35th Bled eConference Digital Restructuring and Human (Re)action : June 26 – 29, 2022, Bled, Slovenia, Conference Proceedings
Abstract: The Bled eConference, organised by the University of Maribor, Faculty of Organizational Sciences, has been shaping electronic interaction since 1988. After 2 years COVID-19 pandemic, when the conference was held online, this year we met again in Bled, Slovenia. The theme of the 35th conference is "Digital Restructuring and Human (re)Action". During the pandemic, we experienced the important role of digital technologies in enabling people and enterprises to interact, collaborate, and find new opportunities and ways to overcome various challenges. The use of digital technologies in these times has accelerated the digital transformation of enterprises and societies. It will be important to leverage this momentum for further implementation and exploitation of digital technologies that will bring positive impacts and solutions for people, enterprises and societies. The need to achieve sustainability goals and sustainable development of society has increased. Digital technologies will continue to play an important role in achieving these goals. The papers in this conference proceedings address digital transformation of enterprises, digital wellness and health solutions, digital ethics challenges, artificial intelligence and data science solutions, new and digital business models, digital consumer behaviour and solutions, including the impact of social media, restructuring of work due to digital technologies, digital education challenges and examples, and solutions for smart sustainable cities.
Keywords: Digital transformation, digital business, digital technologijes, innovations, digitalization, sustainable development, smart and sustainable cities and societies, digital health and wellness, artificial intelligence and data science, digital ethics, digital education, restructured work, digital consumer, social media
Published in DKUM: 23.06.2022; Views: 165; Downloads: 19
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AI for optimizing analog RF parameters on NFC frontends : magistrsko deloMatej Žnidarič
, 2022, master's thesis
Abstract: In this Master’s thesis, we study in detail NFC technology, NFC standardization, Artificial intelligence and GUI topics.Our goal is to optimize the measurement process of the FeliCa listener phase window in order to define the best analog parameters for the NFC IC. Namely, by combining machine learning and test automation, we want to achieve a faster validation time of the NFC IC under test. Firstly, we introduce the main topics related to NFC and present the thesis alongside specific goals. Next, we present the NFC technology on a fewuse cases. We also cover international standards, emphasizing sections that directly affect our validation and, therefore, the understanding of our solution. The NFC coverage is described alongside data representation used to interpret data used in proprietary software. Artificial intelligence is integrated into this software for multidimensional data interpolation task. We also cover the basics of deep neural networks and the most common architectures used in the DL field. The neural network training process is also covered to understand how we can optimize neural network global minimum convergence. In the last part of the thesis, we also explain how proprietary software tool actually works and how it can outperform previous processes. In the end, specific solutions related to the tool are described in more detail to understand our software development decisions better. Finally, we present measurement results and evaluate our goals.
Keywords: NFC wireless communication, artificial intelligence, test coverage, FeliCa, graphical user interface, analog parameter extraction
Published in DKUM: 08.06.2022; Views: 344; Downloads: 0
Perspectives of artificial intelligence in judiciary: application in selected parts of civil proceedings : application in selected parts of civil proceedingsMariia Sokolova
, 2021, master's thesis
Abstract: The master’s thesis is devoted to the issue of Artificial Intelligence (AI) perspectives in the judiciary, in particular, its application to selected parts of civil proceedings.
AI affects virtually the future of every industry and every human being. The application of AI technologies in the legal industry is an issue of growing interest. In particular, attention is drawn to the judicial system due to the fact that, apart from its position of guarantor of justice in society enabling its members to enjoy their rights and freedoms granted by law, it is a service of its nature.
Almost all leading jurisdictions apply AI systems in attempts to enhance the efficiency of the court proceedings. Without any doubts, AI already and successfully can imitate activities traditionally performed by humans in the courts: from vision, recognising and extracting information, whether from the document, picture or natural speech, to analysing of information received and predicting the outcomes or decision-making.
However, it is hard to say that AI-era in the judiciary has already begun. There is no jurisdiction in the world in which AI is fully given ‘green light’- they are all at the beginning of the AI-journey. That is mostly due to the fact that the same technical specifications, which power achievements, accuracy and flexibility of AI, place serious limitations for the wide application thereof. First of all, AI systems rely on data, which can be biased or spoiled in another way initially or easily manipulated later. Secondly, AI systems are not transparent (black-box-problem) and, as a result, are incomprehensible. These two shortcomings place an obstacle for the correct realisation of some fundamental rights in civil proceedings in their traditional understanding, and consequently, for the wide deployment of AI systems therein.
