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In this study, the self-adaptive evolutionary (SaE) agent is employed to structure the contributing elements to process the management of extreme learning machine (ELM) architecture based on a logical procedure. In fact, the SaE algorithm is utilized for possibility of enhancing the performance of the ELM to estimate daily soil temperature (ST) at 6 different depths of 5, 10, 20, 30, 50 and 100 cm. In the developed SaE-ELM model, the network hidden node parameters of the ELM are optimized using SaE algorithm. The precision of the SaE-ELM is then compared with the ELM model. Daily weather data sets including minimum, maximum and average air temperatures (Tmin, Tmax and Tavg), atmospheric... 

In this letter, we consider two problems of sending a bivariate Gaussian source through a two-user Gaussian non-orthogonal multiple-access channel. We provide a new distortion outer bound for the considered joint source-channel coding problems, which significantly reduces the gap between inner and outer bounds of the distortion for correlation coefficients below a threshold. Furthermore, numerical results show, that under some conditions, our proposed outer bound matches with the inner bound obtained via the separate source-channel coding scheme, which proves the optimality of this scheme. © 1997-2012 IEEE  

In this work, we present a novel FPGA-based implementation of the AES algorithm which has a two-layered resistance against power analysis attacks. Our countermeasure is based on the concept of finite state machine equipped with a random number generator. Beyond masking the intermediate variables as the first layer of defense, we randomize the sequences of operations and add dummy computations as the second layer of defense. Therefore, the first order attack is prevented and the number of power traces needed for a successful second order attack is vastly increased and the correlation coefficient is decreased, as expected. © 2017 IEEE