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The emergence of <italic>mobile edge computing</italic> (MEC) in distributed systems has sparked increased attention toward edge data management. A conflict arises from the disparity between limited edge resources and the continuously expanding data ...

With its advantages in ensuring low data retrieval latency and reducing backhaul network traffic, edge computing is becoming a backbone solution for many latency-sensitive applications. An increasingly large number of data is being generated at the edge, ...

In the edge computing environment, app vendors can distribute popular data from the cloud to edge servers to provide low-latency data retrieval. A key problem is how to distribute these data from the cloud to edge servers cost-effectively. Under current ...

Traffic flow prediction plays a crucial role in intelligent transportation systems as it enables effective control and management of urban traffic. However, existing methods that based on Graph Convolutional Networks (GCNs) primarily utilize local ...

In an edge computing environment, data can be cached on edge servers to enable fast data services for users. These edge data are subject to corruption and must be verified to ensure their integrity. Meanwhile, they are also subject to partial ...

Edge computing (EC) enables low-latency services by pushing computing resources to the network edge. Due to the geographic distribution and limited capacities of edge servers, EC systems face the challenge of edge distributed denial-of-service (DDoS) ...

We introduce a projection-based test for assessing logistic regression models using the empirical residual marked empirical process and suggest a model-based bootstrap procedure to calculate critical values. We comprehensively compare this test ...$\mathrm{}$$\mathrm{}$$\mathrm{}$

Mobile edge computing (MEC) offers a new computing paradigm that turns computing and storage resources to the network edge to provide minimal service latency compared to cloud computing. Many research works have attempted to help app vendors allocate ...

This paper proposes a distributed power trading model centered around power aggregators, which aims to optimize the trading processes and efficiency of distributed energy. Then, a blockchain-based distributed resource trading platform is designed ...

The emerging <underline>M</underline>obile <underline>E</underline>dge <underline>C</underline>omputing (MEC) paradigm reforms the way of data caching by motivating App vendors to store latency-sensitive data on distributed edge servers. In volatile MEC ...

<underline>E</underline>dge <underline>I</underline>ntelligence (EI), a burgeoning research area, motivates App vendors to cache data replicas on geographically distributed edge servers to deliver better services. On the downside, this benefit also incurs ...

By pushing computing resources from the cloud to the network edge close to mobile users, mobile edge computing (MEC) enables low latency for a wide variety of applications. Nevertheless, in dynamic MEC systems, MEC services are challenged by the risks of ...

A homogeneous pneumatic soft robot may generate complex output motions using a simple input pressure, resulting from its morphological shape that locally deforms the soft material to different degrees by simultaneously tailoring the structural ...

This study tackles the online user allocation problem in mobile edge computing (MEC) systems powered by non-orthogonal multiple access. App vendors need to determine a proper wireless channel in a base station/edge server and sufficient transmit power for ...

Classification and outcome prediction of intracerebral hemorrhage (ICH) is critical for improving the survival rate of patients. Early or delayed neurological deterioration is common in ICH patients, which may lead to changes in the autonomic ...

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• First proposed applying SKNA signal analysis in ICH classification and outcome prediction.
• The multi-scale features of the SKNA signal were used to analyze and evaluate the specific clinical application.
• The ICH patients with good ...

This bibliometric study offers a comprehensive overview of e-learning research landscape in English as a foreign language (EFL) context, including the publication trend, country contributions and collaboration, productive authors and journals, and key ...

In an edge storage system, popular data can be stored on edge servers to enable low-latency data retrieval for nearby users. Suffering from constrained storage capacities, edge servers must process users' data requests collaboratively. For sourcing data, ...

Dielectric elastomer actuators (DEAs) possess characteristics closest to human muscles and have been rapidly developed. The rolled DEA is considered more suitable as a driving module due to its ability to output unidirectional deformation. This ...

With the rollout of the 5G network around the globe, a massive number of edge servers have been deployed to host online applications demanding low service latency for users. These edge servers constitute multi-access edge computing (MEC) systems. Running ...

Training machine learning (ML) models on mobile and Web-of-Things (WoT) has been widely acknowledged and employed as a promising solution to privacy-preserving ML. However, these end-devices often suffer from constrained resources and fail to accommodate ...