A multimedia environment for investigation of experimental and simulated Dough Kneading data sets I. DELIYANNIS University of Wales Swansea, Computer Science Department, Singleton Park, SA2 8PP, Wales, UK,
[email protected] M. F. WEBSTER Institute of Non-Newtonian Fluid Mechanics, University of Wales Swansea, Computer Science Department, Singleton Park, SA2 8PP, Wales, UK,
[email protected]
Abstract: A detailed industrially-based multimedia case-study is considered, featuring experimental and simulation doughkneading data-sets. Multimedia environments are employed, creating flexible implementations, whilst dealing with large and densely interrelated data. This complicated rheological investigation, aided via multimedia technology, spans across various parameter spaces. These include geometric, fluid-type, speed, depth and stirrer-shape adjustments. Direct data-comparison across valid combinations is actioned, through multi-menus. Voiceover-streams and multiple navigation-paths are characteristic features. Multimedia environment-level retiming supports synchronised presentation of non-uniform animations, reducing re-rendering times. Through multimedia environments, direct system-updates are practical, whilst data-duplication is avoided. Such implementation enhances the presentation impact-factor of the work. As such, the system supports intelligent interrogation, that itself, may lead to heightened awareness and meaningful interpretation of the data. Whilst the resulting systems fulfil base-level presentation requirements over various media, the same systems may be used for further data-evaluation.
Keywords: multimedia, human-computer interaction, navigation, experimentation, simulation, stream-synchronisation, content-evaluation. 1 . CASE STUDY: DOUGH KNEADING The main objective of this work and the Multimedia System (MMS) it has generated are, to illustrate the key factors that affect the process of dough kneading. This is achieved by creating a multi-media visualisation system for the complete, direct and meaningful presentation of the associated data. Use of MMS can prevent presentation deficiencies introduced with proprietary software. In addition, the ability to present results comparatively, from case to case, or via interactive mode-switching, is highly desirable. This implementation is a valuable tool for the comprehension of parameter variation, and consequent affect upon the associated flow or process under consideration. Ultimately, MMS data integration ([11], [23]) has enabled effortless navigation through the vast volume of information, dispensation of data-duplication, and interactive comparison of experimental and simulation animations, within a single MMS frame. Interaction with animations is implemented through user-interface options. In addition, the MMS may be programmed to simulate common interaction modes, as cited in the literature [5]. The flexibility, demonstrated in multimedia environments (MME) and rigorous system-design for large data-sets, is based on the uniqueness of the data and their interrelationships. For industrialists, process optimisation may imply significant economy in production costs. Typical products of the dough-kneading process are everyday goods, such as bread, biscuits and pizza bases. Figure 1 illustrates an empty mixer, two different states of kneading (mixer-lid removed), and a typical, final baked product. This is a rich and varied foods study, that of dough kneading, introduced within the frame of Figure 1, [cc.1]. The associated complex free-surface movement involves wetting and peeling on vessel and stirrers, which have demanded new modelling algorithms. The Multimedia System (MMS) trailer quickly scans what was involved [“Show Animation” option, Figure 1]. The main concern here, is to identify the factors that affect the industrial kneading and mixing of dough. Industrial mixing devices have a number of features that increase their effectiveness, such as dual stirrers and baffles at the outside wall. These introduce additional computational complexity into the modelling. The problem has been investigated in a systematic
manner, via dual simulation [18] and experimentation [4] studies, using simplified model-mixers and model-fluids. The intricacy involved was incremented gradually, as increasingly complex fluids and mixer settings were introduced. Considerable interest is evident in this applied case-study, from computer-science, rheological ([10], [12]) and industrial points of view. From the computer-science perspective, various requirements are exposed. The sheer size of data, introduces storage/retrieval limitations, particularly as non-linear access is supported by the end-system. Synchronous display of multiple streams results in system/network-bottlenecks, particularly as delivery over Internet communication channels is featured by the end-system. In addition, presentation of the data in a meaningful manner has triggered the need for advanced and multiplexed navigational routes, which permit various investigative scenarios, alongside pre-determined presentation-paths. Research in this interdisciplinary area of interactive multimedia has resulted in the development of a wide range of multimedia systems, destined for courseware, research and industrial applications (see [26]). With respect to visualisation and presentation aspects, novel organisation techniques and state-of-the-art visualisation algorithms are utilised. Examples include the application of animated visualisation techniques, to display the position of free-surfaces (“Pov-Ray” with spherical-particles, see Figure 21 below), in form. This is accompanied with a range of techniques to visualise the free-surface in a realistic animated setting, using 2D and 3D views, and solid-modelling procedures. New interface styles for MMS data-presentation have been developed, using a hierarchical organisation, based on model adjustment (via customised multi-menus) and navigational graphs, introducing intelligent navigation ([24], [26]).
