Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage حسب Hetao Guo (15425082)

"…We innovatively adopted the detectable IR radiation power as the optimization fitness function, based on the particle swarm optimization (PSO) algorithm, to execute powerful cooling and simultaneously minimize the emitting within the atmospheric window for enhanced camouflage. …"

Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage حسب Hetao Guo (15425082)

"…We innovatively adopted the detectable IR radiation power as the optimization fitness function, based on the particle swarm optimization (PSO) algorithm, to execute powerful cooling and simultaneously minimize the emitting within the atmospheric window for enhanced camouflage. …"

Easy-to-Manufacture In-Line 2D Nano Antenna for Enhanced Radiation-Cooled IR Camouflage حسب Hetao Guo (15425082)

"…We innovatively adopted the detectable IR radiation power as the optimization fitness function, based on the particle swarm optimization (PSO) algorithm, to execute powerful cooling and simultaneously minimize the emitting within the atmospheric window for enhanced camouflage. …"

Performance on GradEva. حسب Jamilu Yahaya (18563445)

"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"

The considered test problems. حسب Jamilu Yahaya (18563445)

"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"

Performance on FunEva. حسب Jamilu Yahaya (18563445)

"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"

Performance on Iter. حسب Jamilu Yahaya (18563445)

"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"

Continuation of Table 2. حسب Jamilu Yahaya (18563445)

"…The sequences generated by our algorithm identify points that satisfy the first-order necessary condition for Pareto optimality. …"

Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines حسب Ophélie Thomas - - Chemin (19451533)

"…All of the FCs were then classified using machine learning tools with a statistical approach based on a fuzzy logic algorithm, trained to discriminate between nonmalignant and cancerous cells (training base, up to 120 cells/cell line). …"

Pseudo Code of RBMO. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

P-value on CEC-2017(Dim = 30). حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Memory storage behavior. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Elite search behavior. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Description of the datasets. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

S and V shaped transfer functions. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

S- and V-Type transfer function diagrams. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Collaborative hunting behavior. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Friedman average rank sum test results. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

IRBMO vs. variant comparison adaptation data. حسب Chenyi Zhu (9383370)

"…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …"

Growth rate comparison between models and experimental results in mono-culture and co-culture. حسب Elias Vera-Siguenza (16993830)