Prior research has suggested that job satisfaction is a major concern for both nurses and healthcare administrators. A variety of workplace stressors, coping strategies demographic characteristics have been found to contribute positively negatively satisfaction. However, most this conducted in Western culture countries, leaving one wonder if the findings are relevant China, particularly regard intensive care nurses.Therefore, purpose descriptive study was determine, from People's Republic...

Abstract Patient-specific quality assurance (PSQA) of volumetric modulated arc therapy (VMAT) to assure accurate treatment delivery is resource-intensive and time-consuming. Recently, machine learning has been increasingly investigated in PSQA results prediction. However, the classification performance models at different criteria needs further improvement clinical validation (CV), especially for predicting plans with low gamma passing rates (GPRs). In this study, we developed validated a...

A safe and healthy road condition plays a supporting role in the public travel national economy. Therefore, effective management maintenance methods have become key problems that researchers engineers are urgently solving, early damage detection warning also important for disaster emergency treatment, but some traditional identification often costly need to be equipped with professional persons. Due complexity of pavement conditions, existing defects datasets not perfect, although accuracy...

Purpose Recognizing every worker's working status instead of only describing the existing construction activities in static images or videos as most computer vision-based approaches do; identifying workers and their simultaneously; establishing a connection between behaviors. Design/methodology/approach Taking reinforcement processing area research case, new method for recognizing each different activity through position relationship objects detected by Faster R-CNN is proposed. Firstly,...

Abstract To improve the safety of road tunnel pavement, research established pavement water seepage recognition models based on deep learning technology, and a area extraction model image processing technology to finally achieve accurate detection pavements. First, EfficientNet MobileNet were built, trained with self-collected data set, F1 score was introduced evaluate accuracy comprehensive performance two in predicting different categories characteristics. Then three grayscale methods,...

Recognition and classification for construction activities help to monitor manage workers. Deep learning computer vision technologies have addressed many limitations of traditional manual methods in complex environments. However, distinguishing different workers establishing a clear recognition logic remain challenging. To address these issues, we propose novel activity method that integrates multiple deep algorithms. complete this research, created three datasets: 727 images entities, 2546...

With the rapid development of deep learning, computer vision has assisted in solving a variety problems engineering construction. However, very few vision-based approaches have been proposed on work productivity’s evaluation. Therefore, taking super high-rise project as research case, using detected object information obtained by learning algorithm, method for evaluating productivity assembling reinforcement is proposed. Firstly, detector that can accurately distinguish various entities...

Due to the existence of many small and weak defects strong complex background interference in electroluminescence(EL) image photovoltaic cell modules, it leads a challenging task detect modules industrial field. In this paper, we propose Global Channel Spatial Context Module (GCSC), which includes channel spatial self-attention module, adaptively capture global rich context information, establish relationship between each pixel. Moreover, GCSC achieves effect suppressing noise enhancing...

Abstract The art design of interactive device is based on Arduino, an open-source technology and Processing, a programming language, whose application enriches the interactivity expansibility device, improves its visual effect experience. With rapid development social economy, urban noise pollution has become increasingly severe, which been yet to arouse enough public attention. Therefore, research enables people more intuitively experience impact through realizes interaction between...

Aiming at the technical problems of intelligent identification cracks on gantry crane track, a target detection method was proposed based machine vision and deep neural network. YOLOv5s is used as surface defect model, trained model to recognize crack track. Because lack training sets, affine transformation increase sample size set, data set get preliminary weight for transfer learning method. Also, Gaussian smoothing image adopted improve model's accuracy. The test results show that track...

Abstract Background Providing self-management support to kidney transplant recipients is essential. However, a scale identify the they have received lacking. The purpose of this study develop Self-management Support Scale for Kidney Transplant Recipients (SMSSKTR) and test its psychometric properties. Methods This an instrument development validation study, which has three-stage cross-sectional design. In Stage 1, preliminary item pool was formed using literature review, semi-structured...

The production process of photovoltaic (PV) cells can easily lead to various defects. Defect detection is a necessary method ensure the quality PV components. Computer vision-based detectors are widely used in inspection process, which an important means production. During number defects that need be detected may increase gradually. However, traditional object cannot adapt streaming data. Fine-tuning model directly with new data will result catastrophic forgetting, and dataset needs rebuilt...

Defect detection of solar panels plays an essential role in guaranteeing product quality within automated production lines. However, traditional manual inspection panel defects suffers from low efficiency. This paper proposes enhanced YOLOv5 algorithm (EL-YOLOv5) fused with the CBAM hybrid attention module to ensure quality. The focuses on detecting five common types that frequently appear photovoltaic lines, namely hidden cracks, scratches, broken grids, black spots, and short circuits....

Abstract In order to improve the traffic safety of tunnel pavement and reduce impact water seepage on structure, a convolutional neural network (CNN) model is established based image detection technology realize identification, classification statistics seepage. First, compared with MobileNet model, deep learning EfficientNet was built, accuracy two models analyzed for recognition. The F1 Score introduced evaluate comprehensive performance different types characteristics. Then three gray...