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Topic Review
Deep Reinforcement Learning for Resilient Power Systems
Resilience, characterized by the ability to withstand, absorb, and quickly recover from natural disasters and human-induced disruptions, has become paramount in ensuring the stability and dependability of critical infrastructure. The linkage between Deep Reinforcement Learning (DRL) and power system resilience is forged through a systematic classification of DRL applications into five pivotal dimensions: dynamic response, recovery and restoration, energy management and control, communications and cybersecurity, and resilience planning and metrics development. This structured categorization facilitates a methodical exploration of how DRL methodologies can effectively tackle critical challenges within the domain of power and energy system resilience. 
  • 306
  • 08 Dec 2023
Topic Review
Deep Reinforcement Learning-Based BEMS per Building Type
The deep reinforcement learning (DRL)-based building energy management systems (BEMS) field has grown rapidly in the last five years, with numerous creative ideas and innovations for integrating advanced data-driven control methods in the development of fully enabled smart buildings. Although residential buildings are by far the largest energy consumers, other building types, such as offices and educational buildings, are also being investigated. It would be useful to realize the different directions of research, types of applications, and innovative ideas being implemented for each building type. In particular, it is crucial from a data-centric perspective, as being able to train and use data-driven methods requires large amounts of data, particularly when deploying such systems in the real world.
  • 614
  • 28 Nov 2022
Topic Review
Deep Sea Mining
As land-based mining industries face increasing complexities, e.g., diminishing return on investments, environmental degradation, and geopolitical tensions, governments are searching for alternatives. Following decades of anticipation, technological innovation, and exploration, deep seabed mining (DSM) in the oceans has, according to the mining industry and other proponents, moved closer to implementation. The DSM industry is currently waiting for international regulations that will guide future exploitation. 
  • 622
  • 24 May 2021
Topic Review
Deep Ultraviolet Photodetectors Based on Aluminum Nitride Material
Photodetectors are important photoelectric devices that realize sensing detection through photoelectric signal transformation and have been widely used in flame sensing, conversion communication, environmental monitoring, video imaging, night vision imaging, military tracking, medical detection, and other fields. Ultraviolet with a wavelength less than 280 nm is defined as a deep ultraviolet band that will be absorbed by ozone in the atmosphere before entering the earth. Almost no signal background exists in this band on the earth, which is also called a solar-blind band. The application fields represented by ultraviolet short-range secure communication, shipborne guidance, ozone layer monitoring, and water pollution treatment need the continuous development, maturity, transformation, and application of deep ultraviolet (DUV) detection technology. Therefore, further research and development of DUV detection technology have attracted the extensive attention of researchers in relevant fields, whether in daily life or in the construction of modern national defense.
  • 309
  • 27 Jun 2023
Topic Review
Deep-Learning-Based Channel Estimation Methods
With the rapid development of wireless communication technology, intelligent communication has become one of the mainstream research directions after the fifth generation (5G). In particular, deep learning has emerged as a significant artificial intelligence technology widely applied in the physical layer of wireless communication for achieving intelligent receiving processing. Channel estimation, a crucial component of physical layer communication, is essential for further information recovery. 
  • 652
  • 25 Dec 2023
Topic Review
Deep-Learning-Based Cooperative Spectrum Sensing
With the rapid development in wireless communication and 5G networks, the rapid growth in mobile users has been accompanied by an increasing demand for the electromagnetic spectrum. The birth of cognitive radio and its spectrum-sensing technology provides hope for solving the problem of low utilization of the wireless spectrum.
  • 329
  • 07 Nov 2023
Topic Review
Deep-Sea Smart Composites
To solve the global shortage of land and offshore resources, the development of deep-sea resources has become a popular topic. Deep-sea composites are widely used materials in abyssal resources extraction, and corresponding marine exploration vehicles and monitoring devices for deep-sea engineering. In the process of deep-sea resources extraction by DUVs and marine engineering, cracks and fractures or other types of damage can occur due to the fatigue and aging of materials in harsh abyssal environments. With the expansion of cracks and fractures, the composite material splits could lead to the failure of composite structures. Traditional damage detection methods are limited by outdated equipment, low intelligence and poor timeliness, making it difficult to directly detect defects. To avoid irreversible disasters caused by fatigue and aging, and to reduce manpower and financial costs required for periodic inspection, it is necessary to adopt deep-sea smart composites to meet the existing needs.
  • 510
  • 29 Nov 2022
Topic Review
Defect Detection in Clothing
Blind people often encounter challenges in managing their clothing, specifically in identifying defects such as stains or holes. With the progress of the computer vision field, it is crucial to minimize these limitations as much as possible to assist blind people with selecting appropriate clothing. 
  • 444
  • 30 May 2023
Topic Review
Defect Synthesis for Automated Visual Inspection
Defect inspection, which detects defects in real-time and classifies defect types, is one of the key technologies required for smart factory implementation. Defect detection on steel surfaces is an important task to ensure the quality of industrial production. To build an automated visual inspection (AVI) and achieve smartization of steel manufacturing, detecting defects in products in real-time and accurately diagnosing the quality of products are essential elements. 
  • 690
  • 23 Sep 2022
Topic Review
Defect Types and Mechanism of Wind Turbine Blades
There are two main reasons for the damage to wind turbine blades. On the one hand, the wind turbine is in a harsh external environment, and the damage faults are directly caused by external factors, such as strong wind, rain or snow, salt fog, lightning strike, freezing, sandstorm, insects, etc. The other is the invisible defects caused by process problems in the technology of man-made manufacturing. These invisible defects are subject to repeated high loads and harsh external environments during the installation and operation of the wind turbine. The gradual expansion of invisible defects can lead to damage. Due to the complexity of the blade material and structure, each damage type may be caused by a combination of causes. Different defects in the production process and different operating conditions will cause different damage types.
  • 5.0K
  • 28 Sep 2022
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