In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the d...
详细信息
In traditional digital twin communication system testing,we can apply test cases as completely as possible in order to ensure the correctness of the system implementation,and even then,there is no guarantee that the digital twin communication system implementation is completely *** verification is currently recognized as a method to ensure the correctness of software system for communication in digital twins because it uses rigorous mathematical methods to verify the correctness of systems for communication in digital twins and can effectively help system designers determine whether the system is designed and implemented *** this paper,we use the interactive theorem proving tool Isabelle/HOL to construct the formal model of the X86 architecture,and to model the related assembly *** verification result shows that the system states obtained after the operations of relevant assembly instructions is consistent with the expected states,indicating that the system meets the design expectations.
The essence of music is inherently multi-modal – with audio and lyrics going hand in hand. However, there is very less research done to study the intricacies of the multi-modal nature of music, and its relation with ...
详细信息
In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems,...
详细信息
In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.
Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems(IDS).Data labeling difficulties,incorrect conclusions,and vulnerability to malicious data injec...
详细信息
Identifying cyberattacks that attempt to compromise digital systems is a critical function of intrusion detection systems(IDS).Data labeling difficulties,incorrect conclusions,and vulnerability to malicious data injections are only a few drawbacks of using machine learning algorithms for *** overcome these obstacles,researchers have created several network IDS models,such as the Hidden Naive Bayes Multiclass Classifier and supervised/unsupervised machine learning *** study provides an updated learning strategy for artificial neural network(ANN)to address data categorization problems caused by unbalanced *** to traditional approaches,the augmented ANN’s 92%accuracy is a significant improvement owing to the network’s increased resilience to disturbances and computational complexity,brought about by the addition of a random weight and standard *** the ever-evolving nature of cybersecurity threats,this study introduces a revolutionary intrusion detection method.
Alzheimer’s disease(AD)is a significant challenge in modern healthcare,with early detection and accurate staging remaining critical priorities for effective *** Deep Learning(DL)approaches have shown promise in AD di...
详细信息
Alzheimer’s disease(AD)is a significant challenge in modern healthcare,with early detection and accurate staging remaining critical priorities for effective *** Deep Learning(DL)approaches have shown promise in AD diagnosis,existing methods often struggle with the issues of precision,interpretability,and class *** study presents a novel framework that integrates DL with several eXplainable Artificial Intelligence(XAI)techniques,in particular attention mechanisms,Gradient-Weighted Class Activation Mapping(Grad-CAM),and Local Interpretable Model-Agnostic Explanations(LIME),to improve bothmodel interpretability and feature *** study evaluates four different DL architectures(ResMLP,VGG16,Xception,and Convolutional Neural Network(CNN)with attention mechanism)on a balanced dataset of 3714 MRI brain scans from patients aged 70 and *** proposed CNN with attention model achieved superior performance,demonstrating 99.18%accuracy on the primary dataset and 96.64% accuracy on the ADNI dataset,significantly advancing the state-of-the-art in AD *** ability of the framework to provide comprehensive,interpretable results through multiple visualization techniques while maintaining high classification accuracy represents a significant advancement in the computational diagnosis of AD,potentially enabling more accurate and earlier intervention in clinical settings.
Deep learning has been successfully used for tasks in the 2D image *** on 3D computer vision and deep geometry learning has also attracted *** achievements have been made regarding feature extraction and discriminatio...
详细信息
Deep learning has been successfully used for tasks in the 2D image *** on 3D computer vision and deep geometry learning has also attracted *** achievements have been made regarding feature extraction and discrimination of 3D *** recent advances in deep generative models such as generative adversarial networks,effective generation of 3D shapes has become an active research *** 2D images with a regular grid structure,3D shapes have various representations,such as voxels,point clouds,meshes,and implicit *** deep learning of 3D shapes,shape representation has to be taken into account as there is no unified representation that can cover all tasks *** such as the representativeness of geometry and topology often largely affect the quality of the generated 3D *** this survey,we comprehensively review works on deep-learning-based 3D shape generation by classifying and discussing them in terms of the underlying shape representation and the architecture of the shape *** advantages and disadvantages of each class are further *** also consider the 3D shape datasets commonly used for shape ***,we present several potential research directions that hopefully can inspire future works on this topic.
The most prevalent cancer around the world is Skin cancer (SC). Clinical assessment of skin lesions is essential to evaluate the features of the disease;but it is limited by the variety of interpretations and long tim...
详细信息
One of the key challenges in e-commerce is how to provide relevant and personalized product recommendations to users. To achieve this, data analysis and text processing techniques are essential. This research aims to ...
详细信息
Meta-heuristic optimization algorithms have become widely used due to their outstanding features, such as gradient-free mechanisms, high flexibility, and great potential for avoiding local optimal solutions. This rese...
详细信息
Maintaining a regular daily activity routine is essential for overall health and well-being. Wearable sensors offer a convenient way to track daily activities, but accurately identifying a wide range of activities rem...
详细信息
暂无评论