Search Results (2,173)

Maximum likelihood estimation (MLE) in infinite mixture distributions often lacks closed-form solutions, requiring numerical methods such as the Newton–Raphson algorithm. Selecting appropriate initial values is a critical challenge in these procedures. This study introduces a bootstrap-based approach to determine initial parameter values for MLE, employing both nonparametric and parametric bootstrap methods to generate the mixing distribution. Monte Carlo simulations across multiple cases demonstrate that the bootstrap-based approaches, especially the nonparametric bootstrap, provide reliable and efficient initialization and yield consistent maximum likelihood estimates even when raw moments are undefined. The practical applicability of the method is illustrated using three empirical datasets: third-party liability claims in Indonesia, automobile insurance claim frequency in Australia, and total car accident costs in Spain. The results indicate stable convergence, accurate parameter estimation, and improved reliability for actuarial applications, including premium calculation and risk assessment. The proposed approach offers a robust and versatile tool both for research and in practice in complex or nonstandard mixture distributions. Full article

Capacitive ECG sensors in automobiles enable unobtrusive heart rate monitoring as an indicator of a driver’s alertness and health. This paper introduces a capacitive sensor with textile electrodes and provides insights into signal quality and RR duration accuracy. Electrodes of various shapes, sizes, and fabrics were integrated at various positions into the seat back of a driving simulator car seat. Seven subjects completed identical driving circuits with their cardiac signals being recorded simultaneously with textile electrodes and reference Ag-AgCl electrodes. Capacitive ECG signals with observable R peaks (after filtering) could be captured with almost all pairs of textile electrodes, independently of design or placement. Signal quality from textile electrodes was consistently lower compared with reference Ag-AgCl electrodes. Proximity to the heart or even contact with the body seems to be key but not enough to improve signal quality. However, accurate measurement of RR durations was mostly independent of signal quality since 90% of all RR durations measured on capacitive ECG signals had a percentage error below 5% compared to reference ECG signals. Accuracy was actually algorithm-dependent, where a classic Pan–Tompkins-based algorithm was interestingly outperformed by an in-house frequency-domain algorithm. Full article

In the evaluation of vehicle noise, vibration and harshness (NVH) performance, interior noise control is the core consideration. In the early stage of automobile research and development, accurate prediction of interior noise caused by road surface is very important for optimizing NVH performance and shortening the development cycle. Although the data-driven machine learning method has been widely used in automobile noise research due to its advantages of no need for accurate physical modeling, data learning and generalization ability, it still faces the challenge of insufficient accuracy in capturing key local features, such as peaks, in practical NVH engineering. Aiming at this challenge, this paper introduces a forecast approach that utilizes an empirical-informed neural network, which aims to integrate a physical mechanism and a data-driven method. By deeply analyzing the transmission path of interior noise, this method embeds the acoustic mechanism features such as local peak and noise correlation into the deep neural network as physical constraints; therefore, this approach significantly enhances the model’s predictive performance. Experimental findings indicate that, in contrast to conventional deep learning techniques, this method is able to develop better generalization capabilities with limited samples, while still maintaining prediction accuracy. In the verification of specific models, this method shows obvious advantages in prediction accuracy and computational efficiency, which verifies its application value in practical engineering. The main contributions of this study are the proposal of an empirical-informed neural network that embeds vibro-acoustic mechanisms into the loss function and the introduction of an adaptive weight strategy to enhance model robustness. Full article

New energy vehicles face a critical challenge in balancing the thermal safety management of high-specific-energy battery systems with the simultaneous improvement of energy density. With the large-scale application of high-energy-density systems such as silicon-based anodes and solid-state batteries, their inherent thermal runaway risks pose severe challenges to battery thermal management systems (BTMS). Currently, the thermal insulation performance, temperature resistance, and fire protection capabilities of flame-retardant materials (e.g., foam cotton, fiber felts) used in automotive batteries are inadequate to meet the demands of intense combustion and high temperatures generated during thermal failure in high-energy-density batteries. Against this backdrop, thermal insulation and fireproof aerogel materials are emerging as a revolutionary solution for the next generation of power battery thermal protection systems. Leveraging their nanoporous structure’s exceptional thermal insulation properties (thermal conductivity of 0.013–0.018 W/(m·K) at room temperature) and extreme fire resistance (temperature resistance > 1100 °C/UL94 V-0 flame retardancy), aerogels are gaining prominence. This article provides a systematic review of thermal runaway phenomena in automotive batteries and corresponding protective measures. It highlights recent breakthroughs in the selection of material systems, optimization of preparation processes, and fiber–matrix composite technologies for automotive fireproof aerogel composites. The core engineering values of these materials, such as blocking thermal runaway propagation, reducing system weight, and improving volumetric efficiency, are quantitatively validated. Furthermore, the paper explores future research directions, including the development of low-cost aerogel composites and the design of organic–inorganic hybrid composite structures, aiming to provide a foundation and industrial pathway for the research and development of next-generation high-performance battery thermal management systems. Full article

