Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that h...
详细信息
Graph neural networks(GNNs)have gained traction and have been applied to various graph-based data analysis tasks due to their high ***,a major concern is their robustness,particularly when faced with graph data that has been deliberately or accidentally polluted with *** presents a challenge in learning robust GNNs under noisy *** address this issue,we propose a novel framework called Soft-GNN,which mitigates the influence of label noise by adapting the data utilized in *** approach employs a dynamic data utilization strategy that estimates adaptive weights based on prediction deviation,local deviation,and global *** better utilizing significant training samples and reducing the impact of label noise through dynamic data selection,GNNs are trained to be more *** evaluate the performance,robustness,generality,and complexity of our model on five real-world datasets,and our experimental results demonstrate the superiority of our approach over existing methods.
Poverty is considered a serious global issue that must be immediately eradicated by Sustainable Development Goals (SDGs) 1, namely ending poverty anywhere and in any form. As a developing country, poverty is a complex...
详细信息
Driven by improvements in satellite internet and Low Earth Orbit(LEO)navigation augmenta-tion,the integration of communication and navigation has become increasingly common,and further improving navigation capabilitie...
详细信息
Driven by improvements in satellite internet and Low Earth Orbit(LEO)navigation augmenta-tion,the integration of communication and navigation has become increasingly common,and further improving navigation capabilities based on communication constellations has become a significant *** the context of the existing Orthogonal Frequency Division Multiplexing(OFDM)communication systems,this paper proposes a new ranging signal design method based on an LEO satellite communication *** LEO Satellite Communication Constellation Block-type Pilot(LSCC-BPR)signal is superimposed on the com-munication signal in a block-type form and occupies some of the subcarriers of the OFDM signal for transmission,thus ensuring the continuity of the ranging pilot signal in the time and frequency *** estimation in the time and frequency domains is performed to obtain the relevant distance value,and the ranging accuracy and communication resource utilization rate are *** characterize the ranging performance,the Root Mean Square Error(RMSE)is selected as an evaluation *** show that when the number of pilots is 2048 and the Signal-to-Noise Ratio(SNR)is 0 dB,the ranging accuracy can reach 0.8 m,and the pilot occupies only 50%of the communication subcarriers,thus improving the utilization of communication resources and meeting the public demand for communication and location services.
Software-defined networks(SDNs) present a novel network architecture that is widely used in various datacenters. However, SDNs also suffer from many types of security threats, among which a distributed denial of servi...
详细信息
Software-defined networks(SDNs) present a novel network architecture that is widely used in various datacenters. However, SDNs also suffer from many types of security threats, among which a distributed denial of service(DDoS) attack, which aims to drain the resources of SDN switches and controllers,is one of the most common. Once the switch or controller is damaged, the network services can be *** defense schemes against DDoS attacks have been proposed from the perspective of attack detection;however, such defense schemes are known to suffer from a time consuming and unpromising accuracy, which could result in an unavailable network service before specific countermeasures are taken. To address this issue through a systematic investigation, we propose an elaborate resource-management mechanism against DDoS attacks in an SDN. Specifically, by considering the SDN topology, we leverage the M/M/c queuing model to measure the resistance of an SDN to DDoS attacks. Network administrators can therefore invest a reasonable number of resources into SDN switches and SDN controllers to defend against DDoS attacks while guaranteeing the quality of service(QoS). Comprehensive analyses and empirical data-based experiments demonstrate the effectiveness of the proposed approach.
This paper presents ChestBox, a novel approach that utilizes state functions to facilitate low-latency state sharing for stateful serverless computing. When an application function needs to share a state, the state fu...
详细信息
Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised...
详细信息
Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised feature selection has received increasing attention in recent years. However, existing unsupervised feature selection methods tend to prioritize selecting highly correlated features over exploring feature diversity. Thus, a regularized fractal autoencoder(RFAE) method is proposed to select informative features in an unsupervised way. Specifically, the fractal autoencoder network extends autoencoders to construct a correspondence neural network and a selection neural network. The correspondence neural network exploits interfeature correlations and the selection neural network selects the informative features. A redundancy regularization strategy consists of a redundancy elimination regularization term based on the dependency between features and a sparse regularization term based on the group lasso. The redundancy regularization strategy eliminates feature subset redundancy and enhances network generalization ability. Extensive experimental results on six publicly available datasets show that the proposed RFAE outperforms the compared methods regarding clustering accuracy and classification accuracy. Moreover, the proposed RFAE achieves acceptable computation efficiency.
Indonesia has entered a period of demographic bonus. Human resources must be optimized. The number of children who do not in employment, education or training (NEET) in each province needs attention. Several factors t...
详细信息
Graph processing has been widely used in many scenarios,from scientific computing to artificial *** processing exhibits irregular computational parallelism and random memory accesses,unlike traditional ***,running gra...
详细信息
Graph processing has been widely used in many scenarios,from scientific computing to artificial *** processing exhibits irregular computational parallelism and random memory accesses,unlike traditional ***,running graph processing workloads on conventional architectures(e.g.,CPUs and GPUs)often shows a significantly low compute-memory ratio with few performance benefits,which can be,in many cases,even slower than a specialized single-thread graph *** domain-specific hardware designs are essential for graph processing,it is still challenging to transform the hardware capability to performance boost without coupled software *** article presents a graph processing ecosystem from hardware to *** start by introducing a series of hardware accelerators as the foundation of this ***,the codesigned parallel graph systems and their distributed techniques are presented to support graph ***,we introduce our efforts on novel graph applications and hardware *** results show that various graph applications can be efficiently accelerated in this graph processing ecosystem.
1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,G...
详细信息
1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,GNNs may encounter the scalability issue stemming from their multi-layer messagepassing ***,scaling GNNs has emerged as a crucial research area in recent years,with numerous scaling strategies being proposed.
Media power,the impact that media have on public opinion and perspectives,plays a significant role in maintaining internal stability,exerting external influence,and shaping international dynamics for nations/***,prior...
详细信息
Media power,the impact that media have on public opinion and perspectives,plays a significant role in maintaining internal stability,exerting external influence,and shaping international dynamics for nations/***,prior research has primarily concentrated on news content and reporting time,resulting in limitations in evaluating media *** more accurately assess media power,we use news content,news reporting time,and news emotion simultaneously to explore the emotional contagion between *** use emotional contagion to measure the mutual influence between media and regard the media with greater impact as having stronger media *** propose a framework called Measuring Media Power via Emotional Contagion(MMPEC)to capture emotional contagion among media,enabling a more accurate assessment of media power at the media and national/regional *** also interprets experimental results through correlation and causality analyses,ensuring *** analyses confirm the higher accuracy of MMPEC compared to other baseline models,as demonstrated in the context of COVID-19-related news,yielding compelling and interesting insights.
暂无评论