Figure 1, cc1 1 . 1 Many-formatted data considerations Added complication is introduced as data are modelled, calculated and delivered, by multiple research groups, working in parallel. Each group has employed individual methods, to store and provide the data (variety of standards), providing the development workload. Experimental and simulation results generated, range over a variety of investigation areas [Figures 7 to 11], featuring a large number of variables. Frequently, calculations may be repeated with algorithm adjustments. Thus, each time data are received, increased complexity is introduced. It is necessary to identify unique, fresh data to be categorised and inserted, appropriately. Categorisation, ordering and duplication problems arise with PPT and new data. The above deficiencies are amplified, as lack of data-format standards introduce further conversion complexities. Within MMS, new data are inserted, or replaced, straightforwardly to the system without-preferred order. Some initial practical problems to be tackled include the collection, categorisation, visualisation and presentation of simulation results, having established data-sharing practice. This minimises data conversion, and as a consequence, the visualisation workload. The plethora and diversity of data, demands MMS techniques, relating to efficient content-updates and direct data-insertion. Suitable interaction mechanisms had to be created, able to cope with frequent data updates and content re-organisation. The final result involves interactive combination of large volumes of experimental and simulation data, under a pointand-click integrated environment. Experimental data are presented comparatively, either with simulation data (directly) [Figure 15], or via appropriate indirect links [Figures 16, 17]. Comparative results in animated stream format are used. This data format facilitates multiple modes of interaction, via parameter-adjustment. Such combined and interactive features, render the use of a synchronised and ordered, interactive presentation mode, highly valuable, particularly when complex, multi-type data are to be assessed. The problem was modelled in two and three dimensions [8]. For fully-filled simulated cases, results were generated on five separate horizontal slices through the vessel at equal distances set apart, from bottom to top. The free-surface posi-
tion was calculated separately in part-filled cases. Customised “Multi-Menus” were required for these large data sizes, and due to the limited navigational ability of available commercial software. A necessity is to navigate in a user-defined order, whilst simultaneously, allowing direct-access to secondary information. Evaluating the data, or attempting to investigate flow behaviour through variable-adjustment, is a demanding task, for linear presentation organisations. Standard presentation tools are designed to present data by default in a pre-determined manner, disabling direct interaction between multiple variables. Here, utilisation of interactive techniques is required, to allow smooth navigation through data-sets, enabling parameter adjustment, on demand. This MMS allows for such direct adjustment of variables, and the presentation of interrelated data, under an integrated environment. Streaming problems were also encountered, as once completed, the size of the compressed presentation was large, sufficient to fill a Compact-Disk storage-medium (CD, holding over 600 Megabytes). Stream-optimisation and re-use features were required, to reduce data-bottlenecks. For example, all multi-menu icons are pre-loaded into memory before the MMS commences. They are not unloaded until the MMS is closed, reducing loading/unloading times. The cruisecontrol path (described later) is optimised, preloading (caching) the contents of the next slide, whilst at previous slides. 1 . 2 Content-based user-interface design The Multi-Menu structure acts as a graph that depicts link-availability. So, for example, when a geometrical setting is selected, the Multi-Menu provides several possible navigational routes. Interaction is elevated considerably, via the incorporation of such graph-structures within the interface. It becomes immediately apparent to the user, that the nodes of the graph are related to the associated settings. Upon selection, the Multi-Menu constructs (referred to as “cast” members), are programmed to adjust their visual properties (Visible, Dimmed, Selected, Non-Visible), using modern graphical user-interface conventions ([14], [15]]). This property provides direct user-feedback indicating the current choice, and a comprehensive list of other link-paths. Navigational and user-delivery problems became apparent when the MMS was used in practical presentations to different types of audience. Data complexity leads to complicated navigation paths in presentation-mode. This problem was overcome, using multiple colour-coded “cruise control” mechanisms, predefined orientated-routes through the main MMS sections. In this mode, the user is permitted to interact with the data in a non-predetermined manner, and to toggle back to a predetermined mode, as desired.
PPT to MMS Typical organisation problems cited [7] were overcome by first evaluating the data under consideration, and consequently programming interaction, using the MME to support systematic categorisation and interconnection of the data. The resulting system does not rely on external links to access detached presentation units: instead it integrates the data in its original form. Data duplication is removed, by using various object and MM techniques. The data are encapsulated and referenced within the so-called “cast” file. This enables multiple (internal) data-instances to be referenced to a unique (external) file-object. For each MM-frame requested, data are dynamically called from the “cast”. Operations such as resizing, rotations, transformations, animations, fading, colour or frame-rate changes are applied, before the MM-frame is displayed. For subsequent frames, data-instances, already processed, can be retained on screen. New instances follow the above procedure. The data are stored once within the MME, and accessed from various related MM-frames, on-demand (multi-sorted data-context). This integration process does not require the utilisation of external data-format conversion algorithms. Figure 12 below, illustrates how the MMS incorporates requested data within the “Main Presentation” frame. Some of the advantages that this implementation demonstrates are immediately apparent. Duplication is removed, and data integration/categorisation guarantees, that all related frames can be accessed in presentation mode. Insertion of new data into the MMS, performed via the “cast” within Director, does not require a specific order. Nevertheless, grouping of like-data units rationalises frame-linking, that establishes the interrelationships between data. MME may be programmed, so that automatic data-validation is performed for the necessary running components. In this manner, missing content-components may be recovered from alternative locations, prior to launch. Otherwise, diagnostic messages may be displayed, to describe the nature/type of discrepancy, the appropriate action to be taken, and the status of the system to proceed. This procedure guarantees system-integrity and robust status, re presentation. Traditional presentation software, such as PPT, may only achieve presentation integrity via manual verification.
Adjusting Mixing-Orientation Two mixer orientations are modelled, simulated, and validated by experiments within the framework of this project. First, dough-mixing was modelled in vertical-orientation, and subsequently horizontally, for fully-filled settings. Beyond fully-filled scenarios, free-surface situations were considered, under both settings. In this manner, a deeper appreciation may be grasped of the fundamental aspects at play within these processes. Choices of mixer are provided, typically in Figures 3, 12 (mixer-geometry instance), and Figure 2 (vessel-orientation choice), taken from the Multi-Menu.