It is concluded that the application of AI in the judiciary, in general, and in the civil proceedings, in particular, is subject of sufficient limitations mostly due to incompliance of AI systems with the traditional understanding of fundamental rights and principles the civil proceedings stand on. In the pursuit of the effectiveness of judiciary by means of AI application, fundamental guarantees can appear at stake, and vice versa, in the pursuit of respect of fundamental rights, the judiciary may be left out of the modern world in the stage of complete inadequacy to the needs of the society, therefore, the issue is required extensive research in order to find a fair and right balance.
Keywords: artificial intelligence, judiciary, civil proceedings, AI-judge, efficiency of the judiciary, automatic decision-making
Published in DKUM: 24.09.2021; Views: 338; Downloads: 64
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Proceedings of the 2021 7th Student Computer Science Research Conference (StuCoSReC)
Abstract: The 7th Student Computer Science Research Conference is an answer to the fact that modern PhD and already Master level Computer Science programs foster early research activity among the students. The prime goal of the conference is to become a place for students to present their research work and hence further encourage students for an early research. Besides the conference also wants to establish an environment where students from different institutions meet, let know each other, exchange the ideas, and nonetheless make friends and research colleagues. At last but not least, the conference is also meant to be meeting place for students with senior researchers from institutions others than their own.
Keywords: student conference, computer and information science, artificial intelligence, data science, data mining
Published in DKUM: 13.09.2021; Views: 510; Downloads: 67
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Implementation of a new reporting process in a group xSara Črešnik
, 2021, master's thesis
Abstract: Reporting is present in every company. Whether it is small or big, it cannot be avoided. It plays a crucial role in the process and progress of business. The quality of reporting affects the development of the work environment and the company. Since business report is a document that contains business information, which supports the decisions about the future-oriented business decisions, it is very important for it to be designed in such a way that it contains the key information for the recipient and provides support for business decisions. The reporting process can take place horizontally upwards or downwards. Content and structure vary depending on the recipient of the report. We live in an age when our every step is accompanied by digitization, computerization, artificial intelligence, mass data, the Internet of Things, machine learning, and robotics. These changes have also affected the reporting process as well as its processes. The processes of data acquisition, processing and sharing have changed. Furthermore, the data quantity has increased, whereas the speed of the time in which to prepare the reports has decreased. We can have data without information, but we cannot have information without data. There is never enough time, especially nowadays when we are used to having everything at our fingertips. These are two conflicting factors – having more data and less time to prepare quality reports. The systems are developed to optimize the process, increase efficiency and quality and, what is nowadays most important, they have been created to obtain mass data in the shortest possible time. Therefore, it is important to adapt and implement software that can help achieve our daily tasks. We must know how to process huge amounts of real-time data and deliver the information they contain. It is crucial for companies to keep up with the environment and implement changes and innovations into their business process. A company is like a living organism for it must constantly evolve and grow. As soon as it stops growing and evolving, it can fail because it starts lagging and is therefore no longer competitive to others. To deliver faster feedback, companies need data of better quality. There are tools that can improve the business process, better facilitating the capacity of the human agents. The goal is to harness the employees’ full potential and knowledge for important tasks, such as analyzing, reviewing, and understanding data and acting upon them, invoking information technology to automate repetitive processes and facilitate better communication.
The focus in this master’s thesis is on the reporting process in Group X. Group X is one of the world leaders in the automotive industry, a multinational corporation based in Canada with subsidiaries around the world. The complexity of the business reporting that is implemented for the Headquarters in Canada has to address the complexity of the multinational corporation to support the decision process.
The aim of the thesis is to propose a reporting process for preparing and producing reports with a huge amount of data in a very time-efficient manner. We start by examining the existing processes and upon that, identifying the processes required for the reports to reach the final recipients. Our goal is to identify the toolset, which would increase efficiency, accuracy, credibility, and reduce errors in the fastest possible time. We investigate a short-term and a long-term solution. By a short-term solution, we mean a system, program, or a tool that can help us increase our potential by using digital resources, which are already existing in the organization. By a long-term solution, we mean a solution, which requires employment of specialized future tools in the field of reporting and in repetitive processes, which we can identify with current knowledge and expectations for development. This includes machine learning, robotic process automatization, artificial intelligence.
