Flexible Version Research Articles

Solving system problems of a complex structure using multi-criteria analysis methods in the DSS NooTron

There were analyzed the possibilities of using multi-criteria analysis methods from the DSS NooTron (https://nootron.net.ua/) library considering system problems of a complex structure on a finite set of alternatives and criteria.The use of multi-criteria analysis methods is becoming an integral part of solving problems arising from the analysis, optimization, and evaluation of the effectiveness of complex weakly structured systems. These are such problems as comparative analysis and choice of the best alternative, making design decisions, vector optimization, resource allocation, diagnostics, rating compilation.Methods of multi-criteria decision analysis (MCDA) are used in many areas of science and practice. Quantitative methods of MCDA are of particular interest. These methods provide algorithms for dividing the system problem being studied into separate elements (decomposition), analyzing the selected blocks, determining the value of influence of each element on others (analysis), determining local (criterial) results and converting them into a global assessment (aggregation).The purpose of this work is to demonstrate the capabilities of multi-criteria analysis methods from the DSS NooTron library in system problems of a complex structure on a finite set of alternatives and criteria, including the tasks and methods implemented in the new version of NooTron DSS.A group of quantitative multi-criteria methods that are the most widely used and modified are chosen for the study, namely: the analytical hierarchy process, the analytical network process, the BOCR efficiency assessment methodology, the weighted sum method, the decision matrix method.The analysis of the structures of solved practical problems using the DSS NooTron led to the conclusion that this system provides a wide range of possibilities for system analytics, and also allows the analysis of weakly structured systems.The project “DSS NooTron” continues to evolve and improve. At the time of this writing, the following had been performed in the development of the system:1. The project architecture was improved on the basis of selected components of multi-criteria methods and React JavaScript framework for future support and scaling.2. Organized data exchange between components, their synchronization and processing of the application state.3. Improved interaction with the server to obtain intermediate results of solving the problem.4. A unified component flexible version of the analytical hierarchy process was developed using the React JavaScript framework.5. Implemented visualization of a dynamic hierarchical structure of a multi-criteria task in AHP.6. A simplified BOCR algorithm was developed to evaluate the effectiveness of IT projects.

Interpretation of matrix chromatographic-spectral data modeling with parallel factor analysis 2 and multivariate curve resolution

Parallel factor analysis 2 (PARAFAC2) is still being advocated for the processing of second-order chromatographic-spectral data, both for qualitative and quantitative applications. However, neither classical PARAFAC2 nor the newly developed flexible non-negative NN-PARAFAC2 version can adequately model these data in a general situation. In quantitative analysis, considerable bias may result in the estimation of analyte concentrations, due to the fact that both PARAFAC2 models apply an artificial constraint to the retrieved profiles, requiring constant cross-product, i.e., constant overlapping, between all pairs of component elution profiles in all samples. This only occurs under limited conditions. In this report, simulations help to understand, visualize and interpret these PARAFAC2 features. Experimental data are also studied concerning the determination of a fluoroquinolone antibiotic in bovine liver samples by liquid chromatography with multi-wavelength fluorescence detection. Both for simulated and experimental data, the PARAFAC2 versions provide poor analytical results, while correct data processing and reasonable analytical indicators can be achieved using multivariate curve resolution - alternating least-squares (MCR-ALS). For the simulated data sets, root mean square errors/relative errors of prediction were 0.01 concentration units/2% for MCR-ALS, compared to 0.02–0.06 units/4–12% for both PARAFAC2 and NN-PARAFAC2. For the experimental data sets, they were 0.025 µg mL−1/11% for MCR-ALS, 0.09 µg mL−1/40% for PARAFAC2 and 0.16 µg mL−1/71% for NN-PARAFAC2, with average recoveries (standard deviation) of 91(14)%, 185(135)% and 69(35)% respectively.

Prediction of viscosity-density dependence of liquid methane+n-butane+n-pentane mixtures using the molecular dynamics method and empirical correlations

We present a study of viscosities of n-pentane and binary and ternary methane–n-butane–n-pentane mixtures in liquid state at the temperature 360 K by the non-equilibrium molecular dynamics simulations with a modified fully flexible version of the all-atom TraPPE-EH force field. The Batchinski correlation η=C/(v−b) is used to describe the viscosities of pure n-pentane. The calculated viscosity-density dependence for liquid n-pentane is in agreement with the experimental data. We show that the viscosity-volume dependencies of liquid binary and ternary mixtures can be fitted by the Batchinski's equation as well, and the coefficients for the mixtures are obtained by linear mixing of the coefficients for pure components. The model can be used for the interpretation and interpolation of the experimental data on viscosities of hydrocarbon liquids. The Batchinski-like behavior of viscosity of liquid mixtures in some density range can be used as a test for more complex correlations, which we show by comparing the hard sphere correlation and the expanded fluid correlation for hydrocarbons.

