Signal processing methods for EEG data classification

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Water-soaked porous evidence:a comparison of processing methods

This study compared the U.K. Home Office formulation for physical developer (PD) against Oil Red O (ORO) and a modified formulation of physical developer (MPD) that uses Tween 20 instead of Synperonic-N for enhancing fingermarks. Three different donors deposited fingermarks on porous surfaces (white paper, leaflets, and cardboard), with aging periods varying from 7 to 28 days. None of the techniques that were tested provided enhancement of latent fingermarks on leaflets, whereas poor-quality enhancement was observed on cardboard. In contrast, all techniques were more successful on white paper surfaces. The results obtained on white paper suggested that PD and MPD performed similarly, with PD detecting 82.3% of the deposited fingermarks and MPD detecting 86.5% of the deposited fingermarks. PD yielded a higher percentage (38.5%) of fingermarks with fine ridge detail (i.e., those with grade 2 or above) than MPD (35.4%). ORO, however, yielded poor results, enhancing only 4.5% of latent fingermarks, but showed no ridge detail in any of the enhancements (i.e., only showed grade 1 enhancements.

Acceleration Profiles and Processing Methods for Parabolic Flight

Parabolic flights provide cost-effective, time-limited access to "weightless" or reduced gravity conditions experienced in space or on planetary surfaces, e.g. the Moon or Mars. These flights facilitate fundamental research - from materials science to space biology - and testing/validation activities that support and complement infrequent and costly access to space. While parabolic flights have been conducted for decades, reference acceleration profiles and processing methods are not widely available - yet are critical for assessing the results of these activities. Here we present a method for collecting, analyzing, and classifying the altered gravity environments experienced during a parabolic flight. We validated this method using a commercially available accelerometer during a Boeing 727-200F flight with $20$ parabolas. All data and analysis code are freely available. Our solution can be easily integrated with a variety of experimental designs, does not depend upon accelerometer orientation, and allows for unsupervised and repeatable classification of all phases of flight, providing a consistent and open-source approach to quantifying gravito-intertial accelerations (GIA), or $g$ levels. As academic, governmental, and commercial use of space increases, data availability and validated processing methods will enable better planning, execution, and analysis of parabolic flight experiments, and thus, facilitate future space activities.Comment: Correspondence to C.E. Carr ([email protected]). 15 pages, 4 figures, 3 supplemental figures. Code: https://github.com/CarrCE/zerog, Dataset: https://osf.io/nk2w4

Concept paper on processing methods and their labelling

Accurate labelling is a very important part of the organic food concept. Therefore, the aspect of how to develop labelling concepts further down the line is important. Creative labelling solutions must be developed to enable consumers to understand the communication and to avoid additional labelling that leads to misunderstandings. Perhaps new types of labelling systems that guarantee that the product is, for example 'carefully processed' or 'hand-crafted' could also be considered

An annotated bibliography of propellant processing methods

The author has specialized in space resources research for many years, with special emphasis on oxygen reduction methods. He has been retained to write a comprehensive review of these methods, detailing advantages and disadvantages, listing by-products and presenting recommendations. As the first step, an extensive outline was prepared, and the portion of this outline covering product manufacture was selected as the initial goal. A working version is presented

Advanced signal processing methods in dynamic contrast enhanced magnetic resonance imaging

Tato dizertační práce představuje metodu zobrazování perfúze magnetickou rezonancí, jež je výkonným nástrojem v diagnostice, především v onkologii. Po ukončení sběru časové sekvence T1-váhovaných obrazů zaznamenávajících distribuci kontrastní látky v těle začíná fáze zpracování dat, která je předmětem této dizertace. Je zde představen teoretický základ fyziologických modelů a modelů akvizice pomocí magnetické rezonance a celý řetězec potřebný k vytvoření obrazů odhadu parametrů perfúze a mikrocirkulace v tkáni. Tato dizertační práce je souborem uveřejněných prací autora přispívajícím k rozvoji metodologie perfúzního zobrazování a zmíněného potřebného teoretického rozboru.This dissertation describes quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI), which is a powerful tool in diagnostics, mainly in oncology. After a time series of T1-weighted images recording contrast-agent distribution in the body has been acquired, data processing phase follows. It is presented step by step in this dissertation. The theoretical background in physiological and MRI-acquisition modeling is described together with the estimation process leading to parametric maps describing perfusion and microcirculation properties of the investigated tissue on a voxel-by-voxel basis. The dissertation is divided into this theoretical analysis and a set of publications representing particular contributions of the author to DCE-MRI.

Automatization techniques for processing biomedical signals using machine learning methods

The Signal Processing Group (Department of Signal Theory and Communications, University Carlos III, Madrid, Spain) offers the expertise of its members in the automatic processing of biomedical signals. The main advantages in this technology are the decreased cost, the time saved and the increased reliability of the results. Technical cooperation for the research and development with internal and external funding is sought