The structure of a gas transmission system. by Junhao Wei (6816803)

“…In the experimental section, we validate the efficiency and superiority of LSWOA by comparing it with outstanding metaheuristic algorithms and excellent WOA variants. The experimental results show that LSWOA exhibits significant optimization performance on the benchmark functions with various dimensions. …”

The structure of a three-bar truss. by Junhao Wei (6816803)

“…In the experimental section, we validate the efficiency and superiority of LSWOA by comparing it with outstanding metaheuristic algorithms and excellent WOA variants. The experimental results show that LSWOA exhibits significant optimization performance on the benchmark functions with various dimensions. …”

The structure of a tension/compression spring. by Junhao Wei (6816803)

“…In the experimental section, we validate the efficiency and superiority of LSWOA by comparing it with outstanding metaheuristic algorithms and excellent WOA variants. The experimental results show that LSWOA exhibits significant optimization performance on the benchmark functions with various dimensions. …”

The linearly decreasing convergence factor a. by Junhao Wei (6816803)

“…In the experimental section, we validate the efficiency and superiority of LSWOA by comparing it with outstanding metaheuristic algorithms and excellent WOA variants. The experimental results show that LSWOA exhibits significant optimization performance on the benchmark functions with various dimensions. …”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

“…It implements a probabilistic scoring function to match spectra to sequences, a novel combinatorial search strategy for finding post-translational modifications, and a Bayesian approach to locate modification sites. …”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

“…It implements a probabilistic scoring function to match spectra to sequences, a novel combinatorial search strategy for finding post-translational modifications, and a Bayesian approach to locate modification sites. …”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

“…It implements a probabilistic scoring function to match spectra to sequences, a novel combinatorial search strategy for finding post-translational modifications, and a Bayesian approach to locate modification sites. …”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

“…It implements a probabilistic scoring function to match spectra to sequences, a novel combinatorial search strategy for finding post-translational modifications, and a Bayesian approach to locate modification sites. …”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

“…It implements a probabilistic scoring function to match spectra to sequences, a novel combinatorial search strategy for finding post-translational modifications, and a Bayesian approach to locate modification sites. …”

A-B. The boxplots present the distribution of scores for IRF4 and ELANE immune-related functions in low-expression and high-expression groups. by Min-xiao Wang (20868922)

Study workflow. by Sayantan Kumar (20208872)

Functional examination of the 6 key significant genes found in modules 1 and 2. by Ravinder Sharma (13154079)

Comparison of Stage II-B and Stage II-A. by Ferhat Yuna (21519851)

“…The mathematical model was transformed into a fitness function and a solution was provided with the Tabu Search Algorithm and Simulated Annealing. …”

Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

An HSR corridor with m stations and n trains. by Zhipeng Huang (1759759)

“…Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Structure of bi-level programming model. by Zhipeng Huang (1759759)

“…Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Lanzhou-Xi’an HSR corridor. by Zhipeng Huang (1759759)

“…Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Comparison of related studies with our work. by Zhipeng Huang (1759759)

“…Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Unit impedance of each OD pair. by Zhipeng Huang (1759759)

“…Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”

Subscripts and parameters used in TSSN. by Zhipeng Huang (1759759)

“…Impedance functions for various network arcs are developed, incorporating these three key attributes of travel demand and transforming the passenger travel choice issue into a path selection problem within the TSSN. …”