Search Results

Geographically replicating objects across multiple data centers improves the performance and reliability of cloud storage systems. Maintaining consistent replicas comes with high synchronization costs, as it faces more expensive WAN transport ...

The prevalence and perniciousness of fake news have been a critical issue on the Internet, which stimulates the development of automatic fake news detection in turn. In this paper, we focus on the evidence-based fake news detection, where several ...

Online updating of time series forecasting models aims to address the concept drifting problem by efficiently updating forecasting models based on streaming data. Many algorithms are designed for online time series forecasting, with some exploiting cross-...

Graph Structure Learning (GSL) has recently garnered considerable attention due to its ability to optimize both the parameters of Graph Neural Networks (GNNs) and the computation graph structure simultaneously. Despite the proliferation of GSL methods ...

Although link prediction on graphs has achieved great success with the development of graph neural networks (GNNs), the potential robustness under the edge noise is still less investigated. To close this gap, we first conduct an empirical study to ...

Vision-and-Language Navigation (VLN) is a challenging task that requires an agent to navigate through complex environments based on natural language instructions. In contrast to conventional approaches, which primarily focus on the spatial domain ...

Molecular Representation Learning (MRL) has emerged as a powerful tool for drug and materials discovery in a variety of tasks such as virtual screening and inverse design. While there has been a surge of interest in advancing model-centric techniques, ...

This paper proposes a method for implementing a trusted execution environment for a computing platform based on Trusted Platform Control Module (TPCM). The method is based on a dual-architecture, which maintains the original design of the device and ...

• A new heterogeneous graph structure is proposed to represent the state of DFJSP-ITR and the MDP model of DFJSP-ITR is established.
• A three-stage node embedding method for extracting node features is proposed for integrated decision ...

The smart workshop is a powerful tool for manufacturing companies to reduce waste and improve production efficiency through real-time data analysis for self-organized production. Automated Guided Vehicles (AGVs) have been widely used for material ...

• Intelligent detection of citrus green fruit.
• Addressing the issue of image blurriness and degradation during real-world data acquisition.
• Offering a lightweight model suitable for edge smart devices.
• Achieving yield prediction.

Real-time detection of green citrus fruit is crucial for accurate fruit localization and early yield prediction in the citrus growing process. This detection involves three imaging steps: acquisition, transmission, and detection. Image quality ...

To fully exploit the locality of GPU applications, the GPU shared L1 cache architecture, which shares L1 cache among multiple GPU cores, is a promising architecture while still suffering from high-resource contentions. We present a GPU shared L1 cache ...

In recent years, deep learning models have shown their advantages in neuroimage analysis, such as brain disease diagnosis. Unfortunately, it is usually difficult to acquire numerous brain networks at a single centralized site to effectively train ...

Drug recommendation aims to recommend a combination of drugs to patients with specific symptoms based on the interactions between symptom sets and drug sets. However, most existing methods focus on the interaction between single symptom and single drug, ...

Real-time video analytics on edge devices for changing scenes remains a difficult task. As edge devices are usually resource-constrained, edge deep neural networks (DNNs) have fewer weights and shallower architectures than general DNNs. As a ...

In this paper, a convolution neural network (CNN) based data-driven method was proposed to to improve the diagnostic performance of gas turbine gas path fault under multiple operating conditions and multiple fault severities. To apply the CNN to gas path ...

Abstract:In view of the current diversity and structural complexity of protective appliances, the operation inspection part of the protection electrical equipment action characteristics and selective cooperation calibration, can only rely on the ...

Medical image segmentation is a crucial task in many clinical applications, such as tumor detection and surgical planning. However, the annotation process for medical images is often both time-consuming and expensive, which requires professional ...

This paper considers optimal traffic signal control in smart cities, which has been taken as a complex networked system control problem. Given the interacting dynamics among traffic lights and road networks, attaining controller adaptivity and scalability ...

On open source software (OSS) platforms such as GitHub, forking and accepting pull-requests is an important approach for OSS projects to receive contributions, especially from external contributors who cannot directly commit into the source repositories. ...

As technology scales down, the critical charge (QC) of vulnerable nodes decreases, making SRAM cells more susceptible to soft errors in the aerospace industry. This article proposes a Soft-Error-Aware 16T (S8P8N) SRAM cell for aerospace applications to ...