Processed Dataset for “Optimization of Mixed-Model Multi-Manned Assembly Lines for Fuel–Electric Vehicle Co-Production under Workstation Sharing” by Lingling Hu (22555691)

“…<p dir="ltr">This dataset contains the anonymized and processed production data used in the study titled “Optimization of Mixed-Model Multi-Manned Assembly Lines for Fuel–Electric Vehicle Co-Production under Workstation Sharing,” submitted to <i>World Electric Vehicle Journal (WEVJ)</i>.…”

Inspection of Line Defects in Transition Metal Dichalcogenides Using a Microscopic Hyperspectral Imaging Technique by Xiangmin Hu (1612399)

Processed Dataset for “Modeling and Optimization of a Mixed-Model Two-Sided Assembly Line Balancing Problem Considering a Workstation-Sharing Mechanism” by Lingling Hu (22555691)

“…<p dir="ltr">This dataset contains the anonymized and processed production data used in the study titled “Modeling and Optimization of a Mixed-Model Two-Sided Assembly Line Balancing Problem Considering a Workstation-Sharing Mechanism,” submitted to <i>Applied Sciences</i>.…”

The process of optimizing RPGA by Q-Learning. by Yicheng Liu (2179626)

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

“…This in-house algorithm will be helpful for obtaining more accurate NRTL parameters in a timely manner and will facilitate the simulation of biochemical processes for process optimization, energy consumption estimation, and life cycle assessment.…”

Algorithm parameter settings. by Panfei Li (22379086)

“…To address its high-dimensional complexity, we propose an Enhanced Benders Decomposition (EBD) framework that decomposes CALBP-TS into a workload-balancing master problem (MP) addressing worker-process assignment and task-splitting using a rigorous linearization theorem and a feasibility-checking subproblem (SP) handling spatio-temporal constraints via dummy process encoding. …”

Integrated algorithmic framework. by Panfei Li (22379086)

“…To address its high-dimensional complexity, we propose an Enhanced Benders Decomposition (EBD) framework that decomposes CALBP-TS into a workload-balancing master problem (MP) addressing worker-process assignment and task-splitting using a rigorous linearization theorem and a feasibility-checking subproblem (SP) handling spatio-temporal constraints via dummy process encoding. …”

Swarm intelligence algorithms for multi-objective IMP by Francisco Muñoz (9455441)

The pseudo code of HIP algorithm. by Panfei Li (22379086)

“…To address its high-dimensional complexity, we propose an Enhanced Benders Decomposition (EBD) framework that decomposes CALBP-TS into a workload-balancing master problem (MP) addressing worker-process assignment and task-splitting using a rigorous linearization theorem and a feasibility-checking subproblem (SP) handling spatio-temporal constraints via dummy process encoding. …”

Quantitative results. Our different models and ablations are compared under “Online Detection” using the nomenclature “mean (std)”, and superscripts for referencing rows in the tex... by Nicolas Valenchon (13281855)

The pseudo code of local branching algorithm. by Panfei Li (22379086)

“…To address its high-dimensional complexity, we propose an Enhanced Benders Decomposition (EBD) framework that decomposes CALBP-TS into a workload-balancing master problem (MP) addressing worker-process assignment and task-splitting using a rigorous linearization theorem and a feasibility-checking subproblem (SP) handling spatio-temporal constraints via dummy process encoding. …”

Matching percentages of pairwise comparisons within repeats of the same scan settings for D (default setting) and C (chosen optimal setting). by Melvin Geubbelmans (19565593)

Genetic algorithms can be applied to higher-dimensional design problems. by Lu Hong (399882)

Human expert versus automated processing: Running dataset. by Keenon Werling (17512156)

Parallel plot showing hyperparameter exploration. by Ramona Leenings (11167294)

Generation of in silico dataset and calibration pipeline optimization. by Janice Yang (5747246)

Boxplots illustrating key metrics of the model optimization process for infection periods ranging from 8 to 20 days. by Hélder Seixas Lima (18840636)

Temporal response patterns determined by Dirichlet Process-based clustering algorithm across amplitudes and stimuli. by Dinh K. Tang (20469082)

“…<p>The average neuronal activity for each cluster of the Contact <b>(a)</b>, Rough <b>(b)</b> and Smooth stimulus <b>(c)</b> were determined using the Dirichlet Process Mixture Model (DPM) clustering algorithm. …”

Graphical representation of the optimization process in machine learning, focusing on the adjustment of weights during gradient descent. by Liu Liu (512237)

Different steps of the experiment and data processing. by Isabel Barradas (20614853)