Figure 2
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Adjusting Mixing-Complexity Mixer geometry itself, consists of four designs of increasingly complexity: single-stirrer concentric, single-stirrer eccentric, double-stirrer eccentric, and double-stirrer eccentric, with baffles on vessel-wall. These settings are accessible using the associated menu (left-screen), [Figures 12, 13, below], demonstrating transition between two such instances. Vesselorientation and free-surface results can be accessed, via the previously described bottom-screen horizontal set-of-four icons. Navigation is actioned through icon selection. When passing from one menu-option to another, a transition between graph-nodes is performed. The MMS is programmed to respond to these transitions by adjusting the Multi-Menu, highlighting links for further user-interaction. As a consequence, the system responds automatically to subsequent menuchoices, for which inter-related data are held (for example, a geometrical adjustment), and displayed directly, by default. Repeated use of this feature across the MMS, eases navigational strain for the user, aiding direct comparison between data-instances. That is, without utilising complicated control commands to reach disparate data. In instances where, neither simulated nor experimental data are available, the user is directed to the principal menu for that specific choice. MMS specification is orchestrated through a graph data-structure, supporting multi-media data, frames and links. At bottom, right-of-screen, icons are positioned and colour-coded to indicate specific displayed-variables. Using User Interface techniques to improve Interaction User-interface conventions were employed during MMS development ([21], [16]). Colour and link-intensity settings follow modern standards and are consistent across frames. Layout choice accommodates the complex structure of data and menus, allowing for maximum viewable area. In some instances, link-icons are blended alongside the data. This enables identification and easy user-access to data-related links. In addition, this can help deal with instances where more than one choice is provided for the same parameter. Red colour is utilised to indicate selection (free-surface and speedvariation), as icons used are too small in size, and higher visibility is required to depict selection. Here, a non-strict adherence to user-interface guidelines is utilised [15]. These conventions are adopted, whenever toggle navigation-menus are provided, as standard in modern user-interfaces. This factor enhances user-familiarity and experience with the MMS, its multi-faceted data-content and powerful navigational capabilities. Additional interface-enhancing graphic properties have been employed. These allow the MMS to adjust link-options at each stage, and comply with modern user-interface standards, utilising colours, informative graphics and audio feedback. The importance of consistency across the user-interface extends to interaction. A well-designed interface can be rendered useless, without valid and predictable interaction. It is therefore imperative to design the interactive mechanisms and MMS content-linking appropriately. This is achieved through the sound use of graphs, where frame-linking can be tested for completeness at any developmental stage. 1 . 3 Multimedia – “Multi-Menus” and organisation The MMS enables user-interaction at multiple levels. As indicated earlier, the order of interaction, through multi-menus, is first the geometrical level (geometric adjustment), and then, at each subsequent level across the various relevant variable adjustments. The ability to create and re-program each menu at every instance, is one of the most powerful features offered by the MME. Multi-menus are designed to accommodate interaction in multiple modes. Multi-menus are a complex construct, both to program and for the MMS to support. So, when should this interaction mechanism be used? Multi-menus were avoided, for slide-sorters, relating to presentation organisation, instead of actual content. An educated decision must be made, to link only data that can be categorised into sub-sections that does not apply to the whole MMS. Further justification for multi-menu use, is that interactive modes of the presentation are best represented through graph-structures. [6], presents a detailed account of the different links that one may incorporate, and the limitations therein of standard software today. A multiple menu instance is illustrated in Figure 3, together with its corresponding graph-structure. Such menus cater for dynamical adjustment of data-content. Currently-selected nodes are indicated using larger circles. “C on bars” represents comparison between two, or more, related data-sets (forming a node by itself). The user can compare data-instances, interact with the information presented (via mode-switching), and hence, smoothly navigate through the data-tree. MMS organisation follows the project plan structure. This facilitates data integration, as the same structure was utilised for the creation of the .ppt. It also enables the identification of duplicate data, and allows for rapid content updates. First, additional data are appended to the existing .ppt files, and subsequently, to the MMS. Multiple modes of organisation can be observed within the MMS, each at a different level. Starting from the programming level, MM-frames are organ-
ised into related sets. The sets themselves are not ordered within the MMS. This would create insertion, or movement, of MM-frame sets. Colours have also been employed, to indicate alternate frame-sets. Interaction follows the graph organisation which, in turn, is based on the project-plan structure. Additional interactive features include: slide-sets presented using a combined slide-sorter mode; alongside actual slides; or use of “next slide” button. These are accessible, both from the main-menu, or from related frames. Such a modular organisation at each MMS level, allows for the implementation of the multi-menu structure, as individual components with unique properties amongst the separate sections. Thus, the same graphical icon can have multiple functional-response, across different frames, enabling optimal programmability and adjustment, according to the data. The interactive mode accesses the full power of the MMS. A panic-button is included top-left (Dough Mixing INNFM RTN) that returns the user to the starting point. “Variable-priority” rule applies: once a variable has been selected upon a multi-menu, switching to a second multi-menu, will automatically inherit prior variable-choice. By default, this enables direct data-comparison between frames. The user can access ‘green’, ‘orange’ and ‘red’ cruise-control routes, at will. As the primary mode of interaction is full-mode, by default, the user is permitted maximal choice, with combined use of ordered, interactive controls. The availability of on-demand links and the plethora of available routes are strong features of the MMS. A second user-option is to follow a pre-determined order of presentation. This is a desirable feature for public presentation, usually in a limited time-frame and under duress. Under such conditions, large volumes of data can create navigational difficulties. The “Cruise Control” mechanism enables implementation of pre-determined paths, complete with voiceover (VO). Multiple paths can be created, indicated using appropriate colour-coding. The DK-MMS utilises three separate control mechanisms. ‘Red’ guides the user to the main MMS sections, ensuring all major sections are accessed. ‘Orange’ button is a pre-defined, more exhaustive, navigational path through the MMS. ‘Green’ cruise-control is a particular elective path, with voiceover clips, explaining underlying content. 1 . 4 Graphs to model MMS structure
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Figure 6 Within the current case study, extensive use of graphs and related representation structures have been utilised, for the rigorous implementation of navigation, using interaction. The main reasons for this are: large volume of presentation
material; complexities with “Multi-Menus”; need to create a MMS map defining positions for further data-inserts; validation for presentation mode specification. The type of graph used with this case study is a multi-connected graph1 [Figure 4]. For the organisation of PowerPoint (PPT) presentations, a dynamic linked-list structure is employed [Figure 5]. Each branch is itself a presentation, linked to external data (such as experimentally-captured and simulation-generated animations). One immediate disadvantage of this organisation is that, when for example, speed and depth information is demanded, the Z2-plane of the fully-filled case must be used twice. This duplicates the volume of information stored within the PPT, thus increasing final presentation-size. The above data-categorisation is followed within the multi-media organisation, but in a more liberal manner. Replacing strict-ordering of frames (as in above structure), data are retained locally to one instance in the MME. Links join the top-level to the case-study introduction, flyer-animation and project-plan slide-sorter. The second-level (indicated by dark-grey intensity), consists of the menus organised across geometry and setting-complexity (one-stirrer, concentric to two-stirrers, eccentric with baffles). Subsequent levels branch out from the second-level options, providing links to individual frames and their related information. Figure 5 shows a section snapshot of organisation for links to MMS-components. The columns represent some of the image components, animations and sounds (used to construct Figure 17, below). Adjacent columns represent related MM-frames. To represent this hierarchy using a graph, each node must represent a MM-frame. Each such node can inherit properties/attributes from another; new attributes/behaviours may be appended, or replace those previously. This organisation is adaptive and flexible. It may match the relationships for any given data-set. Attributes need not be programmed for each frame, being inherited for a copy-object of an existing frame. When an attribute is programmed, it generates a new database object that may be associated with any component of a frame. Frame components are stored uniquely within the database and are referenced to the same item, when multiple instances are on display. Instead, a link is employed, if many instances of the same data element are required. The user may select when the memory is flushed of that particular element. 2 . GREEN CC-TOUR To provide some insight into the data-content and the power of the MMS, details are provided for the green cc preselected route across the data-domain. Two principal requirements are fulfilled: first, expert description of the data is delivered through interactive MMS access. At the same time, it is demonstrated how this is achieved using newlydeveloped presentation methods. Note, that this navigational path is not restrictive, and can be overridden at any point, via selection of a multi-menu link.
