Model-Driven Development of Interactive Multimedia Applications

The development of highly interactive multimedia applications is still a challenging and complex task. In addition to the application logic, multimedia applications typically provide a sophisticated user interface with integrated media objects. As a consequence, the development process involves different experts for software design, user interface design, and media design. There is still a lack of concepts for a systematic development which integrates these aspects. This thesis provides a model-driven development approach addressing this problem. Therefore it introduces the Multimedia Modeling Language (MML), a visual modeling language supporting a design phase in multimedia application development. The language is oriented on well-established software engineering concepts, like UML 2, and integrates concepts from the areas of multimedia development and model-based user interface development. MML allows the generation of code skeletons from the models. Thereby, the core idea is to generate code skeletons which can be directly processed in multimedia authoring tools. In this way, the strengths of both are combined: Authoring tools are used to perform the creative development tasks while models are used to design the overall application structure and to enable a well-coordinated development process. This is demonstrated using the professional authoring tool Adobe Flash. MML is supported by modeling and code generation tools which have been used to validate the approach over several years in various student projects and teaching courses. Additional prototypes have been developed to demonstrate, e.g., the ability to generate code for different target platforms. Finally, it is discussed how models can contribute in general to a better integration of well-structured software development and creative visual design

Innovative Learning Environments in STEM Higher Education

As explored in this open access book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students. In 2018, Drs. Ryoo and Winkelmann explored the opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories: personalized and adaptive learning, multimodal learning formats, cross/extended reality (XR), and artificial intelligence (AI) and machine learning (ML). This open access book gathers the perspectives expressed during the X-FILEs workshop and its follow-up activities. It is designed to help inform education policy makers, researchers, developers, and practitioners about the adoption and implementation of ILEs in higher education

Updates in metabolomics tools and resources: 2014-2015

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources—in the form of tools, software, and databases—is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table

Digitised engineering knowledge for prefabricated façades

Façade design is a multidisciplinary activity requiring the balancing of many conflicting design requirements. Very often, however, the designed façade does not respond to these requirement, as relevant design and manufacturing knowledge, normally originating downstream in the design process, is not properly used upstream in the process. The inability to respond to this challenge increases the environmental impact of the construction sector, which is currently covering nearly 40% of the global emissions. Also, improving the stagnant sector’s productivity is of paramount importance today, as it is deemed to be nearly as half as that of the manufacturing sector. This research has thus investigated ways to collect, store, represent and digitalise the engineering knowledge that underpins the design of façade products for façades that are better designed. The work has involved a close collaboration with the British general contractor (and façade manufacturer) Laing O’Rourke. The research has explored ways of using design and manufacturing knowledge and it has developed a digital tool and tested its functionalities. In the first part, after a review of the state-of-the-art in knowledge-based approaches in other fields, the digital tool, and relevant methodology, are developed. The tool informs the user about the expected performance and manufacturability of the façade product under analysis. The boundaries of traditional research were also pushed beyond the proof-of-concept by validating the digital tool in both simulated and real-world scenarios. The goal was to understand how people can develop a design solution while being supported by a digital tool. It was found that using such tool increases the user’s awareness about the consequences of the his/her choices in less time. In the last part of the research, the tool was used to develop a novel optimisation algorithm, by including considerations about aesthetics and manufacturability, in parallel with the traditional performance-based approach. The application of the algorithm to a case study has shown that it is possible to improve existing solutions in terms of performance, without affecting aesthetic and manufacturability significantly.EPSRC, Laing O'Rourk

Assessing the effectiveness of managed lane strategies for the rapid deployment of cooperative adaptive cruise control technology

Connected and Automated Vehicle (C/AV) technologies are fast expanding in the transportation and automotive markets. One of the highly researched examples of C/AV technologies is the Cooperative Adaptive Cruise Control (CACC) system, which exploits various vehicular sensors and vehicle-to-vehicle communication to automate vehicular longitudinal control. The operational strategies and network-level impacts of CACC have not been thoroughly discussed, especially in near-term deployment scenarios where Market Penetration Rate (MPR) is relatively low. Therefore, this study aims to assess CACC\u27s impacts with a combination of managed lane strategies to provide insights for CACC deployment. The proposed simulation framework incorporates 1) the Enhanced Intelligent Driver Model; 2) Nakagami-based radio propagation model; and 3) a multi-objective optimization (MOOP)-based CACC control algorithm. The operational impacts of CACC are assessed under four managed lane strategies (i.e., mixed traffic (UML), HOV (High Occupancy Vehicle)-CACC lane (MML), CACC dedicated lane (DL), and CACC dedicated lane with access control (DLA)). Simulation results show that the introduction of CACC, even with 10% MPR, is able to improve the network throughput by 7% in the absence of any managed lane strategies. The segment travel times for both CACC and non-CACC vehicles are reduced. The break-even point for implementing dedicated CACC lane is 30% MPR, below which the priority usage of the current HOV lane for CACC traffic is found to be more appropriate. It is also observed that DLA strategy is able to consistently increase the percentage of platooned CACC vehicles as MPR grows. The percentage of CACC vehicles within a platoon reaches 52% and 46% for DL and DLA, respectively. When it comes to the impact of vehicle-to-vehicle (V2V), it is found that DLA strategy provides more consistent transmission density in terms of median and variance when MPR reaches 20% or above. Moreover, the performance of the MOOP-based cooperative driving is examined. With average 75% likelihood of obtaining a feasible solution, the MOOP outperforms its counterpart which aims to minimize the headway objective solely. In UML, MML, and DL strategy, the proposed control algorithm achieves a balance spread among four objectives for each CACC vehicle. In the DLA strategy, however, the probability of obtaining feasible solution falls to 60% due to increasing size of platoon owing to DLA that constraints the feasible region by introduction more dimensions in the search space. In summary, UML or MML is the preferred managed lane strategy for improving traffic performance when MPR is less than 30%. When MRP reaches 30% or above, DL and DLA could improve the CACC performance by facilitating platoon formation. If available, priority access to an existing HOV lane can be adopted to encourage adaptation of CACC when CACC technology becomes publically available

