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Found 5152 publications
Optimal harmonics prediction for distribution systems powered by multi-energy sources using bidirectional long-short term memory combined with data sequence
Publication Name: Applied Soft Computing
Publication Date: 2025-12-01
Volume: 184
Issue: Unknown
Page Range: Unknown
Description:
A multi-energy resource aims to maintain a balance between energy output and load consumption and to ensure power continuity during different operating conditions. The harmonic distortions can be estimated from the output current of a harmonic source, which may not fully reflect its true harmonic distortions due to the interactions between the state changes at the power network level and the harmonic sources. System operators monitor each system's harmonic performance under different conditions of operation to find the actual contribution of grid-connected systems to harmonic-related issues. Development of machine learning algorithms leads to effective progress in the harmonic prediction and computation. In this paper, the combined data sequencing, and Bidirectional Long-Short Term Memory (Bi-LSTM) network has been exploited for the real-time harmonic prediction of future events in multi-energy sources. The validity of the proposed Model including the applications of ANFIS, ANNs, MLRA and LSTM is conducted on the two standard systems as IEEE 9-bus and IEEE 34-bus multi energy resources system that is associated with PV systems. The simulation results, based on climate changes of solar irradiance and ambient temperature in PV systems, demonstrate that the proposed methods can accurately forecast changes in total harmonic distortion (THD) as well as the voltage profile at the point of common coupling. The performance of Bi-LSTM, original LSTM, Machine Linear Regression (MLR), and Artificial Neural Networks (ANNs) techniques were assessed. These findings provide valuable insights. Four performance validation indices, RMSE, R-squared and MSE are considered to assess the performance of the competitive learning algorithms. The results showed that in the model IEEE 9-bus, Bi-LSTM outperformed all the applied methods as its RMSE value was 0.000019 while its MSE value was 3.61e-10 and finally, the Bi-LSTM had a higher value squared error (R2) was equal 1 which indicates the effectiveness of Bi-LSTM for predicting sequential total harmonic distortion. On the other hand, in case study of IEEE 34-bus, the RMSE, MSE and R2 are 0, 3.276e-30 and 1 using Bi-LSTM which means that the Bi-LSTM leads to the best performance validation indices compared to other competitive algorithms for the tested multi-energy systems.
Open Access: Yes
Halal tourism research in Indonesian context: a bibliometric analysis
Publication Name: Discover Sustainability
Publication Date: 2025-12-01
Volume: 6
Issue: 1
Page Range: Unknown
Description:
Halal tourism is a growing sector of tourism that has attracted considerable attention in recent years due to its potential for economic growth and the need to meet the demands of Muslim travelers. This study aims to provide a comprehensive overview of halal tourism research in Indonesia through the utilization of bibliometric approach. The study utilizes Scopus database to analyze the publication trends, co-authorship, and thematic analysis, as well as the future research directions on this field in the context of Indonesia spanning the years 2017 to 2024. The findings indicate that there is a disparity in the involvement of authors and affiliations from Indonesia in terms of publications. The results show consistent growth in Indonesian publications, but emphasize the need for better quality and global dissemination. Moreover, the findings suggest that Indonesia plays a key role in the development of tourism in Indonesia due to its Muslim population and integration of Islamic principles in education and tourism. These findings highlight the importance of understanding Muslims tourists’ behavior, political economy influences, and service quality in different regions of Indonesia, thereby informing policy-making, industry practices, and future research agendas in this field.
Open Access: Yes
Integration of MULTIMOORA algorithm combined with circular q-rung orthopair fuzzy information for optimizing player positioning
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
The following paper presents a new analytical framework for the optimization of player positioning, a methodology with significant practical implications. The method implements the multi-objective optimization by ratio analysis with full multiplicative form (MULTIMOORA) in a decision-making context in which several non-commensurable performance variables have to be combined. The application of Dombi operationalizes the framework by prioritizing weighted aggregation operators coupled with circular q-rung orthopair fuzzy sets (Cq-ROFSs). The Cq-ROFSs allow multidimensional representation of uncertainty, and allow dynamic actions upon the fuzzy parameter q, such that both intuitionistic fuzzy sets and Pythagorean fuzzy sets are subsets. Two Dombi prioritized operators on Cq-ROFSs are thereby devised a Cq-ROFSs Dombi prioritized weighted averaging operator (Cq-ROFSDPWA) and a Cq-ROFSs Dombi prioritized weighted geometric operator (Cq-ROFSDPWG). Results from empirical experiments are reported that demonstrate the performance of the resulting methodology, highlighting its practical relevance. The fundamental properties of these operators are also examined. The proposed aggregation operators are applied within the MULTIMOORA technique to assess their effectiveness. Numerical examples demonstrate that the methods yield logical and consistent results across different decision-making scenarios. Comparative analyses further highlight the advantages of the Cq-ROFSDPWA and Cq-ROFSDPWG operators over existing approaches.
