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Abstract: Costa''s dirty paper coding (DPC) offers a good framework for precoding for transmission over additive Gaussian channels with additive states non-causally known at the transmitter but not at the receiver. In this paper, rate calculation, error probability analysis and code design for DPC are investigated from a practical point-of-view. Based on Monte-Carlo numerical integration and simulations, we first show that the gap to the full AWGN capacity can be partially bridged using some finite-dimensional lattices with good packing and quantizing properties. Then the difficult problem of codebook selection is addressed through some illustrative examples. Analysis sheds light on the dual roles of “packing” and “shaping” as well as on their inter-connection at finite-dimensional coding, by opposition to the asymptotic case (i.e., infinite dimension) where the two coding components are decoupled. [Copyright &y& Elsevier]

In the paper Patterson – Wiedemann construction revisited by Gangopadhyay et al. (2006), modifying an idempotent function f : G F ( 2 21 ) → G F ( 2 ) , which corresponds to a ( 337 , ( 127 ) ( 49 ) ) -interleaved sequence whose columns are either all 0’s or 1’s, a balanced function h having Δ h < 2 21 + 1 2 is obtained. In this short note, we find that Δ f is computed incorrectly in their paper (leading to Δ h ≮ 2 21 + 1 2 ) and correct their result by disproving the related conjecture for the 21-variable balanced functions. [ABSTRACT FROM AUTHOR]

Boolean functions used in symmetric-key encryption should have high higher-order nonlinearity to resist several known cryptographic attacks, such as algebraic attacks and low-degree approximation attacks. The higher-order nonlinearity also plays an important role in coding theory and theoretical computer science, since it relates to the covering radius of Reed–Muller codes and the Gowers norm, respectively. It is well-known that bent functions have the highest nonlinearity in an even number of variables and thus they possess the best ability to withstand fast correlation attacks and best affine approximation attacks. However, there is currently limited knowledge regarding the higher-order nonlinearity of bent functions because computing the higher-order nonlinearity, or even providing tight lower bounds, is an extremely hard task. In 1974, Dillon proposed two well-known classes of bent functions based on partial spread (in brief, PS), called PS − and PS + , respectively. He also exhibited a subclass of bent functions in PS − , known as partial spread affine plane(PS a p for short). In this paper, we provide a lower bound on the third-order nonlinearity of the simplest PS a p bent functions in n variables, where n ≥ 6 is even, by calculating the nonlinearities of all second-order derivatives of this kind of bent functions. Compared to the two known lower bounds on the third-order nonlinearity given by Carlet and Tang et al. respectively, our lower bound is much better than these two ones. [ABSTRACT FROM AUTHOR]

A well studied problem in algebraic complexity theory is the determination of the complexity of problems relying on evaluations of bilinear maps. One measure of the complexity of a bilinear map (or 3-tensor) is the optimal number of non-scalar multiplications required to evaluate it. This quantity is also described as its tensor rank, which is the smallest number of rank-1 matrices whose span contains its first slice space. In this paper we derive upper bounds on the tensor ranks of certain classes of 3-tensors and give explicit constructions of sets of rank-1 matrices containing their first slice spaces. We also show how these results can be applied in coding theory to derive upper bounds on the tensor rank of some rank-metric codes. In particular, we compute the tensor rank of some families of F q m -linear codes and we show that they are extremal with respect to Kruskal's tensor rank bound. [ABSTRACT FROM AUTHOR]

Elastomeric solid materials typically exhibit a pronounced viscoelastic response. In this paper we consider a large deformation viscoelasticity theory for isotropic elastomeric materials which uses a multi-branch multiplicative decomposition of the deformation gradient. We then describe the numerical implementation of the theory in the open-source finite element program FEniCSx. Several example simulations which demonstrate the capability of the theory and its numerical implementation to model stress-relaxation, creep, stretch-rate sensitivity, hysteresis, damped inertial oscillations, and dynamic column buckling are shown. The source codes for these simulations are provided. The theory and the codes presented in this paper lay the foundation for future extensions of the theory and its numerical implementation to include the effects of coupling with thermal, electrical, and magnetic fields — extensions which are of central importance in modeling the response of soft-active materials. • A large deformation viscoelasticity theory for elastomeric materials is considered. • The theory is numerically implemented in the open-source software FEniCSx. • Example simulations show the robustness of the theory and numerical implementation. • Source codes are provided. [ABSTRACT FROM AUTHOR]

Data aggregation involves the integration of relevant data generated across platforms and devices, leveraging the potential value of sensory data. However, in addition to security and efficiency, which are the basic requirements for data aggregation involving private data, how to achieve fault tolerance and interference of aggregation in real computing networks is imminent and is the main contribution of this paper. In this paper, we propose a secure aggregation framework involving multiple servers based on coding theory, which is not only robust to clients dropping out and tolerant to partial server withdrawal but also resistant to malicious computation by servers and forgery attacks by adversaries. In particular, the proposed protocol employs the Chinese Residual Theorem (CRT) to encode private data and constructs Lagrange interpolation polynomials to perform aggregation, which achieves lightweight privacy preservation while achieving robust, verifiable and secure aggregation goals. • We propose a lightweight computational scheme for aggregation. By adopting the CRT and encoding theory, private data is encoded into polynomial coefficients for aggregation and the random data are introduced for confidential to non-collusive servers. • We propose a non-interactive verifiable security aggregation protocol that satisfies the requirements of clients dropping out and partial server corruption. Furthermore, by introducing redundant shares and utilizing results returned by delayed servers, the proposed scheme achieves verifiable computation. • We provide a thorough analysis of the robustness, verification and security of our proposed. The experimental results show that the proposed scheme is effective in both computation and verification. [ABSTRACT FROM AUTHOR]

