Reliable Distributed Fuzzy Discretizer for Associative Classification of Big data

Data Mining is an essential task because the digital world creates huge data daily. Associative classification is one of the data mining task which is used to carry out classification of data, based on the demand of knowledge users. Most of the associative classification algorithms are not able to analyze the big data which are mostly continuous in nature. This leads to the interest of analyzing the existing discretization algorithms which converts continuous data into discrete values and the development of novel discretizer Reliable Distributed Fuzzy Discretizer for big data set. Many discretizers suffer the problem of over splitting the partitions. Our proposed method is implemented in distributed fuzzy environment and aims to avoid over splitting of partitions by introducing a novel stopping criteria. Proposed discretization method is compared with existing distributed fuzzy partitioning method and achieved good accuracy in the performance of associative classifiers.

An Optimal Control Experiment for an SEIRS Epidemiological Model

This work studies an optimal control model for a discrete-time Susceptible/Exposed/Infective/Removed/Susceptible (SEIRS) deterministic epidemiological model with a finite time horizon and changing population. The model presented converts a continuous SEIRS model that would typically be solved using differential equations into a discrete model that can be solved using dynamic programming. The discrete approach more closely resembles real life situations, as the number of individuals in a population, the rate of vaccination to be applied, and the time steps are all discrete values. The model utilizes a previously developed algorithm and applies it to the presented SEIRS model. To demonstrate the applicability of the algorithm, a series of numerical results are presented for various parameter values. KEYWORDS: Control; Cost; Discrete; Disease; Epidemiology; Minimization; Modeling; Optimality; SEIRS; Vaccination

The method of discretization signals to minimize the fallibility of information recovery

The paper proposes a fundamentally new approach to the formulation of the problem of optimizing the discretization interval (frequency). The well-known traditional methods of restoring an analog signal from its discrete implementations consist of sequentially solving two problems: restoring the output signal from a discrete signal at the output of a digital block and restoring the input signal of an analog block from its output signal. However, this approach leads to methodical fallibility caused by interpolation when solving the first problem and by regularizing the equation when solving the second problem. The aim of the work is to develop a method for the signal discretization to minimize the fallibility of information recovery to determine the optimal discretization frequency.The proposed method for determining the optimal discretization rate makes it possible to exclude both components of the methodological fallibility in recovering information about the input signal. This was achieved due to the fact that to solve the reconstruction problem, instead of the known equation, a relation is used that connects the input signal of the analog block with the output discrete signal of the digital block.The proposed relation is devoid of instabilities inherent in the well-known equation. Therefore, when solving it, neither interpolation nor regularization is required, which means that there are no components of the methodological fallibility caused by the indicated operations. In addition, the proposed ratio provides a joint consideration of the properties of the interference in the output signal of the digital block and the frequency properties of the transforming operator, which allows minimizing the fallibility in restoring the input signal of the analog block and determining the optimal discretization frequency.A widespread contradiction in the field of signal information recovery from its discrete values has been investigated. A decrease in the discretization frequency below the optimal one leads to an increase in the approximation fallibility and the loss of some information about the input signal of the analog-to-digital signal processing device. At the same time, unjustified overestimation of the discretization rate, complicating the technical implementation of the device, is not useful, since not only does it not increase the information about the input signal, but, if necessary, its restoration leads to its decrease due to the increase in the effect of noise in the output signal on the recovery accuracy. input signal. The proposed method for signal discretization based on the minimum information recovery fallibility to determine the optimal discretization rate allows us to solve this contradiction.

Evolution of Hemodynamic Parameters Simulated by Means of Diffusion Models

Diffusion is a well-known physical phenomenon governing such processes as movement of particles or transportation of heat. In this paper, we prove that a close analogy to those processes exists in medical data behavior, and that changes in the values of medical parameters measured while treating patients may be described using diffusion models as well. The medical condition of a patient is usually described by a set of discrete values. The evolution of that condition and, consequently, of the disease has the form of a transition of that set of discrete values, which correspond to specific parameters. This is a typical medical diagnosis scheme. However, disease evolution is a phenomenon that is characterized by continuously varying, temporal characteristics. A mathematical disease evolution model is, in fact, a continuous diffusion process from one discrete slot of the diagnosed parameter value to another inside the mentioned set. The ability to predict such diffusion-related properties offer precious support in diagnostic decision-making. We have examined several hundred patients while conducting a medical research project. All patients were under treatment to stabilize their hemodynamic parameters. A diffusion model relied upon simulating the results of treatment is proposed here. Time evolution of thoraric fluid content (TFC) has been used as the illustrative example. The objective is to prove that diffusion models are a proper and convenient solution for predicting disease evolution processes. We applied the Fokker-Planck equation (FPE), considering it to be most adequate for examining the treatment results by means of diffusion. We confirmed that the phenomenon of diffusion explains the evolution of the heart disease parameters observed. The evolution of TFC has been chosen as an example of a hemodynamic parameter.

