Multidimensional Computer Research Articles

Numerical comparison of sampling strategies for BRDF data manifolds

Abstract The bidirectional reflectance distribution function (BRDF) is one of the fundamental concepts in such diverse fields as multidimensional reflectometry, computer graphics and computer vision. BRDF manifolds form an infinite-dimensional space, but typically the available measurements are very scarce. Therefore, an efficient learning strategy is crucial when performing the measurements. In this paper, we perform simulation studies within a mathematical framework that allows to establish more efficient BRDF sampling and measurement strategies in the sense of statistical design of experiments and generalized proactive learning. Our simulation studies suggest that the default BRDF measurement strategy is suboptimal for a wide class of loss functions.

Performance-Aware Architectures for Parallel 4D Color fMRI Filtering Algorithm: A Complete Performance Indices Package

A parallel 4D fMRI filtering algorithm is proposed to overcome the bottlenecks of large 4D volumetric fMRI data and its overlapping segments by input decimation, multidimensional intensive computation by parallel processing and the boundary conditions by output interpolation. Three spatial convolution architectures implement this parallel multidimensional filtering algorithm in Virtex-6 FPGA board, as automated 4D fMRI filtering systems. These three automated filtering systems are devised as “plug and develop” processors to filter any 4D volumetric data. Then, two sets of generic Edge and noise smoothing filtering operators are prototypically plugged and developed to be improved for filtering a dementia case study of color 256 × 256 × 4 × 3 volumetric fMRI. Accordingly, performance indices of the three architectures are evaluated as a complete package of area, speed, dynamic power, and throughput. Significant improvements have been achieved in keeping a stable speed, decreasing power consumption and increasing throughput in color fMRI filtering applications. All three architectures have an operating (225 MHz) maximum frequency. The power consumption improved more than two-fold using architecture 2 compared to 3. The highest throughput is achieved by architectures 2 and 3 almost (2.5) times than that of architecture 1. Evidently, all three architectures are performance-aware processors, and architecture 2 is optimal.

Designing a Situational Awareness Information Display: Adopting an Affordance-Based Framework to Amplify User Experience in Environmental Interaction Design

User experience remains a crucial consideration when assessing the successfulness of information visualization systems. The theory of affordances provides a robust framework for user experience design. In this article, we demonstrate a design case that employs an affordance-based framework and evaluate the information visualization display design. SolarWheels is an interactive information visualization designed for large display walls in computer network control rooms to help cybersecurity analysts become aware of network status and emerging issues. Given the critical nature of this context, the status and performance of a computer network must be precisely monitored and remedied in real time. In this study, we consider various aspects of affordances in order to amplify the user experience via visualization and interaction design. SolarWheels visualizes the multilayer multidimensional computer network issues with a series of integrated circular visualizations inspired by the metaphor of the solar system. To amplify user interaction and experience, the system provides a three-zone physical interaction that allows multiple users to interact with the system. Users can read details at different levels depending on their distance from the display. An expert evaluation study, based on a four-layer affordance framework, was conducted to assess and improve the interactive visualization design.

The Role of Aesthetics and Perception in Raising Situation Awareness: Lessons from SpringRain

In the face of increased cyber risks, we present our iterative design process and the resulting principles of SpringRain, an information visualization (infoVis) display design concept for large screens in network control rooms (NOCs). It aims to raise team situation awareness by visualizing large-scale multidimensional computer network data sets as a live “rainfall.” We used aesthetic principles and theories of perception to prototype this ambient, yet data-dense, visualization. By applying multiple data dimensions to different properties of a line segment, such as length, motion, and color, the two-dimensional visualization offers analytical affordances (i.e., graphic qualities that make it clear how the display should be “read”) that can be processed pre-attentively (i.e., under 200 ms). This grants that time-sensitive anomalies in the network can be noticed, processed, and addressed in a timely manner. Our design approach was driven by theories rather than existing design works in the hope of encouraging more user-centered theories-driven infoVis designs that are better suited to user needs and requirements. Expert reviewers’ feedback from the VAST 2013 Challenge committee confirmed the novelty of the design and pointed to opportunities for improvements. We discuss three redesign attempts to address some of the identified limitations.