Let F q denote the finite field of size q and F q n denote the set of n -tuples of elements from F q. A family of k -dimensional subspaces of F q n , which forms a partial spread, is called L -almost affinely disjoint (or briefly [ n , k , L ] q -AAD) if each affine coset of a member of this family intersects with only at most L subspaces from the family. Polyanskii and Vorobyev introduced AAD subspace families in [23] (2019) in order to construct some types of primitive batch codes. For this purpose, they made use of Reed-Solomon codes and hence they presented [ n = 2 k + 1 , k , L = k ] -AAD subspace families of size ⌊ q / k ⌋. Later on, AAD spaces received a notable attention and have been studied for various parameters, see Liu et al. [18] (2021) and Otal and Arıkan [21] (2022) for example. In Arıkan et al. (2023) [1] , we presented a construction of [ 2 k + 1 , k , k ] -AAD subspace families of size q , which improves the lower bound ⌊ q / k ⌋ given by Polyanskii and Vorobyev in [23] (2019) k times. We also proved that our construction yields AAD subspace families for k = 2 and k = 3 , and left the proof of the case k ≥ 4 as a conjecture. In this paper, we now prove this conjecture by a newer and more abstract approach. For the proof, we carefully utilize several sophisticated arguments coming from coding theory, algebraic geometry, and linear algebra. In particular, we interpret each subspace as a suitable generator matrix (the lifting idea in random network coding), then algebraically manipulate their AAD-ness relation and produce suitable Van der Monde matrices (the fundamental tools for the BCH bound in coding theory), later apply Cramer's rule (a well-known key tool in linear algebra), and lastly obtain low-degree polynomials as contradictions (the trick coming from algebraic geometry utilized for Goppa codes). We present our constructive proof step-by-step to make it more easy to understand. [ABSTRACT FROM AUTHOR]

Shallow seismic events often induce long-period ground motions in distant sedimentary basins, which can cause damage to structures. The current design earthquake input is usually based on amplitude, while the equally essential phase characteristics of far-field basin seismic waves are often ignored. To address this issue, this paper proposes a semi-empirical model based on group delay, which integrates the effects of source, path, local site, and basin on group delay, we characterize randomness of group delay through a parametric Gaussian probability framework, and approximates the frequency non-stationarity of positive and negative dispersion by introducing piecewise spline gradient regression. As an improvement of the stochastic finite fault method, the proposed method solves the problem that the original method cannot sufficiently reflect the phase characteristics and frequency non-stationarity of basin-induced seismic waves. Based on this model, the stochastic finite fault method and the spectral element method are combined to perform the hybrid simulation of basin ground motion, and the earthquake of 2003 Tokachi-Oki verifies the reliability of the proposed method. This study broadens research by integrating physical information and frequency non-stationarity in the Stochastic Finite-Fault method, supplementing existing literature on Hybrid broadband simulation methods for predicting long-period ground motion in far-field basins with several novel insights: • Introducing a new perspective on stochastic fluctuation theory, associating group delay with physical information (e.g., earthquake magnitude, path factors). • Characterizing randomness of group delay through a parametric Gaussian probability framework and approximating frequency non-stationarity using piecewise spline gradient regression, leading to a modified stochastic finite fault method. • Applying a new Hybrid Broadband (BB) simulation methodology: SEM for LF wave propagation and Modified Stochastic Finite-Fault for HF components, capturing phase characteristics and frequency non-stationarity caused by the basin. [ABSTRACT FROM AUTHOR]

In this paper we focus on modules over a finite chain ring R of size q s. We compute the density of free modules of R n , where we separately treat the asymptotics in n , q and s. In particular, we focus on two cases: one where we fix the length of the module and one where we fix the rank of the module. In both cases, the density results can be bounded by the Andrews-Gordon identities. We also study the asymptotic behaviour of modules generated by random matrices over R. Since linear codes over R are submodules of R n we get direct implications for coding theory. For example, we show that random codes achieve the Gilbert-Varshamov bound with high probability. [ABSTRACT FROM AUTHOR]

Accurate PM 2.5 forecasting provides a possibility for establishing an early warning system to notify the public and take precautionary measures to prevent negative effects on ambient air quality and public health. Considering strong seasonal variation in meteorological conditions, in this paper, a seasonal stacked autoencoder model combining seasonal analysis and deep feature learning is proposed for forecasting the hourly PM 2.5 concentration, named DL-SSAE model. The original data are firstly decomposed into four seasonal subseries according to the Chinese calendar, and then the Kendall correlation coefficient method is employed to search inherent relationships between PM 2.5 concentrations and meteorological parameters within 1-h ahead for each seasonal time series. The inherent relationships of each seasonal subseries are finally extracted, learned, and modeled by different deep neural networks (stacked autoencoders for regression), and the hourly PM 2.5 forecasts are yielded. The addressed model is tested by the dataset collected from three environmental monitoring stations in Beijing, China. The results demonstrate that the proposed model outperforms all other considered models with/without seasonality consideration in this paper. [ABSTRACT FROM AUTHOR]

• Interpolative coding is efficient at chain code compression. • Interpolative coding is improved with Golomb coding. • Proper selection of Golomb parameter yields slightly better compression. A lossless chain code compression algorithm consisting of Burrows-Wheeler Transform, Move-To-Front Transform, and a modified interpolative coding is presented in this paper. The interpolative coding divides a strictly increasing array of integers and encodes the middle element recursively, where the required number of bits is obtained from the difference of the array's border values. In this paper, it is shown that, for some intervals, Golomb coding is more efficient than the interpolative coding. This fact was used to construct a hybrid approach that yields slightly better compression results than the state-of-the-art while compressing Three OrThogonal chain code, Freeman chain code in four and eight directions, and Vertex Chain Code. [ABSTRACT FROM AUTHOR]

The high demand for Meteosat image sequences for various fields and the high rate of presentation of methods dealing with these latter is facing with the low rate of presentation of remote sensing image sequence compression methods generally for different imagers. To tackle this issue, a novel Meteosat image sequence coding method in the Radon field is presented in this paper. The idea behind this paper is to show the contribution of the coding in Radon field to an efficient lossless compression. The Radon field, represented here by a new fast Mojette transform (FMT), gives a homogeneous field through a Mojette matrix engendered by the intra-projections and inter-projections redundancy. As a consequence, the use of an efficient block-based motion estimation (ME) algorithm such as adaptive rood pattern search (ARPS) becomes possible in a such environment, which can help to avoid many problems encountered when using the same techniques for remote sensing image as a block effect by way of example. In order to achieve a high lossless compression, the Sorted Run Length Coding (SRLC) is applied to encode besides the motion vectors (MVs), the residual error represented by separate long sequences of zeros in addition to other repeated symbols. The test phase showed that our proposed scheme exceeds the performances of the JPEG-LS standard. The proposed scheme can also be used as pre-technique for methods using Meteosat images in general and their sequences in particular after the decompression process such as meteorological phenomena tracking, segmentation, and so on. [ABSTRACT FROM AUTHOR]