Project overview
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The project involved: Horizontal or Vertical Mixer Orientation; Incremental Stirrer Complexity for One Stirrer Concentric, One Stirrer Eccentric, Two Stirrers Eccentric, Two Stirrers Eccentric with Baffles; Viscous and Viscoelastic Fluidtypes; Speed of Kneading of 12.5, 25, 50 and 100 rotations per minute; 3D Investigation of the flow across depth for multiple planes; Fully-filled and part-filled mixing; Free-surface in two and three dimensions, including transient development of the free surface; Stirrer shapes that include Full-Stirrer, Half-Stirrer Horizontal, Half-Stirrer Vertical ([19] [20]) 1
VF, HF, VP, HP indicate access to and from Vertically Filled, Horizontally Filled, Vertically Part-filled and Horizontally Partfilled geometries, respectively. Z0 to Z5 indicate intersecting planes, sliced through the vessel. N, IN, VE indicate Newtonian, Inelastic and Viscoelastic fluid choices. VR, SR represent rotation-type, Vessel Rotating or Stirrer Rotating. R1 to R8 are Reynolds Number values, indicating Speeds of Rotation (12.5, 50, 100, and 200 rpm, respectively). C is a combinative-node option, for each of depth, speed, fluid or rotation-type considerations. All links to external sections are suppressed within sub-graphs. Also, all nodes within a sub-graph are linked forming an internally fully-linked sub-structure.
[“Project Summary” option, Figure 1]. Slides showing the extent of analysis are displayed [Figures 7 to 11]. The research plan summarises the simulation and experimental tasks undertaken within the remit of this case study. With simulation tasks, the intricacy of investigation is amplified, as setting adjustments draw closer to real-life situations. Initially, results were generated for model fluids, modelled in a two-dimensional setting, and simplified mixer-geometries. Further investigations included three-dimensional and free-surface modelling. The simulation results at each stage, were validated against those generated from actual kneading experiments. Fully-filled and part-filled cases were considered, in both vertical and horizontal mixer orientations. In industry, the horizontal setting is used for biscuit making, and vertical for bread (production) kneading Experimental fluids cover [Figure 7]: model-fluids (for transparency), model-doughs (for material time-independency), to actual industrial doughs. Each of the above considerations consists of various geometrical and parameter adjustments of incremental complexity [Figure 8]. Fluid model representation ranges from Newtonian to inelastic, and finally, to viscoelastic (viscous to viscoelastic) [Figure 9]. Adjustment of geometry and modelling complexity transcends from one stirrer, concentric to the final case of two stirrers, eccentric, free surface [Figures 9 and 11]. Incrementation through experimental studies is outlined in [Figure 10]. Numerical modelling considered the following scenarios: Viscous Filled (2D, 3D); Viscous Part-Filled (2D, 3D); Viscoelastic Filled (5 Fluids, 1 Stirrer, 2 Stirrers) [Figure 11]; Viscoelastic Filled (Full Stirrer, Horizontally Shaved Stirrer, Vertically Shaved Stirrer) (not shown).
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Figure 11 Five industrial companies provided industrial trial data and the interdisciplinary research cross-referenced INNFM experiments at Aberystwyth with modelling/visualisation at Swansea. The main aims were to: analyse the stirring of dough; gather information on mixer-design choice; relate this against dough rheology; predict how to maximise stretching work input to the dough and enhance the build-up of material structure (i.e. kneading). Kneading, is itself a key aspect to the overall manufacturing procedure.
The MMS accommodates experimental and computer-generated animations, including synchronised graphs with animations. In addition, the diversity of data and lack of standards had to be resolved, when animated streams are generated. New MM mechanisms, designed for synchronised presentation of animated data, were sought for this case study. A further highly-desirable MMS characteristic is the ability to navigate through the data on-demand, using minimal steps to reach the desired information. This demands investigation into the data complexities2, to program interaction routes into the MMS that fulfil minimum path-length criteria. The use of graphs, met the required topological representation, enabling optimal navigation and interconnectivity across data-content. A variety of abstraction levels were considered: from interaction between major data-sections, to interaction at the deepest level among data-instances. 2 . 1 Accessing the data Perspective static views of flow patterns are illustrated for a filled, one-stirrer mixer, with anti-clockwise vessel-rotation, shown half-way up the mixer at 50 rpm (a standard speed and model inelastic fluid) [Figure 12, cc.2]. Asymmetrical structure is apparent with an off-centre vortex: pressure, shear-rate and rate-of-work extrema are localised to the stirrer. As above, each menu icon is, in fact, part of a programmed network (a graph) of the presentation (covering variation in speed, height, material and rotation-type). This case can be contrasted against the two-stirrer instance, upon user-selection of the two-stirrer geometry [Figure 13]. The mixer-geometry is sampled with two-dimensional horizontal slices indicated as Z0 [the base of the mixer] to Z5, the lid of the mixer, with equal separation gap between each, and all normal to the stirrers. Variation across depth is studied through a comparison between results across planes, Z0 to Z5. The default plane of reference is the central Z2-choice; idealised to 2D and removed from end-effects. Interrogation of depth-variation reveals the regional changes encountered within the mixer. This casts light upon localised field variable distribution. This renders a deeper understanding of the flow and process as a whole, and demonstrates the three-dimensional aspects. Some symmetry is observed about the stirrers and a central figure-of-eight vortex pattern emerges.
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Depth-wise investigation
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Data complexities are defined in this context as the set of relations between MM-frames. Each frame containing a set of cast members (multimedia or static data-types), is classified as a single data-instance.
Three-dimensionally information, enable appreciation of depthwise-distribution in rates of shear, extension and work, against stirrers and lid [Figure 14, cc.4]. Here, 3D data for the two-stirrer configuration are displayed. Pressure varies mainly about the stirrers; deformation in shear and extension, likewise, are localised to the stirrers; shear-rate maxima at the lid, extension-rate at the lid and vessel-bottom; rate-of-work done follows the shear deformation, being localised within the narrow-gap section between stirrer and vessel-wall, towards the lid. In the two-stirrer case, the result is symmetrical and localised close to the stirrer. A characteristic animation state can be accessed by selecting the arrow next to the depth-options. Minimal change is reflected in streamline-patters, indicated using animation for one-stirrer and twostirrers, through depth.
