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Sediment data pertains to various hydrological variables with complex sediment hydrodynamics such as sedimentation rates which are often incompletely presented. Thus, the availability of sedimentation data is of utmost necessity for data accessibility. A comparative analysis on the missing fine sediment data imputation performance was made based on four different techniques, namely the k-Nearest Neighbourhood (k-NN), Support Vector Regression (SVR), Multiple Regression (MR), and Artificial Neural Network (ANN), under the single imputation (SI) and multiple imputation (MI) regimes. Across different missing data proportions (10%-50%), the ANN demonstrated optimal results with consistent performance metrics recorded over both SI and MI regimes. For the highest missing data proportion (50%), the ANN presented the best imputation performance with a reported root mean squared error (RMSE) 0.000882, mean absolute error (MAE) 0.000595, coefficient of determination (R2) 71%, and Kling-Gupta Efficiency (KGE) 72%. The imputation performance ranking is as follows: ANN, SVR, MR, and k-NN.

History shows that earthquakes from neighbouring countries cause great structural impacts on Malaysia. A tuned mass damper which is a damping system installed at a specific floor of a high-rise building could minimise the acceleration and dissipation of seismic energy from an earthquake. The case study is a high-rise structure scaled at 1:100, built based on an actual building’s tender drawings. The aim of this study is to investigate the dynamic response of scaled structures with one liquid tuned mass damper. There are three types of Tune Liquid Mass Damper (TLMD) being investigated in this research. TLMD of 0 g (TLMD-0), 337 g (TLMD-337) and 913 g (TLMD-913) of liquid were being installed individually on the roof service floor for dynamic load test. The findings show the scaled model with an increase in mass of TLMD caused the increase of roof top displacement by 15.56 % for TLMD-337 and 27.93 % for TLMD-913 compared to TLMD-0. This finding is due to the increase of inertial force generated by TLMD. The breakthrough of this research shows the ground displacements are reduced by 7.94 % for TLMD-337 and 5.81 % for TLMD-913 as compared to TLMD-0. In conclusion, the novelty of this research is the case study building managed to sustain Seismic Intensity until Level VII with 29.69 % of lateral acceleration reduction for TLMD-337 and 37.26 % for TLMD-913 by adopting effective water depth ratio of 0.286 and mass ratio of 0.11.