Performance analysis of three advanced controllers for polymerization batch reactor: an experimental investigation

The performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC. © 2013 The Institution of Chemical Engineers.

Analytical model to locate the fluidisation interface in a solid-gas vacuum fluidised bed

Vacuum fluidised beds have a distinct advantage of being operated with reduced mass consumption of the fluidising media. However, a low quality of fluidisation reduces the opportunity to utilise the bubbling regime in vacuum fluidised beds. Fluidisation maps are often used to depict the interface between the quiescent, bubbling and slugging regimes inside a fluidised bed. Such maps have been obtained by visual observations of the fluidisation interface in transparent fluidised beds. For beds which are visually inaccessible fluidisation maps are difficult to obtain. The present work therefore attempts to model the interface travel in a vacuum fluidised bed. The pressure gradient due to the bed weight has been determined to be a main contributor for fluidisation/defluidisation under vacuum. A simple analytical model based on the pressure gradient (PG model) is developed to predict the interface location in a vacuum fluidised bed. For a segregated bed, the Gibilaro-Rowe (GR) model is modified and used to predict the jetsam layer growth along with the fluidisation interface. The predictions are compared with the experimental data for minimally and highly segregated particles and it is seen that for non-segregated powders the predictions are quite accurate. Lack of sufficient knowledge of bubble characteristics, however, impeded accurate prediction of the jetsam growth especially at high flow rates. However, an approximate complete fluidisation interface is successfully predicted using the GR-PG model. © 2014 Elsevier B.V.

Towards designing an email classification system using multi-view based semi-supervised learning

The goal of email classification is to classify user emails into spam and legitimate ones. Many supervised learning algorithms have been invented in this domain to accomplish the task, and these algorithms require a large number of labeled training data. However, data labeling is a labor intensive task and requires in-depth domain knowledge. Thus, only a very small proportion of the data can be labeled in practice. This bottleneck greatly degrades the effectiveness of supervised email classification systems. In order to address this problem, in this work, we first identify some critical issues regarding supervised machine learning-based email classification. Then we propose an effective classification model based on multi-view disagreement-based semi-supervised learning. The motivation behind the attempt of using multi-view and semi-supervised learning is that multi-view can provide richer information for classification, which is often ignored by literature, and semi-supervised learning supplies with the capability of coping with labeled and unlabeled data. In the evaluation, we demonstrate that the multi-view data can improve the email classification than using a single view data, and that the proposed model working with our algorithm can achieve better performance as compared to the existing similar algorithms.

The MOVE study: a study protocol for a randomised controlled trial assessing interventions to maximise attendance at physical activity facilities

BACKGROUND: Physical activity is associated with a host of health benefits, yet many individuals do not perform sufficient physical activity to realise these benefits. One approach to rectifying this situation is through modifying the built environment to make it more conducive to physical activity, such as by building walking tracks or recreational physical activity facilities. Often, however, modifications to the built environment are not connected to efforts aimed at encouraging their use. The purpose of the Monitoring and Observing the Value of Exercise (MOVE) study is to evaluate the effectiveness of two interventions designed to encourage the ongoing use of a new, multi-purpose, community-based physical activity facility. METHODS/DESIGN: A two-year, randomised controlled trial with yearly survey points (baseline, 12 months follow-up, 24 months follow-up) will be conducted among 1,300 physically inactive adult participants aged 18-70 years. Participants will be randomly assigned to one of three groups: control, intervention 1 (attendance incentives), or intervention 2 (attendance incentives and tailored support following a model based on customer relationship management). Primary outcome measures will include facility usage, physical activity participation, mental and physical wellbeing, community connectedness, social capital, friendship, and social support. Secondary outcome measures will include stages of change for facility usage and social cognitive decision-making variables. DISCUSSION: This study will assess whether customer relationship management systems, a tool commonly used in commercial marketing settings, can encourage the ongoing use of a physical activity facility. Findings may also indicate the population segments among which the use of such systems are most effective, as well as their cost-effectiveness. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12615000012572 (registered 9 January 2015).

