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Topic Review
Agrivoltaic Systems Design
An agrivoltaic system is a complex system, being, at least, a spatial, an energy and an agronomic system. Its design and assessment must adhere to requirements set depending on the project’s needs in order to meet desired performance quality objectives. Different dimensions of performance need to be taken into account.
  • 1.5K
  • 18 Nov 2021
Topic Review
Agrivoltaics in Alberta Canada
As Alberta increases conventional solar power generation, land-use conflicts with agriculture increase. A solution that enables low-carbon electricity generation and continued (in some cases, increased) agricultural output is the co-locating of solar photovoltaics (PV) and agriculture: agrivoltaics.
  • 731
  • 10 Jan 2023
Topic Review
AH-IV
The AH-IV was a Czechoslovak-designed tankette used by Romania, Sweden and Iran during World War II. The Romanian vehicles saw action on the Eastern Front from Operation Barbarossa to the Vienna Offensive. Twenty vehicles were sold to Ethiopia after the war who used them until the Eighties. Romania also created a prototype, called R-1-a.
  • 343
  • 29 Sep 2022
Topic Review
AI and Neural Network Algorithms
Al increases the potential of Micro-Electro-Mechanical System biosensors and opens up new opportunities for automation, consumer electronics, industrial manufacturing, defense, medical equipment, etc. Micro-Electro-Mechanical System microcantilever biosensors are currently making their way into the daily lives and playing a significant role in the advancement of social technology. Micro-Electro-Mechanical System biosensors with microcantilever structures have a num- ber of benefits over conventional biosensors, including small size, high sensitivity, mass production, simple arraying, integration, etc. These advantages have made them one of the development avenues for high-sensitivity sensors. The next generation of sensors will exhibit an intelligent development trajectory and aid people in interacting with other objects in a variety of scenario applications as a result of the active development of artificial intelligence (AI) and neural networks. A neural algorithm application in Micro-Electro-Mechanical System microcantilever biosensors is anticipated through the associated application of the principal com-ponent analysis approach. Researchers investigation has more scientific study value, because there are currently no favorable reports on the market regarding the use of AI with Micro-Electro-Mechanical System microcantilever sensors.
  • 414
  • 13 Sep 2022
Topic Review
AI Applications for Virtual Sensing of Underground Utilities
Accurately identifying the location and depth of buried utility assets became a considerable challenge in the construction industry, for which accidental strikes can cause important economic losses and safety concerns. While the collection of as-built utility locations is becoming more accurate, there still exists an important need to be capable of accurately detecting buried utilities in order to eliminate risks associated with digging. With advances in artificial intelligence (AI), an opportunity arose in conducting virtual sensing of buried utilities by combining robotics (e.g., drones), knowledge, and logic.
  • 479
  • 18 May 2023
Topic Review
AI in Improving the Sustainability of Agricultural Crops
The rapid growth of the world’s population has put significant pressure on agriculture to meet the increasing demand for food. In this context, agriculture faces multiple challenges, one of which is weed management. While herbicides have traditionally been used to control weed growth, their excessive and random use can lead to environmental pollution and herbicide resistance. To address these challenges, in the agricultural industry, deep learning models have become a possible tool for decision-making by using massive amounts of information collected from smart farm sensors.
  • 303
  • 26 Apr 2023
Topic Review
AI in the Field of Surfactants
Artificial intelligence (AI) is increasingly being used in the field of surfactants to improve the efficiency, effectiveness, and sustainability of surfactant production and applications. One of the main applications of AI in surfactants is in the design and development of new surfactant molecules. By using machine learning algorithms and computational modeling, researchers can predict the properties and behavior of new surfactants before they are synthesized, reducing the time and cost required for research and development. AI is also being used to optimize surfactant production processes, by analyzing large amounts of data generated during production and identifying areas for improvement. For example, AI can be used to optimize surfactant synthesis conditions, such as temperature and pressure, to improve yield and reduce waste. In addition, AI is being used to develop predictive models for surfactant performance in specific applications, such as in the production of emulsions, foams, and coatings. By understanding the relationship between surfactant properties and application performance, researchers can design more effective and sustainable surfactant formulations.
  • 850
  • 24 Mar 2023
Topic Review
AI Methods for Intelligent Sensing
Smart sensors complement and enhance the capabilities of human beings and have been widely embraced in numerous application areas. Artificial intelligence (AI) has made astounding growth in domains of natural language processing, machine learning (ML), and computer vision. The methods based on AI enable a computer to learn and monitor activities by sensing the source of information in a real-time environment. The combination of these two technologies provides a promising solution in intelligent sensing. 
  • 698
  • 10 Jun 2022
Topic Review
AI Mk. VIII Radar
Radar, Airborne Interception, Mark VIII, or AI Mk. VIII for short, was the first operational microwave-frequency air-to-air radar. It was used by Royal Air Force night fighters from late 1941 until the end of World War II. The basic concept, using a moving parabolic antenna to search for targets and track them accurately, remained in use by most airborne radars well into the 1980s. Low-level development began in 1939 but was greatly sped after the introduction of the cavity magnetron in early 1940. This operated at 9.1 cm wavelength (3 GHz), much shorter than the 1.5 m wavelength of the earlier AI Mk. IV. Shorter wavelengths allowed it to use smaller and much more directional antennas. Mk. IV was blinded by the reflections off the ground from its wide broadcast pattern, which made it impossible to see targets flying at low altitudes. Mk. VIII could avoid this by keeping the antenna pointed upward, allowing it to see any aircraft at or above the horizon. The design was just beginning to mature in late 1941 when the Luftwaffe began low-level attacks. A prototype version, the Mk. VII, entered service on the Bristol Beaufighter in November 1941. A small number of these were sent to units across the UK to provide coverage at low altitudes while Mk. IV equipped aircraft operated at higher altitudes. After a small run of the improved Mk. VIIIA, the definitive Mk. VIII arrived in early 1942, offering higher power as well as a host of electronic and packaging upgrades. It arrived just as production rates of the De Havilland Mosquito began to improve, quickly displacing the Beaufighter units in RAF squadrons. Mk. VIII equipped Mosquitoes would be the premier night fighter from 1943 through the rest of the war. The Mk. VIII spawned a number of variants, notably the AI Mk. IX which included a lock-on feature to ease interceptions. A series of events, including a deadly friendly fire incident, so greatly delayed the Mk. IX that it never entered service. During the late-war period, many UK aircraft adopted the US SCR-720 under the name AI Mk. X. This worked on the same general principles as the Mk. VIII, but used a different display system that offered several advantages. Development of the basic system continued, and the Mk. IX would eventually briefly re-appear in greatly advanced form as the AI.17 during the 1950s.
  • 1.1K
  • 16 Nov 2022
Topic Review
AI Public Datasets for Railway Applications
The aim of this entry is to review existing publicly available and open artificial intelligence (AI) oriented datasets in different domains and subdomains of the railway sector. The contribution of this paper is an overview of AI-oriented railway data published under Creative Commons (CC) or any other copyright type that entails public availability and freedom of use. These data are of great value for open research and publications related to the application of AI in the railway sector.
  • 1.9K
  • 09 Oct 2021
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