Huo Ye¹, Jiantong Li², Lingna Xu^3,*

Chalcogenide Letters, Vol.23, No.8, 2026, DOI:10.32604/cl.2026.087654 - 18 September 2026

Abstract SF₆ is the primary insulating and arc extinction medium in gas-insulated switchgear (GIS). Sulfur hexafluoride (SF₆) decomposes to create diagnostic markers, such as sulfur dioxide (SO₂), thionyl fluoride (SOF₂), and hydrogen sulfide (H₂S) when electrical problems occur, such as partial discharge and local overheating. Accurate quantification of these fault-marker gases is important for the early identification of insulation defects and the condition assessment of SF₆-insulated equipment. Molybdenum disulfide (MoS₂) is a well-known and atomically thin van der Waals semiconductor that has attracted considerable attention as a platform for gas-sensing applications. This is due to its large accessible surface area,… More >

Kuldashbay Avazov¹, Jasur Sevinov^2,3, Komil Tashev⁴, Jamila Arzieva⁵, Tulkin Botirov⁶, Alpamis Kutlimuratov⁷, Akmalbek Abdusalomov^{2,4,8,9,10,11}, Boburjon Vafoev¹², Young Im Cho^1,*

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.087927 - 15 September 2026

Abstract Wireless sensor networks (WSNs) and Internet of Things (IoT) systems require lightweight cryptographic primitives that provide strong security under strict constraints on area, latency, and timing predictability. Ascon, selected by National Institute of Standards and Technology (NIST) as the standard for lightweight authenticated encryption, is well suited for such environments, yet application-oriented hardware implementations for WSN platforms remain underexplored. This paper presents a comprehensive evaluation of field programmable gate array (FPGA)-based Ascon architectures for secure WSN and IoT deployments, using iterative design with single permutation round and hybrid design with two-round unrolling across two FPGA… More >

Yusra Mansoor¹, Huma Jamshed^1,*, Mohammed Khouj², Muhammad I. Masud^2,*, Urooj Waheed¹, Abdul Wahid Memon³, Najeeb Ur Rehman Malik^4,*, Touqeer Ahmed Jumani⁵

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.085975 - 15 September 2026

Abstract The increasing demand for sustainable and energy-aware agricultural practices due to climate change, limited natural resources, and increasing food requirements has accelerated the adoption of Internet of Things (IoT) and machine learning (ML) technologies in smart farming. This study proposes a solar-powered IoT and ML-based framework for energy-aware crop suitability prediction in precision agriculture. The system employs low-power IoT sensors to continuously monitor important environmental and soil parameters, including temperature, humidity, soil moisture, soil temperature, heat index, nitrogen (N), phosphorus (P), and potassium (K) levels. To reduce dependence on conventional energy sources, the framework is… More >

Navod Neranjan Thilakarathne^1,*, Madhuka Priyashan Wedisinhage Don², Sharmi Malisha Dilshani³, Jamil Abedalrahim Jamil Alsayaydeh^4,*, Mohd Faizal Bin Yusof⁵, Rostam Affendi Bin Hamzah⁴

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.082189 - 15 September 2026

Abstract With the growing world population and demand for agricultural goods, agriculture requires innovative technologies that make the best use of resource, reduce waste, and increase productivity. So, smart agriculture, which involves the use of innovative digital technologies to enhance the quality and quantity of harvests, has come into play, superseding traditional agriculture. In recent years, the concept of the digital twin has intertwined with smart agriculture to enable precise control of entire farms, facilitating virtual replications. Overall, the digital twin enables continuous monitoring of real-time conditions in the field, providing valuable insights into crop health,… More >

Chirag Devendrakumar Parikh^*

Journal on Big Data, Vol.8, pp. 11-26, 2026, DOI:10.32604/jbd.2026.077330 - 07 September 2026

Abstract Sensors and large-scale measurement systems generate continuous data streams used in industrial monitoring, IoT analytics, and decision-making. However, sensor drift, undocumented maintenance, environmental stress, and component variability often degrade the integrity and reliability of collected measurements. This study proposes a compliance-integrated data integrity framework that combines hardware qualification records, traceability documentation, lifecycle validation checkpoints, and automated anomaly detection methods. The framework introduces five integrity layers that link sensor characterization with statistical filtering and compliance-driven verification. To validate feasibility, a proof-of-concept simulation was conducted using drift-injected sensor datasets. Results show that integrating compliance metadata improve anomaly More >

