Yanzhao Yang¹, Kai Yang², Junwei Zhang³, Fengsuo Jiang¹, Sheng Xu¹, Lei Chen⁴, Jun Bai⁵, Luyi Lu⁵, Hua Ji⁵, Zhihao Jing⁵, Senhao Wang¹, Jingjing Zheng¹, Haifeng Zhai^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.075227 - 06 February 2026

Abstract The low-pressure and low-density conditions encountered at high altitudes significantly reduce the operating Reynolds number of micro radial-flow turbines, frequently bringing it below the self-similarity critical threshold of 3.5 × 10⁴. This departure undermines the applicability of conventional similarity-based design approaches. In this study, micro radial-flow turbines with rotor diameters below 50 mm are investigated through a combined approach integrating high-fidelity numerical simulations with experimental validation, aiming to elucidate the mechanisms by which low Reynolds numbers influence aerodynamic and thermodynamic performance. The results demonstrate that decreasing Reynolds number leads to boundary-layer thickening on blade surfaces, enhanced More >

Nur Afikah Juhari, Khairul Nizam Tahar^*

Revue Internationale de Géomatique, Vol.35, pp. 1-11, 2026, DOI:10.32604/rig.2026.070991 - 19 January 2026

Abstract The use of Unmanned Aerial Vehicles (UAVs) in photogrammetry has grown rapidly due to enhanced flight stability, high-resolution imaging, and advanced Structure from Motion (SfM) algorithms. This study investigates the potential of UAVs as a cost-effective alternative to Terrestrial Laser Scanners (TLS) for 3D building reconstruction. A 3D model of Bangunan Sarjana was generated in Agisoft Metashape Professional v.2.0.2 using 492 aerial images captured at flying altitudes of 40, 50, and 60 m. Ground control points were established using GNSS (RTK-VRS), and Total Station measurements were employed for accuracy validation. The results indicate that the 60 More >

Muhammad Ejaz¹, Muhammad Asim^2,*, Mudasir Ahmad Wani^2,3, Kashish Ara Shakil^4,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072464 - 12 January 2026

Abstract The integration of High-Altitude Platform Stations (HAPS) with Reconfigurable Intelligent Surfaces (RIS) represents a critical advancement for next-generation wireless networks, offering unprecedented opportunities for ubiquitous connectivity. However, existing research reveals significant gaps in dynamic resource allocation, joint optimization, and equitable service provisioning under varying channel conditions, limiting practical deployment of these technologies. This paper addresses these challenges by proposing a novel Fairness-Aware Deep Q-Learning (FAIR-DQL) framework for joint resource management and phase configuration in HAPS-RIS systems. Our methodology employs a comprehensive three-tier algorithmic architecture integrating adaptive power control, priority-based user scheduling, and dynamic learning mechanisms. More >

Minghui Li¹, Hongbo Li^1,*, Jiaqi Zhu², Xupeng Zhang¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072406 - 12 January 2026

Abstract To address the challenge of real-time detection of unauthorized drone intrusions in complex low-altitude urban environments such as parks and airports, this paper proposes an enhanced MBS-YOLO (Multi-Branch Small Target Detection YOLO) model for anti-drone object detection, based on the YOLOv8 architecture. To overcome the limitations of existing methods in detecting small objects within complex backgrounds, we designed a C2f-Pu module with excellent feature extraction capability and a more compact parameter set, aiming to reduce the model’s computational complexity. To improve multi-scale feature fusion, we construct a Multi-Branch Feature Pyramid Network (MB-FPN) that employs a… More >

Zhe He¹, Yaning Zhang^2,*

International Journal of Mental Health Promotion, Vol.27, No.11, pp. 1747-1768, 2025, DOI:10.32604/ijmhp.2025.070491 - 28 November 2025

Abstract Background: Depression represents a significant global mental health burden, particularly among middle-aged and older Chinese with chronic diseases in high-altitude regions, where harsh environmental conditions and limited social support exacerbate mental health disparities. This paper aims to develop an interpretable machine learning prediction framework to identify the key factors of depression in this vulnerable population, thereby proposing targeted intervention measures. Methods: Utilizing data from the China Health and Retirement Longitudinal Study in 2020, this paper screened out and analyzed 2431 samples. Subsequently, Recursive Feature Elimination and Least Absolute Shrinkage and Selection Operator were applied to screen… More >