Unified Spatial Intersection Algorithms Based on Conformal Geometric Algebra

Conformal Geometric Algebra has been introduced into geographic information science as a mathematical theory because of its advantages in terms of uniform multidimensional representation and computation. The traditional intersection computation between two geometric objects of different types is not unified. In this study, we propose algorithms based on Conformal Geometric Algebra to determine the spatial relationships between geographic objects in a unified manner. The unified representation and intersection computation can be realized for geometric objects of different dimensions. Different basic judgment rules are provided for different simple geometries. The algorithms are designed and implemented using MapReduce to improve the efficiency of the algorithms. From the results of several experiments we provide, the correctness and effectiveness of the algorithms can be verified.

Item exposure control for multidimensional computer adaptive testing under maximum likelihood and expected a posteriori estimation.

Item bank stratification has been shown to be an effective method for combating item overexposure in both uni- and multidimensional computer adaptive testing. However, item bank stratification cannot guarantee that items will not be overexposed-that is, exposed at a rate exceeding some prespecified threshold. In this article, we propose enhancing stratification for multidimensional computer adaptive tests by combining it with the item eligibility method, a technique for controlling the maximum exposure rate in computerized tests. The performance of the method was examined via a simulation study and compared to existing methods of item selection and exposure control. Also, for the first time, maximum likelihood (MLE) and expected a posteriori (EAP) estimation of examinee ability were compared side by side in a multidimensional computer adaptive test. The simulation suggested that the proposed method is effective in suppressing the maximum item exposure rate with very little loss of measurement accuracy and precision. As compared to MLE, EAP generates smaller mean squared errors of the ability estimates in all simulation conditions.

Teste Adaptativo Computadorizado Multidimensional com propósitos educacionais: princípios e métodos

Resumo O Teste Adaptativo Computadorizado Multidimensional (MCAT), baseado na Teoria de Resposta ao Item Multidimensional (MIRT), considera as múltiplas habilidades do examinado em testes educacionais. Nesse contexto, o presente artigo: (i) traz subsídios teóricos e metodológicos sobre MCATs com propósitos educacionais e (ii) aborda vantagens e desvantagens da aplicação em cenários educacionais. A revisão da literatura aponta que o MCAT é adequado para testes computadorizados com múltiplas habilidades, administrando um número menor de itens do que os testes tradicionais.

Improved numerical modeling of morphodynamics of rivers with steep banks

The flow and sediment transport processes near steep streambanks, which are commonly found in meandering, braided, and anastomosing stream systems, exhibit complex patterns that produce intricate interactions between bed and bank morphologic adjustment. Increasingly, multi-dimensional computer models of riverine morphodynamics are used to aid in the study of these processes. A number of depth-averaged two-dimensional models are available to simulate morphologic adjustment of both bed and banks. Unfortunately, these models use overly simplified conceptual models of riverbank erosion, are limited by inflexible structured mesh systems, or are unable to accurately account for the flow and sediment transport adjacent to streambanks of arbitrary geometry. A new, nonlinear model is introduced that resolves these limitations. The model combines the river morphodynamics computer models TELEMAC-2D and SISYPHE of the open source TELEMAC-MASCARET suite of solvers with the bank erosion modules of the CONCEPTS channel evolution computer model. The performance of the new model is evaluated for meander-planform initiation and development. The most important findings are: (1) the model is able to simulate a much greater variety and complexity in meander wavelengths; (2) simulated meander development agrees closely with the unified bar-bend theory of Tubino and Seminara (1990); and (3) the rate of meander planform adjustment is greatly reduced if the wavelength of alternate bars is similar to that of meanders.

