94 research outputs found
Analysis of Antarctic Ice Core Data (EPICA Dome C) with Flicker-Noise Spectroscopy
Evolution of Earth’s climate system over the past 800,000 years represents a complex process with successions of uneven glacial and interglacial periods. The length, amplitudes, and development of each climate cycle depend on a number of different factors, including the orbital parameters attributed to insolation and the complex responses of the Earth system to solar radiation primarily through the amplification by Earth’s albedo and greenhouse gas and secondarily through a system of heat reservoirs, such as ice sheet and deep ocean, distributed throughout our planet. The purpose of this study is to analyze the transitions related to climate cycles in Antarctic ice core data (EPICA Dome C) of deuterium composition and dust concentration recorded for the past 800,000 years [1] using Flicker-Noise Spectroscopy (FNS), an analytical toolset for the extraction and analysis of information in stochastic time and space series, containing both regular and chaotic components, by using power spectra and difference moments (structural functions) of various orders [2]. 

The FNS nonstationarity factors for the deuterium composition and dust (logarithm) concentration, which represent the normalized discrete derivative of the second-order structural function of the source signal with respect to a given shifted “window” interval, were built for different intervals of averaging to identify the major changes in the dynamics of both time series and their precursors. It is shown that when displayed together with the source signals, the positive peaks in the nonstationarity factors provide more reliable estimates of the transition of the climate system from one sub-period to another within a specific climate cycle as compared to predefined thresholds in dust or deuterium values. For climatic transitions, the power spectral estimates of the nonstationarity factors contain several periodicities in addition to the orbital ones. These frequencies may be attributed to specific heat accumulation and discharge processes in the climate system. The results of this study demonstrate the potential of FNS in the analysis of climate data series and may be used in refining climate transition models.

This study was supported by the Russian Foundation for Basic Research, project no. 08-02-00230a.
[1] Lambert F., et al. (2008) Dust-climate couplings over the past 800,000 years from the EPICA Dome C ice core, Nature 452, 616-619.
[2] Timashev, S. F., Polyakov Yu. S. (2007) Review of flicker noise spectroscopy in electrochemistry, Fluctuations and Noise Letters 7(2), R15-R47.

