Power system stability plays a significant role in the overall power system analysis. With the high penetration level of distributed generation (DG), especially large-scale wind farms, this problem needs to be addressed. This study investigates the system stability in case of a wind park (WP) integration using doubly fed induction generators (DFIGs) to transmission grid, while focusing on WP fault ride-through ability. The system was modelled for time-domain simulations. The results indicate that WP parallel operation with the high voltage network is possible if specific conditions are met, with fault clearance time being crucial. This is shown through scenarios, in which each of the overhead lines (OHL) was disconnected due to three-phase short circuit symmetrical fault, and the network parameters were observed for each case. The predefined control and protection configurations in the DFIG-based wind farm model simplify the analysis. The introduction of a battery energy storage system (BESS) with P and Q control strategies, improves WP stability during faults. Professional software tools, PSSE, and EMTP-RV, were employed for the analysis. The study showed that simulated WP and BESS connected to a real network, paired with appropriate fault clearance time and protection settings, can operate effectively while maintaining overall system stability. This research is significant for power system planning, especially with the growing integration of large-scale wind generation.

With the development of new technologies, next-generation mobile networks have brought new services with strict performance and security requirements. One promising solution that can ensure the highest possible level of security is quantum key distribution (QKD). This technology provides information-theoretical security using the principles of quantum physics. This paper presents an extended analysis of one implementation of the QKD key delivery protocol defined in the ETSI GS QKD 014 standard, considering a multi-user environment. We propose an empirically derived model of key delivery latency in such an environment based on regression analysis of experimental results. Using the proposed model, we estimate the limitations of the implemented solution in terms of maximum number of simultaneous users connected to one key management server, considering several applications in 5G/6G networks.

Professional football players often need legal help in managing disputes with football clubs. The Professional Football Players Syndicate of Bosnia and Herzegovina is an organization founded with this purpose. Due to an increasing need for legal help and a large number of cases, their legal associates need systematic management of data. This work presents the first information system entirely intended for the usage by sports law professionals. It contains a desktop application where legal disputes are shown in the form of an organized dispute table. Real-time information about football players is acquired by using the TransferMarkt web API. The system was successfully used for two years, resulting in 103 documented cases involving 87 players and 31 clubs. As a result, 69.90% of disputes were archived and 43.69% of disputes resulted in agreements, indicating that the productivity of legal associates and the mediator role of the Syndicate were improved.

Procedural modeling is used to generate virtual content in organized layouts of exterior and interior elements. There is a large number of existing layout generation methods, and newer approaches propose the generation of multiple layout types within the same generation session. This introduces additional constraints when manually created layout elements need to be combined with the automatically generated content. Existing approaches are either designed to work with existing elements for a single layout type, or require a high amount of manual work for adding existing elements within multiple layouts. This paper presents a method that enables the application of existing subdivision methods on multiple layout types by inserting existing content into the generation result. This method can generate test cases by creating variations of partially generated layouts for procedural modeling methods that can work with existing content.

In research aimed at determining the level of interest of high school students in enrolling in colleges, predictive analysis models and comparisons are rarely applied during the classification and processing of various data. All of this leads to significant fluctuations in college admissions, where certain schools are unable to admit a large number of students who show interest in a specific field. On the other hand, high school students lose interest in certain schools, leading to the discontinuation of specific directions essential for today's job market needs. Institutions largely fail to conduct a comparison and linkage of teaching and non-teaching activities when analyzing the talents and interests of high school students from different fields. The goal of this paper is to use programming language classifiers to predict student enrollments in colleges based on the results students demonstrate during regular attendance in high schools through participation in innovation fairs.

This research delves into the crucial role of solar energy, particularly photovoltaic (PV) conversion, in the global shift towards renewable sources. Focusing on the stochastic nature of PV power plants, the study emphasizes fault ride-through operations and their repercussions on electrical power systems. A detailed modeling approach is employed using Electromagnetic Transient Program (EMTP) software to simulate a large-scale PV power plant connected to a high-voltage transmission network. The analysis encompasses various fault scenarios, shedding light on the resilience of PV systems and their broader impacts during faults. This investigation enhances the understanding of PV dynamics in fault conditions, providing valuable insights for sustainable energy systems.

