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Found 6374 publications

Iterative Feedback Tuning of Anti-Windup PI Fuzzy Control of Tower Crane System Payload Position

Claudiu Radu Pozna Radu Emil Precup Miruna Maria Damian Raul Cristian ROMAN

Publication Name: IEEE International Conference on Fuzzy Systems

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This paper proposes the data-driven tuning of low-cost Proportional-Integral (PI) fuzzy control of the payload position of tower crane systems using Iterative Feedback Tuning (IFT). A back-calculation and tracking anti-windup diagram is included to prohibit integrator windup and compensate for the process's dead-zone and saturation nonlinearity. A two-stage tuning strategy is proposed. In the first stage, the parameters of the fuzzy logic part of the PI fuzzy controller and the anti-windup tracking gain are optimally tuned in a model-based manner using an original version of the hybrid Particle Filter-Particle Swarm Optimization algorithm, improved by adding an information feedback model. In the second stage, the parameters of the linear part of the PI fuzzy controller are tuned in a data-driven manner using IFT, and then mapped to the remaining PI fuzzy controller parameters using the modal equivalence principle. The efficacy of the new data-driven fuzzy control strategy is demonstrated through experimental results, and the comparison shows the performance improvement over other strategies designed using competing optimization algorithms.

Open Access: Yes

DOI: 10.1109/FUZZ62266.2025.11152023

Real-Time Out of Distribution Detection in 2D Object Detection for Autonomous Cars

Andrea Ádámné Major Zoltán Weltsch Lóránt Szabó

Publication Name: Engineering Perspective

Publication Date: 2025-01-01

Volume: 5

Issue: Special-Issue

Page Range: 28-35

Description:

The development of autonomous transportation systems represents a critical step toward achieving intelligent and reliable mobility. Ensuring accurate, real-time environmental perception and the robust detection of unexpected or rare events remains a major challenge for autonomous vehicles operating in complex and dynamic environments. To address this, we propose a novel processing pipeline that constructs Bird’s Eye View (BEV) representations from raw 3D LiDAR point clouds using both intensity and height map channels, thereby retaining essential geometric and reflective features. On top of these BEV representations, an optimized YOLOv11-based deep learning model is applied for high-precision object detection. A key contribution of our work is the integration of a real-time Out-of-Distribution (OOD) detection module, which employs lightweight statistical techniques in conjunction with learned feature representations to ensure minimal computational overhead while maintaining operational robustness. The proposed architecture enables the reliable identification of standard traffic objects as well as the detection of atypical or previously unseen events, such as overturned vehicles or unknown obstacles. Experimental evaluation on representative driving scenarios demonstrates that our method achieves approximately 95% detection accuracy, outperforming conventional baselines in both speed and reliability. Overall, the results highlight the potential of combining state-of-the-art deep neural detection frameworks with efficient, statistically grounded OOD analysis for enhancing the safety and trustworthiness of autonomous vehicle perception systems.

Open Access: Yes

DOI: 10.64808/engineeringperspective.1814718

Quantifying the role of digitalization, financial technology, governance and SDG13 in achieving environment conservation in the perspective of emerging economies

Laszlo Vasa Xiqiang Xia Muhammad Sibt-e-Ali Weihao Yi

Publication Name: Environment Development and Sustainability

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Digitalization and fintech are essential in improving financial service delivery and helping businesses and consumers manage their financial services better. Since its successful trial during the COVID-19 measures, digitalization and fintech have emerged as a new hope for low-carbon sustainable economic development. Therefore, advanced and emerging economies concentrate on digitalization (DIG) and fintech to meet carbon neutrality requirements. Thus, this study helps understand the significance of elements in gaining environmental conservation and aims to develop a relevant relationship between digitalization, fintech, SDG13, and governance. To achieve the abovementioned objectives of this study, some modern and traditional econometric tools and methods were adopted, such as ARDL and Q-ARDL, to assess the selected emerging economies dataset from 1990 to 2022. The results of this study show that the study’s components are crucial in achieving environmental preservation over the long run in emerging economies. Moreover, Q-ARDL indicates that every factor in this study influences environmental conservation in different quantiles. Consequently, the Environmental Kuznets curve prevails in the economy, and the long-term attainment of carbon neutrality is greatly assisted by digitization, fintech, governance, and SDG13. Hence, it is essential to implement extensive and far-reaching policy measures in various domains such as environmental regulations, promotion of the digital economy, regulation and sustainable technology, and utilization of clean energy resources.

