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Topic Review
Federated Few-Shot Learning-Based Machinery Fault Diagnosis
Researchers present a novel federated few-shot learning-based machinery fault-diagnosis scheme, named FedCDAE-MN, which utilizes a combination of convolutional denoising auto-encoder and feature-space metric learning across multiple domains.
  • 249
  • 07 Oct 2023
Topic Review
Wi-Fi Assisted Indoor Positioning
As the location-based service (LBS) plays an increasingly important role in real life, the topic of positioning attracts more and more attention. Under different environments and principles, researchers have proposed a series of positioning schemes and implemented many positioning systems.
  • 149
  • 07 Oct 2023
Topic Review
Chinese Pause Fillers Prediction Module
The prediction of pause fillers plays a crucial role in enhancing the naturalness of synthesized speech. Neural networks, including LSTM, BERT, and XLNet, have been employed for pause fillers prediction modules.
  • 230
  • 07 Oct 2023
Topic Review
Customer Advocacy
The rise of online social networks has revolutionized the way businesses and consumers interact, creating new opportunities for customer word-of-mouth (WoM) and brand advocacy. 
  • 253
  • 07 Oct 2023
Topic Review
Self-Supervised Transfer Learning for Fine-Grained Image Recognition
Fine-grained image recognition aims to classify fine subcategories belonging to the same parent category, such as vehicle model or bird species classification. This is an inherently challenging task because a classifier must capture subtle interclass differences under large intraclass variances. Most previous approaches are based on supervised learning, which requires a large-scale labeled dataset. However, such large-scale annotated datasets for fine-grained image recognition are difficult to collect because they generally require domain expertise during the labeling process. Researchers propose a self-supervised transfer learning method based on Vision Transformer (ViT) to learn finer representations without human annotations. Interestingly, it is observed that existing self-supervised learning methods using ViT (e.g., DINO) show poor patch-level semantic consistency, which may be detrimental to learning finer representations. Motivated by this observation, researchers propose a consistency loss function that encourages patch embeddings of the overlapping area between two augmented views to be similar to each other during self-supervised learning on fine-grained datasets.
  • 274
  • 07 Oct 2023
Topic Review
Data Extraction Approach for Empirical Agent-Based Model Development
Agent-based model (ABM) development needs information on system components and interactions. Qualitative narratives contain contextually rich system information beneficial for ABM conceptualization. Traditional qualitative data extraction is manual, complex, and time- and resource-consuming. Moreover, manual data extraction is often biased and may produce questionable and unreliable models. A possible alternative is to employ automated approaches borrowed from Artificial Intelligence.
  • 424
  • 29 Sep 2023
Topic Review
Sensor-Based Human Action Recognition
Sensor-based Human Action Recognition (HAR) is a fundamental component in human–robot interaction and pervasive computing. It achieves HAR by acquiring sequence data from embedded sensor devices (accelerometers, magnetometers, gyroscopes, etc.) of multiple sensor modalities worn at different body locations for data processing and analysis.
  • 255
  • 28 Sep 2023
Topic Review
Shape-Informed Dimensional Reduction in Airfoil/Hydrofoil Modeling Approachs
Parametric models have been widely used in pertinent literature for reconstructing, modifying and representing a wide range of airfoil and/or hydrofoil profile geometries. Design spaces corresponding to these models can be exploited for modeling and profile-shape optimization under various performance criteria. Accuracy requirements, along with the need for modeling local features, often lead to high-dimensional design spaces that hinder the process of shape optimization and design through analysis.
  • 172
  • 28 Sep 2023
Topic Review
Stepping-Stone Intrusion Detection Resistant to Intruders’ Chaff-Perturbation
Using stepping-stone intrusion (SSI), the intruder’s identity is very difficult to discover as it is concealed by a long interactive connection chain of hosts. An effective approach for SSI detection (SSID) is to determine how many connections are contained in a connection chain. 
  • 238
  • 28 Sep 2023
Topic Review
IoT Environment Using a Blockchain-Based Local-Global Consensus Manager
The Internet of Things (IoT) refers to the network of interconnected devices that can communicate and share data over the Internet. The widespread adoption of smart devices within Internet of Things (IoT) networks poses considerable security challenges for their communication. To address these issues, blockchain technology, known for its decentralized and distributed nature, offers potential solutions within consensus-based authentication in IoT networks.
  • 189
  • 28 Sep 2023
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