The rapid expansion of new technologies and services significantly affects society’s development and initiates significant changes within public administration. Many have decided to implement citizen-centric, data-driven, and performance-focused governance and prepare to transform the existing e-government system into a smart government. Along the way, they have encountered problems such as flaws in existing legislation and in the integration of heterogeneous infrastructure from technical, financial, and privacy perspectives. We propose a new approach to information system modeling that introduces an integration layer for existing databases and services and suggests the application of several innovative technologies to achieve better problem-solving, optimal utilization of resources, and policy innovation. To test the effectiveness of the proposed solution, we have used corresponding weighted digraph models to confirm that the proposed solution achieves the desired effects. We have used the time required to collect documents to measure similarity. The obtained results prove the efficiency of the proposed model and indicate that the same model could be used elsewhere in public administration.

Evaluating the block error rate of a digital communication system is usually done using the Monte Carlo simulation method. The main drawback of the Monte Carlo method is the need of a huge sample size for estimating low error rates. Other methods commonly used are the importance sampling technique and the quasi-analytical method. This paper introduces the metric star domain decoder model and shows that many practical decoders fall into this category. The main result is the introduction of a novel SNR-invariant quasi-analytical technique for estimating the block error rate of a communication link over the geodesic channel model (a generalization of a vast number of commonly used channels, including BSC, BEC and AWGN channel) with a metric star domain decoder used at the receiver. This technique outperforms the Monte Carlo and Importance Sampling methods in both accuracy and speed. It is shown that our QA method is at least 103 times faster than MC and 10 times faster than IS for the same accuracy.

We study certain properties of Rényi entropy functionals \(H_\alpha \left( \mathcal{P} \right)\) on the space of probability distributions over ℤ₊. Primarily, continuity and convergence issues are addressed. Some properties are shown to be parallel to those known in the finite alphabet case, while others illustrate a quite different behavior of the Rényi entropy in the infinite case. In particular, it is shown that for any distribution \(\mathcal{P}\) and any r ∈ [0,∞] there exists a sequence of distributions \(\mathcal{P}_n\) converging to \(\mathcal{P}\) with respect to the total variation distance and such that \(\mathop {\lim }\limits_{n \to \infty } \mathop {\lim }\limits_{\alpha \to 1 + } H_\alpha \left( {\mathcal{P}_n } \right) = \mathop {\lim }\limits_{\alpha \to 1 + } \mathop {\lim }\limits_{n \to \infty } H_\alpha \left( {\mathcal{P}_n } \right) + r\) .

Some nonlinear codes, such as Kerdock and Preparata codes, can be represented as binary images under the Gray map of linear codes over rings. This paper introduces MAP decoding of Kerdock and Preparata codes by working with their quaternary representation (linear codes over $\mathbb {Z}_{4}$ ) with the complexity of $\mathcal {O}(N^{2}\log _{2} N)$ , where N is the code length in $\mathbb {Z}_{4}$ . A sub-optimal bitwise APP decoder with good error-correcting performance and complexity of $\mathcal {O}(N\log _{2} N)$ that is constructed using the decoder lifting technique is also introduced. This APP decoder extends upon the original lifting decoder by working with likelihoods instead of hard decisions and is not limited to Kerdock and Preparata code families. Simulations show that our novel decoders significantly outperform several popular decoders in terms of error rate.

We define the bidirectional distance profile (BDP) of a convolutional code as the minimum of the distance profiles of the code and its corresponding “reverse” code. We present tables of codes with the optimum BDP (OBDP), which minimize the average complexity of bidirectional sequential decoding algorithms. The computer search is accelerated by the facts that optimum distance profile (ODP) codes of larger memory must have ODP codes of smaller memory as their “prefixes”, and that OBDP codes can be obtained by “concatenating” ODP and reverse ODP codes of smaller memory. We compare the performance of OBDP codes and other codes by simulation.

Multiamplitude continuous phase modulation (MACPM) microwave transmitter and receiver structures are described. The superposition technique of generating MACPM signals is presented. The ROM and the PLL (phaselocked-loop) transmitters are considered. The optimum Viterbi receiver is developed for MACPM schemes performing maximum-likelihood sequence estimation. The AMF (average matched filter) receivers are examined, and their complexity is discussed.