Hull Methods Research Articles

Comparison of Kernel Density and Local Convex Hull Methods for Assessing Distribution Ranges of Large Mammalian Herbivores

AbstractWhen assessing distribution range shifts, precise information is required on distribution limits, densities in occupied regions, unoccupied gaps, and changes in these measures over time. The local convex hull method recently developed for home range delineation to provide these measures was compared with that of the widely applied parametric kernel density estimation and with the commonly used tile method. The assessment used location records from 14 years of aerial surveys on four mammalian herbivores selected because of their distinct distribution patterns. Impala showed an almost continuous distribution with few gaps, wildebeest a wide distribution with regional concentrations, waterbuck a linear distribution along rivers, and sable antelope a widespread but patchy distribution. The kernel method tended to extend ranges beyond observed records, obscuring gaps within distributions. With parametric kernel approaches, bandwidth obtained via Least Squares Cross Validation techniques was not optimal when the local abundance was widely disparate, as was the case for wildebeest. The LoCoH method most effectively revealed meaningful gaps. The LoCoH method is advantageous for precisely mapping the distributions of conspicuous species for which the absence of records indicates true gaps in occurrence.

Home range and diving behaviour of Heaviside's dolphins monitored by satellite off the west coast of South Africa

Three Heaviside's dolphins Cephalorhynchus heavisidii were fitted with satellite depth recorders off the west coast of South Africa during February–April 1997 and monitored for 51, 73 and 130 days, respectively. In total, 345 locations were received from the three animals, but only 27 from one male. Using α-local convex hull and minimum convex polygon methods, respectively, the home range for the remaining male was estimated at 1 520 and 2 347 km2, with corresponding core-area estimates (50% of locations) of 134 and 123 km2. For the female, the home range estimates were 672 and 1 027 km2, and those for the core area were 71 and 230 km2. The female's home range was the smallest yet described for this species, and the animal was resighted nearly three years later within 13 km of the tagging site. Binned dive data were received at 6-hourly intervals. From comparison of maximum dive depth and time-at-depth data, we concluded that dives <4 m deep were associated with surfacing bouts. Dives to below 4 m occurred throughout 24 h but were shallower during the day and deepest either at dusk or at night. This pattern was consistent with earlier descriptions of offshore movement during the day and may be related to the diel vertical migration of its principal prey, shallow-water hake Merluccius capensis.

Approximate convex skyline: A partitioned layer-based index for efficient processing top-k queries

A top-k query returns k tuples with the highest (or the lowest) scores from a relation. Layer-based methods are the representative ones for processing top-k queries efficiently. These methods construct a list of layers, where the ith layer contains the tuples that can potentially be the top-i answer. Thus, the layer-based methods can answer top-k queries by reading at most k layers. To construct layers, the existing layer-based methods use convex skyline, convex hull or skyline methods. Among them, the convex skyline is constructed by computing the convex hull over the skyline. Accordingly, the layer size of the convex skyline is relatively smaller than those of the convex hull, and the index building time is relatively shorter than those of the skyline. However, for large and high-dimensional databases, the convex skyline suffers from long index building time and large memory usage, because most objects can become the skyline points. This paper focuses on how to build an index, which contains a smaller number of objects comparing to the skyline and uses less time to construct an index comparing to the convex skyline. Specifically, we propose a method, called the Approximate Convex Skyline Enhanced (simply, AppCSE), which reduces the index building time and memory usage of the convex skyline. In the proposed method, we first construct the skyline, and then, partition the region of the skyline into multiple subregions, and compute the convex hull in each subregion with virtual objects. After that, AppCSE combines the objects obtained by computing the convex hull. Through various experiments with synthetic and real datasets, we demonstrate that the proposed method significantly reduces the index building time and memory usage comparing to the existing methods. In addition, we show that the degradation of query performance is negligible when using AppCSE as the layering scheme.

Reference technology sets, Free Disposal Hulls and productivity decompositions

Diewert and Fox (2013) proposed decompositions of a Malmquist-type productivity index into explanatory factors, with a focus on extracting technical progress, technical efficiency change and returns to scale components. A major problem with their decompositions is that it may be difficult to determine the appropriate reference technologies. Using relatively unrestrictive regularity conditions, the paper develops a data envelopment type approach for decomposing productivity growth for a panel of production units into explanatory factors based on the Free Disposal Hull methods pioneered by Tulkens and his co-authors.

