3,347 research outputs found

    Using formal models to design user interfaces a case study

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    The use of formal models for user interface design can provide a number of benefits. It can help to ensure consistency across designs for multiple platforms, prove properties such as reachability and completeness and, perhaps most importantly, can help incorporate the user interface design process into a larger, formally-based, software development process. Often, descriptions of such models and examples are presented in isolation from real-world practice in order to focus on particular benefits, small focused examples or the general methodology. This paper presents a case study of developing the user interface to a new software application using a particular pair of formal models, presentation models and presentation interaction models. The aim of this study was to practically apply the use of formal models to the design process of a UI for a new software application. We wanted to determine how easy it would be to integrate such models into our usual development process and to find out what the benefits, and difficulties, of using such models were. We will show how we used the formal models within a user-centred design process, discuss what effect they had on this process and explain what benefits we perceived from their use

    Data-based fault detection in chemical processes: Managing records with operator intervention and uncertain labels

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    Developing data-driven fault detection systems for chemical plants requires managing uncertain data labels and dynamic attributes due to operator-process interactions. Mislabeled data is a known problem in computer science that has received scarce attention from the process systems community. This work introduces and examines the effects of operator actions in records and labels, and the consequences in the development of detection models. Using a state space model, this work proposes an iterative relabeling scheme for retraining classifiers that continuously refines dynamic attributes and labels. Three case studies are presented: a reactor as a motivating example, flooding in a simulated de-Butanizer column, as a complex case, and foaming in an absorber as an industrial challenge. For the first case, detection accuracy is shown to increase by 14% while operating costs are reduced by 20%. Moreover, regarding the de-Butanizer column, the performance of the proposed strategy is shown to be 10% higher than the filtering strategy. Promising results are finally reported in regard of efficient strategies to deal with the presented problemPeer ReviewedPostprint (author's final draft

    Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation and Experimentation

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    Among the many additive manufacturing (AM) processes for metallic materials, selective laser melting (SLM) is arguably the most versatile in terms of its potential to realize complex geometries along with tailored microstructure. However, the complexity of the SLM process, and the need for predictive relation of powder and process parameters to the part properties, demands further development of computational and experimental methods. This review addresses the fundamental physical phenomena of SLM, with a special emphasis on the associated thermal behavior. Simulation and experimental methods are discussed according to three primary categories. First, macroscopic approaches aim to answer questions at the component level and consider for example the determination of residual stresses or dimensional distortion effects prevalent in SLM. Second, mesoscopic approaches focus on the detection of defects such as excessive surface roughness, residual porosity or inclusions that occur at the mesoscopic length scale of individual powder particles. Third, microscopic approaches investigate the metallurgical microstructure evolution resulting from the high temperature gradients and extreme heating and cooling rates induced by the SLM process. Consideration of physical phenomena on all of these three length scales is mandatory to establish the understanding needed to realize high part quality in many applications, and to fully exploit the potential of SLM and related metal AM processes

    A Survey on Event-B Decomposition

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    Model decomposition is a powerful tool to scale the design of large and complex systems. It enables developers to separate components development from the concerns of their integration and orchestration. Event-B is a refinementbased formal method, equipped with three decomposition styles that come with solid semantic foundations and strong tool support. This paper intends to give some useful insights and modelling guidelines for using these decomposition styles, illustrated by an actual development of a master data updating system

    Formal design of data warehouse and OLAP systems : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems at Massey University, Palmerston North, New Zealand

