Use of Neural Network Based Prediction Algorithms for Powering Up Smart Portable Accessories

Neural Processing Letters - Emerging Trends in the use of smart portable accessories, particularly within the context of the Internet of Things (IoT), where smart sensor devices are employed for...     

Adaptive course generation through learning styles representation

This paper presents an approach to automatic course generation and student modeling. The method has been developed during the European funded projects Diogene and Intraserv, focused on the construction of an adaptive e-learning platform. The aim of the platform is the automatic generation and personalization of courses, taking into account pedagogical knowledge on the didactic domain as well as statistic information on both the student’s knowledge degree and learning preferences. Pedagogical information is described by means of an innovative methodology suitable for effective and efficient course generation and personalization. Moreover, statistic information can be collected and exploited by the system in order to better describe the student’s preferences and learning performances. Learning material is chosen by the system matching the student’s learning preferences with the learning material type, following a pedagogical approach suggested by Felder and Silverman. The paper discusses how automatic learning material personalization makes it possible to facilitate distance learning access to both able-bodied and disabled people. Results from the Diogene and Intraserv evaluation are reported and discussed.     

Finite element analysis of rotating flow in a skewed shrouded rotor geometry

The effect of slight shroud skewness on rotating flow in an enclosed rotor geometry is modelled as a perturbation about axisymmetric flow. Solutions are obtained by the finite element method. Mixed and penalty finite element formulation are employed.     

Characterization of Heat Treated Titanium-Based Implants by Nondestructive Eddy Current and Ultrasonic Tests

This study presents nondestructive characterization of microstructure and mechanical properties of heat treated Ti, Ti-Cu, and Ti-6Al-4V titanium-based alloys and 17-4 PH stainless steel alloy for biomedical implant applications. Ti, Ti-Cu, and 17-4 PH stainless steel based implants were produced by powder metallurgy. Ti-6Al-4V alloy was investigated as bulk wrought specimens. Effects of sintering temperature, aging, and grain size on mechanical properties were investigated by nondestructive and destructive tests comparatively. Ultrasonic velocity in specimens was measured by using pulse-echo and transmission methods. Electrical conductivity of specimens was determined by eddy current tests. Determination of Young’s modulus and strength is important in biomedical implants. Young’s modulus of specimens was calculated by using ultrasonic velocities. Calculated Young’s modulus values were compared and correlated with experimental values.     

Controlling of electronic parameters of GaAs Schottky diode by poly(3,4-ethylenedioxithiophene)-block-poly(ethylene glycol) organic interlayer

The electronic properties of metal-organic semiconductor-inorganic semiconductor structure between GaAs and poly(3,4-ethylenedioxithiophene)-block-poly(ethylene glycol) organic film have been investigated via current-voltage and capacitance-voltage methods. The Au/PEDOT/n-GaAs contact exhibits a rectification behavior with the barrier height of 0.69 eV and ideality factor value of 3.94. The barrier height of the studied diode (0.67 eV) is lower than that of Ni/n-GaAs/In (0.85 eV) and Au/n-GaAs/In Schottky diodes. The decrease in barrier height of Au/n-GaAs/In Schottky diode is likely to be due to the variation in the space charge region in the GaAs. The obtained results indicate that control of the interfacial potential barrier for metal/n-GaAs diode was achieved using thin interlayer of the poly(3,4-ethylenedioxithiophene)-block-poly(ethylene glycol).     

Soluble recombinant neutral endopeptidase (CD10) as a potential antiinflammatory agent

The present study assessed fidelity to the behavioral family management (BFM) model for treating bipolar disorder patients and their families. The BFM Therapist Competency/Adherence Scale (BFM-TCAS) was developed to evaluate clinicians' competency and adherence to BFM, as outlined by Miklowitz' (1989) BFM Manual for use with bipolar patients. Therapist competency and treatment adherence was also evaluated with regard to two family characteristics: overall level of family difficulty and family expressed emotion (EE) status. The BFM-TCAS was used to code 78 videotaped sessions of 26 families with a bipolar member, selected from a larger treatment study of bipolar disorder patients. The findings suggest that, overall, clinicians adhered closely to the BFM manual. Specific areas in which there was high competency and treatment adherence were (a) skill in conveying factual information about bipolar illness, (b) establishment of a therapeutic environment, and (c) ability to take command of therapy sessions. The one area in which there was less competency and relatively weak adherence to the manual was the use of between-session homework assignments to assist families in mastering the BFM exercises. Results of this study also suggest that, for the most part, therapist competency and adherence ratings were not related to overall level of difficulty or to family EE status.     

Anticipation of digital patterns

A memristive device is a novel passive device, which is essentially a resistor with memory. This device can be used for novel technical applications like neuromorphic computation. In this paper, we focus on anticipation—a capability of a system to decide how to react in an environment by predicting future states. Especially, we have designed an elementary memristive circuit for the anticipation of digital patterns, where this circuit is based on the capability of an amoeba to anticipate periodically occurring unipolar pulses. The resulting circuit has been verified by digital simulations and has been realized in hardware as well. For the practical realization, we have used an Ag‐doped TiO_2?x‐based memristive device, which has been fabricated in planar capacitor structures on a silicon wafer. The functionality of the circuit is shown by simulations and measurements. Finally, the anticipation of information is demonstrated by using images, where the robustness of this anticipatory circuit against noise and faulty intermediate information is visualized.