Illustration for the SST-CRN model. by Saraswathi M. (19353597)

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Pe investigation of the SST-CRN under fading channels. by Saraswathi M. (19353597)

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Pnf analysis of the SST-CRN model. by Saraswathi M. (19353597)

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Flowchart of CSA. by Saraswathi M. (19353597)

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Pe analysis of the SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

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Probability of detection analysis of SST-CRN model under fading channels. by Saraswathi M. (19353597)

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Pd analysis of the SST-CRN model under fading channels. by Saraswathi M. (19353597)

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Probability of error analysis of SST-CRN under fading channels. by Saraswathi M. (19353597)

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Pmd analysis of the SST-CRN model. by Saraswathi M. (19353597)

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Pd analysis of the SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

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Structure of DBN model. by Saraswathi M. (19353597)

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Probability of error analysis of SST-CRN model under non-fading channels. by Saraswathi M. (19353597)

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Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level by Giovanni Nattino (561797)

“…We implement the evidence factors method for binary outcomes, which includes a randomization-based testing strategy and a sensitivity analysis for hidden bias in three-group matched designs. …”

Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

“…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …”

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

“…Model evaluation was based on accuracy metrics and qualitative analysis of the confusion matrix.. …”

Supporting data for “Digital immunochromatography: A bead-based bilateral zigzag flow immuno-assay with adaptive differential noise correction for rapid and precise protein detecti... by Zhiting Peng (9722516)

GA-XGBoost optimization process diagram. by Ke Peng (2220973)

“…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …”

Testing results for classifying AD, MCI and NC. by Nicodemus Songose Awarayi (18414494)

“…The model further showed superior results on binary classification compared with existing methods. …”

Summary of existing CNN models. by Nicodemus Songose Awarayi (18414494)

“…The model further showed superior results on binary classification compared with existing methods. …”

Analysis and design of algorithms for the manufacturing process of integrated circuits by Sonia Fleytas (16856403)

“…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”