Synchronisation: Simulation and Experiment An advanced MM feature offered, is the property of data synchronisation, that may be achieved in a variety of ways. So, for example, animations may be synchronised to present information, comparatively. Extensive use of this feature is evident throughout the MMS. Every effort has been made to present information in a concurrent mode, wherever possible. Generally, animation re-timings [3] must be introduced, to synchronise concurrent clips. This method is not restrictive, as other implementations are cited in the literature [17]. The objective is to present multiple animations, so that at any given instance, the information provided relates to the same parameter. The parameter can be any attribute within the particular case study. For example, from the layer used (observing the flow through depth), to speeds (where all clips must be provided for the same speeds). To achieve this objective, control over streams is required, in terms of frame-rate, precise timing to stop/start and control over displayed size. Comprehension of display is aided by synchronous labelling. 2 . 2 Speed-wise interrogation Animated views, passing through increased speeds, allows the direct cross-reference of simulated data, in pressure, extension-rate and motion-blur fields, against experimental flow visualisation (bottom-left, stirrers indicated) [Figure 15, cc.5]. The correspondence in vortex structure is striking. Motion-blur clips at four, set speeds of vessel rotation [Figure 16, cc.6], identify the twisting of the vortex structure with increased speed (in the direction of rotation). This is corroborated in high-speed camera, laser-scatter stills of 1% cmc fluid [Figure 17, cc.7].
Figure 15, cc5 At 50 rpm, the motion-blur flow patterns between one- and two-stirrer mixers may be contrasted (on the left), whilst also taking the industrialist’s view with stirrers rotating (on the right) [Figure 18, cc.8]. The variation of mixer speed is given under Reynolds number representations of 2,4,8 and 16, which translate to speeds of 12.5, 25, 50 and 100 revolutions per minute, respectively. Mixing-speed is highlighted, within the MMS, at the bottom of the “Multi-Menu”. By selecting the individual speed-icons, streamline simulation, experimental laser animation, pressure animation and static three-dimensional extension-rate results are presented, simultaneously [Figure 15, cc.5]. The streamline and pressure simulation results, are animated through speeds, thus the information presented, steps synchronously through the various settings automatically. Typically in PPT, external applications must be used to display individual animations and synchronisation is barely possible. Precise frame-based PPT animation synchronisation can be achieved, through rendering of the individual streams into a single stream. However, this is an exhaustive procedure, both in terms of time and computation.
Simulation versus Experimental Data A variety of techniques were used, for the collection of experimental data, ranging from measurements to identify fluid surface position, to full flow video-footage. The allocation of these experimental data has been in comparative mode to simulation results (taking precedence), for immediate cross-reference. In some isolated instances, experimental results alone are presented. The interface is designed to allow the immediate comparison of simulation results through the “Multi-Menu” construct. Additional interactive buttons are provided, wherever this mechanism is less than adequate. An example is the experimental speed-adjustment results [Figure 17], demonstrating the “figure-of-eight” streamline pattern
visualised, and its change of orientation as the speed increases, for the two-stirrer eccentric case. Figure 16 [cc.6], depicts the comparatively organised motion-blur results when speed increases from Re=2 to Re=16 (25 rpm to 200 rpm). The most interesting flow characteristic that can be observed with this image organisation is the rotation of the figure-of-eight towards the stirrers, as the speed is increased. Upon comparison of the simulation figures with the experimental images (versus Figure 17, cc.7), the same qualitative trends are observed. Note that, the orientation of the stirrers is not aligned at the same position in both experiment and simulation. This far, the vessel has been rotating and the stirrer is fixed. This approach is more straightforward to model, demanding less computational effort as re-meshing is avoided. Industrial-settings usually involve the opposing scenario, a movingstirrer and fixed-vessel. Therefore, numerical inversion of the process was performed to verify that under these rotationconditions, simulation results are close to experimental-type flow-characteristics. Figure 18, [cc.8] displays an animated frame, presenting both settings comparatively. The results follow physical expectation.
Figure 16, cc6
Figure 17, cc7
This comparative multi-media feature is powerful. It enables direct parametric contrast and data-evaluation. Equivalent functionality could only be accomplished with propriety software (PPT), by sequencing the information in-order (copying out of context), or via slide duplication. Either option, would result in considerable increase in PPT file-size.
Figure 18, cc8 2 . 3 Free-surfaces: mixer-speed variation Within other instances of the case study, for example “free-surface, one-stirrer”, various speeds of rotation can be selected. The selection refreshes the surface animation sequences and the graphical animation, with the appropriate data. The consequence of this presentation method is that the programmed system, displays the information in on order dictated by the user. This is convenient when comparisons are made between settings, or across instances. Next, we turn to the vertical, part-filled instance (for bread-making), with a central-stirrer, vessel rotating and compare the final-rise, surface-position graphically against experiment. Agreement is encouraging. Similarly, we may combine cases with three set-speeds, 25, 50 and 100 rpm, to demonstrate variation of fluid height-rise at the outer-vessel. Such results are obtained by modelling the peeling-off and wetting-onto the surfaces, via the adjustment of fluid-surface linesegments, according to their stretch and angle from the solid boundary. Relief of limiting stretch, also relieves critical boundary stress-levels.
Figure 19, cc9
Figure 20
Figure 21, cc10 These figures demonstrate the power of interaction across settings. Figure 19 displays the 25rpm setting. Figure 20 provides the 100rpm speed-setting data, with transient free-surface profile evolution as recorded in line-graph form. Clearly, one can observe that the higher speed-setting, generates greater rise in the fluid free-surface. The animated nature of the data enables the viewer to appreciate that, the vessel is rotating and not the stirrer. It is not necessary to indicate direction/driving motion, as required in static format (journal papers/reports). Within figure 21 [cc.10], comparative visualisation of the simulated, steady-state free-surface profiles, contrasts the results, for various speed-settings, with the experimental measurements charted in graphs below. When considering partfilled cases, the free-surface was modelled in both vessel-orientations, horizontal and vertical. Modelling and computer visualisation was an integral part of the research conducted, demanding new combinations of techniques to visualise flow-surfaces. The experimental and simulation studies generated concurrent results in many instances, for flows of identical setting and variables. This enabled comparison. When experimental and simulation results are presented simultaneously, it is imperative to ensure that the information is compatible. An example where comparison of surface-line profiles illustrates the proximity of the simulation results to their equivalent experimental measurements is described below. Close observation reveals that the levels of fluid were not identical, and the shape of the lines reflect a higher Reynolds number for the ex-
perimental case [Figure 21, Simulation Re=16, Experimentation Re=18]. This is best demonstrated at the maximum speed of 200rpm, in the bottom, blue lines.
