Abstract
This paper compares optimal path planning algorithms based on a Genetic Algorithm and a Particle Swarm Optimization algorithm applied to multiple bioinspired robots in a 2D environment simulation. The planning objectives are related to the harvesting of an apple plantation in which three swarm of butterflies were run, counting the fruits on the ground to optimize the harvest in a cooperative way. Robotic swarms must travel through points on the map to count the fruits. The time for each swarm was also counted for the comparison results. © Springer Nature Switzerland AG 2019.

Abstract
The challenge of noise attenuation in images has led to extensive research on improved noise reduction techniques, preserving important image characteristics, improving not only visual perception, but also enabling the use for special purposes, such as in medicine to increase clarity of medical images. In this paper, a technique for noise attenuation in medical images is proposed. Its operation takes place through the application of an adapted genetic algorithm. The results of experiments show that the proposed approach works best in suppressing artifacts and the preservation of the structure compared with several existing methods.

Abstract
Research Highlights: This study bridges a gap of knowledge about the maximum size-density trajectory for juvenile stands of maritime pine. The continuity of the trajectory along the development stages to maturity is assured with a straightforward approach providing support to determine optimum density along all the revolution periods for the species. Background and Objectives: Forest fire is a significant threat to forests in the Mediterranean regions, but also a natural disturbance that plays a vital role in the perpetuation of forest stands. In recent decades, there has been an increase of burnt area in maritime forests in Portugal, followed by an increased interest in managing the natural and usually abundant regeneration occurring after the fires. The gap in the knowledge of growth dynamics for juvenile stages, for these forest systems, currently constrains their correct management, for forest planning, particularly in determining the optimal densities. The study aims to identify the maximum attainable density trajectory at the early stages of development of the species that could support a non-empirical definition of silvicultural prescriptions and thinning decisions, along the revolution. Materials and Methods: A representative data set collected in stands regenerated after fire supports the analysis of the maximum size-density trajectory for the species. Results: The maximum size-density trajectory for the juvenile stands deviates from the expected trajectory defined in the self-thinning line published for the species. Significant deviation occurs at the lower end of the line, indicating the need for a reevaluation of the existing self-thinning line. We propose a new self-thinning model for the species that explicitly considers the behavior of size-density for juvenile stands. The new model assures a logical continuity for the trajectory from the young stages of development to maturity. Conclusions: The proposed model based on the maximum attainable size-density trajectory provides ecological-based support to define silvicultural guidelines for management of the species.

Abstract
Optical Networks-on-Chip (ONoCs) are a promising solution for high-performance multi-core integration with better latency and bandwidth than traditional Electrical NoCs. Wavelength-routed ONoCs (WRONoCs) offer yet additional performance guarantees. However, WRONoC design presents new EDA challenges which have not yet been fully addressed. So far, most topology analysis is abstract, i.e., overlooks layout concerns, while for layout the tools available perform Place & Route (P&R) but no topology optimization. Thus, a need arises for a novel optimization method combining both aspects of WRONoC design. In this paper such a method, PSION, is laid out. When compared to the state-of-the-art design procedure, results show a 1.8x reduction in maximum optical insertion loss.

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Abstract