Spectrum analysis and prediction possibilities of the onset dates of southwest monsoon over Kerala (India)

Maximum Entropy Spectral Analysis of the time series for the onset dates of the southwest monsoon over Kerala (India) revealed several periodicities significant at a 2a a priori level. some at a 3 C a priori level However these contributed only 40-50% to the total variance thus indicating 50-60% as purely random component. Also many of the significant periodicities observed were in the QBO region (T = 2-3 years) which. due to their variable periodicities and amplitudes, are almost equivalent to a random component. Hence predictions were possible only with a limit exceeding 5 days which are probably not very useful for any planning purposes agricultural or otherwise. No relationship was found between onset dates of established monsoon rainfall and the 50 hPa mean monthly equatorial zonal wind for the months of March, April, May or June. However there is a possibility that a relationship may exist between westerly (easterly) winds in May and early (late) onset of the first monsoon (or pre-monsoon ?) rainfall in Kerala. Meager or otherwise.

Fixed points fix estimates: The accuracy of an effect size estimate is described by its sample’s conditional algorithmic information, as computed across rank permutations

Every statistical estimate is equal to the sum of a nonrandom component, due to parameter values and bias, and a random component, due to sampling error. Estimation theory suggests that the two components are hopelessly confounded in the estimate. We would like to estimate the sign and magnitude of a statistic’s random deviation from its parameter--its accuracy--in the same way we quantify a statistic’s random variability around its parameter--its precision--by estimating the standard error. However, because the random component is an attribute of the sample data, it be described with parametric or Fisher information. In information theory, on the other hand, every information type--entropy, complexity--is understood as describing the extent of randomness in manifest data. This suggests that integrating the two conceptions of information could allow us to describe the two components of a statistical estimate, if only we could identify a common link between the two paradigms.The matching statistic, m, is such a link. For paired, ranked vectors X and Y of length n, m is the total number of paired observations in X and Y with matching ranks, m = Σ R(Xi) = R(Yi). That is, m is the number of fixed points between vectors. m has a long history in statistics, having served as the test statistic of a little-known null hypothesis statistical test (NHST) for the correlation coefficient, dating to around the turn of the twentieth century, called the matching method. Subtracting m from n yields a metric with a long history in information theory, the Hamming distance, a classic metric of the conditional complexity K(Y|X). Thus, m simultaneously contains both the Fisher information in a bivariate sample about the latent correlation and the conditional complexity or algorithmic information about the manifest observations.This paper shows that the presence of these two conflicting information types in m manifests a peculiar attribute in the statistic: m has an asymptotic efficiency less than or equal to zero relative to conventional correlation estimators computed on the same data. This means its Fisher information content decreases with increasing sample size, so that m’s random component is disproportionately large. Furthermore, when m and Pearson’s r are computed on the same sample, the two share a random component, and the value of m is indicative of the accuracy of r with respect to that component. Having proven this utility of m, by means theoretical and empirical (Monte Carlo simulations), additional matching statistics are constructed, including one composite statistic that is even more informative of the accuracy of r, and another that is indicative of the accuracy of Cohen’s d. Potential applications for computing accuracy-adjusted r are described, and implications are discussed.

Application of analysis methods and forecasting of time series of indicators of the effectiveness of airworthiness maintaining of civil aircraft

The use of the analysis methodology and forecasting of time series of indicators of the effectiveness of maintaining airworthiness of aircraft of civil aviation made it possible to present the dynamics of indicators as a combination of the regular component, harmonic components with oscillation periods of 12 months and more, and a random component, which represents random processes developing under the influence of groups of factors affecting the airworthiness maintenance process. The results obtained are aimed at improving the safety and effectiveness of aircraft use. Keywords: aircraft, airworthiness, effectiveness of airworthiness maintenance, analysis methodology, forecasting, time series of effectiveness indicators. [email protected]

The Object According State Prediction to Diagnostic Data

The predicting methodology the state of the object based on diagnostic data is considered. With the selected parameter that determines the state of the object, it is measured in real time at a fixed sampling step. According to the measurement data, the value of this parameter is predicted in the future. This operation is implemented by an extrapolator of the l order - a l degree polynomial, built using the least squares method based on the previous measurements results. The changing process model of the diagnosed parameter is a random time function described by the stationary centered random component sum and a mathematical expectation deterministic change. The estimating prediction error method and the extrapolator parameters influence on its value are presented.

