This article introduces an open-source software stack designed for autonomous 1:10 scale model *** developed for the Bosch Future Mobility Challenge(BFMC)student competition,this versatile software stack is applicable...
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This article introduces an open-source software stack designed for autonomous 1:10 scale model *** developed for the Bosch Future Mobility Challenge(BFMC)student competition,this versatile software stack is applicable to a variety of autonomous driving *** stack comprises perception,planning,and control modules,each essential for precise and reliable scene understanding in complex environments such as a miniature smart city in the context of *** the limited computing power of model vehicles and the necessity for low-latency real-time applications,the stack is implemented in C++,employs YOLO Version 5 s for environmental perception,and leverages the state-of-the-art Robot Operating System(ROS)for inter-process *** believe that this article and the accompanying open-source software will be a valuable resource for future teams participating in autonomous driving student *** work can serve as a foundational tool for novice teams and a reference for more experienced *** code and data are publicly available on GitHub.
The permanent magnet (PM) Vernier machines enhance torque density and decrease cogging torque compared to conventional permanent magnet synchronous motor. This paper presents a novel fractional-slot H-shaped PM Vernie...
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Breast cancer ranks as the second most prevalent cancer in women, recognized as one of the most dangerous types of cancer, and is on the rise globally. Regular screenings are essential for early-stage treatment. Digit...
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Breast cancer ranks as the second most prevalent cancer in women, recognized as one of the most dangerous types of cancer, and is on the rise globally. Regular screenings are essential for early-stage treatment. Digital mammography (DM) is the most recognized and widely used technique for breast cancer screening. Contrast-Enhanced Spectral Mammography (CESM or CM) is used in conjunction with DM to detect and identify hidden abnormalities, particularly in dense breast tissue where DM alone might not be as effective. In this work, we explore the effectiveness of each modality (CM, DM, or both) in detecting breast cancer lesions using deep learning methods. We introduce an architecture for detecting and classifying breast cancer lesions in DM and CM images in Craniocaudal (CC) and Mediolateral Oblique (MLO) views. The proposed architecture (JointNet) consists of a convolution module for extracting local features, a transformer module for extracting long-range features, and a feature fusion layer to fuse the local features, global features, and global features weighted based on the local ones. This significantly enhances the accuracy of classifying DM and CM images into normal or abnormal categories and lesion classification into benign or malignant. Using our architecture as a backbone, three lesion classification pipelines are introduced that utilize attention mechanisms focused on lesion shape, texture, and overall breast texture, examining the critical features for effective lesion classification. The results demonstrate that our proposed methods outperform their components in classifying images as normal or abnormal and mitigate the limitations of independently using the transformer module or the convolution module. An ensemble model is also introduced to explore the effect of each modality and each view to increase our baseline architecture's accuracy. The results demonstrate superior performance compared with other similar works. The best performance on DM images
The issue of signal outages in sub-THz frequency communication for future 6G networks is addressed by this research. A machine learning method is proposed, employing Random Forest and K-Means algorithms to predict the...
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Myocarditis is a significant public health concern because of its potential to cause heart failure and sudden *** standard invasive diagnostic method,endomyocardial bi-opsy,is typically reserved for cases with severe ...
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Myocarditis is a significant public health concern because of its potential to cause heart failure and sudden *** standard invasive diagnostic method,endomyocardial bi-opsy,is typically reserved for cases with severe complications,limiting its widespread ***,non‐invasive cardiac magnetic resonance(CMR)imaging presents a promising alternative for detecting and monitoring myocarditis,because of its high signal contrast that reveals myocardial *** assist medical professionals via artificial intelligence,the authors introduce generative adversarial networks‐multi discriminator(GAN‐MD),a deep learning model that uses binary classification to diagnose myocarditis from CMR *** approach employs a series of convolutional neural networks(CNNs)that extract and combine feature vectors for accurate *** authors suggest a novel technique for improving the classification precision of *** generative adversarial networks(GANs)to create synthetic images for data augmentation,the authors address challenges such as mode collapse and unstable *** a reconstruction loss into the GAN loss function requires the generator to produce images reflecting the discriminator features,thus enhancing the generated images'quality to more accurately replicate authentic data ***,combining this loss function with other reg-ularisation methods,such as gradient penalty,has proven to further improve the perfor-mance of diverse GAN models.A significant challenge in myocarditis diagnosis is the imbalance of classification,where one class dominates over the *** mitigate this,the authors introduce a focal loss‐based training method that effectively trains the model on the minority class *** GAN‐MD approach,evaluated on the Z‐Alizadeh Sani myocarditis dataset,achieves superior results(F‐measure 86.2%;geometric mean 91.0%)compared with other deep learning models and traditional machine learning methods.
Pneumothorax is a life-threatening and urgent chest disease than can be detected using Chest X-Ray (CXR) image. CXR images are low resolution and diagnosis of pneumothorax based on them is error prone. Deep learning-b...
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In real systems, one of the most vital criteria that assess the efficiency of a nonlinear controller is the transient response. Therefore, a new tuning technique is suggested for the composite nonlinear feedback (CNF)...
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One of the most important subjects in statistics is the theory of estimation. In this paper, we consider the generalized Bayes shrinkage estimator of the mean vector for multivariate normal distribution with the unkno...
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In this paper, we consider the neutrosophic generalized Rayleigh distribution (NGRD). Various neutrosophic properties of NGRD are developed and discussed. The developed distribution is specifically more useful to mode...
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CBDC-as-a-problem looks like a mania of interest from central banks and financial institutions all over the world. It may describe CBDC technology and CBDC technology development, the positive aspects of CBDC and its ...
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