A framework for cloud-based healthcare services to monitor noncommunicable diseases patient

Monitoring patients who have noncommunicable diseases is a big challenge. These illnesses require a continuous monitoring that leads to high cost for patients' healthcare. Several solutions proposed reducing the impact of these diseases in terms of economic with respect to quality of services. One of the best solutions is mobile healthcare, where patients do not need to be hospitalized under supervision of caregivers. This paper presents a new hybrid framework based on mobile multimedia cloud that is scalable and efficient and provides cost-effective monitoring solution for noncommunicable disease patient. In order to validate the effectiveness of the framework, we also propose a novel evaluation model based on Analytical Hierarchy Process (AHP), which incorporates some criteria from multiple decision makers in the context of healthcare monitoring applications. Using the proposed evaluation model, we analyzed three possible frameworks (proposed hybrid framework, mobile, and multimedia frameworks) in terms of their applicability in the real healthcare environment.

DNA methylation and the social gradient of osteoporotic fracture: a conceptual model

INTRODUCTION: Although there is a documented social gradient for osteoporosis, the underlying mechanism(s) for that gradient remain unknown. We propose a conceptual model based upon the allostatic load theory, to suggest how DNA methylation (DNAm) might underpin the social gradient in osteoporosis and fracture. We hypothesise that social disadvantage is associated with priming of inflammatory pathways mediated by epigenetic modification that leads to an enhanced state of inflammatory reactivity and oxidative stress, and thus places socially disadvantaged individuals at greater risk of osteoporotic fracture. METHODS/RESULTS: Based on a review of the literature, we present a conceptual model in which social disadvantage increases stress throughout the lifespan, and engenders a proinflammatory epigenetic signature, leading to a heightened inflammatory state that increases risk for osteoporotic fracture in disadvantaged groups that are chronically stressed. CONCLUSIONS: Our model proposes that, in addition to the direct biological effects exerted on bone by factors such as physical activity and nutrition, the recognised socially patterned risk factors for osteoporosis also act via epigenetic-mediated dysregulation of inflammation. DNAm is a dynamic modulator of gene expression with considerable relevance to the field of osteoporosis. Elucidating the extent to which this epigenetic mechanism transduces the psycho-social environment to increase the risk of osteoporotic fracture may yield novel entry points for intervention that can be used to reduce individual and population-wide risks for osteoporotic fracture. Specifically, an epigenetic evidence-base may strengthen the importance of lifestyle modification and stress reduction programs, and help to reduce health inequities across social groups. MINI ABSTRACT: Our conceptual model proposes how DNA methylation might underpin the social gradient in osteoporotic fracture. We suggest that social disadvantage is associated with priming of inflammatory signalling pathways, which is mediated by epigenetic modifications, leading to a chronically heightened inflammatory state that places disadvantaged individuals at greater risk of osteoporosis.

A GARCH model for testing market efficiency

In this paper we propose a generalised autoregressive conditional heteroskedasticity (GARCH) model-based test for a unit root. The model allows for two endogenous structural breaks. We test for unit roots in 156 US stocks listed on the NYSE over the period 1980 to 2007. We find that the unit root null hypothesis is rejected in 40% of the stocks, and only in four out of the nine sectors the null is rejected for over 50% of stocks. We conclude with an economic significance analysis, showing that mostly stocks with mean reverting prices tend to outperform stocks with non-stationary prices.

SUMLOW: Early design-stage sketching of UML diagrams on an e-whiteboard

Most visual diagramming tools provide point-and-click construction of computer-drawn diagram elements using a conventional desktop computer and mouse. SUMLOW is a unified modelling language (UML) diagramming tool that uses an electronic whiteboard (E-whiteboard) and sketching-based user interface to support collaborative software design. SUMLOW allows designers to sketch UML constructs, mixing different UML diagram elements, diagram annotations, and hand-drawn text. A key novelty of the tool is the preservation of hand-drawn diagrams and support for manipulation of these sketches using pen-based actions. Sketched diagrams can be automatically 'formalized' into computer-recognized and -drawn UML diagrams and then exported to a third party CASE tool for further extension and use. We describe the motivation for SUMLOW, illustrate the use of the tool to sketch various UML diagram types, describe its key architecture abstractions and implementation approaches, and report on two evaluations of the toolset. We hope that our experiences will be useful for others developing sketching-based design tools or those looking to leverage pen-based interfaces in software applications.

