Tanyawan Suwandecha¹, Supachai Pisuchpen^2,*

Journal of Renewable Materials, Vol.12, No.11, pp. 1811-1836, 2024, DOI:10.32604/jrm.2024.056334 - 22 November 2024

Abstract This study investigated the development of mycelium-based biofoams as sustainable cushioning materials using Pleurotus ostreatus and Lentinus squarrosulus, combined with different sawdust substrates, and subjected to various pressing methods. The results indicated significant effects of mushroom species, sawdust type, and pressing method on the properties of biofoams. Growth rate, morphology, chemical composition, physical and mechanical properties, water resistance, and cushioning factor were evaluated. The results indicated that Lentinus squarrosulus (LS) exhibited faster growth rates (up to 14.37 mm/day) and produced biofoams with superior properties compared to Pleurotus ostreatus (PO). Core wood (CW) sawdust generally resulted in biofoams with lower… More > Graphic Abstract

Guowei Li^1,*, Shujuan Bu², Xinle Yang², Kaijie Liang¹, Zhengri Shao¹, Xiaobei Song¹, Yitian Tang³, Dejing Zong⁴

Energy Engineering, Vol.121, No.12, pp. 3843-3874, 2024, DOI:10.32604/ee.2024.056195 - 22 November 2024

Abstract A novel dual-pressure organic Rankine cycle system (DPORC) with a dual-stage ejector (DE-DPORC) is proposed. The system incorporates a dual-stage ejector that utilizes a small amount of extraction steam from the high-pressure expander to pressurize a large quantity of exhaust gas to perform work for the low-pressure expander. This innovative approach addresses condensing pressure limitations, reduces power consumption during pressurization, minimizes heat loss, and enhances the utilization efficiency of waste heat steam. A thermodynamic model is developed with net output work, thermal efficiency, and exergy efficiency (W_net, η_t, η_ex) as evaluation criteria, an economic model is established… More >

Xiaohui Ye^1,*, Fucheng Tan¹, Xinli Song², Hanyang Dai², Xia Li², Shixia Mu², Shaohang Hao²

Energy Engineering, Vol.121, No.12, pp. 3689-3710, 2024, DOI:10.32604/ee.2024.055200 - 22 November 2024

Abstract Energy storage batteries can smooth the volatility of renewable energy sources. The operating conditions during power grid integration of renewable energy can affect the performance and failure risk of battery energy storage system (BESS). However, the current modeling of grid-connected BESS is overly simplistic, typically only considering state of charge (SOC) and power constraints. Detailed lithium (Li)-ion battery cell models are computationally intensive and impractical for real-time applications and may not be suitable for power grid operating conditions. Additionally, there is a lack of real-time batteries risk assessment frameworks. To address these issues, in this… More >

Aws Al-Akam^1,*, Ahmed A. Abduljabbar², Ali Jaber Abdulhamed¹

Energy Engineering, Vol.121, No.12, pp. 3761-3777, 2024, DOI:10.32604/ee.2024.055198 - 22 November 2024

Abstract Photovoltaic (PV) panels are essential to the global transition towards sustainable energy, offering a clean, renewable source that reduces reliance on fossil fuels and mitigates climate change. High temperatures can significantly affect the performance of photovoltaic (PV) panels by reducing their efficiency and power output. This paper explores the consequential effect of various rooftop coverings on the thermal performance of photovoltaic (PV) panels. It investigates the relationship between the type of rooftop covering materials and the efficiency of PV panels, considering the thermal performance and its implications for enhancing their overall performance and sustainability. The… More >

Mohammad Al-Omari¹, Qasem Abu Al-Haija^2,*

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1537-1555, 2024, DOI:10.32604/csse.2024.056257 - 22 November 2024

