Neural Structures Using the Eigenstates of a Quantum Harmonic Oscillator

The main result of the paper is the use of orthogonal Hermite polynomials as the basis functions of feedforward neural networks. The proposed neural networks have some interesting properties: (i) the basis functions are invariant under the Fourier transform, subject only to a change of scale, (ii) the basis functions are the eigenstates of the quantum harmonic oscillator, and stem from the solution of Schrödinger's diffusion equation. The proposed feed-forward neural networks demonstrate the particle-wave nature of information and can be used in nonparametric estimation. Possible applications of the proposed neural networks include function approximation, image processing and system modelling.     

Assessment of the flexural capacity of RC beam/column elements allowing for 3d effects

The paper describes an experimental investigation of the deformational response and the stress conditions developing in the compressive zone of reinforced concrete beam-like structural elements in bending and bending combined with axial force. The results obtained confirm the findings of earlier work and demonstrate that the compressive zone at its ultimate-limit state is characterised by the development of triaxial rather than uniaxial-as widely considered-stress conditions. These findings form the basis for introducing a simple modification in the method currently used for calculating flexural capacity and it is shown that, by complementing the proposed method with an approach that takes into account the effect of yielding of the compression reinforcement on structural behaviour, it is possible to achieve predictions of flexural capacity which are considerably closer to experimentally established values than the values obtained through the use of currently adopted methods.     

Extended Kalman and Particle Filtering for sensor fusion in motion control of mobile robots

Motion control of mobile robots and efficient trajectory tracking is usually based on prior estimation of the robots’ state vector. To this end Gaussian and nonparametric filters (state estimators from position measurements) have been developed. In this paper the Extended Kalman Filter which assumes Gaussian measurement noise is compared to the Particle Filter which does not make any assumption on the measurement noise distribution. As a case study the estimation of the state vector of a mobile robot is used, when measurements are available from both odometric and sonar sensors. It is shown that in this kind of sensor fusion problem the Particle Filter has better performance than the Extended Kalman Filter, at the cost of more demanding computations.     

Stability conditions and numerical solutions on oscillatory thermoviscous shearing

We study the analytical and numerical behaviour of the adiabatic shearing flow of an incompressible Newtonian liquid with temperature-dependent viscosity, under a time-periodic boundary velocity. We give sufficient stability conditions for the solution of the governing balance and constitutive equations and we present numerical results for the asymptotic convergence of the flow. Essentially, we verify that the stress decays to a time oscillatory function while the temperature exhibits a strongly non-uniform distribution with its maximum value tending to infinity with time.     

Fuzzy stochastic automata for intelligent vehicle control

Fuzzy stochastic automata (FSA) are proposed for the control of autonomous vehicles. FSA merge the concept of sliding-mode control with fuzzy logic and have interesting robustness properties. Sufficient conditions for the convergence of the FSA control are provided.     

Development and testing of a high precision digital Gaussian generator for Computers

A high precision generator of Gaussian distributed pseudorandom numbers has been developed and tested. The generator is designed so that to be suitable for use with computers in simulation applications. Experimental results are given which verify the theoretically predicted performance. The generator approximates with high accuracy the tails of the Gaussian density and this makes it suitable for simulations of rare events. Depending on the system parameters the originally generated densities can be produced in a form which allows computer scaling without affecting the accuracy over a range of more than $\text{+5}$ standard deviations from the mean.     

Highly Efficient,Bright, and Stable Colloidal Quantum Dot Short‐Wave Infrared Light‐Emitting Diodes

Unbalanced charge injection is deleterious for the performance of colloidal quantum dot (CQD) light‐emitting diodes (LEDs) as it deteriorates the quantum efficiency, brightness, and operational lifetime. CQD LEDs emitting in the infrared have previously achieved high quantum efficiencies but only when driven to emit in the low‐radiance regime. At higher radiance levels, required for practical applications, the efficiency decreased dramatically in view of the notorious efficiency droop. Here, a novel methodology is reported to regulate charge supply in multinary bandgap CQD composites that facilitates improved charge balance. The current approach is based on engineering the energetic potential landscape at the supra‐nanocrystalline level that has allowed to report short‐wave infrared PbS CQD LEDs with record‐high external quantum efficiency in excess of 8%, most importantly, at a radiance level of ≈5 W sr^?1 m², an order of magnitude higher than prior reports. Furthermore, the balanced charge injection and Auger recombination reduction has led to unprecedentedly high operational stability with radiance half‐life of 26 068 h at a radiance of 1 W sr^?1 m^?2.     

MoS2–HgTe Quantum Dot Hybrid Photodetectors beyond 2 µm

Mercury telluride (HgTe) colloidal quantum dots (CQDs) have been developed as promising materials for the short and mid‐wave infrared photodetection applications because of their low cost, solution processing, and size tunable absorption in the short wave and mid‐infrared spectrum. However, the low mobility and poor photogain have limited the responsivity of HgTe CQD‐based photodetectors to only tens of mA W^?1. Here, HgTe CQDs are integrated on a TiO₂ encapsulated MoS₂ transistor channel to form hybrid phototransistors with high responsivity of ≈10⁶ A W^?1, the highest reported to date for HgTe QDs. By operating the phototransistor in the depletion regime enabled by the gate modulated current of MoS₂, the noise current is significantly suppressed, leading to an experimentally measured specific detectivity D* of ≈10¹² Jones at a wavelength of 2 µm. This work demonstrates for the first time the potential of the hybrid 2D/QD detector technology in reaching out to wavelengths beyond 2 µm with compelling sensitivity.