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DIGITALNA TRANSFORMACIJA, EKONOMSKA USPJEŠNOST I ODRŽIVOST UNUTAR EU-A
No full textBy using triple time segmentation and dual model specifications, this paper investigates the relationship between digital transformation, economic performance, and sustainability within the European Union. By employing a multi-stage methodology (PCA, cluster analysis, and fixed effects (FE) panel regression modeling) across 27 EU countries, the study confirms the complex interdependence among these three dimensions. Findings identify four heterogeneous clusters, highlighting a contradiction between digital - economic leaders and sustainability leaders, indicating a significant challenge in decoupling growth from sustainability impacts. The panel regression results confirm digitalization as a robust and statistically significant driver of economic growth. Most importantly, the positive impact of renewable energy sources on economic performance confirms their endogenous benefits.Trostrukom vremenskom segmentacijom i dvostrukim specifikacijama modela ovaj rad istražuje odnos između digitalne transformacije, ekonomske uspješnosti i održivosti unutar Europske unije. Korištenjem višestupanjskom metodologijom (PCA, klaster analiza i model panel regresije s fiksnim učincima) za 27 zemalja EU-a, studija potvrđuje složenu međuovisnost ovih triju dimenzija. Nalazi identificiraju četiri heterogena klastera, ističući kontradikciju između digitalno-ekonomskih lidera i lidera održivosti, što ukazuje na značajan izazov u odvajanju rasta od utjecaja na održivost. Rezultati panel regresije potvrđuju digitalizaciju kao robustan i statistički značajan pokretač gospodarskog rasta. Najvažnije je da pozitivan utjecaj udjela obnovljivih izvora energije na ekonomske uspješnosti potvrđuje endogene koristi obnovljivih izvora energije
Effect of Rubber Seed Oil Biodiesel Additive on Compression Ignition Engines fuelled with Diesel-Ethanol Blends
No full textIn this study, the primary focus revolved around the utilization of rubber seed oil (RSO) biodiesel as a supplement in blends of diesel-ethanol (DE) for a diesel engine. The DE blends were formulated by combining ethanol with diesel and emulsifying them with RSO biodiesel in a 10% (v/v) proportion. The ethanol concentrations in the blends varied between 5% and 15% (v/v). Under conditions of maximum loading, it was observed that the blend labelled DE15B10, comprising 15% ethanol and 10% RSO biodiesel, demonstrated the highest brake thermal efficiency (BTE). Although all the examined fuels exhibited an elevated Brake Specific Fuel Consumption (BSFC) compared to conventional diesel, DE15B10 displayed a 4.30% increase in BSFC over fossil diesel. Nevertheless, the exhaust emission characteristics of DE15B10 were found to be superior to those of conventional diesel. These results indicate that DE-biodiesel blends, especially DE15B10, show potential as a viable alternative fuel option without requiring any modifications to the engine hardware
Development of Drowsy Driving Detection System Using EEG
No full textDrowsy driving is a major contributor to serious traffic accidents, highlighting the urgent need for effective real-time detection systems. This study proposes a real-time drowsiness detection system based on electroencephalogram (EEG) signals and a lightweight convolutional neural network (CNN). The system comprises five main components: EEG signal acquisition, preprocessing, feature extraction, CNN-based classification, and user feedback delivery via an Android application. The experiment involved four healthy adult male participants with an average age of 24.5 years. EEG data were collected using the DSI-24 device, and the relative power in the alpha band from the prefrontal (Fp1, Fp2) and occipital (O1, O2) regions was identified as the primary feature for distinguishing drowsiness. The proposed CNN model, trained on these features, achieved a classification accuracy of 91.56%, comparable to the 92.66% accuracy of the more complex AlexNet model, while being significantly more lightweight and suitable for real-time deployment on embedded systems. The Android application provides real-time feedback on the user’s drowsiness level and recommends nearby rest areas to help mitigate the risk of drowsy driving. This study presents a practical and efficient EEG-based driver monitoring solution. Future work will focus on large-scale data collection under actual driving conditions to further validate and improve the system’s performance
Multimethod survival analysis for identifying predictors and forecasting mortality in a heart patient cohort study
