Automatic detection of defects from wind turbine blade images has shown tremendous progress in recent years. However, there are not many annotated datasets feasible for benchmarking purposes, and a lack of consistency...
详细信息
Tendon-driven systems have become popular and efficient solutions for remotely positioning motors and actuation systems in various mechanisms. They address specific needs such as reducing the weight and inertia of mov...
详细信息
ISBN:
(纸本)9798331516246;9798331516239
Tendon-driven systems have become popular and efficient solutions for remotely positioning motors and actuation systems in various mechanisms. They address specific needs such as reducing the weight and inertia of moving components and minimizing their dimensions. Tendon-actuated systems offer benefits like low cost and the absence of backlash, leading to significant interest in tendon modeling within the scientific community. This interest spans from analytical solutions with inextensible tendons to computer-aided engineering (CAE) approaches utilizing tendons as deformable elements. However, developing tendon-based actuation systems through CAE tools has been limited due to substantial computational requirements and the challenge of obtaining reliable, technically applicable results. Finite element analysis (FEA) becomes complex and unsuitable for the design phase due to the significant deformation and displacement resulting from tendons' flexible behavior. Consequently, research into robotic systems actuated by tendons typically relies on analytical calculus and data from costly prototypes, requiring significant time and investment. Moreover, incorporating soft structures makes creating a comprehensive analytical model of the entire system in three-dimensional space daunting or even impossible, particularly with more complex soft structures, thus making FEA analysis the only viable approach. This work reviews the main solutions explored in the literature for solving these systems, aiming to provide designers with a broader view of the possible techniques that can be used based on the specific application.
In AI-based malware detection, structural features such as function call graphs (FCGs) and control flow graphs (CFGs) are widely used for their ability to encapsulate program execution flow and facilitate cross-archit...
详细信息
The proceedings contain 331 papers. The topics discussed include: research on computer aided French audiovisual intelligence system;feature extraction and intelligent generation of spatial environment design combined ...
ISBN:
(纸本)9798350373646
The proceedings contain 331 papers. The topics discussed include: research on computer aided French audiovisual intelligence system;feature extraction and intelligent generation of spatial environment design combined with deep learning;a federated learning algorithm based on combination of prototype and comparative learning;research on the optimization of wind-solar energy storage systems in park microgrids based on mixed integer linear programming and Monte Carlo simulation;deep learning in biometric recognition: applications and challenges;design and research of virtual human based on deep learning and paddle model;a fault diagnosis method based on TCN-LSTM-SE neural networks for distributed PV systems;and research on real-time image data transmission system of UAV in fault location of distribution network.
This paper addresses the challenge of issue management in complex, component-based software architectures. In these systems, issues in one component often propagate across the architecture along the call chains. Yet, ...
详细信息
Decision-making by Machine Learning (ML) models can exhibit biased behavior, resulting in unfair outcomes. Testing ML models for such biases is essential to ensure unbiased decision-making. In this paper, we propose a...
详细信息
Reports show that the number of phishing web sites is exponentially increasing and it is estimated that between 80% to 93 % of the data breaches are involving phishing attacks. With both probability of occurrence as w...
详细信息
Graph data represents information efficiently and can be used to learn subsequent tasks easily. In the domain of biological science, recommender systems, social network analysis graph representation learning has becom...
详细信息
Nowadays, in order to solve the problem of information sharing in heterogeneous systems, federated database is a mature solution. However, the distributed database system also faces many performance bottlenecks. For e...
详细信息
Network Intrusion Detection systems (NIDSs) detect intrusion attacks in network traffic. In particular, machinelearning-based NIDSs have attracted attention because of their high detection rates of unknown attacks. A ...
详细信息
ISBN:
(纸本)9798350376975;9798350376968
Network Intrusion Detection systems (NIDSs) detect intrusion attacks in network traffic. In particular, machinelearning-based NIDSs have attracted attention because of their high detection rates of unknown attacks. A distributed processing framework for machine-learning-based NIDSs employing a scalable distributed stream processing system has been proposed in the literature. However, its performance, when machine-learningbased classifiers are implemented has not been comprehensively evaluated. In this study, we implement five representative classifiers (Decision Tree, Random Forest, Naive Bayes, SVM, and kNN) based on this framework and evaluate their throughput and latency. By conducting the experimental measurements, we investigate the difference in the processing performance among these classifiers and the bottlenecks in the processing performance of the framework.
暂无评论