Finding groups in data: Cluster analysis with ants

Wepresent in this paper a modification of Lumer and Faieta’s algorithm for data clustering. This approach mimics the clustering behavior observed in real ant colonies. This algorithm discovers automatically clusters in numerical data without prior knowledge of possible number of clusters. In this paper we focus on ant-based clustering algorithms, a particular kind of a swarm intelligent system, and on the effects on the final clustering by using during the classification differentmetrics of dissimilarity: Euclidean, Cosine, and Gower measures. Clustering with swarm-based algorithms is emerging as an alternative to more conventional clustering methods, such as e.g. k-means, etc. Among the many bio-inspired techniques, ant clustering algorithms have received special attention, especially because they still require much investigation to improve performance, stability and other key features that would make such algorithms mature tools for data mining. As a case study, this paper focus on the behavior of clustering procedures in those new approaches. The proposed algorithm and its modifications are evaluated in a number of well-known benchmark datasets. Empirical results clearly show that ant-based clustering algorithms performs well when compared to another techniques

Ant-inspired strategies for opportunistic load balancing in the distributed computation of solutions to embarrassingly parallel problems

Dissertation (MSc(Computer Science))--University of Pretoria, 2016.Computational science is a practice that requires a large amount of computing time. One means of providing the required computing time is to construct a distributed computing system that utilises the ordinary desktop computers found within an organisation. However, when the constituent computers do not all perform computations at the same speed, the overall completion time of a project involving the execution of tasks by all of the computers in the system becomes dependent on the performance of the slowest computer in the network. This study proposes two ant-inspired algorithms for dynamic task allocation that aim to overcome the aforementioned dependency. A procedure for tuning the free parameters of the algorithms is specified and the algorithms are evaluated for their viability in terms of their effect on the overall completion time of tasks as well as their usage of bandwidth in the network.Computer ScienceMSc(Computer Science)Unrestricte

The economic rationality of consumption in the Mycenaean political economy and its role in the reproduction of social personae: modeling prestige networks.

This thesis is a theoretical examination of the economic rationality of consumption as it existed within the Mycenaean political economy. Using a modified paradigm of social network analysis, a semiotic approach is used in the study of identity expression and economic stratification present at three Late Helladic cemeteries. In doing so, the claim that exchange strategies which existed outside of palatial redistribution were present in the Late Helladic was substantiated as a similar logic of mortuary stratification which existed during the palatial era was also found to have existed after the shift to the post-palatial era and the collapse of the prevailing redistributive mode of consumption

Effects of the Manipulation of Aboveground Plant Diversity in Restoration Management on the Diversity of Belowground Arthropod Assemblage

A missing element in restoring belowground soil systems to a relatively healthy state may lie in promoting microarthropod diversity. By contributing to healthy nutrient cycling and assisting in the breakdown of leaf litter a diverse microarthropod population helps improve the overall soil quality. My study evaluated how current restoration practices aimed at maintaining aboveground diversity affects belowground microarthropod populations. I examined how the aboveground manipulation of plant diversity in restoration management practices affects the hyperdiverse assemblage of belowground arthropod communities. Additionally, I examined the relationship between soil nutrient content and microarthropod diversity. This study was conducted within the boundaries of Chicago Wilderness from sites with four different management treatments, ranging from unmanaged (W0) to highly managed (W3). 3 soil cores measuring 5 x 5 centimeters were taken from each site and microarthropods were extracted in a Berlese funnel. Abundance and species diversity were assessed. The microarthropod species data showed that while 12 common species were found at over 70% of the sites, 32 species were present at less than 30% of the sites. Of these 32 rare species, 15 were unique to only 1 site. Further analysis of the common mites revealed specific associations between those 12 common species. My results showed that restoration management had no significant effect on microarthropod diversity. Plant root simulator (PRS) probes were used on each site providing data on fifteen soil nutrients. There was significant explanatory value to the soil nutrient data, especially nitrogen, phosphorus, and zine. As these nutrients increased in the soil, microarthropod diversity also increased. Knowledge of these nutrients offers a simple set of tools for evaluating the relationship between soil quality of a specific site and belowground diversity. I concluded that restoration management aimed at plant diversity was largely ineffective in determining microathropod diversity; nevertheless, the relationship between soil nutrients available and microarthropod diversity may have implications for management. Understanding relationships such as these are instrumental in the development of new restoration management tools

Complex geoarcheological investigation at the Székelyudvarhely-Kadicsfalva/Cãdiseni site (Romania)

Abstract Environmental historical analyses, including sedimentological, pedological, palynological, archeobotanical and phytolith analyses were carried out on samples derived from the Kadicsfalva/Cãdiseni archeological site. Our aim was to provide paleoenvironmental data to the archeological results in order to reconstruct the former milieu of the Gothic population, and to provide information regarding their environment management. At the end of the Pleistocene loess and alluvial loess developed from the eolian dust that accumulated on the wet surfaces of the Pleistocene sediments. The site provided favorable conditions to host a settlement and supports its long-term colonization owning to the riverside terrace surface location. The comparative analysis of the recent and the Gothic soil horizon proved that the recent soil horizon is over-utilized; its productivity can be maintained only by intensive fertilization and almost every one of its parameters is below the element and nutrient composition of the Gothic soil horizon

Modeling Collective Animal Behavior with a Cognitive Perspective: A Methodological Framework

The last decades have seen an increasing interest in modeling collective animal behavior. Some studies try to reproduce as accurately as possible the collective dynamics and patterns observed in several animal groups with biologically plausible, individual behavioral rules. The objective is then essentially to demonstrate that the observed collective features may be the result of self-organizing processes involving quite simple individual behaviors. Other studies concentrate on the objective of establishing or enriching links between collective behavior researches and cognitive or physiological ones, which then requires that each individual rule be carefully validated. Here we discuss the methodological consequences of this additional requirement. Using the example of corpse clustering in ants, we first illustrate that it may be impossible to discriminate among alternative individual rules by considering only observational data collected at the group level. Six individual behavioral models are described: They are clearly distinct in terms of individual behaviors, they all reproduce satisfactorily the collective dynamics and distribution patterns observed in experiments, and we show theoretically that it is strictly impossible to discriminate two of these models even in the limit of an infinite amount of data whatever the accuracy level. A set of methodological steps are then listed and discussed as practical ways to partially overcome this problem. They involve complementary experimental protocols specifically designed to address the behavioral rules successively, conserving group-level data for the overall model validation. In this context, we highlight the importance of maintaining a sharp distinction between model enunciation, with explicit references to validated biological concepts, and formal translation of these concepts in terms of quantitative state variables and fittable functional dependences. Illustrative examples are provided of the benefits expected during the often long and difficult process of refining a behavioral model, designing adapted experimental protocols and inversing model parameters