Problem statement: For solving complex issues, the current tendency goes towards the swarms behaviors, realized on a basis of collective interactions, which results from a cooperative work favoring exchanges between individuals of a same group at microscopic level and allowing the emergence of complex collective behaviors at macroscopic level. Many models were inspired by these attitudes to find simple rules, guiding mobile, autonomous robots with limited capacities in their environment in order to achieve tasks like those of exploration, self-assembly and gathering. Multimarking technique as indirect communication inside the same robots group can optimize time of such achievements Approach: A method based on the reversed emergence principle combined to a genetic algorithm is presented here, making evolve a global behavior inside simulated robots group called agent-robots, with an aim to find the micro-rules forming a heap according to two approaches. The first approach accomplishes an ordinary grouping and the second one, which we propose, based on the exclusive multi-marking principle. The control device, guiding these robots-agent to succeed this task, functions on a basis of sensor-motor rules being used to arbitrate between a given number of elementary behaviors with which we equip each one of them initially. Results: Simulation results, implemented according to a reactive agent's model, making it possible to show the consistency of the detected rules and the efficient of the proposed approach in comparison with the ordinary one, are provided and commented. The time optimization of grouping by robots like these can have a huge economic and strategic impact in sectors as important as industry, agriculture and military domain. Conclusion:Like examples, we can quote the grouping of goods in a warehouse, the grouping of ores from mines, the grouping of vegetables and fruits in gardens and the recovery of weapons, in real time, from a battle field. This work can be generalized, in the future, to the multi-heap formation to perform the classification task according to given criteria.
Problem statement: For solving complex issues, the current tendency goes towards the swarms behaviors, realized on a basis of collective interactions, which results from a cooperative work favoring exchanges between individuals of a same group at microscopic level and allowing the emergence of complex collective behaviors at macroscopic level. Many models were inspired by these attitudes to find simple rules, guiding mobile, autonomous robots with limited capacities in their environment in order to achieve tasks like those of exploration, self-assembly and gathering. Multimarking technique as indirect communication inside the same robots group can optimize time of such achievements Approach: A method based on the reversed emergence principle combined to a genetic algorithm is presented here, making evolve a global behavior inside simulated robots group called agent-robots, with an aim to find the micro-rules forming a heap according to two approaches. The first approach accomplishes an ordinary grouping and the second one, which we propose, based on the exclusive multi-marking principle. The control device, guiding these robots-agent to succeed this task, functions on a basis of sensor-motor rules being used to arbitrate between a given number of elementary behaviors with which we equip each one of them initially. Results: Simulation results, implemented according to a reactive agent's model, making it possible to show the consistency of the detected rules and the efficient of the proposed approach in comparison with the ordinary one, are provided and commented. The time optimization of grouping by robots like these can have a huge economic and strategic impact in sectors as important as industry, agriculture and military domain. Conclusion:Like examples, we can quote the grouping of goods in a warehouse, the grouping of ores from mines, the grouping of vegetables and fruits in gardens and the recovery of weapons, in real time, from a battle field. This work can be generalized, in the future, to the multi-heap formation to perform the classification task according to given criteria.
This paper deals with the lactic bacteria found in the raw camel milk producing antibacterial substances. Samples of milk were obtained from female camels of herds from nomads living in the south of Algeria. The antibacterial activity of the bacteria was tested on Staphylococcus aureus strains and to highlight this activity in a yoghourt for therapeutic purpose.Among the seven (07) strains of lactic bacteria which were isolated from camel milk Lb. fermentum (Lc17) presented the highest antagonistic effect on S. aureus. After incorporation in the yoghourt ,It was verified that there was no interaction between the lactic ferments of yoghourt and Lb. fermentum and no modification of the acidity. However the realization of a yoghourt containing Lb. fermentum with shown a total inhibition of Staphylococcus aureus to a load 5,87 log UFC compared to that of yoghourt made up exclusively of lactic leavens, after 4 hours of incubation in mixed culture.
Cet article a pour but de fournir des données sociolinguistiques sur le parler arabe de la ville d'Annaba (nord-est algérien). Le dialecte étudié présente des faits linguistiques communs aux autres parlers arabes de l'Algérie, mais aussi un faisceau de traits qui le rapprochent des parlers tunisiens et tripolitains. Par ailleurs, on constate l'existence de deux variétés dialectales au sein de ce parler: d'un côté le vieux parler de la Place d'Armes et d'un autre côté le nouveau parler de la ville employé principalement par les jeunes.
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