One of the most challenging tasks while designing an automotive electronic device is to take into account its whole electro-mechanic environment, so that time expensive failure tests can be reduced. We show a case study, developed in collaboration with an industrial partner, in which an automotive Compact Disk (CD) player is modelled. Using VHDL-AMS, not only its whole mixed-signal electro-mech...

Mechanic antennas provide opportunities for human portable, VLF communications, where a rotational dipole emits EM signals with angular momenta. In this paper we analytically derive the electromagnetic fields from electric using Fourier transform method, and find that radiated carries nonzero energy flow density in both orbital spin momentum (AM) parts by AM flux tensors. Intuitively, rotation ...

This study was done as a part of a larger research project where the interest was on exploring if and how gameplay design could give informative principles to the design of educational activities. The researchers conducted a series of studies trying to map game mechanics that had the special quality of being inclusive, i.e., playable by a diverse group of players. This specific study focused on...

Industrial wastes may produce leachates that can contaminate the aquatic ecosystem. Toxicity testing in acute and chronic levels is essential to assess environmental risks from the soluble fractions of these wastes, since only chemical analysis may not be adequate to classify the hazard of an industrial waste. In this study, ten samples of solid wastes from textile, metal-mechanic, and pulp and...

Differential evolution algorithm (DE) is one of the novel stochastic optimization methods. It has a better performance in the problem of the color image quantization, but it is difficult to set the parameters of DE for users. This paper proposes a color image quantization algorithm based on self-adaptive DE. In the proposed algorithm, a self-adaptive mechanic is used to automatically adjust the...

Recognizing Textual Entailment (RTE) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI1) corpus has made it possible to develop and evaluate deep neural network methods for the RTE task. Previous neural network based methods usually try to encode the two sentences and send them together in...