Code based cryptography is a powerful and a promising alternative to the number theoretic cryptography as it is supposed to resist to the quantum computer. The migration to the post quantum hypothetical world requires the design of all the most important cryptographic primitives such as signature schemes. For this reason, we propose in this paper a ring signature and a threshold ring signature schemes that are based on coding theory assumptions. In the case of threshold ring signature scheme, we have a subset of users belonging to a group of users called a ring who collaborate in order to produce a signature on behalf of ring members while maintaining the anonymity of the identity of the real signers. In this paper, we use the AGS identification scheme, which is a coding theory zero-knowledge authentication protocol, to produce a ring signature and a threshold ring signature. By comparing our schemes with the best one in performance so far on 80 bits security level, we find an average 86% reduction of the signature size and also a reduction on the public key length at equivalent security level. The reduction is achieved for different values of the number of signers and ring's size. [ABSTRACT FROM AUTHOR]

Abstract ASME B31 and EN 13480-3 piping design codes are considered as the state-of-the-art codes for many piping engineers. However, as shown in this paper, there seem to be inconsistencies between ASME B31 code and more elaborate calculation codes, such as ASME Section III. In fact, it is shown in the paper that the ASME B31 approach can produce potentially non-conservative results. This seemingly important flaw in the B31 (and other major) piping codes is based on the allowable stress calculation based on equation (1b) of both ASME B31.1 and B31.3 and has been shown in detail in the paper. Finally, the stated flaw is verified by means of a finite element analysis which corroborates the stated concerns. Highlights • Paper presents an overview and comparison of various piping Code philosophies. • Critical overview of verification criteria is provided. • New acceptance criteria which guarantee conservative design are proposed. • Validation of the statements given in form of FEA verification. [ABSTRACT FROM AUTHOR]

Abstract This paper postulates that linguistic message in speech is coded redundantly in both the time and the frequency domains. Such redundant coding of the message in the signal evolved over millennia of human evolution so that relevant spectral and temporal properties of human hearing can be used to extract these messages in the presence of noise. This view of human speech suggests a particular architecture of an automatic recognition (ASR) system in which longer temporal segments of spectrally-smoothed temporal trajectories of spectral energies in individual frequency bands of speech are used to derive estimates of the posterior probabilities of speech sounds. Combinations of these estimates in reliable frequency bands are then adaptively fused to yield the final probability vectors, which best satisfy the adopted performance monitoring criteria. Some ASR systems, which already use elements of the suggested architecture are mentioned in this paper. Graphical abstract Image, graphical abstract [ABSTRACT FROM AUTHOR]

• The paper focuses on evaluating the stress on distribution class surge arresters (SAs) caused by lightning strikes. • Two different SA representations are considered, namely, a static nonlinear resistance and a dynamic, frequency dependent model. • The paper assesses the effect of several factors on the current and energy absorption, namely the presence of a periodically grounded shield wire, of the grounding resistance value, and of the distance between subsequent SAs. • The analysis shows that the static model can be considered accurate enough for evaluating the stress originated by direct and indirect lightnings on distribution class SAs. The paper focuses on evaluating the stress on distribution class surge arresters (SAs) caused by lightning strikes. It proposes a procedure for estimating the statistical distribution of energy absorbed by SAs due to both indirect and direct lightning strikes, which is a crucial step for assessing the probability of SAs failure. Two different SA representations are considered, namely, a static nonlinear resistance and a dynamic, frequency dependent model. After analyzing the overvoltage and current waveforms caused by lightning strikes and considering the effect of flashover occurrence, the paper assesses the effect of several factors on the current and energy absorption, namely the presence of a periodically grounded shield wire, of the grounding resistance value, and of the distance between subsequent SAs. The analysis shows that the static model can be considered accurate enough for evaluating the stress originated by direct and indirect lightning on distribution class SAs. [ABSTRACT FROM AUTHOR]

• A new simulation framework based on the PINNs is presented for modelling crack problems. • An enriched PINNs is proposed to correctly capture the local crack-tip behavior. • The SIFs can be directly calculated with very high accuracy. • A deep-learning algorithm written in MATLAB is provided. In this paper, a method based on the physics-informed neural networks (PINNs) is presented to analyze 2D in-plane crack problems in the linear elastic fracture mechanics. Instead of using a discretizing mesh, the PINNs-based method is meshless and can be trained on batches of discretely sampled collocation points. In order to capture the asymptotic behavior of the near-tip displacement and stress fields, the standard PINNs formulation is enriched here by including the crack-tip asymptotic functions such that the local behavior in the crack-tip region can be modeled accurately without a nodal refinement. The trainable parameters of the enriched PINNs are learned to satisfy the governing partial differential equations of the cracked elastic solid and the corresponding boundary conditions. It is found that the incorporation of the crack-tip enrichment functions in the PINNs is substantially simpler and more feasible than in the conventional finite element method (FEM) or boundary element method (BEM). The present PINNs-based algorithm is tested and verified by several representative benchmark examples for different loading and crack-mode types. Numerical results show that the present PINNs-based method can provide highly accurate stress intensity factors (SIFs) with only few degrees of freedom. For interested readers, a self-contained MATLAB code and data-sets supplementing this paper are also provided in the Supplementary material. [ABSTRACT FROM AUTHOR]

Linear complementary dual (LCD) codes and linear complementary pairs (LCP) of codes have been proposed for new applications as countermeasures against side-channel attacks (SCA) and fault injection attacks (FIA) in the context of direct sum masking (DSM). The countermeasure against FIA may lead to a vulnerability for SCA when the whole algorithm needs to be masked (in environments like smart cards). This led to a variant of the LCD and LCP problems, where several results were obtained intensively for LCD codes, but only partial results were derived for LCP codes. Given the gap between the thin results and their particular importance, this paper aims to reduce this by further studying the LCP of codes in special code families and, precisely, the characterization and construction mechanism of LCP codes of algebraic geometry codes over finite fields. Notably, we propose constructing explicit LCP of codes from elliptic curves. Besides, we also study the security parameters of the derived LCP of codes (C , D) (notably for cyclic codes), which are given by the minimum distances d (C) and d (D ⊥). Further, we show that for LCP algebraic geometry codes (C , D) , the dual code C ⊥ is equivalent to D under some specific conditions we exhibit. Finally, we investigate whether MDS LCP of algebraic geometry codes exist (MDS codes are among the most important in coding theory due to their theoretical significance and practical interests). Construction schemes for obtaining LCD codes from any algebraic curve were given in 2018 by Mesnager, Tang and Qi in [11]. To our knowledge, it is the first time LCP of algebraic geometry codes has been studied. [ABSTRACT FROM AUTHOR]

