Search results for "computer.software_genre"

GEM

2014

The widespread use of digital sensor systems causes a tremendous demand for high-quality time series analysis tools. In this domain the majority of data mining algorithms relies on established distance measures like Dynamic Time Warping (DTW) or Euclidean distance (ED). However, the notion of similarity induced by ED and DTW may lead to unsatisfactory clusterings. In order to address this shortcoming we introduce the Gliding Elastic Match (GEM) algorithm. It determines an optimal local similarity measure of a query time series Q and a subject time series S. The measure is invariant under both local deformation on the measurement-axis and scaling in the time domain. GEM is compared to ED and…

Hardware and firmware developments for the upgrade of the ATLAS Level-1 Central Trigger Processor

2014

The Central Trigger Processor (CTP) is the final stage of the ATLAS first level trigger system which reduces the collision rate of 40 MHz to a Level-1 event rate of 100 kHz. An upgrade of the CTP is currently underway to significantly increase the number of trigger inputs and trigger combinations, allowing additional flexibility for the trigger menu. We present the hardware and FPGA firmware of the newly designed core module (CTPCORE+) module of the CTP, as well as results from a system used for early firmware and software prototyping based on commercial FPGA evaluation boards. First test result from the CTPCORE+ module will also be shown.

MEMORIA: A computer program for experimental control of verbal learning and memory experiments with the Apple II microcomputer

1983

New evidence for chunk-based models in word segmentation.

2014

International audience; : There is large evidence that infants are able to exploit statistical cues to discover the words of their language. However, how they proceed to do so is the object of enduring debates. The prevalent position is that words are extracted from the prior computation of statistics, in particular the transitional probabilities between syllables. As an alternative, chunk-based models posit that the sensitivity to statistics results from other processes, whereby many potential chunks are considered as candidate words, then selected as a function of their relevance. These two classes of models have proven to be difficult to dissociate. We propose here a procedure, which lea…

Countering Adversarial Inference Evasion Attacks Towards ML-Based Smart Lock in Cyber-Physical System Context

2021

Machine Learning (ML) has been taking significant evolutionary steps and provided sophisticated means in developing novel and smart, up-to-date applications. However, the development has also brought new types of hazards into the daylight that can have even destructive consequences required to be addressed. Evasion attacks are among the most utilized attacks that can be generated in adversarial settings during the system operation. In assumption, ML environment is benign, but in reality, perpetrators may exploit vulnerabilities to conduct these gradient-free or gradient-based malicious adversarial inference attacks towards cyber-physical systems (CPS), such as smart buildings. Evasion attac…

Eliciting Information on the Vulnerability Black Market from Interviews

2010

Threats to computing prompted by software vulnerabilities are abundant and costly for those affected. Adding to this problem is the emerging vulnerability black markets (VBMs), since they become places to trade malware and exploits. VBMs are discussed based on information derived from interviews with security researchers. The effort is enriched by further examination of documents surrounding the disclosure of four selected vulnerabilities cases. The result suggests that the VBMs is bifurcated into two distinct parts; the skilled-hacker and the script-kiddie VBMs with a possible link between them, where the latter become places to sell malware or exploit kits after the zero day vulnerability…

Notice of Violation of IEEE Publication Principles: Distributed Multimedia Digital Libraries on Peer-to-Peer Networks

2007

This paper presents an original approach to image sharing in large, distributed digital libraries, in which a user is able to interactively search interesting resources by means of content-based image retrieval techniques. The approach described here addresses the issues arising when the content is managed through a peer-to-peer architecture. In this case, the retrieval facilities are likely to be limited to queries based on unique identifiers or small sets of keywords, which may be quite inadequate, so we propose a novel algorithm for routing user queries that exploits compact representations of multimedia resources shared by each peer in order to dynamically adapt the network topology to …

Genre-adaptive Semantic Computing and Audio-based Modelling for Music Mood Annotation

2016

This study investigates whether taking genre into account is beneficial for automatic music mood annotation in terms of core affects valence, arousal, and tension, as well as several other mood scales. Novel techniques employing genre-adaptive semantic computing and audio-based modelling are proposed. A technique called the ACTwg employs genre-adaptive semantic computing of mood-related social tags, whereas ACTwg-SLPwg combines semantic computing and audio-based modelling, both in a genre-adaptive manner. The proposed techniques are experimentally evaluated at predicting listener ratings related to a set of 600 popular music tracks spanning multiple genres. The results show that ACTwg outpe…

WORDY: a Semi-automatic Methodology aimed at the Creation of Neologisms based on a Semantic Network and Blending Devices

2017

In this paper, we propose a semi-automatic tool, named WORDY, that implements a methodology aimed at speeding-up the pro- cess of creation of neologisms. The approach exploits a semantic network, which is explored through the spreading activation methodology and ex- ploits three blending linguistic techniques together with a proper ranking function in order to support companies in the creation of neologisms ca- pable of evoking semantic meaningful associations to customers.

A Study of a Social Behavior inside the Online Black Markets

2010

Illegal activities in cyberspace involving software vulnerabilities have resulted in tangible damage on computer-based environments. Lately, online black market sites for trading stolen goods, credentials, malware and exploit kits have been intensively examined. The market players are identifiably a group of loosely tied individuals but posses shared interests. However, their social behavior has only been discussed in a limited manner. This paper examines the arrangement of the market insiders’ social behavior that enables such forums to continue or discontinue their operation and become a meaningful threat to security. The results reveal that particular formal and informal regulations and …