Fitting Volume Models for Parana Pine With a Nonlinear Regression, Genetic Algorithm and Simulated Annealing

Improving volumetric quantification of Parana pine (Araucaria angustifolia) in Mixed Ombrophilous Forest is a constant need in order to provide accurate and timely information on current and future growing stock to ensure forest management. Thus, the present study aimed to evaluate and compare the volume estimates obtained through Nonlinear Regression (NR), Genetic Algorithm (GA) and Simulated Annealing (SA) in order to generate accurate volume estimates. Volumetric equations were developed including the independent variables diameter at breast height (dbh), total height (h) and crown rate (cr) and from the fit through the NR, GA and SA approaches. The GA and SA approaches evaluated proved to be a reliable optimization strategy for parameter estimation in Parana pine volumetric modelling, however, no significant differences were found in comparison with the NR approach. This study therefore contributes through the generation of robust equations that could be used for accurate estimates of the volume of the Parana pine in southern Brazil, thus supporting the planning and establishment of management and conservation actions.

Analysis of the Traffic Parameters on a Section in the City of the National Road during Several Years of Operation

The study carried out an analysis of the vehicle traffic parameters on a national road in 2011-2016. The variability and uncertainty of results were evaluated. An analysis of traffic data recorded on the city's entry and exit lanes was carried out. The variations in traffic volume are of interest e.g. in dynamic traffic management systems and navigation services, examining the benefits of flexible work time and places and assessing the environmental effects of traffic congestion. Research has shown that the assumption that lanes perform equally is not always true. Traffic volume models should be periodically calibrated taking into account the shape of the daily profile, which may, for example, allow public transport timetables to be more responsive to the needs of travelers.

Individual Tree Structural Parameter Extraction and Volume Table Creation Based on Near-Field LiDAR Data: A Case Study in a Subtropical Planted Forest

Individual tree structural parameters are vital for precision silviculture in planted forests. This study used near-field LiDAR (light detection and ranging) data (i.e., unmanned aerial vehicle laser scanning (ULS) and ground backpack laser scanning (BLS)) to extract individual tree structural parameters and fit volume models in subtropical planted forests in southeastern China. To do this, firstly, the tree height was acquired from ULS data and the diameter at breast height (DBH) was acquired from BLS data by using individual tree segmentation algorithms. Secondly, point clouds of the complete forest canopy were obtained through the combination of ULS and BLS data. Finally, five tree taper models were fitted using the LiDAR-extracted structural parameters of each tree, and then the optimal taper model was selected. Moreover, standard volume models were used to calculate the stand volume; then, standing timber volume tables were created for dawn redwood and poplar. The extraction of individual tree structural parameters exhibited good performance. The volume model had a good performance in calculating the standing volume for dawn redwood and poplar. Our results demonstrate that near-field LiDAR has a strong capability of extracting tree structural parameters and creating volume tables for subtropical planted forests.

FORM FACTORS AND VOLUME MODELS FOR ESTIMATING TREE BOLE VOLUME OF MAHOGANY AT COMMUNITY FORESTS IN CENTRAL JAVA

Form factors and volume models are often be used in the estimation of tree volumes. However, a few studies have developed and evaluated the accuracy of form factors and volume models for estimating tree volumes of community forests. This study aimed to formulate form factors and volume models and assess their prediction accuracy for estimating tree bole volumes of mahogany at community forests in Central Java. This study used 120 sample trees with diameters of 6–38 cm to formulate artificial and absolute form factors and to develop tree bole volume models. These form factors coupled with bole height and total height were used in simple volume equations. Regression analyses were used to develop volume models using the diameter and total height as predictors. The simple volume equations and volume models' prediction accuracy was evaluated using a cross-validation dataset and independent dataset (30 sample trees). The artificial form factor (0.68 ± 0.11) of mahogany, which was higher than the absolute form factor (0.46 ± 0.09), provided accurate estimates of tree bole volumes when it was used with the bole height instead of the total height. The volume model that uses diameter and total height produced the most accurate estimates, while the volume model that uses diameter alone provided the most practical yet reliable tool for estimating tree bole volumes of mahogany. The results of this study are useful for improving community forest management.

Charting Brain Growth and Aging at High Spatial Precision

Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and use normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1,985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision making.

