Towards a Mirror System for the Development of Socially-Mediated Skills

We present a system that attempts to model the functional role of mirror neurons, namely the activation of structures in response to both the observation of a demonstrated task, and its generation. Through social situatedness and a set of innate skills, perceptual and motor structures develop for recognition and reproduction of demonstrated actions. We believe this is an implementation towards a mirror system, and we test it on two platforms, one in simulation involving imitation of object interactions, the second on a physical robot learning from a human to follow walls

Car Depreciation

Every businessperson is concerned about his or her taxable deductions. Depreciation is one of those deductions. Depreciation is the reasonable allowance deducted every year for the exhaustion and wear and tear as property becomes obsolete.\u27 In 1988, there are many depreciation methods in use. A businessperson must be familiar with all of these methods in order to be able to be in full compliance with the tax law. The average businessperson is in awe of the tax code and will more than likely call up on a qualified tax professional to do his or her taxes. The accountant, CPA, or tax attorney must be knowledgeable of the changes in the tax law. When a new client comes in, however, it is difficult for a professional to know how a prior professional treated the depreciation of an asset

A Weighted Maximum Entropy Language Model for Text Classification

Abstract. The Maximum entropy (ME) approach has been extensively used for various natural language processing tasks, such as language modeling, part-of-speech tagging, text segmentation and text classification. Previous work in text classification has been done using maximum entropy modeling with binary-valued features or counts of feature words. In this work, we present a method to apply Maximum Entropy modeling for text classification in a different way it has been used so far, using weights for both to select the features of the model and to emphasize the importance of each one of them in the classification task. Using the X square test to assess the contribution of each candidate feature from the obtained X square values we rank the features and the most prevalent of them, those which are ranked with the higher X square scores, they are used as the selected features of the model. Instead of using Maximum Entropy modeling in the classical way, we use the X square values to weight the features of the model and give thus a different importance to each one of them. The method has been evaluated on Reuters-21578 dataset for test classification tasks, giving very promising results and performing comparable to some of the "state of the art" systems in the classification field

Materials modelling and process simulation of the pultrusion of curved parts

The present paper addresses the simulation of a concept for the manufacturing of aerospace quality carbon/epoxy composite curved parts using pultrusion. In this approach, the part is first partially cured in a pre-former followed by final curing in a curved post-former. An aerospace epoxy resin system has been fully characterised and the corresponding constitutive material models, incorporating dependence on both temperature and degree of cure, developed. A 3D Finite Element model of the process, to manufacture a T-stiffener, involving impregnation, curing and forming of the curvature was developed and implemented. The simulation results show that a degree of cure of around 62% -close to the gelation point of the resin system considered - at the exit of the pre-former stage is appropriate for the success of the subsequent stage. In the post-former the cure is completed reaching a final degree of cure of about 87%. The stresses generated in post-forming reach a maximum of 54 MPa in compression in the transverse direction and of 200 MPa in tension in the fibre direction showing that the process is feasible without inducing defects linked to micro buckling or rupture

In situ control of graphene oxide dispersions with a small impedance sensor

Abstract Carbon-based nanomaterials (CBNs), such as graphene and carbon nanotubes, display advanced physical and chemical properties, which has led to their widespread applications. One of these applications includes the incorporation of CBNs into cementitious materials in the form of aqueous dispersions. The main issue that arises in this context is that currently no established protocol exists as far as characterizing the dispersions. In the present article, an innovative method for quick evaluation and quantification of graphene oxide (GO) dispersions is proposed. The proposed method is electrical impedance spectroscopy (EIS) with an impedance sensor. The novelty lies on the exploitation of a small sensor for on-site (field) direct dielectric measurements with the application of alternating current. Five different concentrations of GO dispersions were studied by applying EIS and for various accumulated ultrasonic energies. The low GO concentration leads to high impedance values due to low formed current network. Two opposing mechanisms were revealed during the accumulation of ultrasonic energy, that are taking place simultaneously: breakage of the agglomerates that facilitates the flow of the electric current due to the formation of a better dispersed network, nevertheless the surface hydrophilic structure of the GO is damaged with the high accumulated ultrasonic energy. The dielectric measurements were exploited to express an appropriate quantitative ‘quality index’ to facilitate with the dispersion control of the nanostructures. An intermediate concentration of GO is suggested (about 0.15 wt% of the binder materials) to be optimal for the specific engineering application, ultrasonicated at approximately 30 to 65 kJ. The investigated methodology is highly novel and displays a high potential to be applied in-field applications where CBNs must be incorporated in building materials

Optimisation of an in-process lineal dielectric sensor for liquid moulding of carbon fibre composites

A dielectric sensor appropriate for process monitoring of carbon fibre composites manufacturing has been optimised and implemented in Resin Transfer Moulding (RTM). The sensor comprises a pair of twisted insulated copper wires and can be adapted to monitor both flow and cure. To simulate the dielectric response of the sensor, an electric field model was developed. The model was coupled with a multi-objective optimisation genetic algorithm to optimise the sensor design. The optimisation showed that increasing wire radius and decreasing coating thickness increases sensor sensitivity. Different sensor designs were implemented and used in a series of RTM trials to validate the technology in industrial conditions. The sensor operated successfully at pressures up to 7 bar and temperatures up to 180°C. A low diameter sensor using copper wire coated with polyimide showed the best response monitoring flow with an accuracy of 95%, whilst also following the cure and identifying vitrificatio

Modelling heat generation and transfer during cure of thermoset composites processed by resin transfer moulding (RTM)

The development of a heat transfer model for the curing stage of the RTM process is presented. Despite the intense interest in the modelling and simulation of this process the relevant work is currently limited to development of flow models of the filling stage. The principles of heat transfer modelling of composites cure have already been reported and applied to the autoclave process by many investigators. In the present investigation, the same concept is used for the implementation of Galerkin finite element approach to RTM curing. The mathematical basis of the resulting semidiscrete model is presented here and the temporal algorithm is described. The experimental mould, which will be used to evaluate and validate the model is also described

Dielectric monitoring during the cure of epoxy resin blends

Dielectric monitoring and supporting techniques (differential Scanning calorimetry, infra-red spectrosoopy, viscometry, dynamic mechanical thermal analysis and light transmittance) were used to study the isothermal cure reaction of the CTBN rubber modified DGEBA resin/amine hardener blends. The neat system was also examined for the required knowledge of the matrix properties. The complexity of the cure kinetics was demonstrated by the use of a rapid technique for kinetic parameters evaluation. The utility of the dielectric cure monitoring is focused at the observation of evidence o phase separation, gelation and vitrification. The phase separatlon which the blends underwent during the cure was detected by the dielectric »monitoring through a permittivity increase at the low frequency response. The onset of the rapid viscosity increase leading to gelation was also indicated by the sharp decrease o the dielectric constant atlhigh frequencies. The frequency dependence of the times reach the dielectric loss peaks was used to predict successfully the vitrification times during the isothermal reactions o the blends. The in-situ nature o the technique and the basic understanding o the features appearing in the dielectric signal during the cure reaction provide the basis for the use of dielectric monitoring in the process of composite materials, manufacture