How Particular Firm-Specific Features Influence Corporate Debt Level: A Case Study of Slovak Enterprises

Axioms, Journal Year: 2023, Volume and Issue: 12(2), P. 183 - 183

Published: Feb. 10, 2023

Debt financing is related to borrowing funds from enterprises and investors through bonds, banks, or financial institutions. Interest in debt has been rapidly growing recent years now considered one of the most common ways an enterprise can increase its capital run business. However, use a large amount associated with management corporate indebtedness, requiring tracking entire performance company. The chief objective this study was determine assess indebtedness level operating Slovak Republic using 12 crucial ratios then clarify whether there are statistically relevant dissimilarities as result firm size legal form, representing company-specific features having impact on indebtedness. Subsequently, more elaborate analysis addressing between separate relation company form carried out by deploying nonparametric Kruskal–Wallis test. We leveraged Bonferroni correction specify where stochastic ascendancy occurs. test revealed significant values company, which confirmed previous results indicating determinants shaping debt. Recognizing repercussions policy plays important role, these may be perceived proxies for default likelihood volatility assets, making regulatory process creditors stakeholders straightforward. findings theories numerous researchers who claimed that critical aspects

Language: Английский

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Enhancing security of Internet of Robotic Things: A review of recent trends, practices, and recommendations with encryption and blockchain techniques

Internet of Things, Journal Year: 2024, Volume and Issue: 28, P. 101357 - 101357

Published: Sept. 3, 2024

The Internet of Robotic Things (IoRT) integrates robots and autonomous devices, transforming industries such as manufacturing, healthcare, transportation. However, security vulnerabilities in IoRT systems pose significant challenges to data privacy system integrity. To address these issues, encryption is essential for protecting sensitive transmitted between devices. By converting into ciphertext, ensures confidentiality integrity, reducing the risk unauthorized access breaches. Blockchain technology also enhances by offering decentralized, tamper-proof storage solutions. comprehensive insights, practical recommendations, future directions, this paper aims contribute advancement knowledge practice securing interconnected robotic systems, thereby ensuring integrity exchanged within ecosystems. Through a thorough examination requisites, scopes, current implementations IoRT, provides valuable insights researchers, engineers, policymakers involved efforts. integrating blockchain technologies stakeholders can foster secure dependable environment, effectively manage risks, bolster user confidence, expedite widespread adoption across diverse sectors. findings study underscore critical role enhancement highlight potential avenues further exploration innovation. Furthermore, suggests research areas, threat intelligence analytics, design, multi-factor authentication, AI detection. These recommendations support ongoing innovation evolving landscape.

Language: Английский

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Digital twin-based cyber-physical manufacturing systems, extended reality metaverse enterprise and production management algorithms, and Internet of Things financial and labor market technologies in generative artificial intelligence economics

Oeconomia Copernicana, Journal Year: 2024, Volume and Issue: 15(3), P. 837 - 870

Published: Sept. 30, 2024

Research background: Generative artificial intelligence (AI) and machine learning algorithms support industrial Internet of Things (IoT)-based big data enterprise asset management in multiphysics simulation environments by processing, modeling, monitoring, enabling business organizational managerial practices. Machine learning-based decision edge generative AI sensing systems can reduce persistent labor shortages job vacancies power productivity growth market dynamics, shaping career pathways facilitating occupational transitions skill gap identification labor-intensive manufacturing automation path planning spatial cognition algorithms, furthering theoretical implications for sciences. fintech, behavioral analytics assist multi-layered payment transaction processing screening with regard to authorized push payment, account takeover, synthetic identity frauds, flagging suspicious activities combating economic crimes rigorous verification processes. Purpose the article: We show that device functionalities cloud IoT virtual robotic technologies configure plant production route processes across cyber-physical multi-cloud immersive 3D environments, leading tangible outcomes reinforcement convolutional neural networks. Labor-augmenting impact employment participation, increase wage wealth inequality, lead potential displacement massive disruptions. The deep capabilities fintech terms adaptive credit scoring mechanisms enhance financial behaviors algorithmic trading returns, identify fraudulent transactions swiftly, improve forecasts, customized investment recommendations well-informed decisions. Methods: study selection process text mining systematic review software tools leveraged include Abstrackr, CADIMA, Colandr, DistillerSR, EPPI-Reviewer, JBI SUMARI, METAGEAR package R, SluRp, SWIFT-Active Screener. Such reference are harnessed methodologically evidence synthesis, characteristic extraction, predictive document classification, citation record screening, bias assessment, article retrieval automation, classification prioritization. Findings & value added: Industrial augmented reality create streamlining product remote extended reality-based navigation autonomous smart factory articulating level theory implications. operational modeling execute complete complex cognitive task-oriented knowledge economy jobs, producing first-rate quality outputs swiftly while unemployment spells, disruptions, losses, reduced earnings clustering algorithms. decentralized finance, interoperable blockchain networks, cash flow tools, tokenization mitigate fraud risks, enable digital fund crypto investing servicing, automate treasury operations integrating real-time capabilities, routing configurable workflows, lending technologies.

