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  • Open Access

    ARTICLE

    AquaTree: Deep Reinforcement Learning-Driven Monte Carlo Tree Search for Underwater Image Enhancement

    Chao Li1,3,#, Jianing Wang1,3,#, Caichang Ding2,*, Zhiwei Ye1,3

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071242 - 12 January 2026

    Abstract Underwater images frequently suffer from chromatic distortion, blurred details, and low contrast, posing significant challenges for enhancement. This paper introduces AquaTree, a novel underwater image enhancement (UIE) method that reformulates the task as a Markov Decision Process (MDP) through the integration of Monte Carlo Tree Search (MCTS) and deep reinforcement learning (DRL). The framework employs an action space of 25 enhancement operators, strategically grouped for basic attribute adjustment, color component balance, correction, and deblurring. Exploration within MCTS is guided by a dual-branch convolutional network, enabling intelligent sequential operator selection. Our core contributions include: (1) a More >

  • Open Access

    ARTICLE

    Random Eigenvibrations of Internally Supported Plates by the Boundary Element Method

    Michał Guminiak1, Marcin Kamiński2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3133-3163, 2025, DOI:10.32604/cmes.2025.071887 - 23 December 2025

    Abstract The analysis of the dynamics of surface girders is of great importance in the design of engineering structures such as steel welded bridge plane girders or concrete plate-column structures. This work is an extension of the classical deterministic problem of free vibrations of thin (Kirchhoff) plates. The main aim of this work is the study of stochastic eigenvibrations of thin (Kirchhoff) elastic plates resting on internal continuous and column supports by the Boundary Element Method (BEM). This work is a continuation of previous research related to the random approach in plate analysis using the BEM.… More >

  • Open Access

    ARTICLE

    Comparison of Objective Forecasting Method Fit with Electrical Consumption Characteristics in Timor-Leste

    Ricardo Dominico Da Silva1,2, Jangkung Raharjo1,3,*, Sudarmono Sasmono1,3

    Energy Engineering, Vol.122, No.12, pp. 5073-5090, 2025, DOI:10.32604/ee.2025.071545 - 27 November 2025

    Abstract The rapid development of technology has led to an ever-increasing demand for electrical energy. In the context of Timor-Leste, which still relies on fossil energy sources with high operational costs and significant environmental impacts, electricity load forecasting is a strategic measure to support the energy transition towards the Net Zero Emission (NZE) target by 2050. This study aims to utilize historical electricity load data for the period 2013–2024, as well as data on external factors affecting electricity consumption, to forecast electricity load in Timor-Leste in the next 10 years (2025–2035). The forecasting results are expected… More >

  • Open Access

    PROCEEDINGS

    Internal Connection Between the Microstructures and the Mechanical Properties in Additive Manufacturing

    Yifei Wang, Zhao Zhang*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.011121

    Abstract Additive manufacturing (AM) reveals high anisotropy in mechanical properties due to the thermal accumulation induced microstructures. How to reveal the internal connection between the microstructures and the mechanical properties in additive manufacturing is a challenge. There are many methods to predict the mechanical properties based on the microstructural evolutions in additive manufacturing [1–3]. Here we summarized the main methods for the prediction of the mechanical properties in additive manufacturing, including crystal plasticity finite element method (CPFEM), dislocation dynamics (DD), and molecular dynamics (MD). We systematically examine these primary approaches for mechanical property predictions in AM,… More >

  • Open Access

    ARTICLE

    Subdivision-Based Isogeometric BEM with Deep Neural Network Acceleration for Acoustic Uncertainty Quantification under Ground Reflection Effects

    Yingying Guo1, Ziyu Cui2, Jibing Shen1, Pei Li3,*

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4519-4550, 2025, DOI:10.32604/cmc.2025.071504 - 23 October 2025

    Abstract Accurate simulation of acoustic wave propagation in complex structures is of great importance in engineering design, noise control, and related research areas. Although traditional numerical simulation methods can provide precise results, they often face high computational costs when applied to complex models or problems involving parameter uncertainties, particularly in the presence of multiple coupled parameters or intricate geometries. To address these challenges, this study proposes an efficient algorithm for simulating the acoustic field of structures with adhered sound-absorbing materials while accounting for ground reflection effects. The proposed method integrates Catmull-Clark subdivision surfaces with the boundary… More >

  • Open Access

    ARTICLE

    Probabilistic Rock Slope Stability Assessment of Heterogeneous Pyroclastic Slopes Considering Collapse Using Monte Carlo Methodology

    Miguel A. Millán1,*, Rubén A. Galindo2, Fausto Molina-Gómez1

    CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2923-2941, 2025, DOI:10.32604/cmes.2025.069356 - 30 September 2025

