Post processing of the hot torsion test results using a multi-dimensional modelling approach

A model selection scheme was extended to a multi-dimensional representation of the hot torsion test torque, twist and twist rate data to calculate partial derivatives of the torque data with respect to twist and twist rate. These enabled calculation of the instantaneous strain and strain rate hardening indices in the Fields and Backofen method. The concept of an iso-parametric shape function has been borrowed from the finite element method for adding twist rate as a dependant variable to the torque-twist models identified by the model selection scheme. Expressions to calculate the hardening indices, when employing a rational model of torsion data, were derived and presented. Subsequently, the models were used for post processing the data and determining hot strength behaviour, taking into account variations of strain and strain rate hardening indices during the deformation. To substantiate the technique, the hot flow behaviour of API-X70 micro-alloyed steel was determined using a range of hot torsion test data for the material. The flow stress obtained using the instantaneous hardening indices were compared with that obtained by the orthodox technique. For the investigated cases, the onset of dynamic recrystallization (DRX) predicted by the presented technique deviated considerably from those obtained when the average indices were used.

Modelling behavioural and fitness consequences of disturbance for geese along their spring flyway

1. For migratory birds the implications of environmental change may be difficult to predict because they use multiple sites during their annual cycle. Moreover, the migrants’ use of these sites may be interdependent. Along the flyway of the Svalbard pink-footed goose Anser brachyrhynchus population, Norwegian farmers use organized scaring to minimize goose use of their grasslands in spring. We assessed the consequences of this practice for regional site use of pink-footed geese along their spring migration route.

2. We used dynamic programming to find the sequence of migratory decisions that maximizes the fitness of female geese during spring migration, assuming scaring impinges on both food-intake rates and predation risk. The parameterization of the model was based on data gathered from individually marked pink-footed geese between 1991 and 2003.

3. The effect of scaring in terms of fitness and site use was most noticeable regarding food-intake rate. Scaring resulted in a redistribution of geese along the flyway. Furthermore, the outcomes of the modelling exercises were highly dependent on whether or not the geese were omniscient or naive: at moderate scaring levels naive geese were predicted to succumb.

4. On a qualitative basis there was good correspondence between the predictions from the model and the empirical evidence gathered to date.

5. Synthesis and applications. Besides highlighting the importance of learning and changing behaviour in an adaptive fashion, our modelling exercise indicated the potential vulnerability of the geese to abrupt environmental change. In addition, the exercise emphasized the interdependence of site use along the migratory flyway. The model supports the necessity for an integrated flyway management approach. In Norway, discussion is ongoing about the future management of the spring conflict between farming interests and geese. Farmers in north and mid-Norway have announced that they will expand the scaring campaign if a long-term solution, including a compensation scheme, is not forthcoming. If scaring on such a large scale is implemented abruptly, it may have severe consequences for the population: management of both the scaring intensity and its geographical extent is urgently required.

Conceptualizing user satisfaction in the ubiquitous computing era

In this research-in-progress paper we argue that technology in the ubiquitous computing era offers experiences to users that extend well beyond the functional, practical applications offered in the world of work. In this era a realm of engagement is opening up to the individual that transcends the utilitarian, to encompass hedonic and social existence. Our central argument, therefore, is that user satisfaction is a notion which must extend to encompass rich, holistic human experience involving complex and fleeting interactions, driven by highly personal circumstances. We argue that the expectations, requirements and value perceptions of individuals in this dynamic context may only be anticipated and understood if situational factors (such as location, time, context, history-of-use) and quality of life factors (such as life stage, mobility, health, income, background, education) are taken into account. We identify the fundamental differences in key characteristics of user satisfaction between the traditional and ubiquitous computing environments and provide details about our own research approach, in which we are exploring ubiquitous content provision from the perspective of content providers.

