An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Vibration instability in rolling mills: Modeling and experimental results

Models for the occurrence of the vibrational instability during rolling known as third octave chatter are presented and discussed. An analysis of rolling mill chatter was performed for the purpose of identifying characteristics of the vibrations and to determine any dependency on the rolling schedule. In particular, a stability criterion for the critical rolling speed is used to predict the maximum rolling speed without chatter instability on schedules from a 5 stand tandem mill rolling thin steel product. The results correlate well with measurements of critical speed occurring on the mill using a vibration monitor: This research provides significant insights into the chatter phenomena and has been used to investigate control methods for suppression of the instability.

Direction of Causation Modeling Between Cross-Sectional Measures of Parenting and Psychological Distress in Female Twins

Under certain conditions, cross-sectional analysis of cross-twin intertrait correlations can provide important information about the direction of causation (DOC) between two variables. A community-based sample of Australian female twins aged 18 to 45 years was mailed an extensive Health and Lifestyle Questionnaire (HLQ) that covered a wide range of personality and behavioral measures. Included were self-report measures of recent psychological distress and perceived childhood environment (PBI). Factor analysis of the PBI yielded three interpretable dimensions: Coldness, Overprotection, and Autonomy. Univariate analysis revealed that parental Overprotection and Autonomy were best explained by additive genetic, shared, and nonshared environmental effects (ACE), whereas the best-fitting model for PBI Coldness and the three measures of psychological distress (Depression, Phobic Anxiety, and Somatic Distress) included only additive genetic and nonshared environmental effects (AE). A common pathway model best explained the covariation between (1) the three PBI dimensions and (2) the three measures of psychological distress. DOC modeling between latent constructs of parenting and psychological distress revealed that a model which specified recollected parental behavior as the cause of psychological distress provided a better fit than a model which specified psychological distress as the cause of recollected parental behavior. Power analyses and limitations of the findings are discussed.

Recent advances on the role of CD40 and dendritic cells in immunity and tolerance

CD40 is a key signaling pathway for the function of B cells, monocytes, and dendritic cells in the immune system, and plays an important role in inflammatory pathways of nonhemopoietic cells. The NFkappaB family of transcription factors is a critical mediator in inflammation. NFkappaB is involved both in the regulation of CD40 expression and in cell signaling after CD40 ligation. This positive feedback loop linking NFkappaB and CD40 plays an important role in the control of the adaptive immune response, with fundamental implications for immunity and tolerance in vivo.

Digitally-implemented naturally sampled PWM suitable for multilevel converter control

For dynamic closed loop control of a multilevel converter with a low pulse number (ratio of switching frequency to synthesized fundamental), natural sampled pulse-width modulation (PWM) is the best form of modulation. Natural sampling does not introduce distortion or a delayed response to the modulating signal. However previous natural sampled PWM implementations have generally been analog. For a modular multilevel converter, a digital implementation has advantages of accuracy and flexibility. Re-sampled uniform PWM is a novel digital modulation technique which approaches the performance of natural PWM. Both hardware and software implementations for a five level multilevel converter phase are presented, demonstrating the improvement over uniform PWM.

A new wavelet-based adaptive method for solving population balance equations

A new wavelet-based adaptive framework for solving population balance equations (PBEs) is proposed in this work. The technique is general, powerful and efficient without the need for prior assumptions about the characteristics of the processes. Because there are steeply varying number densities across a size range, a new strategy is developed to select the optimal order of resolution and the collocation points based on an interpolating wavelet transform (IWT). The proposed technique has been tested for size-independent agglomeration, agglomeration with a linear summation kernel and agglomeration with a nonlinear kernel. In all cases, the predicted and analytical particle size distributions (PSDs) are in excellent agreement. Further work on the solution of the general population balance equations with nucleation, growth and agglomeration and the solution of steady-state population balance equations will be presented in this framework. (C) 2002 Elsevier Science B.V. All rights reserved.

Fractional-order control and simulation of wind energy systems with PMSG/full-power converter topology

This paper presents a new integrated model for the simulation of wind energy systems. The proposed model is more realistic and accurate, considering a variable-speed wind turbine, two-mass rotor, permanent magnet synchronous generator (PMSG), different power converter topologies, and filters. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with PMSG/full-power converter topology, based on fractional-order controllers. Comprehensive simulation studies are carried out with matrix and multilevel power converter topologies, in order to adequately assert the system performance in what regards the quality of the energy injected into the electric grid. Finally, conclusions are duly drawn.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Training control centers' operators in incident diagnosis and power restoration using intelligent tutoring systems

The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

Reconfigurable SiC Embedded Photonic Structures with Self Optical Bias Control

Multilayered heterostructures based on embedded a-Si:H and a-SiC:H p-i-n filters are analyzed from differential voltage design perspective using short- and long-pass filters. The transfer functions characteristics are presented. A numerical simulation is presented to explain the filtering properties of the photonic devices. Several monochromatic pulsed lights, separately (input channels) or in a polychromatic mixture (multiplexed signal) at different bit rates, illuminated the device. Steady-state optical bias is superimposed from the front and the back side. Results show that depending on the wavelength of the external background and impinging side, the device acts either as a short- or a long-pass band filter or as a band-stop filter. Particular attention is given to the amplification coefficient weights, which allow to take into account the wavelength background effects when a band or frequency needs to be filtered or the gate switch, in which optical active filter gates are used to select and filter input signals to specific output ports in wavelength division multiplexing (WDM) communication systems. This nonlinearity provides the possibility for selective removal or addition of wavelengths. A truth table of an encoder that performs 8-to-1 MUX function exemplifies the optoelectronic conversion.

