Results 241 to 250 of about 346,958 (424)
Advancements in Machine Learning for Microrobotics in Biomedicine
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi+6 more
wiley +1 more source
Indigenous Australians and gambling [PDF]
Summary: This paper synthesises information published about Indigenous Australian gambling, and summarises issues and implications for key stakeholders. It is relevant for raising awareness and promoting community education about gambling for Indigenous ...
Helen Breen, Nerilee Hing
core
An virtual reality augmented‐reality‐ and motion‐capture‐assisted surface remanufacturing system is presented. Operators can interactively reconstruct the virtual model using the designed motion‐captured pointer directly on the physical workpiece surface. Operators can intuitively and interactively manipulate the system to accomplish tasks ranging from
Guoliang Liu, Wenlei Sun, Pinwen Li
wiley +1 more source
Clinical Significance of Psychiatric Comorbidities Among Outpatients With Gambling Disorder in Japan: A 12-Month Follow-Up Study. [PDF]
Yamada R+3 more
europepmc +1 more source
Algorithmically Enhanced Wearable Multimodal Emotion Sensor
This study presents a fully printed, organic wearable sensor for multimodal emotion sensing by noninvasively monitoring physiological indicators like physiological pulse, breathing patterns, and voice signatures. Using LSTM networks and Q‐learning, the system achieves over 91% accuracy, offering a pathway to understanding complex emotions and enhancing
Anand Babu+4 more
wiley +1 more source
The theory of planned behaviour (TPB) and the concept of anticipatory negative emotions have attracted considerable research attention in the formulation of effective preventive interventions.
Derevensky, Jeffrey L+3 more
core
Deep Learning Methods in Soft Robotics: Architectures and Applications
Soft robotics has seen intense research over the past two decades and offers a promising approach for future robotic applications. However, standard industrial methods may be challenging to apply to soft robots. Recent advances in deep learning provide powerful tools to analyze and design complex soft machines that can operate in unstructured ...
Tomáš Čakurda+3 more
wiley +1 more source