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The polar code is a unique coding approach that can achieve Shannon's capacity in modern communication systems' discrete memory-less channels with superior reliability, but it is not secure enough under modern attacks for such systems. This study aims to offer a comprehensive secured polar coding scheme that uses a combination of polar coding and the Mersenne-Twister pseudo-random number generator (MT-PRNG) to achieve a super secured encoding. The pre-shared crypto-system cyphering key initiates the starting state of the MT-PRNG as a seed. The randomly generated sequences govern the values of the frozen bits in polarized bit channels and their associated indices. A half-bit-error-rate probability system performance is calculated when the encoding ciphering keys at the receiver differ by a single bit from those utilized at the transmitter. Using calculated numerical analysis, the system is shown to be secure against brute force attacks, Rao-Nam attacks, and polar code reconstruction attacks.

Jaya algorithm (JAYA) is a recently developed metaheuristic algorithm for global optimization problems. JAYA has a very simple structure and only needs the essential population size and terminal condition for solving optimization problems. However, JAYA is easy to get trapped in the local optimum for solving complex global optimization problems due to its single learning strategy. Motivated by this disadvantage of JAYA, this paper presents an improved JAYA, named comprehensive learning JAYA algorithm (CLJAYA), for solving engineering design optimization problems. The core idea of CLJAYA is the designed comprehensive learning mechanism by making full use of population information. The designed comprehensive learning mechanism consists of three different learning strategies to improve the global search ability of JAYA. To investigate the performance of CLJAYA, CLJAYA is first evaluated by the well-known CEC 2013 and CEC 2014 test suites, which include 50 multimodal test functions and eight unimodal test functions. Then CLJAYA is employed to solve five real-world engineering optimization problems. Experimental results demonstrate that CLJAYA can achieve better solutions for most test problems than JAYA and the other compared algorithms, which indicates the designed comprehensive learning mechanism is very effective. In addition, the source code of the proposed CLJAYA can be loaded from https://www.mathworks.com/matlabcentral/fileexchange/82134-the-source-code-for-cljaya.

Big data becomes the key for ubiquitous computing and intelligence, and Distributed Storage Systems (DSS) are widely used in large-scale data centers or in the cloud for efficient data management. However, the data on stored are likely to be unavailable due to hardware failures and cyberattacks, e.g. DDoS. Maximum Distance Separable (MDS) codes are commonly used for the recovery of faulty storage nodes or unavailable data. However, the recovery of data nodes usually involves access to multiple nodes, which introduces significant communication overheads to the DSS. In this paper, a new DSS based on the Redundant Residue Number System (RRNS) is proposed, where efficient recovery is enabled by applying the second version of Chinese Remainder Theorem (CRT-II). The complexity and network traffic of the proposed data protection scheme is analyzed theoretically and compared with that of traditional MDS based DSSs. Experimental results show that the proposed DSS achieves lower encoding complexity, lower recovery complexity and lower network traffic than the MDS based schemes. Although the proposed data protection scheme introduces computation overheads for the case on which there are no failing nodes, its complexity is still lower for scenarios with frequent data updates. In addition, the proposed scheme introduces additional advantages in terms of security and storage flexibility.

Analysis of error correction performance for error correcting codes is very important when using such codes in digital communication systems. At medium-to-high signal-to-noise ratios, the distance spectrum of the error correcting code represents a good indicator for the error correction performance of the code. It is desired that the minimum distance of the code is as large as possible and that the corresponding multiplicity (i.e. the number of codewords having the weight equal to the minimum distance) is as small as possible. If we know an upper bound of the minimum distance of the code, then we have a good indication about the capabilities and the limitations of the code. One of the classes of the error correcting codes with the best performance is that of turbo codes. For such codes, establishing upper bounds on the minimum distance is challenging because it depends on the interleaver component of the turbo code. In this paper we consider turbo codes with component convolutional codes as in the Long Term Evolution standard. The interleaver lengths are of the form 16Ψ or 48Ψ, with Ψ a product of different prime numbers greater than three. The first achievement in the paper is that for these interleaver lengths, we show that cubic permutation polynomials (CPP), with some constraints on the coefficients, when 3∤(pi-1) for a prime pi>3, always have a true inverse CPP. The most accurate upper bounds on the minimum distance for turbo codes are achieved by identifying bit information sequences leading to a certain weight of the corresponding turbo-codeword. In this paper we have indentified such bit information sequences by means of the full range dual impulse method to estimate the weight of the turbo-codewords. For the previously mentioned turbo codes and CPP interleavers, we show that the minimum distance is upper bounded by the values of 38, 36, and 28, for three different classes of coefficients. Previously, it was shown that for the same interleaver lengths and for quadratic PP (QPP) interleavers, the upper bound of the minimum distance is equal to 38. Several examples show that dmin-optimal CPP interleavers are better than dmin-optimal QPP interleavers because the multiplicities corresponding to the minimum distances for CPPs are about a half of those for QPPs. A theoretical explanation in terms of nonlinearity degrees for this result is given for all considered interleaver lengths and for the class of CPPs for which the upper bound is equal to 38.