Prediction of non-proportionality factors of multiaxial histories using the Moment Of Inertia method

This work studies further an approach originally proposed to evaluate equivalent stress and strain ranges in non-proportional (NP) load histories, called the Moment Of Inertia (MOI) method. The MOI method assumes that the path contour in the deviatoric stress or strain diagram is a homogeneous wire with unit mass. The center of mass of such wire gives then the mean component of the path, while the moments of inertia of the wire can be used to obtain the equivalent stress or strain ranges. The MOI method is an alternative to convex enclosure methods, such as Dang Van’s Minimum Ball or the Maximum Prismatic Hull methods, without the need for computationally-intensive search algorithms or adjustable parameters. The MOI method is extended here to calculate as well the non-proportionality factor Fnp of generic multiaxial load histories, formulated in an alternative sub-space of the deviatoric plastic strains. Experimental results for 14 different multiaxial histories prove the effectiveness of the MOI method to predict the observed non-proportionality factors. Hence, it can be a most useful tool for the computation of multiaxial fatigue damage in practical applications.

On the comparative performance of socially responsible and Islamic mutual funds

This is the first study to provide comprehensive analyses of the relative performance of both socially responsible investment (SRI) and Islamic mutual funds. The analysis proceeds in two stages. In the first, the performance of the two categories of funds is measured using partial frontier methods. In the second stage, we use quantile regression techniques. By combining two variants of the Free Disposal Hull (FDH) methods (order-m and order-α) in the first stage of analysis and quantile regression in the second stage, we provide detailed analyses of the impact of different covariates across methods and across different quantiles. In spite of the differences in the screening criteria and portfolio management of both types of funds, variation in the performance is only found for some of the quantiles of the conditional distribution of mutual fund performance. We established that for the most inefficient funds the superior performance of SRI funds is significant. In contrast, for the best mutual funds this evidence vanished and even Islamic funds perform better than SRI. These results show the benefits of performing the analysis using quantile regression.

Hull-voxel reconstruction of images as a means of structural analysis

Conventional X-ray tomography is an effective tool of medical diagnostics, nondestructive testing of engineering structures, and technical diagnostics of manufactured products. Tomographic reconstruction of objects is a strongly incorrect inverse problem in the case of limited vision angle, small number of projections, and/or insufficient X-ray source energy. Hull and hull-voxel methods of tomographic reconstruction of piecewise-uniform objects are considered in this paper. These approaches are quite effective for image reconstruction of industrial and biological objects under conditions of sparse input data and for analyzing binary and piecewise-uniform images. It will be a priori assumed that the object being reconstructed consists of areas with constant attenuation coefficients.

A scaled line-based kernel density estimator for the retrieval of utilization distributions and home ranges from GPS movement tracks

Utilization distributions (UDs) can be used to describe the intensity with which an animal or human has used a certain geographical location. Within the domain of wildlife ecology, a density distribution model represents one way to describe an animals' home range. Several methods have been developed to derive UDs, and subsequently home ranges. Most of these methods, e.g. kernel density estimation (KDE), and local convex hull methods, have been developed with point-based datasets in mind, and do not utilize additional information that comes with GPS-based tracking data (e.g., temporal information). To employ such additional information we extend the point-based KDE approach to work with sequential GPS-point tracks, the outcome of which is a line-based KDE. We first describe the design criteria for the line-KDE algorithm. Then we introduce the basic modeling approach and its refinement through the introduction of a scaling function. This scaling function modifies the utilization distribution so that a bone-like probability distribution for a single GPS track segment is obtained. Finally we compare the estimated utilization distributions and home ranges for two datasets derived using our line-KDE approach with those obtained using the point-KDE and Brownian Bridge (BB) approaches. Advantages of the line-based KDE by design are (i) a better representation of utilization density near GPS points when compared against the BB approach, and (ii) the ability to model and retain movement corridors when compared against point-KDE.

