Simplification Procedure Research Articles

Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering

This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined in the 4D domain jointly comprising the 3D volume and its 1D intensity range. Crucially, the computation of sparse pdf volumes exploits data coherence in 4D, resulting in a sparse representation with surprisingly low storage requirements. At run time, we dynamically apply transfer functions to the pdfs using simple and fast convolutions. Whereas standard low-pass filtering and down-sampling incur visible differences between resolution levels, the use of pdfs facilitates consistent results independent of the resolution level used. We describe the efficient out-of-core computation of large-scale sparse pdf volumes, using a novel iterative simplification procedure of a mixture of 4D Gaussians. Finally, our data structure is optimized to facilitate interactive multi-resolution volume rendering on GPUs.

A generic double-curvature piezoelectric shell energy harvester: Linear/nonlinear theory and applications

Converting vibration energy to useful electric energy has attracted much attention in recent years. Based on the electromechanical coupling of piezoelectricity, distributed piezoelectric zero-curvature type (e.g., beams and plates) energy harvesters have been proposed and evaluated. The objective of this study is to develop a generic linear and nonlinear piezoelectric shell energy harvesting theory based on a double-curvature shell. The generic piezoelectric shell energy harvester consists of an elastic double-curvature shell and piezoelectric patches laminated on its surface(s). With a current model in the closed-circuit condition, output voltages and energies across a resistive load are evaluated when the shell is subjected to harmonic excitations. Steady-state voltage and power outputs across the resistive load are calculated at resonance for each shell mode. The piezoelectric shell energy harvesting mechanism can be simplified to shell (e.g., cylindrical, conical, spherical, paraboloidal, etc.) and non-shell (beam, plate, ring, arch, etc.) distributed harvesters using two Lamé parameters and two curvature radii of the selected harvester geometry. To demonstrate the utility and simplification procedures, the generic linear/nonlinear shell energy harvester mechanism is simplified to three specific structures, i.e., a cantilever beam case, a circular ring case and a conical shell case. Results show the versatility of the generic linear/nonlinear shell energy harvesting mechanism and the validity of the simplification procedures.

Correlation of solid solubility of 1,4-bis(alkylamino)-9,10-anthraquinones in supercritical carbon dioxide using solution model approach

In this study, solid solubility data of six 1,4-bis(alkylamino)-9,10-anthraquinones (AQs) in supercritical carbon dioxide (CO2) are correlated using a two-parameter solution model developed from the regular solution model coupled with the Flory–Huggins equation. This two-parameter solution model yields satisfactory correlated results comparable to those from commonly used three-parameter semi-empirical equations. The average deviation in correlated solubilities using our two-parameter solution model is about 6%. With appropriate model simplification and generalization procedure, a predictive solution model is proposed in this study for solubility prediction using the chain length of alkyl group of alkylamino side chain. The proposed predictive solution model provides acceptable predicted results and yields average deviation in predicted solubilities of 17%. In addition, the proposed predictive solution model is also employed to predict the solubility data of AQs that are not originally included in the generalization procedure. The calculated results obtained in this study demonstrate that the solution model adopted in this study is applicable for correlation and prediction of solid solubilities of structure-related compounds in supercritical CO2.

Totally organic biphasic solvent systems for extraction and descriptor determinations

Partition between two immiscible solvents is widely used in sample preparation procedures for matrix simplification and isolation of target analytes, for separations using countercurrent, centrifugal partition, and liquid-liquid chromatography, and as a method for determining descriptors for use in modeling chemical, biological, and environmental processes. Until recently, most applications employed water as one component of the biphasic system. For compounds of low water solubility or stability, a series of totally organic biphasic systems have been developed to enhance the application range of liquid-liquid partition methods. These systems, their characterization using the solvation parameter model, and applications to sample preparation and the determination of descriptors are described in this review.

