Search Results (355)

The growing complexity of production systems in the technology sector demands advanced tools to ensure efficiency, flexibility, and cost-effectiveness. This study presents the development of a simulation model for a selective soldering line at a technology manufacturing company in Poland, created during an engineering internship. Using FlexSim 24.2 software, the real production process was replicated, including input/output queues, manual insertion (MI) stations, soldering machines, and quality control points. Special emphasis was placed on implementing dynamic process logic via ProcessFlow, enabling detailed modeling of token flow and system behavior. Through experimentation, various configurations were tested to optimize process time and the number of soldering pallets in circulation. The results revealed that reducing pallets from 12 to 8 maintains process continuity while offering cost savings without impacting performance. An intuitive operator panel was also developed, allowing users to adjust parameters and monitor outcomes in real time. The project demonstrates that simulation not only supports operational decision-making and resource planning but also enhances interdisciplinary communication by visually conveying complex workflows. Ultimately, the study confirms that simulation modeling is a powerful and adaptable approach to production optimization, contributing to long-term strategic improvements and innovation in technologically advanced manufacturing environments. Full article

Sources of renewable energy have attracted considerable attention. Their expanded use will have a substantial impact on both the cost of energy production and climate change. Solar energy is one efficient and safe option; however, solar energy harvesting sites, irrespective of the location, can impact the ecosystem. This experimental study explores the energy available inside and outside of novel miniature energy harvesting cages by measuring light intensity and power generated. Varying light intensity outside the cage has been utilized to study the remaining energy inside the cage of a flexible design, where the heights of the harvesting panels are parameters. Cages are built from custom photovoltaic panels arranged in a staircase manner to provide access to growing plants. The balance between power generation and biological development is investigated. Two different structures are presented to explore the variation of illumination intensity inside the cages. The experimental results show a substantial reduction in energy inside the cages. The experimental results showed up to 24% reduction in illumination inside the cages in winter. The reduction is even larger in summer, up to 57%. The results from the models provide a framework to study the possible impact on a biological system residing inside the cages, paving the way for practical farming with sustainable energy harvesting. Full article

(1) Background: This study investigates whether older adult individuals support childcare policies not only out of altruism, but also due to extended self-interest arising from intergenerational co-residence. It challenges the conventional view that welfare attitudes are shaped solely by one’s own life-cycle needs. (2) Methods: Using the 2013 and 2016 waves of the Korean Welfare Panel Study waves of the Korean Welfare Panel Study, a difference-in-differences (DiD) approach compares attitudes toward government childcare spending between older adults living with children (Co-residing Older Adults) and those who do not (Non-co-residing Older Adults), before and after universal childcare policies were introduced in 2013. (3) Results: The Co-residing Older Adults consistently expressed stronger support for family policies than their counterparts. However, this support did not significantly increase after the 2013 reform, indicating that extended self-interest may not be sensitive to short-term policy changes. (4) Conclusions: Extended self-interest appears to be a stable orientation shaped by family context rather than a flexible, policy-reactive stance. These findings highlight the role of intergenerational household ties in shaping welfare attitudes and offer implications for fostering generational solidarity in aging societies. Full article

Accurate photovoltaic (PV) panel characterization is critical for optimizing renewable energy systems, but it is often hindered by the high cost of commercial tracers or the slow, error-prone nature of manual methods. This paper presents a low-cost, Arduino-based I–V curve tracer that overcomes these limitations through fully automated resistive load switching. By integrating a relay-controlled resistor bank managed by a single microcontroller, the system eliminates the need for manual intervention, enabling rapid and repeatable measurements in just 45 s. This rapid acquisition is a key advantage over manual systems, as it minimizes the impact of fluctuating environmental conditions and ensures the resulting I–V curve represents a stable operating point. Compared to commercial alternatives, our open-source solution offers significant benefits in cost, portability, and flexibility, making it ideal for field deployment. The system’s use of fixed, stable resistive loads for each measurement point also ensures high repeatability and straightforward comparison with theoretical models. Experimental validation demonstrated high agreement with a single-diode PV model, achieving a mean absolute percentage error (MAPE) of 4.40% against the manufacturer’s data. Furthermore, re-optimizing the model with field-acquired data reduces the MAPE from 18.23% to 7.06% under variable irradiance. This work provides an accessible, robust, and efficient tool for PV characterization, democratizing access for research, education, and field diagnostics. Full article

