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There are problems that are difficult to solve through mathematical programming or by classical methods. These problems are called hard problems due to their high complexity or high dimension. On the other hand, mataheuristics intends to seek a better solution to a problem. The Improvement Harmony Search algorithm is proposed under modification of the bandwidth parameter increasing the quality of the exploitation of the solutions. That is why within the state of the art, are mentioned several versions of harmonic search. The state of the art is supports the fact that the algorithm belongs to the category of those who make modifications to its parameters. This research demonstrates the ability of ImHS to solve a problem of high complexity focused on solving four-bar mechanism designs, whose solutions imply high dimension and which are also classified as hard problems. The two problems that are solved in this investigation, are problems very attacked within the state of the art by various metaheuristics. A comparison is then made against previous solutions with traditional metaheuristics and other versions of harmony search algorithm. Finally, the effectiveness of performance is demonstrated, where proposed algorithm it exceeded five metaheuristic algorithms and five harmony search versions. An optimum is provided in an easy and useful way, the parametric statistics are improved and the number of feasible solutions is exceeded in NP-hard problems as in the case of problems with four-bar mechanisms.

A guided wave-based structural health monitoring (GW-SHM) system aims at determining the integrity of a wide variety of plate-like structures such as aircraft fuselages, pipes, and fuel tanks. It is often based on a sparse grid of piezoelectric transducers for exciting and sensing GWs that under certain conditions interact with damage while propagating. In recent years, various defect imaging algorithms have been proposed for processing GWs signals and, particularly, for computing an image representing the integrity of the studied structure. The performance of the GW-SHM system highly depends on a signal processing methodology. This paper compares defect localization accuracy of the three state-of-art defect imaging algorithms (delay-and-sum, minimum variance, and excitelet) applied to an extensive simulated database of GWs propagation and GWs-defect interaction in aluminum plate under varying temperature and transducers degradation. This study is conducted in order to provide statistical inferences, essential for SHM system performance demonstration.

In multi-objective optimization problems, the optimization target is to obtain a set of non-dominated solutions. Comparing solution sets is crucial in evaluating the performances of different optimization algorithms. The use of performance indicators is common in comparing those sets and, subsequently, optimization algorithms. A good solution set must be close to the Pareto-optimal front, well-distributed, maximally extended and fully filled. Therefore, an effective performance indicator must encompass these features as a whole and must be Pareto dominance compliant. Unfortunately, some of the known indicators often fail to properly reflect the quality of a solution set or cost a lot to compute. This paper demonstrates that the Degree of Approximation (DOA) quality indicator, is a weakly Pareto compliant unary indicator that gives a good estimation of the match between the approximated front and the Pareto-optimal front. Moreover, DOA computation is easy and fast.

The purpose of this research is to find a set of relevant parameters for the emotion recognition. In this study we used the recordings from the emotion database SROL which is part of the project "Voiced Sounds of Romanian Language". The database was validated by human listeners. The recognition accuracy of the correct expressed emotion (neutral tone, joy, fury and sadness) for the entire database was 63.97%. We used for the classification of input data the Recurrent Fuzzy C-Means (FCM) and WKNN algorithms. We compared the cluster position with the statistical parameters extracted from vowels in order to establish the relevance of each parameter in the recognition of the emotions. For the extracted parameters for each vowel (mean, median and standard deviation of fundamental frequency - F0 and F1-F4 formants, jitter, and shimmer) the FCM algorithm gave satisfactory results in the phonemes recognition, but not to the emotions. For this reason we used WKNN algorithm in classification, which provided the errors around 20-30% comparing with FCM algorithm when the classification errors are around 40-50%.

A comparison among three Compact-Polarimetry (CP) Synthetic Aperture Radar (SAR) architectures is followed to analyze some polarimetric features sensitivity with respect to the ocean background variation, which is achieved as situational awareness about the environment influence on detection algorithms performance. Thus, architectures are emulated from Radarsat-2 full-polarimetric actual SAR data, according to wave polarimetry concepts. In this analysis, the entropy of the wave scattered off the observed scene is used as polarimetric feature, considering as reference the conventional target entropy evaluated from full-polarimetric SAR data. Then, actual RISAT-1 Hybrid-Polarity (HP) data are analyzed extracting other polarimetric features to investigate their capabilities to discriminate metallic targets from the ocean background. Relative ocean background sensitivity analysis is addressed using an objective metric named Relative Sensitivity of Polarimetric Features (RSPolF), whose characterizes the polarimetric feature sensitivity for the sea state found in each SAR scene. Additionally, on further works, it can objectively support target detection algorithms for threshold definition.

The paper deals with the performance analysis of three Monte Carlo algorithms for some models of computer architectures. To estimate the performance and the speedup of these algorithms, we introduce a special modification of the criterion for the time required to achieve a preset probable error and consider a serial (von Neumann) architecture, a pipeline architecture, and two MIMD (Multiple Instruction stream, Multiple Data stream) parallel architectures. An approach to constructing Monte Carlo vector algorithms to be efficiently run on pipeline computers has also been considered.