Microfluidic liquid actuation through ground-directed electric discharge

In this article, we present a new technique to actuate liquids in microchannels using ground-directed electric discharge generated by a portable corona device. When an electric discharge is applied, the air in the microchannel is ionized causing a change in the surface energy. The resulting change in the contact angle induces rapid liquid transport through the channel by capillary action. In contrast to established plasma treatment this method employs a ground electrode that guides the electric field. This approach enables rapid treatment of select microchannels and thus provides a means of real-time fluid actuation as opposed to simply a pretreatment process. Instantaneous fluid velocities show power-law dependence with time and fit theoretical models at a contact angle of 65°. Average fluid velocities are on the order of 5 cm/s, and thus channels on the order of 1-cm long are filled in ~0.2 s. To demonstrate the potential of this technique for integrated lab-on-a-chip applications, the method was employed in serpentine channel, for on-demand fluid routing, to initiate a mixing process, and through an on-chip integrated microelectrode.     

Introducing the Planar Laser-Induced Fluorescence Technique (PLIF) to Measure Mixing Time in Gas-Stirred Ladles

Metallurgical and Materials Transactions B - The planar laser-induced fluorescence (PLIF) technique was implemented to measure mixing time in a 1/17 water model of a 200-ton ladle furnace. The...     

A PC-based architecture for parameter analysis of vector-controlled induction motor drive

In this article a methodology for constructing a user interface for system control and data acquisition of a drive which is suitable for three-phase induction motors (3?IM) is presented. The entire hardware implementation is shown, including power and digital stages. Communication between the computer and the controller is engaged in order to enhance an analysis of power quality, adjust the controller parameters for tuning the flux and speed loops, and performance of the embedded algorithm. USB and Ethernet protocols have been put into operation in the user front-end because a high speed sample frequency is required in order to guarantee the real-time operation of the whole system. A software interface is developed using LabVIEW environment enabling features not only as filtering signals of phase voltage and current but also power spectrum measurements. Vector-controlled drive is programmed on a digital signal processor (DSP) in order to ensure efficient use of energy in the power stage and proper tracking of the reference at low and high speeds.     

Learning SO(3) Equivariant Representations with Spherical CNNs

International Journal of Computer Vision - We address the problem of 3D rotation equivariance in convolutional neural networks. 3D rotations have been a challenging nuisance in 3D classification...     

Density-driven flow and solute transport problems. A 2-D numerical model based on the network simulation method

The network simulation method, based on the formal equivalence between physical systems and electrical networks, solves numerical problems of relatively mathematical complexity in a versatile, efficient and computationally fast way. In this paper, the method is applied for the first time to the design of a general purpose model for simulating two-dimensional transient density-driven flow and solute transport through porous media, a mathematical model made up by coupled, nonlinear differential equations. Using the Boussinesq approximation and the stream function formulation, the model is used to solve two typical problems related with groundwater flows. Isochlor concentration and stream function curves are presented and successfully compared with those of other authors. Simulation is carried out using the digital computer program Pspice with relatively low computing times.     

Simulation-based sequential analysis of Markov switching stochastic volatility models

We propose a simulation-based algorithm for inference in stochastic volatility models with possible regime switching in which the regime state is governed by a first-order Markov process. Using auxiliary particle filters we developed a strategy to sequentially learn about states and parameters of the model. The methodology is tested against a synthetic time series and validated with a real financial time series: the IBOVESPA stock index (São Paulo Stock Exchange).     

An agent-based genetic algorithm for hybrid flowshops with sequence dependent setup times to minimise makespan

This paper deals with a variant of flowshop scheduling, namely, the hybrid or flexible flowshop with sequence dependent setup times. This type of flowshop is frequently used in the batch production industry and helps reduce the gap between research and operational use. This scheduling problem is NP-hard and solutions for large problems are based on non-exact methods. An improved genetic algorithm (GA) based on software agent design to minimise the makespan is presented. The paper proposes using an inherent characteristic of software agents to create a new perspective in GA design. To verify the developed metaheuristic, computational experiments are conducted on a well-known benchmark problem dataset. The experimental results show that the proposed metaheuristic outperforms some of the well-known methods and the state-of-art algorithms on the same benchmark problem dataset.     

Disassembly sequence planning in a disassembly cell context

In this paper a two-phase approach is proposed for determining the optimal disassembly sequence when the disassembly system has a cellular configuration. Operations are first grouped into cells based on the resources they require with the goal of minimizing machine acquisition costs. The aim is to group together those operations that use similar equipment in order to achieve good utilization levels of such equipment. A maximum cell size may be imposed. Once the cells have been formed and the operations have been assigned to them, a metaheuristic algorithm (namely GRASP) is used to search for the disassembly sequence for each product that leads to the minimum number of intercellular movements. To account for uncertainty regarding the condition in which the product may arrive, each disassembly task is assumed to be required with a certain probability, regardless of the other tasks. AND/OR precedence relations among the disassembly tasks are also considered. The proposed approach is illustrated on a randomly generated disassembly problem.