Literature reviews reveal that there is a very close connection between experimental design and coding theory. Based on a code mapping transformation, this paper provides a new method to construct a class of mixed designs with two- and four-level. A general construction method is described and some theoretical results of obtained designs are given. Analytic connections are established between the generated and the initial designs in terms of aberration criteria and discrepancies. Sharp lower bounds of the wrap-around L 2 - and Lee discrepancies are obtained and used as the benchmarks to measure the uniformity of the generated designs. Examples are provided to illustrate the effectiveness of the construction and lend our results further support. • A new construction method is proposed for a class of mixed designs with two- and four-level. • Analytic connections are established between the generated and the initial designs in terms of aberration criteria and discrepancies. • Sharp lower bounds of the wrap-around L 2 - and Lee discrepancies are obtained. • The generated design is robust for fitting the GP model and can provide precise predictions with a small number of runs. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A method is proposed to characterize a computer program's runtime resource usage from the analysis of its binary executable file. • The approach produces a phylogeny (hierarchical clustering) of programs based on syntactic similarities found in the executable code. • Rationales are introduced to explain that these similarities in the binary file correlate to corresponding similarities in runtime behavior. • The placement of a program in the binary-code phylogeny bears resemblance to the relative similarity of its runtime behavior with respect to the other programs. • Experimental results show numerically significant evidences that the soft computing method is capable of characterizing runtime profile from binary-code similarities. Abstract This paper introduces a methodology for characterizing the runtime resource demands of a computer program from the analysis of its binary executable file. Categorization of applications according to the kind of resources required during execution – such as CPU and memory usage – is a sough-after piece of knowledge for the aims of computer system design and management. Conventional techniques available for this purpose include white-box static source code analysis and profile matching based on historical execution data. The former tends to be challenging in face of complex software architectures and requires access to the source code; the latter is dependent on the availability of reliable past data and on the selection of features yielding effective correlations with resource usage. The alternative data mining approach proposed in this paper avoids those difficulties by manipulating binary executable files. The method combines techniques from information theory, complex networks and phylogenetics to produce a hierarchical clustering of a set of executable files, which can be used to infer potential similarities in terms of runtime resource usage. The paper introduces the method's rationales and presents results of its application to characterize CPU and IO usages of benchmark applications executed on a standard PC platform. Essays carried out over a set of 80 programs from varying sources yielded numerically significant evidences that the prediction of resource usage similarity obtained by the approach is consistent with experimentally measured runtime profile. [ABSTRACT FROM AUTHOR]

Abstract The end-to-end performance metric for a conventional relay network with chase combining is the total Signal-to-Noise Ratio (SNR) delivered at the destination. However, the accumulated mutual information at the destination is the most suitable metric for a relay network which performs code combining (incremental redundancy) instead of chase combining at the destination. This paper investigates the accumulated mutual information acquired at the destination in an Amplify-and-Forward (AF), Decode-and-Forward (DF), and Coded Cooperation (CC) relay network. So far, the analytical comparison of the accumulated mutual information for the different relaying protocols is not reported in the literature. In this paper, it is proved analytically that the mutual information of a relay network with coded cooperation is always greater than or equal to the mutual information of decode-and-forward and amplify-and-forward for the case when all the relays can decode successfully. Moreover, it is also shown that the mutual information of a network with coded cooperation is always greater than or equal to that of a decode-and-forward relay network. [ABSTRACT FROM AUTHOR]

The study of entanglement-assisted quantum error-correcting codes (EAQECCs) is currently a hot topic in coding theory and quantum information theory. As far as we know, there are few constructions of q -ary EAQECCs of large lengths, and most of the q -ary EAQECCs constructed in the literature have lengths less than or equal to q 2 + 1. As a result, it will be interesting to construct q -ary EAQECCs of large lengths. The goal of this paper is to construct some good and new q -ary EAQECCs of large lengths from q 2 -ary matrix-product codes associated with the so-called non-singular by columns (NSC) quasi-unitary matrices. To this end, we first propose an effective method and a corresponding algorithm for constructing NSC quasi-unitary matrices. We then present an effective method for constructing EAQECCs of large lengths from matrix-product codes associated with NSC quasi-unitary matrices. Subsequently, we give the explicit construction of q -ary EAQECCs of lengths kn with n ≤ q 2 + 1 , k = k 0 for q ≥ k 0 , where k 0 = 3 , 4 , 5 , 7 , 8 , 9 , 11 , 13 , 16 , 17 , 19 , and k = q + 2 , q 2 − 1 , q 2 for 3 ≤ q ≤ 19. Finally, some new q -ary EAQECCs of large lengths such as lengths 3 (q 2 − 1) , 3 q 2 , 4 (q 2 − 1) , 4 q 2 , q 3 , q (q 2 + 1) , q 2 (q + 2) , (q 2 + 1) (q + 2) , q 2 (q 2 − 1) , q 4 − 1 , q 4 , q 2 (q 2 + 1) for some q are constructed, which are not covered by previously known ones. [ABSTRACT FROM AUTHOR]

Universum support vector machine ( U -SVM), due to its tremendous accuracy improvements, has been expanded and applied in all kinds of fields. Universum encodes related prior knowledge but does not belong to any class of interest. With Universum, the number of training samples and computational complexity are clearly increased. Inspired by the sparsity of SVMs, a safe sample screening rule (SSSR) for U -SVM is proposed in this paper. Our SSSR eliminates not only the labelled samples but also the Universum samples before training process, then the computational cost is dramatically reduced. Moreover, the same solution as the original problem can be obtained by utilizing our SSSR, that is, the training process is guaranteed to be accelerated safely. Besides, we extend our rule to the Universum twin support vector machine ( U -TSVM), and the SSSR for U -TSVM is also discussed in this paper. To the best of our knowledge, SSSR is the only existing safe screening method for U -SVMs. Numerical experiments on seventeen benchmark datasets, ABCDETC dataset and Chinese wine dataset demonstrate that the computational cost can be dramatically reduced without sacrificing the optimality of the final solution by our SSSR. [ABSTRACT FROM AUTHOR]

Electromagnetic (EM) data obtained by using an m-sequence source is typically segmented with an m-sequence cycle, and the random noise is suppressed by stacking the earth impulse responses recovered from each data segment. However, the stack cannot suppress the powerline noise, which is normally several orders of magnitude greater than the random noise. In this paper, the powerline noise reduction with different data lengths were compared by numerical simulation; the results show that there is always an optimal data length, not a single cycle but several cycles that can achieve maximum powerline noise suppression. The concept of an identification system was proposed and the identified earth impulse response is obtained by measuring the system output with the input of the voltage response. The optimal data length was summarized in two cases by analyzing the identification system with different data lengths. Coding frequency optimization was proposed to shorten the optimal data length to increase the stacking times. Finally, the validity of the theory described in this paper was verified by field data processing. Different from the traditional subtraction method and notch filter, the powerline suppression method presented here does not need a noise record or filter design; the powerline noise is suppressed accompanied by the identification processing without any additional workload; the simple and practical method provides a new insight into the powerline noise reduction. With this method, the utilization of field data is improved and the anti-noise performance of the m-sequence is also fully exploited. [ABSTRACT FROM AUTHOR]