Open Access: Yes
ESG disclosure topics and reporting frameworks: exploratory research across automotive, construction, and energy industries
Publication Name: Discover Sustainability
Publication Date: 2025-12-01
Volume: 6
Issue: 1
Page Range: Unknown
Description:
Environmental, Social, and Governance (ESG) reporting and proper measurement of greenhouse gas emissions are becoming increasingly important for industries with substantial environmental impact. This research aims to assess the current state of ESG reporting practices and highlight areas for improvement across the automotive, construction and energy industries operating in the Central Eastern European (CEE) region. To achieve this aim, a multi-industry sustainability disclosure database was created and analyzed through a Python-based text-mining methodology, using term frequency-inverse document frequency and keyword-in-context analysis. The process involved extracting and preprocessing text from 60 sustainability reports for the year 2021, followed by constructing a custom dictionary of key ESG terms aligned with the European Sustainability Reporting Standards. The findings reveal considerable variance in the focus of qualitative disclosures across industries, particularly regarding climate change and biodiversity. The investigation underscores the need for enhanced transparency, consistent metrics, and rigorous validation in ESG reporting. The study also provides new insights into the technical possibilities of automated text analysis for sustainability reporting in the CEE region, and highlights key areas where improvement appears necessary.
Open Access: Yes
Axial strength of back to back cold formed steel short channel sections with unstiffened and stiffened web holes
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
The increasing adoption of back-to-back built-up cold-formed steel (CFS) channel columns in construction is attributed to their lightweight nature, versatility in shape fabrication, ease of transportation, cost efficiency, and enhanced load-bearing capacity. Additionally, the incorporation of web openings facilitates the integration of electrical, plumbing, and heating systems. These built-up sections are widely utilized in wall studs, truss elements, and floor joists, with intermediate screw fasteners strategically positioned at regular intervals to prevent the independent buckling of channels. Based on 18 experimental tests, this study demonstrates an excellent correlation between finite element analysis and the experimental results, confirming the accuracy of geometrically and materially nonlinear finite element modeling in predicting the axial buckling strength of built-up short columns. Furthermore, the design standards of the American Iron and Steel Institute and Australian/New Zealand Standards were found to underestimate the axial load capacity by approximately 12.5%. The primary objective of this research is to investigate the influence of various hole configurations, both with and without stiffeners, on the axial performance of built-up short CFS channel columns. A total of 180 finite element models were developed, examining four different unstiffened and edge-stiffened hole configurations, validated against experimental results from plain webs. The findings reveal that web holes and edge stiffeners significantly impact axial load-bearing capacity, while the specific shape of the openings has a negligible effect. Specifically, introducing a hole at the centroid of each web results in an approximate 8.5% reduction in axial load capacity in the absence of edge stiffening. However, the incorporation of stiffeners around the perforations mitigates this reduction and enhances both structural efficiency and load-bearing capacity. These results highlight the critical role of edge stiffening in optimizing the structural performance of perforated built-up CFS columns.
Open Access: Yes
Flower fertilization optimization algorithm with application to adaptive controllers
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
This article presents the Flower Fertilization Optimization Algorithm (FFO), a novel bio-inspired optimization technique inspired by the natural fertilization process of flowering plants. The FFO emulates the behavior of pollen grains navigating through the search space to fertilize ovules, effectively balancing exploration and exploitation mechanisms. The developed FFO is theoretically introduced through the article and rigorously evaluated on a diverse set of 32 benchmark optimization problems, encompassing unimodal, multimodal, and fixed-dimension functions. The algorithm consistently outperformed 14 state-of-the-art metaheuristic algorithms, demonstrating superior accuracy, convergence speed, and robustness across all test cases. Also, exploitation, exploration, and parameter sensitivity analyses were performed to have a comprehensive understanding of the new algorithm. Additionally, FFO was applied to optimize the parameters of a Proportional-Integral-Derivative (PID) controller for magnetic train positioning—a complex and nonlinear control challenge. The FFO efficiently fine-tuned the PID gains, enhancing system stability, precise positioning, and improved response times. The successful implementation underscores the algorithm’s versatility and effectiveness in handling real-world engineering problems. The positive outcomes from extensive benchmarking and practical application show the FFO’s potential as a powerful optimization tool. In applying multi-objective PID controller parameter optimization, FFO demonstrated superior performance with a sum of mean errors of 190.563, outperforming particle swarm optimization (250.075) and dynamic differential annealed optimization (219.629). These results indicate FFO’s ability to achieve precise and reliable PID tuning for control systems. Furthermore, FFO achieved competitive results on large-scale optimization problems, demonstrating its scalability and robustness.