A lightwave 3d plug-in for modelling long hair on virtual humans

Multimedia applications today make use of virtual humans. Generating realistic virtual humans is a challenging problem owing to a number of factors, one being the simulation of realistic hair. The difficulty in simulating hair is due to the physical properties of hair. The average human head holds thousands of hairs, with the width of each hair often smaller than the size of a pixel. There are also complex lighting effects that occur within hair. This paper presents a LightWave 3D plug-in for modeling thousands of individual hairs on virtual humans. The plug-in allows the user to specify the length, thickness and distribution of the hair, as well as the number of segments a hair is made up of. The plug-in is able to add hairs to a head model, which the user then modifies to define a hairstyle. The hairs are then multiplied by the plug-in to produce many hairs. By providing a plug-in that does most of the work and produces realistic results, the user is able to produce a hairstyle without modeling each individual strand of hair. This greatly reduces the time spent on hair modeling, and makes the possibility of adding realistic long hair to virtual humans reasonable.

Water quality modelling for drinking water distribution systems

A dynamic water quality model for drinking water distribution systems has been developed in this study, to include processes that occur in the bulk water, as well as those occurring in the biofilm of a distribution system. The model has been validated against water quality data obtained from extensive experimental studies conducted with biofilm reactors. Protein and carbohydrate densities in the biofilm represent biofilm biomass. This model is able to predict the disinfectant decay due to organic matter in the bulk water, as well as that due to biofilm. It simultaneously predicts the growth of biofilm in terms of carbohydrate and protein densities. While this model is complex enough to describe the water quality changes in a distribution system, it is also simple enough to be incorporated into a hydraulic model in order to describe the interaction between disinfectant and microbiological quality throughout a drinking water distribution system.

3D particle-based cell modelling for haptic microrobotic cell injection

Introducing haptic interface to conduct microrobotic intracellular injection has many beneficial implications. In particular, the haptic device provides force feedback to the bio-operator's hand. This paper introduces a 3D particle-based model to simulate the deformation of the cell membrane and corresponding cellular forces during microrobotic cell injection. The model is based on the kinematic and dynamic of spring – damper multi particle joints considering visco-elastic fluidic properties. It simulates the indentation force feedback as well as cell visual deformation during the microinjection. The model is verified using experimental data of zebrafish embryo microinjection. The results demonstrate that the developed cell model is capable of estimating zebrafish embryo deformation and force feedback accurately.

Semantic data modelling and visualization using Noetica

Noetica is a tool for structuring knowledge about concepts and the reIationships between them. It differs from typical information systems in that the knowledge it represents is abstract, highly connected, and includes meta-knowledge (knowledge about knowledge). Noetica represents knowledge using a strongly typed graph data model. By providing a rich type system it is possible to represent conceptual information using formalized structures. A class hierarchy provides a basic classification for all objects. This allows for a consistency of representation that is not often found in `free' semantic networks, and gives the ability to easily extend a knowledge model while retaining its semantics. Visualization and query tools are provided for this data model. Visualization can be used to explore complete sets of link-classes, show paths while navigating through the database, or visualize the results of queries. Noetica supports goal-directed queries (a series of user-supplied goals that the system attempts to satisfy in sequence) and pathfinding queries (where the system finds relationships between objects in the database by following links).

Improving casthouse throughput using discrete-event modeling

The scheduling of metal to different casters in a casthouse is a complicated problem, attempting to find the balance between pot-line, crucible carrier, furnace and casting machine capacity. in this paper, a description will be given of a casthouse modelling system designed to test different scenarios for casthouse design and operation. Using discrete-event simulation, the casthouse model incorporates variable arrival times of metal carriers, crucible movements, caster operation and furnace conditions. Each part of the system is individually modelled and synchronised using a series of signals or semaphores. in addition, an easy to operate user interface allows for the modification of key parameters, and analysis of model output. Results from the model will be presented for a case study, which highlights the effect different parameters have on overall casthouse performance. The case study uses past production data from a casthouse to validate the model outputs, with the aim to perform a sensitivity analysis on the overall system. Along with metal preparation times and caster strip-down/setup, the temperature evolution within the furnaces is one key parameter in determining casthouse performance.