Figure 22
Figure 23, cc11
Figure 24, cc12
Figure 25
The resulting particle-seeded images from the visualised simulation data are displayed in Figure 22 (three-dimensional, steady-state, axisymmetric, rendered animation model). This is viewed from a fixed angle, towards the centre of the vessel, demonstrating the identical surface characteristics as those in the experimental image. Algorithmic details to impose wetting and peeling involving free-surfaces, is covered in figure 23 [cc.11]. Here conditions can be allocated to sets of fluid-particles that make contact with the surfaces, to represent and control both peeling and wetting. A more complicated vertical scenario is that with a single, eccentric-stirrer (vessel-rotating). A surface triangulation (heavy on graphics) illustrates the complex shapes encountered [Figure 24, cc.12]. Different viewing angles, with lighting and shading, indicate the surface rise ahead of and dip behind the stirrer. These validate our predictions. The four simulation images [Figure 25], taken at different viewing angles, can be contrasted against the experimental single-speed of 150 rpm. The experimental views of Figure 26 (still photographs), cover a single viewing angle at four speed-settings, for corresponding steady-states. There is increased contortion of the surface as speed gathers. Similar flow characteristics can be observed in both sets of static images. Some volume of material is located in front of the stirrer and two almost symmetric dips are located at the backside of the stirrer, towards the centre of vessel. The experimental buildup of surface structure is more clearly conveyed as animated from a rest-state at 250 rpm vessel-speed. This flow videofootage is instigated by mouse-click upon the central-frame of Figure 26. In contrast, horizontal mixing (used for biscuit-making), may be viewed from one end at four different times [Figure 27, cc.13]. Here, we detect wetting/peeling at the outer-vessel and peeling from the stirrer, as time progresses. First, we view the simulation through an animation clip [Figure 28]. The wetting/peeling at the outer-vessel is a dominant feature. This may be contrasted against the corresponding experiment for a syrup at 50 rpm [Figure 29]. The surface attachment structure around the inner-section of the stirrer and the central, flat surface-shape are finer detail to capture. Even these particu-
lar details may be predicted, by careful, localised adjustment of control parameters (a) for the inner and outer stirrersections (left-image, constant factor; right-image, dynamic setting, Figure 30).
Figure 26
Figure 27, cc13
Figure 28, cc14
The corresponding results from the simulation and experiment, reflect close agreement. These animated clips allow the user to compare the similarity in evolutionary development and final position of the free-surface (i.e. in time). With the one-stirrer eccentric case, the complexity of visualisation increases, because there are no symmetries within the associated images. Video-footage of the experimental data (available for three speed-settings: 25, 50 and 100 rpm) is activated via bottom-screen button-selection and displayed in the central window, Figure 29, conveying fluid surface movement in time, as the vessel is rotated from a flat rest-state. The fluid is Newtonian in these instances. Figure 30 [cc.16] displays the free-surface position when peeling conditions are adjusted about the stirrer. Adjustment in a-value, and the corresponding visualised result for previous and final setting, are presented comparatively. 2 . 4 Fluid-type comparison The range of materials is broad, varying from inelastic to viscoelastic test-fluids to real-life dough. An example of a combined-menu instance (left-screen) is presented in Figure 31. The menu-choice illustrates (central-window) the corresponding data relating to fluid-type variation. The fluids under consideration are Newtonian versus Inelastic, observed on the Z2-plane for the fully-filled variant, with vessel-rotating at 50rpm. This is equivalent to the setting of Reynolds number 8. The frame-title reflects the data-type being displayed.
Figure 31
Figure 32
Viscous Section By selecting the “Newtonian” button, the MMS directs the user to the “torque versus time” graphical comparison. This illustrates contrast between Newtonian and inelastic materials, for the 50rpm setting. It is the only such data-set available for Newtonian materials; hence, selected by default. When the one-stirrer, eccentric button is selected next, corresponding, “torque versus time” one-stirrer data is provided (variable-priority rule applied). An additional link is provided with the cross-referencing arrow, under the “Newtonian”, “inelastic” and “viscoelastic” buttons. The arrow menu-choice is employed to cross-reference information relating to two, or more cases. Appropriate data are presented within the central window. This enables the comparative presentation of results, for example across geometries or materials. Figure 32 contains a comparative data-combination example, with one and two-stirrers, eccentric, torque versus time trace and Motion-Blur animation. 2 . 5 Viscoelastic Analysis 2D viscoelastic results are available for one and two-stirrer cases, and for three-stirrer geometries: full-stirrer, halfhorizontal and half-vertical. In addition, data have been computed using parallel processing ([1] [2]). General presentation slides, related to the parallel algorithmic implementation, can be accessed from within the viscoelastic section, and the main menu. The viscoelastic section can be accessed from both one and two-stirrer, multi-menus (viscous section). Viscoelastic results are also compared across different model fluids and geometries. The comparison is enabled, upon selection of the “Viscoelastic” option within the “Multi-Menu” construct; or alternatively from the “Viscoelastic” icon [Figure 31, one or two-stirrer eccentric, viscoelastic option]. Results for filled, one-stirrer and two-stirrers, eccentric cases are displayed directly, for variables of shear-rate, pressure and stresses (radial stress t rr, hoop stress t qq, and shear-stress t rq). The results range across five viscoelastic fluid-models: LPPT (0.02), LPPT (0.025), EPTT (0.02), EPTT (0.025) and OLDROYD-B. The notation implies Phan-Thien/Tanner models (PTT), of linear (L) or exponential (E) form. The MMS allows direct-access to any stirrer setting, model and variable, via the use of the bottom-screen-menu with icon-buttons. This mode of interaction enables the selection of different models, whilst results for selected flow variables are displayed.