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    A data warehouse is a single data store, where data from multiple data sources is integrated for online business analytical processing (OLAP) of an entire organisation. The rationale being single and integrated is to ensure a consistent view of the organisational business performance independent from different angels of business perspectives. Due to its wide coverage of subjects, data warehouse design is a highly complex, lengthy and error-prone process. Furthermore, the business analytical tasks change over time, which results in changes in the requirements for the OLAP systems. Thus, data warehouse and OLAP systems are rather dynamic and the design process is continuous. In this thesis, we propose a method that is integrated, formal and application-tailored to overcome the complexity problem, deal with the system dynamics, improve the quality of the system and the chance of success. Our method comprises three important parts: the general ASMs method with types, the application tailored design framework for data warehouse and OLAP, and the schema integration method with a set of provably correct refinement rules. By using the ASM method, we are able to model both data and operations in a uniform conceptual framework, which enables us to design an integrated approach for data warehouse and OLAP design. The freedom given by the ASM method allows us to model the system at an abstract level that is easy to understand for both users and designers. More specifically, the language allows us to use the terms from the user domain not biased by the terms used in computer systems. The pseudo-code like transition rules, which gives the simplest form of operational semantics in ASMs, give the closeness to programming languages for designers to understand. Furthermore, these rules are rooted in mathematics to assist in improving the quality of the system design. By extending the ASMs with types, the modelling language is tailored for data warehouse with the terms that are well developed for data-intensive applications, which makes it easy to model the schema evolution as refinements in the dynamic data warehouse design. By providing the application-tailored design framework, we break down the design complexity by business processes (also called subjects in data warehousing) and design concerns. By designing the data warehouse by subjects, our method resembles Kimball's "bottom-up" approach. However, with the schema integration method, our method resolves the stovepipe issue of the approach. By building up a data warehouse iteratively in an integrated framework, our method not only results in an integrated data warehouse, but also resolves the issues of complexity and delayed ROI (Return On Investment) in Inmon's "top-down" approach. By dealing with the user change requests in the same way as new subjects, and modelling data and operations explicitly in a three-tier architecture, namely the data sources, the data warehouse and the OLAP (online Analytical Processing), our method facilitates dynamic design with system integrity. By introducing a notion of refinement specific to schema evolution, namely schema refinement, for capturing the notion of schema dominance in schema integration, we are able to build a set of correctness-proven refinement rules. By providing the set of refinement rules, we simplify the designers's work in correctness design verification. Nevertheless, we do not aim for a complete set due to the fact that there are many different ways for schema integration, and neither a prescribed way of integration to allow designer favored design. Furthermore, given its °exibility in the process, our method can be extended for new emerging design issues easily

    CO-SOLVENT ASSISTED SPRAY PYROLYSIS FOR THE PREPARATION OF METAL MICROPARTILCE

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    Metal and bimetallic particles play an important role in catalytic, medical and electronic applications. Various techniques have been developed for the preparation of metal particles, including vaporization techniques, sonochemical, polyol method, mechanical alloying and spray pyrolysis. Compared with the other preparation techniques, the spray pyrolysis process has the advantages of easy scale up in industry, tunable particle size and controllable particle composition. Sometimes hydrogen was used in the process to promote the formation of metallic phase in a lower temperature, but it also created a potential safety problem. In order to eliminate the use of hydrogen, a cosolvent assisted ultrasonic spray pyrolysis process was developed, and ethanol (ET) and ethylene glycol (EG) are used as the cosolvent. In this study, the cosolvent assisted ultrasonic spray pyrolysis process was used for the generation of various oxide free oxide particles, and the reaction mechanism was shown. In the first part of this study, properties of ultrasonic droplet generator were investigated. Precursor solutions were atomized by a 1.7 MHz ultrasonic nebulizer. The droplet size distribution and atomization rate were measured. Relationship between droplet diameters and the physical properties were revealed by statistic tools. Bimodal droplets distribution was observed during the experiment. Then copper particles were generated by the spray pyrolysis process. Copper nitrate aqueous solution was used as the precursor and either ET or EG was used as cosolvent. Oxide free particles were generated at temperature from 400 oC to 1000 oC. It was noticed that particles morphology and formation process was strong affected by the properties of the cosolvents. In the following study, the spray pyrolysis process was successfully used for the generation of AgNi, CuNi and AgCu bi-components particles. Various particle structures were observed, and the structures were mainly determined by the thermodynamic properties of the particles components. In the last part of this dissertation, efforts mainly focused on the mechanism of AgCu particle generation. Reaction intermediates were collected. Reaction process from nitrates to pure metal and the phase separation behavior between Cu and Ag was demonstrated

    grain size influence on fatigue behaviour in a cuznal pe sma

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    Abstract Due to their capability to recover the initial shape, Shape Memory Alloys (SMAs) are widely used in many applications. Different grades are commercially available and they can be classified considering either their chemical compositions (Cu based, Ni based, Fe based and so on..) or according to their mechanical behaviour. The most used SMAs are the Ni based alloys thanks to their performances both in terms of mechanical resistance and in terms of fatigue resistance, but their costs are quite high. Cu based alloys are good competitors of the Ni based alloys. The recent optimization of their chemical composition improved both the corrosion resistance in aggressive environments and their mechanical performances. In this work, the influence of the grain size on fatigue crack propagation in two Cu-Zn-Al SMAs focusing on the damaging micromechanisms
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