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The essential facilities doctrine, intellectual property rights, and access to big data
Rok Dacar, 2023, izvirni znanstveni članek

Opis: This paper analyzes the criteria for applying the essential facilities doctrine to intellectual property rights and the possibility of applying it in cases where Big Data is the alleged essential facility. It aims to answer the research question: ‘‘What are the specifics of the intellectual property criteria in essential facilities cases and are these criteria applicable to Big Data?’’ It points to the semantic openness of the ‘‘new product’’ and ‘‘technical progress’’ conditions that have been developed for assessing whether an intellectual property right constitutes an essential facility. The paper argues that the intellectual property criteria are not applicable in all access to Big Data cases because Big Data is not necessarily protected by copyright. While a set of Big Data could be protected by copyright if certain conditions are met, even in such cases the lack of intrinsic value of Big Data significantly limits the applicability of the intellectual property criteria.
Ključne besede: essential facilities doctrine, intellectual property rights, big data, new product condition, technical progress condition
Objavljeno v DKUM: 11.04.2024; Ogledov: 39; Prenosov: 2
.pdf Celotno besedilo (318,47 KB)
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Applying integrated data envelopment analysis and analytic hierarchy process to measuring the efficiency of tourist farms : The Case of Slovenia
Boris Prevolšek, Maja Borlinič Gačnik, Črtomir Rozman, 2023, izvirni znanstveni članek

Opis: This paper examines the efficiency of tourist farms in Slovenia by adopting an approach using a framework of non-parametric programming—Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP), combining the two because the DEA analysis by itself does not take into account all attributes, especially qualitative ones. The beforementioned two methods rank the farm tourism units with respect to their efficiency. By using the DEA method, an input- and output-oriented BCC and CCR model were introduced to upgrade the criteria by including the additional non-numerical criteria of the AHP. The results of the models showed that there are possible improvements on all levels of efficiency, as well as on the criteria of the additional offer of tourist farms, which were analyzed in the AHP model with additional criteria. According to the estimated efficiency, the ranking of tourist farms differed according to the two methods. Within the group of farms assessed as efficient by DEA, the AHP model allowed a more accurate ranking.
Ključne besede: farm tourism, tourist farms, efficiency, data envelopment analysis (DEA), analytic hierarchy process (AHP), Slovenia
Objavljeno v DKUM: 09.04.2024; Ogledov: 55; Prenosov: 4
.pdf Celotno besedilo (1,06 MB)
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CNN-Based Vessel Meeting Knowledge Discovery From AIS Vessel Trajectories
Peng Chen, Shuang Liu, Niko Lukač, 2023, izvirni znanstveni članek

Opis: How to extract a collection of trajectories for different vessels from the raw AIS data to discover vessel meeting knowledge is a heavily studied focus. Here, the AIS database is created based on the raw AIS data after parsing, noise reduction and dynamic Ramer-Douglas-Peucker compression. Potential encountering trajectory pairs will be recorded based on the candidate meeting vessel searching algorithm. To ensure consistent features extracted from the trajectories in the same time period, time alignment is also adopted. With statistical analysis of vessel trajectories, sailing segment labels will be added to the input feature. All motion features and sailing segment labels are combined as input to one trajectory similarity matching method based on convolutional neural network to recognize crossing, overtaking or head-on situations for each potential encountering vessel pair, which may lead to collision if false actions are adopted. Experiments on AIS data show that our method is effective in classifying vessel encounter situations to provide decision support for collision avoidance.
Ključne besede: AIS Data, CNN, Dynamic Rammer-Douglas-Peucker, knowledge discovery, maneuvering pattern, traffic pattern, trajectory
Objavljeno v DKUM: 19.03.2024; Ogledov: 95; Prenosov: 3
.pdf Celotno besedilo (3,84 MB)
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Agile Machine Learning Model Development Using Data Canyons in Medicine : A Step towards Explainable Artificial Intelligence and Flexible Expert-Based Model Improvement
Bojan Žlahtič, Jernej Završnik, Helena Blažun Vošner, Peter Kokol, David Šuran, Tadej Završnik, 2023, izvirni znanstveni članek

