Search results for "Principal Component Analysi"
showing 9 items of 489 documents
UInDeSI4.0 : An efficient Unsupervised Intrusion Detection System for network traffic flow in Industry 4.0 ecosystem
2023
In an Industry 4.0 ecosystem, all the essential components are digitally interconnected, and automation is integrated for higher productivity. However, it invites the risk of increasing cyber-attacks amid the current cyber explosion. The identification and monitoring of these malicious cyber-attacks and intrusions need efficient threat intelligence techniques or intrusion detection systems (IDSs). Reducing the false positive rate in detecting cyber threats is an important step for a safer and reliable environment in any industrial ecosystem. Available approaches for intrusion detection often suffer from high computational costs due to large number of feature instances. Therefore, this paper…
Closed tank pneumatic press application to improve Sauvignon Blanc wine quality and nutraceutical properties
2019
The machines used in the winemaking process directly affect the quality of wine and its nutraceutical properties. Grapes-pressing is a very important step in winemaking as it may promote the presence and/or absence of enzymatic processes on the must, leading to the creation of different products in terms of chemical composition, starting from the same grapes. The aim of the study was to compare two different pressing systems of Sauvignon Blanc grapes using an innovative pneumatic discontinuous closed tank press in two operating modes: the traditional pressing mode in presence of oxygen and the inert pressing mode, performed through grapes pressing under inert gas with nitrogen recovery. Che…
Determination of Changes in the Quality of Surface Water in the River—Reservoir System
2021
Assessing the changing parameters of water quality at different points in the river–reservoir system can help prevent river pollution and implement remedial policies. It is also crucial in modeling water resources. Multivariate statistical analysis is useful for the analysis of changes in surface water quality. It helps to identify indicators that may be responsible for the eutrophication process of a reservoir. Additionally, the analysis of the water quality profile and the water quality index (WQI) is useful in assessing water pollution. These tools can support and verify the results of a multivariate statistical analysis. In this study, changes in water quality parameters of the Turawa r…
Emulation of Sun-Induced Fluorescence from Radiance Data Recorded by the HyPlant Airborne Imaging Spectrometer
2021
The retrieval of sun-induced fluorescence (SIF) from hyperspectral radiance data grew to maturity with research activities around the FLuorescence EXplorer satellite mission FLEX, yet full-spectrum estimation methods such as the spectral fitting method (SFM) are computationally expensive. To bypass this computational load, this work aims to approximate the SFM-based SIF retrieval by means of statistical learning, i.e., emulation. While emulators emerged as fast surrogate models of simulators, the accuracy-speedup trade-offs are still to be analyzed when the emulation concept is applied to experimental data. We evaluated the possibility of approximating the SFM-like SIF output directly based…
Combining PCA and multiset CCA for dimension reduction when group ICA is applied to decompose naturalistic fMRI data
2015
An extension of group independent component analysis (GICA) is introduced, where multi-set canonical correlation analysis (MCCA) is combined with principal component analysis (PCA) for three-stage dimension reduction. The method is applied on naturalistic functional MRI (fMRI) images acquired during task-free continuous music listening experiment, and the results are compared with the outcome of the conventional GICA. The extended GICA resulted slightly faster ICA convergence and, more interestingly, extracted more stimulus-related components than its conventional counterpart. Therefore, we think the extension is beneficial enhancement for GICA, especially when applied to challenging fMRI d…
Online anomaly detection using dimensionality reduction techniques for HTTP log analysis
2015
Modern web services face an increasing number of new threats. Logs are collected from almost all web servers, and for this reason analyzing them is beneficial when trying to prevent intrusions. Intrusive behavior often differs from the normal web traffic. This paper proposes a framework to find abnormal behavior from these logs. We compare random projection, principal component analysis and diffusion map for anomaly detection. In addition, the framework has online capabilities. The first two methods have intuitive extensions while diffusion map uses the Nyström extension. This fast out-of-sample extension enables real-time analysis of web server traffic. The framework is demonstrated using …
Determining the number of sources in high-density EEG recordings of event-related potentials by model order selection
2011
To high-density electroencephalography (EEG) recordings, determining the number of sources to separate the signal and the noise subspace is very important. A mostly used criterion is that percentage of variance of raw data explained by the selected principal components composing the signal space should be over 90%. Recently, a model order selection method named as GAP has been proposed. We investigated the two methods by performing independent component analysis (ICA) on the estimated signal subspace, assuming the number of selected principal components composing the signal subspace is equal to the number of sources of brain activities. Through examining wavelet-filtered EEG recordings (128…
Agronomical evaluation of Sicilian biotypes of Lavandula stoechas L. spp. stoechas and analysis of the essential oils
2015
The aim of this study was to characterize wild lavender, which was collected in three different areas of Sicily (Italy),according to agronomic and chemical evaluation. The collection sites were located in Pantelleria island, Partinico (a warm sub-area of Lauretum) and Castelbuono (a middle sub-area of Lauretum). All the populations were identified as Lavandula stoechas L. ssp. stoechas. Essential oils were extracted by hydrodistillation and analyzed by gas chromatography– flame ionization detector (GC–FID) and GC–mass spectrometry (GC–MS). GC–FID and GC–MS analyses permitted the identification of 101 components from the essential oils. We analyzed only the flowers and leaves of L. stoechas …
Study of quantitative and qualitative variations in essential oils of Sicilian oregano biotypes
2015
Essential oil (EO) was extracted using hydrodistillation from samples of Origanum vulgare subspecies hirtum (Link) Ietswaart, gathered from the wild in various parts of Sicily, Italy; GC-FID and GC-MS analyses were subsequently performed. The aim of the study was to analyze the relationship between essential oil yields and the geographical distribution of oregano wild populations based on variations in environmental factors as collection sites. Moreover, the purpose was to group Origanum vulgare subspecies hirtum biotypes according to the chemical composition of the EO. The seven principal components in the EO was thymol (24.0–54.4%), γ-terpinene (9.8–30.5%), ρ-cymene (5.2–18.7%), α-terpine…