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The G-code file for 3D-printing system related to the fabrication of scaffold with kagome structure
Data Types:
  • Other
  • Dataset
Each folder in this dataset refers to a specific publication and contains: 1) pdf files with an extended list of tables and images referred, but not included, in the main papers: 2) a compressed archive with the generated raw data. For more details, one can read the main articles referenced below.
Data Types:
  • Dataset
  • Document
  • File Set
This code source is a simulation of a hybrid high dimensional automated guided vehicle system design model in python. In fact, our approach aims to solve the problem of dimension growth in a convex 2D environment of an Automated Guided Vehicle System (AGVS), using a Deep reinforcement learning control system of kernels with low dimensions.
Data Types:
  • Dataset
  • File Set
Dataset of the classroom experiments reported in IKEA Effect vs. Trophy Effect - An Experimental Comparison
Data Types:
  • Software/Code
  • Dataset
Supplemental material
Data Types:
  • Software/Code
  • Image
  • Dataset
Cytoscape compatable files of the sequence similarity network (SSN) and genome neighborhood network (GNN) of the flavin amine oxidase superfamily. SSN generated from of 9,192 members of the Flavin amine oxidase superfamily with 1) BLAST E-value of 1e-35 for dataset S3, and 2) BLAST E-value of 1e-50 for dataset S4. Dataset S6 is the GNN generated based on the SSN with BLAST E-value of 1e-50.
Data Types:
  • Software/Code
  • Dataset
Research data of "Characteristics of methane-air combustion with rotating gliding arc discharge plasma assistance"
Data Types:
  • Dataset
  • File Set
The dataset contains the data used in our study "Solving the mixed model sequencing problem with reinforcement learning and metaheuristics". We provide three datasets: (1) The main dataset (folder "data") contains 2160 problem instances for the mixed model sequencing problem. The instances are based on the original dataset provided by Boysen (2011). Each instance contains information about processing times, cycle time, station length and demand plan. The dataset consists of ten mutations of the original dataset. Each mutation is a copy of the original dataset except for the demand plan. The demand plan is generated following a multinomial distribution. (2) The second dataset (folder "Robustness Check: Short-term disturbances") manipulates the demand plan of the main dataset. In each instance, the quantity of one model type is set to zero. The removed jobs are uniformly distributed over all other job models. (3) The third dataset (folder "Robustness Check: Added machines") adds machines to the initial instances. Each instance is extended by 1 to 5 machines. Original instances are used to provide the processing times for the new machines.
Data Types:
  • Other
  • Dataset
  • Text
Metabolic rates, neutrophil : lymphocyte, bacteria killing ability, and corticosterone levels in invasive cane toads from a northern and southern Florida population subjected to an immune stimulant of LPS (strain 011:B4).
Data Types:
  • Software/Code
  • Tabular Data
  • Dataset
MATLAB files for recreation of a HIL setup in a simulation environment. Use Matlab 2017b or later to run the simulation. Execute Simulation.m to start simulation.
Data Types:
  • Dataset
  • File Set
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