Towards the direct numerical simulation of nucleate boiling flows

A flow model is built to capture evaporating interfaces separating liquid and vapour. Surface tension, heat conduction, Gibbs free energy relaxation and compressibility effects are considered. The corresponding flow model is hyperbolic, conservative and in agreement with the second law of thermodynamics. Phase transition is considered through Gibbs energy relaxation, in the same mind as in Saurel et al. (2008). Surface tension effects are modelled following the lines of Brackbill et al. (1992). There is thus no need to resolve the interface structure as jump conditions are inherent features of the model formulation. With the present approach, the same set of partial differential equations is solved everywhere, in pure fluids as well as in the captured diffuse interface. There is thus a unique hyperbolic flow solver that handles flow dynamics, interface motion and eventually acoustic wave dynamics. To make distinction between “pure” fluids and liquid–vapour mixture treatment, different sets of algebraic equations are considered in the relaxation solver. To guarantee accurate computation of the liquid and gas dynamics the preconditioned implicit scheme of LeMartelot et al. (2013) is adapted to the present boiling flow model. The model and method are validated against a one-dimensional test problem having exact solution. Multidimensional computations are then shown to illustrate method capabilities.

Multidimensional CAT Item Selection Methods for Domain Scores and Composite Scores With Item Exposure Control and Content Constraints

The intent of this research was to find an item selection procedure in the multidimensional computer adaptive testing (CAT) framework that yielded higher precision for both the domain and composite abilities, had a higher usage of the item pool, and controlled the exposure rate. Five multidimensional CAT item selection procedures (minimum angle; volume; minimum error variance of the linear combination; minimum error variance of the composite score with optimized weight; and Kullback‐Leibler information) were studied and compared with two methods for item exposure control (the Sympson‐Hetter procedure and the fixed‐rate procedure, the latter simply refers to putting a limit on the item exposure rate) using simulated data. The maximum priority index method was used for the content constraints. Results showed that the Sympson‐Hetter procedure yielded better precision than the fixed‐rate procedure but had much lower item pool usage and took more time. The five item selection procedures performed similarly under Sympson‐Hetter. For the fixed‐rate procedure, there was a trade‐off between the precision of the ability estimates and the item pool usage: the five procedures had different patterns. It was found that (1) Kullback‐Leibler had better precision but lower item pool usage; (2) minimum angle and volume had balanced precision and item pool usage; and (3) the two methods minimizing the error variance had the best item pool usage and comparable overall score recovery but less precision for certain domains. The priority index for content constraints and item exposure was implemented successfully.

Implementing Multi-Dimensional CAD Models to Reduce the Project Cost Estimations Gap between the Financial Ministry and Other Government Ministries in Saudi Arabia

Saudi government ministries have depended on transparent outsourcing regulations, to contract independent competent companies to estimate costs during the conceptualization phases of construction projects. Aforementioned companies often face the errors in their estimations. Unprofessionalism, inflation, lack of standardised industry cost estimation methods and uncertainty play vital role to failure the project estimations. To attain more accurate project cost estimations, the Saudi ministries must regulate their cost estimation methods and should incorporate recent technological solutions into their cost estimation processes. This paper qualitatively analyses project cost estimation processes adopted by Saudi government ministries, identifies their shortcomings and examined the effects of adopting multi-dimensional computer aided design (MDCAD). The information used for this analysis has been collected from ministries, contract companies and academic literature. 

Visualization of multidimensional numerical arrays of solid-state objects

This article is intended for math and computer science subjects study deepening and understanding of multidimensional computer graphics environment. The paper describes multidimensional numeric arrays visualization using object-oriented programming tools. The method allows the multidimensional numeric arrays stored data to simulate virtual reality products which, in turn, can become the reference now intensively developed new embedded system components. Shown an another option to simulate the multidimensional visual objects that may be transformed from capturing or graphically present on the computer screen using a new computational mathematics packages for solving advancedcomputer graphics tasks. It seems comfortable to use new estimated mathematics programs and packages, which already are enriched with digital image processing tools, allowing create a various objects of the real world.

