A Neural Network Model for Cursive Script Production

This article describes a neural network model, called the VITEWRITE model, for generating handwriting movements. The model consists of a sequential controller, or motor program, that interacts with a trajectory generator to move a. hand with redundant degrees of freedom. The neural trajectory generator is the Vector Integration to Endpoint (VITE) model for synchronous variable-speed control of multijoint movements. VITE properties enable a simple control strategy to generate complex handwritten script if the hand model contains redundant degrees of freedom. The proposed controller launches transient directional commands to independent hand synergies at times when the hand begins to move, or when a velocity peak in a given synergy is achieved. The VITE model translates these temporally disjoint synergy commands into smooth curvilinear trajectories among temporally overlapping synergetic movements. The separate "score" of onset times used in most prior models is hereby replaced by a self-scaling activity-released "motor program" that uses few memory resources, enables each synergy to exhibit a unimodal velocity profile during any stroke, generates letters that are invariant under speed and size rescaling, and enables effortless. connection of letter shapes into words. Speed and size rescaling are achieved by scalar GO and GRO signals that express computationally simple volitional commands. Psychophysical data concerning band movements, such as the isochrony principle, asymmetric velocity profiles, and the two-thirds power law relating movement curvature and velocity arise as emergent properties of model interactions.

Good Practice in the use of PowerPoint

This presentation aims to encourage academic staff to make better use of PowerPoint by avoiding dependence on or abuse of bullet points. It highlights PowerPoint's emergent properties and presents clear guidelines for effective slides

Podmiotowość a zmiana społeczna w pismach teoretycznych Margaret S. Archer. Analiza, porównania, rekonceptualizacja pojęć

Wydział Nauk Społecznych: Instytut Socjologii

Truth in complex adaptive systems models should be based on truth by constructive verification

It is argued that the truth status of emergent properties of complex adaptive systems models should be based on an epistemology of proof by constructive verification and therefore on the ontological axioms of a non-realist logical system such as constructivism or intuitionism. ‘Emergent’ properties of complex adaptive systems (CAS) models create particular epistemological and ontological challenges. These challenges bear directly on current debates in the philosophy of mathematics and in theoretical computer science. CAS research, with its emphasis on computer simulation, is heavily reliant on models which explore the entailments of Formal Axiomatic Systems (FAS). The incompleteness results of Gödel, the incomputability results of Turing, and the Algorithmic Information Theory results of Chaitin, undermine a realist (platonic) truth model of emergent properties. These same findings support the hegemony of epistemology over ontology and point to alternative truth models such as intuitionism, constructivism and quasi-empiricism.

Land re-use, complexity and actor-networks: a framework for research

This paper will present a conceptual framework for the examination of land redevelopment based on a complex systems/networks approach. As Alvin Toffler insightfully noted, modern scientific enquiry has become exceptionally good at splitting problems into pieces but has forgotten how to put the pieces back together. Twenty-five years after his remarks, governments and corporations faced with the requirements of sustainability are struggling to promote an ‘integrated’ or ‘holistic’ approach to tackling problems. Despite the talk, both practice and research provide few platforms that allow for ‘joined up’ thinking and action. With socio-economic phenomena, such as land redevelopment, promising prospects open up when we assume that their constituents can make up complex systems whose emergent properties are more than the sum of the parts and whose behaviour is inherently difficult to predict. A review of previous research shows that it has mainly focused on idealised, ‘mechanical’ views of property development processes that fail to recognise in full the relationships between actors, the structures created and their emergent qualities. When reality failed to live up to the expectations of these theoretical constructs then somebody had to be blamed for it: planners, developers, politicians. However, from a ‘synthetic’ point of view the agents and networks involved in property development can be seen as constituents of structures that perform complex processes. These structures interact, forming new more complex structures and networks. Redevelopment then can be conceptualised as a process of transformation: a complex system, a ‘dissipative’ structure involving developers, planners, landowners, state agencies etc., unlocks the potential of previously used sites, transforms space towards a higher order of complexity and ‘consumes’ but also ‘creates’ different forms of capital in the process. Analysis of network relations point toward the ‘dualism’ of structure and agency in these processes of system transformation and change. Insights from actor network theory can be conjoined with notions of complexity and chaos to build an understanding of the ways in which actors actively seek to shape these structures and systems, whilst at the same time are recursively shaped by them in their strategies and actions. This approach transcends the blame game and allows for inter-disciplinary inputs to be placed within a broader explanatory framework that does away with many past dichotomies. Better understanding of the interactions between actors and the emergent qualities of the networks they form can improve our comprehension of the complex socio-spatial phenomena that redevelopment comprises. The insights that this framework provides when applied in UK institutional investment into redevelopment are considered to be significant.

