Showing 1,201 - 1,220 results of 2,508 for search 'significantly ((linear decrease) OR (((teer decrease) OR (greater decrease))))', query time: 0.50s Refine Results
  1. 1201

    S1 Graphical abstract - by Kevin J. Kokesh (19859571)

    Published 2024
    “…Protein kinase C (PKC) activity was greater in the CF cells compared to the non-CF cells, but the activity was significantly attenuated in both cell types after infection with <i>M</i>. …”
  2. 1202
  3. 1203

    Mean parameter values for the selected crops. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  4. 1204

    Performance comparison of ML models. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  5. 1205

    Comparative data of different soil samples. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  6. 1206

    Confusion matrix of random forest model. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  7. 1207

    Sensor value scenario for fuzzy logic algorithm. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  8. 1208

    Evaluation metrics of selected ML models. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  9. 1209

    Block diagram of the proposed system. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  10. 1210

    Chart for applicable amount of fertilizers. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  11. 1211

    Cost analysis of irrigation controller unit. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  12. 1212

    Run times of two algorithms. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  13. 1213
  14. 1214

    Flow chart of Fuzzy Logic based control system. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  15. 1215

    Block diagram for IoT-based irrigation system. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  16. 1216

    Flow chart of Average Value-based control system. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
  17. 1217

    Hardware design for IoT-based irrigation system. by Gourab Saha (8987405)

    Published 2025
    “…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …”
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  19. 1219
  20. 1220

    Characteristics of the study subjects (N = 39). by Layane S. P. Costa (22530327)

    Published 2025
    “…EELV increased in PL (+ 0.7 mL/kg PBW), PR (+2.0), and AR (+2.8), but decreased in AL (−2.3) (<i><i>p</i></i> < 0.001). In the bilateral protocol (n = 10, 70% male; 23.6 ± 3.2 years), regional ventilation showed no significant effects of position, ROI, or interaction (<i><i>p</i></i> > 0.05). …”