Physical-layer security (PLS) provides an information-theoretic framework for securing wireless communications by exploiting channel and signal-structure asymmetries, thereby avoiding reliance on computational hardness assumptions. Within this setting, lattice codes and their algebraic constructions play a central role in achieving secrecy over Gaussian and fading wiretap channels. This article offers a comprehensive survey of lattice-based wiretap coding, covering foundational concepts in algebraic number theory, Construction A over number fields, and the structure of modular and unimodular lattice families. We review key secrecy metrics, including secrecy gain, flatness factor, and equivocation, and consolidate classical and recent results to provide a unified perspective that links wireless-channel models with their underlying algebraic lattice structures. In addition, we review a newly proposed family of p-modular lattices in Khodaiemehr, H., 2018 constructed from cyclotomic fields Q(ζp) for primes p≡1(mod4) via a generalized Construction A framework. We characterize their algebraic and geometric properties and establish a non-existence theorem showing that such constructions cannot be extended to prime-power cyclotomic fields Q(ζpn) with n>1. Finally, motivated by the fact that these p-modular lattices naturally yield mixed-signature structures for which classical theta series diverge, we integrate recent advances on indefinite theta series and modular completions. Drawing on Vignéras’ differential framework and generalized error functions, we outline how modularly completed indefinite theta series provide a principled analytic foundation for defining secrecy-relevant quantities in the indefinite setting. Overall, this work serves both as a survey of algebraic lattice techniques for PLS and as a source of new design insights for secure wireless communication systems.

Geographically and temporally granular housing price indexes are difficult to construct. Data sparseness, in particular, is a limiting factor in their construction. A novel application of a spatial dynamic factor model allows for the construction of census tract level indexes on a quarterly basis while accommodating sparse data. Specifically, we augment the repeat sales model with a spatial dynamic factor model where loadings on latent trends are allowed to follow a spatial random walk thus capturing useful information from similar neighboring markets. The resulting indexes display less noise than similarly constructed non-spatial indexes and replicate indexes from the traditional repeat sales model in tracts where sufficient numbers of repeat sales pairs are available. The granularity and frequency of our indexes is highly useful for policymakers, homeowners, banks and investors.

India’s manufacturing sector reflects a steady growth in the intermediate in- put intensity in the recent time. This paper is designed to examine the rich plant level data on Indian formal manufacturing sector to understand the decomposition of the ratio of input and value of output. These empirical evidences are important to understand the dynamics of manufacturing sector and understand what has driven the rise of expenditure on inputs. In literature there has been a long-standing interest in obtaining the decomposition of input expenditure and revenue into quantity/price indices for explaining the growth in input intensity. Motivated by literature, the paper relies on Balk (Empirical Productivity Indices and Indicators, Oxford University Press, Oxford, 2018), Diewert (Decompositions of Productivity Growth into Sectoral Effects, School of Economics, University of British Columbia, Vancouver, 2013), and Tang and Wang (Canadian Journal of Economics 37:421–444, 2004) to construct indices for understanding quantity and price effect of input expenditure and revenue of plants in Indian formal manufacturing sector. The pattern of quantity and price growth for plants’ revenue on an average show that the associated growth of quantity sold is much higher compared to the rise in the prices in the first panel and afterwards the series mirrors a sharper price growth of output sold by plants. The main conclusion emerging from this study is that, over long time periods, changes in the growth of intermediate input (material inputs) in terms of quantity purchased have been relatively large for both domestic input purchases and imported input purchases. However, in case of energy input the growth in quantity purchases has been more or less constant for years.

Your complete guide to a career in medical billing and coding, updated with the latest changes in the ICD-10 and PPS This fully updated second edition of Medical Billing & Coding For Dummies provides readers with a complete overview of what to expect and how to succeed in a career in medical billing and coding. With healthcare providers moving more rapidly to electronic record systems, data accuracy and efficient data processing is more important than ever. Medical Billing & Coding For Dummies gives you everything you need to know to get started in medical billing and coding. This updated resource includes details on the most current industry changes in ICD-10 (10th revision of the International Statistical Classification of Diseases and Related Health Problems) and PPS (Prospective Payment Systems), expanded coverage on the differences between EHRs and MHRs, the latest certification requirements and standard industry practices, and updated tips and advice for dealing with government agencies and insurance companies. Prepare for a successful career in medical billing and coding Get the latest updates on changes in the ICD-10 and PPS Understand how the industry is changing and learn how to stay ahead of the curve Learn about flexible employment options in this rapidly growing industry Medical Billing & Coding For Dummies, 2nd Edition provides aspiring professionals with detailed information and advice on what to expect in a billing and coding career, ways to find a training program, certification options, and ways to stay competitive in the field.

Interleavers are important blocks of the turbo codes, their types and dimensions having a significant influence on the performances of the mentioned codes. If appropriately chosen, the permutation polynomial (PP) based interleavers lead to remarkable performances of these codes. The most used interleavers from this category are quadratic permutation polynomial (QPP) and cubic permutation polynomial (CPP) based ones. In this paper, we determine the number of different QPPs and CPPs that cannot be reduced to linear permutation polynomials (LPPs) or to QPPs or LPPs, respectively. They are named true QPPs and true CPPs, respectively. Our analysis is based on the necessary and sufficient conditions for the coefficients of second and third degree polynomials to be QPPs and CPPs, respectively, and on the Chinese remainder theorem. This is of particular interest when we need to find QPP or CPP based interleavers for turbo codes.