Abstract More businesses are deploying powerful Intrusion Detection Systems (IDS) to secure their data and physical assets. Improved cyber-attack detection and prevention in these systems requires machine learning (ML) approaches. This paper examines a cyber-attack prediction system combining feature selection (FS) and ML. Our technique’s foundation was based on Correlation Analysis (CA), Mutual Information (MI), and recursive feature reduction with cross-validation. To optimize the IDS performance, the security features must be carefully selected from multiple-dimensional datasets, and our hybrid FS technique must be extended to validate our methodology using the improved UNSW-NB 15 and TON_IoT datasets. More >

Chi-Chou Kao^1,*, Hung-Yi Lin²

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1581-1594, 2024, DOI:10.32604/csse.2024.055073 - 22 November 2024

Abstract Layout synthesis in quantum computing is crucial due to the physical constraints of quantum devices where quantum bits (qubits) can only interact effectively with their nearest neighbors. This constraint severely impacts the design and efficiency of quantum algorithms, as arranging qubits optimally can significantly reduce circuit depth and improve computational performance. To tackle the layout synthesis challenge, we propose an algorithm based on integer linear programming (ILP). ILP is well-suited for this problem as it can formulate the optimization objective of minimizing circuit depth while adhering to the nearest neighbor interaction constraint. The algorithm aims… More >

Trong Thua Huynh^*, Hoang Thanh Nguyen, Du Thang Phu

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2281-2298, 2024, DOI:10.32604/cmc.2024.057954 - 18 November 2024

Abstract In recent years, early detection and warning of fires have posed a significant challenge to environmental protection and human safety. Deep learning models such as Faster R-CNN (Faster Region based Convolutional Neural Network), YOLO (You Only Look Once), and their variants have demonstrated superiority in quickly detecting objects from images and videos, creating new opportunities to enhance automatic and efficient fire detection. The YOLO model, especially newer versions like YOLOv10, stands out for its fast processing capability, making it suitable for low-latency applications. However, when applied to real-world datasets, the accuracy of fire prediction is… More >

Xinmeng Zha¹, Huilin Ren^1,*, Yi Xiong^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011371

Abstract Additive manufacturing of continuous fiber composites is an emerging field that enables the tunable mechanical performance of composite structure by flexibly controlling the spatial layout of continuous fibers. Transverse isotropic strengthening is advantageous property of continuous fiber, which is favorable to align with the principal stress orientation. However, the accuracy and efficiency of traditional methods for calculating principal stress field are unguaranteed due to the inherent complexity and variability of geometries, material properties, and operational conditions in additive manufacturing. Therefore, a machine learning-assisted path planning method is proposed to robustly and efficiently generate the continuous… More >

Lei Peng^1,*, Jin Zhou², Xianfeng Zhang³, Zhongwei Guan^4,5

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.011196

Abstract This paper presents the numerical modelling of the ballistic response of hybrid composite structures subjected to 7.62 mm projectile impact. This study focuses on the modelling of composites made of various materials, including ceramics, Ultra-High-Molecular-Weight Polyethylene (UHMWPE), Kevlar, and compressed wood, with fabrication of hybrid laminated structures that offer promising ballistic resistance capabilities. By employing a range of constitutive models and failure criteria, the finite element model simulates the ballistic behaviors of the constituent materials, facilitating a comprehensive understanding of their performance under high-velocity impacts. The core of the study lies in the comparison between… More >

Ting Tan^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012670

Abstract Owing to their compliance, soft robots demonstrate enhanced compatibility with humans and the environment compared with traditional rigid robots. However, ensuring the working effectiveness of artificial muscles that actuate soft robots in confined spaces or underloaded conditions remains a challenge. Drawing inspiration from avian pneumatic bones, we propose the incorporation of a light weight endoskeleton into artificial muscles to augment the mechanical integrity and tackle load-bearing environmental difficulties. We present a soft origami hybrid artificial muscle that features a hollow origami metamaterial interior with a rolled dielectric elastomer exterior. The programmable nonlinear origami metamaterial endoskeleton More >