List of IEEE publications

ResoluteAI integrates IEEE Metadata into its Foundation Scientific Research Platform

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Wednesday, September 28, 2022
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ResoluteAI, the research platform for science, announced today the addition of metadata from IEEE peer reviewed content to its Foundation service .

Key Points: 
  • ResoluteAI, the research platform for science, announced today the addition of metadata from IEEE peer reviewed content to its Foundation service .
  • This represents approximately 30% of the worlds literature in the electrical and electronics engineering and computer science fields, making IEEE an invaluable resource for scientific research across multiple industries.
  • We believe access to this information for our Foundation customers will be of tremendous value, said Steve Goldstein, CEO of ResoluteAI.
  • IEEE peer-reviewed journals and conference proceedings are now discoverable within the ResoluteAI platform , enabling IEEE subscribers to link through to access the full-text at the IEEE Xplore digital library.

DIII-D National Fusion Facility Adds Capability to Rapidly Test Key Fusion Science

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Tuesday, July 26, 2022
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Called a Toroidal Field Reversing Switch (TFRS), this quick-change function is unique to DIII-D and illustrates the facilitys value and flexibility for fusion science.

Key Points: 
  • Called a Toroidal Field Reversing Switch (TFRS), this quick-change function is unique to DIII-D and illustrates the facilitys value and flexibility for fusion science.
  • DIII-D is the largest magnetic fusion research user facility in the United States and is operated by General Atomics for the U.S. Department of Energy Office of Science.
  • The heart of the facility is a tokamak that uses powerful electromagnets to produce a toroidal (doughnut-shaped) magnetic bottle for confining a fusion plasma.
  • DIII-D is the largest magnetic fusion research facility in the U.S. and has been the site of numerous pioneering contributions to the development of fusion energy science.

Gwangju Institute of Science and Technology Researchers Improve the Scanning Capability of Magnetic Particle Imaging Systems Used for Medical Imaging

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Friday, July 22, 2022
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GWANGJU, South Korea, July 22, 2022 /PRNewswire/ -- Magnetic particle imaging (MPI) is an emerging imaging modality that is based on the detection of superparamagnetic iron oxide nanoparticles that have been injected into the body. The magnetic particles act like tracers and are detected in response to a moving magnetic field free point (FFP), which changes their magnetic direction. As these particles do not naturally exist in the human body, it makes MPI highly sensitive and free from background noise. MPI could potentially transform medical imaging. However, currently available commercial scanners often compromise between coverage volume and imaging resolution.

Key Points: 
  • The magnetic particles act like tracers and are detected in response to a moving magnetic field free point (FFP), which changes their magnetic direction.
  • As these particles do not naturally exist in the human body, it makes MPI highly sensitive and free from background noise.
  • In a new study published online on 29 April 2022 in IEEE Transactions on Industrial Electronics , researchers from Gwangju Institute of Science and Technology (GIST) in South Korea have now addressed this issue.
  • Authors: Tuan-Anh Le*, Minh Phu Bui, and Jungwon Yoon*
    Affiliations: Gwangju Institute of Science and Technology, the Republic of Korea

Are Future Humans Doomed To Be Replaced By Artificial Intelligence?

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Tuesday, June 21, 2022
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Are we just wetware, natural computers doomed to obsolescence by tomorrow's ultra-powerful artificial intelligence?

Key Points: 
  • Are we just wetware, natural computers doomed to obsolescence by tomorrow's ultra-powerful artificial intelligence?
  • Non-Computable You explains how humans are unique and why Artificial Intelligence will never replicate you.
  • Marks, II newest book, Non-Computable You: What You Do That Artificial Intelligence Never Will (Discovery Institute Press 2022) explains how humans are unique and why artificial intelligence will never replicate humans.
  • He is coauthor of the books Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks (MIT Press) and Introduction to Evolutionary Informatics (World Scientific).

Chung-Ang University Scientists Develop New Framework for Home Energy Management Systems

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Wednesday, June 8, 2022
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Fortunately, most decisions and actions needed to optimize our energy use can be delegated to home energy management systems (HEMSs), which efficiently manage the energy consumption of home appliances by scheduling when washing machines should start and strategically turning air conditioners (ACs) on and off.

