MEG and complex systems

MEG beamformer algorithms work by making the assumption that correlated and spatially distinct local field potentials do not develop in the human brain. Despite this assumption, images produced by such algorithms concur with those from other non-invasive and invasive estimates of brain function. In this paper we set out to develop a method that could be applied to raw MEG data to explicitly test his assumption. We show that a promax rotation of MEG channel data can be used as an approximate estimator of the number of spatially distinct correlated sources in any frequency band.

The Greater London Authority:problems of strategy integration

The Act that established the Greater London Authority (GLA) incorporated many of New Labour's aspirations for modern governance. Among those aspirations was the notion of policy integration, or 'joining up'. The Mayor of Greater London was required to develop a number of strategies, broadly in the planning and environmental policy domains, and to ensure that those strategies meshed into a coherent overall strategy for promoting London's economic, social and environmental well-being. How would this work in practice, given the need for coordination between the GLA and a number of related functional bodies, and given the political imperative for the GLA to make an impact quickly? Through our analysis of the strategy development and integration efforts of the GLA in its first nine months, we have gleaned new insights into the highly complex and difficult process of policy integration. We argue that the high aspirations of the Act for policy integration have not been met, policy integration instead being narrowly interpreted as the coordination of strategies to the Mayor's political agenda. Finally,we reflect on the likelihood of the GLA, as currently constituted, evolving to meet the functional requirement of policy integration.

Electronic Education in the Field of Electrical Engineering Disciplines. Combined Didactic Interactive Program System

At present in the educational process of electrical engineering disciplines electronic learning program, providing control over reproductive educational-cognitive activity (the decision of standard problems) and universal modeling program systems, for instance Electronics Workbench, giving a chance of organizing productive, in particular research activity are basically used. However universal modeling program systems can not provide auto control over educational-cognitive activity because of the absence of the feedback with students. The combined didactic interactive program system, providing the closed directed auto control over both the reproductive and productive heuristic educational-cognitive activity of the student is offered.

The Problems of Forming the Inner Personal Conflict as a Factor which Influences Decision-making

the article views examine the problems concerning with the sources of origin of unconscious the inner personal conflicts and the way the presence of this factor is reflected on the decision-making process by a person.

Peculiarities of the Electronic Educational and Methodological Complex under the Point-rating Technology

At present in the sphere of electronic learning in the light of solving tasks put by the Bologna Declaration an important place is being taken by electronic educational and methodological complexes (EMC).The authors have put forward new components of EMC necessary for the organization of educational process and for the determination of labour intensity according to modules and students’ activity type. They also suggested a technology of defining the rating of the grade in the credit-module system.

Hierarchical Logical Description and Neural Recognition of Complex Patterns

Authors suggested earlier hierarchical method for definition of class description at pattern recognition problems solution. In this paper development and use of such hierarchical descriptions for parallel representation of complex patterns on the base of multi-core computers or neural networks is proposed.

Using cognitive load theory to interpret student difficulties with a problem-based learning approach to engineering education:a case study

This article reports on an investigationwith first year undergraduate ProductDesign and Management students within a School of Engineering and Applied Science. The students at the time of this investigation had studied fundamental engineering science and mathematics for one semester. The students were given an open ended, ill-formed problem which involved designing a simple bridge to cross a river.They were given a talk on problemsolving and given a rubric to follow, if they chose to do so.They were not given any formulae or procedures needed in order to resolve the problem. In theory, they possessed the knowledge to ask the right questions in order tomake assumptions but, in practice, it turned out they were unable to link their a priori knowledge to resolve this problem. They were able to solve simple beam problems when given closed questions. The results show they were unable to visualize a simple bridge as an augmented beam problem and ask pertinent questions and hence formulate appropriate assumptions in order to offer resolutions.

On a Five-Diagonal Jacobi Matrices and Orthogonal Polynomials on Rays in the Complex Plane

∗ Partially supported by Grant MM-428/94 of MESC.

Situation Centers in Modern State

Development of information technologies and hardware-software means make it possible to integrate various engineering solutions of technical, technological and information nature within the framework of the single system of implementation. The situation center (SC) represents the complex of hardware-software means for the personal and team work of the managers group. Its main task consists in supporting decision-making on technical and strategic management solutions based on visualization and analytical procession of information. The SC ensures the support of preparation and decision making in particular: − elaboration of the versions and recommendations taking into account various conditions and limitations; − choice or creation of the situation analysis model; − structurization of the problems and definition of the most informative parameters; − monitoring of socio-economical and socio-political information.