Real Color Model of a Cadaver for Deep Brain Stimulation of the Subthalamic Nucleus

When performing deep brain stimulation (DBS) of the subthalamic nucleus, practitioners should interpret the magnetic resonance images (MRI) correctly so they can place the DBS electrode accurately at the target without damaging the other structures. The aim of this study is to provide a real color volume model of a cadaver head that would help medical students and practitioners to better understand the sectional anatomy of DBS surgery. Sectioned images of a cadaver head were reconstructed into a real color volume model with a voxel size of 0.5 mm × 0.5 mm × 0.5 mm. According to preoperative MRIs and postoperative computed tomographys (CT) of 31 patients, a virtual DBS electrode was rendered on the volume model of a cadaver. The volume model was sectioned at the classical and oblique planes to produce real color images. In addition, segmented images of a cadaver head were formed into volume models. On the classical and oblique planes, the anatomical structures around the course of the DBS electrode were identified. The entry point, waypoint, target point, and nearby structures where the DBS electrode could be misplaced were also elucidated. The oblique planes could be understood concretely by comparing the volume model of the sectioned images with that of the segmented images. The real color and high resolution of the volume model enabled observations of minute structures even on the oblique planes. The volume models can be downloaded by users to be correlated with other patients’ data for grasping the anatomical orientation.

Evaluation of Compatible Taper and Volume Models for Combretum hartmannianum and Lonchocarpus laxiflorus Tree Species.

This paper developed and evaluated the performance of the current functional tree taper and volume models. The models were applied to some selected economically important natural tree species common to central Sudan, namely, Combretum hartmannianum and, Lonchocarpus Laxiflorus. The tree variables measured were the diameter at breast height (DBH, cm), diameter at the base of the tree (d0, cm), upper stem diameters (di), total tree height (H), and height to the base of the crown (Hb). In total, 19 taper and 32 volume models were tested and evaluated (22 models were two-variable models (Diameter at breast height and total tree height or bole height) and 10 were three-variable models (Diameter at ground level, Diameter at breast height and total tree height or bole height). The model goodness of fit was evaluated in terms of adjusted coefficient of determination (Ra2), standard error (SE), mean absolute residual (MAR), bias (BI) Akaike’s information criterion (AIC), homogeneity of the residuals and significance of the regression parameters. As far as taper models is concerned, Models, some of the models were found to yield satisfactory results for the tow selected species with R2 range of 0.94 – 0.96. For the within species variation of models on the basis of the AIC values, the ranking of the models (smaller AIC first) were in consistant with the rankings due to SE and Ra2 values although AIC penalizes models in proportion to the number regression parameters. In general the results of the study indicated that higher residuals valuse are in most of the cases associated with the lower parts of the bole, the butress portion of the stem. This suggests that care should be taken during the application of such models for hardwood species, especially in open woodlands where butress is a common characteristic.The results for volume models revealed differences in the behaviour of different models for each species as the degree of significance of the regression parameters varies between tree species. However, the replacement of the total tree height by the bole height (merchantable height) improves both the level of parameter significance and the coefficient of determination. The results also reveal that inclusion of diameter at grown level to the original two variables (DBH, Ht) and the replacement of the original model total height with the bale height results in quite significant improvement of the Ra2 values. In general, the study concluded that taper and volume models can provide precise and accurate estimation of tree growth variables for the studied species with reasonable cost and time, but care should be taken when dealing with same model for the same species across varying growth and management condition, or when dealing with different species. country.

Impact of stem lean on estimation of Douglas-fir (Pseudotsuga menziesii) diameter and volume using mobile lidar scans

The value of Douglas-fir (Pseudotsuga menziesii), which is the predominant commercial species in the Pacific Northwest, depends on tree verticality; trees with same dimensions can differ substantially in value due to lean. The objective of this study was to assess the impact of tree leaning on estimation of stem dimensions using high density terrestrial mobile lidar point clouds. We estimated lean with two metrics: the horizontal distance between stem centers at 1.3m and 18m, and the mean of seven successive lean angles along the tree bole (at 1, 3, 5, 7, 10, 12, and 15m). For modeling, we used four existing taper equations and three existing volume equations. For trees leaning >2º, we enhanced the existing volume models by including lean as a predictor. Because lean estimates depend on the distribution and number of points describing the stem, we found that including the distance from scanner to tree improved the computed volume. When DBH was replaced with diameter at heights between 7 - 10m, the volume models for leaning trees improved significantly, whereas the vertical trees had favorable results with heights between 5-15m. Our study suggests the inclusion of lean magnitude improves estimates of stem volume when lean is >2°.

Optimization and parallelization of the discrete ordinate method for radiation transport simulation in OpenFOAM: Hierarchical combination of shared and distributed memory approaches

This paper describes the reduction in memory and computational time for the simulation of complex radiation transport problems with the discrete ordinate method (DOM) model in the open-source computational fluid dynamics platform OpenFOAM. Finite volume models require storage of vector variables in each spatial cell; DOM introduces two additional discretizations, in direction and wavelength, making memory a limiting factor. Using specific classes for radiation sources data, changing the store of fluxes and other minor changes allowed a reduction of 75% in memory requirements. Besides, a hierarchical parallelization was developed, where each node of the standard parallelization uses several computing threads, allowing higher speed and scalability of the problem. This architecture, combined with optimization of some parts of the code, allowed a global speedup of x15. This relevant reduction in time and memory of radiation transport opens a new horizon of applications previously unaffordable.