Data_Sheet_2_Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways.pdf by Maxim Sorokin (4379848)

“…We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. …”

Data_Sheet_1_Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways.zip by Maxim Sorokin (4379848)

“…We proposed an algorithm that identifies functional roles of the pathway components and applied it to annotate 3,044 human molecular pathways extracted from the Biocarta, Reactome, KEGG, Qiagen Pathway Central, NCI, and HumanCYC databases and including 9,022 gene products. …”

WSN optimized by different algorithms. by Qingwen Meng (156386)

“…The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

Compare algorithm parameter settings. by Qingwen Meng (156386)

“…The ASBOA algorithm was evaluated using the CEC2017 and CEC2022 benchmark test functions and compared with other algorithms (such as PSO, GWO, DBO, and CPO). …”

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Evolution of objective function. by Serdar Ekinci (15927455)

“…A custom optimizer, the quadratic wavelet-enhanced gradient-based optimization (QWGBO) algorithm, is developed. …”

Brief sketch of the quasi-attraction/alignment algorithm. by Takayuki Niizato (162226)

“…The focal agent selects its next direction randomly based on . (D) A brief sketch of the avoidance algorithm. …”

The convergence curves of all the 10 algorithms. by WanRu Zhao (18980374)

“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”

Multi-scale detection of hierarchical community architecture in structural and functional brain networks by Arian Ashourvan (6685232)

“…To address this limitation, we exercise a multi-scale extension of a common community detection technique, and we apply the tool to synthetic graphs and to graphs derived from human neuroimaging data, including structural and functional imaging data. …”

Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" by Saeed Parsa (13893726)

“…</p> <p><br></p> <p>3. Algorithm</p> <p>Below is the main body of the test data generator program:</p> <p>  </p> <p>the main body of a Python program to generate test data for Python functions.…”

Flowchart of the specific incarnation of the BO algorithm used in the experiments. by Lisa Laux (9367681)

“…To choose the next pipeline configuration to evaluate, the BO algorithm uses an Expected Improvement function to trade off maximisation of QS with the need to fully learn the GP. …”

Loss function and accuracy curve comparison. by Dayu Zhang (710629)

Phase diagram for global archetype model as a function of temperature. by Giulio Ruffini (383994)

Algorithm of the main experiment targeted to measure the perceptual point spread function (pPSF) treating patients visual system including its optics, physiology and psychology as an integrated imaging system, and patient’s perceptions as its output signal. by Krzysztof Petelczyc (3954203)

“…<p>In the algorithm, the following variables were used: “Ic” denotes the intensity of the central diode (Ic = 40 cd); “DIST(i)” is a randomly sorted list of “D” angular stimuli positions distributed equally as a function of distance from 0.24° to 7.67° from the central point (D = 10), while “i” is an index corresponding to the current distance of a probe diode (“d”); “N” denotes the number of trials for each stimuli position (N = 20); “s” denotes the perceptual brightness value transformed to diode luminous intensity by an array “I(s)” corresponds to the table “scale (level)” determined by the algorithm presented in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0306331#pone.0306331.g003" target="_blank">Fig 3</a>; “cnt” is a counter of trials for the current probe diode’s distance, array threshold (d), and slope (d), i.e., it denotes the intensity of the single point of the pPSF and its uncertainty. …”

Flowchart of step() function. by Raed Alharthi (18340157)

Standard benchmark functions [42]. 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. …”

Objective function value statistics. by Chao Li (145513)

F4 function and convergence curve graph. by Jiangli Yu (4601986)

F5 function and convergence curve graph. by Jiangli Yu (4601986)

F1 function and convergence curve graph. by Jiangli Yu (4601986)