A novel time computation model based on algorithm complexity for data intensive scientific workflow design and scheduling

Scientific workflow offers a framework for cooperation between remote and shared resources on a grid computing environment (GCE) for scientific discovery. One major function of scientific workflow is to schedule a collection of computational subtasks in well-defined orders for efficient outputs by estimating task duration at runtime. In this paper, we propose a novel time computation model based on algorithm complexity (termed as TCMAC model) for high-level data intensive scientific workflow design. The proposed model schedules the subtasks based on their durations and the complexities of participant algorithms. Characterized by utilization of task duration computation function for time efficiency, the TCMAC model has three features for a full-aspect scientific workflow including both dataflow and control-flow: (1) provides flexible and reusable task duration functions in GCE;(2) facilitates better parallelism in iteration structures for providing more precise task durations;and (3) accommodates dynamic task durations for rescheduling in selective structures of control flow. We will also present theories and examples in scientific workflows to show the efficiency of the TCMAC model, especially for control-flow. Copyright©2009 John Wiley & Sons, Ltd.

Modelling based design of a pilot-scale membrane bioreactor for combined nutrient removal from domestic wastewater

A three stage-treatment of domestic wastewater including anaerobic, anoxic and aerobic phases is employed in this study while a clarifier unit is replaced with a submerged membrane in the aerobic unit. The effects of operational parameters on the performance of a pilot scale submerged membrane bioreactor (SMBR) namely hydraulic retention time (HRT), ratio of return activated sludge (QRS), ratio of internal recycle (QIR), solid retention time (SRT) and dissolved oxygen (DO) are evaluated by simulations, using a hybrid model composed of TUDP model, oxygen transfer model, biofouling model due to extra-cellular polymeric substances (EPS) and turbulent shear model. The results showed that anaerobic HRT of 3 hours, anoxic HRT of 6 hours, QRS of 20% and QIR of 300 % are satisfactory in obtaining a high removal efficiency (>90%) of COD, NH4-N, P04-P as well as a less sludge production. An increase of sludge production causes an increase in EPS, which fouls the membrane surface and increase the cleaning cycle of membrane. Operation of 5MBR system at 2 mg/I of DO and 30 days of SRT can extend the membrane cleaning cycle dramatically. The membrane cleaning cycle however is strongly dependent on the initial and terminal specific fluxes and displays inverse power relationships to those fluxes.

Uplink power control via adaptive Hidden-Markov-Model-Based pathloss estimation

Dynamic variations in channel behavior is considered in transmission power control design for cellular radio systems. It is well known that power control increases system capacity, improves Quality of Service (QoS), and reduces multiuser interference. In this paper, an adaptive power control design based on the identification of the underlying pathloss dynamics of the fading channel is presented. Formulating power control decisions based on the measured received power levels allows modeling the fading channel pathloss dynamics in terms of a Hidden Markov Model (HMM). Applying the online HMM identification algorithm enables accurate estimation of the real pathloss ensuring efficient performance of the suggested power control scheme.

A shadow-like task migration model based on context semantics for mobile and pervasive environments

Pervasive computing is a user-centric mobile computing paradigm, in which tasks should be migrated over different platforms in a shadow-like way when users move around. In this paper, we propose a context-sensitive task migration model that recovers program states and rebinds resources for task migrations based on context semantics through inserting resource description and state description sections in source programs. Based on our model, we design and develop a task migration framework xMozart which extends the Mozart platform in terms of context awareness. Our approach can recover task states and rebind resources in the context-aware way, as well as support multi- modality I/O interactions. The extensive experiments demonstrate that our approach can migrate tasks by resuming them from the last broken points like shadows moving along with the users.

A Taylor Model Based Description of the proof stress of magnesium AZ31 during hot working

A series of hot-compression tests and Taylor-model simulations were carried out with the intention of developing a simple expression for the proof stress of magnesium alloy AZ31 during hot working. A crude approximation of wrought textures as a mixture of a single ideal texture component and a random background was employed. The shears carried by each deformation system were calculated using a full-constraint Taylor model for a selection of ideal orientations as well as for random textures. These shears, in combination with the measured proof stresses, were employed to estimate the critical resolved shear stresses for basal slip, prismatic slip, ⟨c+a⟩ second-order pyramidal slip, and { } twinning. The model thus established provides a semianalytical estimation of the proof stress (a one-off Taylor simulation is required) and also indicates whether or not twinning is expected. The approach is valid for temperatures between ∼150 °C and ∼450 °C, depending on the texture, strain rate, and strain path.

Consumer complaint actions: a conceptual model based on complainants about advertising in Australia

This article presents a new conceptual model detailing consumer complaint responses relating to exposure to unacceptable advertising. The model is initiated by consumer perceptions of negative inequity which elicits one of three consumer complaint responses based on the identified triggers that may influence complaining propensity such as demographic, psychographic, cultural, situational and social factors. Complainant perception of the process encountered together with the overall outcome of their experience affect future complaint behaviour as shown by this evolving model as the end reaction flows on to form the consumer’s next response to a similar situation. The advertising industry in Australia is valued annually at over $8 billion and some advertisements have been identified as ‘unacceptable’ by elements in society. Industry and regulatory response to consumer complaints is thus an important area to address and there is no extant literature utilising such an holistic model.

