S. Younus, N. Amin^*, A. Ali, K. Mahmood

Chalcogenide Letters, Vol.22, No.10, pp. 905-915, 2025, DOI:10.15251/CL.2025.2210.905

Abstract Wastewater generated by the textile industry contains high levels of various pollutants. Advanced conventional methods, such as chemical and electrical treatments, are effective in addressing these contaminants. However, the significant operational and capital costs associated with these conventional systems limit their accessibility for industrial stakeholders. In contrast, more economically viable methods tend to be less efficient. This study aims to identify a suitable approach for integrating photocatalytic degradation (PCD) with a low-cost method to enhance the cost-effectiveness of wastewater treatment processes in the textile sector. The study utilized silver copper sulfide (AgCuS) nanocomposites as a… More >

R. K. Mishra^a,*, M. N. Anwar^a, M. A. Hasan^b

Chalcogenide Letters, Vol.22, No.10, pp. 871-882, 2025, DOI:10.15251/CL.2025.2210.871

Abstract This study introduces a novel approach to enhancing the performance of CdTe/IGZO-based heterojunction solar cells by utilizing IGZO as both a window layer and an electron transport layer (ETL). A comprehensive simulation using SCAPS-1D was conducted to evaluate the impact of various transparent conductive oxides (TCOs), including ITO, SnO_₂, ZnO, and FTO, on key photovoltaic parameters such as power conversion efficiency (PCE), open-circuit voltage (Voc), short-circuit current density (Jsc), and fill factor (FF). The research also explores the critical role of transport layers (HTL/ETL) and their material properties, band alignment, carrier mobility, and defect density, in More >

Xinjian Li¹, Yu Zhang^1,2,*, Zewen Wang¹, Zhenyun Song¹

Energy Engineering, Vol.122, No.11, pp. 4603-4619, 2025, DOI:10.32604/ee.2025.065799 - 27 October 2025

Abstract Power prediction has been critical in large-scale wind power grid connections. However, traditional wind power prediction methods have long suffered from problems, for instance low prediction accuracy and poor reliability. For this purpose, a hybrid prediction model (VMD-LSTM-Attention) has been proposed, which integrates the variational modal decomposition (VMD), the long short-term memory (LSTM), and the attention mechanism (Attention), and has been optimized by improved dung beetle optimization algorithm (IDBO). Firstly, the algorithm’s performance has been significantly enhanced through the implementation of three key strategies, namely the elite group strategy of the Logistic-Tent map, the nonlinear… More >

Weicong Tan^1,#, Qiwu Wu^2,3,#,*, Lingzhi Jiang¹, Tao Tong², Yunchen Su²

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3621-3652, 2025, DOI:10.32604/cmc.2025.068781 - 23 September 2025

Abstract This study introduces a novel algorithm known as the dung beetle optimization algorithm based on bounded reflection optimization and multi-strategy fusion (BFDBO), which is designed to tackle the complexities associated with multi-UAV collaborative trajectory planning in intricate battlefield environments. Initially, a collaborative planning cost function for the multi-UAV system is formulated, thereby converting the trajectory planning challenge into an optimization problem. Building on the foundational dung beetle optimization (DBO) algorithm, BFDBO incorporates three significant innovations: a boundary reflection mechanism, an adaptive mixed exploration strategy, and a dynamic multi-scale mutation strategy. These enhancements are intended to… More >

Yi-Hao Tu, Yi-Wei Ma^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4563-4582, 2025, DOI:10.32604/cmc.2025.066899 - 30 July 2025

Abstract This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network (SETL-DDQN) and an extended Gumbel distribution method, designed to optimize the Contention Window (CW) in IEEE 802.11 networks. Unlike conventional Deep Reinforcement Learning (DRL)-based approaches for CW size adjustment, which often suffer from overestimation bias and limited exploration diversity, leading to suboptimal throughput and collision performance. Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions. First, SETL adopts a DDQN architecture (SETL-DDQN) to improve Q-value estimation accuracy and enhance training stability. Second, we incorporate a… More >