Dietary patterns and risk of oral cancer: a case-control study in São Paulo, Brazil

OBJECTIVE: To analyze the association between dietary patterns and oral cancer. METHODS: The study, part of a Latin American multicenter hospital-based case-control study, was conducted in São Paulo, Southeastern Brazil, between November 1998 and March 2002 and included 366 incident cases of oral cancer and 469 controls, frequency-matched with cases by sex and age. Dietary data were collected using a food frequency questionnaire. The risk associated with the intake of food groups defined a posteriori, through factor analysis (called factors), was assessed. The first factor, labeled "prudent," was characterized by the intake of vegetables, fruit, cheese, and poultry. The second factor, "traditional," consisted of the intake of rice, pasta, pulses, and meat. The third factor, "snacks," was characterized as the intake of bread, butter, salami, cheese, cakes, and desserts. The fourth, "monotonous," was inversely associated with the intake of fruit, vegetables and most other food items. Factor scores for each component retained were calculated for cases and controls. After categorization of factor scores into tertiles according to the distribution of controls, odds ratios and 95% confidence intervals were calculated using unconditional multiple logistic regression. RESULTS: "Traditional" factor showed an inverse association with cancer (OR=0.51; 95% CI: 0.32; 0.81, p-value for trend 0.14), whereas "monotonous" was positively associated with the outcome (OR=1.78; 95% CI: 1.78; 2.85, p-value for trend <0.001). CONCLUSIONS: The study data suggest that the traditional Brazilian diet, consisting of rice and beans plus moderate amounts of meat, may confer protection against oral cancer, independently of any other risk factors such as alcohol intake and smoking.

An adaptive educational system for higher education

The main objective of an Adaptive System is to adequate its relation with the user (content presentation, navigation, interface, etc.) according to a predefined but updatable model of the user that reflects his objectives, preferences, knowledge and competences [Brusilovsky, 2001], [De Bra, 2004]. For Educational Adaptive Systems, the emphasis is placed on the student knowledge in the domain application and learning style, to allow him to reach the learning objectives proposed for his training [Chepegin, 2004]. In Educational AHS, the User Model (UM), or Student Model, has increased relevance: when the student reaches the objectives of the course, the system must be able to readapt, for example, to his knowledge [Brusilovsky, 2001]. Learning Styles are understood as something that intent to define models of how given person learns. Generally it is understood that each person has a Learning Style different and preferred with the objective of achieving better results. Some case studies have proposed that teachers should assess the learning styles of their students and adapt their classroom and methods to best fit each student's learning style [Kolb, 2005], [Martins, 2008]. The learning process must take into consideration the individual cognitive and emotional parts of the student. In summary each Student is unique so the Student personal progress must be monitored and teaching shoul not be not generalized and repetitive [Jonassen, 1991], [Martins, 2008]. The aim of this paper is to present an Educational Adaptive Hypermedia Tool based on Progressive Assessment.

Controlo directo de binário de uma máquina assíncrona trifásica

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Edição gráfica de layout fabril no apoio ao planeamento e controlo da produção

O contributo da área de investigação Interacção Humano-Computador (HCI) está patente não só na qualidade da interacção, mas também na diversificação das formas de interacção. A HCI define-se como sendo uma disciplina que se dedica ao desenho, desenvolvimento e implementação de sistemas de computação interactivos para uso humano e estudo dos fenómenos relevantes que os rodeiam. Pretende-se, no âmbito desta tese de mestrado, o desenvolvimento de um Editor Gráfico de Layout Fabril a integrar num SAD para suporte ao Planeamento e Controlo da Produção. O sistema deve ser capaz de gerar um layout fabril do qual constam, entre outros objectos, as representações gráficas e as respectivas características/atributos do conjunto de recursos (máquinas/processadores) existentes no sistema de produção a modelar. O módulo desenvolvido será integrado no projecto de I&D ADSyS (Adaptative Decision Support System for Interactive Scheduling with MetaCognition and User Modeling Experience), melhorando aspectos de interacção referentes ao sistema AutoDynAgents, um dedicado ao escalonamento, planeamento e controlo de produção. Foi realizada a análise de usabilidade a este módulo com a qual se pretendeu realizar a respectiva avaliação, através da realização de um teste de eficiência e do preenchimento de um inquérito, da qual se identificaram um conjunto de melhorias e sugestões a serem consideradas no refinamento deste módulo.

Analysis of tongue shape and motion in speech production using statistical modeling

The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.