Automatic Energy Extraction Methods for EEG Channel Selection

2018 ◽  
Author(s):  
Hilman Fauzi ◽  
Mohd Ibrahim Shapiai ◽  
Shahrum Shah Abdullah ◽  
Zuwairie Ibrahim
Keyword(s):  
Channel Selection ◽  
Extraction Methods ◽  
Energy Extraction

scholarly journals Expanding the Role of Sub-Exploited DOE-High Energy Extraction and Metabolomic Profiling towards Agro-Byproduct Valorization: The Case of Carotenoid-Rich Apricot Pulp

Molecules ◽  
2020 ◽  
Vol 25 (11) ◽  
pp. 2702 ◽  
Author(s):  
Thalia Tsiaka ◽  
Charalambos Fotakis ◽  
Dimitra Z. Lantzouraki ◽  
Konstantinos Tsiantas ◽  
Eleni Siapi ◽  
...  
Keyword(s):  
Unsaturated Fatty Acids ◽  
Extraction Methods ◽  
High Energy ◽  
Extensive Study ◽  
Carotenoid Content ◽  
Bioactive Metabolites ◽  
Energy Extraction ◽  
Industrial Sectors ◽  
Metabolomic Profiling ◽  
Branched Chain

Traditional extraction remains the method-of-choice for phytochemical analyses. However, the absence of an integrated analytical platform, focusing on customized, validated extraction steps, generates tendentious and non-reproducible data regarding the phytochemical profile. Such a platform would also support the exploration and exploitation of plant byproducts, which are a valuable source of bioactive metabolites. This study deals with the incorporation of (a) the currently sub-exploited high energy extraction methods (ultrasound (UAE)- and microwave-assisted extraction (MAE)), (b) experimental design (DOE), and (c) metabolomics, in an integrated analytical platform for the extensive study of plant metabolomics and phytochemical profiling. The recovery of carotenoids from apricot by-products (pulp) is examined as a case study. MAE, using ethanol as solvent, achieved higher carotenoid yields compared to UAE, where 1:1 chloroform-methanol was employed, and classic extraction. Nuclear magnetic resonance (NMR)-based metabolomic profiling classified extracts according to the variations in co-extractives in relation to the extraction conditions. Extracts with a lower carotenoid content contained branched-chain amino acids as co-extractives. Medium carotenoid content extracts contained choline, unsaturated fatty acids, and sugar alcohols, while the highest carotenoid extracts were also rich in sugars. Overall, the proposed pipeline can provide different the phytochemical fractions of bioactive compounds according to the needs of different industrial sectors (cosmetics, nutraceuticals, etc.).

Dynamic Modeling of Hydrokinetic Energy Extraction

2010 ◽  
Vol 132 (9) ◽  
Author(s):  
Veronica B. Miller ◽  
Laura A. Schaefer
Keyword(s):  
Electrical Energy ◽  
Extraction Methods ◽  
Ecological Impacts ◽  
Energy Extraction ◽  
Cfd Model ◽  
Large Reservoir ◽  
River Flows ◽  
Hydrokinetic Energy ◽  
Power Extraction ◽  
Flow Modification

The world is facing an imminent energy crisis. In order to sustain our energy supply, it is necessary to advance renewable technologies. Despite this urgency, however, it is paramount to consider the larger environmental effects associated with using renewable resources. Hydropower, in the past, has been seen as a viable resource to examine, given that its basics of mechanical to electrical energy conversion seem to have little effect on the environment. Discrete analysis of dams and in-stream diversion set-ups, although, has shown otherwise. Modifications to river flows and changes in temperature (from increased and decreased flows) cause adverse effects to fish and other marine life because of changes in their adaptive habitat. Recent research has focused on kinetic energy extraction in river flows, which may prove to be more sustainable, as this type of extraction does not involve a large reservoir or large flow modification. The field of hydrokinetic energy extraction is immature; little is known about the devices’ performance in the river environment and their risk of impingement, fouling, and suspension of sediments. The governing principles of hydrokinetic energy extraction are presented, along with a two-dimensional computational fluid dynamics (CFD) model of the system. Power extraction methods are compared and CFD model validation is presented. It is clear that more research is required in hydrokinetic energy extraction with an emphasis toward lower environmental and ecological impacts.