Strain gradients in Cu-Fe thin films and multilayers during micropillar compression

Plastic strain gradients can influence the work-hardening behaviour of metals due to the accumulation of geometrically necessary discolations at the micron/submicron scale. A finite element model based on the conventional theory of mechanism-based strain-gradient plasticity has been developed to simulate the micropillar compression of Cu–Fe thin films and multilayers. The modelling results show that the geometric constraints lead to inhomogeneous deformation in the Cu layers, which agrees well with the bulging of Cu layers observed experimentally. Plastic strain gradients develop inside the individual layers, leading to extra work-hardening due to the accumulation of geometrically necessary dislocations. In the multilayer specimens, the Cu layers deform more severely than the Fe layers, resulting in the development of tensile stresses in the Fe layers. It is proposed that these tensile stresses are responsible for the development of micro-cracks in the Fe layers.

Ocular exposure to UV-B in sunlight: the Melbourne Visual Impairment Project model

Quantification of ocular exposure to ultraviolet-B radiation (UV-B) has become an important public health issue, with reports that the ozone layer is being depleted worldwide. Ocular exposure to UV-B is determined by ambient UV-B levels, the duration of outdoor exposure, the proportion of ambient UV-B that reaches the eye, and the use of ocular protection. We have developed a simplified model for quantifying lifetime ocular UV-B exposure that can be used in large epidemiological surveys. Exposure to UV-B is assessed and quantified using a model based on personal exposure over the six summer months. Data available for a population-based sample of 1150 people in the age range 40-98 years revealed a distribution in average annual lifetime ocular UV-B exposure similar to that reported in a previous study on which this model is based, and also demonstrate that people can recall lifetime personal behaviour related to ocular protection. It takes 12 minutes on average to collect these data. This model can be employed by researchers worldwide for uniform assessment of ocular UV-B exposure.

A distributed gateway selection algorithm for UAV networks

In recent years, unmanned aerial vehicle (UAV) has been widely adopted in military and civilian applications. For small UAVs, cooperation based on communication networks can effectively expand their working area. Although the UAV networks are quite similar to the traditional mobile ad hoc networks, the special characteristics of the UAV application scenario have not been considered in the literature. In this paper, we propose a distributed gateway selection algorithm with dynamic network partition by taking into account the application characteristics of UAV networks. In the proposed algorithm, the influence of the asymmetry information phenomenon on UAVs' topology control is weakened by dividing the network into several subareas. During the operation of the network, the partition of the network can be adaptively adjusted to keep the whole network topology stable even though UAVs are moving rapidly. Meanwhile, the number of gateways can be completely controlled according to the system requirements. In particular, we define the stability of UAV networks, build a network partition model, and design a distributed gateway selection algorithm. Simulation results show using our proposed scheme that the faster the nodes move in the network, the more stable topology can be found, which is quite suitable for UAV applications.

Hybrid controller with the combination of FLC and neural network-based IMC for nonlinear processes

This work presents a hybrid controller based on the combination of fuzzy logic control (FLC) mechanism and internal model-based control (IMC). Neural network-based inverse and forward models are developed for IMC. After designing the FLC and IMC independently, they are combined in parallel to produce a single control signal. Mean averaging mechanism is used to combine the prediction of both controllers. Finally, performance of the proposed hybrid controller is studied for a nonlinear numerical plant model (NNPM). Simulation result shows the proposed hybrid controller outperforms both FLC and IMC.

Prediction interval-based neural network controller for nonlinear processes

Prediction interval (PI) has been extensively used to predict the forecasts for nonlinear systems as PI-based forecast is superior over point-forecast to quantify the uncertainties and disturbances associated with the real processes. In addition, PIs bear more information than point-forecasts, such as forecast accuracy. The aim of this paper is to integrate the concept of informative PIs in the control applications to improve the tracking performance of the nonlinear controllers. In the present work, a PI-based controller (PIC) is proposed to control the nonlinear processes. Neural network (NN) inverse model is used as a controller in the proposed method. Firstly, a PI-based model is developed to construct PIs for every sample or time instance. The PIs are then fed to the NN inverse model along with other effective process inputs and outputs. The PI-based NN inverse model predicts the plant input to get the desired plant output. The performance of the proposed PIC controller is examined for a nonlinear process. Simulation results indicate that the tracking performance of the PIC is highly acceptable and better than the traditional NN inverse model-based controller.