One and two-stirrers Having entered the viscoelastic section [Figure 33, cc.17], navigation across five model fluids is provided. With the use of the local multi-menu options, to switch between model fluids, one may compare results across component stresses, pressure and shear-rate for all five models. A link allows direct-access to all five-models for increase of Weissenberg number, using a tree-like structure. At the top-level of this section, without model selection, general information relating to all five models is displayed. Upon fluid-model selection, rheological properties for that particular fluid are presented. A further choice of variable is required to display data from a palette of icons. With a selected model, material function plots of ms(g) and m e (e) appear. In addition, links may be activated to further field-variable data inclusive of: Shear-rate •
( g ), rate-of-work-done (rwd), pressure (p), radial stress (trr,) hoop stress (tqq), and shear-stress (trq). Within these MM frames, the data are presented in three or four-up format, with increasing Weissenberg number. “Comb-1S “and “Comb2S” buttons allow direct interaction between one and two-stirrer results, for all PTT models of the study. Data in both visualised and tabular format, are available within the slide-sorter. At each child-frame, one may toggle between one- and two-stirrer information. The data presented will remain of the same type, switching to selected geometry. The “We Var” button links to data for only the EPTT (0.25) model. Component stresses, pressure and shear-rate data are available, with variation of Weissenberg setting in the range of values 1 to 3.
Figure 33, cc17
Figure 34, cc18
The two-stirrer section maps the organisation adopted for one-stirrer. [Figure 34, cc.18]. Hence, the utilisation of the MMS allows interaction with the data selectively, and more importantly, across cases. This interface feature can be used to demonstrate the difference the introduction of a second stirrer in mixing flows can have for the materials under consideration. Data in tabular format are also accessible for one- and two-stirrer geometries [Figures 35 and 36, cc.19 and cc.20]. These display simulation measurements of shear-rate, local rate-of-work and power. Tabulations of localised work-input for the double-stirrer case, reveal that elastic work (stretching, shown in red) is dominated by viscous work (shown in blue). Here, shear influences prevail in the totalled work-input. In contrast, the asymmetric, single-stirrer design provides ten-times the elastic to viscous work: this is amplified for fluids with some strain-hardening (as occurs with dough). At this point, we arrive at a crucial observation: optimal kneading for dough is achieved with more asymmetrical mixer designs, one-stirrer better than two. More complex stirrer shapes are usual. In this respect, we observe for realistic dough that flat-bottomed, half-stirrer shapes, produce better results (see below).
Figure 35, cc19
Figure 36, cc20
Stirrer-shape adjustment At the final point of the cc tour, attention was given to more dough-like, viscoelastic materials, and filled scenarios. A further aspect of investigation within the Viscoelastic section, is that concerning stirrer-shape for those more dough-like materials. In particular, contrasting how this affects the flow, and ultimately, the process design being modelled. Stirrer adjustment appears in the “mixing with two-stirrers and baffles” section, hence the selection-icon is appropriately positioned and designed to reflect the available link. Three stirrer-shapes have been considered: full, horizontal-shaved and vertical-shaved [Figure 37, cc.21]. Here, we may observe the stretching and shear stresses across the mixer for a singlestirrer design, or one with a double-stirrer. Maxima in stress are localised about the stirrer, in the narrow-gap between stirrer and vessel; the hoop stress dominates. Three menu sections can be utilised, each with different organisation of the data. The first menu is selected already, within the stirrer-shape, adjustment section. It consists of three slides that present general model information, and the bottom-right corner-palette of buttons can be used to present a range of further choices. Again, individual data-instances can be accessed using the icon-options. This time, results are displayed in comparative view across the three stirrergeometries. For a selected variable, data for Newtonian, inelastic and viscoelastic fluids are accessible upon selection of a
different setting from the multi-menu. The buttons “E-F1S”, “E-H1S” and “E-V1S” allow direct-access to the results for each stirrer-shape individually. The results are organised into sets of visualised images. One, that combines shear-rate, pressure and rate of work-done for the same stirrer-shape. Another, for component stresses, and additional MM-frames, that group together numerical results in tabular form, streamline and colour-filled-streamline-plotted images. These are all accessible upon selection of the bottom-right link-palette, programmed to reflect the data within the current presentation mode. The third menu enables the comparison of streamline results for a given stirrer-setting, across different fluids. It is located next to the button-palette, and consists of three slides. Each with three Weissenberg number settings, across Newtonian, inelastic and viscoelastic model-fluids.
Figure 37, cc21 3 . COMBINING DATA TYPES The visualised data units, require commonly available organisation methods, for easy identification and referencing. External (PPT) software was used, enabling explanatory data to be inserted directly. Sending the generated file (with all the information embedded), using electronic mail transfer was the usual route to receive and organise the data. This proved to be generally better understood and straightforward to implement. Cross-platform compatibility and a simple modus operandi render this tool useful for storage and transportation of images and static data. Other data (animations), had to be compressed separately and transferred across file-systems. The organisation of the MMS-data, was performed in a similar manner. The related MMS-section had to be identified. This was effortlessly achieved by following the menu choices: first, to the appropriate vessel orientation, followed by the stirrer complexity, and lastly, the particular related variable to the new information supplied. The next step was to identify secondary reference links. The graph-structure was used extensively to determine links between the various sections of the MMS. At this point, the nature of the data determines the links to other frames. Testing and cruise-control links are the final tasks required to complete the system.
Solid-modelling with simulation data Simulation and solid-modelling visual results often had to be combined for realism. Additionally, in many cases, the experimental results do not appear in two-dimensional slices; instead, in three-dimensional real-life video-footage. The aim here is for numerical predictions to be presented in a comparative and realistic manner, similar to that of the experiment. One solution is achieved via the use of solid-modelling, with rendering software for the creation of threedimensional representations, based on simulated data. For this Dough-Kneading case study, a number of solid-modelling techniques were utilised. As discussed above in figure 22, for free-surface representation, simulated three-dimensional free-surface results are combined, with surface visualisation, to generate an animated computer visualisation. This image was generated in two stages. Initially, free-surface positions were represented as three-dimensional spherical-particles in space3. These particles were rendered with the same camera-orientation as that of the solid model. Subsequently, rendered versions were animated as a background to the solid model, for different particle-positions. Finally, resulting renderedframes were used as a basis to create a full-360° animated-rotation. Variable combination on-demand On-demand variable combination is one powerful feature that MMEs introduces, here applied for multimedia content, as opposed to traditional hypermedia applications [9]. Programming such a feature with non-multimedia orientated software, is generally impractical and time-consuming. Therefore, it was necessary to develop techniques for efficient framelinking (see Scientific Interactive Multimedia Model/Framework, SIMM/SIMF [26]). The flexibility of such an implementation is more powerful than that achieved with traditional sequential implementations, for complicated presentations. In addition, the lack of control over the multi-media data (including re-timings) requires synchronised streams. In 3
X, Y, Z coordinates were plotted in space as spheres, and animated through viewpoint-rotation using PovRay.