Keywords: Consolidated reporting, reporting process, robotic process automatization, business intelligence, artificial intelligence, machine learning, SharePoint, Big Data, digital transformation, electronic data interchange.
Published in DKUM: 01.09.2021; Views: 376; Downloads: 3
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Nature-inspired algorithms for hyperparameter optimization : magistrsko deloFilip Glojnarić
, 2019, master's thesis
Abstract: This master thesis is focusing on the utilization of nature-inspired algorithms for hyperparameter optimization, how they work and how to use them. We present some existing methods for hyperparameter optimization as well as propose a novel method that is based on six different nature-inspired algorithms: Firefly algorithm, Grey Wolf Optimizer, Particle Swarm Optimization, Genetic algorithm, Differential Evolution, and Hybrid Bat algorithm. We also show the optimization results (set of hyperparameters) for each algorithm and we present the plots of the accuracy for each combination and handpicked one. In discussion of the results, we provide the answers on our research questions as well as propose ideas for future work.
Keywords: artificial intelligence, artificial neural networks, machine learning, nature-inspired algorithms, evolutionary algorithms
Published in DKUM: 09.12.2019; Views: 1119; Downloads: 90
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Artificial intelligence versus human talents in learning processJanez Bregant
, Boris Aberšek
, 2011, original scientific article
Abstract: To highlight the differences between conventional educational systems and CBLS - computer based learning systems. It is useful to consider CBLS, as the class of a system most closely related to artificial intelligence - AI. In such a system, the ultimate goal is to create a virtual duplicate of reality for learning, analysis, training, experimentation, or other purposes. Simulating reality is an approach that may or may not be useful at creating experience. This distinction yield several consequences. In CBLS, behaviour should be as realistic as possible, the representation of environment tends to be uniform and consistent and allowing users to act freely within that environment.
To teach users through realistic experience CBLS design techniques can make the experience much more memorable. In such an environment the context and control afforded by design techniques allow the integration of technologies and evaluation of the overall experience. Perhaps it is time to take lessons of CBLS and AI in a learning design and teaching tools seriously.
At the beginning we will point out one simple question: could the ideas, methodology and techniques of AI also be applied to a development of relatively serious mind applications and can they substitute human teachers? And the answer will be continued in our paper.
Keywords: education, intelligent tutors, artificial intelligence, CBLS
Published in DKUM: 12.12.2017; Views: 959; Downloads: 77
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Advances in production and industrial engineering
2017, scientific monograph
Abstract: This publication, scientific monograph, offers comprehensive chapter series from scientific researchers conducted by regional authors, authorities in the fields and summarizes the principal scientific contributions. The chapters deal with range topics from optimization techniques in production development, quality in production processes, product and process development, technologies for business development and factors of social and economic development. Edited by two editors with contributions from chapters’ authors, this scientific monograph presents advanced topics for students, educators and practitioners. The editors would like to thank all chapters’ authors for devoting of the research results and expertise with the great enthusiasm. We encourage all of them to continue successful highly valuable cooperation, between Faculty of Mechanical Engineering at the University of Maribor and Faculty of Mechanical Engineering at the Ss. Cyril and Methodius University in Skopje.
Keywords: mechanical engineering, production management, manufacturing, artificial intelligence, process development, economic development
Published in DKUM: 19.07.2017; Views: 1023; Downloads: 348
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Intelligent design and optimization of machining fixturesDjordje Vukelić
, Goran Šimunović
, Branko Tadic
, Borut Buchmeister
, Tomislav Šarić
, Nenad Simeunovic
, 2016, original scientific article
Abstract: This work presents an integral system for machining fixture layout design and optimization. The optimization module of this system allows determination of optimal positions of locating and clamping elements, which provides required accuracy and surface quality, while at the same time guarantees design of collision-free fixtures. The design module performs selection of required fixture elements based on a set of predefined production rules. Adequate criteria for the selection of fixture elements are defined for locating, clamping, tool guiding, and tool adjustment elements, as well as for fixture body elements, connecting elements and add-on elements. The system uses geometry and feature workpiece characteristics, as well as the additional machining, and process planning information. It has been developed to accommodate machining processes of turning, drilling, milling, and grinding of rotational and prismatic workpieces. A segment of output results is also shown. Finally, conclusions are presented with directions for future investigation.
Keywords: artificial intelligence, fixture, process planning
Published in DKUM: 12.07.2017; Views: 813; Downloads: 329
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