On the simplification of kinetic reaction mechanisms of air–ethanol under high pressure conditions

In the last decade, the interest towards non-petroleum based fuels is strongly increased due to the current concerns about the impact of the transport system on atmospheric pollutions, mainly due to CO2 emissions. Ethanol, either blended with conventional fuels or in its pure form, is one of such fuels already in use in the automotive industries. As an example, the flex-fuel engines are designed to employ gasoline from 10% up to 85% of ethanol (E10,E85). In this work, the oxidation kinetics of ethanol with air has been considered and analyzed in an ambient at high pressure, ranging from 4 to 6MPa, by means of a Computational Singular Perturbation methodology. This study starts from a detailed kinetic reaction mechanism, which is extensively used in the literature and is made up by 235 reversible reactions among 46 chemical species. This mechanism has been used to get several families of simplified (skeletal) mechanisms by considering equivalence ratios in the range 0.2–2.0 and two sets of initial temperatures (900–1200K and 1200–1700K). The skeletal mechanisms have been validated by comparing the temperature and major chemical species profiles and the ignition delay time with those obtained by employing the detailed mechanism. Advantages and limitations of these mechanisms are highlighted. The accuracy of the skeletal mechanisms is very good in the range of equivalence ratio and temperature considered in the simplification procedure. Moreover, it is shown that a further simplification of the reaction mechanism is obtained by narrowing the range of equivalence ratio instead of the range of temperature. The most simplified skeletal mechanisms show an error in the prediction of temperature and fuel profiles lower than 3%, except for the case of low temperature and lean mixtures, where the maximum error increases up to 14%. Finally, the main reaction pathways are analyzed to show how the most important intermediate chemical species and products characterize the skeletal mechanisms for different values of equivalence ratio and temperature. The skeletal mechanisms are given as Supplementary data. The reader can refer to such data for the entire set of the retained reactions and species for each skeletal mechanism.

지형 데이터의 효율적 단순화

Presented in the paper is a procedure to extract simplified triangular mesh from a height map (terrain data). The proposed algorithm works directly on a height map that extracts a simplified triangular mesh. For the simplification, the paper employs an iterative method of edge contractions. To determine an edge to be contracted, the contraction cost of an edge is evaluated through the QEM method. Normally, an edge contraction will remove two triangles sharing the edge. Although the edge contraction can be implemented easily on a triangular mesh, it is not viable to implement the operation on a height map due to the irregular topology. To handle the irregular topology during the simplification procedure, a new algorithm is introduced.

Action emulation

The effects of public announcements, private communications, deceptive messages to groups, and so on, can all be captured by a general mechanism of updating multi-agent models with update action models, now in widespread use. There is a natural extension of the definition of a bisimulation to action models. Surely enough, updating with bisimilar action models gives the same result (modulo bisimulation). But the converse turns out to be false: update models may have the same update effects without being bisimilar. We propose action emulation as a notion of equivalence more appropriate for action models, and generalizing standard bisimulation. It is proved that action emulation provides a full characterization of update effect. We first concentrate on the general case, and next focus on the important case of action models with propositional preconditions. Our notion of action emulation yields a simplification procedure for action models, and it gives designers of multi-agent systems a useful tool for comparing different ways of representing a particular communicative action.

Simplifying Complex Computer-Generated Reactions Network to Suppress Its Stiffness

Creation of mathematical model of complex radical processes manually is a very time-consuming process. Steam-cracking model created automatically by automated reaction network generation, on the other hand, becomes very large and complex for bigger molecules. This work was aimed at applying pseudo-steady state assumption automatically to components inside generated reactions network. The details of simplifying procedure are provided and the comparison of experimental data (lab-scale) to simulations by original and simplified model is presented. In overall, the simplification procedure lead only to marginal deviations in the simulated results, but the model ability to simulate bigger molecules has substantially improved.

Optimal design and operation of a C3MR refrigeration system for natural gas liquefaction

LNG liquefaction is an energy-intensive process. Energy efficiency is the major concern in LNG liquefaction process design and operation. In this paper, a new methodology for LNG liquefaction synthesis targeting energy consumption minimization is presented. It is based on thermodynamic analysis, mathematical programming, and rigorous simulation. The procedure for MINLP (mixed-integer non-linear programming) model development and simplification is described in detail. LINDOGlobal solver in GAMS is employed to solve the MINLP problem and the optimization results are further validated through rigorous simulations. Based on the development, the optimal design and operational conditions for LNG liquefaction process can be simultaneously achieved. A C3MR LNG liquefaction process is employed to demonstrate the efficacy of the developed methodology. Comprehensive thermodynamic analysis is also conducted to give insights of the optimization results.