Open Access: Yes
Dynamic modelling of vapour compression cycles based on an all-mode switchable moving boundary model
Publication Name: Applied Thermal Engineering
Publication Date: 2025-11-15
Volume: 279
Issue: Unknown
Page Range: Unknown
Description:
With the increasing demand for energy and growing environmental concerns, research on the performance and dynamic control strategies of chillers is vital for energy conservation and emission reduction. This work presents a seventh-order nonlinear moving boundary model with an all-mode switchable scheme for evaporators and condensers of vapour compression cycles. The proposed model, encompassing six modes, introduces a robust switching scheme that supports adjacent-mode and cross-mode transitions. Key advancements include a refined void fraction derivative model, addressing prior simplifications, and heat transfer coefficient modelling for louvred tube-fin and microchannel heat exchangers, extending applicability beyond round-tube designs. A dynamic simulation of a chiller system, validated against integral calculations, demonstrated high accuracy with simulation errors below 0.9 % and mass and energy variations of 0.15 % and 0.27 % over 24 h. A refrigerant charge model identified 0.02995 kg as optimal for maximising COP and cooling capacity under varying conditions. Steady-state and dynamic analyses showed that increased compressor speed enhances cooling performance by boosting flow rates and temperature differentials, while air velocity improves condenser efficiency and system COP. The dynamic response exhibited rapid pressure fluctuations with slower temperature changes due to external variations or heat exchanger efficiency. These findings underline the model's reliability and practical relevance.
Open Access: Yes
Design constraints of a forerunner UAV in safety improvement of first responders
Publication Name: Transportation Research Interdisciplinary Perspectives
Publication Date: 2025-11-01
Volume: 34
Issue: Unknown
Page Range: Unknown
Description:
Unmanned Aerial Vehicles (UAVs) are already in use by emergency services. Drones are becoming faster and more reliable, making them suitable for safety-critical tasks. A forerunner UAV can fly ahead of an emergency ground vehicle (EGV). It can make a decision on the traffic situation at the next intersection to notify the EGV driver if other vehicles have given the right of way or not. This notification service can increase the speed of the EGV and prevent crashes that may occur due to the driver's obstructed view. A forerunner drone for slow-speed EGV (10 m/s) has already been developed and successfully tested; however, the applicability of current drone technology to the forerunner task at higher speeds was not analyzed. This paper identifies the key parameters of the task itself and the forerunner system in a general case, and gives the main tradeoff inequalities of these design parameters. The requirements and limitations of a forerunner drone are investigated within a reasonable parameter space, and the most relevant configurations are tested in dynamic simulation using optimized velocity profiles for the drone. Software-in-the-loop tests were also performed in a complete city simulation. The results indicate that the forerunner task is solvable with current fastest or near-future drone technology if the route of the EGV is known to the UAV control.
Open Access: Yes
Empowering circular economy transformation through immersive digital open innovation
Publication Name: Journal of Innovation and Knowledge
Publication Date: 2025-11-01
Volume: 10
Issue: 6
Page Range: Unknown
Description:
Despite broad support for sustainability, the transition from linear to circular economic models remains slow and fragmented across industries. Digital technologies such as the metaverse present new opportunities for enabling circular economy (CE) practices, yet their strategic integration within organizational systems is not fully understood. To address this gap, this study proposes and empirically validates a model that explains how metaverse adoption influences CE implementation through the mediating role of Immersive Knowledge Co-Creation (IKCC), and the moderating effect of Open Eco-Innovation Capability (OEIC). Grounded in the knowledge-based view (KBV), interactive learning theory, and dynamic capabilities theory, the research develops a process-driven and capability-oriented framework to explore the mechanisms and boundary conditions for digital-enabled circular transformation. Empirical data were collected from 220 respondents in Germany's advanced manufacturing sector and analyzed using partial least squares structural equation modeling. The results confirm that IKCC significantly mediates the relationship between metaverse adoption and CE implementation, and that this mediated relationship is stronger in firms with high OEIC. These findings contribute to the growing body of literature on digital innovation in the CE by highlighting the critical role of immersive collaboration and organizational readiness in driving circular processes.
Open Access: Yes