Fractional coverage metrics based on ecological home range for calculation of the effective peak capacity in comprehensive two-dimensional separations

Optimization of comprehensive two-dimensional separations frequently relies on the assessment of the peak capacity of the system. A correction is required for the fact that many pairs of separation systems are to some degree correlated, and consequently the entire separation space is not chemically accessible to solutes. This correction is essentially a measure of the fraction of separation space area where the solutes may elute. No agreement exists in the literature as to the best form of the spatial coverage factor. In this work, we distinguish between spatial coverage factors that measure the maximum occupiable space, which is characteristic of the separation dimensionality, and the space actually occupied by a particular sample, which is characteristic of the sample dimensionality. It is argued that the former, which we call fcoverage, is important to calculating the peak capacity. We propose five criteria for a good fcoverage metric and use them to evaluate various area determination methods that are used to measure animal home ranges in ecology. We consider minimum convex hulls, convex hull peels, α-hulls, three variations of local hull methods, and a kernel method and compare the results to the intuitively satisfying but subjective Stoll–Gilar method. The most promising methods are evaluated using two experimental LC×LC data sets, one with fixed separation chemistry but variable gradient times, and a second with variable first dimension column chemistry. For the 12 separations in the first data set, in which fcoverage is expected to be constant, the minimum convex hull is the most precise method (fcoverage=0.68±0.04) that gives similar results to the Stoll–Gilar method (fcoverage=0.67±0.06). The minimum convex hull is proposed as the best method for calculating fcoverage, because it has no adjustable parameters, can be scaled to different retention time normalizations, is easily calculated using available software, and represents the expected area of solute occupation based on a proposed linear free energy formalism.

An IKONOS-based comparison of methods to estimate cattle home ranges in a semi-arid landscape of southern Africa

We estimated home range (HR) and core areas of cattle herds in a semi-arid rangeland in southern Africa using the fixed kernel and the local convex hull (LoCoH) methods. We also compared the HR values of the two methods with the aid of high spatial resolution IKONOS imagery. We also compared area estimates determined by the two methods at different probability contours of the utilization distribution (UD). Results showed that the LoCoH performed better than the kernel method in estimating UD. We found significant (p < 0.05) differences concerning the area estimated at each probability contour of the UD between the fixed kernel and LoCoH methods. However, both methods produced similar land cover preferences within the HR and core areas. Based on IKONOS-imagery-aided evaluation, our results imply that LoCoH determines core areas in HR analysis better than the kernel method, while both methods can be used in preference analysis.

Comparing isotopic niche widths among and within communities: SIBER - Stable Isotope Bayesian Ellipses in R

1. The use of stable isotope data to infer characteristics of community structure and niche width of community members has become increasingly common. Although these developments have provided ecologists with new perspectives, their full impact has been hampered by an inability to statistically compare individual communities using descriptive metrics. 2. We solve these issues by reformulating the metrics in a Bayesian framework. This reformulation takes account of uncertainty in the sampled data and naturally incorporates error arising from the sampling process, propagating it through to the derived metrics. 3. Furthermore, we develop novel multivariate ellipse-based metrics as an alternative to the currently employed Convex Hull methods when applied to single community members. We show that unlike Convex Hulls, the ellipses are unbiased with respect to sample size, and their estimation via Bayesian inference allows robust comparison to be made among data sets comprising different sample sizes. 4. These new metrics, which we call SIBER (Stable Isotope Bayesian Ellipses in R), open up more avenues for direct comparison of isotopic niches across communities. The computational code to calculate the new metrics is implemented in the free-to-download package Stable Isotope Analysis for the R statistical environment.

Seaport performance analysis using robust non-parametric efficiency estimators

Seaport services have been developing year on year, playing an increasingly important role in the economy and the transportation markets of each country. This increases interest in measuring their performance. This paper evaluates the performance of a set of European seaports by means of robust non-parametric approaches. Using order-m and bootstrap procedures, the major problems of traditional data envelopment analysis and free disposal hull methods – concerning noise, presence of outliers and the ‘curse of dimensionality’ – are overcome. With this study considerable levels of inefficiency were found in the European seaports sector.

