RESUMO

Nature-inspired computing is a promising field of artificial intelligence. This area is mainly devoted to designing computational models based on natural phenomena to address complex problems. Nature provides a rich source of inspiration for designing smart procedures capable of becoming powerful algorithms. Many of these procedures have been successfully developed to treat optimization problems, with impressive results. Nonetheless, for these algorithms to reach their maximum performance, a proper balance between the intensification and the diversification phases is required. The intensification generates a local solution around the best solution by exploiting a promising region. Diversification is responsible for finding new solutions when the main procedure is trapped in a local region. This procedure is usually carryout by non-deterministic fundamentals that do not necessarily provide the expected results. Here, we encounter the stagnation problem, which describes a scenario where the search for the optimum solution stalls before discovering a globally optimal solution. In this work, we propose an efficient technique for detecting and leaving local optimum regions based on Shannon entropy. This component can measure the uncertainty level of the observations taken from random variables. We employ this principle on three well-known population-based bio-inspired optimization algorithms: particle swarm optimization, bat optimization, and black hole algorithm. The proposal's performance is evidenced by solving twenty of the most challenging instances of the multidimensional knapsack problem. Computational results show that the proposed exploration approach is a legitimate alternative to manage the diversification of solutions since the improved techniques can generate a better distribution of the optimal values found. The best results are with the bat method, where in all instances, the enhanced solver with the Shannon exploration strategy works better than its native version. For the other two bio-inspired algorithms, the proposal operates significantly better in over 70% of instances.

RESUMO

Offsite pesticide losses in tropical mountainous regions have been little studied. One example is measuring pesticide drift soil deposition, which can support pesticide risk assessment for surface water, soil, bystanders, and off-target plants and fauna. This is considered a serious gap, given the evidence of pesticide-related poisoning in those regions. Empirical data of drift deposition of a pesticide surrogate, Uranine tracer, within one of the highest potato-producing regions in Colombia, characterized by small plots and mountain orography, is presented. High drift values encountered in this study reflect the actual spray conditions using hand-held knapsack sprayers. Comparison between measured and predicted drift values using three existing empirical equations showed important underestimation. However, after their optimization based on measured drift information, the equations showed a strong predictive power for this study area and the study conditions. The most suitable curve to assess mean relative drift was the IMAG calculator after optimization.

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RESUMO

Accumulated rainfall thresholds were studied in seven field experiments conducted in Ecuador and Peru for their value in timing applications of fungicide to control potato late blight, caused by Phytophthora infestans. Fungicide regimes based on accumulated rainfall thresholds ranging from 10 to 70 mm were compared with calendar spray schemes of every 5 or 7 days. Very low thresholds of 10 to 20 mm gave similar levels of control and resulted in similar number of sprays as did calendar spraying. However, neither low thresholds nor calendar sprays were effective in protecting susceptible potato genotypes in over half of the experiments. Thresholds of 25 to 50 mm of rainfall led to reduction in the number of sprays needed to protect resistant cultivars but also resulted in high levels of disease on susceptible cultivars. We conclude that timing fungicide sprays based on accumulated rainfall thresholds could be a successful component of integrated management strategies that include cultivars with moderate or high levels of resistance. The simplicity of measuring accumulated rainfall means that the technology can potentially be used by resource-poor farmers in developing countries.

RESUMO

Este trabalho apresenta os resultados do monitoramento realizado durante 330 dias na Estaçäo de Piscicultura da Universidade Estadual de Londrina - UEL, com o objetivo de utilizar técnicas de controle de qualidade para atingir maior produtividade de tilápias. Foram utilizados 240 alevinos de tilápia do Nilo (Oreochromis niloticus), distribuídos num delineamento inteiramente casualizado. Os valores da temperatura média mensal revelaram estar "fora de controle estatístico" e mostraram através da aplicaçäo dos índices de capacidade (Cp e Cpk) que 39,74 por cento estäo abaixo do limite inferior de especificaçäo (LIE). A análise dos resultados obtidos, através da aplicaçäo das técnicas de Pareto e Problema da Mochila, evidenciaram a soluçäo ótima para resolver os problemas de Saprolenea sp-2 e Laerner sp-4 com a funçäo objetivo Z* maximizada

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