An email classification model based on rough set theory

The communication via email is one of the most popular services of the Internet. Emails have brought us great convenience in our daily work and life. However, unsolicited messages or spam, flood our email boxes, which results in bandwidth, time and money wasting. To this end, this paper presents a rough set based model to classify emails into three categories - spam, no-spam and suspicious, rather than two classes (spam and non-spam) in most currently used approaches. By comparing with popular classification methods like Naive Bayes classification, the error ratio that a non-spam is discriminated to spam can be reduced using our proposed model.

An innovative spam filtering model based on support vector machine

Spam is commonly defined as unsolicited email messages and the goal of spam categorization is to distinguish between spam and legitimate email messages. Many researchers have been trying to separate spam from legitimate emails using machine learning algorithms based on statistical learning methods. In this paper, an innovative and intelligent spam filtering model has been proposed based on support vector machine (SVM). This model combines both linear and nonlinear SVM techniques where linear SVM performs better for text based spam classification that share similar characteristics. The proposed model considers both text and image based email messages for classification by selecting an appropriate kernel function for information transformation.

Learning = playing: Interactive learning with game-based design principles

This paper explores the rapid escalation of demand for information in both complex and convergent forms of accessible technology. The authors contend that this growth creates a concomitant demand for a highly skilled information technology workforce. To ensure the preservation and continued development of this workforce, education of the information technology professional is increasingly acknowledged as one of the primary challenges
confronting educators and educational institutions. Many institutions have sought solutions to this educational conundrum in populist concepts of e-learning

Validation of model-based estimates (synthetic estimates) of the prevalence of risk factors for coronary heart disease for wards in England

Several sets of model-based estimates (synthetic estimates) of the prevalence of risk factors for coronary heart disease for small areas in England have been developed. These have been used in policy documents to indicate which areas are in need of intervention. In general, these models have not been subjected to validity assessment. This paper describes a validity assessment of 16 sets of synthetic estimates, by comparison of the models with national, regional and local survey-based estimates, and local mortality rate estimates. Model-based estimates of the prevalence of smoking, low fruit and vegetable consumption, obesity, hypertension and raised cholesterol are found to be valid.

The role of cultural capital towards the development of a sustainable business model for design firm internationalization

This paper reports the results of three case studies of firms involved with design for the built environment who have been working in international markets for more than two decades. The first two firms are architectural practices and the third is a construction firm which designs and constructs. Their markets are diverse and their strategies have evolved over the two decades. There are numerous differences between countries including cultural, social, project governance structures, regulatory, procurement strategies, terminology, codes, etc. What is it that makes these firms able to develop sustainable business models in internationalisation? A grounded theory approach was used to examine the three case studies and develop a reflexive capability model drawing from the sociological theory of reflexivity to interpret the characteristics of the firms' ability to be able to adapt different international conditions. Twenty-two interviews were conducted across the three firms. Results indicated that sustainable business models rely upon the management of social, cultural and intellectual capital. The strategic management of capital leads to the development of increasing reflexive capability within the processes related to internationalisation. Reflexive capability is a characteristic of the three successful case study firms internationalising and working within global models of practice. This paper focuses on the role of cultural capital in a reflexive capability model for sustainable internationalisation.

A full body musculoskeletal model based on flexible multibody simulation approach utilised in bone strain analysis during human locomotion

Load-induced strains applied to bone can stimulate its development and adaptation. In order to quantify the incident strains within the skeleton, in vivo implementation of strain gauges on the surfaces of bone is typically used. However, in vivo strain measurements require invasive methodology that is challenging and limited to certain regions of superficial bones only such as the anterior surface of the tibia. Based on our previous study [Al Nazer et al. (2008) J Biomech. 41:1036–1043], an alternative numerical approach to analyse in vivo strains based on the flexible multibody simulation approach was proposed. The purpose of this study was to extend the idea of using the flexible multibody approach in the analysis of bone strains during physical activity through integrating the magnetic resonance imaging (MRI) technique within the framework. In order to investigate the reliability and validity of the proposed approach, a three-dimensional full body musculoskeletal model with a flexible tibia was used as a demonstration example. The model was used in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model was developed using the actual geometry of human tibia, which was obtained from three-dimensional reconstruction of MRI. Motion capture data obtained from walking at constant velocity were used to drive the model during the inverse dynamics simulation in order to teach the muscles to reproduce the motion in the forward dynamics simulation. Based on the agreement between the literature-based in vivo strain measurements and the simulated strain results, it can be concluded that the flexible multibody approach enables reasonable predictions of bone strain in response to dynamic loading. The information obtained from the present approach can be useful in clinical applications including devising exercises to prevent bone fragility or to accelerate fracture healing.

Model-based character recognition in low resolution

We propose a combined character separation and recognition approach for low-resolution images of alphanumeric text. By synthesising the image formation process a set of low-resolution templates is created for each character. Cluster algorithms and normalised cross-correlation are then applied to match these templates and thereby allowing both character separation and recognition to be achieved at the same time. Thus characters are recognised using their low-resolution appearance only without applying image enhancement methods. Experiments showed that this approach is able to recognise low-resolution alphanumeric text of down to 5 pixels in size.