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Topic Review
Crucial Technologies of Digital Thread Implementation
The digital thread is identified as an integrated information flow using recognized authoritative data sources (e.g., requirements, system architecture, technical data packages (TDP), 3D CAD models) connecting all stages of the product lifecycle. The objective of the digital thread is to establish an integrated framework that consolidates all stages of the product lifecycle and systems, facilitating efficient and effective lifecycle measurements and supporting a data-driven approach.
  • 211
  • 11 Mar 2024
Topic Review
Anomaly Detection in Autonomous Robotic Missions
An anomaly in autonomous robotic missions (ARM) is a deviation from the expected behaviour, performance, or state of the robotic system and its environment, which may impact the mission’s objectives, safety, or efficiency; and this anomaly can be caused either by system faults or the change in the environmental dynamics of interaction. The nuanced understanding of anomaly categories facilitates a more strategic approach, ensuring that detection methods are more effective in addressing the specific nature of the anomaly.
  • 434
  • 11 Mar 2024
Topic Review
Applications of Blockchain-Based Federated Learning
Federated learning (FL) and blockchains exhibit significant commonality, complementarity, and alignment in various aspects, such as application domains, architectural features, and privacy protection mechanisms. Blockchain-based federated learning (BFL) has gained the capability and prospects for applications in highly privacy-sensitive industries. 
  • 110
  • 08 Mar 2024
Topic Review
Lane Changing Maneuvers for Vehicle Driving Safety
The increasing number of vehicles has caused traffic conditions to become increasingly complicated in terms of safety. Emerging autonomous vehicles (AVs) have the potential to significantly reduce crashes. The advanced driver assistance system (ADAS) has received widespread attention. Lane keeping and lane changing are two basic driving maneuvers on highways. It is very important for ADAS technology to identify them effectively. The lane changing maneuver recognition has been used to study traffic safety for many years.
  • 101
  • 08 Mar 2024
Topic Review
Transfer Learning Strategies
Discriminatively trained models perform well if labeled data are available in abundance, but they do not perform adequately for tasks with scarce datasets as this limits their learning abilities. To address this issue, Large language models (LLMs) were first pretrained on large unlabeled datasets using the self-supervised approach, where the learning was then transferred discriminatively on specific tasks. As a result, transfer learning helps to leverage the capabilities of pretrained models and is advantageous, especially in data-scare settings. For example, generative pretrained transformer (GPT) used the generative language model objective for pretraining, followed by discriminative finetuning. Compared to pretraining, the transfer learning process is inexpensive and converges faster than training the model from scratch. Additionally, pretraining uses an unlabeled dataset and follows a self-supervised approach, whereas transfer learning follows a supervised technique using a labeled dataset particular to the downstream task. The pretraining dataset comes from a generic domain, whereas, during transfer learning, data come from specific distributions (supervised datasets specific to the desired task).
  • 216
  • 08 Mar 2024
Topic Review
Categories of Cloud-Based Interactive Applications
A cloud-based interactive application (CIA) is an application running in the cloud with stringent interactivity requirements, such as remote desktop and cloud gaming. These services have experienced a surge in usage, primarily due to the adoption of new remote work practices during the pandemic and the emergence of entertainment schemes similar to cloud gaming platforms. Evaluating the quality of experience (QoE) in these applications requires specific metrics, including interactivity time, responsiveness, and the assessment of video- and audio-quality degradation. 
  • 152
  • 08 Mar 2024
Topic Review
Machine Vision and Industry 4.0 to Industry 5.0
With the emergence of artificial intelligence (AI) and its integration into various intelligent robotics, the Fourth Industrial Revolution, also known as Industry 4.0, managed to trigger changes. Its need has been emphasized in multiple situations, such as that of the COVID-19 pandemic, entering every area of human life, with Industry 4.0 being more and more involved in production processes. Industry 4.0 is an emerging concept that is multidisciplinary and complex. Leveraging not just one, but a patchwork of technologies that can work individually as well as in combination, Industry 4.0 strives to achieve a more general digital transformation with high expectations both in the production of products and services in real-time. This effort is mainly based on advanced computers with fast processors able to store, manage, process, and analyze a large amount of data, spending less time and resources than ever before.
  • 156
  • 08 Mar 2024
Topic Review
Advanced Persistent Thread and Common Systems Behavioral Sources
The rapid proliferation of Internet of Things (IoT) networks in Colombia and various global regions has unquestionably resulted in a significant increase in cyberattacks. This rapid expansion of interconnected devices carries significant implications for individuals, organizations, and governing entities.
  • 343
  • 08 Mar 2024
Topic Review
Modelling and Measuring Trust in Human–Robot Collaboration
Human–Robot Collaboration (HRC) has emerged as a critical area in the engineering and social sciences domain. In any kind of collaboration, including HRC, trust has been identified as a significant factor that can either motivate or hinder cooperation, especially in scenarios characterized by incomplete or uncertain information.
  • 104
  • 08 Mar 2024
Topic Review
Advancements and Challenges in Handwritten Text Recognition
Handwritten Text Recognition (HTR) involves automatically transforming a source’s handwritten text within a digital image into its machine text representation.
  • 444
  • 07 Mar 2024
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