Binary Willshaw learning yields high synaptic capacity for long-term familiarity memory

We investigate from a computational perspective the efficiency of the Willshaw synaptic update rule in the context of familiarity discrimination, a binary-answer, memory-related task that has been linked through psychophysical experiments with modified neural activity patterns in the prefrontal and perirhinal cortex regions. Our motivation for recovering this well-known learning prescription is two-fold: first, the switch-like nature of the induced synaptic bonds, as there is evidence that biological synaptic transitions might occur in a discrete stepwise fashion. Second, the possibility that in the mammalian brain, unused, silent synapses might be pruned in the long-term. Besides the usual pattern and network capacities, we calculate the synaptic capacity of the model, a recently proposed measure where only the functional subset of synapses is taken into account. We find that in terms of network capacity, Willshaw learning is strongly affected by the pattern coding rates, which have to be kept fixed and very low at any time to achieve a non-zero capacity in the large network limit. The information carried per functional synapse, however, diverges and is comparable to that of the pattern association case, even for more realistic moderately low activity levels that are a function of network size.Comment: 20 pages, 4 figure

INTEGRATED DESIGN OF A LIGHTWEIGHT POSITIONING SYSTEM

Abstract In this paper a new approach to the design of positioning systems is introduced. The approach aims at the design of fast and accurate systems that are lightweight compared to classical designs. The new design reduces peak power requirements and thermal effects that deteriorate performance of the whole system

Increased fracture rate in women with breast cancer: a review of the hidden risk

Women with breast cancer, particularly individuals diagnosed at a relatively early age, have an increased incidence of fractures. Fractures can have serious clinical consequences including the need for major surgery, increased morbidity and mortality, increased cost of disease management, and reduced quality of life for patients. The primary cause of the increased fracture risk appears to be an accelerated decrease in bone mineral density (BMD) resulting from the loss of estrogenic signaling that occurs with most treatments for breast cancer, including aromatase inhibitors. However, factors other than BMD levels alone may influence treatment decisions to reduce fracture risk in this setting. Our purpose is to review current evidence for BMD loss and fracture risk during treatment for breast cancer and discuss pharmacologic means to reduce this risk.Journal ArticleResearch Support, Non-U.S. Gov'tReviewSCOPUS: re.jinfo:eu-repo/semantics/publishe

Mixed control for discrete-time systems via convex optimization,

A mixed control problem for discrete-time systems is considered, where an upper bound on the norm of a closed loop transfer matrix is minimized subject to an constraint on another closed loop transfer matrix. Both state-feedback and output-feedback cases are considered. It is shown that these problems are equivalent to finite-dimensional convex programming problems. In the state-feedback case, nearly optimal controllers can be chosen to be static gains. In the output feedback case, nearly optimal controllers can be chosen to have a structure similar to that of the central single objective controller. In particular, the state dimension of nearly optimal output-feedback controllers need not exceed the plant dimension.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31038/1/0000715.pd

Precision engineering : from pre-polishing to deep-hole drilling

Cranfield University designs and produces top-of-the-art precision machines for machining, grinding and polishing, but they use commercial machines as well. One of its specialties is producing precision optics, but projects in other fields are not uncommon. This traineeship involves measurement of static and dynamic responses of a low cost robot based equipment towards implementation instrumentations required for a smoothing process. Steps towards automatic measurement and error compensation programs have been made. Another subject of this traineeship involves designing an in situ measurement device that can measure the straightness of a deep-drilled-hole with a diameter of 25 mm within at least 6 arc second (about 30 ??m/m) over a length of 3 m of which a detailed design is presented

Disturbance rejection in diesel engines for low emissions and high fuel efficiency

This brief presents a novel and time-efficient control design for modern heavy-duty diesel engines using a variable geometry turbine and an exhaust gas recirculation valve. The goal is to simultaneously and robustly achieve low fuel consumption and low emissions of nitrogen oxides (NOx) and particulate matter (PM). A new combination of three controlled outputs is used: 1) specific engine-out NOx emissions; 2) air-fuel equivalence ratio; and 3) the pressure difference between intake and exhaust manifold, which reflect NOx and PM emissions and fuel efficiency, respectively. It is shown that this combination allows for effective disturbance rejection and results in a well-conditioned system. An underactuated input-output system is formed, for which a linear feedback controller is designed. In addition to this feedback controller, a feedforward controller is implemented, which improves the torque response and lowers the PM emissions during fast changes in torque demand. The combined control system is suitable for the full range of speed and load variations. This new controller is tested experimentally on a modern heavy-duty engine running a hot world harmonized transient cycle and compared with a baseline controller. The new controller reduces the NOx and PM emissions by 3.9% and 11.7%, respectively, without a fuel penalty

Energy management strategies for vehicular electric power systems

In the near future, a significant increase in electric power consumption in vehicles is expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storage/retrieval, distribution, and consumption of electric power will be used. Inspired by the research on energy management for hybrid electric vehicles (HEVs), this paper presents an extensive study on controlling the vehicular electric power system to reduce the fuel use and emissions, by generating and storing electrical energy only at the most suitable moments. For this purpose, both off-line optimization methods using knowledge of the driving pattern and on-line implementable ones are developed and tested in a simulation environment. Results show a reduction in fuel use of 2%, even without a prediction of the driving cycle being used. Simultaneously, even larger reductions of the emissions are obtained. The strategies can also be applied to a mild HEV with an integrated starter alternator (ISA), without modifications, or to other types of HEVs with slight changes in the formulation