Anisotropic halo model: implementation and numerical results

In the present work, we extend the classic halo model for the large-scale matter distribution including a triaxial model for the halo profiles and their alignments. In particular, we derive general expressions for the halo-matter cross correlation function. In addition, by numerical integration, we obtain instances of the cross-correlation function depending on the directions given by halo shape axes. These functions are called anisotropic cross-correlations. With the aim of comparing our theoretical results with the simulations, we compute averaged anisotropic correlations in cones with their symmetry axis along each shape direction of the centre halo. From these comparisons we characterise and quantify the alignment of dark matter haloes on the $\Lambda$CDM context by means of the presented anisotropic halo model. As our model requires multidimensional integral computation we implement a Monte Carlo method on GPU hardware which allows us to increase the precision of the results whereas it improves the performance of the computation.

Toward efficient multidimensional subspace skyline computation

Skyline queries have attracted considerable attention to assist multicriteria analysis of large-scale datasets. In this paper, we focus on multidimensional subspace skyline computation that has been actively studied for two approaches. First, to narrow down a full-space skyline, users may consider multiple subspace skylines reflecting their interest. For this purpose, we tackle the concept of a skycube, which consists of all possible non-empty subspace skylines in a given full space. Second, to understand diverse semantics of subspace skylines, we address skyline groups in which a skyline point (or a set of skyline points) is annotated with decisive subspaces. Our primary contributions are to identify common building blocks of the two approaches and to develop orthogonal optimization principles that benefit both approaches. Our experimental results show the efficiency of proposed algorithms by comparing them with state-of-the-art algorithms in both synthetic and real-life datasets.

Perturbation Theory for Solar Cell Efficiency II—Delineating Series Resistance

Recently proposed perturbation analysis and reciprocity relations in photovoltaic conversion are demonstrated in 2-D simulations. The main parameters discussed are the current-conversion efficiency, which enables accurate calculation of the sensitivity of maximum power to different recombination parameters, and its derived local series resistance, whose weighted average is exactly equal to the series resistance obtained by the double illumination method. Both parameters can be displayed as spatial maps to visually aid multidimensional computer simulations. Finally, the suitability of mapping the local series resistance from luminescence images is discussed with the help of simulated examples. The experimental and computational procedures to generate these maps are among the easiest proposed so far in the literature and require no ad hoc assumptions.

Development of a non-reflecting boundary condition for multidimensional nonlinear duct acoustic computation

The quality of any time-domain nonlinear CFD simulation of silencers is determined by the modeling procedure used for the anechoic termination at the boundary end of the computational domain. In this study, a novel anechoic boundary condition based on the characteristic theory combined with the linear relaxation method has been developed in an open source CFD code. Wave propagation in ducts and mufflers has been analyzed and the effect of the damping properties of the boundary condition has been studied. The study shows that the explicit damping of the solution vector produces good performance at all the frequencies with acoustic waves having varying incidence to the boundary. Also, results indicate that numerical reflection of acoustic waves with high incident angles is reduced if the damping is applied at the boundary within the semi-implicit solution of the governing equations. Finally, the boundary condition has been applied together with a nonlinear solver to evaluate the acoustic attenuation performance of circular flow-reversing chambers and single-plug perforated mufflers with and without mean flow velocity of the gas. Code validation has been carried out against experimental data.

One-step R-estimation in linear models with stable errors

Classical estimation techniques for linear models either are inconsistent, or perform rather poorly, under α-stable error densities; most of them are not even rate-optimal. In this paper, we propose an original one-step R-estimation method and investigate its asymptotic performances under stable densities. Contrary to traditional least squares, the proposed R-estimators remain root-n consistent (the optimal rate) under the whole family of stable distributions, irrespective of their asymmetry and tail index. While parametric stable-likelihood estimation, due to the absence of a closed form for stable densities, is quite cumbersome, our method allows us to construct estimators reaching the parametric efficiency bounds associated with any prescribed values (α0,b0) of the tail index α and skewness parameter b, while preserving root-n consistency under any (α,b) as well as under usual light-tailed densities. The method furthermore avoids all forms of multidimensional argmin computation. Simulations confirm its excellent finite-sample performances.