Phase inversion in reusable baths (PIRBs): A new polymer membrane fabrication method as applied to EVOH

ABSTRACTA flexible version of the phase inversion variety of porous membrane fabrication that employs cold solvent as a solidification bath is presented. A nonsolvent is included both in the dope and in the bath, and the liquid compositions are such that the bath is reusable; the concept is demonstrated for the water/dimethyl sulfoxide/poly(ethylene‐co‐vinyl alcohol) system. The effects of the reusable bath (RB) temperature and the bath strength on membrane morphologies are explored. From the pure water flux measurements, it is found that membranes prepared from RB possess higher permeation fluxes than those from other baths. Filtration against blue dextran (2000 kDa) indicates that those membranes precipitated from RB at 5 °C exhibit the highest rejection (98%) at the permeation flux of 14.56 L m−2 h−1. In addition, it is found that the composition of the RB remains unchanged after 240 applications of the new process. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 136, 48193.

A simple model to predict effective conductivity of multicomponent matrix-based composite materials with high volume concentration of particles

For high-contrast-component-property composites, most popular effective medium approximations that are based on the dilute analytical solution for an ellipsoidal inclusion embedded in an infinite matrix diverge significantly from each other and from experimental and numerical data. This paper discusses the challenges in this research area and proposes some homogenization strategies to solve the problems. In this work, a simple effective medium approximation is constructed to predict the effective conductivity of multicomponent matrix-based composites containing high concentrations of particles in d-dimensional space (d=2,3). The maximum volume fraction that depends on particle size distribution and the geometric approximation are accounted for in the micromechanical model to obtain new closed-form solutions. A flexible version of the model containing a free parameter is proposed to make the predictions more accurate at very high-volume fraction of inclusions. Applications are illustrated by comparing the theoretical predictions with the available experimental data or finite element simulations for various types of material to show the agreeable results close to the maximal packing points of the interactions.

Improved ultra-broadband chirp excitation.

The design and application of ultra-broadband excitation pulses have been among the most interesting and timely areas in NMR and EPR methodology in recent years, due especially to advances in hardware design in EPR, the advent and popularity of high- and ultrahigh-field NMR, and the application of numerical methods like optimal control theory to the design and optimization of radiofrequency pulses and pulse sequences. In this communication, we present a short, robust, and flexible version of the CHORUS family of constant-phase, very broadband excitation sequences. We demonstrate that more than 0.5 MHz excitation with uniform amplitudes and phases can be achieved with this excitation sequence.

A New Extremely Flexible Version of the Exponentiated Weibull Model: Theorem and Applications to Reliability and Medical Data Sets

In this work, a new lifetime model is introduced and studied. The major justification for the practicality of the new model is based on the wider use of the exponentiated Weibull and Weibull models. We are also motivated to introduce the new lifetime model since it exhibits decreasing, upside down-increasing, constant, increasing-constant and J shaped hazard rates also the density of the new distribution exhibits various important shapes. The new model can be viewed as a mixture of the exponentiated Weibull distribution. It can also be considered as a suitable model for fitting the symmetric, left skewed, right skewed and unimodal data. The importance and flexibility of the new model is illustrated by four read data applications.

Fork-free hybrid consensus with flexible Proof-of-Activity

Bitcoin and its underlying blockchain mechanism have been attracting much attention. One of their core innovations, Proof-of-Work (PoW), is notoriously inefficient which potentially motivates a centralization of hash power, defeating the original goal of decentralization. Proof-of-Stake (PoS) is later proposed to replace PoW. However, both PoW and PoS have different inherent advantages and disadvantages, so does Proof-of-Activity (PoA) of Bentov et al. (SIGMETRICS 2014) which only offers limited hybrids of two mechanisms. On the other hand, the hybrid consensus protocol of Pass and Shi (DISC 2017) aims to improve the efficiency by dynamically maintaining a rotating committee. Yet, there are unsatisfactory issues including chain forks and fair committee election.In this paper, we firstly devise a generalized variant of PoW. After that, we leverage our generalized PoW to construct a fork-free hybrid consensus protocol. We further combine our fork-free hybrid consensus mechanism with PoS for a flexible version of PoA with tunable parameters between PoW and PoS. Compared with Bentov et al.’s PoA, our “flexible PoA” improves the efficiency, leading to a more applicable consensus protocol.

Products of ideals of linear forms in quadric hypersurfaces

Conca and Herzog proved that any product of ideals of linear forms in a polynomial ring has a linear resolution. The goal of this paper is to establish the same result for any quadric hypersurface. The main tool we develop and use is a flexible version of Derksen and Sidman's approximation systems.

Thermodynamics and the potential energy landscape: case study of small water clusters.