Opis: Over the past few decades, machine learning has emerged as a valuable tool in the field of medicine, driven by the accumulation of vast amounts of medical data and the imperative to harness this data for the betterment of humanity. However, many of the prevailing machine learning algorithms in use today are characterized as black-box models, lacking transparency in their decision-making processes and are often devoid of clear visualization capabilities. The transparency of these machine learning models impedes medical experts from effectively leveraging them due to the high-stakes nature of their decisions. Consequently, the need for explainable artificial intelligence (XAI) that aims to address the demand for transparency in the decision-making mechanisms of black-box algorithms has arisen. Alternatively, employing white-box algorithms can empower medical experts by allowing them to contribute their knowledge to the decision-making process and obtain a clear and transparent output. This approach offers an opportunity to personalize machine learning models through an agile process. A novel white-box machine learning algorithm known as Data canyons was employed as a transparent and robust foundation for the proposed solution. By providing medical experts with a web framework where their expertise is transferred to a machine learning model and enabling the utilization of this process in an agile manner, a symbiotic relationship is fostered between the domains of medical expertise and machine learning. The flexibility to manipulate the output machine learning model and visually validate it, even without expertise in machine learning, establishes a crucial link between these two expert domains.
Ključne besede: XAI, explainable artificial intelligence, data canyons, machine learning, transparency, agile development, white-box model
Objavljeno v DKUM: 14.03.2024; Ogledov: 109; Prenosov: 5
.pdf Celotno besedilo (5,28 MB)
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Implementation of acoustic data link technology in industries : diplomsko delo
Simon Srebot, 2023, diplomsko delo

Opis: The main topic of this bachelor's thesis is the implementation of Acoustic Data Link (ADL) in the industry, where the aim is to find suitable industrial applications where the implementation of ADL would be feasible and expedient. The thesis is based on a six-month Product Innovation Project hosted by the Institute of Industrial Management at the Graz University of Technology and in cooperation with TDK Corporation, where our international team of students were given the challenge of exploring possible industrial applications of ADL. The bachelor's thesis includes the description, composition and explained operation of ADL technologies as well as other similar technologies. It also includes the comparison between existing technologies and ADL, idea generation methods for possible applications and research results for each use case of the technology. The thesis concludes with a comparison of possible ADL implementations and their market research.
Ključne besede: Data Transfer, Acoustic Data Link, Piezo Elements, Radio Frequency Identification
Objavljeno v DKUM: 28.02.2024; Ogledov: 105; Prenosov: 5
.pdf Celotno besedilo (5,34 MB)

Privacy and data protection concerns in the regulatory framework of Slovenian energy law
Zoran Dimović, 2023, izvirni znanstveni članek

Opis: The implementation of smart energy systems (SES) in the Slovenian energy sector has raised significant privacy and data protection concerns. The collection and processing of personal data from energy consumers, as well as cybersecurity threats, pose risks that must be addressed. The legal framework governing privacy and data protection in the energy field in Slovenia is based on the GDPR, ZOEE, ZVPot-1, ZVOP-2 and others, which impose significant obligations on entities processing personal data. To mitigate these risks, exact terminology must be used to implement privacy, data protection and also cybersecurity measures and ensure compliance with the legal framework.
Ključne besede: cybersecurity, data protection, energy law, green and digital transformation, privacy protection
Objavljeno v DKUM: 20.02.2024; Ogledov: 132; Prenosov: 7
.pdf Celotno besedilo (456,29 KB)
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LiDAR-Based Maintenance of a Safe Distance between a Human and a Robot Arm
David Podgorelec, Suzana Uran, Andrej Nerat, Božidar Bratina, Sašo Pečnik, Marjan Dimec, Franc Žaberl, Borut Žalik, Riko Šafarič, 2023, izvirni znanstveni članek

