Anping Wan^1,2,3, Yingchang Gao^1,3, Weikang Liu¹, Rui Yin¹, Khalil Al-Bukhaiti^1,3,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081719 - 15 June 2026

Abstract Vertical roller mills are essential for energy-intensive grinding in cement, minerals, and metallurgy industries, consuming up to 50% of plant electricity and frequently experiencing operational instabilities (including excessive vibration and main motor current fluctuations) that drive unplanned downtime, increased wear, and reduced throughput. Despite their importance, real-time autonomous optimization remains challenging due to the nonlinear interactions among grinding pressure, feed rate, separator speed, and aerodynamic factors, which limit traditional control strategies under varying loads. This paper presents a real-time operational optimization system for large-scale vertical roller mills using big industrial data and artificial intelligence (AI).… More >

Peeyush Kumar Kamlesh^1,*, Himanshi Sharma², Shrikant Verma¹, Ajay Singh Verma^3,4, Reena Saxena⁵, Dinesh C. Sharma⁶

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081382 - 15 June 2026

Abstract In the present work, Ba₃PX₃ (X = F, Cl, Br, I) all-inorganic and lead-free halide compositions have been studied as possible replacements for hybrid perovskites using first-principles calculations. All the considered materials were found to exhibit direct band gaps at the Γ-point, decreasing from 2.37 eV (Ba₃PF₃) to 1.48 eV (Ba₃PI₃). The optical calculations reveal strong absorption in the visible and near-UV regions, with the static dielectric constants ranging from 2.75 to 4.35 in the halide series. All the compounds are mechanically stable and have tuneable ductility and stiffness properties. Lattice stability is confirmed by thermodynamic analysis More >

Peiying Zhang^1,2, Yihong Yu^1,2, Lizhuang Tan^3,4,*, Shuqing He⁵, Jian Wang⁶, Ameer El-Sayed⁷

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081224 - 15 June 2026

Abstract As a core information infrastructure in the 6G era, the Space-Air-Ground Integrated Network (SAGIN) integrates space-based, air-based, and ground-based network resources to achieve seamless communication across all domains. However, its characteristics such as heterogeneous node coupling and dynamic topology changes make it prone to cascading failures, severely threatening critical business continuity in Internet of Things (IoT) applications spanning smart cities, healthcare, transportation, and industrial automation. This paper conducts systematic research addressing challenges including modeling difficulties in SAGIN cascading failure propagation, insufficient coordination of defense strategies, and poor resource adaptability. First, a multi-factor coupled dynamic model… More >

Ambreen Memon¹, Aaron Bere¹, Muhammad Nadeem Ali², Byung-Seo Kim^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.078988 - 15 June 2026

Abstract The modern internet infrastructure has enabled numerous applications by providing a seamless connectivity experience across each mode of connectivity. Infrastructure-based connectivity and device-to-device (D2D) are well-known connectivity modes for internet-based applications. The selection of the underlying communication medium significantly affects energy consumption during data transfer. This study proposes an Energy-Efficient Data Dissemination Approach (EEDDA) that integrates encounter prediction with a multi-criteria decision-making (MCDM) framework to reduce infrastructure-based energy consumption in IoT mobility environments. Unlike traditional optimization approaches that focus on single-objective routing or static network models, the proposed framework dynamically selects between Device-to-Device (D2D) and More >

Priyanka Halder, Gopikrishnan Sundaram^*

Journal on Internet of Things, Vol.8, pp. 127-153, 2026, DOI:10.32604/jiot.2026.073962 - 29 May 2026

Abstract The need for intelligent learning frameworks that can function under stringent limitations relating to privacy, energy, scalability, and trust has increased due to the Internet of Things’ (IoT) and the Internet of Artificial Things’ (IoAT) explosive expansion. Federated Learning (FL), which allows collaborative model training without sharing raw data, has become a potential approach. Non-IID data delivery, inconsistent client engagement, vulnerability to poisoning assaults, and low resource knowledge are among of the significant obstacles that FL alone must overcome. Blockchain integration adds extra overhead in terms of latency, energy consumption, and scalability, but it has… More >

Meng Zhao¹, Shuai Li¹, Yuanyuan Zhang^2,3, Yunduan Qin^2,3, Yu Xu^2,3, Chunyang Feng^2,3, Kekang Su^2,3, Xinlei Guo^2,3, Changwei Shen^1,*, Jingping Yuan^2,3,*

