Intent-driven network management has become an important part of autonomous systems in Beyond 5G (B5G) towards Sixth-Generation (6G) networks, by enabling flexibility in the interaction among applications, operators and users. Intents play an important role in the communication of road users like autonomous vehicles and pedestrians to edge computing services. As sensor technologies for modern vehicles are cheaper, smaller, diverse and computing capable, more demand for applications and services on the road is increasing. A flexible intent interpretation and coordination are needed to deal with the dynamic environment and constantly changing goals. This paper presents a proof-of-concept of Zero-touch Network and Service Management (ZSM) for vehicular communication services, using an Intent Management Entity (IME) to translate user objectives into actionable directives. This paper describes a realistic testbed setup at the Smart Highway, where a Deep Reinforcement Learning (DRL) algorithm is used to optimize the selection of Roadside Units (RSUs) for service orchestration. This paper also discusses the challenges and opportunities of enhancing the IME with time-based intent coordination, using Artificial Intelligence and Machine Learning (AI/ML) techniques to estimate the waiting time and priority in intent coordination. The paper aims to demonstrate the benefits of ZSM and Intent-driven Management for vehicular edge computing and B5G/6G autonomous network management frameworks.

Network slicing enables multiple virtual networks to share physical resources, allowing network operators to deliver highly customizable and efficient networking solutions that meet the diverse requirements of modern applications. The automated management of network slices has been studied in the last years to make such solutions more flexible, ready to support new applications, and capable of optimizing network resource utilization. Many works in the literature give a top-down approach, focusing on the high-level decision processes, and relying on abstracted infrastructure managers and simulation tools to apply/execute such decisions. In this work, we leverage components that we previously developed for network monitoring, flexible traffic shaping, and Software-Defined Time-Sensitive Networking control, to create a bottom-up approach toward automated slice management. We describe the intricate coordination of elements required for an automated control loop and present the results achieved with a proof-of-concept executed in a real testbed of wired and Wi-Fi nodes. The results show the capability of the system to correctly identify the bottleneck of a flow and apply corrective actions to reestablish its intended performance level.

The challenge of ensuring safety in autonomous driving or sailing involves predicting and replicating various potential scenarios on roads and waterways, posing difficulties and high costs. In response, the European project 5G-Blueprint addresses this by introducing a complementary technology, i.e., teleoperation, which leverages 5G connectivity to enable human interventions in complex situations beyond autonomous capabilities, thereby removing the physical link between the human operator and the remotely controlled vehicle/vessel. This operational mode brings stringent connectivity requirements, including high uplink bandwidth for transmitting video streams from onboard cameras to the teleoperation center, low latency, and an ultra-reliable connection for relaying commands from the teleoperator to the remote vehicle/vessel. Additionally, it emphasizes minimal interruption time when the teleoperated vehicle/vessel crosses international borders, ensuring seamless connectivity and uninterrupted remote operation. Therefore, this paper summarizes extensive evaluations of network and service performance, highlighting key results across pilot locations and providing conclusions and analysis of 5G-enhanced teleoperation in various use cases. Additionally, it outlines lessons learned from pilot activities.

A generation of orthogonal signals in single-phase systems, crucial for various applications such as power converters synchronization, faces challenges in handling disturbances like DC offset and low order harmonics present in power grids. This paper presents an orthogonal signal generator based on the principles of adaptive noise canceller, offering immunity to low order harmonics and DC offset. By leveraging adaptive techniques, this novel generator surpasses traditional approaches, which lack disturbance rejection capabilities. Simulation results in MATLAB validate the performance and robustness of the proposed generator, marking a significant advancement in generating orthogonal signals for single-phase systems.

This study offers experimental testing of commercial and laboratory inverters, utilized in a laboratory prototype of an urban microgrid. Operation of grid inverters supplied by PV arrays in urban environments, encounters challenges such as partial shading and soiling. Emulation of the current-voltage characteristics of PV arrays enables repeated and reliable testing of inverter operation under irregular supply conditions. It has been shown that finding the maximum power point can be challenging under conditions of partial shading and soiling. Additionally, meeting the grid quality standards for the delivered power represents a challenge. Satisfying these requirements can be achieved through careful design of LCL filters at inverter output terminals, but further improvement can be achieved only through an adequate selection of the primary controller. To further improve the quality of grid currents, the possibility of applying innovative control algorithms has been demonstrated for laboratory inverters. Application of sliding mode controllers, besides ensuring system robustness, can prevent overshoots and fault responses from the current protection circuit by introducing a specific anti-windup structure.

Background: Most human movements are supported by its functional capabilities of the anaerobic type, which is dominated by submaximal and maximal sports activities performed in a short time. Functional capabilities of the anaerobic type of man participate in most of his movement activities. Conditioned on adequate and extremely good interaction and functioning of the cardiovascular and respiratory systems, morphological status, metabolic processes, muscle structure, nutritional status, physical activity, etc. Purpose: The research was conducted in the conditions of the so-called field testing with the primary goal of assessing the acute state of anaerobic abilities of physical and sports students, by calculating the fatigue index (FI). Methods: The sample included 80 students of Physical and Sports Education, different geographical regions, average weight 77.88±8.49kg, age 20-23 years. The Running Anaerobic Sprint Test (RAST) was used to assess FI, and the basic statistical parameters were calculated. Results: The average value of the student's leg power is 573.89 watts (378.42 watts vs. 817.99watts), and the recorded average (FI) of 8.35 watts/sec (3.97watts/sec. vs. 16.93watts/sec.). Conclusions: The obtained results confirmed the average values of anaerobic capacity which are suitable for the examined population of subjects, while the maximal the value of FI suggests a weaker state of the anaerobic capacity of the individuals (less tolerance to lactates).