Is Sustainable Development of Deserts Feasible?
Hot deserts that presently cover about one-fifth of the land area of our planet are rapidly devouring more and more arable lands mostly due to anthropogenic causes. We propose an interdisciplinary approach to revitalizing and commercializing hot deserts, which is based on systems thinking and Russian and NASA space technology experience in designing life-support systems for long-duration flights. We formulate ten principles for the design of sustainable life support systems in deserts, which can make the development of the deserts feasible. It is discussed how the principles can be employed to design and operate desert’s eco-industrial parks with greenhouses in which the transpired and evaporated moisture is collected and condensed. The potential benefits of setting up the eco-industrial parks in deserts include the slowdown and eventual reversal of the desertification trend, the migration of many industrial production facilities from mild-climate regions to deserts, the increased availability of potable water and food in deserts, the development of poor African countries, and the emergence of new investment markets
Is It Possible to Predict Strong Earthquakes?
The possibility of earthquake prediction is one of the key open questions in
modern geophysics. We propose an approach based on the analysis of common
short-term candidate precursors (2 weeks to 3 months prior to strong
earthquake) with the subsequent processing of brain activity signals generated
in specific types of rats (kept in laboratory settings) who reportedly sense an
impending earthquake few days prior to the event. We illustrate the
identification of short-term precursors using the groundwater sodium-ion
concentration data in the time frame from 2010 to 2014 (a major earthquake
occurred on February 28, 2013), recorded at two different sites in the
south-eastern part of the Kamchatka peninsula, Russia. The candidate precursors
are observed as synchronized peaks in the nonstationarity factors, introduced
within the flicker-noise spectroscopy framework for signal processing, for the
high-frequency component of both time series. These peaks correspond to the
local reorganizations of the underlying geophysical system that are believed to
precede strong earthquakes. The rodent brain activity signals are selected as
potential "immediate" (up to 2 weeks) deterministic precursors due to the
recent scientific reports confirming that rodents sense imminent earthquakes
and the population-genetic model of Kirshvink (2000) showing how a reliable
genetic seismic escape response system may have developed over the period of
several hundred million years in certain animals. The use of brain activity
signals, such as electroencephalograms, in contrast to conventional abnormal
animal behavior observations, enables one to apply the standard
"input-sensor-response" approach to determine what input signals trigger
specific seismic escape brain activity responsesComment: 28 pages, 3 figures; accepted by Pure and Applied Geophysics. arXiv
admin note: text overlap with arXiv:1202.0096, arXiv:1101.147
Feedback algorithm for switch location : analysis of complexity and application to network design
An accelerated feedback algorithm to solve the single-facility minisum problem is studied with application to designing networks with the star topology. The algorithm, in which the acceleration with respect to the Weiszfeld procedure is achieved by multiplying the current Weiszfeld iterate by an accelerating feedback factor, is shown to converge faster than the accelerating procedures available in the literature. Singularities encountered in the algorithm are discussed in detail. A simple practical exception handling subroutine is developed. Several applications of the algorithm to designing computer networks with the star topology are demonstrated. Applications of the algorithm as a subroutine for multi-switch location problems are considered. Various engineering aspects involved in acquiring and processing coordinates for geographic locations are discussed. A complete algorithm in pseudocode along with the source code listing in Mathematica 4.1 is presented
Analytical method for parameterizing the random profile components of nanosurfaces imaged by atomic force microscopy
The functional properties of many technological surfaces in biotechnology,
electronics, and mechanical engineering depend to a large degree on the
individual features of their nanoscale surface texture, which in turn are a
function of the surface manufacturing process. Among these features, the
surface irregularities and self-similarity structures at different spatial
scales, especially in the range of 1 to 100 nm, are of high importance because
they greatly affect the surface interaction forces acting at a nanoscale
distance. An analytical method for parameterizing the surface irregularities
and their correlations in nanosurfaces imaged by atomic force microscopy (AFM)
is proposed. In this method, flicker noise spectroscopy - a statistical physics
approach - is used to develop six nanometrological parameters characterizing
the high-frequency contributions of jump- and spike-like irregularities into
the surface texture. These contributions reflect the stochastic processes of
anomalous diffusion and inertial effects, respectively, in the process of
surface manufacturing. The AFM images of the texture of corrosion-resistant
magnetite coatings formed on low-carbon steel in hot nitrate solutions with
coating growth promoters at different temperatures are analyzed. It is shown
that the parameters characterizing surface spikiness are able to quantify the
effect of process temperature on the corrosion resistance of the coatings. It
is suggested that these parameters can be used for predicting and
characterizing the corrosion-resistant properties of magnetite coatings.Comment: 7 pages, 3 figures, 2 tables; to be published in Analys
Anomalous diffusion in the dynamics of complex processes
Anomalous diffusion, process in which the mean-squared displacement of system
states is a non-linear function of time, is usually identified in real
stochastic processes by comparing experimental and theoretical displacements at
relatively small time intervals. This paper proposes an interpolation
expression for the identification of anomalous diffusion in complex signals for
the cases when the dynamics of the system under study reaches a steady state
(large time intervals). This interpolation expression uses the chaotic
difference moment (transient structural function) of the second order as an
average characteristic of displacements. A general procedure for identifying
anomalous diffusion and calculating its parameters in real stochastic signals,
which includes the removal of the regular (low-frequency) components from the
source signal and the fitting of the chaotic part of the experimental
difference moment of the second order to the interpolation expression, is
presented. The procedure was applied to the analysis of the dynamics of
magnetoencephalograms, blinking fluorescence of quantum dots, and X-ray
emission from accreting objects. For all three applications, the interpolation
was able to adequately describe the chaotic part of the experimental difference
moment, which implies that anomalous diffusion manifests itself in these
natural signals. The results of this study make it possible to broaden the
range of complex natural processes in which anomalous diffusion can be
identified. The relation between the interpolation expression and a diffusion
model, which is derived in the paper, allows one to simulate the chaotic
processes in the open complex systems with anomalous diffusion.Comment: 47 pages, 15 figures; Submitted to Physical Review
Bootstrapping in FHEW-like Cryptosystems
FHEW and TFHE are fully homomorphic encryption (FHE) cryptosystems that can evaluate arbitrary Boolean circuits on encrypted data by bootstrapping after each gate evaluation. The FHEW cryptosystem was originally designed based on standard (Ring, circular secure) LWE assumptions, and its initial implementation was able to run bootstrapping in less than 1 second. The TFHE cryptosystem used somewhat stronger assumptions, such as (Ring, circular secure) LWE over the torus with binary secret distribution, and applied several other optimizations to reduce the bootstrapping runtime to less than 0.1 second. Up to now, the gap between the underlying security assumptions prevented a fair comparison of the cryptosystems for the same security settings.
We present a unified framework that includes the original and extended variants of both FHEW and TFHE cryptosystems, and implement it in the open-source PALISADE lattice cryptography library using modular arithmetic. Our analysis shows that the main distinction between the cryptosystems is the bootstrapping procedure used: Alperin-Sherif--Peikert (AP) for FHEW vs. Gama--Izabachene--Nguyen--Xie (GINX) for TFHE. All other algorithmic optimizations in TFHE equally apply to both cryptosystems. The GINX bootstrapping method makes essential the use of binary secrets, and cannot be directly applied to other secret distributions. In the process of comparing the two schemes, we present a simple, lightweight method to extend GINX bootstrapping (e.g., as employed by TFHE) to ternary uniform and Gaussian secret distributions, which are included in the HE community security standard. Our comparison of the AP and GINX bootstrapping methods for different secret distributions suggests that the TFHE/GINX cryptosystem provides better performance for binary and ternary secrets while FHEW/AP is faster for Gaussian secrets. We make a recommendation to consider the variants of FHEW and TFHE cryptosystems based on ternary and Gaussian secrets for standardization by the HE community
Demystifying Bootstrapping in Fully Homomorphic Encryption
Bootstrapping is a term used very often in the context of Fully Homomorphic Encryption (FHE). Anyone who is familiar with FHE knows that bootstrapping is the most sophisticated and compute-intensive component of an FHE scheme. However, very few non-FHE-experts understand what the bootstrapping operation really is and that there are various bootstrapping methods, each with its own tradeoffs. The goal of this paper is to provide a high-level introduction to common bootstrapping methods and evaluate their performance using the existing implementations in OpenFHE and HElib open-source libraries.
Our performance evaluation suggests that the bootstrapping in the Cheon-Kim-Kim-Song (CKKS) scheme provides highest throughput and efficiently achieves large precision for vectors of real numbers, which are often used in machine learning applications. The Ducas-Micciancio (DM) and Chillotti-Gama-Georgieva-Izabachene (CGGI) schemes achieve the smallest latency (typically for small integers or small-precision fixed-point numbers) and provide a general capability for evaluating arbitrary functions (programmable bootstrapping) via lookup tables. The Brakerski-Gentry-Vaikuntanathan (BGV) and Brakerski/Fan-Vercauteren (BFV) schemes provide higher bootstrapping throughput than DM/CGGI for vectors of small integers or finite-field elements but do not support programmable bootstrapping.
The target audience is anyone interested in FHE. We intend to keep this paper up-to-date to include new bootstrapping results as they become available
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