Uncertainty Characterization Of A Conceptual Rainfall-Runoff Model By Using Grey Numbers

A procedure for characterizing global uncertainty of a rainfall-runoff simulation model based on using grey numbers is presented. By using the grey numbers technique the uncertainty is characterized by an interval; once the parameters of the rainfall-runoff model have been properly defined as grey numbers, by using the grey mathematics and functions it is possible to obtain simulated discharges in the form of grey numbers whose envelope defines a band which represents the vagueness/uncertainty associated with the simulated variable. The grey numbers representing the model parameters are estimated in such a way that the band obtained from the envelope of simulated grey discharges includes an assigned percentage of observed discharge values and is at the same time as narrow as possible. The approach is applied to a real case study highlighting that a rigorous application of the procedure for direct simulation through the rainfall-runoff model with grey parameters involves long computational times. However, these times can be significantly reduced using a simplified computing procedure with minimal approximations in the quantification of the grey numbers representing the simulated discharges. Relying on this simplified procedure, the conceptual rainfall-runoff grey model is thus calibrated and the uncertainty bands obtained both downstream of the calibration process and downstream of the validation process are compared with those obtained by using a well-established approach, like the GLUE approach, for characterizing uncertainty. The results of the comparison show that the proposed approach may represent a valid tool for characterizing the global uncertainty associable with the output of a rainfall-runoff simulation model.

Configuração da gestão da educação a distância: entendendo os resultados do ENADE para o curso piloto da universidade aberta do Brasil

A educação a distância tem tido expressivo crescimento no Brasil nos últimos anos e com essa expansão aumentam também os desafios relacionados à sua gestão. Este trabalho focaliza as diversas concepções e fundamentos teóricos acerca das abordagens sobre estrutura organizacional e sistemas de educação a distância, para concepção do que denominou-se configuração da gestão da EAD. Como delineamento de pesquisa analisou-se a relação entre as configurações das gestões dos cursos a distância de Administração, projeto piloto da Universidade Aberta do Brasil e os seus conceitos definidos pelo Exame Nacional de Desempenho de Estudantes, identificando-se as teorias e modelos manifestos em seu contexto. O trabalho parte de uma descrição da estrutura organizacional da área responsável pela educação a distância na Universidade Estadual do Maranhão, na Universidade Estadual da Paraíba e na Universidade Federal do Ceará, realizando uma análise comparativa das dimensões complexidade, centralização e coordenação nessas três instituições. Também foram analisados e comparados os sistemas de EAD do curso piloto da UAB, a partir dos referenciais de qualidade para educação superior a distância do MEC, especificamente concentrados nos componentes interdisciplinaridade, materiais didáticos, avaliação, equipe multidisciplinar, comunicação e infraestrutura de polos. Com base nessas análises, discute-se os diferentes conceitos atribuídos pelo Enade aos referidos cursos e explicam-se as correspondências das estruturas organizacionais e dos sistemas de EAD descritos, em relação a esses resultados. Trata-se de uma pesquisa predominantemente qualitativa, descritiva, explicativa e multicaso, cuja coleta de dados foi feita a partir de entrevistas, grupos focais, questionários online e documentos. Os dados primários foram tratados mediante análise de conteúdo categorial e os dados secundários, por meio da análise documental. As observações elaboradas, dentro de uma perspectiva descritivo-interpretativa e de um corte seccional permitem induções acerca das configurações das gestões em cada universidade. Evidencia-se relação forte e direta entre as configurações das gestões do curso piloto e os respectivos resultados no Enade. Constata-se que a teoria da industrialização de Otto Peters e o modelo de educação a distância baseado na distribuição em polos podem explicar a estruturação traduzida no modus operandi da Universidade Aberta do Brasil. Assim, conclui-se que as diferenças nos resultados no Enade dos estudantes da Uema, UEPB e UFC têm relação direta com o modo de estruturação dos setores responsáveis pela intermediação da EAD nessas universidades. Constata-se que o curso piloto da UAB na UEPB não demonstrou ter a aderência necessária aos referenciais de qualidade do MEC, enquanto a Uema e a UFC demonstraram grande adequação aos critérios estabelecidos, o que confirma a relação entre tais referenciais de qualidade e o resultado no Enade. Conclui-se, ainda, que os componentes avaliação e equipe multidisciplinar foram os que mais sugestionaram relação com os desempenhos dos estudantes no Enade. Os resultados encontrados foram discutidos à luz do referencial teórico revisado e foram apresentadas recomendações derivadas dos achados desta pesquisa.