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significantly lower » significantly higher (Expand Search)
linear decrease » linear increase (Expand Search)
lower decrease » larger decrease (Expand Search), we decrease (Expand Search), showed decreased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
significantly lower » significantly higher (Expand Search)
linear decrease » linear increase (Expand Search)
lower decrease » larger decrease (Expand Search), we decrease (Expand Search), showed decreased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
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2281
Validation of the optimum formula.
Published 2025“…The cytotoxicity of the optimized bilosomal formulation was enhanced on the MCF-7 breast and OV-2774 ovarian cancer cell lines compared to AXT suspension even at lower concentrations. Flow cytometry showed that AXT loaded BSMs made a significant increase in the percentage of apoptotic cells in MCF-7 and OV-2774 cells, respectively. …”
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2282
Raw data for all figures.
Published 2025“…The mutant displayed a lower stomatal density and index, leading to reduced net photosynthetic rate, transpiration rate, and stomatal conductance but increased water-use efficiency (WUE). …”
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2283
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2284
Mean parameter values for the selected crops.
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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2285
Performance comparison of ML models.
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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2286
Comparative data of different soil samples.
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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2287
Confusion matrix of random forest model.
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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2288
Sensor value scenario for fuzzy logic algorithm.
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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2289
Evaluation metrics of selected ML models.
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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2290
Block diagram of the proposed system.
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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2291
Chart for applicable amount of fertilizers.
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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2292
Cost analysis of irrigation controller unit.
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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2293
Run times of two algorithms.
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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2294
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2295
Flow chart of Fuzzy Logic based control system.
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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2296
Block diagram for IoT-based irrigation system.
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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2297
Flow chart of Average Value-based control system.
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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2298
Hardware design for IoT-based irrigation system.
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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2299
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2300