<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…<p dir="ltr"><b>Opti2Phase: Python Scripts for Two-Stage Focal Reducer Design</b></p><p dir="ltr">The folder <b>Opti2Phase</b> contains the Python scripts used to generate the results presented in the manuscript. …”

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…Functional groups are widely used in organic chemistry, because they provide a rationale to analyze physicochemical and reactivity properties. …”

SP results of algorithms in the CEC 2009 test functions. by Vahid Goodarzimehr (21343124)

MS results of algorithms in the CEC 2009 test functions. by Vahid Goodarzimehr (21343124)

Flowchart of DAPF-RRT algorithm. by Zhenggang Wang (1753657)

Subjects: “…target gravitational function…”

Performance comparison of different algorithms. by Zhenggang Wang (1753657)

Subjects: “…target gravitational function…”

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density. by Hassan Mehboob (8960273)

“…<p>A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.…”

(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

Subjects:

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

Subjects:

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov (20682324)

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms by Saadiallakh Normatov (20682324)

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. …”

Flowchart of proposed algorithm. by Tibebu Legesse (21030014)

“…Moreover, the proposed algorithm significantly extends network lifetime, with a <b>3.5%</b> and <b>7.5%</b> improvement over EAPS-AODV and AODV. …”

Line charts of the elbow method and the k-value selection algorithm: (A) elbow method; (B) k-value selection algorithm. by Jingnan Yan (20727331)

Subjects:

Flowchart of the general algorithm for one trial. by Junying Wang (509009)

Reward function related parameters. by Honglei Pang (22693724)

Subjects:

Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms. by Ruyi Dong (9038174)

Subjects: “…dimensional benchmark functions…”

CPU usage of benchmark function: (a) CPU Usage during the Execution of Benchmark Functions F21-F30, (b) CPU Usage during the Execution of Benchmark Functions F31-F40 and (c) CPU Us... by Ruyi Dong (9038174)

Subjects: “…dimensional benchmark functions…”

Iteration curve of benchmark function: (a) Convergence curves of the average best fitness for functions F21-F30, (b) Convergence curves of the average best fitness for functions F3... by Ruyi Dong (9038174)

Subjects: “…dimensional benchmark functions…”