A Combination Model of Shifting Joint Angle Changes With 3D-Deep Convolutional Neural Network to Recognize Human Activity.

Research in the field of human activity recognition is very interesting due to its potential for various applications such as in the field of medical rehabilitation. The need to advance its development has become increasingly necessary to enable efficient detection and response to a wide range of movements. Current recognition methods rely on calculating changes in joint distance to classify activity patterns.

Efficient photocatalytic bactericidal performance of green-synthesised TiO/reduced graphene oxide using banana peel extracts.

In this study, the fabrication of titanium dioxide/reduced graphene oxide (TiO/rGO) utilising banana peel extracts ( L.) as a reducing agent for the photoinactivation of () and () was explored. The GO synthesis was conducted using a modified Tour method, whereas the production of rGO involved banana peel extracts through a reflux method.

Diagnostic Accuracy of Lymph Nodes Fine Needle Aspiration Biopsy Based on The Sydney System for Reporting Lymph Node Cytology.

Objective: To evaluate the diagnostic accuracy and malignancy risk of The Sydney System Reporting for Lymph Nodes Cytology.

Material And Methods: This study utilized secondary data from 156 cases to conduct a retrospective analysis of a diagnostic test method. During 2019-2021, data were collected at Dr.

Current Status and Complexity of Three Species in Pepper Plants in Lowlands and Highlands in Java Island, Indonesia.

Three primary species from the genus, (PepYLCIV), (TYLCKaV), and (ToLCNDV), are suspected of spreading throughout pepper production centers, and plants are infected by a single species or a combination of two or three species. This study was conducted to provide complete information about the symptoms, incidence and severity, whitefly biotypes, as well as the dominance status of the three species in pepper-producing areas in Java. A DNA analysis was carried out on leaf samples to identify species and biotypes of collected from 18 areas (16 districts) in lowlands (<400 m asl) and highlands (>700 m asl).

Deep-Stacked Convolutional Neural Networks for Brain Abnormality Classification Based on MRI Images.

An automated diagnosis system is crucial for helping radiologists identify brain abnormalities efficiently. The convolutional neural network (CNN) algorithm of deep learning has the advantage of automated feature extraction beneficial for an automated diagnosis system. However, several challenges in the CNN-based classifiers of medical images, such as a lack of labeled data and class imbalance problems, can significantly hinder the performance.