Universal locally testable codes (universal - LTC s), recently introduced in our companion paper (CJTCS , 2018), are codes that admit local tests for membership in numerous subcodes, allowing for testing properties of the encoded message. Unfortunately, universal - LTC s suffer strong limitations, which motivate us to initiate, in this work, the study of the "NP analogue" of these codes, wherein the testing procedures are also given free access to a short proof, akin the MA proofs of proximity of Gur and Rothblum (Computational Complexity 2018). We call such codes "universal locally verifiable codes" (universal - LVC s). A universal - LVC C : { 0 , 1 } k → { 0 , 1 } η for a family of functions F = { f i : { 0 , 1 } k → { 0 , 1 } } i ∈ [ M ] is a code such that, for every i ∈ [ M ] , membership in the subcode { C (x) : f i (x) = 1 } can be verified locally using explicit access to a short (sublinear length) proof. A universal - LVC can be viewed as providing an encoding of inputs under which a large family of properties of the encoded inputs can be locally testable using a short proof. We show universal - LVC s of block length O ˜ (n 2) for the family of all functions expressible by t -ary constraint satisfaction problems (t -CSP) over n constraints and k variables, with proof length and query complexity O ˜ (n 2 / 3) , where t = O (1) and n ≥ k. In addition, we prove a lower bound of p ⋅ q = Ω ˜ (k) for every polynomial length universal - LVC , having proof complexity p and query complexity q , for such CSP functions. We give an application of universal - LVC s for interactive proofs of proximity (IPP), introduced by Rothblum, Vadhan, and Wigderson (STOC 2013), which are interactive proof systems wherein the verifier queries only a sublinear number of input bits to the end of asserting that, with high probability, the input is close to an accepting input. Specifically, we show a 3-round IPP for the set of assignments that satisfy fixed CSP instances, with sublinear communication and query complexity, which we derive from our universal - LVC for CSP functions. [ABSTRACT FROM AUTHOR]

Ground motion, geotechnical materials, and structural materials are three primary uncertainty sources in the seismic design and assessment of metro station structures. However, the effects of the latter two have often been ignored, which brings doubts about the rationality of the design and evaluation results. In this paper, based on the probability density evolution theory, the non-linear stochastic seismic analyses and reliability analyses under multi-source uncertainty conditions were carried out for a metro station structure in soft soils, and the effects of three primary uncertainty sources, i.e., ground motion, geotechnical materials, and structural materials, were explored. Random variable models were established to quantify the involved uncertainties of non-linear materials. The results showed that for underground structures, the uncertainty of geotechnical materials is nonnegligible, because it not only changes the soil-structure relative stiffness, but also changes the deformation mode of strata, resulting in both an increase in the elastic reliability and a decrease in the elastic-plastic reliability. The uncertainty source of structural materials changes the soil-structure relative stiffness, but has little effect on the lateral deformation response and elastic-plastic reliability of the station structure. • Non-linear stochastic seismic analyses on an underground structure were carried out. • Effects of multi-source uncertainties on the seismic response were explored. • Both the uncertainties of ground motion and geotechnical materials are nonnegligible. • The effect of the uncertainty of structural materials is very limited. [ABSTRACT FROM AUTHOR]

Based on good algebraic structures and practicabilities, generalized quasi-cyclic (GQC) codes play important roles in coding theory. In this paper, we study some results on GQC codes over Z 4 including normalized generating sets, minimal generating sets and normalized generating sets of their dual codes. As an application, new Z 4 -linear codes and good binary nonlinear codes are constructed from GQC codes over Z 4. [ABSTRACT FROM AUTHOR]

The symbol-pair read channel was first proposed by Cassuto and Blaum. Later, Yaakobi et al. generalized it to the b -symbol read channel. It is motivated by the limitations of the reading process in high density data storage systems. One main task in b -symbol coding theory is to determine the b -symbol weight hierarchy of codes. In this paper, we study the b -symbol weight hierarchy of the Kasami codes, which are well known for their applications to construct sequences with optimal correlation magnitudes. The complete symbol-pair weight distribution of the Kasami codes is determined. [ABSTRACT FROM AUTHOR]

Galois inner product is a generalization of the Euclidean inner product and Hermitian inner product. The theory on linear codes under Galois inner product can be applied in the constructions of MDS codes and quantum error-correcting codes. In this paper, we construct Galois self-dual codes and MDS Galois self-dual codes from extensions of constacyclic codes. First, we explicitly determine all the Type II splittings leading to all the Type II duadic constacyclic codes in two cases. Second, we propose methods to extend two classes of constacyclic codes to obtain Galois self-dual codes, and we also provide existence conditions of Galois self-dual codes which are extensions of constacyclic codes. Finally, we construct some (almost) MDS Galois self-dual codes using the above results. Some Galois self-dual codes and (almost) MDS Galois self-dual codes obtained in this paper turn out to be new. [ABSTRACT FROM AUTHOR]

A novel multiscale coupling methodology based on a domain overlapping approach has been developed to couple a computational fluid dynamics code with a best-estimate thermal hydraulic code. The methodology has been implemented in the coupling infrastructure code Janus , developed at the University of Michigan, providing methods for the online data transfer between the commercial computational fluid dynamics code STAR-CCM+ and the US NRC best-estimate thermal hydraulic system code TRACE. Coupling between these two software packages is motivated by the desire to extend the range of applicability of TRACE to scenarios in which local momentum and energy transfer are important, such as three-dimensional mixing. These types of flows are relevant, for example, in the simulation of passive safety systems including large containment pools, or for flow mixing in the reactor pressure vessel downcomer of current light water reactors and integral small modular reactors. The intrafluid shear forces neglected by TRACE equations of motion are readily calculated from computational fluid dynamics solutions. Consequently, the coupling methods used in this study are built around correcting TRACE solutions with data from a corresponding STAR-CCM+ solution. Two coupling strategies are discussed in the paper: one based on a novel domain overlapping approach specifically designed for transient operation, and a second based on the well-known domain decomposition approach. In the present paper, we discuss the application of the two coupling methods to the simulation of open and closed loops in both steady state and transient operation. The objective of this study is to examine the performance of each coupling method in terms of convergence, consistency, and numerical stability. As expected, the results produced by the two methods were found to be identical once numerical convergence is achieved and consistent with the standalone STAR-CCM+ solution in both steady state and transient cases. However, the domain overlapping method was found to achieve convergence at larger integration time steps than the domain decomposition approach and exhibited superior convergence and numerical stability characteristics in both steady state and transient scenarios. [ABSTRACT FROM AUTHOR]