The effect of habitat fragmentation on cyclic population dynamics: a reduction to ordinary differential equations

Habitat fragmentation is known to be a key factor affecting population dynamics. In a previous study by Strohm and Tyson (Bull Math Biol 71:1323–1348, 2009), the effect of habitat fragmentation on cyclic population dynamics was studied using spatially explicit predator–prey models with four different sets of reaction terms. The difficulty with spatially explicit models is that often analytical tractability is lost and the mechanisms behind the behaviour of the models are difficult to analyse. In this study, we employ a simplification procedure based on a Fourier series first-term truncation of the spatially explicit models Strohm and Tyson (Bull Math Biol 71:1323–1348, 2009) to obtain spatially implicit models. These simpler models capture the main features of the spatially explicit models and can be used to explain the dynamics observed by Strohm and Tyson. We find that the spatially implicit models and the spatially explicit models produce similar responses to habitat fragmentation for larger high-quality patch sizes. Additionally, we find that the critical patch size of the spatially implicit models provides an upper bound on the critical patch size of the spatially explicit models. Finally, we derive an approximation of the multi-patch habitat by a single-patch habitat with partial flux boundary conditions which allows for a lower bound on the critical patch size to be calculated.

Bounded rationality, strategy simplification, and equilibrium

It is frequently suggested that predictions made by game theory could be improved by considering computational restrictions when modeling agents. Under the supposition that players in a game may desire to balance maximization of payoff with minimization of strategy complexity, Rubinstein and co-authors studied forms of Nash equilibrium where strategies are maximally simplified in that no strategy can be further simplified without sacrificing payoff. Inspired by this line of work, we introduce a notion of equilibrium whereby strategies are also maximally simplified, but with respect to a simplification procedure that is more careful in that a player will not simplify if the simplification incents other players to deviate. We study such equilibria in two-player machine games in which players choose finite automata that succinctly represent strategies for repeated games; in this context, we present techniques for establishing that an outcome is at equilibrium and present results on the structure of equilibria.

Use of Syntactic Elaboration Techniques to Enhance Comprehensibility of EST Texts

The current study examined differential effects of two pre-modification types, syntactic elaboration and syntactic simplification (at the level of syntax and irrespective of problematic lexis), on EST students’ reading comprehension. The purpose was to see whether a priori syntactic elaborative adjustment, given its advantages over simplification, can augment comprehensibility of scientific texts in order to replace simplification adjustment. To carry out the study, three versions of 5 passages including Baseline, syntactically simplified, and syntactically elaborated were provided. All the five passages were relevant to civil engineering and they were modified using two above-mentioned techniques. The subjects of the study were composed of 185 homogenous civil engineering students who participated in different phases. The results revealed that syntactic simplification and syntactic elaboration procedures operated nearly in the same way in orienting the EST texts toward comprehensibility. The results of the study even indicated that students benefited more from elaborated than simplified texts although it was not statistically significant. Therefore, the study supports the view that syntactic elaborative adjustment can be exercised in advance on EST materials for pedagogical purposes since it increases the reading comprehension at the same time keeps unfamiliar syntactic units intact to be learned by EST readers

A simple work flow for biologically inspired model reduction--application to early JAK-STAT signaling.