A trend analysis mentioned that the global automotive Vehicle-to-Everything—also called V2X—market size will be reached at several billions in the near future. This information clearly highlights the importance of developing V2X communication. Nowadays, automobile manufacturers have introduced vehicles equipped with driver assistance and even conditional autonomous driving features. Light detection and ranging (LiDAR) components are used in sensor networks to detect objects around. Also, vehicles take advantage of LiDAR sensors to discover the neighbor cars in cognitive systems for road safety. Carrying on from our previous works, we found that organizing vehicles into groups can enhance the safety of the vehicle networks by LiDAR assistance. However, the success rate and reliability of grouping vehicles is an important issue. Also, enhancing existing Vehicle-to-Vehicle (V2V) communication mechanisms remains a key factor in ensuring that emergency messages can be transmitted both timely and accurately. To address this, in this research, a method is proposed to make vehicles on the road be self-organized well for Intelligent Transportation Systems (ITS). Also, we found that before data in each car is transmitted, the scenario that data is queued for waiting a random time exponentially distributed outperforms data being sent immediately. Full article

Bioethanol manifests an extraordinary potential to overcome the severe energy crises and reliance on fossil fuels, yet it supports the sustainable and cost-effective production of fuels for automobile engines and contributes to the reduction of greenhouse gas (GHG) emissions and other global climate-related challenges. The present study examines the potential of Mixed Lignocellulosic Biomass (MLB) as a sustainable feedstock for the consistent year-round production of bioethanol. The primary MLB sources considered in this research to underscore the significance of this heterogeneous strategy include sweet sorghum bagasse (SSB), sugarcane bagasse (SCB), and date palm trunk (DPT). Each of the three feedstocks, i.e., SSB, SCB, and DPT, were individually subjected to alkaline pretreatment, a step aimed at breaking down structural barriers and facilitating greater release of fermentable sugars during fermentation. Likewise, the alkaline-pretreated biomasses were subjected to simultaneous saccharification and fermentation (SSF) for 96 h, both individually as well as in various combined proportions. Individually, pretreated sweet sorghum bagasse (SSB) fibers produced the highest ethanol concentration, of 30.79 ± 0.44 g/L; an ethanol yield of 0.40 ± 0.62 g/g; an ethanol productivity of 0.42 ± 0.87 g/L/h; and a theoretical ethanol yield of 79.81% at 72 h. In contrast, the combination of MLB (50% of pretreated SSB and 50% of DPT fibers) produced a significantly higher ethanol concentration of 31.47 ± 0.57 g/L and an ethanol productivity of 0.653 ± 0.24 g/L/h in much less time, i.e., 48 h of SSF fermentation. The empirical data confirms that MLB offers a sustainable paradigm for ethanol biosynthesis by curtailing fermentation time and optimizing economic and operational efficacy. Full article

Amid rising sustainability demands, the automotive industry must understand how its Environmental, Social, and Governance (ESG) management influences consumer purchase decisions for high-involvement products. This study investigates this relationship by examining the mediating roles of brand value, perceived quality, and corporate trust. To test the research model, we analyzed survey data from Korean automotive market consumers using partial least-squares structural equation modeling. The findings reveal that governance transparency and social responsibility significantly enhance corporate trust and brand value, which are the primary drivers of purchase intention. In contrast, environmental initiatives do not directly foster trust, and the effect of perceived quality is fully mediated by brand value and corporate trust. This study advances value-driven consumption theory by demonstrating that non-financial ESG dimensions—especially governance and social responsibility—can supersede functional quality in shaping purchase decisions in high-involvement contexts. These findings suggest that automakers should prioritize governance and social initiatives as strategic levers to build trust and strengthen long-term consumer loyalty. Full article

