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Topic Review
Artificial Intelligence Techniques in Concrete
Due to the speed of artificial intelligence (AI) techniques in solving engineering problems, there has been a tendency to use these techniques in various fields of civil engineering, including designing construction materials (concrete mixtures for example) or estimating their properties.  As it is hard to predict the compressive strength of concrete due to the different nonlinearities inherent in the mixture designs, various concrete companies are continuously looking to use new methods and technologies to predict the compressive strength. Such methods include numerical modelling and artificial intelligence due to their advantages. 
  • 285
  • 07 Oct 2023
Topic Review
Automated Stuttering Classification
Speech disfluency, particularly stuttering, can have a significant impact on effective communication. Stuttering is a speech disorder characterized by repetitions, prolongations, and blocks in the flow of speech, which can result in communication difficulties, social isolation, and low self-esteem. Stuttering can also lead to negative reactions from listeners, such as impatience or frustration, which can further exacerbate communication difficulties.
  • 334
  • 07 Oct 2023
Topic Review
Validated Questionnaires in Flow Theory
Psychological flow has been measured in several areas to analyse to what extent users are engaged in particular tasks, and is relevant in the design of products like software, videogames, and eLearning courses.
  • 296
  • 07 Oct 2023
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.
  • 267
  • 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.
  • 159
  • 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.
  • 274
  • 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. 
  • 279
  • 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.
  • 314
  • 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.
  • 437
  • 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.
  • 265
  • 28 Sep 2023
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