Data_Sheet_1_Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health.PDF by Minhua Guo (18392646)

Results from different ML algorithms. by Caroline L. Alves (14271413)

Definitions of global parameters used for constructing random ecosystems. by Robert Marsland (8616483)

Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

Reward function related parameters. by Honglei Pang (22693724)

Subjects:

Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

“…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. For accessing other networks used in the study, please refer to the article for references to the primary sources of those network data.…”

PyNoetic’s online mode in action. Data is streamed from an Emotiv EPOC headset. by Gursimran Singh (575288)

Subjects:

Data from: Structural and Functional Analysis of Multi-interface Domains by ZHAO Liang (8657694)

“…This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. …”

Plots of the SDNR versus each algorithm from the in-focus plane. by Tsutomu Gomi (7382183)

Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

Selected optimal solutions from the QLNSGA-II algorithm. by Zhongfeng Li (3965060)

Performance of various deep learning models from PyNoetic’s classification module on the Motor Imagery decoding task. by Gursimran Singh (575288)

Subjects:

3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" by Saeed Parsa (13893726)

“…</p> <p><br></p> <p>3. Algorithm</p> <p>Below is the main body of the test data generator program:</p> <p>  </p> <p>the main body of a Python program to generate test data for Python functions.…”

Case-selection algorithms with more complicated functions for aggregating information from more than one variable. by Thomas Plümper (3902578)

“…<p>Case-selection algorithms with more complicated functions for aggregating information from more than one variable.…”

Wilcoxon rank sum test results from MWOA and 7 comparison algorithms on CEC2005 functions. by Yi-Qiang Xia (20161326)

“…<p>Wilcoxon rank sum test results from MWOA and 7 comparison algorithms on CEC2005 functions.…”

Predicted body weights (kg) as a function of time (age in weeks) obtained from MARS algorithm. by Turgay Şengül (12801990)

“…<p>Predicted body weights (kg) as a function of time (age in weeks) obtained from MARS algorithm.…”

Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective by Xiangyang Jia (10026932)

3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)