Designing and Integrating a Digital Thread System for Customized Additive Manufacturing in Multi-Partner Kayak Production

Additive manufacturing (AM) opens the vision of decentralised and individualised manufacturing, as a tailored product can be manufactured in proximity to the customers with minimal physical infrastructure required. Consequently, the digital infrastructure and systems solution becomes substantially more complex. There is always a need to design the entire digital system so that different partners (or stakeholders) access correct and relevant information and even support design iterations despite the heterogenous digital environments involved. This paper describes how the design and integration of a digital thread for AM can be approached. A system supporting a digital thread for AM kayak production has been designed and integrated in collaboration with a kayak manufacturer and a professional collaborative product lifecycle management (PLM) software and service provider. From the demonstrated system functionality, three key lessons learnt are clarified: (1) The need for developing a process model of the physical and digital flow in the early stages, (2) the separation between the data to be shared and the processing of data to perform each parties\u27 task, and (3) the development of an ad-hoc digital application for the involvement of new stakeholders in the AM digital flow, such as final users. The application of the digital thread system was demonstrated through a test of the overall concept by manufacturing a functional and individually customised kayak, printed remotely using AM (composed of a biocomposite containing 20% wood-based fibre)

Opportunities for Dutch Biorefineries

Deze Roadmap Bioraffinage beschrijft een aantal mogelijke routes naar de ontwikkeling en implementatie van een bioraffinage-gerelateerde Bio-based Economy in Nederland. De Roadmap combineert korte- en middellange termijn mogelijkheden (commerciële implementatie, demonstratie plants, pilot plants en gerelateerd toegepast onderzoek) met strategisch onderzoek voor de langere termijn. Tevens zijn vier z.g. Moonshots uitgewerkt, als voorziene bioraffinagestrategieën met een grote potentie voor de Nederlandse economi

Building Programmable Wireless Networks: An Architectural Survey

In recent times, there have been a lot of efforts for improving the ossified Internet architecture in a bid to sustain unstinted growth and innovation. A major reason for the perceived architectural ossification is the lack of ability to program the network as a system. This situation has resulted partly from historical decisions in the original Internet design which emphasized decentralized network operations through co-located data and control planes on each network device. The situation for wireless networks is no different resulting in a lot of complexity and a plethora of largely incompatible wireless technologies. The emergence of "programmable wireless networks", that allow greater flexibility, ease of management and configurability, is a step in the right direction to overcome the aforementioned shortcomings of the wireless networks. In this paper, we provide a broad overview of the architectures proposed in literature for building programmable wireless networks focusing primarily on three popular techniques, i.e., software defined networks, cognitive radio networks, and virtualized networks. This survey is a self-contained tutorial on these techniques and its applications. We also discuss the opportunities and challenges in building next-generation programmable wireless networks and identify open research issues and future research directions.Comment: 19 page

Traffic monitoring using image processing : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Information and Telecommunications Engineering at Massey University, Palmerston North, New Zealand

Traffic monitoring involves the collection of data describing the characteristics of vehicles and their movements. Such data may be used for automatic tolls, congestion and incident detection, law enforcement, and road capacity planning etc. With the recent advances in Computer Vision technology, videos can be analysed automatically and relevant information can be extracted for particular applications. Automatic surveillance using video cameras with image processing technique is becoming a powerful and useful technology for traffic monitoring. In this research project, a video image processing system that has the potential to be developed for real-time application is developed for traffic monitoring including vehicle tracking, counting, and classification. A heuristic approach is applied in developing this system. The system is divided into several parts, and several different functional components have been built and tested using some traffic video sequences. Evaluations are carried out to show that this system is robust and can be developed towards real-time applications

Shape-based defect classification for Non Destructive Testing

The aim of this work is to classify the aerospace structure defects detected by eddy current non-destructive testing. The proposed method is based on the assumption that the defect is bound to the reaction of the probe coil impedance during the test. Impedance plane analysis is used to extract a feature vector from the shape of the coil impedance in the complex plane, through the use of some geometric parameters. Shape recognition is tested with three different machine-learning based classifiers: decision trees, neural networks and Naive Bayes. The performance of the proposed detection system are measured in terms of accuracy, sensitivity, specificity, precision and Matthews correlation coefficient. Several experiments are performed on dataset of eddy current signal samples for aircraft structures. The obtained results demonstrate the usefulness of our approach and the competiveness against existing descriptors.Comment: 5 pages, IEEE International Worksho

Building Efficient Query Engines in a High-Level Language

Abstraction without regret refers to the vision of using high-level programming languages for systems development without experiencing a negative impact on performance. A database system designed according to this vision offers both increased productivity and high performance, instead of sacrificing the former for the latter as is the case with existing, monolithic implementations that are hard to maintain and extend. In this article, we realize this vision in the domain of analytical query processing. We present LegoBase, a query engine written in the high-level language Scala. The key technique to regain efficiency is to apply generative programming: LegoBase performs source-to-source compilation and optimizes the entire query engine by converting the high-level Scala code to specialized, low-level C code. We show how generative programming allows to easily implement a wide spectrum of optimizations, such as introducing data partitioning or switching from a row to a column data layout, which are difficult to achieve with existing low-level query compilers that handle only queries. We demonstrate that sufficiently powerful abstractions are essential for dealing with the complexity of the optimization effort, shielding developers from compiler internals and decoupling individual optimizations from each other. We evaluate our approach with the TPC-H benchmark and show that: (a) With all optimizations enabled, LegoBase significantly outperforms a commercial database and an existing query compiler. (b) Programmers need to provide just a few hundred lines of high-level code for implementing the optimizations, instead of complicated low-level code that is required by existing query compilation approaches. (c) The compilation overhead is low compared to the overall execution time, thus making our approach usable in practice for compiling query engines