Wyniki wyszukiwania - Biblioteka Nauki

Ten serwis zostanie wyłączony 2025-02-11.

Nowa wersja platformy, zawierająca wyłącznie zasoby pełnotekstowe, jest już dostępna.
Przejdź na https://bibliotekanauki.pl

Ograniczanie wyników

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

A two-step fall detection algorithm combining threshold-based method and convolutional neural network

100%

Xu T. , Se H. , Liu J.

2021

tom Vol. 28, nr 1

23--40

Falls are one of the leading causes of disability and premature death among the elderly. Technical solutions designed to automatically detect a fall event may mitigate fall-related health consequences by immediate medical assistance. This paper presents a wearable device called TTXFD based on MPU6050 which can collect triaxial acceleration signals. We have also designed a two-step fall detection algorithm that fuses threshold-based method (TBM) and machine learning (ML). The TTXFD exploits the TBM stage with low computational complexity to pick out and transmit suspected fall data (triaxial acceleration data). The ML stage of the two-step algorithm is implemented on a server which encodes the data into an image and exploits a fall detection algorithm based on convolutional neural network to identify a fall on the basis of the image. The experimental results show that the proposed algorithm achieves high sensitivity (97.83%), specificity (96.64%) and accuracy (97.02%) on the open dataset. In conclusion, this paper proposes a reliable solution for fall detection, which combines the advantages of threshold-based method and machine learning technology to reduce power consumption and improve classification ability.

Stability analysis of open-pit bench slope under repeated heavy vehicle loading based on stress-corrosion model

75%

Zhao L. , Li Z. , Liu Y. , Xu Y. , Wasantha P. L. P. , Zheng X. , Xu T.

Archives of Mining Sciences

2024

tom Vol. 69, no. 2

211--230

In the present study, we address an important and increasingly relevant topic in mining safety and efficiency, namely the stability of open-pit bench slopes subjected to daily heavy truck cyclic loading. Specifically, we focus on the stability of Zhahanur open-pit slope (Inner Mongolia region, China) and investigate the potential role of daily heavy truck cyclic loading in bench slope instability. To this end, we incorporate a stress corrosion model into the particle flow code to develop a time-dependent deformation model of the rock. With the established model, we quantitatively analyse the effect of heavy truck cyclic loading on the bench slope stability. Our results support the hypothesis that daily heavy truck loading can cause gradual downward deformation of a rock mass, leading to slope instability. To validate our numerical modelling results, we compare and analyse them with in situ monitoring data. Our study demonstrates the significant impact of daily heavy vehicles on bench slope stability in open-pit mines and provides a practical tool for assessing the long-term stability of open-pit bench slopes and optimising mining operations.

A comparative study of face milling of D2 steel using AL2O3 based nanofluid minimum quantity lubrication and minimum quantity lubrication

75%

Ahsan Ul Haq M. , Khan A. M. , Gong L. , Xu T. , Meng L. , Hussain S.

Advances in Science and Technology. Research Journal

2018

tom Vol. 12, no 1

99--105

This study aims to investigate the effects of process parameters: feed, depth of cut and flow rate, on the temperature during face milling of the D2 tool steel under two different lubricant conditions, Minimum Quantity Lubrication (MQL) and Nano fluid Minimum Quantity Lubrication (NFMQL). Deionized water with the flow rate range 200–400 ml/h was used in MQL. 2% by weight concentration of Al2O3 nano particles with deionized water as a base fluid used as NFMQL with the same flow rate. Response surface methodology RSM central composite design CCD was used to design experiment run, modeling and analysis. ANOVA was used for the adequacy and validation of the system. The comparison shows that NFMQL condition reduced temperature more efficiently during machining.