Development and validation of a practical machine-learning triage algorithm for the detection of patients in need of critical care in the emergency department

Identifying critically ill patients is a key challenge in emergency department (ED) triage. Mis-triage errors are still widespread in triage systems around the world. Here, we present a machine learning system (MLS) to assist ED triage officers better recognize critically ill patients and provide a text-based explanation of the MLS recommendation. To derive the MLS, an existing dataset of 22,272 patient encounters from 2012 to 2019 from our institution’s electronic emergency triage system (EETS) was used for algorithm training and validation. The area under the receiver operating characteristic curve (AUC) was 0.875 ± 0.006 (CI:95%) in retrospective dataset using fivefold cross validation, higher than that of reference model (0.843 ± 0.005 (CI:95%)). In the prospective cohort study, compared to the traditional triage system’s 1.2% mis-triage rate, the mis-triage rate in the MLS-assisted group was 0.9%. This MLS method with a real-time explanation for triage officers was able to lower the mis-triage rate of critically ill ED patients.

Experimental Investigation of Heavy Oil Emulsion Stability: the Effect of Various Physicochemical Parameters

The formation of stable heavy oil emulsion, which may upset separation facilities and eventually lead to production impairment, is one of the most common issues encountered in the development of heavy oil reservoirs. This paper investigates the influence of various physicochemical parameters, including water cut, polymer status (sheared/unsheared), polymer concentration, demulsifier type and concentration, and the coexistence of polymer and demulsifiers on the stability of heavy oil emulsion. The viscosity of heavy oil emulsion is also studied at various water cut and polymer concentration. In this study, water-in-heavy oil emulsion was prepared at the water cut of 30% as the blank sample using heavy oil with API gravity of 14.5° and the synthetic brine. The effect of the water cut was investigated by both the bottle test method and multiple light scattering (MLS) method to validate the effectiveness and reliability of the MLS method. The other parameters were studied only through the MLS method. The results showed that the increasing water cut resulted in the decrease of heavy oil emulsion stability and could potentially invert the stable w/o emulsion to loose o/w emulsion at the phase inversion point where the emulsion viscosity peak occurred. Adding polymer, regardless of the polymer status, tended to reduce the stability of heavy oil emulsion, and the unsheared polymer contributed to less emulsion stability. However, the influence of polymer concentration was rather complicated. The emulsion stability decreased as polymer concentration increased, and further increasing polymer concentration enhanced the emulsion stability. A similar trend was also evidenced by emulsion viscosity with increasing polymer concentration. The addition of three oil-soluble emulsion breakers was able to break the heavy oil emulsion efficiently, whereas the water-soluble demulsifier had little demulsification effect. Furthermore, there existed an optimal concentration for the selected oil-soluble demulsifier to achieve the maximum separation. Although polymer itself could intensify the destabilization of heavy oil emulsion, it hindered the destabilization process of the heavy oil emulsion when the oil-soluble demulsifiers were added. This study will provide a comprehensive understanding of the factors affecting heavy oil emulsion stability.

Application of moving least squares algorithm for solving systems of Volterra integral equations

The numerical method developed in the current paper is based on the moving least squares (MLS) method. To this end, the MLS approximation method has been used, and a program has been made which can solve the system of Volterra integral equations (VIEs) with any number of equations and unknown functions. And then the proposed method is implemented on the system of linear VIEs with variable coefficients. The numerical examples are given that show the acceptable accuracy and efficiency of the proposed scheme.

3D GEOSPATIAL TECHNIQUE IN ANALYSING THE MALAY HERITAGE BUILDING STRUCTURES

Malay buildings are synonym with the unique design of full decorative on motive, unique façade design, and roof structured. Most of heritage buildings had been demolished and left out without proper documentation and preserving the building database. Latest mapping systems provide an efficient technique for acquiring dense point clouds in analysing the building structure. This paper aim to explore on the technique acquiring the data for distribution and the façade of building with the Malay architecture design using the laser scanning. Data acquisition was taken for two sites which are Kota Bharu, Kelantan and Alor Setar, Kedah with two different techniques were applied for data collection which are TLS and MLS method. Both methods had succeed in capturing the detail of the features and building in the study area in point cloud form and the analysis of the data was able to analysed on the classification and identification of the Malay building elements and features which still preserved Malay design at the facade and roof element in the study area. As the final results and findings, there were big gaps between the building which still preserved the Malay design in the study area where Kota Bharu recorded 71 units building meanwhile Alor Setar only 15 buildings. The results showed that, most of the Traditional Malay building still being preserved in Kota Bharu compared to Alor Setar.

An Accurate Image Measurement Method Based on a Laser-Based Virtual Scale

Image measurement methods have been widely used in broad areas due to their accuracy and efficiency. However, current techniques usually involve complex calibration, an elaborate optical design, or sensitivity to the test environment. In this paper, a simple optical device was designed to emit parallel beams to obtain a virtual scale for measurement purposes. The proposed theory ensures the robustness of the system when obtaining each scale in the presence of uncertainty. The scale creates a mapping from image coordinates to world coordinates. By using the moving least squares (MLS) method, a full-field scale map can be reconstructed to achieve high-precision measurement at the sub-pixel level. Experimental verifications are carried out, showing that the proposed method provides very accurate and reliable results. The proposed approach is simple in terms of equipment, and the scale can be automatically calculated. Therefore, the system proposed in this paper is a promising candidate as a tool for non-contacting measurements (e.g., the crack development, geometric size) in the inaccessible structures such as high-rise buildings and long-span bridges.