Opis: This paper focuses on a comprehensive study of penal policy in Slovenia in the last 70 years, providing an analysis of statistical data on crime, conviction, and prison populations. After a sharp political and penal repression in the first years after World War II, penal and prison policy began paving the way to a unique "welfare sanction system", grounded in ideas of prisoners' treatment. After democratic reforms in the early 1990s, the criminal legislation became harsher, but Slovenia managed to avoid the general punitive trends characterized by the era of penal state and culture of control. The authoritarian socialist regime at its final stage had supported the humanization of the penal system, and this trend continued in the first years of the democratic reforms in the 1990s, but it lost its momentum after 2000. In the following two decades, Slovenia experienced a continuous harshening of criminal law and sanctions on the one hand and an increasing prison population rate on the other. From 2014 onwards, however, there was a decrease in all segments of penal statistics. The findings of the study emphasize the exceptionalism of Slovenian penal policy, characterized by penal moderation, which is the product of the specific local historical, political, economic, and normative developments.
Ključne besede: LIDAR, robot, human-robot collaboration, speed and separation monitoring, intelligent control system, geometric data registration, motion prediction
Objavljeno v DKUM: 16.02.2024; Ogledov: 206; Prenosov: 17
.pdf Celotno besedilo (5,27 MB)
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Data sharing concepts : a viable system model diagnosis
Igor Perko, 2023, izvirni znanstveni članek

Opis: Purpose Artificial intelligence (AI) reasoning is fuelled by high-quality, detailed behavioural data. These can usually be obtained by the biometrical sensors embedded in smart devices. The currently used data collecting approach, where data ownership and property rights are taken by the data scientists, designers of a device or a related application, delivers multiple ethical, sociological and governance concerns. In this paper, the author is opening a systemic examination of a data sharing concept in which data producers execute their data property rights. Design/methodology/approach Since data sharing concept delivers a substantially different alternative, it needs to be thoroughly examined from multiple perspectives, among them: the ethical, social and feasibility. At this stage, theoretical examination modes in the form of literature analysis and mental model development are being performed. Findings Data sharing concepts, framework, mechanisms and swift viability are examined. The author determined that data sharing could lead to virtuous data science by augmenting data producers' capacity to govern their data and regulators' capacity to interact in the process. Truly interdisciplinary research is proposed to follow up on this research. Research limitations/implications Since the research proposal is theoretical, the proposal may not provide direct applicative value but is largely focussed on fuelling the research directions. Practical implications For the researchers, data sharing concepts will provide an alternative approach and help resolve multiple ethical considerations related to the internet of things (IoT) data collecting approach. For the practitioners in data science, it will provide numerous new challenges, such as distributed data storing, distributed data analysis and intelligent data sharing protocols. Social implications Data sharing may post significant implications in research and development. Since ethical, legislative moral and trust-related issues are managed in the negotiation process, data can be shared freely, which in a practical sense expands the data pool for virtuous research in social sciences. Originality/value The paper opens new research directions of data sharing concepts and space for a new field of research.
Ključne besede: hybrid reality, data sharing, systems thinking, cybernetics, artificial intelligence
Objavljeno v DKUM: 14.02.2024; Ogledov: 224; Prenosov: 6
.pdf Celotno besedilo (663,49 KB)
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LAPPD operation using ToFPETv2 PETSYS ASIC
Andrej Seljak, Marko Bračko, Rok Dolenec, Peter Križan, Andrej Lozar, Rok Pestotnik, Samo Korpar, 2023, objavljeni znanstveni prispevek na konferenci

Opis: Single photon sensitive detectors used in high energy physics are, in some applica-tions, required to cover areas the size of several m2, and more specifically in very strong demand with an ever finer imaging and timing capability for Cherenkov Ring Imaging Detector (RICH) configurations. We are evaluating the Large Area Picosecond Photo-detector (LAPPD) produced by INCOM company, as a possible candidate for future RICH detector upgrades. In this work we perform tests on the second generation device, which is capacitively coupled to a custom designed anode back plane, consisting of various pixels and strips varying in size, that allows for connecting various readout systems such as standard laboratory equipment, as well as the TOFPET2 ASIC from PETsys company. Our aim is to evaluate what can be achieved by merging currently available technology, in order to find directions for future developments adapted for specific uses.
Ključne besede: data acquisition circuits, data acquisition concept, front-end electronics for detector readou, digital electronic circuits
Objavljeno v DKUM: 06.02.2024; Ogledov: 131; Prenosov: 7
.pdf Celotno besedilo (1,36 MB)
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