A graphical method of cumulative differences between two subpopulations

Comparing the differences in outcomes (that is, in “dependent variables”) between two subpopulations is often most informative when comparing outcomes only for individuals from the subpopulations who are similar according to “independent variables.” The independent variables are generally known as “scores,” as in propensity scores for matching or as in the probabilities predicted by statistical or machine-learned models, for example. If the outcomes are discrete, then some averaging is necessary to reduce the noise arising from the outcomes varying randomly over those discrete values in the observed data. The traditional method of averaging is to bin the data according to the scores and plot the average outcome in each bin against the average score in the bin. However, such binning can be rather arbitrary and yet greatly impacts the interpretation of displayed deviation between the subpopulations and assessment of its statistical significance. Fortunately, such binning is entirely unnecessary in plots of cumulative differences and in the associated scalar summary metrics that are analogous to the workhorse statistics of comparing probability distributions—those due to Kolmogorov and Smirnov and their refinements due to Kuiper. The present paper develops such cumulative methods for the common case in which no score of any member of the subpopulations being compared is exactly equal to the score of any other member of either subpopulation.

Choosing an approach to statistical processing of the ship’s pitching record

The developed instrumentation and software provides discrete values for the angles of a vessel’s list on an operational voyage in sea conditions at specified time intervals.The half-periods of pitching are considered; the half-period and the corresponding pitching amplitude can be obtained in three different ways: as the amplitude from one board to the other one with the reference of the initial peak-to-peak amplitude or with the reference of the final peak-to-peak amplitude; as the time interval of the ship listing on one side between zero roll angles. It was found that each method corresponds to its own, different from the others, amplitude-period statistics. This makes it difficult to compare different registrations and identify the essential reactions of the vessel to the seaway, unless a method is specified for determining the half-periods and linking the roll amplitudes to them. The proposal is justified to unify the processing by defining the half-period as the time of the ship listing on one board with the corresponding amplitude angle of the roll, that is, as the difference of the moments of time between two next values of the zero angle of the roll.

Comparison of spatial interpolation methods for estimation of weekly rainfall in West Bengal, India

Rainfall is one of the most eloquently researched contemporary meteorological phenomena affecting the agricultural practices dramatically, particularly along the humid, sub-tropics, where agriculture is predominantly rainfed. It is a key parameter of agricultural production in West Bengal due to lack irrigation facilities in most of the areas. Thus, it is very important to have detailed information of rainfall distribution pattern of West Bengal. In practice rainfall data is collected only at few discrete stations scattered all over the whole state. However, rainfall is a spatially continuous phenomenon rather than discrete. Thus it becomes essential to apply a robust spatial interpolation technique to transform the discrete values into a continuous spatial pattern. In the present study, three spatial interpolation techniques namely Kriging, Inverse Distance Weighted (IDW) and SPLINE, are used for a comparative analysis to identify the most efficient interpolation technique. Weekly average rainfall data available between 1901 and 1985 for 19 standard meteorological weeks (SMW), Week 22 to Week 40 are used for the analysis. The errors of the three interpolation techniques are analyzed and the best method is chosen based on the minimum mean absolute deviation (MAD) and the minimum mean squared deviation (MSD) criteria. The IDW method is found to be the best spatial interpolation technique.

Estimation of Depth of Discharge of Li-ion Battery Using Neural Network

This paper deals with the estimation of depth of discharge for Li-ion batteries. Estimation is based on the knowledge of discharging curves measured for discrete values of loading currents. The estimator of the depth of discharge is a form of feedforward neural network which is trained with the measured data of discharge curves. Accuracy of estimation of the depth of discharge is shown for arbitrary generated and measured loading characteristics, where the depth of discharge is estimated by the designed neural network and measured by using the Coulomb counting method.

Static Metasurface Reflectors with Independent Magnitude and Phase Control using Coupled Resonator Configuration

<div>A static metasurface reflector based on a novel coupled resonator configuration is proposed to independently control</div><div>the reflection phase and magnitude of linearly polarized incident fields, and is demonstrated experimentally in the millimeter-wave Ka-band around 30 GHz. The proposed concept is illustrated using a unit cell design consisting of a rectangular ring coupled with a rectangular slot resonator backed by a grounded dielectric slab. By geometrically tuning various dimensions of the two resonators, a near-perfect amplitude-phase coverage is achieved at a fixed design frequency of 30 GHz. To demonstrate the flexible beam-forming capability of the proposed metasurface reflectors, illustrative examples of fixed beam steering with varying reflection magnitudes, and asymmetric dual-beam patterns with specified reflection magnitude, reflection angles and beam-widths, are successfully shown. Compared to the standard method based on polarization rotation and resistive loadings with discrete values, the proposed technique does not generate undesired cross-polarization field reflection, and provides a continuous magnitude tuning including full absorption, along with wide phase coverage.</div>

Static Metasurface Reflectors with Independent Magnitude and Phase Control using Coupled Resonator Configuration

<div>A static metasurface reflector based on a novel coupled resonator configuration is proposed to independently control</div><div>the reflection phase and magnitude of linearly polarized incident fields, and is demonstrated experimentally in the millimeter-wave Ka-band around 30 GHz. The proposed concept is illustrated using a unit cell design consisting of a rectangular ring coupled with a rectangular slot resonator backed by a grounded dielectric slab. By geometrically tuning various dimensions of the two resonators, a near-perfect amplitude-phase coverage is achieved at a fixed design frequency of 30 GHz. To demonstrate the flexible beam-forming capability of the proposed metasurface reflectors, illustrative examples of fixed beam steering with varying reflection magnitudes, and asymmetric dual-beam patterns with specified reflection magnitude, reflection angles and beam-widths, are successfully shown. Compared to the standard method based on polarization rotation and resistive loadings with discrete values, the proposed technique does not generate undesired cross-polarization field reflection, and provides a continuous magnitude tuning including full absorption, along with wide phase coverage.</div>