Key Points: 
  • Fortunately, most decisions and actions needed to optimize our energy use can be delegated to home energy management systems (HEMSs), which efficiently manage the energy consumption of home appliances by scheduling when washing machines should start and strategically turning air conditioners (ACs) on and off.
  • Usually, hand-crafted models that use abstract equations to represent appliances and distributed energy resources are used to program HEMSs.
  • Dr. Choi envisions a more comprehensive version of this framework that also considers electric cars and energy trading between households.
  • We certainly have our fingers crossed for the secure optimization of energy consumption in future.

SphereGAN: Novel and Improved Neural Network Developed by Researchers from Chung-Ang University

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Tuesday, June 7, 2022
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SEOUL, South Korea, June 7, 2022 /PRNewswire/ -- Deep neural networks are popularly used for object recognition, detection, and segmentation across different avenues. Of these, generative adversarial networks (GANs) are a superior class of neural networks whose performance exceeds that of conventional neural networks. They are meant to minimize the inconsistencies between real and fake data, and have proven successful for image detection, medical imaging, video prediction, 3D image reconstruction, and more.

Key Points: 
  • Of these, generative adversarial networks (GANs) are a superior class of neural networks whose performance exceeds that of conventional neural networks.
  • Training conventional GANs is difficult and involves very high computational costs, making them unreliable for complex computer vision problems.
  • They found that by incorporating Riemannian geometry in this model, SphereGAN demonstrated a considerably improved performance as compared to conventional GANs.
  • In the coming years, these and more advanced image generation applications will be possible with a robust model like SphereGAN".

THINK Surgical and Concordia University Receive NSERC Alliance and MEDTEQ+ 3-Year Grant to Develop Artificial Intelligence for Robotic Surgery

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Thursday, April 28, 2022
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The focus of this project will be on developing advanced image registration algorithms using machine learning and Artificial Intelligence (AI).

Key Points: 
  • The focus of this project will be on developing advanced image registration algorithms using machine learning and Artificial Intelligence (AI).
  • The results may then be incorporated in THINK Surgical's next-generation robotic solutions for orthopedic surgery.
  • THINK Surgical, Inc., a privately held U.S.-based medical device and technology company, develops, manufactures, and markets active robotics for orthopedic surgery.
  • THINK Surgical and TSolution One are registered trademarks of THINK Surgical, Inc. 2022 THINK Surgical, Inc. All rights reserved.

New Algorithm by Pusan National University Scientists Can Repair Missing Data in Event Logs with Superior Accuracy

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Wednesday, December 15, 2021
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However, the quality of the optimization process is only as good as the data stored and event logs with missing events lead to poor analysis and data models.

Key Points: 
  • However, the quality of the optimization process is only as good as the data stored and event logs with missing events lead to poor analysis and data models.
  • In event logs, events have attributes that are linked to other events in "single event" or "multiple event" relationships.
  • These sequences can be compared with an event log without missing data to restore the missing event attributes.
  • These imputation methods were applied simultaneously by a bagging recurrent event imputation (BREI) algorithm, uses bootstrap sampling and recurrent event imputation (REI) to repair the event log.

Gwangju Institute of Science and Technology Scientists Showcase the Potential of Demand Response in Reducing CO2 Emissions

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Monday, November 29, 2021
Electricity, GIST, Carbon, Gwangju Institute of Science and Technology, Behavior, Environment, Water, Artificial intelligence, List of IEEE publications, CO2, Efficiency, Medical device, Renewable energy

Now, scientists from the Gwangju Institute of Science and Technology propose an AI-based approach to estimate the DR potential per household based on real-world user behavior, demonstrating that DR programs arebeneficial for customers, suppliers, and the environment.

Key Points: 
  • Now, scientists from the Gwangju Institute of Science and Technology propose an AI-based approach to estimate the DR potential per household based on real-world user behavior, demonstrating that DR programs arebeneficial for customers, suppliers, and the environment.
  • This mismatch between power supply and demand and the inefficient operation of power stations lead to higher carbon dioxide (CO2) emissions.
  • Fortunately, communication technologies have unlocked a clever strategy to address this problem: demand response (DR) programs.
  • The team also calculated the potential contributions of DR programs in terms of reduction in CO2 emissions and the cost of managing coal-powered generators.