Performance modelling of speculative prefetching for compound requests in low bandwidth networks

To improve the accuracy of access prediction, a prefetcher for web browsing should recognize the fact that a web page is a compound. By this term we mean that a user request for a single web page may require the retrieval of several multimedia items. Our prediction algorithm builds an access graph that captures the dynamics of web navigation rather than merely attaching probabilities to hypertext structure. When it comes to making prefetch decisions, most previous studies in speculative prefetching resort to simple heuristics, such as prefetching an item with access probabilities larger than a manually tuned threshold. The paper takes a different approach. Specifically, it models the performance of the prefetcher and develops a prefetch policy based on a theoretical analysis of the model. In the analysis, we derive a formula for the expected improvement in access time when prefetch is performed in anticipation for a compound request. We then develop an algorithm that integrates prefetch and cache replacement decisions so as to maximize this improvement. We present experimental results to demonstrate the effectiveness of compound-based prefetching in low bandwidth networks.

Development of an expert system modelling the construction process

The construction industry in the UK needs to improve its performance and provide clients with an improved level of satisfaction. The inefficient design and construction process is usually criticised as one of the main causes of poor performance.

A new construction process system, CONstruction Best Practice System (CONBPS), has been developed based on the use of an expert system. CONBPS is based on the traditional procurement strategy as it is probably the most popular procurement method in the UK and yet it is subject to most criticism. This model clearly identifies the roles and responsibilities of the major parties within the building team and identifies the activities and the key issues within the project cycle. The completed model reflects the full project cycle from inception to completion.

The prototype of this system has been demonstrated to the construction participants for their comments. The practitioners included architects, quantity surveyors, planning supervisors, private and public clients. The method of collecting data was through the use of semi-structured interviews.

Following feedback from practitioners, the CONBPS has been updated. This version is more robust; besides, it is more practical and user-friendly as it incorporates the comments from practitioners, who are also the potential users.

The primary aim of this paper is to discuss the development of the updated CONBPS. The improvement of the updated CONBPS includes the information for constructing the system, the computerised functions, system structure, knowledge representation structure and the system operation.

Dynamic path determination policy for distributed multimedia content adaptation

Multimedia content adaptation allows the ever increasing variety of handheld devices such as Smartphones to access distributed rich media resources available on the Internet today. Path planning and determination is a fundamental problem in enhancing performance of distributed multimedia content adaptation systems. Most of the existing path determination mechanisms use static path determination criteria based solely on associating a path with a single behavior aggregate score. However, some criteria such as availability are best represented using different functionality rather than being accumulated into the aggregate score. Moreover, since selection criteria have different behavior towards the score, this principle need to be considered. In this paper, we propose a dynamic multi-criteria path determination policy that selects an optimal path to the content adaptation services that best meet the user preferences and QoS requirements. The performance of the proposed approach is studied in terms of score’s fairness and reliability under different variations. The results indicate that the proposed policy performs substantially better than the baseline policy.

Structural equation modeling for evaluating the user perceptions of E-learning effectiveness in higher education

A crucial prerequisite for sustainable e-learning is the understanding of learners’ preferences for various pedagogical strategies, technologies, and the management of learning resources. This paper presents an empirical study aiming to empirically test the theoretical (pedagogies, technologies and management) (PTM) model on the preference of learners and on the perceived impact of the effectiveness of e-learning. This study uses structural equation modelling (SEM) to identify the critical dimensions in the PTM model for augmenting the effectiveness of e-learning. This leads to the development of a PTM model with the path coefficients showing weak to strong relationships ranging from 0.15 to 0.42 with acceptable significance levels. The results support the hypothesis that management, technology, resources and metadata ontology dimensions affect the effectiveness of elearning both directly and indirectly through enhancing the management effectiveness of learning resources. However, the result does not support positive influence of pedagogical strategy per se on e-learning effectiveness. The implications of this study indicate the criticality of effective management of learning resources to enhance e-learning effectiveness.