    Abstract Volcanic terrains exhibit a complex structure of pyroclastic deposits interspersed with sedimentary processes, resulting in irregular lithological sequences that lack lateral continuity and distinct stratigraphic patterns. This complexity poses significant challenges for slope stability analysis, requiring the development of specialized techniques to address these issues. This research presents a numerical methodology that incorporates spatial variability, nonlinear material characterization, and probabilistic analysis using a Monte Carlo framework to address this issue. The heterogeneous structure is represented by randomly assigning different lithotypes across the slope, while maintaining predefined global proportions. This contrasts with the more common approach… More >

  • Open Access

    ARTICLE

    Cuckoo Search-Deep Neural Network Hybrid Model for Uncertainty Quantification and Optimization of Dielectric Energy Storage in Na1/2Bi1/2TiO3-Based Ceramic Capacitors

    Shige Wang1, Yalong Liang2, Lian Huang3, Pei Li4,*

    CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2729-2748, 2025, DOI:10.32604/cmc.2025.068351 - 23 September 2025

    Abstract This study introduces a hybrid Cuckoo Search-Deep Neural Network (CS-DNN) model for uncertainty quantification and composition optimization of Na1/2Bi1/2TiO3 (NBT)-based dielectric energy storage ceramics. Addressing the limitations of traditional ferroelectric materials—such as hysteresis loss and low breakdown strength under high electric fields—we fabricate (1 − x)NBBT8-xBMT solid solutions via chemical modification and systematically investigate their temperature stability and composition-dependent energy storage performance through XRD, SEM, and electrical characterization. The key innovation lies in integrating the CS metaheuristic algorithm with a DNN, overcoming local minima in training and establishing a robust composition-property prediction framework. Our model accurately… More >

  • Open Access

    ARTICLE

    Antioxidant Potential of Different Plant Part of Allium roseum L. from Montenegro

    Zoran S. Ilić1,*, Ljiljana Stanojević2, Lidija Milenković1, Ljubomir Šunić1, Dragana Lalević1, Aleksandra Milenković2, Žarko Kevrešan3

    Phyton-International Journal of Experimental Botany, Vol.94, No.8, pp. 2515-2527, 2025, DOI:10.32604/phyton.2025.069082 - 29 August 2025

    Abstract This study aims to determine the phytochemical composition and antioxidant activity (AA) of different plant parts (bulbs, stalk, leaves and flowers) of wild rosy garlic (Allium roseum) from Montenegro. The flower exhibited the highest concentration of total phenols (55.7 GAE/g d.e.), followed by the leaf (25.6 mg GAE/g d.e.). The leaf displayed the highest concentration of total flavonoids (41.48 mg RE/g d.e.), followed by the flower (36.26 mg RE/g d.e.) and top part of the stalk (26.80 mg RE/g d.e.). The AA of different parts of A. roseum after 60 min of incubation decreased in the following… More >

  • Open Access

    ARTICLE

    Statistical and Visual Evaluation of Artificial Neural Networks and Multiple Linear Regression Performances in Estimating Reference Crop Evapotranspiration for Mersin

    Fatma Bunyan Unel1,*, Lutfiye Kusak1, Murat Yakar1, Abdullah Sahin2, Hakan Dogan3, Fikret Demir4

    Revue Internationale de Géomatique, Vol.34, pp. 433-460, 2025, DOI:10.32604/rig.2025.065502 - 29 July 2025

    Abstract This study aimed to create a model for calculating the total reference crop evapotranspiration (ETo) in Mersin Province from May 2015 to 2020 and to generate maps using spatial analysis. Lemons from citrus play a significant role in Mersin’s agriculture, and because of lemons’ sensitivity to temperature, ETo is essential for them. It was observed that the ETo value () calculated using the Penman-Monteith (PM) method increased over the years. A model was developed using data from 36 Automated Weather Observing Systems (AWOS) in Mersin, Türkiye, which is located in a semi-arid climate zone. The… More >

  • Open Access

    ARTICLE

    Spatial Variability Assessment on Staple Crop Yields in Hisar District of Haryana, India Using GIS and Remote Sensing

    Sanghati Banerjee1, Om Pal2, Tauseef Ahmad3, Shruti Kanga4, Suraj Kumar Singh1,*, Bhartendu Sajan1

    Revue Internationale de Géomatique, Vol.34, pp. 71-88, 2025, DOI:10.32604/rig.2025.057963 - 24 February 2025

    Abstract Agriculture is a primary activity in many countries, with wheat being a major cereal crop in India. Accurate pre-harvest forecasts of crop acreage and production are critical for policymakers to address supply-demand dynamics, pricing, and trade. This study focuses on estimating wheat acreage and yield in Barwala block, Hisar district, Haryana, for the 2019–2020 Rabi season using remote sensing techniques. Multi-temporal satellite data capturing phenological stages of wheat (Seedling to Ripening) were processed using supervised classification with a maximum likelihood classifier in ERDAS Imagine. Wheat crop acreage was determined by overlaying ground truth points on… More >

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