Xiao-Juan Li, Yu Zhang^*, Xing-She Zhou, Meng-Jie Li, Xin-Yue Liu

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.085689 - 28 August 2026

Abstract Sensor-equipped Unmanned Aerial Vehicles (UAVs) are increasingly deployed for collaborative aerial sensing, yet selecting an optimal subgroup from a heterogeneous fleet remains challenging. Existing approaches rank individual UAVs by fixed, isolated metrics (e.g., sensor type, residual energy) and deploy them sequentially, failing to quantify task-specific performance under coupled operational uncertainties arising from platform heterogeneity, sensor configuration, and environmental dynamics. To address this, we propose Near-Optimal Group UAV Selection (OGU), a capability-driven modeling method. Rather than directly manipulating raw, heterogeneous hardware parameters, OGU aggregates each UAV–sensor unit into a capability entity characterized by intrinsic task-oriented attributes… More >

Qingmin Hou¹, Guanghua Xiao¹, Tongtong Dai^2,*

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.087157 - 24 August 2026

Abstract To address the issue of angular deviation in inclined single-axis photovoltaic tracking mounts during long-term operation-caused by wind disturbances, mechanical transmission gaps, installation inaccuracies, and environmental factors-a angle sensor based on reflective fiber-optic ranging principles has been developed for monitoring the rotation angle of the main shaft. This sensor employs a structural conversion approach of “using straight lines to replace curves”, transforming the shaft’s rotational angle into linear displacement of a mirror via a gear-rack mechanism, and generating corresponding output voltage signals through variations in reflected light intensity to measure rotation angles. Due to factors… More >

Bayan Alabdullah¹, Muhammad Waqas Ahmed², Mohammad Shorfuzzaman^3,*, Jasem Almotiri⁴, Mohammed Alonazi⁵, Ahmad Jalal^6,7,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.086985 - 13 August 2026

Abstract Multimodal data fusion and deep learning have opened new frontiers in the analysis of complex visual data acquired from heterogeneous sensing systems. Flood inundation mapping represents one of the most demanding applications in this domain, requiring robust interpretation of complementary but conflicting image modalities under severe real-world constraints. This paper presents CAG-Transformer, a novel multimodal AI architecture for bi-temporal flood change detection through intelligent fusion of Sentinel-1 SAR and Sentinel-2 multispectral imagery. Three tightly integrated contributions address the core challenges of heterogeneous multimodal image analysis. A Change Attention Gate (CAG) performs adaptive channel-wise representation learning,… More >

Yaolei Wang¹, Wangyan Li^1,*, Guoliang Wei²

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.085054 - 13 August 2026

Abstract With the rapid development of unmanned aerial vehicle (UAV) technologies, simultaneous localization and mapping (SLAM) has emerged as a key enabling paradigm for autonomous navigation and environmental perception. This paper presents a comprehensive survey of recent trends in UAV-based SLAM. First, we review the fundamental components of UAV-based SLAM systems, including commonly used onboard sensors and front-end odometry methods such as visual odometry, visual-inertial odometry, and LiDAR-inertial odometry, which provide reliable ego-motion estimation. Next, we summarize back-end methodologies that enhance estimation accuracy and global consistency, covering pose graph optimization, 3D reconstruction techniques, filter-based SLAM, fusion-based multi-UAV SLAM, More >

Adeel Iqbal^1,#,*, Muhammad Faisal Siddiqui^2,#,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084851 - 13 August 2026

Abstract Hop-constrained packet routing is a fundamental problem in wireless sensor networks (WSNs), where latency constraints, energy limitations, and practical feasibility requirements greatly restrict routing choices. Traditional methods based on shortest path and greedy routing have low complexity but cannot adapt to dynamic network changes well, while reinforcement learning for routing has the potential to adapt to network variations but has not been well explored in the hard hop-constrained setting. The current study attempts to fill the gap by modeling hop-constrained routing as the decision-making problem in a finite-horizon setting. An integrated simulation environment is proposed… More >