Federated Learning is a machine learning framework in which multiple clients engage in collaborative training of a model, while the training data remains distributed across the client devices. The training process is ...
详细信息
Telemedicine is of great importance as it increases the availability of health care for people living in remote or undeveloped areas. It reduces the cost of health care, allows for early diagnosis and treatment of chr...
详细信息
Unmanned sailboats are driven only by wind, making them good platforms for the synchronous observation of air-sea interfaces over a large range. Compared with traditional unmanned ships, the unmanned sailboat involves...
详细信息
Unmanned sailboats are driven only by wind, making them good platforms for the synchronous observation of air-sea interfaces over a large range. Compared with traditional unmanned ships, the unmanned sailboat involves simultaneous sail and rudder control for path tracking in unpredictable marine environments. The system is characterized by strong coupling and nonlinearity, creating challenges for the design of controllers. This paper combines line-of-sight (LOS) guidance with the introduction of a sideslip angle observer and model predictive control. A high-precision path tracking strategy suitable for cooperative sail and rudder control for unmanned sailboats is proposed. First, considering the lateral error easily caused by the large sideslip angle of sailboats, a full-path fixed-time guidance strategy with double fixed-time sideslip angle observers (DFSO) is proposed. Second, different from the previous strategy of decoupling the sail and rudder to control the speed and heading, the proposed cooperative control framework uses Lyapunov-based model predictive control (LMPC). The sailing speed and heading angle are both accounted for in the objective function, and the stability is verified by Lyapunov theory. Finally, the feasibility and superiority of this proposed method are confirmed by numerical simulation experiments involving the path tracking of a four degree of freedom sailboat model integrated with wind and waves in an ocean environment. IEEE
This research provides a comprehensive approach in designing a recommendation system for women's health issues, with emphasis on menopause and optimal eating plan with Shatavari nutrition plan incorporated. The da...
详细信息
Human gait recognition(HGR)is the process of identifying a sub-ject(human)based on their walking *** subject is a unique walking pattern and cannot be simulated by other ***,gait recognition is not easy and makes the ...
详细信息
Human gait recognition(HGR)is the process of identifying a sub-ject(human)based on their walking *** subject is a unique walking pattern and cannot be simulated by other ***,gait recognition is not easy and makes the system difficult if any object is carried by a subject,such as a bag or *** article proposes an automated architecture based on deep features optimization for *** our knowledge,it is the first architecture in which features are fused using multiset canonical correlation analysis(MCCA).In the proposed method,original video frames are processed for all 11 selected angles of the CASIA B dataset and utilized to train two fine-tuned deep learning models such as Squeezenet and *** transfer learning was used to train both fine-tuned models on selected angles,yielding two new targeted models that were later used for feature *** are extracted from the deep layer of both fine-tuned models and fused into one vector using *** improved manta ray foraging optimization algorithm is also proposed to select the best features from the fused feature matrix and classified using a narrow neural network *** experimental process was conducted on all 11 angles of the large multi-view gait dataset(CASIA B)dataset and obtained improved accuracy than the state-of-the-art ***,a detailed confidence interval based analysis also shows the effectiveness of the proposed architecture for HGR.
Rheumatic Fever or Acute Rheumatic Fever (RF) and Rheumatic Heart Disease (RHD) are commonly suffered by people of all ages around the world. RF usually begins with strep throat infections, skin problems, joint pain e...
详细信息
With the continuous attention given to 'smart manufacturing' and 'smart factories,' the importance of equipment networking and data collection has been increasing. One key issue is the standardization ...
详细信息
The rise of end-user applications powered by large language models (LLMs), including both conversational interfaces and add-ons to existing graphical user interfaces (GUIs), introduces new privacy challenges. However,...
详细信息
Fog networking is an aspect of the IoT (Internet of Things) idea, which sees most of the products used by humans on a daily basis connected to one another. Smart phones, smart health monitoring equipment, as...
详细信息
Diabetic retinopathy (DR) is an infection that bases eternal visualization loss in patients with diabetes mellitus. With DR, the glucose level in the blood increases, as well as its viscosity, this results in fluid le...
详细信息
Diabetic retinopathy (DR) is an infection that bases eternal visualization loss in patients with diabetes mellitus. With DR, the glucose level in the blood increases, as well as its viscosity, this results in fluid leakage into surrounding tissues in the retina. In other words, DR represents the pathology of capillaries and venules in the retina with leakage effects, being the main acute retinal disorder caused by diabetes. Many DR detection methods have been previously discussed by different researchers;however, accurate DR detection with a reduced execution time has not been achieved by existing methods. The proposed method, the Shape Adaptive box linear filtering-based Gradient Deep Belief network classifier (SAGDEB) Model, is performed to enhance the accuracy of DR detection. The objective of the SAGDEB Model is to perform an efficient DR identification with a higher accuracy and lower execution time. This model comprises three phases: pre-processing, feature extraction, and classification. The shape adaptive box linear filtering image pre-processing is carried out to reduce the image noise without removing significant parts of image content. Then, an isomap geometric feature extraction is performed to compute features of different natures, like shape, texture, and color, from the pre-processed images. After that, the Adaptive gradient Tversky Deep belief network classifier is to perform classification. The deep belief network is probabilistic and generative graphical model that consists of multiple layers such as one input unit, three hidden units, and one output unit. The extracted image featuresare considered in the input layer and these images are sent to hidden layers. Tversky similarity index is applied in hidden layer 1 to analyze the extracted features with testing features. Regarding the similarity value, the sigmoid activation function is determined in hidden layer 2 so different levels of DR can be identified. Finally, the adaptive gradient method is
暂无评论