No full textThis study presents a multi-method survival analysis of 125 cardiac patients from IIMCT-Pakistan Railway Hospital in Rawalpindi, Pakistan. Parametric accelerated failure-time modeling identified the Weibull distribution as optimal for describing time-to-event data. Semi-parametric analyses, including Cox proportional hazards and Bayesian Cox regression, consistently identified hypertension, ischemic heart disease, and smoking as significant predictors of elevated mortality risk. Higher systolic blood pressure demonstrated a protective effect. Kaplan-Meier analysis revealed steadily declining survival rates up to 300 days with no significant gender differences. The random survival forest model achieved robust predictive accuracy, identifying ischemic heart disease, smoking, and age as the most influential predictors. Our multi-methodological approach demonstrates the value of integrating parametric, semi-parametric, Bayesian, and machine learning techniques for comprehensive risk assessment in cardiac patient cohorts, offering potential for enhanced clinical risk stratification and personalized prognosis
Influence of Age and Palm Surface Area on Secondary Task Performance in a Driving Simulator
No full textGesture control allows for reduced glance interaction compared to touchscreens when controlling secondary functions in cars. However, to date, there has been a lack of research investigating the influence of age and palm surface area (PSA) on performance during dual task applications, such as driving a car and using gestures with mid-air haptics feedback for controlling secondary functions. The following study investigates ways to introduce a characteristic feedback point on a virtual slider which differs from the adjacent points. This is either by changing the intensity or the distance to adjacent points. The time and the slider value set by the participant were saved. Participants gave ratings for each of the nine parameter sets by answering questions about the usability and the user experience questionnaire. The study consisted of two age groups: 30 younger participants with an average age of 31.0 years and 31 older participants with an average age of 63.0 years. Three of the older participants reported not feeling the mid-air haptics at all. Significant differences were found between the age groups in subjective and objective terms, and significant correlations for PSA and two subjective parameters. Further research will evaluate the findings in a more immersive static driving simulator
Electrochemical performance evaluation of ZnCo2O4 nanoflakes for hybrid supercapacitors
No full textThis study focuses on the synthesis and characterization of zinc cobaltite (ZnCo2O4) as an electrode material for supercapacitor (SC) applications. ZnCo2O4 was synthesized via an efficient sol-gel method, followed by annealing. Morphological and structural characterrizations revealed that ZnCo2O4 forms as nanoflakes with a well-crystallized structure. Electrochemical parameters of ZnCo2O4 were examined by various electrochemical techniques in a 3 M KOH aqueous electrolyte. The highest specific capacitance (Csp) of 321 F g-1 was obtained at a current density of 0.8 A g-1. The electrochemical performance of the ZnCo2O4 electrode is superior, owing to its porous nanoflake morphology, which provides numerous active sites and enables substantial charge storage. Moreover, multiple oxidation states of Zn and Co enhance redox reactions at the electrode surface, thereby improving the electrode's pseudocapacitance. The superior electrochemical performance of ZnCo2O4 indicates that it is a promising cathode material for hybrid SC devices
Assessing Risk in Postal Services – The Role of Users’ Subjective Security Perceptions
No full textThe paper explores the possibility and necessity of incorporating users’ subjective perceptions of safety into risk assessments. The survey has been done as a statistical analysis of questionnaires fulfilled by Croatian Post (HP – Hrvatska pošta) users, highlighting their perceptions of various aspects and suggestions about physical security, transaction security and postal items handling. This way, subjective perception is offered as a base for further definition or calibration of already existing variables used for risk assessment calculations. At the same time, this aspect of monitoring and analysing postal services offers the possibility of assessing service quality not only based on transit time or the number of complaints, as is currently the case, but also through the function of perceived safety. The results show a high level of user confidence in their interactions with the postal system, although there is significant room and need for improvement in procedures when an unwanted incident occurs. The survey results provide a comprehensive overview of user perceptions and areas for improvement in the security and protection of postal services
