Domain adaptation(DA) aims to find a subspace,where the discrepancies between the source and target domains are reduced. Based on this subspace, the classifier trained by the labeled source samples can classify unlabe...
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Domain adaptation(DA) aims to find a subspace,where the discrepancies between the source and target domains are reduced. Based on this subspace, the classifier trained by the labeled source samples can classify unlabeled target samples *** approaches leverage Graph Embedding Learning to explore such a subspace. Unfortunately, due to 1) the interaction of the consistency and specificity between samples, and 2) the joint impact of the degenerated features and incorrect labels in the samples, the existing approaches might assign unsuitable similarity, which restricts their performance. In this paper, we propose an approach called adaptive graph embedding with consistency and specificity(AGE-CS) to cope with these issues. AGE-CS consists of two methods, i.e., graph embedding with consistency and specificity(GECS), and adaptive graph embedding(AGE).GECS jointly learns the similarity of samples under the geometric distance and semantic similarity metrics, while AGE adaptively adjusts the relative importance between the geometric distance and semantic similarity during the iterations. By AGE-CS,the neighborhood samples with the same label are rewarded,while the neighborhood samples with different labels are punished. As a result, compact structures are preserved, and advanced performance is achieved. Extensive experiments on five benchmark datasets demonstrate that the proposed method performs better than other Graph Embedding methods.
Fish farmers operating at Sirindhorn Dam in Ubon Ratchathani have faced significant challenges, including high mortality rates attributable to unstable weather conditions that compromise water quality. To tackle these...
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One of the greatest developments in computerscience is undoubtedly quantum computing. It has demonstrated to give various benefits over the classical algorithms, particularly in the significant reduction of processin...
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A well-designed curriculum is essential to ensure that students can maintain a healthy academic life, whether at school, college, or university. Such a curriculum would help students balance their academic work and ex...
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The current work aims to present abundant families of the exact solutions of Mikhailov-Novikov-Wang equation via three different *** adopted methods are generalized Kudryashov method(GKM),exponential rational function...
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The current work aims to present abundant families of the exact solutions of Mikhailov-Novikov-Wang equation via three different *** adopted methods are generalized Kudryashov method(GKM),exponential rational function method(ERFM),and modified extended tanh-function method(METFM).Some plots of some presented new solutions are represented to exhibit wave *** results in this work are essential to understand the physical meaning and behavior of the investigated equation that sheds light on the importance of investigating various nonlinear wave phenomena in ocean engineering and *** equation provides new insights to understand the relationship between the integrability and water waves’phenomena.
Breast cancer, the most common cancer affecting female patients, presents serious challenges for proper detection. Although computer-aided diagnostic techniques have progressed, their accuracy and efficacy remain limi...
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The brain is one of the most complicated human organs, and diseases associated with the brain are still hard to diagnose, treat and manage. The development of devices such as Artificial Intelligence technology has mad...
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With the rise of the Internet of Vehicles(IoV)and the number of connected vehicles increasing on the roads,Cooperative Intelligent Transportation systems(C-ITSs)have become an important area of *** the number of Vehic...
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With the rise of the Internet of Vehicles(IoV)and the number of connected vehicles increasing on the roads,Cooperative Intelligent Transportation systems(C-ITSs)have become an important area of *** the number of Vehicle to Vehicle(V2V)and Vehicle to Interface(V2I)communication links increases,the amount of data received and processed in the network also *** addition,networking interfaces need to be made more secure for which existing cryptography-based security schemes may not be ***,there is a need to augment them with intelligent network intrusion detection *** machine learning-based intrusion detection and anomaly detection techniques for vehicular networks have been proposed in recent ***,given the expected large network size,there is a necessity for extensive data processing for use in such anomaly detection *** learning solutions are lucrative options as they remove the necessity for feature ***,with the amount of vehicular network traffic increasing at an unprecedented rate in the C-ITS scenario,the need for deep learning-based techniques is all the more *** work presents three deep learning-based misbehavior classification schemes for intrusion detection in IoV networks using Long Short Term Memory(LSTM)and Convolutional Neural Networks(CNNs).The proposed Deep Learning Classification Engines(DCLE)comprise of single or multi-step classification done by deep learning models that are deployed on the vehicular edge *** data received by the Road Side Units(RSUs)is pre-processed and forwarded to the edge server for classifications following the three classification schemes proposed in this *** proposed classifiers identify 18 different vehicular behavior types,the F1-scores ranging from 95.58%to 96.75%,much higher than the existing *** running the classifiers on testbeds emulating edge servers,the prediction performance and prediction time comparison of
An extensive knowledge of cognitive development from early infancy to late adolescence is required to investigate brain neural pathways. The success in recognizing diverse stimuli is one of the remarkable frameworks t...
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The purpose of this article is to propose Stability-based Energy-Efficient Link-State Hybrid Routing(S-ELHR),a low latency routing proto-col that aims to provide a stable mechanism for routing in unmanned aerial vehic...
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The purpose of this article is to propose Stability-based Energy-Efficient Link-State Hybrid Routing(S-ELHR),a low latency routing proto-col that aims to provide a stable mechanism for routing in unmanned aerial vehicles(UAV).The S-ELHR protocol selects a number of network nodes to create a Connected Dominating Set(CDS)using a parameter known as the Stability Metric(SM).The SM considers the node’s energy usage,connectivity time,and node’s *** the highest SM nodes are chosen to form *** node declares a Willingness to indicate that it is prepared to serve as a relay for its neighbors,by employing its own energy state.S-ELHR is a hybrid protocol that stores only partial topological information and routing tables on CDS *** of relying on the routing information at each intermediary node,it uses source routing,in which a route is generated on-demand,and data packets contain the addresses of the nodes the packet will transit.A route recovery technique is additionally utilized,which first locates a new route to the destination before forwarding packets along *** simulation for various network sizes and mobility speeds,the efficiency of S-ELHR is *** findings demonstrate that S-ELHR performs better than Optimized Link State Routing(OLSR)and Energy Enhanced OLSR(EE-OLSR)in terms of packet delivery ratio,end-to-end delay,and energy consumption.
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