The paper introduces a novel coevolutionary approach (CoEvoSG) for solving Sequential Stackelberg Security Games. CoEvoSG maintains two competing populations of players’ strategies. In the process inspired by biological evolution both populations ...

Simulations of the microvasculature can elucidate the effects of various blood flow parameters on micro-scale cellular and fluid phenomena. At this scale, the non-Newtonian behavior of blood requires the use of explicit cell models, which are ...

Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent flow. Solving both systems simultaneously is computationally prohibitive. Instead, given the difference in scales at which the two sub–systems ...

Data-flow computing is a natural and convenient paradigm for expressing parallelism. This is particularly true for tools that automatically extract the data dependencies among the tasks while allowing to exploit both distributed and shared memory ...

Rapid progress in machine learning (ML) and artificial intelligence (AI) has brought increased attention to the potential vulnerability and reliability of AI technologies. To counter this issue a multitude of methods has been proposed. Most of ...

The human face contains important information enabling the social identification of the owner about the age and gender. In technical systems, the face contains a number of important information that enables the identification of a person. The ...

The aim of this paper is to investigate the applicability of language models to the problem of lexical substitution in a strongly inflected language. For this purpose, we focus on pre-trained models based on transformer architectures, in ...

QR factorization of dense matrices is a ubiquitous tool in high performance computing (HPC). From solving linear systems and least squares problems to eigenvalue problems, and singular value decompositions, the impact of a high performance QR ...

This paper examines whether the probability of default (Merton 1974) can be applied to banks’ default predictions. Using the case of US banks in the post-crisis period (2010–2014), we estimate several Cox proportional hazard models as well as ...

In the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, ...

The term ‘privacy paradox’ refers to the apparent inconsistency between people’s concerns about their privacy and their actual privacy behaviour. Although several possible explanations for this phenomenon have been provided so far, these assume ...

A bond-based peridynamic damage model is proposed to incorporate the deformation and the damage process into a unified framework. This new model is established based on absolute bond elongation, and both the elastic and damage parameters of the ...

The root-finding problem is very important in many applications and has become an extensive research field. One of the directions in this field is the use of various iteration schemes. In this paper, we propose a new generalised iteration scheme. ...

QUIC-Fire is a modern fire simulation tool that can simulate the progression of three-dimensional fuel consumption over a landscape, modeling the interaction of a wildfire with weather such as wind conditions around the wildfire. The resulting ...

Cyberbullying is an aggressive and intentional behavior committed by groups or individuals, and its main manifestation is to make offensive or hurtful comments on social media. The existing researches on cyberbullying detection underuse natural ...

The expansion of modern supply chains constantly triggers the need of maintaining resilience and agility for higher profit. There is a need to change the standard methods of inventory control to new approaches that are highly adaptable to ...

The stock market is a complex network that consists of individual stocks exhibiting various financial properties and different data distribution. For stock prediction, it is natural to build separate models for each stock but also consider the ...

We propose a method for dynamic classification of bank clients by the predictability of their transactional behavior (with respect to the chosen prediction model, quality metric, and predictability measure). The method adopts incremental learning ...

Event extraction is a key task of information extraction. Existing methods are not effective due to two challenges of this task: 1) Most of previous methods only consider a single granularity information and they are often insufficient to ...

The need to analyze information from streams arises in a variety of applications. One of its fundamental research directions is to mine sequential patterns over data streams. Current studies mine series of items based on the presence of the ...