Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Privacy and security enhanced offline oblivious transfer for massive data distribution

Unauthorized accesses to digital contents are serious threats to international security and informatics. We propose an offline oblivious data distribution framework that preserves the sender's security and the receiver's privacy using tamper-proof smart cards. This framework provides persistent content protections from digital piracy and promises private content consumption.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Comparison of palmtop-computer-assisted brief cognitive-behavioral treatment to cognitive-behavioral treatment for panic disorder

In the present study, the authors sought to determine whether the efficiency and cost-effectiveness of cognitive-behavioral treatment (CBT) for panic disorder could be improved by adjunctive computer-assisted therapy. Eighteen participants who met Diagnostic and Statistical Manual of Mental Disorders (3rd ed., revised; American Psychiatric Association, 1987) criteria for panic disorder were randomly assigned to a 12-session CBT (CBT12) condition (D. H. Barlow & M. G. Craske, 1989) or to a 4-session computer-assisted CBT (CBT4-CA) condition. Palmtop computers, with a program developed to incorporate basic principles of CBT, were used by CBT4-CA clients whenever they felt anxious or wanted to practice the therapy techniques and were used by all participants as a momentary assessment tool. CBT4-CA clients carried the computer at all times and continued to use it for 8 weeks after termination of therapy. Analyses of clinically significant change showed superiority of CBT12 at posttest on some measures; however, there were no differences at follow-up.

Computer technology - A political player in social policy processes

The absence of considerations of technology in policy studies reinforces the popular notion that technology is a neutral tool, Through an analysis of the role played by computers in the policy processes of Australia's Department of Social Security, this paper argues that computers are political players in policy processes, Findings indicate that computers make aspects of the social domain knowable and therefore governable, The use of computers makes previously infeasible policies possible, Computers also operate as bureaucrats and as agents of client surveillance. Increased policy change, reduced discretion and increasingly targeted and complex policies can be attributed to the use of computer technology, If policy processes are to be adequately understood and analysed, then the role of technology in those processes must be considered.

Genetic influence on ERP slow wave measures of working memory

Individual differences in the variance of event-related potential (ERP) slow wave (SW) measures were examined. SW was recorded at prefrontal and parietal sites during memory and sensory trials of a delayed-response task in 391 adolescent twin pairs. Familial resemblance was identified and there was a strong suggestion of genetic influence. A common genetic factor influencing memory and sensory SW was identified at the prefrontal site (accounting for an estimated 35%-37% of the reliable variance) and at the parietal site (51%-52% of the reliable variance). Remaining reliable variance was influenced by unique environmental factors. Measurement error accounted for 24% to 30% of the total variance of each variable. The results show genetic independence for recording site, but not trial type, and suggest that the genetic factors identified relate more directly to brain structures, as defined by the cognitive functions they support, than to the cognitive networks that link them.

Two-link approximation schemes for loss networks with linear structure and trunk reservation

Loss networks have long been used to model various types of telecommunication network, including circuit-switched networks. Such networks often use admission controls, such as trunk reservation, to optimize revenue or stabilize the behaviour of the network. Unfortunately, an exact analysis of such networks is not usually possible, and reduced-load approximations such as the Erlang Fixed Point (EFP) approximation have been widely used. The performance of these approximations is typically very good for networks without controls, under several regimes. There is evidence, however, that in networks with controls, these approximations will in general perform less well. We propose an extension to the EFP approximation that gives marked improvement for a simple ring-shaped network with trunk reservation. It is based on the idea of considering pairs of links together, thus making greater allowance for dependencies between neighbouring links than does the EFP approximation, which only considers links in isolation.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.

Albert-László Barabási, Linked – The New Science of Networks, Perseus, Cambridge, 2002. Duncan J. Watts, Six Degrees – The Science of a Connected Age, William Heinemann, Londres, 2003.

Com a criação da teoria das redes, assistiu-se nos últimos anos a uma revolução científica de carácter interdisciplinar Não é uma teoria inteiramente nova, tendo sido precedida pela criação por P. Erdvos, nos anos sessenta, da teoria dos grafos aleatórios. Esta última é uma teoria puramente matemática, donde termos escrito “grafo” em lugar de “rede”. Apenas recentemente podemos falar de uma efectiva teoria das redes reais, e isso devido ao abandono de algumas das ideias essenciais avançadas por Erdvos, em especial a ideia de partir de um conjunto previamente dado de nós, os quais de seguida vão sendo conectados aleatoriamente com probabilidade p. Este quadro geral começou a ser modificado pelo chamado modelo dos “mundo-pequenos” proposto em 1998 por Duncan Watts e Steve Strogatz, modificação que se tornou ainda mais radical quando, em 1999, Albert Barabási e colaboradores propuseram um modelo no qual os nós vão progressivamente nascendo e conectados por uma função de preferência: um nó conecta-se em proporção às ligações que os outros nós já possuem, pelo que quantas mais ligações um nó possui maior a probabilidade de receber ulteriores ligações.

Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems

Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.

Gestão e monitorização de uma rede departamental: um caso de estudo

Mestrado em Engenharia Electrotécnica e de Computadores