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Study on the design of a robust network against malicious attacks has gained increased interest in various areas such as wireless communications networks. One of the main obstacles towards finding the optimum robust network is the large number of possible network configurations. In this paper, we propose a novel method to design robust networks against malicious attacks based on the network degree...
Testing of software is a worthwhile aspect of software development life cycle. Effective and efficient test cases must be designed to test the software which will reduce the testing cost, time and effort. Nowadays, testing an aspect-oriented program is becoming a challenge for the testers. This paper proposes a novel approach to generate test case scenarios for an aspect oriented program derived from...
The paper presents a new mechanism to apply evolutionary complication of models in the previously introduced hybrid COMBI-GA sorting-out algorithm to find optimal model structure. The mechanism is based on generation of model structures using binomial random number generator with low probability and specific mutation operator. The presented experimental results demonstrate that this algorithm performs...
Time and budget constraints in developing a software create an adverse effect in terms of the adequacy of maintenance and test processes. This case can be considered as a burden for persons who account for test processes. In order to alleviate this burden, test case prioritization is one of the solutions. A nature-inspired method namely BITCP, which was developed based on bat algorithm, produced promising...
Massive multiple-input multiple-output (MIMO), also known as very-large MIMO systems, is an attracting technique in 5G, as it can provide higher rates and power efficiency than 4G. However the radio-frequency(RF) chains associated with the antennas increase the system complexity and cost. Antenna selection is an effective way to reduce the number of RF chains. In this paper, we proposed an antenna...
In this paper, the challenging problem of data detection for orthogonal frequency division multiplexing (OFDM) systems under rapidly time- varying channels is considered. Time-varying channels within a multicarrier symbol will lead to a loss of sub-channel orthogonality, and result in inter-channel interference (ICI) and an irreducible error floor in traditional receivers. The genetic algorithm (GA)...
A two-step method is proposed to compute the antenna array parameters for reducing excitation complexity of plane wave generator in this paper. Both the least squares method and genetic algorithm are combined to figure out the phase and position of each unit with selected amplitude. The validity of the method is confirmed by computer simulation and virtual experiments.
Deep Neural Networks (DNN) have become a powerful, widely used, and successful mechanism to solve problems of different nature and varied complexity. Their ability to build models adapted to complex non-linear problems, have made them a technique widely applied and studied. One of the fields where this technique is currently being applied is in the malware classification problem. The malware classification...
This paper concerns evolutionary algorithms for minimization exclusive-or sum-of-products representations of Boolean functions. These representations are used in logic synthesis for certain class of circuits. Minimization is based on a decomposition for Boolean functions with parameter function. Selection of this function is a search task which can be solved with evolutionary algorithms. Algorithms...
In this paper the algorithm of receiving the minimal complexity of Boolean function representations in the class of Kronecker forms based on evolutionary algorithm is constructed. Operator approach is used for function representation. Each Boolean function corresponds to unique representation, the special operator form. The obtained algorithm of receiving the minimal representation is based on the...
In the fast moving world of smart urban conglomerates, emergency services need to move even faster through the crowded infrastructure. Providing the emergency crew with a route that avoids congestions can save valuable travel time. It is challenging to compute such a route fast enough for practical usage while taking into consideration traffic fluctuations, uncertainties, and unpredictable user behaviour...
This research focuses on studying the effect of using evolutionary algorithms in improving neural network capabilities in identification of non-linear multi-input and multi-output dynamic systems such as a quadcopter. In addition, comparison of the different neural network based approaches is carried out in order to reveal the variations among the different methods. The results show that using evolutionary...
In this paper, we propose a two-stage thermal-aware task scheduling policy which exploits the application and system architecture characteristics to decouple the mapping of task-graphs for the performance and peak temperature optimization into two stages. At the first stage, the algorithm collects the best mapping of task-graphs exploiting the application and architecture characteristics to minimize...
For optimal synthesis of discrete logic devices, we have to use the exhaustive search algorithms, accompanied by a large amount of computational work. In practice, the synthesis is carried out with the help of heuristic algorithms that are looking for sub-optimal decision. To achieve fault-tolerance functionally complete tolerance element is used. Genetic algorithm used for decision search. It is...
In Underwater Sensor Networks (UWSNs) with high volume of data recording activity, a mobile sink such as a Autonomous Underwater Vehicle (AUV) can be used to offload data from the sensor nodes. When the AUV approaches the underwater node, it can use high data rate optical communication. However, the data is not considered delivered when it was transferred from the sensor node to the AUV, but when...
Generalized Memory Polynomial (GMP) models are widely used for the linearization of power amplifiers. They offer a good tradeoff between linearization performance and implementation complexity. Their structure is defined by 8 integer parameters representing different non-linearity orders and memory lengths. These 8 degrees of freedom allow achieving very good linearization performance with a small...
This paper describes the implementation steps used to assign a swarm of unmanned aerial vehicles (UAVs) tasked to effectively deliver items to target locations. Several possible and acceptable constraints are defined and solved in each step of implementation in order to facilitate the actual operation of aerial autonomous deliveries for a large warehouse. The proposed implementation is determined...
In this work, a method for placing anchor nodes for lateration based wireless 3D indoor locating systems is presented. It combines genetic optimization with radio impulse propagation simulation using a physical ray-tracer. It is shown that the proposed method's results decrease the locating error for a variety of real environments with increasing complexity in comparison to an organic equidistant...
One of the problems to be solved in the management of rail traffic is the problem of attaching the traction resources to the trains. In this paper, we will examine in detail two algorithms that are used for performing this task — stochastic algorithm and genetic algorithm. The second problem is schedule optimization problem. This paper presents auction method for solving this problem.
The compact genetic algorithm cGA is used in this paper to design an efficient soft-decision decoding algorithm, especially for the cyclic codes, because the cGA dramatically reduces the population's size and rapidly converges to the optimal solution compared to classical genetic algorithms. Our main contribution is to exploit the cyclic property of cyclic linear codes to reduce the complexity of...
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