POTENTIAL APPLICATION OF HARDWARE PROTECTED SYMMETRIC AUTHENTICATION MICROCIRCUITS TO ENSURE THE SECURITY OF INTERNET OF THINGS

The paper objective is to determine the basic schemes and their characteristics for ensuring the security of Internet of Things nodes using symmetric authentication cryptographic microcircuits. The main results that had been obtained by using method of structural and functional design represent potentially possible options for using symmetric authentication cryptomicrocircuits to ensure the protection of Internet of Things nodes. The analysis of the presented schemes’ functioning made it possible to form the following conclusions. The host-side private key storage authentication scheme provides a fast symmetric authentication process, but requires secure storage of the private key on the host side. The simplest authentication scheme without storing a secret key on the host side, which does not imply the use of a cryptographic chip on the host side, provides a fast symmetric authentication process, but has a relatively low cryptographic strength, since the interaction in the system is performed without a random component in cryptographic transformations, which assumes constant the nature of requests in the system, and, consequently, the possibility of cryptanalysis of messages. To increase the cryptographic strength of such a scheme, it is advisable to introduce into the interaction system a random component in cryptographic transformations and use additional hashing procedures with an intermediate key, which leads to the complication of the scheme due to double hashing, but significantly increases the level of information security of IoT nodes. Downloading software in the system is implemented using secret encryption and authentication keys, which are permanently stored in the secure non-volatile memory of cryptographic chips of IoT nodes. In this case, session keys for encrypting the firmware code or decrypting it are generated on the client and host side, respectively. This approach allows creating unique downloads of the original firmware code (application) by preventing cryptanalysts from obtaining its images and algorithms. The peculiarity of the scheme of exchange of symmetric session encryption keys of messages are: use of a secret key stored on the side of the host and the client; the determination of the session key is performed as a result of hashing a random number with a secret key, that is, the exchange of the session key is performed in an encrypted secure form.

Determination of the Error in Transferring of Length Unit’s Size when Measuring the Nanoparticles’ Diameter Using an Analyzer of Particles’ Differential Electrical Mobility

The quality of nanomaterials and nanotechnologies is largely determined by the stability of the applied technologies, which, to a large extent, depend on the constancy of particle sizes. In this regard, metrological problems arise that are associated both with measuring the dimensions of the microstructure of aerosols, suspensions and powders, and with ensuring the uniformity of measurements when transferring a unit of a physical quantity from a standard to working measuring instruments. The purpose of this work was to determine and calculate the error in transferring the size of a unit of length when measuring the diameter of nanoparticles.An analyzer of differential electric mobility of particles was determined as a reference measuring instrument for which the calculation was made. It allows the separation of aerosol particles based on the dependence of their electrical mobility on the particle size. In combination with a condensation particle counter, it allows you to scan an aerosol and build a particle size distribution function. This measurement method is the most accurate in the field of measuring the diameters of particles in aerosols, therefore, the error in the transmission of particle size must be set as for a standard.The paper describes the physical principles of measurement by this method and presents an equation for determining the diameter of nanoparticles. Based on this equation, the sources of non-excluded systematic error were identified. Also, an experimental method was used to determine the random component of the measurement error of nanoparticles and to calculate the error in transferring the size of a unit of length when measuring the diameter of nanoparticles.The obtained results will be used for metrological support of standard samples of particle size, ensuring traceability of measurements of aerosol particle counters and for aerosol research.

Stochastic Population Models

The chapter “Stochastic Population Models” introduces the concept of stochasticity, why it is sometimes incorporated into models, the consequences of stochasticity for population models, and how these types of models are used to evaluate extinction risk. Ecological systems are (seemingly) governed by randomness, or “stochasticity.” A stochastic model is one that explicitly includes randomness in the prediction of state variable dynamics. Because these models have a random component, each model run will be unique and will rarely look like a deterministic simulation. In this chapter, simple unstructured and density-dependent models are presented to show core concepts, and extensions to structured and density-dependent models are given.