In an era where sustainable development is increasingly a core strategic issue for businesses, how top management, as the architects of corporate strategy, can achieve a synergy of economic, social, and environmental benefits through internal management mechanisms to promote corporate sustainability is a central focus for both academia and practice. This study aims to explore how Executive Cognitive Flexibility (CF) influences Firm Performance and to uncover the mediating effects of Non-market Strategy. We use panel data from Chinese A-share listed companies between 2016 and 2022 to examine and empirically analyze this mechanism. Our findings indicate that CF has a positive impact on Firm Performance. This relationship is realized through the pathway of Non-market Strategy, specifically manifesting as a reduction in Corporate Social Responsibility (CSR) and an increase in Corporate Political Activity (CPA). Further analysis reveals that the impact of executive cognitive flexibility on firm performance is differentially influenced by internal and external environmental contexts. The findings of this study provide important practical insights and policy recommendations for companies on cultivating executive cognitive flexibility, optimizing non-market strategies, and enhancing firm performance in various internal and external environments. Full article

This study introduces an intrinsic Gaussian Process Regression (iGPR) model for the first time, which incorporates non-Euclidean spatial covariates via a Gaussian process prior to analyzing the relationship between digitalization and carbon emission efficiency. The iGPR model’s hierarchical design embeds a Gaussian process as a flexible spatial random effect with a heat-kernel-based covariance function to capture the manifold geometry of spatial features. To enable tractable inference, we employ a penalized maximum-likelihood estimation (PMLE) approach to jointly estimate regression coefficients and covariance hyperparameters. Using a panel dataset linking a national digitalization (modernization) index to carbon emission efficiency, the empirical analysis demonstrates that digitalization has a significantly positive impact on carbon emission efficiency while accounting for spatial heterogeneity. The iGPR model also exhibits superior predictive accuracy compared to state-of-the-art machine learning methods (including XGBoost, random forest, support vector regression, ElasticNet, and a standard Gaussian process regression), achieving the lowest mean squared error (MSE = 0.0047) and an average prediction error near zero. Robustness checks include instrumental-variable GMM estimation to address potential endogeneity across the efficiency distribution and confirm the stability of the estimated positive effect of digitalization. Full article

Structural Health Monitoring (SHM) is an essential technique for continuously assessing structural conditions using integrated sensor systems during operation. SHM technologies have evolved to address the increasing demand for efficient maintenance strategies in advanced engineering fields, such as civil infrastructure, aerospace, and transportation. However, developing a miniaturized, cost-effective, and multi-sensor solution based on Wireless Sensor Networks (WSNs) remains a significant challenge, particularly for SHM applications in weight-sensitive aerospace structures. To address this, the present study introduces a novel WSN-based Multi-Sensor System (MSS) that integrates multiple sensing capabilities onto a 3 × 3 cm flexible Printed Circuit Board (PCB). The proposed system combines a Piezoelectric Transducer (PZT) for impact detection; a strain gauge for mechanical deformation monitoring; an accelerometer for capturing dynamic responses; and an environmental sensor measuring temperature, pressure, and humidity. This high level of functional integration, combined with real-time Data Acquisition (DAQ) and precise time synchronization via Bluetooth Low Energy (LE), distinguishes the proposed MSS from conventional SHM systems, which are typically constrained by bulky hardware, single sensing modalities, or dependence on wired communication. Experimental evaluations on composite panels and aluminum specimens demonstrate reliable high-fidelity recording of PZT signals, strain variations, and acceleration responses, matching the performance of commercial instruments. The proposed system offers a low-power, lightweight, and scalable platform, demonstrating strong potential for on-board SHM in aircraft applications. Full article

