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An Overview of Cybersecurity: Key Issues and Emerging Solutions
No full textIn an age where digital interconnectivity permeates every aspect of daily life, cyber threats have grown more advanced, and as a result, they pose very dangerous threats to individuals, enterprises, and governments all the same. This review offers a systematic synthesis of cyber threats, new attack surfaces, and new defense techniques, with emphasis on the convergence of artificial intelligence (AI) and domain-specific issues within cloud, IoT, and mobile networks. Upcoming new technologies like quantum and 5G further present risks that require further new developments in cryptography and solutions in network security. In addition to providing an overview of current work, this paper makes an original contribution by presenting a comparison of prominent methods and studies, divided by defense strategy, domain, and performance measures. The approach for the study focuses more on the requirement of technical innovation to be blended with frameworks that are ethical and regulatory in nature, addressing complex and dynamic threats in the nature of cybersecurity. Recommendations for further research in the future include quantum-resistant algorithms, improved AI models that can be used for more effective cybersecurity, and creation of ethical standards in the digital defense of the resources of the nation to do it more robustly and responsibly
Josip Mužić, Beskompromisna politika katolika. Principi o kojima se ne pregovara, Glas Koncila, Zagreb, 2025., 239 stranica
No full textPrikaz knjige: Josip Mužić, Beskompromisna politika katolika. Principi o kojima se ne pregovara, Glas Koncila, Zagreb, 2025., 239 stranic
Revenue management reinvented: Leveraging technical know-how to unlock hotel efficiency
No full textPurpose – Revenue management (RM) is no longer just a tool for optimizing revenue but
a strategic framework for driving net profits and sustainable growth. This study reimagines
RM in green hotels as a dynamic, innovation-driven process, leveraging digitalization
to create smarter, data-driven decision-making ecosystems. It explores the role of RM
enablers—organizational culture (OC), demand prediction (DP), distribution networks (DN),
competition analysis (CA), tailored pricing (TP), and regular evaluations (RE)—in boosting
hotel efficiency. Additionally, it investigates how technical know-how (TKH) acts as a
catalyst, mediating the link between RM practices and hotel efficiency.
Methodology/Design/Approach – A multiple case study approach was applied, targeting green
hotels in Saudi Arabia. Data were collected through 405 self-designed questionnaires distributed
among hotel executives. Data envelopment analysis (DEA) was employed to calculate hotel
efficiency scores. The random forest (RF) algorithm was utilized as a machine learning tool to
predict model performance and identify feature importance metrics. Finally, structural equation
modeling (SEM) was used to test the proposed hypotheses and mediation effects.
Findings – The study identified a significant positive relationship between RM enablers
and hotel efficiency. TP, DP, and CA emerged as the most influential enablers, with high
contributions to model accuracy and node purity. While, OC, DN, and RE showing limited
effects. Machine learning analysis confirmed the predictive accuracy and feature importance
of the proposed model. The mediation analysis revealed that TKH strengthens the relationship
between RM actions and hotel efficiency.
Originality of the research – This study integrates advanced machine learning techniques
with RM enablers to provide a comprehensive framework for enhancing hotel efficiency. It
highlights the mediating role of TKH, offering new perspectives for RM literature
Aktualnosti iz projekta “Znanje+Kreativnost = STEM Inspiracija”: Kalendar događanja ožujak 2026. (“Znanje+Kreativnost = STEM Inspiracija”)
No full textOsvrti: Osvrt na BIP program “Ostvarivanje ciljeva održivog razvoja kroz prizmu kemije, kemijskeiprehrambene tehnologije”
No full textOsvrti: SPIN projekti: Nove suradnje Kemijsko-tehnološkog fakulteta u Splitu i industrije
No full textGLDM Algorithm for Big Data (SCADA) Wind Speed Modelling
No full textThis study enhances wind speed forecasting by implementing the second-order Generalized Least Deviation Method (GLDM), focusing on wind turbines in Turkey. The research aims to improve predictive accuracy and operational efficiency in renewable energy systems through advanced mathematical modeling in meteorology. The GLDM, utilizing a quasilinear recurrence equation, addresses the inherent non-linearity and variability of wind speed data. By applying the method to extensive SCADA data, this study minimizes residuals in nonlinear big data environments, integrating both linear and nonlinear components to refine predictions. A critical aspect of this research is the comparison between the second-order GLDM and traditional forecasting models, including statistical methods and machine learning approaches. The results demonstrate the superior performance of GLDM, as indicated by lower prediction errors and greater accuracy across key metrics. The study also underscores the importance of GLDM coefficients, , in improving predictive capabilities. The findings advocate for the adoption of GLDM in wind speed forecasting, highlighting its potential to significantly enhance wind energy management through increased accuracy. This study also sets a precedent for broader applications of advanced mathematical models in environmental science, illustrating the effectiveness of GLDM in optimizing renewable energy resources
Determination of Thermal Characteristics of Fe-C Cast Iron Using Hot Disk Method
No full textThis paper explores the influence of graphite shape, type, and dimensions on the thermal characteristics of Fe-C cast iron. Test samples were prepared from blocks of grey and nodular cast iron, specifically examining castings with D and A types of graphite as well as nodular graphite in a ferrite matrix. To analyze the effect of surface texture, sample surfaces were prepared with varying parameters of surface roughness, achieving values of 0.5 μm for polished and 12.6 μm for unpolished surfaces. Thermal characteristics, including thermal conductivity and effusivity, were evaluated using unsteady hot disk methods, with water as the contact agent, to simulate practical thermal conditions. Additionally, the microstructure of each sample was analyzed using optical microscopy. Results indicate that graphite content, type, shape, and surface roughness collectively have the most significant impact on the thermal properties of cast iron. This study’s findings provide valuable insights into optimizing cast iron for applications requiring efficient thermal management and highlight the importance of graphite morphology and surface finish in enhancing thermal performance
Impact of Infill Pattern Design on Stress-Strain behaviour of 3D Printed Parts
No full textCompared to some conventional manufacturing processes, the properties of additive manufacturing parts can depend on the structural and manufacturing process parameters, rather than just on the type of materials used. The purpose of this paper is to evaluate the tensile mechanical properties of the components printed with a 3D printer by changing the design of the infill pattern. The study presents the data of 13 (by 3 tests for each form of filling) different infill pattern designs, prepared and tested according to the ISO 527-2:2012 standard. The samples were analyzed according to the paired sample tests, considering the weight and the results of the tests, as well as the impact of the infill pattern on the test results. Significant differences were observed among the samples in terms of engineering stress and strain. The line infill pattern demonstrated better results in the engineering strain whereas the concentric infill pattern yielded superior values for engineering stress. Regarding ultimate tensile strength, concentric infill pattern shows significantly higher results than all other samples. Taking into consideration the results of the samples, it is concluded that there are significant differences between the design of the infill pattern and the other analyzed studies, which should be considered depending on the intended use of the 3D printed elements