This study is focused towards analyzing the heat and flow movement among two stretching rotating disks inside water-based carbon nanotubes. The idea of thermal boundary conditions convection used system expressed in partial differential equations. Using similarity techniques, model successfully converted to a nonlinear ordinary equation. A familiar collocation method simulate outcomes governed while validated through set tables assessed with existing literature. physical aspects proposed...

Accurate detection of wood defects plays a crucial role in optimizing utilization, minimizing corporate expenses, and safeguarding precious forest resources. To achieve precise identification surface wood, we present novel approach called the Omni-dynamic convolution coordinate attention-based YOLO (ODCA-YOLO) model. This model incorporates an Omni-dimensional dynamic convolution-based attention (ODCA) mechanism, which significantly enhances its ability to detect small target boosts...

The detection of defects on the surface is great importance for both production and application strip steel. In order to detect accurately, an improved YOLOv7-based model detecting steel developed. To enhances ability extract features identify small features, ConvNeXt module introduced backbone network structure, attention mechanism embedded in pooling module. reduce size improves inference speed model, C3 was used replace ELAN head. experimental results show that, compared with original...

The detection of wood defect is a crucial step in processing and manufacturing, determining the quality reliability products. To achieve accurate detection, novel method named BPN-YOLO proposed. ordinary convolution ELAN module YOLOv7 backbone network replaced with Pconv partial convolution, resulting P-ELAN module. Wood performance improved by this modification while unnecessary redundant computations memory accesses are reduced. Additionally, Biformer attention mechanism introduced to more...

Wood surface defect detection is a critical step in wood processing and manufacturing. To address the performance degradation caused by small targets multi-scale features detection, novel deep learning model proposed this study, FDD-YOLO, specifically designed for task. In feature extraction stage, C2f module funnel attention (FA) mechanisms are integrated into design of C2f-FA to enhance model’s ability extract defects various sizes. Additionally, Dual Spatial Pyramid Pooling-Fast (DSPPF)...

Introduction Tomatoes are one of the most economically significant crops worldwide, with their yield and quality heavily impacted by foliar diseases. Effective detection these diseases is essential for enhancing agricultural productivity mitigating economic losses. Current tomato leaf disease methods, however, encounter challenges in extracting multi-scale features, identifying small targets, complex background interference. Methods The model Tomato Focus-Diffusion Network (TomaFDNet) was...

The detection and the reconstruction of actuator faults in a flight control system are crucial to avoid negative impacts on aircraft itself, as well human environmental systems. In this paper, an fault scheme based classification for hex-rotor unmanned aerial vehicle designed. First, type is analyzed classified, then model established multiple classification. Second, (FDR) proposed. proposed scheme, observer group extended Kalman filter (EKF) designed isolation, state feedback required by...

Strong background noise and complicated interfering signatures when implementing vibration-based monitoring make it difficult to extract the weak diagnostic features due incipient faults in a multistage gearbox. This can be more challenging multiple coexist. paper proposes an effective approach multi-fault of wind turbine gearbox based on integration minimum entropy deconvolution (MED) multipoint optimal adjusted (MOMEDA). By using simulated periodic transient signals with different signal...

Sepsis is a severe infection-induced disease with multiple organ failure, and sepsis-induced cardiomyopathy fatal condition. Inflammatory response oxidative stress are reported to be involved in the development of cardiomyopathy. Dulaglutide novel antidiabetic agent that currently exert an anti-inflammatory effect. The present study aims explore potential protective property dulaglutide on lipopolysaccharide (LPS)-induced injury cardiomyocytes.LPS was used induce vitro model cardiomyocytes....

Wood surface defect detection is a challenging task due to the complexity and variability of types. To address these challenges, this paper introduces novel deep learning approach named SiM-YOLO, which built upon YOLOv8 object framework. A fine-grained convolutional structure, SPD-Conv, introduced with aim preserving detailed information during feature extraction process, thus enabling model capture subtle variations complex details wood defects. In fusion stage, SiAFF-PANet-based module...

<title>Abstract</title> Wood surface defect detection technology offers the advantages of being non-destructive, rapid, accurate, and economical. It plays a crucial role in wood grade sorting, detection, improving quality sawn timber, accelerating automation processing. Currently, there are challenges accurately identifying multi-scale defects insufficient overall accuracy field detection. To address these issues, new model named DRR-YOLO is proposed this study. This combines DWR module DRB...

<title>Abstract</title> Using deep learning methods is a promising approach to improving bark removal efficiency and enhancing the quality of wood products. However, lack publicly available datasets for plate segmentation in processing poses challenges researchers this field. To address issue, benchmark named WPS-dataset proposed study, which consists 4863 images. We designed an image acquisition device assembled it on equipment capture images real industrial settings. evaluated using six...

Accurate detection of wood surface defects plays a pivotal role in enhancing grade sorting precision, maintaining high standards processing quality, and safeguarding forest resources. This paper introduces an efficient precise approach to detecting defects, building upon enhancements the YOLOv8 model, which demonstrates significant performance handling multi-scale small-target commonly found wood. The proposed method incorporates dilation-wise residual (DWR) module trunk deformable large...

An improved Sage-Husa adaptive extended Kalman filter algorithm is proposed to ensure the precision and stability of calculating attitude angles a multi-rotor Unmanned Aerial Vehicle (UAV) under actual flight conditions, such as unknown time-varied noise statistical properties, main disturbance source in vibration high dynamically changed. The uses angle variance estimated by gyroscope real time estimate system only adopts an measurement on-line filtering. Meanwhile, it introduces criterion...

Zhang, Y.X.; Li, T.Y.; B.; J.; Wang, R.J.; Jiang, L.R., and Diao, X.H., 2020. Fault detection method of AC charging pile in coastal cities based on Kalman filtering algorithm. In: Guido Aldana, P.A. Kantamaneni, K. (eds.), Advances Water Resources, Coastal Management, Marine Science Technology. Journal Research, Special Issue No. 104, pp. 210–215. Coconut Creek (Florida), ISSN 0749-0208.Aiming at the problems fault detection, such as large amount iterative calculation low ability...

In order to satisfy the demands of stabilized control for airborne platform mounted on multi-rotor Unmanned Aerial Vehicle (mUAV), a fuzzy adaptive PID hybrid strategy with switching condition is put forward, and structure has dual rate-speed loops. After analyzed anti-disturbance ability deeply, self-adjusting factor self-learning rules are introduced improve rapid response capability system. The variable speed integral used ensure high stable precision achieve smoothly. Experimental...

Quickly detecting and accurately diagnosing early bearing faults is the key to ensuring stable operation of high-precision equipment. In actual industrial applications, it common face issues big data poor fault identification accuracy. To automatically realize diagnostics rolling bearings, a convolutional neural network algorithm feature enhancement method proposed. A two-dimensional space extraction based on Cyclostationary theory wavelet transform shows good results in noise suppression....