Shoulder pain and injury are highly prevalent among manual wheelchair users with spinal cord injury (SCI) [18]. The consequences of upper extremity (UE) pain are significant because manual wheelchair users rely on their arms for mobility and independence. Specific biomechanical parameters of wheelchair propulsion such as cadence, magnitude of force, and pattern of the hand during the no propuls...

Determining the appropriate dosage of warfarin is an important yet challenging task. Several prediction models have been proposed to estimate a therapeutic dose for patients. The models are either clinical models which contain clinical and demographic variables or pharmacogenetic models which additionally contain the genetic variables. In this paper, a new methodology for warfarin dosing is pro...

GNSS time series for static reference stations record the deformation of monitored targets. However, missing data are very common in monitoring because receiver crashes, power failures, etc. In this paper, we propose a Temporal and Spatial Hankel Matrix Factorization (TSHMF) method that can simultaneously consider temporal correlation single spatial among different stations. Moreover, is verifi...

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected ...

Construction projects are often subject to scheduling errors caused by uncertainty and systematic planning fallacies. This paper evaluates the prediction accuracy of CatBoost expert intuition predict duration public construction in predesign phase. The authors use a dataset city New York (USA) with 367 projects. Both compared performance indicator Mean Absolute Error (MAE) absolute preferrence....

The air temperature is an essential variable in many applications related to Earth science. Sporadic spatial distribution of weather stations causes a low spatial resolution of measured air temperatures. This study focused on modeling the air diurnal temperature cycle (DTC) based on the land surface temperature (LST) DTC. The air DTC model parameters were estimated from LST DTC model parameters...

common heat transfer fluids such as water, ethylene glycol, and engine oil have limited heat transfer capabilities due to their low heat transfer properties. nanofluids are suspensions of nanoparticles in base fluids, a new challenge for thermal sciences provided by nanotechnology. in this study, we are to optimize and report the effects of various parameters such as the ratio of the thermal co...

This paper develops ensemble machine learning models (XGBoost, Gradient Boosting, and AdaBoost in addition to Random Forest) for predicting stock returns of Indian banks using technical indicators. These indicators are based on three broad categories analysis: Price, Volume, Turnover. Various error metrics like Mean Absolute Error (MAE), Squared (MSE), Percentage (MAPE), Root-Mean-Squared-Error...

Robust variants of nonlinear canonical correlation analysis (NLCCA) are introduced to improve performance on datasets with low signal-to-noise ratios, for example those encountered when making seasonal climate forecasts. The neural network model architecture of standard NLCCA is kept intact, but the cost functions used to set the model parameters are replaced with more robust variants. The Pear...

This is the second paper of a two part tutorial on the fundamentals of univariate time series ltering using order statistics where both temporal and rank orderings are considered jointly This second paper focuses on order statistic selection lters where the lter output is restricted to be one of the input samples In particular we treat class of Weighted Order Statistic WOS lters and the more ge...