We prove that $J(R_e)=R_e\cap J(R),$ where $S$ is a cancellative partial groupoid with idempotent $e,$ $R=\bigoplus_{s\in S}R_s$ an Artinian $S$-graded ring inducing $S,$ $J(R)$ the Jacobson radical of $R$ and $J(R_e)$ the Jacobson radical of $R_e.$ We also prove that $J(R)$ is nil if $J(R_e)$ is nil under certain assumptions.

Independent of the respective NFC (near field communication) application the specific NFC device has to be tested for standard compliance. In the present work we propose a hybrid surrogate-model based synthesis strategy which enables the incorporation of standard compliance tests in the synthesis process. While the surrogate model is used in early optimization phases applying a stochastic optimization strategy, the highfidelity model is applied in the final deterministic optimization part. The high fidelity model is based on a thin wire partial element equivalent circuit method.

One strategy for utilizing ammonia as an energy vector is to replace conventional hydrocarbons with hydrogen-enriched ammonia in existing or retrofitted combustors. However, the strong differential diffusion effect of hydrogen can significantly alter the combustion properties and cause challenges in combustor operability. Therefore, this numerical study performs a systematic investigation on the effect of differential diffusion on fundamental combustion properties of ammonia/hydrogen fuel blends. The investigated combustion properties span from the initiation of combustion, i

Abstract This study investigates the benefits of international diversification in the stock markets of the 28 European countries (the EU and the UK) over two five-year periods: a stable period from 2014 to 2019 and a turbulent period from 2019 to 2024. The analysis draws on the Markowitz mean-variance, Sharpe reward-to-variability, and naive diversification models, based on which different investment strategies were developed and implemented. We find that actively managed portfolios perform significantly better than naively diversified portfolios. The analyzed markets exhibit positive short-term associations, with an average correlation coefficient of 0.29 in the first period and 0.46 in the second period. However, these markets do not show long-term cointegration. Recent crises have reduced diversification benefits, yet significant opportunities for diversification remain. Diversification benefits are almost halved in the second period: average single-market standard deviation can be reduced by 60.5% with investments in 20-indices portfolios in the stable period, and only by 33.7% with the same portfolio size in the turbulent period.

Abstract In this paper, we investigate the determinants of bank profitability by examining endogenous factors used to measure the size of a financial institution. We underscore the significance of bank employees in embodying institutional values and playing a pivotal role in sales channels, as well as the impact of technological integration on customer expectations and workforce dynamics. Utilizing a dataset from regulatory agencies, which includes information from 47 banks and insurance companies in Bosnia and Herzegovina for the year 2021, the study explores the relationship between the independent variables which include the volume of total assets and the number of employees, and the dependent variable for profitability. By calculating Return on Equity (ROE) and employing a multiple linear regression model, the study finds that a statistically significant relation between independent variables and the dependent variable does not exist. Despite this, the research highlights the need for further investigation, particularly considering the differentiation between banks and insurance companies, the potential impact of outliers, and the broader economic context of the year studied. The findings suggest that a more refined model, possibly incorporating panel data, could provide clearer insights into the profitability determinants of financial institutions in Bosnia and Herzegovina.

Abstract The public sector of the Federation of Bosnia and Herzegovina (FBiH) from the aspect of complexity and comprehensiveness, includes all levels of government established within the state government, public companies, and the insurance system including: pension, health and social. The importance of performing duties and obligations in a transparent manner, and the possibility of detecting warning factors for corrupt activity are especially important in the public sector. Corrupt activities at all levels of the state structure of Bosnia and Herzegovina (BiH), as well as fraudulent behaviour and abuses within it, are precisely the consequences of the complexity of the state system, and the impossibility of efficient and rational use of public funds. Adequately organized, in accordance with the law, and accepted as such by employees within a certain public sector organization, internal auditing contributes to more efficient operations and prevention of corrupt practices. The aim of the subject research is to look at the process of functioning of the internal audit in the public sector of FBiH in the field of prevention of corrupt activities. The results of the research indicate the non-functioning and non-establishment of the internal audit in the manner specified by law, as well as the inadequate implementation of its recommendations, degrading and derogating its role, importance and contribution in the prevention of corrupt activities in the public sector of FBiH.

Abstract This literature review focuses on concepts related to the role of information technology (IT) capabilities and managerial support in the context of advancing digital transformation and improving internal audit in the institutional environment. Through the synthesis of relevant academic sources, it is investigated how IT capacities and strategic management support influence the organizational ability to adapt to digital innovations. Special emphasis is placed on the complex dynamics that shape the interactions between these factors and their impact on institutional responsibility and performance. The results of the literature review illustrate the key mechanisms that support the digital transformation process, including the integration of technological systems, the development of digital competencies, and the role of management in providing resources and support. Further, a deeper understanding of the complexity of these interactions serves as a basis for further research in the field of digital transformation management and internal audit in an institutional context.

Abstract The integration of data analytics into forensic accounting has revolutionized the detection and prevention of financial fraud. This paper conducts a comprehensive analysis of recent advancements in this field, highlighting the application of machine learning, data mining, and big data techniques in identifying fraudulent activities. By reviewing the latest research and examining case studies, we demonstrate the enhanced accuracy and efficiency these technologies offer over traditional methods. The findings suggest that financial institutions should adopt these advanced tools to mitigate fraud risks and improve overall financial security. The paper also explores future research directions, emphasizing the need for developing hybrid models and real-time detection systems to further enhance fraud detection capabilities.