Generating bitmap graphics from text has gained considerable attention, yet for scientific figures, vector graphics are often preferred. Given that vector graphics are typically encoded using low-level graphics primit...
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The creation of digital content and the easy accessibility of information have led to a surge in academic and textual plagiarism. Plagiarism detection in multiple languages is essential to maintain the integrity of ac...
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Current deep learning approaches in medical image registration usually face the challenges of distribution shift and data collection, hindering real-world deployment. In contrast, universal medical image registration ...
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Exploratory visual data analysis tools empower data analysts to efficiently and intuitively explore data insights throughout the entire analysis cycle. However, the gap between common programmatic analysis (e.g., with...
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ISBN:
(数字)9798350354850
ISBN:
(纸本)9798350354867
Exploratory visual data analysis tools empower data analysts to efficiently and intuitively explore data insights throughout the entire analysis cycle. However, the gap between common programmatic analysis (e.g., within computational notebooks) and exploratory visual analysis leads to a disjointed and inefficient data analysis experience. To bridge this gap, we developed PyGWalker, a Python library that offers on-the-fly assistance for exploratory visual data analysis. It features a lightweight and intuitive GUI with a shelf builder modality. Its loosely coupled architecture supports multiple computational environments to accommodate varying data sizes. Since its release in February 2023, PyGWalker has gained much attention, with 612k downloads on PyPI and over 10.5k stars on GitHub as of June 2024. This demonstrates its value to the datascience and visualization community, with researchers and developers integrating it into their own applications and studies.
As satellite network communication systems become an increasingly pivotal role in modern life, The routine maintenance of satellite networks is challenging due to limited resources and their susceptibility to interfer...
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ISBN:
(数字)9798331518677
ISBN:
(纸本)9798331518684
As satellite network communication systems become an increasingly pivotal role in modern life, The routine maintenance of satellite networks is challenging due to limited resources and their susceptibility to interference. Satellite networks are more reliant on interruption detection systems than terrestrial networks. The importance of interruption detection systems in satellite networks is becoming increasingly evident. In this paper, we propose a novel intrusion detection model based on Proximal Policy Optimization (PPO). This method interacts with the environment to learn and optimize detection strategies, allowing for dynamic adaptation to environmental changes and attack patterns. We evaluated our model on benchmark datasets and compared its performance metrics against existing models. The results demonstrate that our proposed model significantly enhances overall accuracy and precision, and outperforms baseline models in terms of training convergence speed.
Over the continuous utilization in real-world applications, Artificial Intelligence (AI) proved to be state-of-the-art technology, delivering more benefits at little incremental effort or cost to its utilization. This...
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This study addresses the challenges and limitations of surface defect detection on industrial parts. Traditional manual inspection methods are inefficient, error-prone, and difficult to meet the requirements of mass p...
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ISBN:
(数字)9798350377903
ISBN:
(纸本)9798350377910
This study addresses the challenges and limitations of surface defect detection on industrial parts. Traditional manual inspection methods are inefficient, error-prone, and difficult to meet the requirements of mass production. Therefore, machine vision technology becomes an alternative. However, existing methods still have problems with leakage and false detection, especially in the NEU-DET data set, which is prone to leakage and false detection when identifying tiny defects like the background. Inspired by this, this research aims to introduce the Coordinate Attention (CA) mechanism and add it to the bottleneck layer, replace all C3 modules in the backbone network with CA _ C3 modules, and optimize the original Spatial Pyramid Pooling (SPP) method, improved and named SPPCSPCGroup, and optimizes the original loss function (QFocalLoss) by adding a penalty factor to specific categories that are prone to misdiagnosis to improve recognition accuracy. Experiments show that the average accuracy (mAP) of the original YOLOv5 is 75.7% on the NEU-DET data set, and the average accuracy (mAP) we obtained is 79.1 %, which is increased by 3.4% through the improved defect detection method proposed in this study. The innovation of this study is to improve the efficiency and accuracy of surface defect detection in industrial applications by improving existing methods and providing reliable technical support for quality control in the industrial production process.
In this paper,we describe the nonlinear behavior of a generalized fourth-order Hietarinta-type equa-tion for dispersive waves in(2+1)*** various wave formations are retrieved by using Hirota’s bilinear method(HBM)and...
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In this paper,we describe the nonlinear behavior of a generalized fourth-order Hietarinta-type equa-tion for dispersive waves in(2+1)*** various wave formations are retrieved by using Hirota’s bilinear method(HBM)and various test function *** Hirota method is a widely used and robust mathematical tool for finding soliton solutions of nonlinear partial differential equa-tions(NLPDEs)in a variety of disciplines like mathematical physics,nonlinear dynamics,oceanography,engineering sciences,and others requires bilinearization of nonlinear *** different wave structures in the forms of new breather,lump-periodic,rogue waves,and two-wave solutions are *** addi-tion,the physical behavior of the acquired solutions is illustrated in three-dimensional,two-dimensional,density,and contour profiles by the assistance of suitable *** on the obtained results,we can assert that the employed methodology is straightforward,dynamic,highly efficient,and will serve as a valuable tool for discussing complex issues in a diversity of domains specifically ocean and coastal *** have also made an important first step in understanding the structure and physical be-havior of complex structures with our findings *** believe this research is timely and relevant to a wide range of engineering *** results obtained are useful for comprehending the fundamental scenarios of nonlinear sciences.
The IoMT has dramatically empowered the process of remote patient monitoring (RPM) through much better real-time data collection and health analysis. The real struggle lies in categorizing and evaluating the patient&#...
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High-Dimension, Low-Sample Size (HDLSS) datasets are the datasets that their sample sizes are much smaller than the number of feature dimensions. In spite of that, HDLSS datasets appear in many domains and organizatio...
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