The determining role of firm innovativeness in the implementation of circular business models: an empirical study of the manufacturing industry in Bosnia and Herzegovina
No full textThis paper conceptually and empirically examines the role of firm innovativeness as a determinant of circular business model (CBM) implementation in the manufacturing industry (NACE Section C) of Bosnia and Herzegovina. The theoretical framework builds on the Resource-Based View and the Dynamic Capabilities View, differentiating between technological (product and process) and non-technological (organisational and marketing) innovativeness and their complementary roles in slowing, closing, and narrowing resource flows. The methodological design employs standardised firm-level measures and appropriate statistical techniques to assess how these innovation dimensions relate to the degree of CBM implementation. The research is based on a sample of 159 manufacturing firms, using harmonised business statistics indicators. The analytical procedure includes factor analysis, descriptive and correlational statistics, as well as multiple regressions with robust standard errors (HC3). The findings indicate that technological innovativeness provides the material and process foundations of circularity, through eco-design, process efficiency, and digital traceability, while non-technological innovativeness creates organisational and market conditions for diffusion and scaling, such as servitisation, reverse logistics routines, and stakeholder alignment. The contribution of this study is threefold. Theoretically, it refines the link between the Resource-Based View and the Dynamic Capabilities View perspectives and contemporary CBM typologies. Methodologically, it operationalises and tests “hard” and “soft” forms of innovation in parallel. At the practical and policy level, the study outlines key measures to support standardisation, servitisation, and circular material flows consistent with EU standards, with implications for managerial practice and industrial policy
Evolutionary Game Analysis of Carbon Emission Reduction Behaviour in Shipping Industry under Government Reward and Punishment
No full textTo promote the low-carbon transformation of the shipping industry, this study explores the impact of the government’s reward and punishment mechanisms on carbon reduction behaviours in the shipping industry. Specifically, this study constructs a tripartite evolutionary game model among the government, shipping companies and port enterprises, and examines the factors involved. The main results of this study are as follows. First, government reward and punishment mechanisms have a significant effect on the sustainable development of the shipping industry. The probability of shipping companies and port enterprises adopting carbon emission reduction behaviour will rise when the government effectively implements the reward and punishment mechanism. Second, the regulatory cost has an important influence on the decision of the government. With a decrease in the cost of conducting government regulation, the government is inclined to adopt active regulation strategies. Third, the short operational time has adverse effects on the green transition of the shipping industry. However, when the ships’ operational time is long, shipping companies are inclined to adopt proactive carbon reduction strategies. Besides, shipping companies tend to prioritise local port enterprises for the refuelling of clean energy ships. Therefore, the probability of port enterprises building clean energy refuelling stations will rise when shipping companies choose to adopt clean energy ships. The aim of this study is to offer policy suggestions for mitigating carbon emissions in the shipping industry and to help stakeholders choose the relatively optimal strategy
Cybersecurity Threat Analysis and Risk Assessment for Intelligent Connected Vehicles
No full textWith the rapid development of intelligent connected vehicles, cybersecurity issues have become increasingly prominent, posing significant challenges to vehicle safety and user privacy. This paper conducts a study on threat analysis and risk assessment (TARA) for intelligent connected vehicles based on the ISO/SAE 21434 standard. The research analyses and examines the practical methodologies of the standard from systematic and practical perspectives, constructing a comprehensive risk assessment framework that covers risk identification, analysis, assessment and response strategies. The rationality and effectiveness of the framework are validated through case studies. This study not only provides systematic security guidance for automotive manufacturers and technology developers but also offers empirical evidence for regulatory compliance reviews, thereby promoting the secure development of intelligent connected vehicles