Haiyan Sun^1,*, Chenglong Shao¹, Jianwei Zhang¹, Kun Wang², Wanwei Huang¹

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1451-1470, 2025, DOI:10.32604/cmc.2025.059724 - 26 March 2025

Abstract To address the problem that existing studies lack analysis of the relationship between attack-defense game behaviors and situation evolution from the game perspective after constructing an attack-defense model, this paper proposes a network attack-defense game model (ADGM). Firstly, based on the assumption of incomplete information between the two sides of the game, the ADGM model is established, and methods of payoff quantification, equilibrium solution, and determination of strategy confrontation results are presented. Then, drawing on infectious disease dynamics, the network attack-defense situation is defined based on the density of nodes in various security states, and… More >

N. A. Jahan^*, S. I. Parash, Md. Asif Hossain, T. Chowdhury

Chalcogenide Letters, Vol.21, No.8, pp. 675-686, 2024, DOI:10.15251/CL.2024.218.675

Abstract In this study, the primary focus was on enhancing the performance of Photovoltaic devices by modifying the ETL and HTL transport layers. We conducted a comprehensive analysis of efficiency and fill factor variations resulting from adjustments in key device parameters, notably the active layer` thickness. The HTL layer employed materials such as CdTe (Cadmium telluride) and CISSe (Copper indium sulfur selenide), while the ETL layer utilized CdS (Cadmium sulfide), ZnO (Zinc oxide), SnOx (Stannous oxalte), SnO₂ (Tin oxide), and TiO₂ (Titanium dioxide). Additionally, Silicon (Si) was incorporated into our structure. Our highest efficiency recorded was 27.38%, More >

Mario Eugenio Sello^1,*, Rafael Adrian Maddio¹, Santiago Ignacio Hurtado¹, Daniel Alejandro Castillo¹, Daiana Vanesa Perri¹, Octavio Agusto Bruzzone², Marcos Horacio Easdale¹

Phyton-International Journal of Experimental Botany, Vol.93, No.9, pp. 2479-2498, 2024, DOI:10.32604/phyton.2024.053168 - 30 September 2024

Abstract Adaptive management in arid and semi-arid regions of Patagonia, Argentina, requires a thorough understanding of vegetative dynamics, which can be obtained via rangeland assessment and monitoring. These practices are essential for decision-making to prevent environmental degradation, especially in the light of drought aggravated by climate change. In turn, most methods used to evaluate rangelands focus on data obtained from field measurements and vegetation classifications based on remote sensing data. One of the most frequent problems is that field-based rangeland assessments, based on field measurements, turn out to be expensive because they require high efforts in… More >

Wei Liu^*, Tengteng Ren

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2979-3000, 2024, DOI:10.32604/cmc.2024.053627 - 15 August 2024

Abstract Feature Selection (FS) is a key pre-processing step in pattern recognition and data mining tasks, which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models. In recent years, meta-heuristic algorithms have been widely used in FS problems, so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization (HBCSSDBO) algorithm is proposed in this paper to improve the effect of FS. In this hybrid algorithm, the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem. By combining the… More >

Xueping Song^1,*, Jianming Yang¹, Shuyu Zhang¹, Jicun Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4551-4572, 2024, DOI:10.32604/cmc.2024.049446 - 20 June 2024

Abstract To address the shortage of public datasets for customs X-ray images of contraband and the difficulties in deploying trained models in engineering applications, a method has been proposed that employs the Extract-Transform-Load (ETL) approach to create an X-ray dataset of contraband items. Initially, X-ray scatter image data is collected and cleaned. Using Kafka message queues and the Elasticsearch (ES) distributed search engine, the data is transmitted in real-time to cloud servers. Subsequently, contraband data is annotated using a combination of neural networks and manual methods to improve annotation efficiency and implemented mean hash algorithm for… More >