Search Results (3)

Reliable project management during planning stages of a building project is a meticulous process typically requiring sufficient precedencies. Typical construction duration estimation is based on previous cases of similar projects used to validate construction duration proposals from contractors, plan overall project duration, and set a standard for project success or failure. In cases of high-rise buildings exceeding 200 m, insufficient data commonly arise from the rarity of such projects, leading to a rough estimation of construction duration. Therefore, in this study, oversampling and data augmentation techniques derived from engineering principles, such as parametric optimization and data imbalance problems, are explored for curtain wall construction for high-rise buildings. The study was conducted in two phases. First, oversampling and data augmentation techniques, including Latin Hypercube, optimal Latin Hypercube, simple Monte Carlo, descriptive Monte Carlo, Sobol Monte Carlo, synthetic minority oversampling technique (SMOTE), and SMOTE–Tomek, were applied to 15 raw datasets collected from previous projects. The dataset was split into 8:2 for training and testing, where the mentioned techniques were applied to generate 500 virtual samples from the training data. Second, support vector regression was applied to forecast construction duration, where statistical performance criteria were applied for evaluation. The results showed that SMOTE and SMOTE–Tomek best represented the original dataset based on box plot analysis showcasing data distribution. Moreover, according to statistical performance criteria, it was found that the oversampling techniques improved the prediction performance, where Pearson correlation for linear, polynomial, and RBF increased by 0.611%, 4.232%, and 0.594%, respectively, for the best-performing sampling method. Finally, for the prediction models, probabilistic oversampling methods outperformed other methods according to the statistical performance criteria. Full article

Commiphora myrrha (T.Nees) Engl. resin extracts were prepared via immersion in extraction solvents (hot water, DMSO, hexane, ethanol, and methanol) which have various physical properties, such as different polarity and dielectric constant values. Methanolic C. myrrha (T.Nees) Engl. resin extracts showed broad antibacterial activity against isolated airborne bacteria. All methanolic C. myrrha (T.Nees) Engl. resin extracts were analyzed using GC-MS and Furanoeudesma-1,3-diene and curzerene were found as the main terpenoids. In addition, the methanolic C. myrrha (T.Nees) Engl. resin extracts were found to have antiviral activity (81.2% viral RNA inhibition) against the H1N1 influenza virus. Biochars (wood powder- and rice husk-derived) coated with C. myrrha (T.Nees) Engl. resin extracts also showed antiviral activity (22.6% and 24.3% viral RNA inhibition) due to the adsorption of terpenoids onto biochar. C. myrrha (T.Nees) Engl. resin extract using methanol as the extraction solvent is a promising agent with antibacterial and antiviral efficacy that can be utilized as a novel material via adsorption onto biochar for air filtration processes, cosmetics, fertilizers, drug delivery, and corrosion inhibition. Full article

The levels of aspartate aminotransferase (AST/GOT) and alanineaminotransferase (ALT/GPT) in serum can help people diagnose body tissues especially theheart and the liver are injured or not. This article provides a comprehensive review ofresearch activities that concentrate on AST/GOT and ALT/GPT detection techniques due totheir clinical importance. The detection techniques include colorimetric, spectrophotometric,chemiluminescence, chromatography, fluorescence and UV absorbance, radiochemical, andelectrochemical techniques. We devote the most attention on experimental principle. Insome methods a few representative devices and important conclusions are presented. Full article