Clustering users on social media based on text involves grouping individuals with similar text patterns, language usage, or content interests. This text-based clustering provides insights into user preferences, enables personalized content recommendations, and facilitates understanding of social networking trends and user engagement. However, traditional text clustering methods rely heavily on language-specific features. This limits their applicability in multilingual media environments where linguistic diversity prevails. In this paper, the problem of clustering users on social networks, specifically focusing on text-based clustering independent of the language in which the text is written, is addressed. A practical methodology is presented, outlining an iterative procedure for clustering based solely on language-independent features such as emojis, hashtags, URLs, text length, and punctuation count. The effectiveness of the language-independent clustering approach is compared with the usual text based clustering approach. Comparison of these results shows that for the used dataset, the proposed clustering method using language independent features gives higher quality results than text clustering.

This paper describes a new smartphone-based colorimetric method for the determination of N-acetyl-L-cysteine and glutathione using a reaction with the Cu(II)–neocuproine complex. The reaction resulted in the formation of a yellow Cu(I)–neocuproine complex. Reaction solutions, prepared according to the selected optimal conditions, are placed in front of a light blue background, and a smartphone camera is used for digital image acquisition. The intensity of the blue RGB canal was selected for analytical response and determined using the free Color Grab mobile app. Also, absorbance at a wavelength of 450 nm was measured for all reaction solutions using a UV–Vis spectrophotometer. The proposed procedures allow the determination of both thiols in the linear dynamic range from 3.0 × 10–6 to 2.0 × 10–4 mol L−1 for a spectrophotometer as a detector, or from 6.0 × 10–6 to 2.0 × 10–4 mol L−1 for a smartphone as a detector. The obtained results indicate that the proposed method is accurate, simple, cost-effective, and applicable to the determination of thiols in pharmaceuticals.

Working with different DBMS for programmers in their daily work represents a significant challenge in terms of choosing the appropriate way of connecting to the DBMS for the appropriate needs, given that a significant number of factors can influence the same. Although experience is usually one of the important elements that has influence on the selection of the appropriate way to connect to a DBMS, the choice can still vary from system to system and from situation to situation. For this reason, it is necessary to conduct appropriate analysis and research in accordance with various factors that can be an indicator of whether a connection with a DBMS is good or bad. In this research, an analysis was performed between the two leading methods of interaction between Java Spring Boot applications and PostgreSQL databases, namely Spring JDBC and Spring Hibernate. The results of the analysis indicate that there are certain differences in the speed of query execution in certain situations, which Java programmers should pay special attention to when choosing one of the two mentioned technologies to achieve more complex functionalities.

Statisticians rank oral and lip cancer sixth in global mortality at 10.2%. Mouth opening and swallowing are challenging. Hence, most oral cancer patients only report later stages. They worry about surviving cancer and receiving therapy. Oral cancer severely affects QOL. QOL is affected by risk factors, disease site, and treatment. Using oral cancer patient questionnaires, we use light gradient Boost Tree classifiers to predict life quality. DIAS records were used for 111 oral cancer patients. The European Organisation for Research and Treatment of Cancer’s QLQ-C30 and QLQ-HN43 were used to document the findings. Anyone could enroll, regardless of gender or age. The IHEC/SDC/PhD/OPATH-1954/19/TH-001 Institutional Ethical Clearance Committee approved this work. After informed consent, patients received the EORTC QLQ-C30 and QLQ-HN43 questionnaires. Surveys were in Tamil and English. Overall, QOL ratings covered several domains. We obtained patient demographics, case history, and therapy information from our DIAS (Dental Information Archival Software). Enrolled patients were monitored for at least a year. After one year, the EORTC questionnaire was retaken, and scores were recorded. This prospective analytical exploratory study at Saveetha Dental College, Chennai, India, examined QOL at diagnosis and at least 12 months after primary therapy in patients with histopathologically diagnosed oral malignancies. We measured oral cancer patients’ quality of life using data preprocessing, feature selection, and model construction. A confusion matrix was created using light gradient boosting to measure accuracy. Light gradient boosting predicted cancer patients’ quality of life with 96% accuracy and 0.20 log loss. Oral surgeons and oncologists can improve planning and therapy with this prediction model.

Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age‐specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age‐specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome‐wide association study data, and the within‐pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

In this paper we derive some new identities involving the Fibonacci and Lucas polynomials and the Chebyshev polynomials of the first and the second kind. Our starting point is a finite trigonometric sum which equals the resolvent kernel on the discrete circle with $m$ vertices and which can be evaluated in two different ways. An expression for this sum in terms of the Chebyshev polynomials was deduced in \cite{JKS} and the expression in terms of the Fibonacci and Lucas polynomials is deduced in this paper. As a consequence, we establish some further identities involving trigonometric sums and Fibonacci, Lucas, Pell and Pell-Lucas polynomials and numbers, thus providing a"physical"interpretation for those identities. Moreover, the finite trigonometric sum of the type considered in this paper can be related to the effective resistance between any two vertices of the $N$-cycle graph with four nearest neighbors $C_{N}(1,2)$. This yields further identities involving Fibonacci numbers.

Given the uncertainty surrounding how existing explainability methods for autonomous vehicles (AVs) meet the diverse needs of stakeholders, a thorough investigation is imperative to determine the contexts requiring explanations and suitable interaction strategies. A comprehensive review becomes crucial to assess the alignment of current approaches with varied interests and expectations within the AV ecosystem. This study presents a review to discuss the complexities associated with explanation generation and presentation to facilitate the development of more effective and inclusive explainable AV systems. Our investigation led to categorising existing literature into three primary topics: explanatory tasks, explanatory information and explanatory information communication. Drawing upon our insights, we have proposed a comprehensive roadmap for future research centred on (i) knowing the interlocutor, (ii) generating timely explanations, (ii) communicating human-friendly explanations and (iv) continuous learning. Our roadmap is underpinned by principles of responsible research and innovation, emphasising the significance of diverse explanation requirements. To effectively tackle the challenges associated with implementing explainable AV systems, we have delineated various research directions, including the development of privacy-preserving data integration, ethical frameworks, real-time analytics, human-centric interaction design and enhanced cross-disciplinary collaborations. By exploring these research directions, the study aims to guide the development and deployment of explainable AVs, informed by a holistic understanding of user needs, technological advancements, regulatory compliance and ethical considerations, thereby ensuring safer and more trustworthy autonomous driving experiences.

Messaging apps, such as Telegram and WhatsApp, are routinely used to communicate, chat and make decisions. Group Recommender Systems (GRSs) have been introduced as self standing tools to support group interactions and decision-making. We present here a TelegramBot, named CHARM, that supports groups to make a decision on an arbitrary topic by leveraging GRSs techniques. CHARM helps elicit the group members’ preferences, ranks the items that the members have suggested to be considered, provides a summary of the current status of the discussion, and finally recommends a fair choice. A focus group study has revealed that the designed functionality includes features that users expect to find in a bot aimed at supporting group decision-making.

Purpose. The purpose of this paper is to determine and analyze the determinants of the capital structure of joint-stock companies in Bosnia and Herzegovina that are listed on the Banja Luka Stock Exchange. This study will answer the question as to which factors determine the capital structure of BiH companies and whether existing financial theories of the capital structure hold true in that context. The main research objective is to estimate the effects of a firm’s level determinants on its capital structure measures in different ownership structures. Those findings will certainly advance our understanding of listed companies financing behavior. Methodology. For the research, we took into account firm-specific characteristics and divided joint-stock companies into private and state-owned. The results of the research show that the capital structure of these two groups of enterprises is differently affected by individual determinants. Findings and implications. While state-owned enterprises rely more on borrowed resources to finance both short-term and long-term assets, private enterprises even finance part of their short-term assets with their own capital. However, the most important determinant in both groups of enterprises is the share of inventories in short-term assets, which confirms that short-term liabilities, i.e. free sources of financing in the form of liabilities to suppliers are the determinant that most positively affect the indebtedness of all enterprises. Unlike previous research that observed enterprises according to their size or affiliation to individual industries, the focus of our research is enterprises of different ownership structures. The empirical statistical results provide basis for logical conclusion and appropriate policy implications. The study points to the specifics of the capital structure in private and publicly listed joint-stock companies. The stated opposite influence of certain ratios on the indebtedness of the enterprises is explained by a number of factors. Limitations. This study focuses only on the presentation of the recent indicators of capital structure of listed companies - listed on the Banja Luka Stock Exchange, which is one of its major limitations. The limitation of this search is the sample size which can be considered low. Further research may be conducted by using other capital markets to explore more information regarding the effect of the variables affecting the capital structure. In addition, further research may also be conducted by using other proxies or by adding more variables, sample size, and research period to get a better result. Originality. The study is an original research paper. It has not been published in any other peer-reviewed journal not under consideration for publication by any other journal. The paper adds to the existing literature on Bosnia and Hezegovina by giving an overview of recent developments in the flexi purity concept, pointing out the areas that require policy response.