In this paper, we consider decoding of loss tolerant data encoded by network coding and transmitted over error-prone networks. Intermediate network nodes typically perform the random linear network coding in a Galois field and a Gaussian elimination is used for decoding process in the terminal nodes. In such settings, conventional decoding approaches can unfortunately not reconstruct any encoded data unless they receive at least as many coded packets as the original number of packets. In this paper, we rather propose to exploit the incomplete data at a receiver without major modifications to the conventional decoding architecture. We study the problem of approximate decoding for inter-dependent sources where the difference between source vectors is characterized by a unimodal distribution. We propose a mode-based algorithm for approximate decoding, where the mode of the source data distribution is used to reconstruct source data. We further improve the mode-based approximate decoding algorithm by using additional short information that is referred to as position similarity information (PSI). We analytically study the impact of PSI size on the approximate decoding performance and show that the optimal size of PSI can be determined based on performance requirements of applications. The proposed approach has been tested in an illustrative example of data collection in sensor networks. The simulation results confirm the benefits of approximate decoding for inter-dependent sources and further show that 93.3% of decoding errors are eliminated when the approximate decoding uses appropriate PSI. [ABSTRACT FROM AUTHOR]

There is increasing interest in the development of reliable, rapid and non-intrusive security control systems. Multimodal biometrics such as palmprints and iris provide highly effective automatic mechanisms for use in personal identification and helps to minimize the system error rate. This paper presents a new method for extracting features in spatial domain from palmprints and iris. Thepade's Block Truncation Coding using level 2 is taken here to reduce the feature vector size. For improving accuracy in form of genuine acceptance rate(GAR)in multimodal biometric identification we take iris and palmprint together at matching score level. The test beds of 60 pairs of Iris and Palmprint samples of 10 person (6 per person of iris as well as Palmprint) are used as test bed for experimentation. In this Paper different color spaces are considered on iris images for improvement in genuine acceptance ratio (GAR). Experimental results consider different matching score proportion of Iris: Palmprint. Using propose techniques with Iris: Palmprint Score 15:1 using TSTBTC Level2 given better performance as indicated by higher GAR values than all other considers scores. RGB color spaces for multimodal fusion of Iris: Palmprint gives high GAR than all other color spaces like YCgCb, YIQ, YCbCr, YIQ, and KLUV. [ABSTRACT FROM AUTHOR]

This paper revisits the vector of locally aggregated descriptors (VLAD), which aggregates the residuals of local descriptors to their cluster centers. Since VLAD usually adopts a small-size codebook, the clusters are coarse and residuals not discriminative. To address this problem, this paper proposes to generate a number of residual codebooks descended from the original clusters. After quantizing local descriptors with these codebooks, we pool the resulting secondary residuals as well as the primary ones to obtain the fine residuals. We show that, with two-step aggregation, the fine-residual VLAD has the same dimension as the original. Experiments on two image search benchmarks confirm the improved discriminative power of our method: we observe consistent superiority to the baseline and competitive performance to the state-of-the-arts. [ABSTRACT FROM AUTHOR]

In this paper, we examine the problem of learning sparse representations of visual patterns in the context of artificial and biological vision systems. There are a myriad of strategies for sparse coding that often result in similar feature properties for the learned feature set. Typically this results in a bank of Gabor-like or edge filters that are sensitive to a range of distinct angular and radial frequencies. The theory and experimentation that is presented in this paper serves to provide a better understanding of a number of specific properties related to low-level feature learning. This includes close examination of the role of phase pairing in complex cells, the role of depth information and its relationship to variation of intensity and chroma, and deriving hybrid features that borrow from both analytic forms and statistical methods. Together, these specific examples provide context for more general discussion of effective strategies for feature learning. In particular, we make the case that imposing additional constraints on mechanisms for feature learning inspired by biological vision systems can be useful in guiding constrained optimization towards convergence, or specific desirable computational properties for representation of visual input in artificial vision systems. [ABSTRACT FROM AUTHOR]

This paper tries to model the code obfuscation as satisfiability problem. In this paper, we try to develop the model to represent the obfuscated code as the satisfiable problem which could be then checked by the SAT solver to check whether at certain instances the model is satisfiable. We provide the notion of converting the SSA format of the instructions to the propositional logic and then by the help of the theorem provers, we tell whether both the code snippets of obfuscated code are same or not. This can be done by converting both codes from their original code to the mathematical signature or relational encoding and then checking their logical equivalence. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the problem of optimization of multivariate performance measures, and propose a novel algorithm for it. Different from traditional machine learning methods which optimize simple loss functions to learn prediction function, the problem studied in this paper is how to learn effective hyper-predictor for a tuple of data points, so that a complex loss function corresponding to a multivariate performance measure can be minimized. We propose to present the tuple of data points to a tuple of sparse codes via a dictionary, and then apply a linear function to compare a sparse code against a given candidate class label. To learn the dictionary, sparse codes, and parameter of the linear function, we propose a joint optimization problem. In this problem, the both the reconstruction error and sparsity of sparse code, and the upper bound of the complex loss function are minimized. Moreover, the upper bound of the loss function is approximated by the sparse codes and the linear function parameter. To optimize this problem, we develop an iterative algorithm based on descent gradient methods to learn the sparse codes and hyper-predictor parameter alternately. Experiment results on some benchmark data sets show the advantage of the proposed methods over other state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