Open Access: Yes

DOI: 10.1007/s10668-024-05940-4

Exploring murE protein inhibitors of Tropheryma whipplei through pharmacoinformatic approaches incorporating solubility-enhancing formulation insights

Seil Kim Ibrar Ahmed Y. Waheed Hanan A. Ogaly Zarrin Basharat Fatimah A.M. Al-Zahrani Madiha Islam Calvin R. Wei

Publication Name: Frontiers in Pharmacology

Publication Date: 2025-01-01

Volume: 16

Issue: Unknown

Page Range: Unknown

Description:

Tropheryma whipplei the causative agent of Whipple disease, presents a diagnostic challenge due to its diverse symptomatology, including weight loss, abdominal pain, diarrhea, joint pain, fever, and occasionally neurological manifestations. Its resistance to fluoroquinolones complicates treatment further. Traditional methods for antibiotic susceptibility testing are ineffective as Tropheryma whipplei cannot be cultured in axenic media. To address this, we explored potential drug targets within its core genome as no drug targets from this bacterium have been studied so far. murE, a macrolide-resistant enzyme, emerged as a promising candidate exhibiting both resistance and drug target characteristics. We screened over 1,000 lead-like Ayurvedic compounds against the target enzyme UDP-N-acetylmuramyl-tripeptide synthetase and identified three promising candidates: (1) Ergost-5-en-3-ol (3beta,24xi), (2) [6]-Gingerdiol 3-monoacetate, and (3) Valtrate. DiffDock and GNINA rescoring yielded consistent binding strength rankings. Molecular dynamics simulations over 100 nanoseconds confirmed stable interactions with these compounds. ADMET analysis indicated low water solubility, but coupling with cyclodextrin SBE-β-CD improved solubility. None of the compounds showed hepatotoxic effects, though Valtrate exhibited AMES toxicity. Based on the favorable properties, we propose scaffold hopping and further in vitro/in vivo studies on [6]-Gingerdiol 3-monoacetate. Our findings offer potential avenues for combating T. whipplei infections, addressing the limitations posed by antibiotic resistance.

Open Access: Yes

DOI: 10.3389/fphar.2025.1630038

Combined asymmetric influences of renewable energy consumption and categorical economic policy uncertainty on economic growth in Japan: New insights from QQR and KRLS approaches

Gagan Deep Sharma Magdalena Radulescu D. Balsalobre-Lorente Sanjeet Singh M. Usman

Publication Name: Environment Development and Sustainability

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This study focuses on the asymmetric relationship between categorical economic policy uncertainty indices and Japanese economic growth and renewable energy consumption from January 1987 to December 2021. Economic policy uncertainty has multidimensional effects on the global economy. To address non-linearity, Kernel-Based Regularized Least Squares (KRLS) and quantile-on-quantile regression (QQR) are applied to examine the impact of fiscal policy uncertainty, monetary policy uncertainty, trade policy uncertainty, and exchange rate uncertainty on economic growth and renewable energy consumption. The average KRLS results indicate that fiscal and exchange rate policy uncertainty negatively influence economic growth, while uncertainty in monetary and trade policy has a favorable impact in the long-term. A significant decrease in renewable energy consumption is attributed to increasing fiscal and trade policy uncertainty indices, whereas monetary and exchange rate policy uncertainty contributes to the enhancement of renewable energy consumption. The QQR results align with the KRLS findings, with a slight variation for monetary policy uncertainty, which was found to be negligible for economic growth across all quartiles according to QQR approach. Given the recent increase in economic policy uncertainty due to the COVID-19 pandemic and the Ukrainian conflict, our findings support several crucial policy recommendations for promoting economic development and renewable energy consumption in Japan.

Open Access: Yes

DOI: 10.1007/s10668-025-06156-w

Performance Evaluation and Selection of Appropriate Congestion Control Algorithms for MPT Networks

Naseer Al-Imareen Gábor Lencse

Publication Name: International Journal of Advanced Computer Science and Applications

Publication Date: 2025-01-01

Volume: 16

Issue: 2

Page Range: 109-119

Description:

Recent academic research highlights a growing interest in multipath technologies, which offer promising solutions to networking challenges in complex environments. This interest is reflected in the emergence of protocols such as Multipath TCP (MPTCP) and Multipath UDP-in-GRE (MPT-GRE). The development of network protocols, particularly various iterations of the Transmission Control Protocol (TCP), has been distinguished by congestion detection and control algorithms, such as HighSpeed, CUBIC, Reno, LP, BBR, and Illinois. This paper evaluates the performance and suitability of these algorithms for multipath MPT-GRE networks under varying conditions, including delay, jitter, and data loss at different transmission speeds (both symmetric and asymmetric). Using StarBED resources, we applied delay, jitter, or packet loss to one of two physical paths to simulate congestion. The results demonstrate that some algorithms, HighSpeed and BBR among them, significantly enhance Quality of Service (QoS) metrics and network throughput in multipath MPT-GRE networks. These findings provide valuable insights into their performance and practical applications.