turn, this is difficult to achieve, if streams originate from a variety of sources. The drawback of such an approach lies with the number of links that must be programmed to support non-sequential frame-access. The solution to this obstacle, demanding reprogramming of multiple-links, was reached through object-oriented MM frame-creation. Links are separated into two sections: those relating to the global presentation, and those relating only to local, current frame-data. The problem of frame-linking appears when a parent-frame is used to create a child MM-frame. Global links must be fully-defined within the parent-frame, before the child-frame global-links are completed, and only local-link programming remains. This enables rapid creation of fully-functional child MM-frames. Global-links are localised to the multi-menu construct. Local-links are programmed with the icon-palette at frame-bottom. Although in this instance, the menu-location is separate, these may be blended within a single menu. 4 . IMPROVING SYSTEM PERFORMANCE System performance becomes important, with the introduction of multiple, large, simultaneously displayed and synchronised data-streams. Presentation delays, slow animation frame-rate and system failures are typical. Investigating how system performance can be improved to accommodate such processing strain is critical. Comparison between PPT and MMS technologies when dealing with complex data is required in the corresponding areas of: stream storage/retrieval, stream synchronisation and multiple-stream presentation. Here, large streams are considered. Implementation cost is reduced, by avoiding hardware-based system improvements [22]. Instead, software-based boosts to overall system performance are presented.
Stream storage/retrieval Data-streams can be stored, both locally (hard disk drive) and remotely (via TCP/IP connection) and accessed on-demand, when using both PPT and MME technologies. The choice of processor, speed and type, operating system, size of random-access memory, bus-size and hard-disk speed can all affect hardware performance. Most of the problems encountered within stream storage/retrieval can be corrected with stream-optimisation techniques, software algorithms for streamrendering. The result of this procedure generates streams of reduced size, that require less data-transfer per time-unit. Typical, is the example encountered within the MMS [Figure 15]. The two-stirrer, speed-variation section is illustrated using four animated-streams of different data-types. MB and pressure, animated in two-dimensions, and extension-rate, animated in three-dimensions, through speed-variation. These simulated results are complemented with an experimental digitised video-footage of the actual flow for a fixed speed-setting. The original experimental video-stream, in its raw format, was 115 megabytes in size, without compression. Its total play-length was 30 seconds. The repetitive nature of the footage, enabled the animation to be partitioned into smaller sections, from which only an 8 second partition was selected for the MMS. This first-step reduced the file-size by approximately 1/3 of the original size. Then, a further video-stream compression algorithm was utilised (Indeo 5.1 codec), that reduced the stream to approximately 12 Mbytes. Reduction is achieved to approximately 10 per cent of original size. This enables the MME to load the whole animation within system memory and avoid caching using the hard-disk (a very time-consuming operation). Faster response-times are observed within PPT, when optimised streams are used for similar reasons. The disadvantage with PPT technology is that, when a stream is encapsulated more than once within a single presentation entity, the original data are stored doubly. This increases file-sizes enormously and can cause system failure for relatively simple presentations with multiple stream-instances. This is not the case with MME, that utilise a single-stream. Reference is made to the same, unique stream, when called from different frames. Stream synchronisation In figure 15, stream synchronisation is utilised. This enables the synchronised presentation of different streams in relation with a common changing setting (here speed) [13]. Close observation reveals that motion-blur animations are displayed and synchronised to those for pressure. When the two animations are played independently, using an external animation player, the two streams are of different time-lengths. To set the desired frame-rate for each animation, retiming is utilised. An animation with 60 frames and an animation with 30 frames can be synchronised if the faster animation is played at double the frame-rate. Commonly, this is not a practical option, as current realistic frame-rate for personal computers (without dedicated hardware), do not exceed 30 frames per second. A remedy is to program the MME to skip every second frame, so that re-timing is achieved. This approach requires sufficient computation power and relatively small-sized streams, else caching will force the MME to drop frames. On the other hand, our favoured option is to achieve the same effect by removing every second frame from the faster animation, an operation reducing the stream-size by one-half. Performance can be improved further at the interface level. Avoiding overlapping animations enables direct-drawing techniques to be utilised. Also, with the introduction of multiple streams, using common data-format, faster decompression is accessed as the same algorithm is used to process all streams. In the main, algorithmic improvements are sufficient to improve overall system performance. This is a key factor for the distribution of MMS technology. The wide availability of the ‘so-called’ personal computer, with basic multi-media capabilities as standard, is sufficient. 5 . CONCLUSIONS AND FURTHER DOUGH-MMS ENHANCEMENTS A number of enhancements have been incorporated into the MMS at later stages, to cover presentation requirements for a wide variety of target audiences. Multi-mode animation is available in “User-specified variable selection”, “Pre-defined order across main sections (orange cruise control)” and “Exhaustive, in-order navigation (red cruise control)”. Al-
though these navigation options enable multiple-modes of interaction, (where combination is permitted in special cases), tightly specified order may be required. ‘Green cruise-control’ covers this contingency, where the pre-defined order of slides reflects presentation order. Hence, backward-compatibility is ensured, to more traditional, linear-presentation methods (PPT). This property alone categorises the MMS as superior to other linearly-ordered presentation methods. It sets the standards for interaction, prioritised in terms of data or user-selection. Beyond the implementation of a pre-defined order, a further iterative step, is the compilation of a voiceover. Digital recording and partitioning of the voiceover allows its incorporation into MM-frames. This, in turn, allows for dynamic demonstration with vocal explanation, relating to each individual frame. Figure 33 shows a characteristic frame that is part of the green cruise-control path, with VCR slide-bar controller for the digitised voiceover. Other enhancements include the delivery over different media. Internet delivery has been implemented efficiently through SHOCKWAVE [25]. The interface is fully-functional and streaming with compression is utilised to deliver multimediacontent. This client-server data-on-request approach, does not require the complete MMS contents to be downloaded before viewing. A few additional improvements may readily be incorporated. Using the client-server Internet contentdelivery approach, one may specify data to be accessed from different locations. Data may be stored locally. Once updated, the MMS will access and present the latest version. This non-centralised approach is particularly useful when the subject-matter is on-going and requires frequent updates. It follows the PREMO standard [11], which specifies data as non-centralised. Note, this does not guarantee all connections will be accessible, and may lead to lack of data for presentation.
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