Statistical information about the objective values of the algorithms. by Emre Demir (6190242)

(Movie for Fig 2B) Same as S1 Movie but using a small value for the <i>r</i> parameter. by Toviah Moldwin (10866708)

For Case-<i>24</i>, the values of three parameters that correspond to the airports. by Emre Demir (6190242)

(Movie for Fig 2C) Similar to S1 Movie, but trained on a negative example, with synapse locations initiated such that synapses are clustered with same-sign input values. by Toviah Moldwin (10866708)

The parameter Positive Predictive Value (PPV) of the HELIOS method with referencing the Smith-Waterman algorithm in the accuracy measurement of classification output. by Ehsan Maleki (14149418)

The parameter Negative Predictive Value (NPV) of the HELIOS method with referencing the Smith-Waterman algorithm in the accuracy measurement of classification output. by Ehsan Maleki (14149418)

(Movie for Fig 2A) Dynamics of synaptic clustering due to the G-clusteron location update rule, using a large value for the <i>r</i> parameter and trained on a single positive-labe... by Toviah Moldwin (10866708)

The mAP@50 values of black spot disease and jujube at different DCN embedding positions. by Zhi-Ben Yin (17743139)

Fitness value v.s. iteration. by Siji Chen (14883420)

Constructing scatter diagrams and discriminating algorithms. by Keiichiro Nishihara (9954854)

The weighted value of each node. by Tang Ruipeng (20141334)

“…In order to cover as much area as possible, farms usually deploy multiple monitoring devices in different locations of the same area. …”

Geographical location of the Mentougou District. by Xiaodan Li (132227)

An algorithmic multiple attribute decision-making context to model uncertainty associated with hospital site selection problem using complex sv-neutrosophic soft information by Khuram Ali Khan (19138115)

G-clusteron classification of handwritten digits (MNIST) and the resultant distribution of synaptic locations and activations. by Toviah Moldwin (10866708)

Attack and defense behaviors with the sensory–motor algorithm between multiple predators and prey. by Hiroyuki Ichijo (13891153)

IGD values in robustness testing. by Xiaodan Li (132227)

The G-clusteron requires the weight and location update rules to solve the XOR problem from arbitrary initial conditions. by Toviah Moldwin (10866708)

Average IGD values of two algorithems. by Xiaodan Li (132227)

IGD values under different problems. by Xiaodan Li (132227)

Validation analyses with multiple cohorts of datasets and characterization of genes located in regions with predicted CNV events. by Deng Wu (805710)