Open Access: Yes

DOI: 10.14569/IJACSA.2025.0160211

Sustainable Design of Steel Frames Based on Topological Optimization Considering Geometrical and Material Nonlinearities

Marco Domaneschi Majid Movahedi Rad Raffaele Cucuzza Muayad Habashneh Péter Grubits

Publication Name: Lecture Notes in Civil Engineering

Publication Date: 2025-01-01

Volume: 770 LNCE

Issue: Unknown

Page Range: 204-213

Description:

This research introduces a sustainable approach to designing steel frames, specifically focusing on the topological optimization of I-beam webs. The proposed methodology incorporates the plastic behavior of structural steel and considers geometric nonlinearity. The primary objective of the study is to provide an environmentally sustainable design that achieves maximum material efficiency. To accomplish this goal, the bi-directional evolutionary structural optimization (BESO) approach is employed. Four different beam-column setups, each featuring various beam web formations, were validated according to previous experimental tests. Based on the results, topology optimization was conducted, considering the volume fraction corresponding to the different web openings. Subsequently, the structural behavior in terms of stress intensity of the optimized and conventional configurations was compared. Subsequently, during the final stage, the volume fraction was reduced to 60%, and the performance of the resulting setup was examined. The results of this research demonstrate the efficiency of topology optimization and suggest that this technique has the potential to reduce the material quantity required for producing steel structures while achieving better performance in terms of stress levels, thus providing an environmentally sustainable design.

Open Access: Yes

DOI: 10.1007/978-3-032-08407-1_18

MODFLOW-Based Simulation of Groundwater Response to Rainfall in the Coastal Plain of Al-Hsain Coastal Basin, Syria

Katalin Bene Mahmoud Ahmad

Publication Name: Chemical Engineering Transactions

Publication Date: 2025-01-01

Volume: 121

Issue: Unknown

Page Range: 25-30

Description:

Groundwater is an important factor in sustaining water supply in semi-arid coastal basins, where surface water resources are limited and climatic variability greatly affects availability. Rainfall events translated to groundwater recharge are of paramount importance for planning as well as for sustainable resource management in the Mediterranean catchment. The interaction between rainfall and groundwater level is particularly complex within areas of geological heterogeneity and seasonal climatic regimes. As valuable as this relationship is, it continues to be poorly understood in the most vulnerable areas, including western Syria. This research examines the dynamic interaction between rainfall and groundwater levels in the Al-Hsain Basin, a semi-arid coastal area in western Syria. A transient groundwater flow model was built with MODFLOW and calibrated against 4 y (2020–2024) of monthly data from 35 observation wells and local precipitation measurements. The model effectively replicated seasonal groundwater variations controlled largely by rain, and spatial variations related to geological heterogeneity. A (0–1) month time lag between rainfall maxima and groundwater response suggests delayed infiltration in the unsaturated zone. Model performance was tested with statistical and hydrograph analyses, illustrating excellent agreement against over 95 % of observed data. The results confirmed the model as it gave a hydraulic head distribution very similar to the monitoring wells data (variations of less than 0.10–0.25 m). Spatial maps and water balance overviews under wet and dry conditions proved the model's robustness under hydrological conditions. Despite some data limitations, this study offers helpful data on groundwater recharge processes and practical recommendations for improving water resource management in similar Mediterranean coastal settings.

Open Access: Yes

DOI: 10.3303/CET25121005

Correction: The Gaza conflict and its implications for the sustainable development goals: a comprehensive analysis (Environment, Development and Sustainability, (2025), 10.1007/s10668-025-06763-7)

Carlos Parra-López Monica Trif Yehia El-Temsah Abdo Hassoun Mohamed Buheji Dunya Ahmed Iman Dankar Ashutosh Samadhiya Abderahman Rejeb Lana Shehadeh Claudia Terezia Socol Dalal Iriqat Tarek Ben Hassen Nadia Mahdi Ahmad Nour Hassoun Muna Khoury Omer Althafery Saker Ben Abdallah

Publication Name: Environment Development and Sustainability

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

In this article, the author name ‘Abderahman Rejeb’ was incorrectly published as ‘Abderrahman Rajeb’. The original article has been corrected.

Open Access: Yes

DOI: 10.1007/s10668-025-07082-7