Yuanyuan Yang¹, Xian Shi^1,2,*, Cheng Ji³, Yujie Yan³, Na An³, Teng Zhang⁴

Energy Engineering, Vol.121, No.12, pp. 3667-3688, 2024, DOI:10.32604/ee.2024.056266 - 22 November 2024

Abstract Based on a geology-engineering sweet spot evaluation, the high-quality reservoir zones and horizontal well landing points were determined. Subsequently, fracture propagation and production were simulated with a multilayer fracturing scenario. The optimal hydraulic fracturing strategy for the multilayer fracturing network was determined by introducing a vertical asymmetry factor. This strategy aimed to minimize stress shadowing effects in the vertical direction while maximizing the stimulated reservoir volume (SRV). The study found that the small vertical layer spacing of high-quality reservoirs and the presence of stress-masking layers (with a stress difference of approximately 3~8 MPa) indicate that… More > Graphic Abstract

Farhad Mortezapour Shiri^*, Thinagaran Perumal, Norwati Mustapha, Raihani Mohamed

Journal on Artificial Intelligence, Vol.6, pp. 301-360, 2024, DOI:10.32604/jai.2024.054314 - 20 November 2024

Abstract Deep learning (DL) has emerged as a powerful subset of machine learning (ML) and artificial intelligence (AI), outperforming traditional ML methods, especially in handling unstructured and large datasets. Its impact spans across various domains, including speech recognition, healthcare, autonomous vehicles, cybersecurity, predictive analytics, and more. However, the complexity and dynamic nature of real-world problems present challenges in designing effective deep learning models. Consequently, several deep learning models have been developed to address different problems and applications. In this article, we conduct a comprehensive survey of various deep learning models, including Convolutional Neural Network (CNN), Recurrent… More >

Jiajun Liu¹, Lina Tan^1,*, Zhili Zhou², Weijin Jiang¹, Yi Li¹, Peng Chen¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3221-3240, 2024, DOI:10.32604/cmc.2024.054542 - 18 November 2024

Abstract Many existing coverless steganography methods establish a mapping relationship between cover images and hidden data. One issue with these methods is that as the steganographic capacity increases, the number of images stored in the database grows exponentially. This makes it challenging to build and manage a large image database. To improve the image library utilization and anti-attack capability of the steganography system, we propose an efficient coverless scheme based on dynamically matched substrings. We utilize You Only Look Once (YOLO) for selecting optimal objects and create a mapping dictionary between these objects and scrambling factors.… More >

Kusum Yadav¹, Yasser Alharbi¹, Eissa Jaber Alreshidi¹, Abdulrahman Alreshidi¹, Anuj Kumar Jain², Anurag Jain³, Kamal Kumar⁴, Sachin Sharma⁵, Brij B. Gupta^6,7,8,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2665-2683, 2024, DOI:10.32604/cmc.2024.053565 - 18 November 2024

Abstract In today’s world, image processing techniques play a crucial role in the prognosis and diagnosis of various diseases due to the development of several precise and accurate methods for medical images. Automated analysis of medical images is essential for doctors, as manual investigation often leads to inter-observer variability. This research aims to enhance healthcare by enabling the early detection of diabetic retinopathy through an efficient image processing framework. The proposed hybridized method combines Modified Inertia Weight Particle Swarm Optimization (MIWPSO) and Fuzzy C-Means clustering (FCM) algorithms. Traditional FCM does not incorporate spatial neighborhood features, making More >

Kaixin Xia¹, Yu Gong^2,*, Xinxin Qi^3,4, Libin Zhao^3,4,*, Linjuan Wang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011650

Abstract The crack tip of the asymmetric four-point bend end-notched flexure (4AENF) delamination testing under shear loading often exhibits a proportion of mode I component, making it a typical mixed-mode I/II problem. Characterizing the total fracture toughness in 4AENF laminates is crucial for understanding the delamination phenomenon in composites. In this study, 4AENF tests were conducted on carbon fiber-reinforced epoxy asymmetric laminates to evaluate the total interlaminar fracture toughness under shear loading conditions. Additionally, the variation of interlaminar fracture toughness in asymmetric laminates with different fiber orientation angles was considered. Theoretical modelling was performed using an More >