BackgroundModeling of biological pathways is a key issue in systems biology. When constructing a model, it is tempting to incorporate all known interactions of pathway species, which results in models with a large number of unknown parameters. Fortunately, unknown parameters need not necessarily be measured directly, but some parameter values can be estimated indirectly by fitting the model to experimental data. However, parameter fitting, or, more precisely, maximum likelihood parameter estimation, only provides valid results, if the complexity of the model is in balance with the amount and quality of the experimental data. If this is the case the model is said to be identifiable for the given data. If a model turns out to be unidentifiable, two steps can be taken. Either additional experiments need to be conducted, or the model has to be simplified.ResultsWe propose a systematic procedure for model simplification, which consists of the following steps: estimate the parameters of the model, create an identifiability ranking for the estimated parameters, and simplify the model based on the identifiability analysis results. These steps need to be applied iteratively until the resulting model is identifiable, or equivalently, until parameter variances are small. We choose parameter variances as stopping criterion, since they are concise and easy to interpret. For both, the parameter estimation and the calculation of parameter variances, multi-start parameter estimations are run on a parallel cluster. In contrast to related work in systems biology, we do not suggest simplifying a model by fixing some of its parameters, but change the structure of the model.ConclusionsWe apply the proposed approach to a model of early signaling events in the JAK-STAT pathway. The resulting model is not only identifiable with small parameter variances, but also shows the best trade-off between goodness of fit and model complexity.

An ant colony system for enhanced loop-based aisle-network design

The purpose of this paper is to develop a global optimization model, simplification schemes, and a heuristic procedure for the design of a shortcut-enhanced unidirectional loop aisle-network with pick-up and drop-off stations. The objective is to minimize the total loaded and empty trip distances. This objective is the main determinant for the fleet size of the vehicles, which in turn is the driver of the total life-cycle cost of vehicle-based unit-load transport systems. The shortcut considerably reduces the length of the trips while maintaining the simplicity of the system. The global model solves simultaneously for the loop design, stations’ locations and shortcut design. We then develop two simplifications each containing two serial phases. Phase-1 of the first simplification step focuses on both loaded and empty trips, while that of the second simplification focuses only on loaded trips. In phase-2, both designs are enhanced with a shortcut to minimize both loaded and empty trip distances. The quality and efficiency of the three alternative designs are tested for a set of problems with different layout size and product mix. While the solution time of the second simplification procedure is a small percentage of the global formulation, it generates satisfactory solutions. On this foundation, we then develop a heuristic procedure to replace phase-1 of the second simplification. The heuristic procedure is using ant colony system to generate feasible solutions and then we implement a local search algorithm to improve the results. The heuristic algorithm quickly generates close to optimal solutions for phase-1 of the second simplification. By applying phase-2 of the this second simplification on a set of loops generated by the heuristic, close to optimal solutions are also quickly obtained for the global model.

HILK++: an interpretability-guided fuzzy modeling methodology for learning readable and comprehensible fuzzy rule-based classifiers

This work presents a methodology for building interpretable fuzzy systems for classification problems. We consider interpretability from two points of view: (1) readability of the system description and (2) comprehensibility of the system behavior explanations. The fuzzy modeling methodology named as Highly Interpretable Linguistic Knowledge (HILK) is upgraded. Firstly, a feature selection procedure based on crisp decision trees is carried out. Secondly, several strong fuzzy partitions are automatically generated from experimental data for all the selected inputs. For each input, all partitions are compared and the best one according to data distribution is selected. Thirdly, a set of linguistic rules are defined combining the previously generated linguistic variables. Then, a linguistic simplification procedure guided by a novel interpretability index is applied to get a more compact and general set of rules with a minimum loss of accuracy. Finally, partition tuning based on two efficient search strategies increases the system accuracy while preserving the high interpretability. Results obtained in several benchmark classification problems are encouraging because they show the ability of the new methodology for generating highly interpretable fuzzy rule-based classifiers while yielding accuracy comparable to that achieved by other methods like neural networks and C4.5. The best configuration of HILK will depend on each specific problem under consideration but it is important to remark that HILK is flexible enough (thanks to the combination of several algorithms in each modeling stage) to be easily adaptable to a wide range of problems.

Aperture Antenna Modeling by a Finite Number of Elemental Dipoles From Spherical Field Measurements

A method to determine a distribution of a finite number of elementary dipoles that reproduce the radiation behavior of the antenna under test (AUT) from truncated spherical field measurements is proposed. It is based on the substitution of the actual antenna by a finite number of equivalent infinitesimal dipoles (electric and magnetic), distributed over the antenna aperture. This equivalent set of elementary dipoles is optimized using the transmission coefficient involving the spherical wave expansion of the measured field and using an appropriate matching method. Once the current excitation of each dipole is known, the radiated field of the antenna at different distances can be rapidly determined. Moreover, using an iterative simplification procedure, the number of equivalent dipoles is reduced, which eases the implementation of the antenna equivalent model in any existing electromagnetic code. The feasibility, the reliability and the accuracy of the method are shown using experimental data issued from the measurement of an X-band horn antenna, in two different measurement setups.

