Graphical illustration of sample size estimation for the study protocol. by Müge Yalçin (16486563)

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Illustration of the BRIDES algorithm and the selection process. by Cindy Bouchard (6844979)

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Comparison of the results obtained for active power losses reduction (Standard IEEE 30-bus test system). by Abdullah Khan (377292)

Construction of kinetic data based on the Arrhenius equation with distributed activation energy. by László Zimányi (2649973)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

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Performance of optimization algorithms in six different network types. by Maurits H. W. Oostenbroek (11331123)

Performance of optimization algorithms in an network of education organizations of ± 250 nodes. by Maurits H. W. Oostenbroek (11331123)

Optimal ALARM BN discovered by CausNet. by Nand Sharma (21519845)

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Genetic Algorithm (GA) and CAGE-based personalization block diagrams. by Dmitrii Smirnov (8822324)

Cell fishing: A similarity based approach and machine learning strategy for multiple cell lines-compound sensitivity prediction by E. Tejera (7470644)

“…In the present research, we propose and discuss a straightforward strategy not based on any learning modelling but exclusively relying upon the chemical similarity of a query compound to reference compounds with annotated activity against cell lines. …”

The feature selection process of the IG-GPSO. by Fangyuan Yang (2567629)

Optimal ovarian cancer BNs learned by CausNet and CausNet-partial. by Nand Sharma (21519845)

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The feature ranking grouping process of the IG-GPSO. by Fangyuan Yang (2567629)

Dose distributions of optimized plans. by Hojin Kim (462672)

Comparison between the performance of the steady-state-based, the conventional LMSE, and the dual optimization approaches in estimating parameters of the TM model. by Alireza Ghadimi (13839874)

Expression values and standard errors of genes within each patient group under the optimal feature filtering method (ALOGA < 128) used for (blue bars) distinguishing each individua... by Song Cui (553627)

Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm by Interdis Sci Comp Life Sci (7335308)

“…</p><p dir="ltr"> (2) Isolated genes were properly processed by the IDS to optimize the network structure.…”

Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm by Interdis Sci Comp Life Sci (7335308)

“…This work mainly focuses on the following aspects: (1) On the basis of the IPC-MB and DPI, we presented a novel feature selection method called the improved MB discovery algorithm (IMBDA), which can accurately identify direct and indirect regulatory genes when inferring networks. (2) Isolated genes were properly processed by the IDS to optimize the network structure. (3) The performance of IMBDANET was assessed with extensive experiments. …”

Results from trajectory optimization of walking. by Antoine Falisse (6061601)

Optimization framework. by Nisha Ann Viswan (20371285)