Available functions in the phase-shifting package. by Raul Castañeda (13932971)

Available functions in the numerical propagation package. by Raul Castañeda (13932971)

Available functions in the phase reconstruction package. by Raul Castañeda (13932971)

The SSA based SVM objective function minimization against iterations. by Ali Ahmed (2567584)

Subjects:

Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Programmable Droplet Microfluidics Based on Machine Learning and Acoustic Manipulation by Kyriacos Yiannacou (10292766)

“…Using this method, we demonstrate 2D transportation and merging of water droplets in oil and oil droplets in water, and we performed the chemistry that underlies the basis of a colorimetric glucose assay. We show that we can manipulate drops with volumes ranging from ∼200 pL up to ∼30 nL with our setup. …”

Programmable Droplet Microfluidics Based on Machine Learning and Acoustic Manipulation by Kyriacos Yiannacou (10292766)

“…Using this method, we demonstrate 2D transportation and merging of water droplets in oil and oil droplets in water, and we performed the chemistry that underlies the basis of a colorimetric glucose assay. We show that we can manipulate drops with volumes ranging from ∼200 pL up to ∼30 nL with our setup. …”

Programmable Droplet Microfluidics Based on Machine Learning and Acoustic Manipulation by Kyriacos Yiannacou (10292766)

“…Using this method, we demonstrate 2D transportation and merging of water droplets in oil and oil droplets in water, and we performed the chemistry that underlies the basis of a colorimetric glucose assay. We show that we can manipulate drops with volumes ranging from ∼200 pL up to ∼30 nL with our setup. …”

Programmable Droplet Microfluidics Based on Machine Learning and Acoustic Manipulation by Kyriacos Yiannacou (10292766)

“…Using this method, we demonstrate 2D transportation and merging of water droplets in oil and oil droplets in water, and we performed the chemistry that underlies the basis of a colorimetric glucose assay. We show that we can manipulate drops with volumes ranging from ∼200 pL up to ∼30 nL with our setup. …”

Programmable Droplet Microfluidics Based on Machine Learning and Acoustic Manipulation by Kyriacos Yiannacou (10292766)

“…Using this method, we demonstrate 2D transportation and merging of water droplets in oil and oil droplets in water, and we performed the chemistry that underlies the basis of a colorimetric glucose assay. We show that we can manipulate drops with volumes ranging from ∼200 pL up to ∼30 nL with our setup. …”

Programmable Droplet Microfluidics Based on Machine Learning and Acoustic Manipulation by Kyriacos Yiannacou (10292766)

“…Using this method, we demonstrate 2D transportation and merging of water droplets in oil and oil droplets in water, and we performed the chemistry that underlies the basis of a colorimetric glucose assay. We show that we can manipulate drops with volumes ranging from ∼200 pL up to ∼30 nL with our setup. …”

Programmable Droplet Microfluidics Based on Machine Learning and Acoustic Manipulation by Kyriacos Yiannacou (10292766)

“…Using this method, we demonstrate 2D transportation and merging of water droplets in oil and oil droplets in water, and we performed the chemistry that underlies the basis of a colorimetric glucose assay. We show that we can manipulate drops with volumes ranging from ∼200 pL up to ∼30 nL with our setup. …”

Parameters of the genetic algorithm. by Jian Ma (170138)

List of feature selection methods used in the voting algorithm. by Mahmoud Zeydabadinezhad (12289570)

Subjects:

Python cv coding screenshots of all developed fingerprints on distinct surfaces. by Nisha Yadav (366131)

A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases by Maru Song (22593561)

Subjects:

The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

“…First, physico-chemical inputs as bulk density (BD), initial water content (W_i), saturated water content (W_s), mean weight diameter (MWD), and geometric mean diameter (GMD) of aggregates, pH, electrical conductivity (EC), and calcium carbonate equivalent (CCE) were measured. Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”

The schematic view of the fruit fly optimization algorithm (FOA). by Mohsen Hesami (6917390)

Subjects:

Calibration and sample phase objects for the JL setup. by Benedict Diederich (4903576)

Immune infiltration analysis by ssGSEA algorithm. by Yubin Xue (1537042)