Rui Zhang^1,2, Tonghai Liu^1,2,*, Wenzheng Liu^1,2, Chaungchuang Yuan^1,2, Xiaoyue Seng^1,2, Tiantian Guo^1,2, Xue Wang^1,2

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1275-1296, 2024, DOI:10.32604/phyton.2024.052397

Abstract Rice diseases can adversely affect both the yield and quality of rice crops, leading to the increased use of pesticides and environmental pollution. Accurate detection of rice diseases in natural environments is crucial for both operational efficiency and quality assurance. Deep learning-based disease identification technologies have shown promise in automatically discerning disease types. However, effectively extracting early disease features in natural environments remains a challenging problem. To address this issue, this study proposes the YOLO-CRD method. This research selected images of common rice diseases, primarily bakanae disease, bacterial brown spot, leaf rice fever, and dry… More >

Md. Parvez Anwar^*, Masuma Akhter, Sharmin Aktar, Sinthia Afsana Kheya, A. K. M. Mominul Islam^*, Sabina Yeasmin, Ahmed Khairul Hasan, Md. Harun Or Rashid

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1159-1177, 2024, DOI:10.32604/phyton.2024.049073

Abstract Seed priming is a pre-germinated technique that can enhance seed germination percentage, faster and synchronized germination, better seedling growth, and yield under stress conditions. To ascertain the most effective seed priming method that would ensure the potential yield of wheat in Bangladesh, two experiments were carried out from December 2021 to March 2022 at the Department of Agronomy, Bangladesh Agricultural University. Two wheat varieties namely BARI Gom-28 and BWMRI Gom-1 were subjected to a range of priming chemicals in both lab and pot tests. These compounds included the following: control (no priming), hydropriming (distilled water),… More >

Ivan Karpunin^*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1219-1232, 2024, DOI:10.32604/fdmp.2024.051062

Abstract The dynamics of a solid spherical body in an oscillating liquid flow in a vertical axisymmetric channel of variable cross section is experimentally studied. It is shown that the oscillating liquid leads to the generation of intense averaged flows in each of the channel segments. The intensity and direction of these flows depend on the dimensionless oscillating frequency. In the region of studied frequencies, the dynamics of the considered body is examined when the primary vortices emerging in the flow occupy the whole region in each segment. For a fixed frequency, an increase in the… More >

Lijun Mu, Xiaojia Xue, Jie Bai^*, Xiaoyan Li, Xueliang Han

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1365-1379, 2024, DOI:10.32604/fdmp.2024.049013

Abstract Following large-scale volume fracturing in shale oil reservoirs, well shut-in measures are generally employed. Laboratory tests and field trials have underscored the efficacy of fracturing fluid imbibition during the shut-in phase in augmenting shale oil productivity. Unlike conventional reservoirs, shale oil reservoirs exhibit characteristics such as low porosity, low permeability, and rich content of organic matter and clay minerals. Notably, the osmotic pressure effects occurring between high-salinity formation water and low-salinity fracturing fluids are significant. The current understanding of the mobilization patterns of crude oil in micro-pores during the imbibition process remains nebulous, and the… More >

Huiyan Zhao¹, Xuezhong Chen¹, Zhijian Hu^2,*, Man Chen¹, Bo Xiong³, Jianying Yang¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1313-1330, 2024, DOI:10.32604/fdmp.2024.048840

Abstract Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis, a model is developed to predict the related well production rate. This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales, as well as the flow characteristics in different types of thin layers (tight sandstone gas, shale gas, and coalbed gas). Moreover, a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir. A… More > Graphic Abstract

Xiao Huang^1,2, Jin Yang^3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1393-1406, 2024, DOI:10.32604/fdmp.2024.046360

Abstract Cement-based materials are fundamental in the construction industry, and enhancing their properties is an ongoing challenge. The use of superabsorbent polymers (SAP) has gained significant attention as a possible way to improve the performance of cement-based materials due to their unique water-absorption and retention properties. This study investigates the multifaceted impact of kaolin intercalation-modified superabsorbent polymers (K-SAP) on the properties of cement mortar. The results show that K-SAP significantly affects the cement mortar’s rheological behavior, with distinct phases of water absorption and release, leading to changes in workability over time. Furthermore, K-SAP alters the hydration More >

Siti Aekbal Salleh^1,2,*, Nafisah Khalid¹, Natasha Danny⁶, Nurul Ain Mohd. Zaki^2,3, Mustafa Ustuner⁴, Zulkiflee Abd Latif^1,2, Vladimir Foronda⁵

Revue Internationale de Géomatique, Vol.33, pp. 183-199, 2024, DOI:10.32604/rig.2024.050723

Abstract Due to the spectral and spatial properties of pervious and impervious surfaces, image classification and information extraction in detailed, small-scale mapping of urban surface materials is quite difficult and complex. Emerging methods and innovations in image classification have centred on object-based classification techniques and various segmentation techniques, which are fundamental to this approach. Consequently, the purpose of this study is to determine which classification method is most suitable for extracting linear features in terms of techniques and performance by comparing two classification methods, pixel-based approach and object-based approach, using WorldView-2 satellite imagery to specifically highlight… More > Graphic Abstract

Yuting Zhou¹, Xuemei Yang¹, Junping Yin^2,3,4,*, Shiqi Liu¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5313-5333, 2024, DOI:10.32604/cmc.2024.052060

Abstract Gliomas have the highest mortality rate of all brain tumors. Correctly classifying the glioma risk period can help doctors make reasonable treatment plans and improve patients’ survival rates. This paper proposes a hierarchical multi-scale attention feature fusion medical image classification network (HMAC-Net), which effectively combines global features and local features. The network framework consists of three parallel layers: The global feature extraction layer, the local feature extraction layer, and the multi-scale feature fusion layer. A linear sparse attention mechanism is designed in the global feature extraction layer to reduce information redundancy. In the local feature… More >

Ragini Thatikonda¹, Prakash Kodali^1,*, Ramalingaswamy Cheruku², Eswaramoorthy K.V³

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4683-4702, 2024, DOI:10.32604/cmc.2024.051844

Abstract In the realm of low-level vision tasks, such as image deraining and dehazing, restoring images distorted by adverse weather conditions remains a significant challenge. The emergence of abundant computational resources has driven the dominance of deep Convolutional Neural Networks (CNNs), supplanting traditional methods reliant on prior knowledge. However, the evolution of CNN architectures has tended towards increasing complexity, utilizing intricate structures to enhance performance, often at the expense of computational efficiency. In response, we propose the Selective Kernel Dense Residual M-shaped Network (SKDRMNet), a flexible solution adept at balancing computational efficiency with network accuracy. A… More >

Xuejie Wang¹, Jianxun Zhang^1,*, Ye Tao², Xiaoli Yuan¹, Yifan Guo¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4621-4639, 2024, DOI:10.32604/cmc.2024.051556

Abstract While single-modal visible light images or infrared images provide limited information, infrared light captures significant thermal radiation data, whereas visible light excels in presenting detailed texture information. Combining images obtained from both modalities allows for leveraging their respective strengths and mitigating individual limitations, resulting in high-quality images with enhanced contrast and rich texture details. Such capabilities hold promising applications in advanced visual tasks including target detection, instance segmentation, military surveillance, pedestrian detection, among others. This paper introduces a novel approach, a dual-branch decomposition fusion network based on AutoEncoder (AE), which decomposes multi-modal features into intensity… More >