Comparison of Improved Slope Uniform Theory of Diffraction with Some Geometrical Optic and Physical Optic Methods for Multiple Building Diffractions

This article presents a review of diffraction algorithms based on the uniform theory of diffraction for multiple building transition zone diffractions and proposes an improved uniform theory of diffraction model for fast and more accurate field prediction for multiple diffractions. The proposed method is based on the improved version of the slope uniform theory of diffraction and Fresnel zone concept, called the slope uniform theory of diffraction with convex hull. This article also provides a comparison for uniform theory of diffraction based algorithms and discusses the results for computation time and accuracy. Furthermore, the slope uniform theory of diffraction and the slope uniform theory of diffraction with convex hull methods are compared with a physical optics solution based on numerical computation of the Kirchhoff-Huygens integrals. Results of extensive simulations are presented and discussed for the development of fast and accurate radio network planning tools.

Shield fields

We describe a unified representation of occluders in light transport and photography using shield fields: the 4D attenuation function which acts on any light field incident on an occluder. Our key theoretical result is that shield fields can be used to decouple the effects of occluders and incident illumination. We first describe the properties of shield fields in the frequency-domain and briefly analyze the "forward" problem of efficiently computing cast shadows. Afterwards, we apply the shield field signal-processing framework to make several new observations regarding the "inverse" problem of reconstructing 3D occluders from cast shadows -- extending previous work on shape-from-silhouette and visual hull methods. From this analysis we develop the first single-camera, single-shot approach to capture visual hulls without requiring moving or programmable illumination. We analyze several competing camera designs, ultimately leading to the development of a new large-format, mask-based light field camera that exploits optimal tiled-broadband codes for light-efficient shield field capture. We conclude by presenting a detailed experimental analysis of shield field capture and 3D occluder reconstruction.

Feasible region approximation: a comparison of search cone and convex hull methods

The concept of the design space encapsulates the search for optimal design configurations of engineering systems. During this search, infeasible or unsafe regions may be encountered, representing particular combinations of parameter values which cause the system to fail. These regions need to be characterized so that they can be avoided during the search for improved designs. In addition, the proximity of a design to a feasible boundary may be related to the reliability and robustness of the design in the face of variation in manufacture and use. A chemical engineering example is used to show how feasible design regions can be modelled using integer lattices and kriging methods. An algorithm using Hilbert bases is developed and used to select points on the boundary of the feasible region with arbitrary closeness so that the properties of the kriging model are such that the model remains stable and the star-shaped necessary condition is met.

Baltic Ice Class IA를 적용한 115K Ice Tanker 개발

There are very few numbers of 115K FPP (Fixed Pitch Propulsion) Tankers for the Baltic ice class IA because the minimum power requirement of FMA (Finish- Swedish Maritime Association) needs quite large engine power and the 40 m Beam is out of calculation range of FMA minimum power requirements. The shipyard has no choice except to increase the engine power to satisfy FMA minimum power requirement Rule. And the operation cost, efficiency of hullform and its building cost are not good from the ship owners' point of view To solve this problem, the experience of ice breaking tanker development and the ice tank test results were adopted. The main idea to reduce the ice resistance is by reducing waterline angle at design load waterline. The reason behind the main idea is to reduce the ice-clearing force. Two hull forms were developed to satisfy Baltic Ice class IA. Two ice tank tests and one towing tank test was performed at MARC (Kvaener-Masa Arctic Research Center) and SSMB (Samsung Ship Model Basin) facilities, respectively. The purpose of these tests was to verify the performance in ice and open water respectively The hull form 2 shows less speed loss compared to Hull form 1 in open water operation but hull form 2 shows very good ice clearing ability. finally the Hull Form 2 satisfying Baltic ice class IA. The merit of this hull form is to use the same engine capacity and no major design changes in hull form and other related designs But the hull structure has to be changed according to the ice class grade. The difference in two hull form development methods, ice model test methods and analysis methods of ice model test will be described in this paper.

