Speed tracking curve before and after friction compensation. by Wanjun Zhang (496858)

Subjects:

Position tracking curve before and after friction compensation. by Wanjun Zhang (496858)

Subjects:

LuGre Model---dataset. by Wanjun Zhang (496858)

Subjects:

Comparison of different objective function value curves. by Wanjun Zhang (496858)

Subjects:

Simulation and experimental research route. by Wanjun Zhang (496858)

Subjects:

Physical picture of linear motor platform: 1-Gantry linear motor platform; 2-Linear motor servo drive; 3- industrial control computer.; 4-X-axis grating ruler displacement sensor;... by Wanjun Zhang (496858)

Subjects:

Basic principles of system identification. by Wanjun Zhang (496858)

Subjects:

Sinusoidal signal simulation. by Wanjun Zhang (496858)

Subjects:

High precision open servo platform system structure. by Wanjun Zhang (496858)

Subjects:

Description, feature counts, and data partitioning of the MIMIC-III clinical database (v1.4) used in this study. The table categorizes patient data into three main relevant modalit... by Medhat A. Tawfeek (22522087)

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... by Zhao Li (300229)

Explanations when optimized towards prediction. by Bettina Soós (10860933)

Subjects:

Evaluating motif projections. by Bettina Soós (10860933)

Subjects:

Average evaluation metrics of explanation methods (<i>n</i> = 57). by Bettina Soós (10860933)

Subjects:

Graph of a molecule. by Bettina Soós (10860933)

Subjects:

Partitioning graphs by a graphlet motif. by Bettina Soós (10860933)

Subjects:

Average target value and evaluation metrics of the optimized explanations with different optimization strategies and machine learning models. by Bettina Soós (10860933)

Subjects:

A comparative summary of relevant work on cardiovascular disease prediction using machine learning and deep learning. The table compares methods, datasets, key performance metrics,... by Medhat A. Tawfeek (22522087)

Compare classification performance. Papa et al. (2012) applied sequencing data to supervised learning classification algorithms using a software pipeline called Synthetic Learning in Microbial Ecology (SLiME), which utilizes relevant metadata as classification labels.... by Jeseok Lee (21101255)

“…Papa et al. (2012) applied sequencing data to supervised learning classification algorithms using a software pipeline called Synthetic Learning in Microbial Ecology (SLiME), which utilizes relevant metadata as classification labels. …”

Execution time comparisons between DECMDR(D), HS-MMGKG(G), SEE(S), SHEIB-AGM(B) and Epi-SSA(P) on the DNME3 100 dataset. by Liyan Sun (760586)

Subjects: