Authentication is very important in validating a medical content in the domain of telemedicine; however, there are many challenges. Accurate verification is paramount, and any misuse of personal information may have serious consequences. Many authentication processes tried to design various methods to minimise such discrepancies. In this current work, we propose a new approach to design a robust biomedical content authentication system by embedding logo of the hospital within the electrocardiogram signal by means of both discrete wavelet transformation and cuckoo search CS. An adaptive meta-heuristic cuckoo search is used to find the optimal scaling factor settings for logo embedding. Results show that the proposed method can serve as a secure and accurate authentication system.
No abstract is provided for this article.
No abstract is provided for this article.
Resource allocation in an OFDMA system has been an extremely challenging optimization task. Due to the nature of the problem, this optimization problem can be NP-hard. The majority of existing methods are based on Lagrangian duality, in combination with gradient-based methods. In this paper, we apply genetic algorithm to tune the power allocated to each sub-channel in an OFDMA system. This is done by applying GA in tuning the power allocated for the m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> user in the n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> channel (p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m,n</sub> ) after solving the resource allocation problem. The first part is a binary optimization problem, whereas the latter part is a continuous optimization problem. In solving the energy-efficient resource allocation problem, the objective is to minimize the transmitted power while fulfilling the transmission rate demand per user. Our simulation results showed that the GA method can obtain global solutions with speedy convergence.
Many quantities such as velocities and forces are vectors because they have both directions and magnitudes. In fact, vectors are crucially important in many disciplines such as engineering and physics. This chapter first introduces vectors and then presents the basic vector algebra.
Cuckoo search (CS) is one of the latest nature-inspired metaheuristic algorithms, developed in 2009 by Xin-She Yang of Cambridge University and Suash Deb of C. V. Raman College of Engineering. CS is based on the brood parasitism of some cuckoo species. In addition, this algorithm is enhanced by the so-called Lévy flights rather than by simple isotropic random walks. Recent studies show that CS is potentially far more efficient than PSO, genetic algorithms, and other algorithms.
Many problems in science and engineering can be formulated as optimization problems, subject to complex nonlinear constraints. The solutions of highly nonlinear problems usually require sophisticated optimization algorithms, and traditional algorithms may struggle to deal with such problems. A current trend is to use nature-inspired algorithms due to their flexibility and effectiveness. However, there are some key issues concerning nature-inspired computation and swarm intelligence. This paper provides an in-depth review of some recent nature-inspired algorithms with the emphasis on their search mechanisms and mathematical foundations. Some challenging issues are identified and five open problems are highlighted, concerning the analysis of algorithmic convergence and stability, parameter tuning, mathematical framework, role of benchmarking and scalability. These problems are discussed with the directions for future research.
Many design problems in engineering are typically multiobjective, under complex nonlinear constraints. The algorithms needed to solve multiobjective problems can be significantly different from the methods for single objective optimization. Computing effort and the number of function evaluations may often increase significantly for multiobjective problems. Metaheuristic algorithms start to show their advantages in dealing with multiobjective optimization. In this paper, we formulate a new cuckoo search for multiobjective optimization. We validate it against a set of multiobjective test functions, and then apply it to solve structural design problems such as beam design and disc brake design. In addition, we also analyze the main characteristics of the algorithm and their implications.
Meta-heuristic algorithms are often nature-inspired, and they are becoming very powerful in solving global optimisation problems. More than a dozen major meta-heuristic algorithms have been developed over the last three decades, and there exist even more variants and hybrids of meta-heuristics. This paper intends to provide an overview of nature-inspired meta-heuristic algorithms, from a brief history to their applications. We try to analyse the main components of these algorithms and how and why they work. Then, we intend to provide a unified view of meta-heuristics by proposing a generalised evolutionary walk algorithm (GEWA). Finally, we discuss some of the important open questions.
The small-world networks recently introduced by Watts and Strogatz [Nature 393, 440 (1998)] has attracted much interests in studying the interesting properties of the networks without time-delay. However, a signal or influence travelling on the small-world networks often associated with time-delay features which are very common in biological and physical networks. We develop an analytical approach as well as numerical simulations to try to characterize the effect of time-delay on the properties of small-world networks. An analytical expression of the fractal dimension of the small-world networks is given and thus compared with the results from numerical simulations. Analysis shows that small-world networks with time-delay generally have the multifractals property.
No abstract is provided for this article.
No abstract is provided for this article.