Chao Li^1,3,#, Quanzhi Feng^1,3,#, Caichang Ding^2,*, Zhiwei Ye^1,3

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3605-3621, 2025, DOI:10.32604/cmc.2025.063703 - 03 July 2025

Abstract The increasing adoption of unmanned aerial vehicles (UAVs) in urban low-altitude logistics systems, particularly for time-sensitive applications like parcel delivery and supply distribution, necessitates sophisticated coordination mechanisms to optimize operational efficiency. However, the limited capability of UAVs to extract state-action information in complex environments poses significant challenges to achieving effective cooperation in dynamic and uncertain scenarios. To address this, we presents an Improved Multi-Agent Hybrid Attention Critic (IMAHAC) framework that advances multi-agent deep reinforcement learning (MADRL) through two key innovations. Firstly, a Temporal Difference Error and Time-based Prioritized Experience Replay (TT-PER) mechanism that dynamically adjusts… More >

Halah Hasan Mahmoud¹, Marwan Kadhim Mohammed Al-Shammari¹, Gehad Abdullah Amran^2,3,*, Elsayed Tag eldin^4,*, Ala R. Alareqi⁵, Nivin A. Ghamry⁶, Ehaa ALnajjar⁷, Esmail Almosharea⁸

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 573-589, 2023, DOI:10.32604/cmc.2023.039363 - 08 June 2023

Abstract Utilizing artificial intelligence (AI) to protect smart coastal cities has become a novel vision for scientific and industrial institutions. One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles (UVs) for anti-submarine attacks. This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy. The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach, and the Re-fragmentation strategy is used in the Network… More >

Shuqin Zhang^1,#, Bin Zhang^2,#, Jianying Wu³, Jin Luo¹, Haomin Shi¹, Jirong Qi^3,4,*, Huilian Yang^1,5,*

Congenital Heart Disease, Vol.18, No.2, pp. 127-150, 2023, DOI:10.32604/chd.2023.025616 - 15 March 2023

Abstract Objectives: To estimate the prevalence of Congenital Heart Disease (CHD) in school-age children, to identify the extent to which altitude affects the prevalence of the disease, and to examine trends in prevalence over time in China. Methods: Seven databases were systematically searched and last retrieved on September 10, 2021 for all studies reporting the prevalence of CHD in children after 1970 in China, which were then divided into high and low altitude regions based on 2500 meters above sea level. The random-effected model was used to combine prevalence data and subgroups analysis. The baseline data of… More > Graphic Abstract

Saifur Rahman Sabuj¹, Mohammad Saadman Alam², Majumder Haider², Md Akbar Hossain³, Al-Sakib Khan Pathan^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2023.024078 - 06 February 2023

Abstract This paper discusses the significance and prospects of low altitude small satellite aerial vehicles to ensure smooth aerial-ground communications for next-generation broadband networks. To achieve the generic goals of fifthgeneration and beyond wireless networks, the existing aerial network architecture needs to be revisited. The detailed architecture of low altitude aerial networks and the challenges in resource management have been illustrated in this paper. Moreover, we have studied the coordination between promising communication technologies and low altitude aerial networks to provide robust network coverage. We talk about the techniques that can ensure userfriendly control and monitoring More > Graphic Abstract

Jianghua Cheng^1,2, Xiaojian Li², Lei Shi^3,*, Kangbo Lu³, Ling Leng³

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.4, pp. 959-975, 2023, DOI:10.32604/fdmp.2023.023687 - 02 November 2022

Abstract Power deterioration is a major problem for diesel engines operating at high altitudes. This problem stems from the limited availability of turbocharger energy, which is not enough to increase the boost pressure to the required level. In this study, a control strategy is introduced in order to achieve engine power recovery at different altitudes. It is shown that as the altitude increases from 0 to 4500 m, the required boost pressure ratio increases from 2.4 to 4.3. The needed turbocharger energy should be increased accordingly by 240%, and the TCC (turbine characterization coefficient) should be More >