Phyton-International Journal of Experimental Botany, Vol.95, No.5, 2026, DOI:10.32604/phyton.2026.077668 - 27 May 2026

Abstract Chinese cabbage (Brassica rapa ssp. pekinensis) is a typical potassium (K)-demanding crop that is highly sensitive to soil K availability. Severe soil potassium deficiency in production fields frequently impairs both yield and quality. Therefore, screening for potassium-efficient varieties is essential for identifying germplasm resources and breeding materials tolerant to low-K conditions. To evaluate genetic variation in potassium utilization efficiency, 12 Chinese cabbage germplasms were assessed under two field conditions: with adequate potassium supply (K₂O 165 kg/ha) and without potassium application (K₂O 0 kg/ha). Fourteen parameters, including yield, plant growth, potassium content, and potassium accumulation, were measured and compared.… More >

José M. Campos-Salazar^1,*, Felipe Santander², Eduardo Keim³

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.075407 - 27 May 2026

Abstract A nonlinear dynamic framework is developed to represent the coupled mass- and energy-transfer phenomena governing an industrial phosphate-pebble dryer. The formulation integrates combustion, gas–solid heat exchange, moisture evaporation, and exhaust-draft dynamics into a unified set of nonlinear differential equations suitable for transient analysis and control design. Steady-state operating conditions are first established, followed by local linearization to enable the synthesis of decentralized proportional–integral (PI) controllers using direct-synthesis principles. The resulting control architecture regulates key process variables, including vacuum pressure, outlet moisture content, and furnace temperature. The proposed model is implemented in MATLAB/Simulink using a modular… More > Graphic Abstract

Federico Minelli^1,*, Diana D’Agostino¹, Vennapusa Jagadeeswara Reddy², Panagiotis Michailidis^3,4

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.074048 - 27 May 2026

Abstract This study investigates the problem of prioritizing rooftop renewable energy (RE) system configurations for a multi-family residential building in Mediterranean climate. The analysis focuses on fixed-tilt photovoltaics (PV), single-axis and dual-axis tracking PV, and small vertical-axis wind turbines (VAWT), each assessed with and without lithium-ion storage. A co-simulation framework is used, coupling EnergyPlus building-HVAC system simulation with PV and wind generation modeling and rule-based battery dispatch to evaluate hourly demand–supply interactions. Three decision criteria are considered for each alternative: total system cost, annual building electric energy demand reduction, and net avoided life-cycle emissions. Stakeholder preferences… More > Graphic Abstract

Salahuddin¹, Khalid Haseeb^1,*, Mansoor Nasir¹, NZ Jhanjhi², Mamoona Humayun³

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079584 - 08 May 2026

Abstract Intelligent Transportation System (ITS) interconnects smart technologies for the advancement in communication and autonomous decision making in vehicle interactions. It manages traffic control infrastructure, analyses road conditions, and supports cooperative awareness in a crucial environment. The sensors continuously collect real-time vehicle data, process it, and forward it to analysis servers to predict the behavior of Vehicular Ad hoc Networks (VANETs). Many approaches have been proposed to address research challenges in routing and improve communication for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) systems. However, due to dynamic topology, the network becomes disturbed and loses established connections, leading… More >

Bing-Zhou Chen^1,2, Hai-Ying Zheng^1,2, Ao-Wen Wang^1,3, Ke-Lei Xia^1,2, Li-Feng Fan^1,3, Zhong-Yi Wang^1,3, Lan Huang^1,2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078894 - 08 May 2026

Abstract Many sensing and imaging modalities naturally yield complex-valued signals, where magnitude and phase jointly convey information. Complex-valued neural networks (CVNNs) possess unique advantages in processing phase-sensitive data (e.g., synthetic aperture radar (SAR) and magnetic resonance imaging (MRI)), yet their widespread adoption is hindered by significant computational overhead and training instability. To address these challenges, this paper presents the Wirtinger Derivative Complete Complex Network (WCCN), a unified and efficient framework for complex-valued deep learning. The proposed framework systematically addresses three key challenges in CVNNs: computational efficiency, parameter redundancy, and training stability. WCCN integrates three core components.… More >