AIMC Topic: Pressure

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Application of unsupervised and supervised learning to a material attribute database of tablets produced at two different granulation scales.

International journal of pharmaceutics
The purpose of this study is to demonstrate the usefulness of machine learning (ML) for analyzing a material attribute database from tablets produced at different granulation scales. High shear wet granulators (scale 30 g and 1000 g) were used and da...

An overview of the implementation of SeDeM and SSCD in various formulation developments.

International journal of pharmaceutics
The Sediment Delivery Model explains experimental analysis and quantitative assessment of the powdered substance characterizing parameters, which offer pertinent data about the material's appropriateness for direct compression (DC) of tablet, which i...

Deep Neural Network for the Detections of Fall and Physical Activities Using Foot Pressures and Inertial Sensing.

Sensors (Basel, Switzerland)
Fall detection and physical activity (PA) classification are important health maintenance issues for the elderly and people with mobility dysfunctions. The literature review showed that most studies concerning fall detection and PA classification add...

Design and Implementation of a Smart Insole System to Measure Plantar Pressure and Temperature.

Sensors (Basel, Switzerland)
An intelligent insole system may monitor the individual's foot pressure and temperature in real-time from the comfort of their home, which can help capture foot problems in their earliest stages. Constant monitoring for foot complications is essentia...

AutoAtlas: Neural Network for 3D Unsupervised Partitioning and Representation Learning.

IEEE journal of biomedical and health informatics
We present a novel neural network architecture called AutoAtlas for fully unsupervised partitioning and representation learning of 3D brain Magnetic Resonance Imaging (MRI) volumes. AutoAtlas consists of two neural network components: one neural netw...

Skeleton-Based Spatio-Temporal U-Network for 3D Human Pose Estimation in Video.

Sensors (Basel, Switzerland)
Despite the great progress in 3D pose estimation from videos, there is still a lack of effective means to extract spatio-temporal features of different granularity from complex dynamic skeleton sequences. To tackle this problem, we propose a novel, s...

Generative machine learning algorithm for lattice structures with superior mechanical properties.

Materials horizons
Lattice structures are typically made up of a crisscross pattern of beam elements, allowing engineers to distribute material in a more structurally effective way. However, a main challenge in the design of lattice structures is a trade-off between th...

Using multiple linear regression and BP neural network to predict critical meteorological conditions of expressway bridge pavement icing.

PloS one
Icy bridge deck in winter has tremendous consequences for expressway traffic safety, which is closely related to the bridge pavement temperature. In this paper, the critical meteorological conditions of icy bridge deck were predicted by multiple line...

Deep learning approach to estimate foot pressure distribution in walking with application for a cost-effective insole system.

Journal of neuroengineering and rehabilitation
BACKGROUND: Foot pressure distribution can be used as a quantitative parameter for evaluating anatomical deformity of the foot and for diagnosing and treating pathological gait, falling, and pressure sores in diabetes. The objective of this study was...

Evaluation of Deep Neural Network Compression Methods for Edge Devices Using Weighted Score-Based Ranking Scheme.

Sensors (Basel, Switzerland)
The demand for object detection capability in edge computing systems has surged. As such, the need for lightweight Convolutional Neural Network (CNN)-based object detection models has become a focal point. Current models are large in memory and deplo...