We investigated the structure and the thermodynamic properties of small water clusters with the nested sampling computational technique, using two different water models, the coarse-grained mW (up to 25 molecules) and the flexible version of the TIP3P (up to 16 molecules). By mapping the entire potential energy landscape of the clusters, we calculated the heat capacity curves, located the structural transitions and identified those local minimum basins which contribute the most to the total partition function. We found that in the case of the mW model, trends in first-order-like and continuous-like transitions can be very well matched to the characteristics of the landscape: cluster sizes with fewer and narrower local minimum basins show a sharper 'melting' peak on the heat capacity curve. Trends in the case of the TIP3P model were not easily assigned to the changing occupation of basins, and the contribution of local minima was negligible, except for n = 7, 15 and 16.

A Flexible Stochastic Method for Solving the MAP Problem in Topic Models

The estimation of the posterior distribution is the core problem in topic models, unfortunately it is intractable. There are approximation and sampling methods proposed to solve it. However, most of them do not have any clear theoretical guarantee of neither quality nor rate of convergence. Online Maximum a Posteriori Estimation (OPE) is another approach with concise guarantee on quality and convergence rate, in which we cast the estimation of the posterior distribution into a non-convex optimization problem. In this paper, we propose a more general and flexible version of OPE, namely Generalized Online Maximum a Posteriori Estimation (G-OPE), which not only enhances the flexibility of OPE in different real-world situations but also preserves key advantage theoretical characteristics of OPE when comparing to the state-of-the-art methods. We employ G-OPE as inference a document within large text corpora. The experimental and theoretical results show that our new approach performs better than OPE and other state-of-the-art methods.

Implicit Dual-Domain Convolutional Network for Robust Color Image Compression Artifact Reduction

Several dual-domain convolutional neural network-based methods show outstanding performance in reducing image compression artifacts. However, they suffer from handling color images because the compression processes for gray-scale and color images are completely different. Moreover, these methods train a specific model for each compression quality and require multiple models to achieve different compression qualities. To address these problems, we proposed an implicit dual-domain convolutional network (IDCN) with the pixel position labeling map and the quantization tables as inputs. Specifically, we proposed an extractor-corrector framework-based dual-domain correction unit (DCU) as the basic component to formulate the IDCN. A dense block was introduced to improve the performance of extractor in DRU. The implicit dual-domain translation allows the IDCN to handle color images with the discrete cosine transform (DCT)-domain priors. A flexible version of IDCN (IDCN-f) was developed to handle a wide range of compression qualities. Experiments for both objective and subjective evaluations on benchmark datasets show that IDCN is superior to the state-of-the-art methods and IDCN-f exhibits excellent abilities to handle a wide range of compression qualities with little performance sacrifice and demonstrates great potential for practical applications.

A New Flexible Version of the Lomax Distribution with Applications

A new version of the Lomax model is introduced andstudied. The major justification for the practicality of the new model isbased on the wider use of the Lomax model. We are also motivated tointroduce the new model since the density of the new distribution exhibitsvarious important shapes such as the unimodal, the right skewed and the leftskewed. The new model can be viewed as a mixture of the exponentiated Lomaxdistribution. It can also be considered as a suitable model for fitting thesymmetric, left skewed, right skewed, and unimodal data sets. The maximumlikelihood estimation method is used to estimate the model parameters. Weprove empirically the importance and flexibility of the new model inmodeling two types of aircraft windshield lifetime data sets. The proposedlifetime model is much better than gamma Lomax, exponentiated Lomax, Lomaxand beta Lomax models so the new distribution is a good alternative to thesemodels in modeling aircraft windshield data.

Fully spherical stretchable silicon photodiodes array for simultaneous 360 imaging

Imaging is one of the important wonders of today's world. While everyday millions of snaps are taken, new advances like panoramic imaging have become increasingly popular. However, as of today an imaging system which can simultaneously capture images from all 360° viewpoints with a single sensor has not been achieved. Here, we show a physically flexible and stretchable version of arrayed silicon photodiodes made from low-cost bulk monocrystalline silicon (100) that can capture simultaneous omnidirectional images. The present report, with multiple wavelength detection, fast photoresponsivity, a wide viewing angle, selective aberration, and dynamic focusing enabled by 3D printed pneumatic actuators (note, today millions of image sensors can be integrated in mm2 area), overcomes previous demonstrations of only hemispherical photodetection capability. Such imaging capability will make unmanned air vehicles or self-driven cars safer, affordable augmented and virtual reality and more importantly, in-vivo biomedical imaging will be more effective.

