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  • Open Access

    REVIEW

    A Challenge-Driven Survey on UAV-Based Target Tracking

    Lingyu Jin1,2, Rui Wang1,2, Bo Huang1,2,*

    CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.080050 - 08 May 2026

    Abstract Unmanned Aerial Vehicle (UAV) target tracking is one of the key technologies in aerial intelligent perception systems, playing a vital role in applications such as traffic monitoring, border patrol, disaster response, search and rescue, environmental monitoring, and military reconnaissance. Compared with generic object tracking tasks, UAV platforms exhibit significant differences in imaging perspectives, target scales, motion patterns, and onboard computing capabilities, which pose unique challenges for UAV target tracking, including small targets and drastic scale variations, platform motion and motion blur, complex backgrounds and frequent occlusions, low-light conditions at night, as well as real-time and… More >

  • Open Access

    ARTICLE

    Optimization and Scheduling Method for Wind-Solar-Thermal-Storage Power System of Multiple Energy Stations Using Correlation-IGDT

    Yang Liu1, Yinguo Yang1, Pingping Xie1, Qiuyu Lu1, Yue Chen1, Zhanpeng Xu2,*, Zejie Huang2

    Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2025.068436 - 27 April 2026

    Abstract With the large-scale integration of wind and solar energy into the power grid, the power system is facing uncertainty challenges in multiple links, such as source, grid, and load. How to efficiently dispatch flexible resources, such as energy storage, has become an urgent problem to be solved. To this end, this paper considers the correlation between new energy stations due to natural conditions, uses Vine-Copula theory to describe the correlation characteristics of the output of multiple new energy stations, and proposes a wind solar new energy output scenario generation method based on Vine-Copula theory; Then,… More >

  • Open Access

    ARTICLE

    A Robust Damage Identification Method Based on Modified Holistic Swarm Optimization Algorithm and Hybrid Objective Function

    Xiansong Xie1,*, Xiaoqian Qian2

    Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.074148 - 31 March 2026

    Abstract Correlation function of acceleration responses-based damage identification methods has been developed and employed, while they still face the difficulty in identifying local or minor structural damages. To deal with this issue, a robust structural damage identification method is developed, integrating a modified holistic swarm optimization (MHSO) algorithm with a hybrid objective function. The MHSO is developed by combining Hammersley sequence-based population initialization, chaotic search around the worst solution, and Hooke-Jeeves pattern search around the best solution, thereby improving both global exploration and local exploitation capabilities. A hybrid objective function is constructed by merging acceleration correlation… More >

  • Open Access

    ARTICLE

    Numerical Investigation of Rainfall-Induced Shear Crack Propagation in Railway Embankment Slopes

    Jiye Chen1,*, Min Fu2, Sudath Loku-Pathirage3, Bing Leng4

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.073689 - 30 March 2026

    Abstract Slope failures, particularly in railway embankments during intense rainfall, are a major cause of economic damage and humanitarian loss. To forecast how shear cracks develop in slopes under heavy precipitation, we present a novel modeling framework: the Extended Cohesive Damage Element enhanced by soil moisture (SMECDE). The method first translates forecasted rainfall into soil moisture levels via an established correspondence. Then, recognizing that rainfall infiltration lowers soil cohesion—particularly at varying depths—we introduce a Soil Moisture Decoherence Model (SMDM) based on experimental data, which quantifies how cohesion degrades with moisture and how depth affects this process. More >

  • Open Access

    ARTICLE

    Semantic Causality Evaluation of Correlation Analysis Utilizing Large Language Models

    Adam Dudáš*

    CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.076507 - 12 March 2026

    Abstract It is known that correlation does not imply causality. Some relationships identified in the analysis of data are coincidental or unknown, and some are produced by real-world causality of the situation, which is problematic, since there is a need to differentiate between these two scenarios. Until recently, the proper−semantic−causality of the relationship could have been determined only by human experts from the area of expertise of the studied data. This has changed with the advance of large language models, which are often utilized as surrogates for such human experts, making the process automated and readily… More >

  • Open Access

    ARTICLE

    Association of tertiary lymphoid structures and benign lymphoepithelial lesions in NIH-category IV prostatitis: pathophysiological correlations