Xiaodong Shi^*, Tingyu Wang, Sui Ai, Jiasi Li

Phyton-International Journal of Experimental Botany, Vol.93, No.10, pp. 2571-2581, 2024, DOI:10.32604/phyton.2024.056606 - 30 October 2024

Abstract Cotton rose (Hibiscus mutabilis) is a well-known ornamental plant that produces large flowers of vibrant colors. However, metabolites in H. mutabilis flowers with vibrant color have not been fully understood. By performing a combined analysis of metabolomics and transcriptomics data, we here explored mechanisms for the production of primary active compounds in this plant. Multivariate statistics unveiled differences in flavonoid metabolism between white and pink flowers, with pink flowers exhibiting a greater flavonoid abundance. The white-to-pink transition of cotton rose flowers may be attributed to pelargonidin-3-O-glucoside formation. On examining the expression of genes related to the structure More > Graphic Abstract

Nigel Walford^*

Revue Internationale de Géomatique, Vol.33, pp. 445-464, 2024, DOI:10.32604/rig.2024.054535 - 25 October 2024

Abstract The impact of World War II on the physical landscape of British towns and cities as a result of airborne assault is well known. However, less newsworthy but arguably no less significant is the impact of the war on agriculture and the countryside, especially in South-East England. This paper outlines the building of an historical Geographical Information System (GIS) from different data sources including the National Farm Survey (NFS), Luftwaffe and Royal Air Force (RAF) aerial photographs and basic topographic mapping for the South Downs in East and West Sussex. It explores the impact and… More >

Ragil Widyorini^1,*, Greitta Kusuma Dewi¹, Arif Nuryawan², Eddy Heraldy³, Nanang Masruchin⁴

Journal of Renewable Materials, Vol.12, No.10, pp. 1757-1770, 2024, DOI:10.32604/jrm.2024.054821 - 23 October 2024

Abstract Despite its considerable potential, oil palm trunk (OPT) remains underutilized, largely owing to the cyclical replanting process that occurs every 25–30 years. This study aimed to address this issue by developing an eco-friendly oriented strand board (OSB) using vascular bundles (VBs) from oil palm, both in binderless form and with the incorporation of natural adhesives made from sucrose and ammonium dihydrogen phosphate (ADP). The VB was extracted from OPT using a pressure cooker and mixed with a sucrose-ADP solution at various ratios. The mixture was then pressed at temperatures of 180°C and 200°C for 10… More > Graphic Abstract

Huan Ma¹, Linlin Ma², Zengwei Wang^3,*, Zhendong Li³, Yuanzhen Zhu¹, Yutian Liu³

Energy Engineering, Vol.121, No.11, pp. 3133-3160, 2024, DOI:10.32604/ee.2024.055051 - 21 October 2024

Abstract With the increasing penetration of renewable energy in power system, renewable energy power ramp events (REPREs), dominated by wind power and photovoltaic power, pose significant threats to the secure and stable operation of power systems. This paper presents an early warning method for REPREs based on long short-term memory (LSTM) network and fuzzy logic. First, the warning levels of REPREs are defined by assessing the control costs of various power control measures. Then, the next 4-h power support capability of external grid is estimated by a tie line power prediction model, which is constructed based More > Graphic Abstract

Hongsheng Su, Shilin Song^*, Xingsheng Wang

Energy Engineering, Vol.121, No.11, pp. 3289-3303, 2024, DOI:10.32604/ee.2024.054643 - 21 October 2024

Abstract This paper introduces the Particle Swarm Optimization (PSO) algorithm to enhance the Latin Hypercube Sampling (LHS) process. The key objective is to mitigate the issues of lengthy computation times and low computational accuracy typically encountered when applying Monte Carlo Simulation (MCS) to LHS for probabilistic trend calculations. The PSO method optimizes sample distribution, enhances global search capabilities, and significantly boosts computational efficiency. To validate its effectiveness, the proposed method was applied to IEEE34 and IEEE-118 node systems containing wind power. The performance was then compared with Latin Hypercubic Important Sampling (LHIS), which integrates significant sampling More >