Phase-Structure in Conditional Simulation of Spatially Varying Ground Motion and Possible Influence on Structural Demand

Recorded ground motion is nonstationary in both intensity and frequency contents. Two methodologies were reported by the authors elsewhere for generating spatially varying ground motion (SVGM), namely, (i) auto-spectral density (ASD)-based framework, and (ii) evolutionary power-spectral density (EPSD)-based framework. While the former framework imparts nonstationarity through a uniform modulation (that accounts for nonstationarity only in intensities), the latter framework accounts for nonstationarity in both intensity and frequency contents. Reported EPSD-based framework was modeled through a decay function and a random component and was investigated only in the context of horizontal ground motion. Reported EPSD-based framework made two strong assumptions that need further investigation: (i) spatial variation of the random component was assumed to be frequency independent; and (ii) phase-structure of the ground excitation simulated around the reference station (with seed motion) was assumed to be same as that of the seed motion. This paper investigates the possible impact of these two assumptions on the simulated SVGM through appropriately revising the framework and introducing the phase-structure accordingly. Possible effects of the phase-structure on structural demand are investigated through an idealized long-span bridge. Revised EPSD-based framework is next assessed against the vertical recordings of SMART1 array along with the auto-spectral density (ASD) framework. Though spectral representation is nearly identical in both the frameworks, the acceleration time series simulated using the revised EPSD-based framework matches the recorded data better when compared with the ASD-based framework. Possible effect of spatially varying vertical ground motion on the seismic design is investigated through the same idealized bridge model. Significant increase in the demand of axial force in piers and mid-span moment in the deck are observed. Although these inferences are contingent on the idealized example considered for illustration, the spatially varying vertical ground motion is expected to contribute significantly to the seismic design of long-span bridges.

Impact of the ISM magnetic field on GRB afterglow polarization

Linear polarization has been measured in several GRB afterglows. After a few days, polarization arises from the forward shock emission which depends on the post-shock magnetic field. The latter can originate both from compression of existing fields, here the ISM magnetic field, and from shock generated instabilities. For short GRBs, previous modelling of the polarization arising from the forward shock considered a random field fully or partially confined to the shock plane. However, the ISM magnetic field likely consists of both random and ordered components. Here we study the impact of a more realistic magnetic field having both ordered and random components. We present our semi-analytical model and compute polarization curves arising for different magnetic field configurations. We find that the presence of an ordered component, even significantly weaker than the random one, has distinct signatures that could be detectable. In the presence of an ordered component not in the observer plane, we show that: i) for an observer inside the jet, the polarization angle θp either remains constant during all the afterglow phase or exhibits variations smaller than the 90○ swing expected from a random component solely, ii) for an off-axis observer, the polarization angle evolves from $\theta _p^{\max }$, before the jet break to its opposite after the jet break. We also find that the upper limit polarization for GRB170817 requires a random field not fully confined to the shock plane and is compatible with an ordered component as large as half the random one.

Risk Attitude in Multicriteria Decision Analysis: A Compromise Approach

In fields on which decisions need to be taken including health, as we are seeing nowadays in the COVID-19 crisis, decision-makers face multiple criteria and results with a random component. In stochastic multicriteria decision-making models, the risk attitude of the decision maker is a relevant factor. Traditionally, the shape of a utility function is the only element that represents the decision maker’s risk attitude. The eduction process of multi-attribute utility functions implies some operational drawbacks, and it is not always easy. In this paper, we propose a new element with which the decision maker’s risk attitude can be implemented: the selection of the stochastic efficiency concept to be used during a decision analysis. We suggest representing the risk attitude as a conflict between two poles: risk neutral attitude, associated with best expectations, and risk aversion attitude, associated with a lower uncertainty. The Extended Goal Programming formulation has inspired the parameter that is introduced in a new risk attitude formulation. This parameter reflects the trade-off between the two classical poles with respect to risk attitude. Thus, we have produced a new stochastic efficiency concept that we call Compromise Efficiency.