A feature-based approach to the Computer-Aided Design of sculptured products

Computer-Aided Design systems offer considerable potential for improving design process efficiency. To reduce the 'ease of use' barrier hindering full realisation of this potential amongst general mechanical engineering industries, many commercial systems are adopting a Feature-Based Design (FBD) metaphor. Typically the user is allowed to define and manipulate the design model using interface elements that introduce and control parametric geometry clusters, with engineering meaning, representing specific product features (such as threaded holes, slots, pockets and bosses). Sculptured products, such as golf club heads, shoe lasts, crockery and sanitary ware, are poorly supported by current FBD systems and previous research, because their complex shapes cannot be accurately defined using the geometrically primitive feature sets implemented. Where sculptured surface regions are allowed for, the system interface, data model and functionality are little different from that already provided in many commercial surface modelling systems, and so offer very little improvement in ease of use, quality or efficiency. This thesis presents research to propose and develop an FBD methodology and system suitable for sculptured products. [Continues.

Comparison of shipbuilding and construction industries from the product structure standpoint

Copyright © 2018 Inderscience Enterprises Ltd. The use of building information modelling (BIM) in construction compares to the use of product lifecycle management (PLM) in manufacturing. Previous research has shown that it is possible to improve BIM with the features and the best practices from the PLM approach. This article provides a comparison from the standpoint of the bill of materials (BOM) and product structures. It compares the product beginning of life in both construction and shipbuilding industries. The research then tries to understand the use, form and evolution of product structures and BOM concepts in shipbuilding with the aim of identifying equivalent notions in construction. Research findings demonstrate that similar concepts for structuring information exist in construction; however, the relationship between them is unclear. Further research is therefore required to detail the links identified by the authors and develop an equivalent central structuring backbone as found in PLM platforms

Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

The Materials Genome Initiative, a national effort to introduce new materials into the market faster and at lower cost, has made significant progress in computational simulation and modeling of materials. To build on this progress, a large amount of experimental data for validating these models, and informing more sophisticated ones, will be required. High-throughput experimentation generates large volumes of experimental data using combinatorial materials synthesis and rapid measurement techniques, making it an ideal experimental complement to bring the Materials Genome Initiative vision to fruition. This paper reviews the state-of-the-art results, opportunities, and challenges in high-throughput experimentation for materials design. A major conclusion is that an effort to deploy a federated network of high-throughput experimental (synthesis and characterization) tools, which are integrated with a modern materials data infrastructure, is needed

Application of knowledge based engineering principles to intelligent automation systems

The automation of engineering processes provides many benefits over manual methods including significant cost and scheduling reduction as well as intangible advantages of greater consistency based on agreed methods, standardisation and simplification of complex problems and knowledge retention. Knowledge Based Engineering (KBE) and Design Automation (DA) are two sets of methodologies and technologies for automating engineering processes through software. KBE refers to the structured capture, modelling and deployment of engineering knowledge in high level intelligent systems that provide a wide scope of automation capability. KBE system development is supported by numerous mature methodologies that cover all aspects of the development process including: problem identification and feasibility studies, knowledge capture and modelling, and system design, development and deployment. Conversely, DA is the process of developing automated solutions to specific, well defined engineering tasks. The DA approach is characterised by agile software development methods, producing lower level systems that are intentionally limited in scope. DA-type solutions are more commonly adopted by industry than KBE applications due to shorter development schedules, lower cost and less complex development processes. However, DA application development is not as well supported by theoretical frameworks, and consequently, development processes can be unstructured and best practices not observed. The research presented in this thesis is divided into two key areas. Firstly, a methodology for automating engineering processes is proposed, with the aim of improving the accessibility of mature KBE methods to a broader industrial base. This methodology supports development of automation applications ranging in complexity from high level KBE systems to lower level DA applications. A complexity editing mechanism is introduced that relates detailed processes of KBE methodologies to a set of characteristics that can be exhibited by automated solutions. Depending on individual application requirements, complexity of automated solutions can lowered by deselecting one or more of these characteristics, omitting associated high-level processes from the development methodology. At the lowest level of complexity, the methodology provides a structured process for producing DA applications that incorporates principles of mature KBE methodologies. The second part of this research uses the proposed automation methodology to develop a system to automate the layout design of aircraft electrical harnesses. Increasing complexity of aircraft electrical systems has an associated increase in the number and size of electrical harnesses required to connect subsystems throughout the airframe. Current practices for layout design are highly manual, with many governing rules and best practices. The automation of this process will provide a significant reduction in low level, repetitive, manual work. The resulting automated routing tool implements path-finding techniques from computer game artificial intelligence and microprocessor design domains, together with new methods for incorporating the numerous design rules governing harness placement. The system was tested with a complex industrial test case, and was found to provide harness solutions in a fraction of the time and with comparable quality as equivalent manual design processes. The repeatability of the automated process can also minimise scheduling impacts caused by late design changes