To address the issue of deformation mismatch between the exterior wall panels and the resilient frame structure under large deformations, two novel flexible devices (FDs) with different working principles are proposed in this paper. These FDs enable the exterior wall panels to achieve cooperative deformation with frame columns or beams under horizontal loads, thus improving the seismic performance of the frame structure with additional exterior wall panels. This study begins by explaining the specific design thought of the FDs based on examining the deformation characteristics of frame structures. Then, a series of low-cycle loading tests are conducted on frame specimens to demonstrate the effectiveness of the FDs. The experimental results indicate that the FDs can improve the interaction between the exterior wall panels and the main frame, reduce plastic damage to the wall panels, and increase the peak load-bearing capacity of the overall structure by approximately 17–21%. In addition, a refined finite element modeling method for the proposed FDs is presented using the ABAQUS software, providing a basis for further research on frame structures with additional exterior wall panels. Full article

Natural disasters in the United States frequently wreak havoc on critical infrastructure, affecting energy, water, transportation, and communication systems. To address these disruptions, the use of mobile power solutions like PowerKiosk trailers is a partial solution during recovery periods. PowerKiosk is a trailer equipped with renewable energy sources such as solar panels and biogas generators, offering a promising strategy for emergency power restoration. With a daily power output of 12.1 kWh, PowerKiosk trailers can support small lift stations or a few homes, providing a temporary solution during emergencies. Their key strength lies in their mobility, allowing them to quickly reach disaster-affected areas and deliver power when and where it is most needed. This flexibility is particularly valuable in regions like Florida, where hurricanes are common, and power outages can cause widespread disruption. Although the PowerKiosk might not be suitable for long-term use because of its limited capacity, it can play a critical role in disaster recovery efforts. In a community-wide power outage, deploying the PowerKiosk to a lift station ensures essential services like wastewater management, benefiting everyone. By using this mobile power solution, community resilience can be enhanced in the face of natural disasters. Full article

As the global demand for clean and sustainable energy grows, photovoltaics (PVs) have become an important technology in this industry. Thin-film and flexible PV modules offer noticeable advantages for irregular surface mounts and mobile applications. This study investigates the use of four machine learning models to detect different flexible PV module geometries based on power output data. Three identical flexible PV modules were mounted in flat, concave, and convex configurations and connected to batteries via solar chargers. The experimental results showed that all geometries fully charged their batteries within 6–7 h on a sunny day with the flat, concave-, and convex-shaped modules achieving a peak power of 95 W. On a cloudy day, the concave and convex modules recorded peak outputs of 72 W and 65 W, respectively. Simulation results showed that the XGBoost model delivered the best classification performance, showing 93% precision with the flat-mounted module and 98% recall across all geometries. In comparison, the KAN model recorded the lowest precision (78%) with the curved geometries. A calibration analysis on the ML models showed that Random Forest and XGBoost were well calibrated for the flat-mounted module. However, they also showed overconfidence and underconfidence issues with the curved module geometries. Full article

Grape marc spirits represent a significant category within the alcoholic beverage sector, particularly across Mediterranean Europe. This study aimed to construct a sensory flavor wheel—covering aroma, taste, and mouthfeel modalities—specifically for non-flavored and non-wood-aged grape marc distillates. To achieve this, we explored the feasibility of a novel methodological approach combining three rapid sensory techniques: Ultra Flash Profiling (UFP), Check-All-That-Apply (CATA), and Rate-All-That-Apply (RATA). Forty-five (45) samples from Greece, Cyprus, and Italy were evaluated by a trained panel of 12 assessors. UFP generated 205 initial descriptors, which were refined to 59 for CATA. Despite the long attribute list, CATA data helped identify the most relevant terms for the final RATA experiment. The sequential application of these methods, along with intermediate data filtering, led to the selection of 45 key descriptors with occurrence frequencies ranging from 33.3% to 97.7%. These were organized into a comprehensive flavor wheel grouped into 12 general categories. This approach offers a flexible framework for future flavor wheel construction in other under-characterized product categories. Full article

