ARTMAP: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-Organizing Neural Network

This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.

Chemical gas sensors based on functionalized self-actuated piezo-resistive cantilevers

Der Schwerpunkt dieser Arbeit liegt in der Anwendung funktionalisierter Mikrocantilever mit integrierter bimorpher Aktuation und piezo-resistiver Detektion als chemische Gassensoren für den schnellen, tragbaren und preisgünstigen Nachweis verschiedener flüchtiger Substanzen. Besondere Beachtung erfährt die Verbesserung der Cantilever-Arbeitsleistung durch den Betrieb in speziellen Modi. Weiterer Schwerpunkt liegt in der Untersuchung von spezifischen Sorptionswechselwirkungen und Anwendung von innovativen Funktionsschichten, die bedeutend auf die Sensorselektivität wirken.

Norepinephrine ignites local hot spots of neuronal excitation: how arousal amplifies selectivity in perception and memory

Arousal sometimes enhances and sometimes impairs perception and memory. In our Glutamate Amplifies Noradrenergic Effects (GANE) model, glutamate at active synapses interacts with norepinephrine released by the locus coeruleus to create local ‘hot spots’ of activity that enable the selective effects of arousal. This hot spot mechanism allows local cortical regions to self-regulate norepinephrine release based on current activation levels. In turn, hot spots bias global energetic delivery and functional network connectivity to enhance processing of high priority representations and impair processing of lower priority representations.

Stepwise synthesis of Gly−Gly−His on gold surfaces modified with mixed self-assembled monolayers

Peptide-modified electrode surfaces have been shown to have excellent recognition properties for metal ions. An efficient method of screening a potential peptide for its selectivity for a given metal would involve the synthesis of the peptide directly on the electrode surface. This paper outlines a procedure in which the tripeptide Gly−Gly−His was synthesized one amino acid at a time on a gold surface modified with a self-assembled monolayer of the mixed alkanethiolates 3-mercaptopropionic acid (MPA) and 3-mercaptopropane (MP). Electrochemistry and high-resolution mass spectrometry were used to elucidate the structure of the adsorbed species and follow the synthesis. The amino acids can be attached only to MPA, but the presence of a diluting unreactive molecule of MP reduces steric crowding about the reaction center. The maximum coverage of synthesized tripeptide occurs at a ratio of MPA/MP of 1:1.

The facet selectivity of inorganic ions on silver nanocrystals in etching reactions

The facet selectivity of the halide ions and chlorauric acid for several shaped silver nanocrystals is presented in this paper. Two inorganic ions show different representations when they are used for etching silver nanocrystals in the self-sacrificial template reaction. The morphological changes of the silver nanocrystals indicate that the halide ions prefer to etch the (110) facets of silver nanocrystals, while in the chlorauric acid etching reaction, gold first modifies the (110) facets and then lets chlorauric acid etch the (111) facets instead. The selective facet etching on individual nanoparticles in the solution phase has crucial significance in the control-synthesis of nanocrystals and the facet asymmetric reaction.

Nanostructured screen-printed electrodes modified with self-assembled monolayers for determination of metronidazole in different matrices

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Toward Self-Organising Service Communities

This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.).