Metabolomic Coverage of Chemical-Group-Submetabolome Analysis: Group Classification and Four-Channel Chemical Isotope Labeling LC-MS by Shuang Zhao (484057)

“…We developed a computer algorithm to classify chemical structures according to their functional groups. …”

Metabolomic Coverage of Chemical-Group-Submetabolome Analysis: Group Classification and Four-Channel Chemical Isotope Labeling LC-MS by Shuang Zhao (484057)

“…We developed a computer algorithm to classify chemical structures according to their functional groups. …”

Metabolomic Coverage of Chemical-Group-Submetabolome Analysis: Group Classification and Four-Channel Chemical Isotope Labeling LC-MS by Shuang Zhao (484057)

“…We developed a computer algorithm to classify chemical structures according to their functional groups. …”

Table4_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table3_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table2_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table5_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table1_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

datasheet1_Real-Time Dispatching Performance Improvement of Multiple Multi-Energy Supply Microgrids Using Neural Network Based Approximate Dynamic Programming.pdf by Bei Li (90587)

“…The results show that the neural network based ADP one-step decision algorithm has almost the same performance as the Global optimization algorithm, and the highest performance among all others Local optimization algorithms. …”

Data_Sheet_1_A Novel Method Based on Combination of Independent Component Analysis and Ensemble Empirical Mode Decomposition for Removing Electrooculogram Artifacts From Multichann... by Chao-Lin Teng (11545063)

“…Then, by performing the EEMD algorithm on EOG-related ICs, the intrinsic mode functions (IMFs) linked to EOG were discriminated and eliminated. …”

Models and Dataset by M RN (9866504)

“…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …”

Logical Fault Detection Approach for Mixed Control Flipping Faults in Reversible Circuits by Mousum Handique (21385838)

“…Experimental results are evaluated based on the MixCFF detection and the MixCFF fault coverage range with the help of different benchmark circuits using the suggested ATPG algorithm.…”

Analysis of kinematics and leveling performance of a novel cable-driven parallel automatic leveling robot for spacecraft hoisting by Zhuohong Dai (21215147)

“…The simulation and experiment results showed that the proposed cable and counterweight adjustment algorithms can achieve the desired leveling goals. The leveling accuracy is less than 0.11° after the two-stage adjustment, meeting the accuracy requirements for practical conditions. …”

Datasheet1_A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images.zip by Stefania Marcotti (5896853)

“…Using pre-existing datasets of cell and ECM images, we demonstrate our approach and compare and contrast this workflow with two other well-known ImageJ algorithms to quantify image feature alignment. These comparisons reveal that AFT has a number of advantages due to its grid-based FFT approach. 1) Flexibility in defining the window and neighborhood sizes allows for performing a parameter search to determine an optimal length scale to carry out alignment metrics. …”

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…</p><p dir="ltr">These biological metrics were used to define a binary toxicity label: entries were classified as toxic (1) or non-toxic (0) based on thresholds from standardized guidelines (e.g., ISO 10993-5:2009) and literature consensus. …”