Search

Bitcoin is the first implementation of what has become known as a 'publicpermissionless' blockchain. Guaranteeing security and protocol conformitythrough its elegant combination of cryptographic assurances and game theoreticeconomic incentives, it permits censorship resistant public read-write...

An accurate modelling of bio-electrochemical processes that govern MicrobialFuel Cells (MFCs) and mapping their behaviour according to several parameterswill enhance the development of MFC technology and enable their successfulimplementation in well defined applications. The geometry of the...

The article describes information model and the method for searching patentanalogs for Personal Research Information System.

In this paper, two image encryption schemes are proposed for grayscale andcolor images. The two encryption schemes are based on dividing each image intoblocks of different sizes. In the first scheme, the two dimension ($2$D) inputimage is divided into various blocks of size $N \times N$. Each block...

Purpose: Interventions at the otobasis operate in the narrow region of thetemporal bone where several highly sensitive organs define obstacles withminimal clearance for surgical instruments. Nonlinear trajectories forpotential minimally-invasive interventions can provide larger distances to...

Detectability is a basic property of dynamic systems: when it holds one canuse the observed output signal produced by a system to reconstruct its currentstate.In this paper, we consider properties of this type in the framework ofdiscrete event systems modeled by Petri nets (a.k.a. place/transition...

This article continues the investigation started in [9] on subdivisionschemes refining 2D point-normal pairs, obtained by modifying linearsubdivision schemes using the circle average. While in [9] the convergence ofthe Modified Lane-Riesenfeld algorithm and the Modified 4-Point schemes isproved...

In times of more and more complex interaction techniques, we point out thepowerfulness of colored light as a simple and cheap feedback mechanism. Sinceit is visible over a distance and does not interfere with other modalities, itis especially interesting for mobile robots. In an online survey, we...

Recommender systems rely heavily on the predictive accuracy of the learningalgorithm. Most work on improving accuracy has focused on the learningalgorithm itself. We argue that this algorithmic focus is myopic. Inparticular, since learning algorithms generally improve with more and betterdata, we...

There is an undeniable communication barrier between deaf people and peoplewith normal hearing ability. Although innovations in sign language translationtechnology aim to tear down this communication barrier, the majority ofexisting sign language translation systems are either intrusive or...

One of the biggest problems in deep learning is its difficulty to retainconsistent robustness when transferring the model trained on one dataset toanother dataset. To conquer the problem, deep transfer learning was implementedto execute various vision tasks by using a pre-trained deep model in a...

Batch normalization was introduced in 2015 to speed up training of deepconvolution networks by normalizing the activations across the current batch tohave zero mean and unity variance. The results presented here show aninteresting aspect of batch normalization, where controlling the shape of...

There are many practical applications based on the Least Square Error (LSE)approximation. It is based on a square error minimization 'on a vertical' axis.The LSE method is simple and easy also for analytical purposes. However, ifdata span is large over several magnitudes or non-linear LSE is used...

Here we show how reversible computation processes, like Margolus diffusion,can be envisioned as physical turning operations on a 2-dimensional rigidsurface that is cut by a regular pattern of intersecting circles. We thenbriefly explore the design-space of these patterns, and report on the...

The top-k error is a common measure of performance in machine learning andcomputer vision. In practice, top-k classification is typically performed withdeep neural networks trained with the cross-entropy loss. Theoretical resultsindeed suggest that cross-entropy is an optimal learning objective for...

In this paper, we propose a new design method of irregular spatially-coupledlow-density paritycheck (SC-LDPC) codes with non-uniform degree distributionsby linear programming (LP). In general, irregular SC-LDPC codes withnon-uniform degree distributions is difficult to design with low...

A sliding window algorithm receives a stream of symbols and has to output ateach time instant a certain value which only depends on the last $n$ symbols.If the algorithm is randomized, then at each time instant it produces anincorrect output with probability at most $\epsilon$, which is a constant...

This work focuses on the development of a non-conforming domain decompositionmethod for the approximation of PDEs based on weakly imposed transmissionconditions: the continuity of the global solution is enforced by a discretenumber of Lagrange multipliers defined over the interfaces of...

In many scenarios we need to find the most likely program under a localcontext, where the local context can be an incomplete program, a partialspecification, natural language description, etc. We call such problem programestimation. In this paper we propose an abstract framework, learning...

We investigate data-enriched models, like Petri nets with data, whereexecutability of a transition is conditioned by a relation between data valuesinvolved. Decidability status of various decision problems in such models maydepend on the structure of data domain. According to the WQO...