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Topic Review
Thematic Evolution of Virtual Manufacturing Literature (1983–2023)
Virtual manufacturing (VM) technology emerged in the 1980s as a revolutionary strategy to optimize and streamline the entire product/service manufacturing lifecycle. However, over the years, its popularity appears to have waned. Further, the advent of the fourth industrial revolution (4IR) or Industry 4.0 brings with it other integrated digital technologies, including the Internet of Things (IoT), Blockchain, and digital twin (DT), among others. DT offers functions like VM plus other benefits, including intelligent manufacturing, to revolutionize future manufacturing operations activities and predictive capability using real-time data.
  • 203
  • 30 Oct 2023
Topic Review
Video Super-Resolution
Super-resolution (SR) refers to yielding high-resolution (HR) images from corresponding low-resolution (LR) images. As a branch of this field, video super-resolution (VSR) mainly utilizes the spatial information of the frame and the temporal information between neighboring frames to reconstruct the HR frame. 
  • 192
  • 27 Oct 2023
Topic Review
Multiple-Instance Learning Methods
Multiple-instance learning has become popular due to its use in some special scenarios. It is basically a type of weakly supervised learning where the learning dataset contains bags of instances instead of a single feature vector. Each bag is associated with a single label. This type of learning is flexible and a natural fit for multiple real-world problems. MIL has been employed to deal with a number of challenges, including object detection and identification tasks, content-based image retrieval, and computer-aided diagnosis. Medical image analysis and drug activity prediction have been the main uses of MIL in biomedical research. 
  • 355
  • 27 Oct 2023
Topic Review
Deep Learning Architectures for Multivariate Time-Series Forecasting
Deep learning algorithms, renowned for their ability to extract intricate patterns from complex datasets, have proven particularly adept at handling the multifaceted time-series data characteristic of smart city IoT applications. Deep learning architectures model complex relationships through a series of nonlinear layers—the set of nodes of each intermediate layer capturing the corresponding feature representation of the input.
  • 199
  • 27 Oct 2023
Topic Review
HVAC Data-Driven Maintenance
Buildings’ heating, ventilation, and air-conditioning (HVAC) systems account for significant global energy use. Proper maintenance can minimize their environmental footprint and enhance the quality of the indoor environment. The adoption of Internet of Things (IoT) sensors integrated into HVAC systems has paved the way for data-driven predictive maintenance (PdM) grounded in real-time operational metrics.
  • 185
  • 27 Oct 2023
Topic Review
Secure Internet of Things Based on Blockchain
Centralized networks can host ubiquitous interconnected objects using Internet of Things (IoT) platforms. It is also possible to implement decentralized peer-to-peer solutions using blockchain technology, including smart homes and connected cars. However, both models have limitations regarding their ability to provide privacy and security due to limited resources, centralization management, and scalability, cost, and response time. The diversity of IoT network nodes is expected to result in different throughputs and rates. Centralized networks control and improve the performance of a large number of IoT devices. However, centralizing systems suffer from a number of disadvantages. A third party often has to manipulate the data collected by central cloud storage, which could lead to information leaks that could compromise the user’s privacy.
  • 269
  • 27 Oct 2023
Topic Review
Requirements of Compression in Key-Value Stores
A key–value store is a de facto standard database for unstructured big data. Key–value stores, such as Google’s LevelDB and Meta’s RocksDB, have emerged as a popular solution for managing unstructured data due to their ability to handle diverse data types with a simple key–value abstraction. Simultaneously, a multitude of data management tools have actively adopted compression techniques, such as Snappy and Zstd, to effectively reduce data volume.
  • 454
  • 27 Oct 2023
Topic Review
Self-Attention-Based 3D Object Detection for Autonomous Driving
Autonomous vehicles (AVs) play a crucial role in enhancing urban mobility within the context of a smarter and more connected urban environment. Three-dimensional object detection in AVs is an essential task for comprehending the driving environment to contribute to their safe use in urban environments. 
  • 191
  • 27 Oct 2023
Topic Review
Federated Meta-Learning for Driver Distraction Detection
Driver distraction detection (3D) is essential in improving the efficiency and safety of transportation systems. Federated learning (FL) is emerging as a feasible solution that can train models without private and sensitive information leaving its local repository. Even though various solutions are proposed by using FL to upgrade the model learning paradigm of 3D, considering the requirements for user privacy and the phenomenon of data growth in real-world scenarios, existing methods are insufficient to address four emerging challenges, i.e., data accumulation, communication optimization, data heterogeneity, and device heterogeneity. 
  • 165
  • 27 Oct 2023
Topic Review
Human Operation Augmentation through Wearable Robotic Limb
The supernumerary robotic limb (SRL) is a new type of wearable robot that improves the human body’s ability to move, perceive, and operate through mechanical and human limbs’ integration, mutual assistance, and cooperation. Unlike traditional collaborative robots, SRLs have a closer human–computer interaction mode and a cooperative mode of moving with the human body.
  • 113
  • 27 Oct 2023
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