Development of low-cost mobile laser scanning for 3D construction indoor mapping by using inertial measurement unit, ultra-wide band and 2D laser scanner

Purpose The purpose of this paper is to introduce the development of an innovative mobile laser scanning (MLS) method for 3D indoor mapping. The generally accepted and used procedure for this type of mapping is usually performed using static terrestrial laser scanning (TLS) which is high-cost and time-consuming. Compared with conventional TLS, the developed method proposes a new idea with advantages of low-cost, high mobility and time saving on the implementation of a 3D indoor mapping. Design/methodology/approach This method integrates a low-cost 2D laser scanner with two indoor positioning techniques – ultra-wide band (UWB) and an inertial measurement unit (IMU), to implement a 3D MLS for reality captures from an experimental indoor environment through developed programming algorithms. In addition, a reference experiment by using conventional TLS was also conducted under the same conditions for scan result comparison to validate the feasibility of the developed method. Findings The findings include: preset UWB system integrated with a low-cost IMU can provide a reliable positioning method for indoor environment; scan results from a portable 2D laser scanner integrated with a motion trajectory from the IMU/UWB positioning approach is able to generate a 3D point cloud based in an indoor environment; and the limitations on hardware, accuracy, automation and the positioning approach are also summarized in this study. Research limitations/implications As the main advantage of the developed method is low-cost, it may limit the automation of the method due to the consideration of the cost control. Robotic carriers and higher-performance 2D laser scanners can be applied to realize panoramic and higher-quality scan results for improvements of the method. Practical implications Moreover, during the practical application, the UWB system can be disturbed by variances of the indoor environment, which can affect the positioning accuracy in practice. More advanced algorithms are also needed to optimize the automatic data processing for reducing errors caused by manual operations. Originality/value The development of this MLS method provides a novel idea that integrates data from heterogeneous systems or sensors to realize a practical aim of indoor mapping, and meanwhile promote the current laser scanning technology to a lower-cost, more flexible, more portable and less time-consuming trend.

Effect of DEM Interpolation Neighbourhood on Terrain Factors

Topographic factors such as slope and aspect are essential parameters in depicting the structure and morphology of a terrain surface. We study the effect of the number of points in the neighbourhood of a digital elevation model (DEM) interpolation method on mean slope, mean aspect, and RMSEs of slope and aspect from the interpolated DEM. As the moving least squares (MLS) method can maintain the inherent properties and other characteristics of a surface, this method is chosen for DEM interpolation. Three areas containing different types of topographic features are selected for study. Simulated data from a Gauss surface is also used for comparison. First, the impact of the number of points on the DEM root mean square error (RMSE) is analysed. The DEM RMSE in the three study areas decreases gradually with the number of points in the neighbourhood. In addition, the effect of the number of points in the neighbourhood on mean slope and mean aspect was studied across varying topographies through regression analysis. The two variables respond differently to changes in terrain. However, the RMSEs of the slope and aspect in all study areas are logarithmically related to the number of points in the neighbourhood and the values decrease uniformly as the number of points in the neighbourhood increases. With more points in the neighbourhood, the RMSEs of the slope and aspect are not sensitive to topography differences and the same trends are observed for the three studied quantities. Results for the Gauss surface are similar. Finally, this study analyses the spatial distribution of slope and aspect errors. The slope error is concentrated in ridges, valleys, steep-slope areas, and ditch edges while the aspect error is concentrated in ridges, valleys, and flat regions. With more points in the neighbourhood, the number of grid cells in which the slope error is greater than 15° is gradually reduced. With similar terrain types and data sources, if the calculation efficiency is not a concern, sufficient points in the spatial autocorrelation range should be analysed in the neighbourhood to maximize the accuracy of the slope and aspect. However, selecting between 10 and 12 points in the neighbourhood is economical.

Reduction Method for Mobile Laser Scanning Data

Mobile Laser Scanning (MLS) technology acquires a huge volume of data in a very short time. In many cases, it is reasonable to reduce the size of the dataset with eliminating points in such a way that the datasets, after reduction, meet specific optimization criteria. Various methods exist to decrease the size of point cloud, such as raw data reduction, Digital Terrain Model (DTM) generalization or generation of regular grid. These methods have been successfully applied on data captured from Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS), however, they have not been fully analyzed on data captured by an MLS system. The paper presents our new approach, called the Optimum Single MLS Dataset method (OptD-single-MLS), which is an algorithm for MLS data reduction. The tests were carried out in two variants: (1) for raw sensory measurements and (2) for a georeferenced 3D point cloud. We found that the OptD-single-MLS method provides a good solution in both variants; therefore, the choice of the reduction variant depends only on the user.

A Moving-Least-Square Immersed Boundary Method for Rigid and Deformable Boundaries in Viscous Flow

We present a moving-least-square immersed boundary method for solving viscous incompressible flow involving deformable and rigid boundaries on a uniform Cartesian grid. For rigid boundaries, noslip conditions at the rigid interfaces are enforced using the immersed-boundary direct-forcing method. We propose a reconstruction approach that utilizes moving least squares (MLS) method to reconstruct the velocity at the forcing points in the vicinity of the rigid boundaries. For deformable boundaries, MLS method is employed to construct the interpolation and distribution operators for the immersed boundary points in the vicinity of the rigid boundaries instead of using discrete delta functions. The MLS approach allows us to avoid distributing the Lagrangian forces into the solid domains as well as to avoid using the velocity of points inside the solid domains to compute the velocity of the deformable boundaries. The present numerical technique has been validated by several examples including a Poiseuille flow in a tube, deformations of elastic capsules in shear flow and dynamics of red-blood cell in microfluidic devices.