scholarly journals Energy extraction method for EEG channel selection

2019 ◽  
Vol 17 (5) ◽  
pp. 2561
Author(s):  
Hilman Fauzi ◽  
M. Abdullah Azzam ◽  
Mohd. Ibrahim Shapiai ◽  
Masaki Kyoso ◽  
Uswah Khairuddin ◽  
...  
Keyword(s):  
Extraction Method ◽  
Channel Selection ◽  
Energy Extraction

scholarly journals Analysis and Implementation of Brain Waves Feature Extraction and Classification to Control Robotic Hand

2019 ◽  
Vol 1 (3) ◽  
pp. 31-41 ◽  
Author(s):  
Mohammed Z. Al-Faiz ◽  
Ammar A. Al-hamadani
Keyword(s):  
Feature Extraction ◽  
Dimensionality Reduction ◽  
Frequency Domain ◽  
Error Rate ◽  
Time Domain ◽  
Channel Selection ◽  
Extraction Methods ◽  
Robotic Hand ◽  
Selection Algorithm ◽  
Absolute Value

In this paper, (i) time domain, frequency domain and spatial domain feature extraction methods were investigated. (ii) Two dimensionality reduction methods were proposed, implemented and compared. (iii) The method pair (feature extraction + dimensionality reduction) that owns the lowest classification error rate will be used to learn a machine learning algorithm to control robotic hand in offline mode. Two classes EEG dataset of three bipolar channels was used. The extracted feature vectors were fed into Support Vector Machine with Radial Basis Function kernel (SVM-RBF) to train the classifier. The experimented time domain feature extraction methods were: Mean Absolute Value (MAV), integrated Absolute Value (IAV), Zero Crossing (ZC), Root Mean Square (RMS), Waveform Length (WL) and Slope Sign Change (SSC). Frequency domain feature was the Autoregressive Feature (AR). Finally, the spatial domain feature was the Common Spatial Patterns (CSP). Matlab codes for Principal Component Analysis (PCA) and channel selection algorithm were designed and used to reduce the dimensionality of the features vector. Results showed that CSP features got the lowest error rate for both dimensionality reduction technique with 2.14%. Results recommends to use channel selection algorithm over PCA since it owns the lowest processing time of 8.2s over 8.5s for PCA.

The effect of different extraction methods on chemical composition profile and pharmacological activities of essential oils and hydrosols

Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381
Author(s):  
F Ghavidel ◽  
MM Zarshenas ◽  
A Sakhteman ◽  
A Gholami ◽  
Y Ghasemi ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Essential Oils ◽  
Extraction Methods ◽  
Composition Profile ◽  
Pharmacological Activities

Characterization of dissolved organic matter (DOM) extracted from soils by hot water percolation (HWP)

2010 ◽  
Vol 59 (1) ◽  
pp. 99-108 ◽  
Author(s):  
M. Takács ◽  
Gy. Füleky
Keyword(s):  
Organic Matter ◽  
Humic Acid ◽  
Natural Organic Matter ◽  
Extraction Methods ◽  
Soil Samples ◽  
Hot Water ◽  
Soil Extracts ◽  
Water Percolation ◽  
Soil Humic Acid

The Hot Water Percolation (HWP) technique for preparing soil extracts has several advantages: it is easily carried out, fast, and several parameters can be measured from the same solution. The object of this study was to examine the possible use of HWP extracts for the characterization of soil organic matter. The HPLC-SEC chromatograms, UV-VIS and fluorescence properties of the HWP extracts were studied and the results were compared with those of the International Humic Substances Society (IHSS) Soil Humic Acid (HA), IHSS Soil Fulvic Acid (FA) and IHSS Suwannee Natural Organic Matter (NOM) standards as well as their HA counterparts isolated by traditional extraction methods from the original soil samples. The DOM of the HWP solution is probably a mixture of organic materials, which have some characteristics similar to the Soil FA fractions and NOM. The HWP extracted organic material can be studied and characterized using simple techniques, like UV-VIS and fluorescence spectroscopy.

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