Language: Английский

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Leveraging Monte Carlo Dropout for Uncertainty Quantification in Real-Time Object Detection of Autonomous Vehicles

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 33384 - 33399

Published: Jan. 1, 2024

With the recent advancements in machine learning technology, accuracy of autonomous driving object detection models has significantly improved. However, due to complexity and variability real-world traffic scenarios, such as extreme weather conditions, unconventional lighting, unknown participants, there is inherent uncertainty models, which may affect planning control driving. Thus, rapid accurate quantification this crucial. It contributes a better understanding intentions vehicles strengthens trust technology. This research pioneers quantifying YOLOv5 model, thereby improving speed probabilistic detection, addressing real-time operational constraints current contexts. Specifically, novel model named M-YOLOv5 proposed, employs MC-drop method capture discrepancies between results real world. These are then converted into Gaussian parameters for class scores predicted bounding box coordinates quantify uncertainty. Moreover, limitations Mean Average Precision (MAP) evaluation metric, we introduce new measure, Probability-based Detection Quality (PDQ), incorporated component loss function. metric simultaneously assesses quality label positional Experiments demonstrate that compared original algorithm, algorithm shows 74.7% improvement PDQ. When with most advanced targeting MS COCO dataset, achieves 14% increase MAP, 17% PDQ, 65% FPS. Furthermore, against state-of-the-art BDD100K exhibits 31.67% enhancement MAP 125.6%

Language: Английский

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Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities

Sensors, Journal Year: 2024, Volume and Issue: 24(13), P. 4254 - 4254

Published: June 30, 2024

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet Things (IoT) in smart cities. In this paper, we introduce an advanced network slicing framework designed to meet complex demands cities' IoT deployments. development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, validation final design. Our evaluations demonstrate framework's high efficiency, evidenced by low round-trip time (RTT), minimal packet loss, increased availability, enhanced throughput. Notably, scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption rate authentication success. discussion elaborates on these findings, underscoring impressive performance, scalability, capabilities.

Language: Английский

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Stabilized GAN models training with kernel-histogram transformation and probability mass function distance

Applied Soft Computing, Journal Year: 2024, Volume and Issue: 164, P. 112003 - 112003

Published: July 18, 2024

Language: Английский

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Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis

Information, Journal Year: 2023, Volume and Issue: 14(11), P. 607 - 607

Published: Nov. 9, 2023

Nowadays, more and sciences are involved in strengthening the work of law enforcement authorities. Scientific documentation is evidence highly respected by courts administering justice. As involvement science solving crimes increases, so does human subjectivism, which often leads to wrong conclusions and, consequently, bad judgments. From above arises need create a single information system that will be fed with scientific such as fingerprints, genetic material, digital data, forensic photographs, from report, etc., also investigative data witnesses’ statements, apology accused, various crime scenes able, through formal reasoning procedure, conclude possible perpetrators. The present study examines proposal for developing an can basis creating ontology—a semantic representation scene—through descriptive logic owl language. Interoperability-Enhanced developed could assist authorities crimes. At same time, it would promote closer cooperation between academia, civil society, state institutions fostering culture engagement common good.

Language: Английский

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The role of knowledge and interpersonal competences in the development of civic and public engagement and entrepreneurial intention

International Entrepreneurship and Management Journal, Journal Year: 2023, Volume and Issue: 20(1), P. 189 - 213

Published: Oct. 14, 2023

Language: Английский

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On Fusing Wireless Fingerprints with Pedestrian Dead Reckoning to Improve Indoor Localization Accuracy

Sensors, Journal Year: 2025, Volume and Issue: 25(5), P. 1294 - 1294

Published: Feb. 20, 2025

Accurate indoor positioning remains a critical challenge due to the limitations of single-source systems, such as signal instability and environmental obstructions. This study introduces multi-source fusion algorithm that integrates inertial sensors fingerprints address these issues. Using weighted method, employs pedestrian dead reckoning (PDR) for trajectory tracking combines its outputs with wireless fingerprints. Experimental evaluations conducted on diverse trajectories reveal significant improvements in accuracy, achieving 35.3% enhancement over wireless-only systems 71.4% improvement compared standalone PDR. The proposed method effectively balances computational efficiency demonstrating robustness complex dynamic environments. These findings establish algorithm’s potential practical applications navigation, robotics, Industry 4.0, where precise localization is essential.

Language: Английский

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Legal Framework, Information Technologies, and Economic Impact In Agricultural Sciences: a Digital Transformation Approach

Journal of Lifestyle and SDGs Review, Journal Year: 2025, Volume and Issue: 5(3), P. e05007 - e05007

Published: Feb. 21, 2025

Objective: This study analyzes the intersection of digital transformation, legal frameworks, and economic impact in agriculture. It aims to identify regulatory gaps, assess disparities technology adoption, propose policy recommendations for a balanced inclusive transition sector. Theoretical Framework: The research is grounded agriculture, governance, development theories. explores how artificial intelligence, IoT, big data, blockchain influence productivity, sustainability, market dynamics. Additionally, it examines frameworks affecting data ownership, intellectual property, cross-border trade. Method: A mixed-methods approach was used, combining systematic literature review, stakeholder surveys, expert interviews, case analysis. Quantitative from reports adoption surveys were analyzed using statistical methods, while qualitative interviews studies examined through thematic Results Discussion: Findings indicate that agriculture enhances efficiency resource optimization, inconsistencies create barriers widespread adoption. Small medium-sized farms struggle with financial constraints, limiting their access advanced technologies. Case reveal regions clear support exhibit higher rates benefits. Research Implications: highlights need harmonized policies ensure equitable tools, protect rights, foster sustainable agricultural practices. Policymakers must address prevent further marginalization small farmers. Originality/Value: contributes discourse on digitalization by integrating legal, economic, technological perspectives. provides actionable insights governments, agribusinesses, researchers develop resilient policies.

Language: Английский

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