CNC machines are widely used in production fields since they produce similar parts in a minimum time, at higher speed and with possibly minimum error. A control system is designed, implemented and tested to control the operation of a laboratory CNC milling machine having three axes that are moved by using a stepper motor attached to each axis. The control system includes two parts, hardware part and software part, the hardware part used a PC (works as controller) connected to the CNC machine through its parallel port by using designed interface circuit. The software part includes the algorithms needed to control the CNC. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD or 3D MAX and is saved in a well-known file format (DXF), then that file is fed to the CNC machine controller by the CNC operator, so that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts (line, circle or arc) shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.
Building a Three-Axis CNC Milling Machine Control System
CNC Milling Machine
Stepper Motors
Interpolation
Polylines
DXF
Publication Date
Sat Oct 31 2020
Journal Name
International Journal Of Intelligent Engineering And Systems
Automatic Computer Aided Diagnostic for COVID-19 Based on Chest X-Ray Image and Particle Swarm Intelligence
COVID-19
Chest X-ray
Li s' method
Particle swarm intelligence
Laws' masks
Gray level co-occurrence matrix (GLCM)
Weighted voting
Support vector machine (SVM)
(25)
(7)
Publication Date
Thu Jan 01 2026
Journal Name
Innovations In Sustainable Sports Infrastructure For Eco-friendly Design And Operations
Redacting The Performance of 110m Hurdle Runners Through the Analysis of Physical and Functional Abilities
Hurdling
Sprinting
Performance
Speed
Strength Further studies could increase sample size and employ machine learning to improve the model by including more biomechanical and psychological predictors
increasing the accuracy and applicability of performance predictions in sprint hurdling.
The performance in the 110-meter hurdles at the sprint hurdles event is determined by several physical and physiological qualities. Nonetheless, relatively little attention has been paid to the predictability of such factors in determining race performance. This study seeks to fill this gap by establishing the most critical physical and physiological characteristics affecting elite hurdlers’ performance and creating a statistical model that predicts race times from the identified measurable characteristics. The study utilized a descriptive research design in-volving six elite male hurdlers, all of whom completed a battery of standardized physical and functional tests to assess their explosive lower-body strength, agility, reaction
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