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Smart management of construction and demolition (C&D) waste is imperative, and researchers have implemented machine learning for estimating waste generation. In Korea, the management of demolition waste (DW) is important due to old buildings, and it is necessary to predict the amount of DW to manage it. Thus, this study employed decision tree (DT)-based ensemble models (i.e., random forest—RF, extremely randomized trees—ET, gradient boosting machine—GBM), and extreme gradient boost—XGboost) based on data characteristics (i.e., small datasets with categorical inputs) to predict the demolition waste generation rate (DWGR) of buildings in urban redevelopment areas. As a result of the study, the RF and GBM algorithms showed better prediction performance than the ET and XGboost algorithms. Especially, RF (6 features, 450 estimators; mean, 1169.94 kg·m−2) and GBM (4 features, 300 estimators; mean, 1166.25 kg·m−2) yielded the top predictive performances. In addition, feature importance affecting DWGR was found to have a significant impact on the order of gross floor area (GFA) > location > roof material > wall material. The straightforward collection of features used here can facilitate benchmarking as a decision-making tool in demolition waste management plans for industry stakeholders and policy makers. Therefore, in the future, it is required to improve the predictive performance of the model by updating additional data and building a reliable dataset.

Objective To determine the effects of an integrated training device for strength and balance on extremity muscle strength, postural balance, and cognition in older adults using a combination with various rehabilitation training games, in which balance, strength, and cognitive training were configured in a single device.Methods This prospective study included 20 healthy participants aged 65–85 years. Participants trained for 30 minutes daily, 3 days weekly, for 6 weeks with an integrated training device for strength and balance (SBT-120; Man&Tel Inc., Gumi, Korea). Main outcomes were measured using the Korean Mini-Mental State Examination (K-MMSE), Korean version of the Montreal Cognitive Assessment (K-MoCA), Timed Up and Go Test (TUG), Functional Reach Test (FRT), Berg Balance Scale (BBS), and Manual Muscle Test. Measurements were taken at three time points: T0 (pretreatment), T1 (immediately after treatment), and T2 (4 weeks after treatment).Results All 20 patients completed the training, and TUG, FRT, and BBS scores significantly improved at T1 and T2 compared to T0. Mean TUG scores decreased by 0.99±2.00 at T1 and 1.05±1.55 at T2 compared to T0. Mean FRT scores increased by 6.13±4.26 at T1 and 6.75±4.79 at T2 compared to T0. BBS scores increased by 0.60±0.94 at T1 and 0.45±1.15 at T2 compared to T0. Moreover, muscle strength and cognition (K-MMSE and K-MoCA scores) increased after training.Conclusion Our findings suggest that an integrated training device for strength and balance can be a safe and useful tool for older adults.

Supplemental material, sj-pdf-1-imr-10.1177_03000605221104768 for Association of bladder trabeculation and neurogenic bladder with spinal cord injury by Yu Hui Won, Da-Sol Kim, Gi-Wook Kim, Sung-Hee Park, Myoung-Hwan Ko and Jeong-Hwan Seo in Journal of International Medical Research

Supplemental material, sj-pdf-1-imr-10.1177_03000605221104768 for Association of bladder trabeculation and neurogenic bladder with spinal cord injury by Yu Hui Won, Da-Sol Kim, Gi-Wook Kim, Sung-Hee Park, Myoung-Hwan Ko and Jeong-Hwan Seo in Journal of International Medical Research