On a Direct Approach to the Solution of Inverse Optical Problems

The evaluation from experimental data, of physical quantities, which enter into the electromagnetic Maxwell equations, is described as inverse optical problem. The functional relations between the dependent and independent variables are of transcendental character and numeric procedures for evaluation of the unknowns are largely used. Herein, we discuss a direct approach to the solution, illustrated by a specific example of determination of thin films optical constants from spectrophotometric data. New algorithm is proposed for the parameters evaluation, which does not need an initial guess of the unknowns and does not use iterative procedures. Thus we overcome the intrinsic deficiency of minimization techniques, such as gradient search methods, Simplex methods, etc. The price of it is a need of more computing power, but our algorithm is easily implemented in structures such as grid clusters. We show the advantages of this approach and its potential for generalization to other inverse optical problems.

A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems

In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.

The Notion of Model in Software Engineering

Милослав A. Средков - Понятията модел и моделиране се използват толкова интензивно в много дисциплини, че е трудно да им се придаде конретно значение. Дори в Софтуерните технологии, разбирането на тези понятия силно зависи от контекста. Ние смятаме, че това допринася за неконсистентността между подходите за моделиране там. В тази статия посочваме някои от произтичащите проблеми, както и важността да има подходяща дефиниция, съчетана с подходящи инструменти. Преглеждаме по-общите дефиниции на модел отвъд границите на Софтуерните технологии. Минаваме през моделирането на различни вторични продукти на процесите от Софтуерните технологии. Накрая представяме нашата визия относно използването на такава обща основа за наша полза.

Architectural aspects of self-aware and self-expressive computing systems:from psychology to engineering

Work on human self-Awareness is the basis for a framework to develop computational systems that can adaptively manage complex dynamic tradeoffs at runtime. An architectural case study in cloud computing illustrates the framework's potential benefits.

Guest editorial

Full text: With the rapid development of the aerospace industry, manufacturing technologies have to continuously develop and adjust themselves to ever-growing demands coming from more complex component designs and the use of highly engineered materials. Today there is an increased number of manufacturers contributing to the realization of final products, i.e. avionics, so it is easy to perceive the truly globalized dimension of the aerospace manufacturing business. With this comes the demand for further engineering developments on which the academic/industrial research institutes need to deliver solutions to real aerospace manufacturing problems. This is a challenging task since aerospace manufacturing technologies have to cover a wide range of materials (from composites to advanced Ni/Ti alloys), processes (from forging to non-traditional machining and assembly), and parts’ dimensions/batch sizes (from airframes to turbine blades). In this wide context, this Special Issue includes high quality theoretical and experimental scientific contributions on the following topics related to the aerospace manufacturing technology: (a) machining of advance aerospace alloys; (b) abrasive processes applied to aerospace components; (c) surface treatments to enhance fatigue performance of aerospace components; (d) joining and assembly of aerospace components; (e) laser machining of aerospace alloys; (f) automated/supervised manufacture of aerospace components; (g) quality supervision of aerospace manufacturing routes. The breadth of topics in this Special Issue is perhaps indicative of the complexity and challenges that the research related to aerospace manufacturing technology can offer. We hope that this issue will act as a catalyst for the development of further research, academic and industrial interactions, and publications related to aerospace manufacturing technologies for the benefit of the academic and industrial research communities.

Large-volume metrology instrument selection and measurability analysis

A wide range of metrology processes are involved in the manufacture of large products. In addition to the traditional tool-setting and product-verification operations, increasingly flexible metrology-enabled automation is also being used. Faced with many possible measurement problems and a very large number of metrology instruments employing diverse technologies, the selection of the appropriate instrument for a given task can be highly complex. Also, as metrology has become a key manufacturing process, it should be considered in the early stages of design, and there is currently very little research to support this. This paper provides an overview of the important selection criteria for typical measurement processes and presents some novel selection strategies. Metrics that can be used to assess measurability are also discussed. A prototype instrument selection and measurability analysis application is also presented, with discussion of how this can be used as the basis for development of a more sophisticated measurement planning tool. © 2010 Authors.