This paper presents a study of the approaches in the state-of-the-art in the field of pathological speech signal analysis with a special focus on parametrization techniques. It provides a description of 92 speech features where some of them are already widely used in this field of science and some of them have not been tried yet (they come from different areas of speech signal processing like speech recognition or coding). As an original contribution, this work introduces 36 completely new pathological voice measures based on modulation spectra, inferior colliculus coefficients, bicepstrum, sample and approximate entropy and empirical mode decomposition. The significance of these features was tested on 3 (English, Spanish and Czech) pathological voice databases with respect to classification accuracy, sensitivity and specificity. To our best knowledge the introduced approach based on complex feature extraction and robust testing outperformed all works that have been published already in this field. The results (accuracy, sensitivity and specificity equal to 100.0 ± 0.0 % ) are discussable in the case of Massachusetts Eye and Ear Infirmary (MEEI) database because of its limitation related to a length of sustained vowels, however in the case of Príncipe de Asturias (PdA) Hospital in Alcalá de Henares of Madrid database we made improvements in classification accuracy ( 82.1 ± 3.3 % ) and specificity ( 83.8 ± 5.1 % ) when considering a single-classifier approach. Hopefully, large improvements may be achieved in the case of Czech Parkinsonian Speech Database (PARCZ), which are discussed in this work as well. All the features introduced in this work were identified by Mann–Whitney U test as significant ( p < 0.05 ) when processing at least one of the mentioned databases. The largest discriminative power from these proposed features has a cepstral peak prominence extracted from the first intrinsic mode function ( p = 6.9443 × 10 − 32 ) which means, that among all newly designed features those that quantify especially hoarseness or breathiness are good candidates for pathological speech identification. The paper also mentions some ideas for the future work in the field of pathological speech signal analysis that can be valuable especially under the clinical point of view. [ABSTRACT FROM AUTHOR]

In this paper, a new coding scheme, local Gabor maximum edge position octal patterns (LGMEPOP) is proposed for content based image retrieval. The standard local binary pattern (LBP) collects the sign edge (binary code) information between the center pixel and its surrounding neighbors in an image. Further, the concept of LBP is extended to local maximum edge binary pattern (LMEBP) which collects the sign code (binary code) using the magnitude edges. These magnitude edges are collected based on the maximum edges between the center pixel and its surrounding neighbors in an image. In this paper, we propose a new feature descriptor, octal code which is coded based on the maximum edge positions (MEP) on Gabor responses. Specially, each pixel of every Gabor response gains eight edges based on the relationship between the referenced pixel and its neighbors. LGMEPOP utilizes the first three dominant (maximum) edge positions in an octal code generation. Then, these three maximum edge positions are encoded into three-eight octal numbers to produce the LGMEPOP. Further, the LGMEPOP is classified into two categories which are named as sign maximum edge position octal pattern (SMEPOP) and magnitude maximum edge position octal pattern (MMEPOP). The SMEPOP and MMEPOP are coded based on the sign and magnitudes of dominant edges respectively. The performance of the proposed method is tested on two benchmark databases. The results after being investigated show a significant improvement as compared to other existing methods (LBP and LBP variants) in terms of average retrieval precision (ARP) and average retrieval rate (ARR) on Corel-5000 and Corel-10000 databases. [ABSTRACT FROM AUTHOR]

Scheduling for the Earth observation satellite (EOS) imaging mission is generally considered as a complicated combinatorial optimization problem subjected to various technical constraints, which requires massive computational costs to find the optimal solution, especially for multiple EOSs imaging missions. In this paper, a novel individual reconfiguration based integer coding genetic algorithm (IRICGA) is developed to reduce the computational costs and improve the optimality of multiple EOSs scheduling for area target observation. The proposed individual reconfiguration procedure contributes to generating feasible solutions during the evolutionary process. Considering the diversity of individual population, two different reconfiguration mechanisms are proposed for handling various technique constraints. Based on the proposed algorithm, an efficient multi-satellite imaging scheduling framework for area target observation is developed. The scheduling framework consists of two separate phases, i.e., pro-processing and scheduling process. In the pro-processing phase, a semi-analytical method is proposed to calculate the visible time window (VTW) of area target and observation strip. Moreover, the binary search techniques are utilized to improve calculation efficiency and accuracy. Besides, a new area partitioning method based on two kinds of discrete parameters is proposed to divide the area target into a series of feasible observation strips. Based on the pro-processing results, the multiple EOSs scheduling problem is formulated as an integer programming model. In the scheduling process, based on the analysis of characteristics of the multiple EOSs scheduling problem, the IRICGA is constructed to generate the optimal scheduling solution. In the end, a real-world multiple EOSs scheduling example is investigated to illustrate the high-efficiency and reliability of the proposed method. • Individual reconfiguration mechanisms are developed to generate feasible solutions. • An IRICGA is proposed to solve the multi-satellite imaging scheduling problem. • An efficient multi-satellite scheduling framework is developed based on the IRICGA. • Effective techniques are proposed to decrease the calculation cost of satellite scheduling. • The simulation results reveal that the proposed algorithms display high-efficiency. [ABSTRACT FROM AUTHOR]

This work describes the practical implementation of an interleaved multi-phase, multi-switch boost converter for fuel cell applications. The paper aims to validate the concept of digitally-controlled Multi-Interleaving Boost Converter (MIBC) for fuel cell applications, from two-phase, four-legs per phase, synchronous boost converter, abbreviated as 2-4-MIBC. Compared with the Interleaved Boost Converter (IBC), MIBC exhibits interesting performance in terms of magnetics, input and output current ripple, part count and distributed power losses. A potential field of application is indeed medium and higher power fuel cell front-end converters, where minimizing input current ripple is significant but also redundancy and reliability are crucial. Actually, this approach covers all these aspects since provide module and device redundancy with real-time and flexible digital control reconfiguration. Relevant aspects related to design, modeling, simulation and experimental verification of 1 kW, FPGA-controlled, 2-4-MIBC are treated in this paper. [ABSTRACT FROM AUTHOR]

In this paper, channel coding strategies for the problem of communication over a two-user Z-interference channel (ZIC) in the presence of non-causal side information (NSI) at transmitters are presented. First, an achievable rate region for the general discrete memoryless ZIC-NSI is derived using rate splitting technique, superposition coding, Gel’fand–Pinsker-type binning scheme and joint typicality decoding. Next, the capacity region of a special case of the orthogonal ZIC-NSI is characterized. Then, the Gaussian version of the channel called the Gaussian Doubly Dirty ZIC (GDD-ZIC) is defined and a general outer bound to the capacity region of the GDD-ZIC is presented. After that, an inner bound for the sum-capacity of the channel using Costa's dirty paper coding is derived and thereby it is shown that Costa's strategy cannot achieve any positive rates over the GDD-ZIC for the case of strong state-interference. Finally, lattice-based achievable rates for the GDD-ZIC are obtained. These lattice-based rates are independent of the state-interference powers and thus, lattice-strategies are able to achieve positive rates for the case of strong state-interference. Moreover, it is shown that lattice-strategies are optimal for a class of the GDD-ZIC. [ABSTRACT FROM AUTHOR]