Redes neurais e representação mental: um ensaio sobre harmonia e racionalidade

Investigaremos, a partir da perspectiva da Ciência Cognitiva, a noção de representação mental, no domínio da percepção visual humana. Ênfase é dada ao paradigma Conexionista, ou de Redes Neurais, de acordo com o qual tais representações mentais são descritas como estruturas emergentes da interação entre sistemas de processamento de informação que se auto-organizam - tais como o cérebro - e a luz estruturada no meio ambiente. Sugerimos que essa noção de representação mental indica uma solução para uma antiga polêmica, entre Representacionalistas e Eliminativistas, acerca da existência de representações mentais no sistema perceptual humano.

Agent-based model to rural-urban migration analysis

In this paper, we analyze the rural-urban migration phenomenon as it is usually observed in economies which are in the early stages of industrialization. The analysis is conducted by means of a statistical mechanics approach which builds a computational agent-based model. Agents are placed on a lattice and the connections among them are described via an Ising-like model. Simulations on this computational model show some emergent properties that are common in developing economies, such as a transitional dynamics characterized by continuous growth of urban population, followed by the equalization of expected wages between rural and urban sectors (Harris-Todaro equilibrium condition), urban concentration and increasing of per capita income. (c) 2005 Elsevier B.V. All rights reserved.

A Harris-Todaro agent-based model to rural-urban migration

The Harris-Todaro model of the rural-urban migration process is revisited under an agent-based approach. The migration of the workers is interpreted as a process of social learning by imitation, formalized by a computational model. By simulating this model, we observe a transitional dynamics with continuous growth of the urban fraction of overall population toward an equilibrium. Such an equilibrium is characterized by stabilization of rural-urban expected wages differential (generalized Harris-Todaro equilibrium condition), urban concentration and urban unemployment. These classic results obtained originally by Harris and Todaro are emergent properties of our model.

Modelos dinâmicos de assembléia

The structure of an ecological community is shaped by several temporally varying mechanisms. Such mechanisms depend in a large extent on species interactions, which are themselves manifestations of the community's own structure. Dynamics and structure are then mutually determined. The assembly models are mathematical or computational models which simulate the dynamics of ecological communities resulting from a historical balance among colonizations and local extinctions, by means of sequential species introductions and their interactions with resident species. They allow analyzing that double relationship between structure and dynamics, recognizing its temporal dependence. It is assumed two spatiotemporal scales: (i) a local scale, where species co-occur and have their dynamics explicitly simulated and (ii) a regional scale without dynamics, representing the external environment which the potential colonizers come from. The mathematical and computational models used to simulate the local dynamics are quite variable, being distinguished according to the complexity mode of population representation, including or not intra or interspecific differences. They determine the community state, in terms of abundances, interactions, and extinctions between two successive colonization attempts. The schedules of species introductions also follow diverse (although arbitrary) rules, which vary qualitatively with respect to species appearance mode, whether by speciation or by immigration, and quantitatively with respect to their rates of introduction into the community. Combining these criteria arises a great range of approaches for assembly models, each with its own limitations and questions, but contributing in a complementary way to elucidate the mechanisms structuring natural communities. To present such approaches, still incipient as research fields in Brazil, to describe some methods of analysis and to discuss the implications of their assumptions for the understanding of ecological patterns are the objectives of the present review.