Escalas e simplificações: exemplos em sistemas físicos e biológicos

Neste artigo são apresentados exemplos onde podem ser usadas simplificações matemáticas e adimensionalizações em sistemas físicos e biológicos. A importância destes procedimentos é discutida de forma didática. É feita uma rápida dedução de como este procedimento auxilia na resolução de um problema de mecânica clássica simples e posteriormente comparado com um sistema predador-presa em ecologia.

FPGA-Based Implementation of Real Time Optical Flow Algorithm and Its Applications for Digital Image Stabilization

Abstract An efficient simplification procedure of the optical flow (OF) algorithm as well as its hardware implementation using the field programmable gate array (FPGA) technology is presented. The modified algorithm is based on block matching of subsets of successive frames, and exploits onedimensional representation of subsets as well as the adaptive adjustments of their sizes. Also, an l1- norm-based correlation function requiring no multiplication/division operations is used. As a result, it was possible to reduce the computational complexity of the algorithm without compromising the processing accuracy. Both the accuracy and the limitations resulting from the introduced simplifications have been verified based on several examples of both synthetic and real movie samples. The presented algorithm has been implemented using VirtexII-1000 FPGA to realize a digital stabilization system for the CMOS camera images. Experimental results fully confirm the efficiency of the presented algorithm when working with limited computational resources. This demonstrates the possibility of using our algorithm in the autonomous navigation and other battery-powered systems.

Model simplification procedure for signal transduction pathway models: An application to IL-6 signaling

Mathematical models of signal transduction pathways are characterized by a large number of proteins and uncertain parameters. One challenge involving these models is parameter identifiability as only a limited amount of quantitative data is generally available. One potential solution to this problem is model simplification, as the parts of the model that cannot be identified in experiments can be reduced. It is the main goal of the presented work to derive a model simplification procedure for signal transduction pathways such that: (1) the model size is significantly reduced such that the model can be validated using available experimental data, and (2) the physical interpretation of the remaining states and parameters is retained. In a first step, sensitivity analysis is performed to determine which parts of the model contain parameters that have highly correlated effects on the outputs of the system. These model parts can then be replaced by a simpler representation as it is not be possible to verify the values of all of the reaction parameters. Representative state variables are then chosen for each part of the model via quantification of the degree of observability of the state variables of the model for potential measurements. A new model structure can be derived based upon this analysis. The initial estimates of the parameters are generated from simulation data of the original model. In a final step, the parameters of the simplified model are re-estimated using available experimental data. The presented technique is used to derive a simplified version of an IL-6 signal transduction model. The number of equations and parameters in the model has been reduced from 68 to 13 and from 118 to 19, respectively. It is shown that the identifiability of the model has been improved significantly. The new model is able to adequately predict the dynamic behavior of key proteins of the signal transduction pathway both in simulations but also when compared to available experimental data.

Structure optimization of BiLinear Recurrent Neural Networks and its application to Ethernet network traffic prediction

The BiLinear Recurrent Neural Network (BLRNN) based on the bilinear polynomial has been successfully applied to several nonlinear time series prediction problems. In order to obtain faster convergence in training the BLRNN, two procedures are applied to the network: (i) a structure simplification procedure whereby the multiplications for bilinear components in the BLRNN are reduced and (ii) a pruning procedure entailing application of a genetic algorithm. A structurally optimized BLRNN is thereby obtained. The computational complexity of the optimized BLRNN is reduced by about half in terms of the number of weights while preserving its generalization ability. Experiments on application of the structurally optimized BLRNN to a network traffic prediction problem are conducted on a real-world Ethernet network traffic data set. Results show that the optimized BLRNN-based prediction scheme can reduce the training time by roughly half when compared with the original BLRNN while preserving the prediction accuracy of the latter in terms of Normalized Mean Square Error (NMSE).