This paper introduces the wavelet image two-line (Wi2l) coding algorithm for low complexity compression of images. The algorithm recursively encodes an image backwards reading only two lines of a wavelet subband, which are read in blocks of 512 bytes from flash memory. It thus only requires very little memory, i.e., a memory array for two wavelet subband lines, an array to store intermediate tree level data, and an array for writing binary data. A picture of 256×256 pixels would require 1152 bytes of memory. Computation time for the coding is derived analytically and measured on a real system. The times on a low-cost microcontroller for 256×256 grayscale pictures are measured as 0.25–0.6 s for encoding and 0.22–0.77 s for decoding. The algorithm can thus realize a low complexity system for compression of images when combined with a customized scheme for the wavelet transform; low complexity here refers to low memory, minimum write access to flash memory, usage of integer operations only, and low conceptual complexity (ease of implementation). As demonstrated in this paper, a compression performance similar to JPEG 2000 and the more recent Google WebP picture compression is achieved. The compression system uses flash memory (SD or MMC card) and a small camera sensor thus building an image communication system. It is also suitable for mobile devices or satellite communication. The underlying C source code is made publicly available. [ABSTRACT FROM AUTHOR]

Distributed file system for the storage of massive files have obvious advantages compared with the conventional file system. For instance, Hadoop Distributed File System (HDFS) implemented with commodity hardware has the advantages of low cost, high fault tolerance, scalability, etc. However, HDFS has the potential safety hazard due to the unencrypted data stored in Datanode, which may cause data leakage during the manipulation. In this paper, we purpose a new architecture based on HDFS, combined with network coding and multi-node reading, to improve the security and storage efficiency of the distributed file system. Experiments have shown that the method proposed in this paper greatly improves the safety of files transfer and storage, while the speed of files reading has increased threefold compared to the original HDFS model. [ABSTRACT FROM AUTHOR]

Application of coupled CFD (Computational Fluid Dynamics) and STH (System Thermal Hydraulics) codes is a prerequisite for computationally affordable and sufficiently accurate prediction of thermal-hydraulics of complex systems. Coupled STH and CFD codes require validation for understanding and quantification of the sources of uncertainties in the code prediction. TALL-3D is a liquid Lead Bismuth Eutectic (LBE) loop developed according to the requirements for the experimental data for validation of coupled STH and CFD codes. The goals of the facility design are to provide (i) mutual feedback between natural circulation in the loop and complex 3D mixing and stratification phenomena in the pool-type test section, (ii) a possibility to validate standalone STH and CFD codes for each subsection of the facility, and (iii) sufficient number of experimental data to separate the process of input model calibration and code validation. Description of the facility design and its main components, approach to estimation of experimental uncertainty and calibration of model input parameters that are not directly measured in the experiment are discussed in the paper. First experimental data from the forced to natural circulation transient is also provided in the paper. [ABSTRACT FROM AUTHOR]

Temporal graphs represent vertices and binary relations that change along time. In this paper, a temporal graph is conceptualized as the sequences of changes on its edges during its lifetime, also known as temporal adjacency logs. The paper explores the use of compression techniques, and compact and self-indexed data structures, to represent large temporal graphs. More specifically, we present four strategies to represent temporal graphs. The first two strategies, Time-interval Log per Edge ( EdgeLog ) and the Adjacency Log of Events ( EveLog ), use compression techniques over the inverted indexes that represent the adjacency logs. Then, we introduce two new strategies to represent temporal graphs using compact and self-indexed data structures. Compact Adjacency Sequence ( CAS ) represents changes on adjacent vertices as a sequence stored in a Wavelet Tree , and the Compact Events ordered by Time ( CET ) represents the edges that change in each time instant using Interleaved Wavelet Tree , a new compact and self-indexed data structure specifically designed in this work that is able to represent a sequence of multidimensional symbols (that is, tuples of symbols encoded together). We experimentally evaluate the four strategies and compare them with previous alternatives in the state-of-the-art showing that the four alternatives can represent large temporal graphs making efficient use of space, while keeping good time performance for a wide range of useful queries. We conclude that the use of compression techniques or the use of compact and self-indexed data structures open the possibility for the design of interesting representations of temporal graphs that fit the needs of different application domains. [ABSTRACT FROM AUTHOR]

This paper is concerned with four unusual grammatical structures in Shua (“Khoisan”, Botswana). Three of these presume the exceptionality of a salient discourse entity as a thing of its type and contradict this with an assertion of non-exceptionality; the fourth presumes the typicality of the salient entity, contrasting this with a claim to exceptionality. The paper describes the formal properties and meanings of these structures, distinguishing between their coded and inferred meanings. It is argued that the coded meaning of each is of the interpersonal type. The paper further suggests that the structures represent four distinct constructions that are partly motivated, and that crucial to each is repetition of key lexical components. [ABSTRACT FROM AUTHOR]

This paper presents analytical model on motion-compensated predictive processing of the video signals. Multihypothesis prediction extends motion compensation with one prediction signal to the linear superposition of several motion-compensated prediction signals with the result of increased coding efficiency. The prediction error variances of the multihypothesis pictures are derived and minimized in this paper in order to find optimal bit allocations. Then, coding gains of the multihypothesis structures are calculated and compared, which is based on traditional prediction theories. Also, the corresponding rate-distortion functions are obtained in the closed form. Some experimental results show that more multihypotheses bring the smaller distortion of signals and hence improve the efficiency of video coding. [ABSTRACT FROM AUTHOR]

The perception-action (P-A) cycle is the process of receiving information about sensory events taking place in the environment through sensory systems, processing this information and triggering motor systems to initiate corresponding action events back into the environment. This information processing along the P-A pathway requires defining a certain level of dependency between the sensory events and their corresponding action events. This dependency is what determines the behavior of the system and its ability to implement its goals and to react to its environment. Information processing within the P-A process is based on the transmission of signals between the sensory and motor systems. This transmission is subject to noise. Noise leads to errors in the transmitted signals and reduces the amount of useful information carried by the signals, thus impacting the sensory-action dependency that can be defined by the organism. According to communication theory, managing information transmission along a channel is achieved by matching the messages to be transmitted with the specifics of that channel according to the statistical characteristics of the messages. The current paper argues that managing information transmission within the P-A process requires the brain to have dedicated information transmission control processes and structures. It is argued that one such control process is based on managing the mapping of the events involved in the P-A process to the signals used by the P-A process. The paper suggests the required structure that should enable the brain to access the required variables for managing the information transmission and examines the approach of the Theory of Event Coding. [ABSTRACT FROM AUTHOR]