Electrochemical Capacitors: Challenges and Opportunities for Real-World Applications

2008 ◽  
Vol 17 (1) ◽  
pp. 53-57 ◽  
Author(s):  
John R. Miller ◽  
Andrew Burke
Keyword(s):  
Real World ◽  
Electrochemical Capacitors ◽  
Real World Applications ◽  
Challenges And Opportunities

SpeeChin

2021 ◽  
Vol 5 (4) ◽  
pp. 1-23
Author(s):  
Ruidong Zhang ◽  
Mingyang Chen ◽  
Benjamin Steeper ◽  
Yaxuan Li ◽  
Zihan Yan ◽  
...  
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Real World ◽  
User Study ◽  
Imaging System ◽  
User Studies ◽  
Ir Imaging ◽  
Real World Applications ◽  
Challenges And Opportunities ◽  
Silent Speech

This paper presents SpeeChin, a smart necklace that can recognize 54 English and 44 Chinese silent speech commands. A customized infrared (IR) imaging system is mounted on a necklace to capture images of the neck and face from under the chin. These images are first pre-processed and then deep learned by an end-to-end deep convolutional-recurrent-neural-network (CRNN) model to infer different silent speech commands. A user study with 20 participants (10 participants for each language) showed that SpeeChin could recognize 54 English and 44 Chinese silent speech commands with average cross-session accuracies of 90.5% and 91.6%, respectively. To further investigate the potential of SpeeChin in recognizing other silent speech commands, we conducted another study with 10 participants distinguishing between 72 one-syllable nonwords. Based on the results from the user studies, we further discuss the challenges and opportunities of deploying SpeeChin in real-world applications.

NeckFace

2021 ◽  
Vol 5 (2) ◽  
pp. 1-31
Author(s):  
Tuochao Chen ◽  
Yaxuan Li ◽  
Songyun Tao ◽  
Hyunchul Lim ◽  
Mose Sakashita ◽  
...  
Keyword(s):  
Deep Learning ◽  
Facial Expressions ◽  
Real World ◽  
User Study ◽  
Form Factors ◽  
Physical Activities ◽  
Sensing Technology ◽  
Study Results ◽  
Real World Applications ◽  
Challenges And Opportunities

Facial expressions are highly informative for computers to understand and interpret a person's mental and physical activities. However, continuously tracking facial expressions, especially when the user is in motion, is challenging. This paper presents NeckFace, a wearable sensing technology that can continuously track the full facial expressions using a neck-piece embedded with infrared (IR) cameras. A customized deep learning pipeline called NeckNet based on Resnet34 is developed to learn the captured infrared (IR) images of the chin and face and output 52 parameters representing the facial expressions. We demonstrated NeckFace on two common neck-mounted form factors: a necklace and a neckband (e.g., neck-mounted headphones), which was evaluated in a user study with 13 participants. The study results showed that NeckFace worked well when the participants were sitting, walking, or after remounting the device. We discuss the challenges and opportunities of using NeckFace in real-world applications.

scholarly journals Electronic Phenomena of Transition Metal Oxides

Crystals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 256
Author(s):  
Christian Rodenbücher ◽  
Kristof Szot
Keyword(s):  
Solid State ◽  
Transition Metal ◽  
Metal Oxides ◽  
Real World ◽  
Transition Metal Oxides ◽  
Major Research ◽  
Research Fields ◽  
Real World Applications

Transition metal oxides with ABO3 or BO2 structures have become one of the major research fields in solid state science, as they exhibit an impressive variety of unusual and exotic phenomena with potential for their exploitation in real-world applications [...]

scholarly journals Applications of Distributed-Order Fractional Operators: A Review

Entropy ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. 110
Author(s):  
Wei Ding ◽  
Sansit Patnaik ◽  
Sai Sidhardh ◽  
Fabio Semperlotti
Keyword(s):  
Fractional Calculus ◽  
Real World ◽  
Transport Processes ◽  
Model Systems ◽  
Variable Order ◽  
Fractional Operators ◽  
Research Activity ◽  
Road Map ◽  
Real World Applications ◽  
Distributed Order

Distributed-order fractional calculus (DOFC) is a rapidly emerging branch of the broader area of fractional calculus that has important and far-reaching applications for the modeling of complex systems. DOFC generalizes the intrinsic multiscale nature of constant and variable-order fractional operators opening significant opportunities to model systems whose behavior stems from the complex interplay and superposition of nonlocal and memory effects occurring over a multitude of scales. In recent years, a significant amount of studies focusing on mathematical aspects and real-world applications of DOFC have been produced. However, a systematic review of the available literature and of the state-of-the-art of DOFC as it pertains, specifically, to real-world applications is still lacking. This review article is intended to provide the reader a road map to understand the early development of DOFC and the progressive evolution and application to the modeling of complex real-world problems. The review starts by offering a brief introduction to the mathematics of DOFC, including analytical and numerical methods, and it continues providing an extensive overview of the applications of DOFC to fields like viscoelasticity, transport processes, and control theory that have seen most of the research activity to date.

scholarly journals Mobile Manipulation Hackathon: Moving into Real World Applications

2021 ◽  
pp. 2-14
Author(s):  
Maximo A. Roa ◽  
Mehmet R. Dogar ◽  
Jordi Pages ◽  
Carlos Vivas ◽  
Antonio Morales ◽  
...  
Keyword(s):  
Real World ◽  
Mobile Manipulation ◽  
Real World Applications
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