With the surge in global maritime trade of new energy vehicles (NEVs), the roll-on/roll-off (Ro-Ro) shipping market faces a severe supply–demand imbalance, pushing shipping rates to persistently high levels. To tackle this challenge, NEV manufacturers and other automakers have begun establishing their own Ro-Ro fleets, creating an urgent need for optimized operational scheduling of these proprietary fleets. Against this context, this study focuses on optimizing the operational scheduling of automakers’ self-owned Ro-Ro fleets. Under the premise of deterministic automobile export transportation demands, a mixed-integer programming model is developed to minimize total fleet operational costs, with decision variables covering vessel port call sequence/selection, port loading and unloading quantities, and voyage speeds. A genetic algorithm is designed to solve the model, and the effectiveness of the proposed approach is validated through a real-world case study. The results demonstrate that the optimization method generates clear, actionable scheduling schemes for self-owned Ro-Ro fleets, effectively helping automakers refine their maritime logistics strategies for proprietary fleets. This study contributes to the field by focusing on automaker-owned Ro-Ro fleets and filling the research gap in cargo-owner-centric scheduling, providing a practical tool for automakers’ overseas logistics operations. Full article

Background: Cities worldwide face continuous challenges in sustainable development, particularly in transportation systems where decisions have long-lasting impacts on urban infrastructure and quality of life. The evaluation of sustainable transportation alternatives requires careful consideration of multiple indicators, making it a complex multi-criteria decision-making process. Existing multi-criteria decision-making (MCDM) frameworks often overlook the dual uncertainties introduced by both fuzzy expert judgments and probabilistic performance measures, hindering robust evaluation of transportation alternatives in developing countries. Methods: In response, this study introduces a novel hybrid methodology combining fuzzy set theory and Monte Carlo simulation to evaluate transportation alternatives through 14 comprehensive sustainability indicators. Addressing the critical need for sustainable public transportation assessment in rapidly urbanizing developing countries, where existing assessment frameworks frequently prove inadequate, we present a case study from Amman, Jordan. Results: The results reveal that a Bus Rapid Transit (BRT) system outperforms both conventional automobiles and small buses in 87.06% of simulation scenarios, underscoring its robust sustainability profile. The sensitivity analysis highlights that a BRT system is highly robust, with minimal sensitivity to changes in most criteria and strong responsiveness to critical factors such as land usage. Conclusions: This research provides decision-makers with a comprehensive, evidence-based tool for evaluating public transport investment under uncertainty. The methodology’s ability to account for multiple stakeholder perspectives while handling uncertainty makes it particularly valuable for urban planners and policymakers facing complex transportation infrastructure decisions in rapidly evolving urban environments. Full article

This study examines the mediating role of corporate culture in the relationship between corporate financial strategy and sustainability performance within Guangxi’s automobile industry. Employing a stratified sampling method, data were collected from 400 chief financial officers through questionnaires administered via Question Star. Structural equation modeling was used to analyze the responses. The findings reveal that the average score for corporate financial strategy was 3.399 (SD = 0.948), indicating moderate variation in perceptions. Corporate culture received a comparable mean of 3.463 (SD = 0.963), reflecting a similarly modest range of views among participants. Sustainability performance reported a mean score of 3.416, with a higher standard deviation (SD = 1.081), suggesting more diverse opinions regarding sustainability outcomes. The analysis confirms that both corporate financial strategy and corporate culture exert a positive influence on sustainability performance. These results indicate the need for managers in the automobile sector to continuously enhance financial strategies and foster a supportive corporate culture, as these factors significantly contribute to improved sustainability performance. Full article

Environmental, social, and governance (ESG) has increasingly received attention for its expected capacity to simultaneously enhance sustainability performance and mitigate risks among micro, small, and medium-sized enterprises (MSMEs) in supply chains. This study examines how external drivers, particularly the influences of buying firms and governments, as well as corporate entrepreneurship as an internal driver, foster MSME suppliers’ sustainability innovation management. A survey of the automobile industry in a Republic of Korea context indicates that buying firms and corporate entrepreneurship play critical roles in enhancing MSME suppliers’ sustainability innovation management. This study also reveals that corporate entrepreneurship accentuates the effects of external drivers on MSME suppliers’ sustainability innovation. Although a relationship between sustainability innovation management and operational performance was unconfirmed, this study demonstrates that corporate entrepreneurship enhances operational performance. As one of the first to explore the topic of MSME suppliers’ sustainability innovation from a corporate entrepreneurship perspective, this study has significant implications for academics, practitioners, and policymakers. Full article

