Search

Your search keyword '"Hussain, Sardar Mehboob"' showing total 17 results
Start Over Author "Hussain, Sardar Mehboob"
17 results on '"Hussain, Sardar Mehboob"'

3. An Efficient Scheduling of Electrical Appliance in Micro Grid Based on Heuristic Techniques

Author

Hussain, Sardar Mehboob, Zafar, Ayesha, Khalid, Rabiya, Abid, Samia, Qasim, Umar, Khan, Zahoor Ali, Javaid, Nadeem, Kacprzyk, Janusz, Series editor, Pal, Nikhil R., Advisory editor, Bello Perez, Rafael, Advisory editor, Corchado, Emilio S., Advisory editor, Hagras, Hani, Advisory editor, Kóczy, László T., Advisory editor, Kreinovich, Vladik, Advisory editor, Lin, Chin-Teng, Advisory editor, Lu, Jie, Advisory editor, Melin, Patricia, Advisory editor, Nedjah, Nadia, Advisory editor, Nguyen, Ngoc Thanh, Advisory editor, Wang, Jun, Advisory editor, Barolli, Leonard, editor, and Terzo, Olivier, editor

Published
2018
Full Text
View/download PDF

5. Explainable deep learning for medical image processing: computer-aided diagnosis and robot-assisted surgery

Author

Hussain, Sardar Mehboob

Subjects
robot-assisted surgery, explainable deep learning, image-guided surgery, deep learning, artificial intelligence, evaluation of XAI, machine learning, Explainable artificial intelligence, robotic surgery, computer-aided diagnosis, image-guided surgery, XAI, evaluation of XAI, breast cancer classification, XAI, Settore ING-INF/06 - Bioingegneria Elettronica e Informatica, computer-aided diagnosis
Published
2023

12. Segmentation and Identification of Vertebrae in CT Scans Using CNN, k-Means Clustering and k-NN

Author

Altini, Nicola, primary, De Giosa, Giuseppe, additional, Fragasso, Nicola, additional, Coscia, Claudia, additional, Sibilano, Elena, additional, Prencipe, Berardino, additional, Hussain, Sardar Mehboob, additional, Brunetti, Antonio, additional, Buongiorno, Domenico, additional, Guerriero, Andrea, additional, Tatò, Ilaria Sabina, additional, Brunetti, Gioacchino, additional, Triggiani, Vito, additional, and Bevilacqua, Vitoantonio, additional

Published
2021
Full Text
View/download PDF

17. Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations.

Author

Javaid, Nadeem, Hussain, Sardar Mehboob, Ullah, Ibrar, Noor, Muhammad Asim, Abdul, Wadood, Almogren, Ahmad, and Alamri, Atif

Subjects
*ENERGY consumption of buildings, *ENERGY demand management, *HEURISTIC algorithms, *MATHEMATICAL optimization, *GENETIC algorithms
Abstract

Today's buildings are responsible for about 40% of total energy consumption and 30-40% of carbon emissions, which are key concerns for the sustainable development of any society. The excessive usage of grid energy raises sustainability issues in the face of global changes, such as climate change, population, economic growths, etc. Traditionally, the power systems that deliver this commodity are fuel operated and lead towards high carbon emissions and global warming. To overcome these issues, the recent concept of the nearly zero energy building (nZEB) has attracted numerous researchers and industry for the construction and management of the new generation buildings. In this regard, this paper proposes various demand side management (DSM) programs using the genetic algorithm (GA), teaching learning-based optimization (TLBO), the enhanced differential evolution (EDE) algorithm and the proposed enhanced differential teaching learning algorithm (EDTLA) to manage energy and comfort, while taking the human preferences into consideration. Power consumption patterns of shiftable home appliances are modified in response to the real-time price signal in order to get monetary benefits. To further improve the cost and user discomfort objectives along with reduced carbon emission, renewable energy sources (RESs) are also integrated into the microgrid (MG). The proposed model is implemented in a smart residential complex of multiple homes under a real-time pricing environment. We figure out two feasible regions: one for electricity cost and the other for user discomfort. The proposed model aims to deal with the stochastic nature of RESs while introducing the battery storage system (BSS). The main objectives of this paper include: (1) integration of RESs; (2) minimization of the electricity bill (cost) and discomfort; and (3) minimizing the peak to average ratio (PAR) and carbon emission. Additionally, we also analyze the tradeoff between two conflicting objectives, like electricity cost and user discomfort. Simulation results validate both the implemented and proposed techniques. [ABSTRACT FROM AUTHOR]

Published
2017
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results