A dynamical adaptive resonance architecture

A set of nonlinear differential equations that describe the dynamics of the ART1 model are presented, along with the motivation for their use. These equations are extensions of those developed by Carpenter and Grossberg (1987). It is shown how these differential equations allow the ART1 model to be realized as a collective nonlinear dynamical system. Specifically, we present an ART1-based neural network model whose description requires no external control features. That is, the dynamics of the model are completely determined by the set of coupled differential equations that comprise the model. It is shown analytically how the parameters of this model can be selected so as to guarantee a behavior equivalent to that of ART1 in both fast and slow learning scenarios. Simulations are performed in which the trajectories of node and weight activities are determined using numerical approximation techniques

After Brown: What Would Martin Luther King Say?

The occasion of the first Martin Luther King Jr. Day Speech at Lewis and Clark Law School, following on the heels of the Supreme Court's rejection of two voluntary racial school integration plans, warrants revisiting the conception of equality that called for school integration, the prospects for equal opportunity without education, and remaining arguments for integration. "Integration" here means more than terminating legally-enforced segregation, and more than sheer mixing of people with different races and identities in the same setting. As Dr. King described it, integration involves the creation of a community of relationships among people who view one another as valuable, who take pride in one another's contributions, and who know that commonalities and synergies outweigh any extra efforts that bridging differences may require. Before the disillusionment accompanying the apparent failure of judicially-mandated school integration, integration was inseparable from access to opportunity as a goal of civil rights reformers from the 19th century through the middle of the 20th. W. E. B. DuBois and Martin Luther King, Jr. separately emphasized that racially separate instruction by teachers who believe in their students' capacities would be better than racially-mixed instruction by teachers who disparaged African-American children - but integration would be still better. Opposition to court-ordered desegregation remedies and judicial retreat occurred just as approval of racial mixing and even integration succeeded as cultural and political ideals. Current educational wisdom identifies strategies for equal educational opportunity apart from integration. These include curricular and academic supports that demand high standards, prepare minority students to achieve in a sometimes hostile world, and craft for each student the social identity of an achiever who is a member of a community of learners. Focused school reforms aligning the curriculum with standards, more "time-on-task" with longer school days, initiatives to recruit and support effective teachers, and shifts in school finance guided by standards of adequate education and comparable opportunities can mitigate the disparities still associated with racially distinct school communities. But as even the good arguments for socioeconomic integration reveal, failure to pursue racial integration - including efforts to create truly inclusive communities of mutual respect - can recreate racial segregation through tracking, special education assignments, and students' own divisions in lunch tables and cliques. Racial integration informed by the demographic changes making this a multicultural and multi-racial society remains a distinctive goal apart from other efforts to ensure equal educational opportunities. Justice Kennedy's separate opinion in Parents Involved in Community Schools v. Seattle School District No. 1 along with the four dissenters create a fragile majority that would permit school systems and housing developers to local schools with the aim of encouraging racial integration, to develop programs designed to attract racially diverse groups of students, and to hold meetings and recruitment efforts to attract diverse groups of students and teachers. Contrary to the Court's majority opinion, pretending to have achieved color-blind as well as open opportunity - when we have not - disables individuals and communities from understanding what is going on and from becoming equipped to deal with it. In addition to the strategies for integration left open, families and students can choose integrated schools by their residential choices and by making their own lives look like the high-concept ads celebrating integration

Coordinated Machine Learning and Decision Support for Situation Awareness

For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator\u27s input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario

Creating restoration landscapes: partnerships in large-scale conservation in the UK

It is increasingly recognized that ecological restoration demands conservation action beyond the borders of existing protected areas. This requires the coordination of land uses and management over a larger area, usually with a range of partners, which presents novel institutional challenges for conservation planners. Interviews were undertaken with managers of a purposive sample of large-scale conservation areas in the UK. Interviews were open-ended and analyzed using standard qualitative methods. Results show a wide variety of organizations are involved in large-scale conservation projects, and that partnerships take time to create and demand resilience in the face of different organizational practices, staff turnover, and short-term funding. Successful partnerships with local communities depend on the establishment of trust and the availability of external funds to support conservation land uses. We conclude that there is no single institutional model for large-scale conservation: success depends on finding institutional strategies that secure long-term conservation outcomes, and ensure that conservation gains are not reversed when funding runs out, private owners change priorities, or land changes hands

A new class of neural architectures to model episodic memory : computational studies of distal reward learning

A computational cognitive neuroscience model is proposed, which models episodic memory based on the mammalian brain. A computational neural architecture instantiates the proposed model and is tested on a particular task of distal reward learning. Categorical Neural Semantic Theory informs the architecture design. To experiment upon the computational brain model, embodiment and an environment in which the embodiment exists are simulated. This simulated environment realizes the Morris Water Maze task, a well established biological experimental test of distal reward learning. The embodied neural architecture is treated as a virtual rat and the environment it acts in as a virtual water tank. Performance levels of the neural architectures are evaluated through analysis of embodied behavior in the distal reward learning task. Comparison is made to biological rat experimental data, as well as comparison to other published models. In addition, differences in performance are compared between the normal and categorically informed versions of the architecture

Fuzzy neural network pattern recognition algorithm for classification of the events in power system networks

This dissertation introduces advanced artificial intelligence based algorithm for detecting and classifying faults on the power system transmission line. The proposed algorithm is aimed at substituting classical relays susceptible to possible performance deterioration during variable power system operating and fault conditions. The new concept relies on a principle of pattern recognition and detects the existence of the fault, identifies fault type, and estimates the transmission line faulted section. The approach utilizes self-organized, Adaptive Resonance Theory (ART) neural network, combined with fuzzy decision rule for interpretation of neural network outputs. Neural network learns the mapping between inputs and desired outputs through processing a set of example cases. Training of the neural network is based on the combined use of unsupervised and supervised learning methods. During training, a set of input events is transformed into a set of prototypes of typical input events. During application, real events are classified based on the interpretation of their matching to the prototypes through fuzzy decision rule. This study introduces several enhancements to the original version of the ART algorithm: suitable preprocessing of neural network inputs, improvement in the concept of supervised learning, fuzzyfication of neural network outputs, and utilization of on-line learning. A selected model of an actual power network is used to simulate extensive sets of scenarios covering a variety of power system operating conditions as well as fault and disturbance events. Simulation results show improved recognition capabilities compared to a previous version of ART neural network algorithm, Multilayer Perceptron (MLP) neural network algorithm, and impedance based distance relay. Simulation results also show exceptional robustness of the novel ART algorithm for all operating conditions and events studied, as well as superior classification capabilities compared to the other solutions. Consequently, it is demonstrated that the proposed ART solution may be used for accurate, high-speed distinction among faulted and unfaulted events, and estimation of fault type and fault section