Helsinki University of Technology

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

Distributed energy generation and sustainable development

Abstract: Conventionally, power plants have been large, centralized units. A new trend is developing toward distributed energy generation, which means that energy conversion units are situated close to energy consumers, and large units are substituted by smaller ones. A distributed energy system is an efficient, reliable and environmentally friendly alternative to the traditional energy system. In this article, we will first discuss the definitions of a distributed energy system. Then we will evaluate political, economic, social, and technological dimensions associated with regional energy systems on the basis of the degree of decentralization. Finally, we will deal with the characteristics of a distributed energy system in the context of sustainability. This article concludes that a distributed energy system is a good option with respect to sustainable development.

Simple and Accurate Analytical Model of Planar Grids and High-Impedance Surfaces Comprising Metal Strips or Patches

Abstract: Simple analytical formulas are introduced for the grid impedance of electrically dense arrays of square patches and for the surface impedance of high-impedance surfaces based on the dense arrays of metal strips or square patches over ground planes. Emphasis is on the oblique-incidence excitation. The approach is based on the known analytical models for strip grids combined with the approximate Babinet principle for planar grids located at a dielectric interface. Analytical expressions for the surface impedance and reflection coefficient resulting from our analysis are thoroughly verified by full-wave simulations and compared with available data in open literature for particular cases. The results can be used in the design of various antennas and microwave or millimeter wave devices which use artificial impedance surfaces and artificial magnetic conductors (reflect-array antennas, tunable phase shifters, etc.), as well as for the derivation of accurate higher-order impedance boundary conditions for artificial (high-) impedance surfaces. As an example, the propagation properties of surface waves along the high-impedance surfaces are studied.

Generalizations of the clustering coefficient to weighted complex networks

Abstract: The recent high level of interest in weighted complex networks gives rise to a need to develop new measures and to generalize existing ones to take the weights of links into account. Here we focus on various generalizations of the clustering coefficient, which is one of the central characteristics in the complex network theory. We present a comparative study of the several suggestions introduced in the literature, and point out their advantages and limitations. The concepts are illustrated by simple examples as well as by empirical data of the world trade and weighted coauthorship networks.

Self-organizing semantic maps

Abstract: Self-organized formation of topographic maps for abstract data, such as words, is demonstrated in this work The semantic relationships in the data are reflected by their relative distances in the map Two different simulations, both based on a neural network model that implements the algorithm of the selforganizing feature maps, are given For both, an essential, new ingredient is the inclusion of the contexts, in which each symbol appears, into the input data This enables the network to detect the "logical similarity" between words from the statistics of their contexts In the first demonstration, the context simply consists of a set of attribute values that occur in conjunction with the words In the second demonstration, the context is defined by the sequences in which the words occur, without consideration of any associated attributes Simple verbal statements consisting of nouns, verbs, and adverbs have been analyzed in this way Such phrases or clauses involve some of the abstractions that appear in thinking, namely, the most common categories, into which the words are then automatically grouped in both of our simulations We also argue that a similar process may be at work in the brain