    Dorian Dikov1, Maria Koleva2,*, Kiril Simitchiev3, Anelia Bivolarska4, Albena Fakirova5, Victoria Sarafian6,7

    Canadian Journal of Urology, Vol.33, No.1, pp. 125-134, 2026, DOI:10.32604/cju.2025.068575 - 28 February 2026

    Abstract Background: Chronic inflammation is closely associated with the most common and socially significant prostate conditions, including benign prostatic hyperplasia (BPH), prostate cancer (PCa), and prostatitis syndromes. NIH-category IV prostatitis (histologic prostatitis, HP) is defined as asymptomatic chronic inflammation of the prostate. The presence of lymphoid follicles, referred to as tertiary lymphoid structures (TLSs), along with benign lympho-epithelial lesions (BLELs), is among the key histological indicators of immune inflammation and can be assessed relatively easily. This study aimed to quantitatively assess TLSs and BLELs, as well as their relationship with the severity of HP. Methods: We… More >

  • Open Access

    ARTICLE

    Multilevel Military Image Encryption Based on Tri-Independent Keying Approach

    Shereen S. Jumaa1, Mohsin H. Challoob2, Amjad J. Humaidi2,*

    CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074752 - 10 February 2026

    Abstract Military image encryption plays a vital role in ensuring the secure transmission of sensitive visual information from unauthorized access. This paper proposes a new Tri-independent keying method for encrypting military images. The proposed encryption method is based on multilevel security stages of pixel-level scrambling, bit-level manipulation, and block-level shuffling operations. For having a vast key space, the input password is hashed by the Secure Hash Algorithm 256-bit (SHA-256) for generating independently deterministic keys used in the multilevel stages. A piecewise pixel-level scrambling function is introduced to perform a dual flipping process controlled with an adaptive… More >

  • Open Access

    ARTICLE

    Spatio-Temporal Graph Neural Networks with Elastic-Band Transform for Solar Radiation Prediction

    Guebin Choi*

    CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.073985 - 29 January 2026

    Abstract This study proposes a novel forecasting framework that simultaneously captures the strong periodicity and irregular meteorological fluctuations inherent in solar radiation time series. Existing approaches typically define inter-regional correlations using either simple correlation coefficients or distance-based measures when applying spatio-temporal graph neural networks (STGNNs). However, such definitions are prone to generating spurious correlations due to the dominance of periodic structures. To address this limitation, we adopt the Elastic-Band Transform (EBT) to decompose solar radiation into periodic and amplitude-modulated components, which are then modeled independently with separate graph neural networks. The periodic component, characterized by strong More >

  • Open Access

    ARTICLE

    Integrating Attention Mechanism with Code Structural Affinity and Execution Context Correlation for Automated Bug Repair

    Jinfeng Ji1, Geunseok Yang2,*

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071733 - 12 January 2026

    Abstract Automated Program Repair (APR) techniques have shown significant potential in mitigating the cost and complexity associated with debugging by automatically generating corrective patches for software defects. Despite considerable progress in APR methodologies, existing approaches frequently lack contextual awareness of runtime behaviors and structural intricacies inherent in buggy source code. In this paper, we propose a novel APR approach that integrates attention mechanisms within an autoencoder-based framework, explicitly utilizing structural code affinity and execution context correlation derived from stack trace analysis. Our approach begins with an innovative preprocessing pipeline, where code segments and stack traces are… More >

  • Open Access

    ARTICLE

    Improving Online Restore Performance of Backup Storage via Historical File Access Pattern

    Ruidong Chen1,#, Guopeng Wang2,#, Jingyuan Yang1, Ziyu Wang1, Fang Zou1, Jia Sun1, Xingpeng Tang1, Ting Chen1,*

    CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.068878 - 12 January 2026

    Abstract The performance of data restore is one of the key indicators of user experience for backup storage systems. Compared to the traditional offline restore process, online restore reduces downtime during backup restoration, allowing users to operate on already restored files while other files are still being restored. This approach improves availability during restoration tasks but suffers from a critical limitation: inconsistencies between the access sequence and the restore sequence. In many cases, the file a user needs to access at a given moment may not yet be restored, resulting in significant delays and poor user… More >

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