successfully used in the real-world applications for estimating the proportions of positive, negative and neutral news in the selected web media, and for monitoring the dynamics of sentiment. When estimating the proportions of positive, negative and neutral news, approximately half of the retrieved news is neutral. In general, the proportion of negative news is twice as high as the proportion of positive news. The study of sentiment dynamics shows that sentiment is on average more explicit at the beginning of documents and loses sharpness towards the end.
Ključne besede: news corpus, sentiment analysis, lexicon, corpus linguistics, machine learning, document classification, monitoring sentiment dynamics, doctoral dissertation
Objavljeno v ReVIS: 22.08.2018; Ogledov: 4367; Prenosov: 209
.pdf Celotno besedilo (4,05 MB)

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Future knowledge and process pattern recognition in weakly defined organizational formations : doctoral dissertation
Jernej Agrež, 2016, doktorska disertacija

Opis: Customer knowledge as an influence on service provider’s business processes during emergencies is an interesting and relevant research topic. The aim of this research was to identify possible emergency response process improvements based on existing learning processes, and possible future knowledge exchange improvements. I reached the predefined objective, i.e. to identify how customer knowledge influences providers’ business processes and consequently triggers social impact, by conducting extensive work on all five parts of the thesis. I confirmed that the customer-provider relation based on customer knowledge exists and appears in several different forms. Finally, I identified possible improvements of the research and possibilities for further research by applying the designed methodological framework network analysis on a broader geographical scale. A significant contribution of this thesis is the integration of three fields of management: business process management, knowledge management, and disaster management. The research focuses on identifying knowledge-based customer-provider relations by emphasizing customer knowledge as an influence on provider’s business processes and possible consequential social impact. By studying these relations, I went beyond the usual comfort zone of conventional formal organizations and employed a loosely coupled system which emerges as a flood response mechanism during flood events.
Ključne besede: business process management, knowledge management, disaster management, public safety, loosely coupled systems, customer knowledge, flood events, doctoral dissertation
Objavljeno v ReVIS: 22.08.2018; Ogledov: 3006; Prenosov: 158
.pdf Celotno besedilo (5,32 MB)

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