Search results for "Pattern"
showing 10 items of 4203 documents
Large-scale nonlinear dimensionality reduction for network intrusion detection
2017
International audience; Network intrusion detection (NID) is a complex classification problem. In this paper, we combine classification with recent and scalable nonlinear dimensionality reduction (NLDR) methods. Classification and DR are not necessarily adversarial, provided adequate cluster magnification occurring in NLDR methods like $t$-SNE: DR mitigates the curse of dimensionality, while cluster magnification can maintain class separability. We demonstrate experimentally the effectiveness of the approach by analyzing and comparing results on the big KDD99 dataset, using both NLDR quality assessment and classification rate for SVMs and random forests. Since data involves features of mixe…
MANAGEMENT CHALLENGES - A PREVIEW IN FUTURE OF CAPITALISM
2012
The economic crisis comes in the context the deepest political crisis faced by the EU today. Economic catastrophe led to the strongest economic crisis since the '30s. Downturns were commonly explained using technical arguments, economic or financial reasons. Because they were discussed by experts in language often inaccessible, so often we face today and dangerous misunderstanding of the population crisis. When talking about economic crises tend to forget that they come in a political context, social and cultural. At the same time, how society reacts to the crisis is decisively influenced by the values it embraces.
A New Feature Selection Methodology for K-mers Representation of DNA Sequences
2015
DNA sequence decomposition into k-mers and their frequency counting, defines a mapping of a sequence into a numerical space by a numerical feature vector of fixed length. This simple process allows to compare sequences in an alignment free way, using common similarities and distance functions on the numerical codomain of the mapping. The most common used decomposition uses all the substrings of a fixed length k making the codomain of exponential dimension. This obviously can affect the time complexity of the similarity computation, and in general of the machine learning algorithm used for the purpose of sequence analysis. Moreover, the presence of possible noisy features can also affect the…
Hybrid vibration signal monitoring approach for rolling element bearings
2019
New approach to identify different lifetime stages of rolling element bearings, to improve early bearing fault detection, is presented. We extract characteristic features from vibration signals generated by rolling element bearings. This data is first pre-labelled with an unsupervised clustering method. Then, supervised methods are used to improve the labelling. Moreover, we assess feature importance with each classifier. From the practical point of view, the classifiers are compared on how early emergence of a bearing fault is being suggested. The results show that all of the classifiers are usable for bearing fault detection and the importance of the features was consistent. peerReviewed
Flow-bed interactions analysis and application of automatic close range digital photogrammetric survey in a laboratory flume
2014
This paper reports on a laboratory study in which the automatic digital photogrammetric survey was applied to derive the high-resolution Digital Surface Model (DSM) of the bed topography, used for the flow-bed interactions analysis, in a large amplitude meandering laboratory flume. The analysis has been conducted with the aid of detailed data of three-dimensional flow field previously collected using the acoustic Doppler velocity profiler DOP2000. The applied surveying procedure has allowed the evaluation of the DSM with a resolution of ±0.5 mm. The detailed DSM has been compared with peculiar maps describing the flow velocity pattern (downstream and the crossstream flows) and the shear vel…
Regional variations in occupancy frequency distributions patterns between odonate assemblages in Fennoscandia
2018
Odonate (damselfly and dragonfly) species richness and species occupancy frequency distributions (SOFD) were analysed in relation to geographical location in standing waters (lakes and ponds) in Fennoscandia, from southern Sweden to central Finland. In total, 46 dragonfly and damselfly species were recorded from 292 waterbodies. Species richness decreased to the north and increased with waterbody area in central Finland, but not in southern Finland or in Sweden. Species occupancy ranged from 1 up to 209 lakes and ponds. Over 50% of the species occurred in less than 10% of the waterbodies, although this proportion decreased to the north. In the southern lakes and ponds, none of the species o…
Digital Correlation Method Based on Micro-geometrical Texture Pattern for Strain Field Measurement
2011
International audience; Image correlation methods are widely used in experimental mechanics to obtain displacement field measurements. Currently, these methods are applied using digital images of the initial and deformed surfaces sprayed with black or white paint. Speckle patterns are then captured and the correlation is performed with a high degree of accuracy to an order of 0.01 pixels. In 3D, however, stereo-correlation leads to a lower degree of accuracy. Correlation techniques are based on the search for a sub-image (or pattern) displacement field. The work presented in this paper introduces a new correlation-based approach for 3D displacement field measurement that uses an additional …
Minimal learning machine in anomaly detection from hyperspectral images
2020
Abstract. Anomaly detection from hyperspectral data needs computationally efficient methods to process the data when the data gathering platform is a drone or a cube satellite. In this study, we introduce a minimal learning machine for hyperspectral anomaly detection. Minimal learning machine is a novel distance-based classification algorithm, which is now modified to detect anomalies. Besides being computationally efficient, minimal learning machine is also easy to implement. Based on the results, we show that minimal learning machine is efficient in detecting global anomalies from the hyperspectral data with low false alarm rate.
Interpersonal dynamics in 2-vs-1 contexts of football: the effects of field location and player roles
2019
This study analyzed the spatial-temporal interactions that sustained 2-vs-1 contexts in football at different field locations near the goal. Fifteen male players (under 15 years, age 13.2 ± 1.03 years, years of practice 4.2 ± 1.10 years), 5 defenders, 7 midfielders, and 3 attackers, participated in the study. Each participant performed a game to simulate a 2-vs-1 sub-phase as a ball carrier, second attacker, and defender at three different field locations, resulting in a total number of 142 trials. The movements of participants in each trial were recorded and digitized with TACTO software. Values of interpersonal distance between the ball carrier and defender and interpersonal angles betwee…
Genome-Wide Inhibition of Pro-atherogenic Gene Expression by Multi-STAT Targeting Compounds as a Novel Treatment Strategy of CVDs.
2018
Cardiovascular diseases (CVDs), including atherosclerosis, are globally the leading cause of death. Key factors contributing to onset and progression of atherosclerosis include the pro-inflammatory cytokines Interferon (IFN)a and IFN? and the Pattern Recognition Receptor (PRR) Toll-like receptor 4 (TLR4). Together, they trigger activation of Signal Transducer and Activator of Transcription (STAT)s. Searches for compounds targeting the pTyr-SH2 interaction area of STAT3, yielded many small molecules, including STATTIC and STX-0119. However, many of these inhibitors do not seem STAT3-specific. We hypothesized that multi-STAT-inhibitors that simultaneously block STAT1, STAT2, and STAT3 activit…