| 1. |
- Gupta, Siddhartha, et al.
(författare)
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Breast Cancer Detection Using Image Processing Techniques
- 2019
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Ingår i: 2019 Innovations in Power and Advanced Computing Technologies (i-PACT). - : Institute of Electrical and Electronics Engineers Inc..
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Konferensbidrag (refereegranskat)abstract
- Cancer is the uncontrolled multiplication of group of cells in a particular location of the body and is the second largest disease leading to the death of women in the world. The disease can be cured if it is detected in early stages. A lot of research has been done to find out the tumor correctly but a 100% accurate method has not been found. Research on breast cancer detection using digital image processing is not new but many new approaches in this field is being considered to accurately predict the tumor region. The present approach is to detect the tumor region visually as well as to figure out in which region the tumor is mostly concentrated. This work majorly focuses on finding out the best algorithm/s to detect the tumor present in the breast. In the proposed work, a variety of algorithms has been applied but the best one suited for cancer detection is the combination of K Means, Closing, Dilation and Canny Edge Detection algorithm. © 2019 IEEE.
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| 2. |
- Ramasamy, Sudha, 1974-, et al.
(författare)
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Automated Path Planning for Plug Produce in a Cutting-tool Changing Application
- 2019
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Ingår i: 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). ; , s. 356-362
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Konferensbidrag (refereegranskat)abstract
- In this paper, a path planning algorithm is designed and tested with a real robot for a Plug & Produce demonstrator. The demonstrator is divided into modules that can be connected and removed. Modules are used for various processes like tool change and storage. This paper focuses on the process of cutting-tool change for the production industry. The Plug & Produce demonstrator uses a multi-agent system where parts and resources are agents. A part agent, e.g., a cutting-tool, can request a robot to perform skills like transportation. This requires the robot to be autonomous. The aim of this paper is to automate the path planning for industrial robotics in a Plug & Produce system. This is done by implementing a sampling based RRT algorithm combined with a collision detection function in RobotStudio. With various real time scenarios, the path planning execution time is observed and presented in the paper.
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| 3. |
- Reddy, Damodhar, et al.
(författare)
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A back propagation network based MPPT algorithm for grid-tied wind energy system with Vienna Rectifier
- 2019
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Ingår i: International Journal of Renewable Energy Research. - 1309-0127. ; 9:2, s. 1097-1107
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a boost type Vienna Rectifier with a back propagation network algorithm for maximum power point tracking (MPPT) from the wind energy system. The preferred control algorithm deals with non-linear problems with improved conversance precision and reduced learning time. In this system, boost type Vienna Rectifier is employed as a machine side converter for single stage energy conversion of AC to DC with the enhanced output voltage and a grid side converter worked for DC to AC conversion. Vienna Rectifier facilitates power flow with high power density, continuous sinusoidal input current, improved power factor and offers low voltage stress across the switches. The proposed system is designed to meet the load power demand of 1kW Active power with the combined contribution of the wind and the main grid. The resulting analysis of the Vienna Rectifier with the aforementioned control algorithm is validated through Matlab-Simulink for variable wind speeds. © 2019, International Journal of Renewable Energy Research.
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| 4. |
- Reddy, Damodhar, et al.
(författare)
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Comparative Analysis of P & O and RBFN MPPT Controller Based Three Level SEPIC Topology for 1.2kW Solar PV System
- 2019
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Ingår i: Gazi University Journal of Science. - Ankara : Gazi University. - 2147-1762. ; 32:3, s. 853-869
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This paper accords an intelligent controller based 3-level SEPIC configuration for energy transformation in the solar PV system. An artificial intelligence based radial basis function network is engaged as a control algorithm for the maximum power extraction and the converter control can be done based on the duty cycle generated by the controller. In this system, a SEPIC topology is used for high voltage gain with reduced switching losses. In this paper, an RBFN controller based 3-level SEPIC topology is designed for 1.2kW solar PV system over the traditional P & O (Perturb & Observe) control method and the comparative result analysis is done though the simulation output for the corresponding input parameters.
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