Real-Time Dynamic Intelligent Image Recognition and Tracking System for Rockfall Disasters.

Taiwan, frequently affected by extreme weather causing phenomena such as earthquakes and typhoons, faces a high incidence of rockfall disasters due to its largely mountainous terrain. These disasters have led to numerous casualties, government compensation cases, and significant transportation safety impacts. According to the National Science and Technology Center for Disaster Reduction records from 2010 to 2022, 421 out of 866 soil and rock disasters occurred in eastern Taiwan, causing traffic disruptions due to rockfalls.

Research on nano H/O bubble generating mechanism and characteristics.

In this research, electrolysis water is used to produce hydrogen and oxygen for carrying out the vertical cutting through high-speed water in order that the bubbles will be refined for generating the nano H/O bubble liquid. In the meantime, a Nanobubble Generator is developed to verify the basic characteristics of the produced nano H/O bubbles. Its purpose is to identify the maximum concentration of bubbles in the nano H/O bubble liquid, the bubble production efficiency and bubble electrification characteristics as well as the effect of reducing the pipe flow friction resistance together with the characteristics of nanobubbles containing varied gases.

Deep Convolutional Neural Network Optimization for Defect Detection in Fabric Inspection.

This research is aimed to detect defects on the surface of the fabric and deep learning model optimization. Since defect detection cannot effectively solve the fabric with complex background by image processing, this research uses deep learning to identify defects. However, the current network architecture mainly focuses on natural images rather than the defect detection.

Study on the Measurement of Laser Drilling Depth by Combining Digital Image Relationship Measurement in Aluminum.

In this study, laser processing equipment was used to drill aluminum alloy materials and with different auxiliary mechanisms, the deformation around the holes after processing was observed. The experimental results show that, due to the high temperature generated during laser processing, a large thermal gradient causes thermal stress to be introduced into the test piece and outward expansion deformation occurs. In this study, the digital image correlation and residual stress detection methods were applied.

Micro-Drilling of Sapphire using Electro Chemical Discharge Machining.

Electrochemical discharge machining (ECDM) refers to a non-traditional machining method for performing effective material removal on non-conductive hard and brittle materials. To increase the ECDM machining efficiency, traditionally, the method of increasing the machining voltage or increasing the electrolyte concentration is used. These methods can also cause overcut reaming of the drilled holes and a rough surface on the heat affected area.

Characteristics of the Arcing Plasma Formation Effect in Spark-Assisted Chemical Engraving of Glass, Based on Machine Vision.

Spark-assisted chemical engraving (SACE) is a non-traditional machining technology that is used to machine electrically non-conducting materials including glass, ceramics, and quartz. The processing accuracy, machining efficiency, and reproducibility are the key factors in the SACE process. In the present study, a machine vision method is applied to monitor and estimate the status of a SACE-drilled hole in quartz glass.

On-line estimation of laser-drilled hole depth using a machine vision method.

The paper presents a novel method for monitoring and estimating the depth of a laser-drilled hole using machine vision. Through on-line image acquisition and analysis in laser machining processes, we could simultaneously obtain correlations between the machining processes and analyzed images. Based on the machine vision method, the depths of laser-machined holes could be estimated in real time.