This systematic bibliometric review, conducted in accordance with the PRISMA methodology, examines the literature on waste rubber tyres (WRTs) and their applications, measuring correlations between several standard metrics and identifying gaps that may stimulate new research. Using a thirty-year database from Scopus, both numerical and graphical results highlight key aspects, including geographic distribution, journal analysis, keywords, and three main research categories: environment, application, and property. Publications have grown exponentially at a rate of 17% per year. Research is concentrated in India and China, with Africa and Central America lagging behind. The United States leads in impact, while publication volume correlates moderately with gross domestic product (GDP), but negatively with international collaboration. Notably, several leading countries in automobile and tyre production have a limited academic presence in WRT research. The most prominent studies focus on material development; however, there remains a lack of practical applications for these materials. Recent trends show growing interest in WRTs within engineering, materials science, and environmental science, with multidisciplinary approaches emerging. A keyword analysis indicates a steady evolution in end-of-life tyres (ELT) research over recent years. In environmental studies, interest in ELT recycling methods has grown, though aspects such as toxicity, life cycle analysis, and leaching remain relatively unexplored. In terms of applications, research is primarily focused on pavements, while areas such as facades, blocks, and roofs remain under-studied. Finally, in material property studies, most research addresses compressive strength, while critical areas such as fire resistance, impact resistance, and thermal testing offer promising avenues for future research. Full article

Studies comparing and benchmarking cities on transport and planning have been undertaken for decades. The unique methodology in this paper is explained and then applied to the Greater Manchester (GM) and Leicester (LM) metropolitan areas in the UK. The data cover land use, wealth, transport infrastructure, mobility patterns, energy use and selected externalities. The paper asks: How do the Greater Manchester and Leicester Metropolitan Areas compare with each other and to a sample of global cities in the sustainability of their urban passenger transport systems, what are the key factors that underpin their automobile dependence and what might be done to improve the prospects for public transport, walking and cycling? The answer is presented as standardised indicators comparing GM and LM to metropolitan areas in the USA, Canada, Australia, Europe and Asia (averages), as well as ten Swedish cities plus Freiburg-im-Breisgau, Germany. Both UK metropolitan areas rank poorly on most transport factors, especially public transport and cycling rates. They have uncharacteristically high car use and energy use compared to peer cities, especially since they have supportive urban densities and other factors that can underpin much less automobile dependence. Fundamental issues are raised about GM and LM and how to improve their transport sustainability. Policy implications with eleven recommendations are provided. Full article

In the weld bonding used in automobiles, inspecting the adhesive areas is important to achieve the desired increase in rigidity. Active infrared thermography using flash lamp heating was applied to a weld-bonded specimen. Temperature differences were observed on the measurement surface depending on the presence or absence of adhesive, enabling the detection of the bonded areas. Furthermore, singular value decomposition (SVD) was applied to obtain time-series temperature variation data. SVD emphasizes the boundaries of the adhesive areas, improving the accuracy of inspections of the adhesive application areas. Full article

As part of recent measures to combat global warming, automobiles are required to be electrified and their weight reduced, leading to the advancement of multi-material structures that include aluminum alloys and aluminum die castings. Conventional fusion welding methods for joining aluminum alloys and steel materials have poor joining performance due to differences in thermal conductivity between the materials and the presence of oxide films. Friction stir welding (FSW) has been attracting attention in recent years because it is a solid-phase joining method and can also be used to join dissimilar materials. In this study, FSW overlay joints were fabricated: Aluminum alloy AA6111 was used for the upper plate, AA6061 was used for the lower plate. Non-destructive testing was performed on each joint to instantly inspect and visualize joint defects. In the case of FSW joints, no difference was observed in the heat transfer process when the joints were heated directly, but the location of the hooking could be identified by heating from a distance from the joints. The results of the analysis of the temperature change at the defect location showed a difference in heat propagation. Full article