Vocal Outcome After CO2 Laser Cordectomy Performed on Patients Affected by Early Glottic Carcinoma

The objectives of this study were to assess the influence of the different types of laser cordectomy on vocal outcome and highlight the relationship between some perceptive, acoustic, and endoscopic evaluations. Retrospective observational study. Thirteen patients, staged as having T1a tumor, underwent laser CO(2)cordectomy (1 patient type I and type II, 2 patients type II, 6 patients type III, and 4 patients type IV) between January and June 2010. Grade, roughness, breathiness, asthenia, and strain evaluation scale; voice handicap index-10 questionnaire; multidimensional computer analysis of voice and speech; maximum phonation time; and stroboscopic examination were performed 12 months after the surgery. Correlations between jitter% and R, shimmer% and R, noise-to-harmonic ratio (NHR) and G were studied. Patients were first divided into groups according to type of cordectomy performed and, later, according to stroboscopic findings. Wilcoxon test, Spearman index, and Kruskal-Wallis test, followed by post hoc analysis, were used. No significant differences were found in type III and type IV cordectomy groups. Jitter% and R values showed a correlation as did shimmer% and B values, and NHR and G values in type III cordectomy group. Moreover, shimmer% and NHR values significantly increase in direct proportion to the severity of the endoscopic status. Results indicate that the type of surgery performed, functional compensation, and outcome measures were related, although for some data, there were no statistical evidence. Individual compliance could strongly influence vocal outcome in these patients.

Multidimensional CAT Item Selection Methods for Domain Scores and Composite Scores: Theory and Applications.

Multidimensional computer adaptive testing (MCAT) can provide higher precision and reliability or reduce test length when compared with unidimensional CAT or with the paper-and-pencil test. This study compared five item selection procedures in the MCAT framework for both domain scores and overall scores through simulation by varying the structure of item pools, the population distribution of the simulees, the number of items selected, and the content area. The existing procedures such as Volume (Segall in Psychometrika, 61:331-354, 1996), Kullback-Leibler information (Veldkamp & vander Linden in Psychometrika 67:575-588, 2002), Minimize the error variance of the linear combination (vander Linden in J. Educ. Behav. Stat. 24:398-412, 1999), and Minimum Angle (Reckase in Multidimensional item response theory, Springer, New York, 2009) are compared to a new procedure, Minimize the error variance of the composite score with the optimized weight, proposed for the first time in this study. The intent is to find an item selection procedure that yields higher precisions for both the domain and composite abilities and a higher percentage of selected items from the item pool. The comparison is performed by examining the absolute bias, correlation, test reliability, time used, and item usage. Three sets of item pools are used with the item parameters estimated from real live CAT data. Results show that Volume and Minimum Angle performed similarly, balancing information for all content areas, while the other three procedures performed similarly, with a high precision for both domain and overall scores when selecting items with the required number of items for each domain. The new item selection procedure has the highest percentage of item usage. Moreover, for the overall score, it produces similar or even better results compared to those from the method that selects items favoring the general dimension using the general model (Segall in Psychometrika 66:79-97, 2001); the general dimension method has low precision for the domain scores. In addition to the simulation study, the mathematical theories for certain procedures are derived. The theories are confirmed by the simulation applications.

Improving Personality Facet Scores With Multidimensional Computer Adaptive Testing

Narrowly defined personality facet scores are commonly reported and used for making decisions in clinical and organizational settings. Although these facets are typically related, scoring is usually carried out for a single facet at a time. This method can be ineffective and time consuming when personality tests contain many highly correlated facets. This article investigates the possibility of increasing the precision of the NEO PI-R facet scores by scoring items with multidimensional item response theory and by efficiently administering and scoring items with multidimensional computer adaptive testing (MCAT). The increase in the precision of personality facet scores is obtained from exploiting the correlations between the facets. Results indicate that the NEO PI-R could be substantially shorter without attenuating precision when the MCAT methodology is used. Furthermore, the study shows that the MCAT methodology is particularly appropriate for constructs that have many highly correlated facets.