Confronting the Settler Legacy: Indigenisation and Transformation in South Africa and Zimbabwe

This article examines attempts to negotiate a perceived residual dominance of settler populations in South Africa and Zimbabwe by means of developmental and cultural policies deemed necessary to restore sovereignty to Africans. Indigenisation has become a preferred strategy for reconstructing post-colonial states in Africa: indigenisation of the economy as part of a Third Chimurenga in Zimbabwe and Black Economic Empowerment in the socio-cultural context of Ubuntu in South Africa. These are issues arising from the regional legacy of contested and uneven transitions to majority rule. Identifying how governments frame the ‘settler problem’, and politicise space in doing so, is crucial for understanding post-colonial politics. Indigenisation in Zimbabwe allows the government to maintain a network of patronage and official rhetoric is highly divisive and exclusivist although couched in terms of reclaiming African values and sovereignty. Revival of Ubuntu as a cultural value system in South Africa facilitates a more positive approach to indigenisation, although Black Economic Empowerment displays elitist tendencies and cultural transformation remains controversial and elusive. The perceived need to anchor policy in socially acceptable (i.e., ostensibly indigenous/traditional) contexts has become a prominent feature of post-colonial politics and is indicative of an indigenous turn in Southern African politics.

It's good to be queen: classically eusocial colony structure and low worker fitness in an obligately eusocial sweat bee.

Lasioglossum malachurum, a bee species common across much of Europe, is obligately eusocial across its range but exhibits clear geographic variation in demography and social behaviour. This variation suggests that social interactions between queens and workers, opportunities for worker oviposition, and patterns of relatedness among nest mates may vary considerably, both within and among regions. In this study, we used three microsatellite loci with 12–18 alleles each to examine the sociogenetic structure of colonies from a population at Agios Nikolaos Monemvasias in southern Greece. These analyses reveal that the majority of colonies exhibit classical eusocial colony structure in which a single queen mated to a single male monopolizes oviposition. Nevertheless, we also detect low rates of multiqueen nest founding, occasional caste switching by worker-destined females, and worker oviposition of both gyne and male-producing eggs in the final brood. Previous evidence that the majority of workers show some ovarian development and a minority (17%) have at least one large oocyte contrasts with the observation that only 2–3% of gynes and males (the so-called reproductive brood) are produced by workers. An evaluation of the parameters of Hamilton's Rule suggests that queens benefit greatly from the help provided by workers but that workers achieve greater fitness by provisioning and laying their own eggs rather than by tending to the queen's eggs. This conflict of interest between the queen and her workers suggests that the discrepancy between potential and achieved worker oviposition is due to queen interference. Comparison of relatedness and maternity patterns in the Agios Nikolaos Monemvasias population with those from a northern population near Tübingen, Germany, points to a north–south cline of increasingly effective queen control of worker behaviour.

The Agent-Rule-Class Framework for Multi-Agent Systems

Multi-agent systems have become increasingly mature, but their appearance does not make the traditional OO approach obsolete. On the contrary, OO methodologies can benefit from the principles and tools designed for agent systems. The Agent-Rule-Class (ARC) framework is proposed as an approach that builds agents upon traditional OO system components and makes use of business rules to dictate agent behaviour with the aid of OO components. By modelling agent knowledge in business rules, the proposed paradigm provides a straightforward means to develop agent-oriented systems based on the existing object-oriented systems and offers features that are otherwise difficult to achieve in the original OO systems. The main outcome of using ARC is the achievement of adaptivity. The framework is supported by a tool that ensures agents implement up-to-date requirements from business people, reflecting desired current behaviour, without the need for frequent system rebuilds. ARC is illustrated with a rail track example.

A recursive rule base adjustment algorithm for a fuzzy logic controller

This paper introduces a recursive rule base adjustment to enhance the performance of fuzzy logic controllers. Here the fuzzy controller is constructed on the basis of a decision table (DT), relying on membership functions and fuzzy rules that incorporate heuristic knowledge and operator experience. If the controller performance is not satisfactory, it has previously been suggested that the rule base be altered by combined tuning of membership functions and controller scaling factors. The alternative approach proposed here entails alteration of the fuzzy rule base. The recursive rule base adjustment algorithm proposed in this paper has the benefit that it is computationally more efficient for the generation of a DT, and advantage for online realization. Simulation results are presented to support this thesis. (c) 2005 Elsevier B.V. All rights reserved.

The Combination of Multiple Classifiers Using an Evidential Reasoning Approach

In many domains when we have several competing classifiers available we want to synthesize them or some of them to get a more accurate classifier by a combination function. In this paper we propose a ‘class-indifferent’ method for combining classifier decisions represented by evidential structures called triplet and quartet, using Dempster's rule of combination. This method is unique in that it distinguishes important elements from the trivial ones in representing classifier decisions, makes use of more information than others in calculating the support for class labels and provides a practical way to apply the theoretically appealing Dempster–Shafer theory of evidence to the problem of ensemble learning. We present a formalism for modelling classifier decisions as triplet mass functions and we establish a range of formulae for combining these mass functions in order to arrive at a consensus decision. In addition we carry out a comparative study with the alternatives of simplet and dichotomous structure and also compare two combination methods, Dempster's rule and majority voting, over the UCI benchmark data, to demonstrate the advantage our approach offers. (A continuation of the work in this area that was published in IEEE Trans on KDE, and conferences)