Search results for "Theoretical Computer Science"

A multi-step finite-state automaton for arbitrarily deterministic Tsetlin Machine learning

2021

How Low Can Approximate Degree and Quantum Query Complexity Be for Total Boolean Functions?

2012

It has long been known that any Boolean function that depends on n input variables has both degree and exact quantum query complexity of Omega(log n), and that this bound is achieved for some functions. In this paper we study the case of approximate degree and bounded-error quantum query complexity. We show that for these measures the correct lower bound is Omega(log n / loglog n), and we exhibit quantum algorithms for two functions where this bound is achieved.

Equivalence closure in the two-variable guarded fragment

2015

We consider the satisfiability and finite satisfiability problems for the extension of the two-variable guarded fragment in which an equivalence closure operator can be applied to two distinguished binary predicates. We show that the satisfiability and finite satisfiability problems for this logic are 2-ExpTime-complete. This contrasts with an earlier result that the corresponding problems for the full two-variable logic with equivalence closures of two binary predicates are 2-NExpTime-complete.

[Editorial] Special issue on computational intelligence and nature-inspired algorithms for real-world data analytics and pattern recognition

2018

Cagnoni, S., & Castelli, M. (2018). [Editorial]. Special issue on computational intelligence and nature-inspired algorithms for real-world data analytics and pattern recognition. Algorithms, 11(3), 1-2. DOI: 10.3390/a11030025 This special issue of Algorithms is devoted to the study of Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition. The special issue considered both theoretical contributions able to advance the state-of-the-art in this field and practical applications that describe novel approaches for solving real-world problems. published

Learning Automata-based Misinformation Mitigation via Hawkes Processes

2021

AbstractMitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint ra…

Secure random number generation in wireless sensor networks

2014

The increasing adoption of wireless sensor networks as a flexible and inexpensive tool for the most diverse applications, ranging from environmental monitoring to home automation, has raised more and more attention to the issues related to the design of specifically customized security mechanisms. The scarcity of computational, storage, and bandwidth resources cannot definitely be disregarded in such context, and this makes the implementation of security algorithms particularly challenging. This paper proposes a security framework for the generation of true random numbers, which are paramount as the core building block for many security algorithms; the intrinsic nature of wireless sensor no…

Seeking Information on Social Commerce: An Examination of the Impact of User- and Marketer-generated Content Through an Eye-tracking Study

2021

Following the growing popularity of social commerce sites, there is an increased interest in understanding how consumers decide what products to purchase based on the available information. Consumers nowadays are confronted with the task of assessing marketer-generated (MGC) as well as user-generated information (UGC) in a range of different forms to make informed purchase-related decisions. This study examines the information types and forms that influence consumers in their decision-making process on social commerce. Building on uses and gratifications and dual-process theories, we distinguish between marketer and user generated content, and differentiate formats into informational and no…

An optimized mass storage FFT for vector computers

1995

Abstract The performance of a segmented FFT algorithm which allows the out-of-core computation of the Fourier transform of a very large mass storage data array is presented. The code is particularly optimized for vector computers. Tests performed mainly on a CONVEX C210 vector computer showed that, for very long transforms, tuning of the main parameters involved leads to computation speed and global efficiency better than for FFTs performed in-core. The use of tunable parameters allows optimization of the algorithm on machines with different configurations.

SAUCE: A web application for interactive teaching and learning of parallel programming

2017

Abstract Prevalent hardware trends towards parallel architectures and algorithms create a growing demand for graduate students familiar with the programming of concurrent software. However, learning parallel programming is challenging due to complex communication and memory access patterns as well as the avoidance of common pitfalls such as dead-locks and race conditions. Hence, the learning process has to be supported by adequate software solutions in order to enable future computer scientists and engineers to write robust and efficient code. This paper discusses a selection of well-known parallel algorithms based on C++11 threads, OpenMP, MPI, and CUDA that can be interactively embedded i…

Analyzing the performance of a cluster-based architecture for immersive visualization systems

2008

Cluster computing has become an essential issue for designing immersive visualization systems. This paradigm employs scalable clusters of commodity computers with much lower costs than would be possible with the high-end, shared memory computers that have been traditionally used for virtual reality purposes. This change in the design of virtual reality systems has caused some development environments oriented toward shared memory computing to require modifications to their internal architectures in order to support cluster computing. This is the case of VR Juggler, which is considered one of the most important virtual reality application development frameworks based on open source code. Thi…