Correlation between the number of times each node is selected and the network centrality corresponding to Fig 6. by Xiaochen He (455300)

Schematic diagram of software architecture and chassis node program flow for wheeled robot platform. by Weihua Zhou (19271)

Summary of the BRIDES node selection procedure providing the minimum number of nodes required to reach a maximal score, and the number of multiple solutions with the same score for... by Cindy Bouchard (6844979)

Table_1_Overlapping Structures Detection in Protein-Protein Interaction Networks Using Community Detection Algorithm Based on Neighbor Clustering Coefficient.docx by Yan Wang (15435)

“…The contributions of the NLC algorithm are threefold: (i) Combine the edge-based community detection method with local expansion in seed selection and the local clustering coefficient of neighboring nodes to improve the accuracy of seed selection; (ii) A method of measuring the distance between edges is improved to make the result of community division more accurate; (iii) A community optimization strategy for the excessive overlapping nodes makes the overlapping structure more reasonable. …”

Table_1_Overlapping Structures Detection in Protein-Protein Interaction Networks Using Community Detection Algorithm Based on Neighbor Clustering Coefficient.docx by Yan Wang (15435)

“…The contributions of the NLC algorithm are threefold: (i) Combine the edge-based community detection method with local expansion in seed selection and the local clustering coefficient of neighboring nodes to improve the accuracy of seed selection; (ii) A method of measuring the distance between edges is improved to make the result of community division more accurate; (iii) A community optimization strategy for the excessive overlapping nodes makes the overlapping structure more reasonable. …”

Scenarios for algorithms using IEEE 33 bus. by Bachirou Bogno (20485724)

Scenarios for algorithms using IEEE 69 bus. by Bachirou Bogno (20485724)

Node coordinates and production. by Chen Hao (352436)

“…An optimization method for medical waste collection site selection and vehicle routing is proposed. Given the NP-hard nature of the problem, a location allocation method based on minimum envelope clustering analysis is employed, and an improved NSGA-II algorithm incorporating a fast non-dominated sorting mechanism is designed to obtain Pareto optimal solutions. …”

Data Sheet 1_Contrast-enhanced CT radiomics combined with multiple machine learning algorithms for preoperative identification of lymph node metastasis in pancreatic ductal adenoca... by Yue Huang (285485)

“…Objectives<p>This research aimed to assess the value of radiomics combined with multiple machine learning algorithms in the diagnosis of pancreatic ductal adenocarcinoma (PDAC) lymph node (LN) metastasis, which is expected to provide clinical treatment strategies.…”

List of relevant studies using DL and ML algorithms for skin cancer identification. by Ahmad Naeem (15246749)

A Bottom-Up Approach to Testing Hypotheses That Have a Branching Tree Dependence Structure, With Error Rate Control by Yunxiao Li (1816909)

The flowchart of the FSIAC algorithm. by Siji Chen (14883420)

“…Thirdly, the FA is put forward for cluster-head (CH) selection and cluster formation. Simulation results indicate that the proposed FSICL algorithm achieves the higher localization accuracy faster, and the FSIAC algorithm achieves the higher stability of clusters, longer link expiration time (LET), and longer node lifetime, all of which improve the communication performance for indoor FANETs.…”

The flowchart of the FSICL algorithm. by Siji Chen (14883420)

“…Thirdly, the FA is put forward for cluster-head (CH) selection and cluster formation. Simulation results indicate that the proposed FSICL algorithm achieves the higher localization accuracy faster, and the FSIAC algorithm achieves the higher stability of clusters, longer link expiration time (LET), and longer node lifetime, all of which improve the communication performance for indoor FANETs.…”

The assignment of seizures to the fast, slow and multi-domino groups computed by submitting the first 8 seconds of each EEG recording epoch to the seizure detection algorithm. by Jennifer Creaser (9427932)

Performances of different clustering algorithms. by Siji Chen (14883420)

“…Thirdly, the FA is put forward for cluster-head (CH) selection and cluster formation. Simulation results indicate that the proposed FSICL algorithm achieves the higher localization accuracy faster, and the FSIAC algorithm achieves the higher stability of clusters, longer link expiration time (LET), and longer node lifetime, all of which improve the communication performance for indoor FANETs.…”

An example of one propagation of multiple influences (colors) in a multilayer network <i>G</i>. by Yu Chen (29959)

Action potential detection with high temporal accuracy using a convolutional neural network (CNN). by Tjitse van der Molen (20391106)

Action potential detection with high temporal accuracy using a convolutional neural network (CNN). by Tjitse van der Molen (20391106)

Minimum node lifetime v.s. UAV number. by Siji Chen (14883420)

“…Thirdly, the FA is put forward for cluster-head (CH) selection and cluster formation. Simulation results indicate that the proposed FSICL algorithm achieves the higher localization accuracy faster, and the FSIAC algorithm achieves the higher stability of clusters, longer link expiration time (LET), and longer node lifetime, all of which improve the communication performance for indoor FANETs.…”

BRIDES node selection process for scenario Ap and Model B³D¹E²S³ (3, 0, 0, 1, 2, 3). by Cindy Bouchard (6844979)