Helsinki University of Technology

About: Helsinki University of Technology is a based out in . It is known for research contribution in the topics: Thin film & Vortex. The organization has 8962 authors who have published 20136 publications receiving 723787 citations. The organization is also known as: TKK & Teknillinen korkeakoulu.

Self-organized formation of topologically correct feature maps

Abstract: This work contains a theoretical study and computer simulations of a new self-organizing process. The principal discovery is that in a simple network of adaptive physical elements which receives signals from a primary event space, the signal representations are automatically mapped onto a set of output responses in such a way that the responses acquire the same topological order as that of the primary events. In other words, a principle has been discovered which facilitates the automatic formation of topologically correct maps of features of observable events. The basic self-organizing system is a one- or two-dimensional array of processing units resembling a network of threshold-logic units, and characterized by short-range lateral feedback between neighbouring units. Several types of computer simulations are used to demonstrate the ordering process as well as the conditions under which it fails.

The self-organizing map

Abstract: The self-organized map, an architecture suggested for artificial neural networks, is explained by presenting simulation experiments and practical applications. The self-organizing map has the property of effectively creating spatially organized internal representations of various features of input signals and their abstractions. One result of this is that the self-organization process can discover semantic relationships in sentences. Brain maps, semantic maps, and early work on competitive learning are reviewed. The self-organizing map algorithm (an algorithm which order responses spatially) is reviewed, focusing on best matching cell selection and adaptation of the weight vectors. Suggestions for applying the self-organizing map algorithm, demonstrations of the ordering process, and an example of hierarchical clustering of data are presented. Fine tuning the map by learning vector quantization is addressed. The use of self-organized maps in practical speech recognition and a simulation experiment on semantic mapping are discussed. >

Cellulose nanocrystals: chemistry, self-assembly, and applications.

Abstract: Cellulose constitutes the most abundant renewable polymer resource available today. As a chemical raw material, it is generally well-known that it has been used in the form of fibers or derivatives for nearly 150 years for a wide spectrum of products and materials in daily life. What has not been known until relatively recently is that when cellulose fibers are subjected to acid hydrolysis, the fibers yield defect-free, rod-like crystalline residues. Cellulose nanocrystals (CNs) have garnered in the materials community a tremendous level of attention that does not appear to be relenting. These biopolymeric assemblies warrant such attention not only because of their unsurpassed quintessential physical and chemical properties (as will become evident in the review) but also because of their inherent renewability and sustainability in addition to their abundance. They have been the subject of a wide array of research efforts as reinforcing agents in nanocomposites due to their low cost, availability, renewability, light weight, nanoscale dimension, and unique morphology. Indeed, CNs are the fundamental constitutive polymeric motifs of macroscopic cellulosic-based fibers whose sheer volume dwarfs any known natural or synthetic biomaterial. Biopolymers such as cellulose and lignin and † North Carolina State University. ‡ Helsinki University of Technology. Dr. Youssef Habibi is a research assistant professor at the Department of Forest Biomaterials at North Carolina State University. He received his Ph.D. in 2004 in organic chemistry from Joseph Fourier University (Grenoble, France) jointly with CERMAV (Centre de Recherche sur les Macromolecules Vegetales) and Cadi Ayyad University (Marrakesh, Morocco). During his Ph.D., he worked on the structural characterization of cell wall polysaccharides and also performed surface chemical modification, mainly TEMPO-mediated oxidation, of crystalline polysaccharides, as well as their nanocrystals. Prior to joining NCSU, he worked as assistant professor at the French Engineering School of Paper, Printing and Biomaterials (PAGORA, Grenoble Institute of Technology, France) on the development of biodegradable nanocomposites based on nanocrystalline polysaccharides. He also spent two years as postdoctoral fellow at the French Institute for Agricultural Research, INRA, where he developed new nanostructured thin films based on cellulose nanowiskers. Dr. Habibi’s research interests include the sustainable production of materials from biomass, development of high performance nanocomposites from lignocellulosic materials, biomass conversion technologies, and the application of novel analytical tools in biomass research. Chem. Rev. 2010, 110, 3479–3500 3479

Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain

Abstract: Magnetoencephalography (MEG) is a noninvasive technique for investigating neuronal activity in the living human brain. The time resolution of the method is better than 1 ms and the spatial discrimination is, under favorable circumstances, 2-3 mm for sources in the cerebral cortex. In MEG studies, the weak 10 fT-1 pT magnetic fields produced by electric currents flowing in neurons are measured with multichannel SQUID (superconducting quantum interference device) gradiometers. The sites in the cerebral cortex that are activated by a stimulus can be found from the detected magnetic-field distribution, provided that appropriate assumptions about the source render the solution of the inverse problem unique. Many interesting properties of the working human brain can be studied, including spontaneous activity and signal processing following external stimuli. For clinical purposes, determination of the locations of epileptic foci is of interest. The authors begin with a general introduction and a short discussion of the neural basis of MEG. The mathematical theory of the method is then explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices. Finally, several MEG experiments performed in the authors' laboratory are described, covering studies of evoked responses and of spontaneous activity in both healthy and diseased brains. Many MEG studies by other groups are discussed briefly as well.