Final path. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Expansion procedure. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Artificial potential field method. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Modified D-H parameters. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Path comparison before and after smoothing. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Schematic diagram of dynamic step size expansion. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Mirobot six-axis robot arm. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Comparison before and after path pruning. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Time and path length of 30 simulation planning. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Joint coordinate system. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Schematic diagram of path pruning process. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Mirobot robot arm model. by Zhenggang Wang (1753657)

“…<div><p>In response to the widely used RRT-Connect path planning algorithm in the field of robotic arms, which has problems such as long search time, random node growth, multiple and unsmooth path turns, a path planning algorithm combining dynamic step size and artificial potential field is proposed. …”

Two artificial intelligence algorithms give similar predicted 3D structures of <i>MTB</i> PhoR. by Wladimir Malaga (239246)

A Wavelet Lifting Approach for Representing and Denoising Functions on Network Edges by Dingjia Cao (22411671)

Data Sheet 1_Surrogate-based worst-case analysis of a knee joint model using Genetic Algorithm.docx by Adam Ciszkiewicz (19204642)

“…The main idea of the paper is to search for two models with the greatest different response in terms of displacement-load curve. Real-Coded Genetic Algorithm is employed to effectively explore the high-dimensional space of uncertain parameters of a 2D dynamic knee model, while Radial Basis Function surrogates reduce the computation by orders of magnitude to near real-time, with negligible impact on the quality. …”

DataSheet1_A self-training subspace clustering algorithm based on adaptive confidence for gene expression data.PDF by Dan Li (106345)

“…The superiority of the proposed SSCAC algorithm is mainly reflected in the following aspects. 1) In order to improve the discriminative property of gene expression data, the low-rank representation with distance penalty is used to mine the potential subspace structure of data. 2) Considering the problem of mislabeling in self-training, a semi-supervised clustering objective function with label confidence is proposed, and a self-training subspace clustering framework is constructed on this basis. 3) In order to mitigate the negative impact of mislabeled data, an adaptive adjustment strategy based on gravitational search algorithm is proposed for label confidence. …”

Table1_Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis.XLSX by Lu Li (14069)

“…Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. …”

Table2_Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis.XLSX by Lu Li (14069)

“…Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. …”

Table3_Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis.XLSX by Lu Li (14069)

“…Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. …”

ddPCR mtDNA amplicon concentration as a function of distance. by Patrick Kurtz (21772385)