Poor correlation between published methods to predict creatinine clearance and measured creatinine clearance in asymptomatic HIV infected individuals

The purpose of this study was to evaluate the predictive ability of six published creatinine clearance (CCr) equations in healthy human immunodeficiency virus (HIV) infected individuals. A 24-h urine collection to determine CCr was done on an out patient basis in 18 subjects. Predicted CCr was compared with the measured values, and the predictive performance was assessed with percentage mean error (bias) and percentage root mean error (precision). Mean ± standard deviation measured CCr was 107 ± 35 mL/min/1.73 M2. CCr determined using each of the published equations correlated poorly with measured values. CCr determined using Hull methods was significantly different from the measured values. Though Cockcroft and Gault and Jelliffe methods had the lowest mean bias and greater precision, a significant range of difference from measured CCr was observed (-12 to + 28%). All methods over estimated the measured CCr in HIV-infected individuals. Until other approaches are developed, a 24 h urine collection may be the best approach for assessing renal function in HIV-infected individuals, especially in those receiving medications with narrow therapeutic indices that are cleared by the kidney.

CARVE-a constructive algorithm for real-valued examples

A constructive neural-network algorithm is presented. For any consistent classification task on real-valued training vectors, the algorithm constructs a feedforward network with a single hidden layer of threshold units which implements the task. The algorithm, which we call CARVE, extends the "sequential learning" algorithm of Marchand et al. from Boolean inputs to the real-valued input case, and uses convex hull methods for the determination of the network weights. The algorithm is an efficient training scheme for producing near-minimal network solutions for arbitrary classification tasks. The algorithm is applied to a number of benchmark problems including Gorman and Sejnowski's sonar data, the Monks problems and Fisher's iris data. A significant application of the constructive algorithm is in providing an initial network topology and initial weights for other neural-network training schemes and this is demonstrated by application to backpropagation.

Detection of Heat-Resistant Proteases Produced by Psychrotrophs in Refrigerated Milk

Proteases from four species of Pseudomonas were added to pasteurized milk at .18, 1.8, and 18 units of protease activity per milliliter followed by incubation at 5C for 18 days. During this period milks were analyzed every 2 days for proteolysis by methods of Hull, ninhydrin, and absorption at 280nm. Sensory analysis was done twice weekly for 18 days. There were no significant differences noted for protease activity when ninhydrin and absorption at 280nm were used; however, only 18 units protease/ml were detected by the Hull test. Sensory evaluation correlated with the Hull test data. When 50 and 500 cells/ml were added to milk, a curvilinear increase in proteolysis was noted by 11 and 13 days, respectively, for three of the four Pseudomonas species as detected by the Hull method. Heat inactivation of the proteases at 62.8°C for 30min was 0 to 73.1% and 10 to 36% as measured by the Hull and agar diffusion methods, respectively.

Spectrophotometric Assay Using o-Phthaldialdehyde for Determination of Proteolysis in Milk and Isolated Milk Proteins

A rapid, sensitive, and convenient Spectrophotometric assay was developed and characterized for measurement of proteolysis of milk proteins in buffered solutions or in milk. α-Amino groups released by hydrolysis react with ο-phthaldialdehyde and (β-mercaptoethanol to form an adduct that absorbs strongly at 340nm. The absorptivity (ɛ = 6000M−1 cm−1) is similar for all α-amino groups. Moreover, the absorptivity of the adduct with both α- and ɛ-amino groups of proteins is also similar and unaffected by local environment when proteins are denatured in sodium dodecyl sulfate. Thus, background is constant for a particular sample, and α-amino groups released by proteolysis can be quantitated accurately. Inclusion of sodium dodecyl sulfate in the assay provides a convenient way to terminate proteolysis and to insure full exposure and complete reaction of amino groups. Because all hydrolytic products are assayed, the method is more accurate than procedures that depend upon properties of aromatic residues (Hull and Lowry methods). Furthermore, the &ogr;-phthaldialdehyde Spectrophotometric assay is more rapid and convenient than methods using ninhydrin, 2,4,6-trinitrobenzenesulfonic acid, or fluorescamine. The assay proved to be especially useful for measuring proteolysis in milk from microbial culture organisms such as Streptococcus lactis C2. Because trichloroacetic acid filtrates are used, the method should be adaptable to other dairy products.