Space manipulators play an important role in the on-orbit services and planetary surface *** the extreme environment of space,space manipulators are susceptible to a variety of unknown *** to have a resilient guarante...
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Space manipulators play an important role in the on-orbit services and planetary surface *** the extreme environment of space,space manipulators are susceptible to a variety of unknown *** to have a resilient guarantee in failure or disturbance is the core capability of its future *** with traditional motion planning,learning-based motion planning has gradually become a hot spot in current ***,no matter what kind of research ideas,the single robotic manipulator is studied as an independent agent,making it unable to provide sufficient flexibility under conditions such as external force disturbance,observation noise,and mechanical ***,this paper puts forward the idea of“discretization of the traditional single manipulator”.Different discretization forms are given through the analysis of the multi-degree-of-freedom single-manipulator joint relationship,and a single-manipulator representation composed of multiple new subagents is ***,to verify the ability of the new multiagent representation to deal with interference,we adopted a centralized multiagent reinforcement learning *** influence of the number of agents and communication distances on learning-based planning results is analyzed in *** addition,by imposing joint locking failures on the manipulator and introducing observation and action interference,it is verified that the“multiagent robotic manipulator”obtained after discretization has stronger antidisturbance resilient capability than the traditional single manipulator.
Presently,video surveillance is commonly employed to ensure security in public places such as traffic signals,malls,railway stations,etc.A major chal-lenge in video surveillance is the identification of anomalies that...
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Presently,video surveillance is commonly employed to ensure security in public places such as traffic signals,malls,railway stations,etc.A major chal-lenge in video surveillance is the identification of anomalies that exist in it such as crimes,thefts,and so ***,the anomaly detection in pedestrian walkways has gained significant attention among the computer vision communities to enhance pedestrian *** recent advances of Deep Learning(DL)models have received considerable attention in different processes such as object detec-tion,image classification,*** this aspect,this article designs a new Panoptic Feature Pyramid Network based Anomaly Detection and Tracking(PFPN-ADT)model for pedestrian *** proposed model majorly aims to the recognition and classification of different anomalies present in the pedestrian walkway like vehicles,skaters,*** proposed model involves panoptic seg-mentation model,called Panoptic Feature Pyramid Network(PFPN)is employed for the object recognition *** object classification,Compact Bat Algo-rithm(CBA)with Stacked Auto Encoder(SAE)is applied for the classification of recognized *** ensuring the enhanced results better anomaly detection performance of the PFPN-ADT technique,a comparison study is made using Uni-versity of California San Diego(UCSD)Anomaly data and other benchmark data-sets(such as Cityscapes,ADE20K,COCO),and the outcomes are compared with the Mask Recurrent Convolutional Neural Network(RCNN)and Faster Convolu-tional Neural Network(CNN)*** simulation outcome demonstrated the enhanced performance of the PFPN-ADT technique over the other methods.
The pursuit of trend prediction in diverse datasets has captivated the interest of researchers over the years. The significance of predictive modeling spans various domains, including business models, scientific resea...
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The burgeoning discipline of affective computing, which sits at the nexus of AI and psychology, aims to improve our capacity to comprehend and analyze human emotions as they manifest themselves in visual data. This ab...
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This study explores the effectiveness of various machine learning algorithms in forecasting hair health using a comprehensive dataset incorporating individual traits and lifestyle elements. Logistic regression, random...
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As a complex hot problem in the financial field,stock trend forecasting uses a large amount of data and many related indicators;hence it is difficult to obtain sustainable and effective results only by relying on empi...
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As a complex hot problem in the financial field,stock trend forecasting uses a large amount of data and many related indicators;hence it is difficult to obtain sustainable and effective results only by relying on empirical *** in the field of machine learning have proved that random forest can form better judgements on this kind of problem,and it has an auxiliary role in the prediction of stock *** study uses historical trading data of four listed companies in the USA stock market,and the purpose of this study is to improve the performance of random forest model in medium-and long-term stock trend *** study applies the exponential smoothing method to process the initial data,calculates the relevant technical indicators as the characteristics to be selected,and proposes the D-RF-RS method to optimize random *** the random forest is an ensemble learning model and is closely related to decision tree,D-RF-RS method uses a decision tree to screen the importance of features,and obtains the effective strong feature set of the model as ***,the parameter combination of the model is optimized through random parameter *** experimental results show that the average accuracy of random forest is increased by 0.17 after the above process optimization,which is 0.18 higher than the average accuracy of light gradient boosting machine *** with the performance of the ROC curve and Precision–Recall curve,the stability of the model is also guaranteed,which further demonstrates the advantages of random forest in medium-and long-term trend prediction of the stock market.
In the contemporary landscape, autonomous vehicles (AVs) have emerged as a prominent technological advancement globally. Despite their widespread adoption, significant hurdles remain, with security standing out as a c...
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Group communication is widely used by most of the emerging network applications like telecommunication,video conferencing,simulation applications,distributed and other interactive *** group communication plays a vital...
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Group communication is widely used by most of the emerging network applications like telecommunication,video conferencing,simulation applications,distributed and other interactive *** group communication plays a vital role in case of providing the integrity,authenticity,confidentiality,and availability of the message delivered among the group members with respect to communicate securely between the inter group or else within the *** secure group communications,the time cost associated with the key updating in the proceedings of the member join and departure is an important aspect of the quality of service,particularly in the large groups with highly active ***,the paper is aimed to achieve better cost and time efficiency through an improved DC multicast routing protocol which is used to expose the path between the nodes participating in the group *** this process,each node constructs an adaptive Ptolemy decision tree for the purpose of generating the contributory *** of the node is comprised of three keys which will be exchanged between the nodes for considering the group key for the purpose of secure and cost-efficient group *** rekeying process is performed when a member leaves or adds into the *** performance metrics of novel approach is measured depending on the important factors such as computational and communicational cost,rekeying process and formation of the *** is concluded from the study that the technique has reduced the computational and communicational cost of the secure group communication when compared to the other existing methods.
Nowadays, photoplethysmograph (PPG) technology is being used more often in smart devices and mobile phones due to advancements in information and communication technology in the health field, particularly in monitorin...
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Diabetes is a widespread chronic condition that impacts people all over the globe and requires a clear and timely diagnosis. Untreated diabetes leads to retinopathy, nephropathy, and damage to the nervous system. In t...
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