By Douglas L. Cairns
This can be the 1st learn in English to ascertain the most an important phrases in Greek moral and social discourse, aidos, inside of a variety of Greek literature. mostly rendered "shame," "modesty," or "respect," aidos is among the such a lot elusive and hard Greek phrases to translate. Dr. Cairns discusses the character and alertness of aidos and different suitable phrases in a few authors; with specific emphasis on their manifestations in epic, tragedy, and philosophy. He indicates that the essence of the concept that is to be present in its courting with Greek values of honor, within which context it may possibly realize and reply to the honour of either the self and others. It hence includes either self- and different- concerning habit, aggressive and cooperative values.
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Additional info for Aidos: The Psychology and Ethics of Honour and Shame in Ancient Greek Literature
285-299. Hassan, F. A. (1978). Sediments in archaeology: Methods and implications for palaeoenvironmental and cultural analysis. Journal of Field Archaeology 5, pp. 197-213. Kontogiorgos, D, Leontitsis, A. (2005). Micro-artefacts weight estimation by Genetic Algorithm minimisation, Journal of Archaeological Science 32, pp. 1275-1282. , and Narihisa, H. (2001). The efficiency of hybrid mutation genetic algorithm for the travelling salesman problem. Mathematical and Computer Modelling 31, pp. 197-203.
3 shows the microartifacts weight percentages. 1. Discrepancies between actual sub-sample weight values and the estimated subsample weight values from the data obtained from the data-base. Test again for the Optimum! 45 Discrepancies may be observed between the actual sub-sample weight values (d) and the estimated values (Cx). These discrepancies have to be relatively small. 1 presents the discrepancies between actual sub-sample weight values and the estimated sub-sample weight values from the data obtained from the database.
45 Discrepancies may be observed between the actual sub-sample weight values (d) and the estimated values (Cx). These discrepancies have to be relatively small. 1 presents the discrepancies between actual sub-sample weight values and the estimated sub-sample weight values from the data obtained from the database. 5. CONCLUSIONS This study explored once again the use of Genetic Algorithms as an option for estimating the weights of microartifacts and the corresponding confidence intervals. The method achieved to estimate mean microartifact weight by minimizing the discrepancies caused may be due to the variation in the depositional and post-depositional disturbances on different types of archaeological sediments and contexts.