Soft body armor (SBA) remains an essential component of first responder protection. However, most SBA design concepts do not adequately address the unique performance, morphological, and psychological needs of women as first responders. In this review, female-specific designs of ballistic-resistant panels, material systems, and SBA performance testing are critically examined. The paper also explores innovations in shaping and design techniques, including darting, dartless shape construction, modular assembly, and body scanning with CAD integration to create contoured and structurally stable panels with improved coverage, reduced bulk, and greater mobility. In addition, the review addresses broadly used and emerging dry textile fabrics and fiber-reinforced polymers, considering various innovations, such as 3D warp interlock weave, shear thickening fluid (STF) coating, nanomaterials, and smart composites that improve energy dissipation and impact tolerance without sacrificing flexibility. In addition, the paper also examines various emerging ballistic performance testing standards and their revisions to incorporate gender-specific standards and measures their ability to decrease trauma effects and maintain flexibility and practical protection. Finally, it identifies existing challenges and areas of future research, such as optimizing multi-layer systems, addressing fatigue behavior, and improving multi-angle and low-velocity impact performance while providing avenues for future sustainable, adaptive, and performance-optimized body armor. Full article

This study investigates how digital transformation (DT) shapes ambidextrous innovation patterns (simultaneous vs. sequential) in tourism firms. It distinguishes between simultaneous and sequential innovation patterns and examines the mediating role of strategic flexibility in these relationships. Using econometric modeling, we analyze 11-year panel data (2012–2022) from 72 Chinese listed tourism enterprises. The study finds that DT positively influences both simultaneous and sequential innovation patterns. Furthermore, strategic flexibility plays a stronger mediating role in the simultaneous innovation pattern than in the sequential one. The research contributes to the DT literature by shedding light on how tourism firms can manage the challenges associated with ambidextrous innovation patterns to enhance long-term competitiveness and sustainable development. It also enriches the ambidextrous innovation literature by providing a holistic model that captures the dynamics of both patterns, offering valuable insights for tourism firms to better balance resource allocation and integrated utilization in pursuit of sustainable innovation outcomes. Full article

Communication between families and schools is foundational for students’ academic success, community support for schools, and teachers’ experience. Yet, few preservice teacher education programs teach novices how to engage in equitable and effective collaborations with families. This manuscript reports on a pilot study in which preservice teachers traveled to a local community school and role-played academic conversations with adults whose children were enrolled in the school. The analysis of the transcripts of the role plays, a debrief panel by family participants, and written reflections of eight participating preservice teachers and six family participants used codes derived from the Dual Capacity-Building Framework for Family-School Partnerships. The findings show that both groups of participants found opportunities for thoughtful engagement. In the role plays, preservice teachers were most likely to demonstrate cognition by thinking flexibly about how to accommodate family and student needs. Family participants were most likely to demonstrate confidence by displaying their expertise and coaching the teachers. Activities like this may be useful sites for teachers and community members to practice effective collaboration skills. More broadly, the results may point toward an underutilized capacity within preservice teacher education to support family- and community-oriented schooling. Full article

Dual Maximum Power Point Tracking (MPPT) inverters are essential in residential and small commercial solar power systems, optimizing power extraction from two independent solar panel arrays to enhance efficiency and energy harvesting. On the other hand, the Three-Level T-Type Voltage Source Inverter (3L T-Type VSI) is known for its reduced switching losses, improved harmonic distortion, and reduced part count in comparison to other three-level topologies. In this paper, a novel architecture is proposed to integrate the dual MPPT structure directly to each DC-side split capacitor of the 3L T-Type VSI, taking advantage of the intrinsic characteristics of the inverter’s topology. Further performance enhancement is achieved by integrating a classical MPPT strategy to the control framework to make it feasible for a real-case grid integration. The combination of these methods ensures faster and stable tracking under dynamic irradiance conditions. Considering that strategies dedicated to balancing the DC-link capacitor’s voltage slightly affect the AC-side current waveform, an enhanced sliding mode control (SMC) strategy tailored for dual MPPT and 3L T-Type VSI is deployed, combining the simplicity of conventional PI controllers used in the independent MPPT-based DC-DC converters with the superior robustness and dynamic performance of SMC. Real-time results obtained using the OPAL-RT Hardware-in-the-Loop platform validated the performance of the proposed control strategy under realistic test scenarios. The current THD was maintained below 4.8% even under highly distorted grid conditions, and the controller achieved a steady state within approximately 15 ms following perturbations in the DC-link voltage, sudden irradiance variations, and voltage sags and swells. Additionally, the power factor remained unitary, enhancing power transfer from the renewable source to the grid. The proposed system was able to achieve efficient power extraction while maintaining high power quality (PQ) standards for the output, positioning it as a practical and flexible solution for advanced solar PV systems. Full article