Macroecologia de cetáceos marinhos (ordem cetacea)

Pós-graduação em Ciências Biológicas (Zoologia) - IBRC

O problema da consciência: a abordgem neurocientífica do problema-corpo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

O conceito de organismo: uma introdução à epistemologia do conhecimento biológico na formação de graduandos de biologia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise de propriedades topológicas das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)

Caracterização topológica dos motivos das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

The reducionism method has helped in the clari cation of functioning of many biological process. However, such process are extremely complex and have emergent properties that can not be explained or even predicted by reducionism methods. To overcome these limits, researchers have been used a set of methods known as systems biology, a new area of biology aiming to understand the interactions between the multiple components of biological processes. These interactions can be represented by a mathematical object called graph or network, where the interacting elements are represented by a vertex and the interactions by edges that connect a pair of vertexes. Into graphs it is possible to nd subgraphs, occurring in complex networks at numbers that are signi cantly higher than those in randomized networks, they are de ned as motifs. As motifs in biological networks may represent the structural units of biological processess, their detection is important. Therefore, the aim of this present work was detect, count and classify motifs present in biological integrated networks of bacteria Escherichia coli and yeast Saccharomyces cere- visiae. For this purpose, we implemented codes in MathematicaR and Python environments for detecting, counting and classifying motifs in these networks. The composition and types of motifs detected in these integrated networks indicate that such networks are organized in three main bridged modules composed by motifs in which edges are all the same type. The connecting bridges are composed by motifs in which the types of edges are diferent

Evolutionary methods for self-organizing cooperation in peer-to-peer networks

The Peer-to-Peer network paradigm is drawing the attention of both final users and researchers for its features. P2P networks shift from the classic client-server approach to a high level of decentralization where there is no central control and all the nodes should be able not only to require services, but to provide them to other peers as well. While on one hand such high level of decentralization might lead to interesting properties like scalability and fault tolerance, on the other hand it implies many new problems to deal with. A key feature of many P2P systems is openness, meaning that everybody is potentially able to join a network with no need for subscription or payment systems. The combination of openness and lack of central control makes it feasible for a user to free-ride, that is to increase its own benefit by using services without allocating resources to satisfy other peers’ requests. One of the main goals when designing a P2P system is therefore to achieve cooperation between users. Given the nature of P2P systems based on simple local interactions of many peers having partial knowledge of the whole system, an interesting way to achieve desired properties on a system scale might consist in obtaining them as emergent properties of the many interactions occurring at local node level. Two methods are typically used to face the problem of cooperation in P2P networks: 1) engineering emergent properties when designing the protocol; 2) study the system as a game and apply Game Theory techniques, especially to find Nash Equilibria in the game and to reach them making the system stable against possible deviant behaviors. In this work we present an evolutionary framework to enforce cooperative behaviour in P2P networks that is alternative to both the methods mentioned above. Our approach is based on an evolutionary algorithm inspired by computational sociology and evolutionary game theory, consisting in having each peer periodically trying to copy another peer which is performing better. The proposed algorithms, called SLAC and SLACER, draw inspiration from tag systems originated in computational sociology, the main idea behind the algorithm consists in having low performance nodes copying high performance ones. The algorithm is run locally by every node and leads to an evolution of the network both from the topology and from the nodes’ strategy point of view. Initial tests with a simple Prisoners’ Dilemma application show how SLAC is able to bring the network to a state of high cooperation independently from the initial network conditions. Interesting results are obtained when studying the effect of cheating nodes on SLAC algorithm. In fact in some cases selfish nodes rationally exploiting the system for their own benefit can actually improve system performance from the cooperation formation point of view. The final step is to apply our results to more realistic scenarios. We put our efforts in studying and improving the BitTorrent protocol. BitTorrent was chosen not only for its popularity but because it has many points in common with SLAC and SLACER algorithms, ranging from the game theoretical inspiration (tit-for-tat-like mechanism) to the swarms topology. We discovered fairness, meant as ratio between uploaded and downloaded data, to be a weakness of the original BitTorrent protocol and we drew inspiration from the knowledge of cooperation formation and maintenance mechanism derived from the development and analysis of SLAC and SLACER, to improve fairness and tackle freeriding and cheating in BitTorrent. We produced an extension of BitTorrent called BitFair that has been evaluated through simulation and has shown the abilities of enforcing fairness and tackling free-riding and cheating nodes.