Weighted and flexible versions of block CMRH method for solving nonsymmetric linear systems with multiple right-hand sides

Block Krylov subspace methods are the most popular algorithms for solving large nonsymmetric linear systems with multiple right-hand sides. One of them is the block CMRH method. This method generates a (non orthogonal) basis of the Krylov subspace through the block Hessenberg process. To accelerate the convergence of the block CMRH method, we will introduce two new methods. First, we present the block CMRH method with weighting strategy. In this method, the block CMRH method uses a different product at each restart. Second, we introduce a flexible version of the block CMRH algorithm that allows varying preconditioning at every step of the algorithm. Numerical experiments illustrate the benefits of the presented methods.

The impact of brief reflective responses on student performance

One-minute papers allow students to process what they learned during class and improve student performance. However, this activity can become monotonous and takes significantly longer than the name implies. The research described here tests the effectiveness of a briefer, more flexible version of this technique to increase the perceived relevance of the material and, in turn, performance. Students were randomly assigned to either self-generate a reflective response or answer a content-specific question generated by the instructor at the end of class. Students positively evaluated the brief reflective response activity. Moreover, answering the self-generated reflective responses was associated with greater perceived relevancy of course material to students’ daily lives compared to answering the content-specific questions. Perceived relevancy, in turn, was associated with higher examination grades. Thus, brief reflective responses are a useful tool to increase meaningful connections to course material which enhances examination performance.

Alternatives to polynomial trend-corrected differences-in-differences models

ABSTRACTA common problem with differences-in-differences (DD) estimates is the failure of the parallel-trend assumption. To cope with this, most authors include polynomial (linear, quadratic…) trends among the regressors, and estimate the treatment effect as a once-in-a-time trend shift. In practice, that strategy does not work very well, because inter alia the estimation of the trend uses post-treatment data. An extreme case is when sample covers only one period before treatment and many after. Then the trend’s estimate relies almost completely on post-treatment developments, and absorbs most of the treatment effect. What is needed is a method that i) uses pretreatment observations to capture linear or nonlinear trend differences, and ii) extrapolates these to compute the treatment effect. This article shows how this can be achieved using a fully flexible version of the canonical DD equation. It also contains an illustration using data on a 1994–2000 EU programme that was implemented in the Belgian province of Hainaut.

Genuine belief and genuine doubt in Peirce

AbstractPeirce makes it clear that doubt and belief oppose one another. But that slogan admits of a weaker and a stronger reading. The weaker reading permits and the stronger reading forbids one to be in a state of doubt and of belief with respect to the same proposition at the same time. The stronger claim is standardly attributed to Peirce, for textual and philosophical reasons. This paper maintains that this standard construal is excessively strong. It argues that the secondary literature tends to presuppose the strong reading and that it often does so by confusing sufficient conditions for belief with necessary ones. It acknowledges some textual evidence on behalf of the strong reading but maintains that, taken as a whole, the relevant passages are as friendly to the weak as to the strong interpretation of Peirce. The paper then links the doubt–belief theory of “The Fixation of Belief” to the papers on probability that occupy the bulk of the Illustrations of the Logic of Science. It shows that Peirce's discussion of probability, strength of belief, and weight of evidence makes room for confidence, but not belief, to be undermined and thus offers a more flexible version of Peirce's theory of inquiry.

Measuring Credit Demand and Supply: A Bayesian Model with an Application to Greece (2003–2011)

AbstractMotivated by the linkage between credit and growth in the Greek economy and the deceleration of credit since the financial crisis, this paper studies the evolution of credit demand and supply in Greece during the period 2003M1–2011M3. A model of the credit market is explored which disentangles demand and supply. A Bayesian estimation methodology with data augmentation for the latent variables is proposed. The analysis is carried out separately for each type of loan (short- and long-term business loans, consumer loans and mortgages) enabling the comparative study of the credit rationing and supply constraint effects across loan categories. The results indicate that, for all loan categories, excess demand characterized the boom period. After the intensification of the debt crisis, long-term business loans, consumer loans and mortgages were constrained from the supply side, however, demand for short-term business loans has slowed down more than supply, reflecting businesses’ need for stable funding. Finally, the structural effects of the crisis are investigated. The present paper aims to contribute to the strand of literature investigating the tools to analyse credit developments by formulating an enhanced and flexible version of a model which disentangles credit demand and supply and enables the monitoring of the evolution of financial imbalances.

Morocco: A Practical Approach to Monetary Policy Analysis in a Country with Capital Controls

The Central Bank of Morocco has been working on developing a Forecasting and Policy Analysis System (FPAS) to support a gradual move toward a more flexible exchange rate regime and the eventual adoption of a full-fledged inflation-targeting (IT) regime. At the center of the FPAS is a quarterly projection model that was tailored for two different types of exchange rate regimes. Presently, the fixed exchange rate model version is to be used during the pre-IT period, while the flexible exchange rate model version is to be used to prepare alternative scenarios for monetary policy decision makers to discuss the potential policy implications of shocks under an IT regime.