Interoperability requirements for automated manufacturing systems in construction

Multi-disciplinary software interoperability in the Architecture, Engineering, Construction and Operations industry is becoming a new and widely adopted business culture. Technical advances in interoperability architectures, frameworks, methods and standards during the last decade resulted in higher maturity of product and process models. Mature models, in effect, enable data exchange by an increasing number of software applications in the industry. This establishes trust in data exchange and results in the lower cost impact of inefficient interoperability. The negative cost impact increases with advancing life-cycle phase, from planning and design phase to construction phase and to operation and maintenance phase. Interoperability in the planning and design phase is most mature and well published, while interoperability in the construction phase and for automated manufacturing is less researched. This paper reviews state-of-the art automated manufacturing systems in construction and researches interoperability requirements for automated construction in context of the entire building lifecycle. Our research is based on experimental free-form clay building, designed with embedded simple HVAC components, and manufactured with additive layer technology. Conclusions provide valuable results for interoperability research and practice in construction projects with automated manufacturing systems in place.     

Workflows for Heliophysics

In this paper we describe how we have introduced workflows into the working practices of a community for whom the concept of workflows is very new, namely the heliophysics community. Heliophysics is a branch of astrophysics which studies the Sun and the interactions between the Sun and the planets, by tracking solar events as they travel throughout the Solar system. Heliophysics produces two major challenges for workflow technology. Firstly it is a systems science where research is currently developed by many different communities who need reliable data models and metadata to be able to work together. Thus it has major challenges in the semantics of workflows. Secondly, the problem of time is critical in heliophysics; the workflows must take account of the propagation of events outwards from the sun. They have to address the four dimensional nature of space and time in terms of the indexing of data. We discuss how we have built an environment for Heliophysics workflows building on and extending the Taverna workflow system and utilising the myExperiment site for sharing workflows. We also describe how we have integrated the workflows into the existing practices of the communities involved in Heliophysics by developing a web portal which can hide the technical details from the users, who can concentrate on the data from their scientific point of view rather than on the methods used to integrate and process the data. This work has been developed in the EU Framework 7 project HELIO, and is being disseminated to the worldwide Heliophysics community, since Heliophysics requires integration of effort on a global scale.     

Relational generative topographic mapping

The generative topographic mapping (GTM) has been proposed as a statistical model to represent high-dimensional data by a distribution induced by a sparse lattice of points in a low-dimensional latent space, such that visualization, compression, and data inspection become possible. The formulation in terms of a generative statistical model has the benefit that relevant parameters of the model can be determined automatically based on an expectation maximization scheme. Further, the model offers a large flexibility such as a direct out-of-sample extension and the possibility to obtain different degrees of granularity of the visualization without the need of additional training. Original GTM is restricted to Euclidean data points in a given Euclidean vector space. Often, data are not explicitly embedded in a Euclidean vector space, rather pairwise dissimilarities of data can be computed, i.e. the relations between data points are given rather than the data vectors themselves. We propose a method which extends the GTM to relational data and which allows us to achieve a sparse representation of data characterized by pairwise dissimilarities, in latent space. The method, relational GTM, is demonstrated on several benchmarks.     

Fast Recognition of Fibonacci Cubes

Fibonacci cubes are induced subgraphs of hypercubes based on Fibonacci strings. They were introduced to represent interconnection networks as an alternative to the hypercube networks. We derive a characterization of Fibonacci cubes founded on the concept of resonance graphs. The characterization is the basis for an algorithm which recognizes these graphs in O(mlog n) time. A. Vesel supported by the Ministry of Science of Slovenia under the grant 0101-P-297.     

Student progress assessment with the help of an intelligent pupil analysis system

Students and lecturers would like to know how well students have learned the study materials being taught. A formal test or exam would cause needless stress for students. To resolve this problem, the authors of this article have developed an Intelligent Pupil Analysis (IPA) System. A sufficient amount of studies worldwide prove an interrelation between pupil size and a person's cognitive load. The obtained research results are comparable with the results from other similar studies. The original contribution of this article, compared to the research results published earlier, is as follows: the IPA System developed by the authors is superior to the traditional pupil analysis research due to the integration of pupil analysis with subsystems of decision support, recommender and intelligent tutoring systems and innovative Models of the Model-base, which permit a more detailed analysis of the knowledge attained by a student. This article ends with a case study to demonstrate the practical operation of the IPA System.     

Using Discriminative Dimensionality Reduction to Visualize Classifiers

Neural Processing Letters - Albeit automated classifiers offer a standard tool in many application areas, there exists hardly a generic possibility to directly inspect their behavior, which goes...     

Workload characterization of JVM languages

Originally developed with a single language in mind, the JVM is now targeted by numerous programming languages—its automatic memory management, just‐in‐time compilation, and adaptive optimizations—making it an attractive execution platform. However, the garbage collector, the just‐in‐time compiler, and other optimizations and heuristics were designed primarily with the performance of Java programs in mind. Consequently, many of the languages targeting the JVM, and especially the dynamically typed languages, are suffering from performance problems that cannot be simply solved at the JVM side. In this article, we aim to contribute to the understanding of the character of the workloads imposed on the JVM by both dynamically typed and statically typed JVM languages. To this end, we introduce a new set of dynamic metrics for workload characterization, along with an easy‐to‐use toolchain to collect the metrics. We apply the toolchain to applications written in six JVM languages (Java, Scala, Clojure, Jython, JRuby, and JavaScript) and discuss the findings. Given the recently identified importance of inlining for the performance of Scala programs, we also analyze the inlining behavior of the HotSpot JVM when executing bytecode originating from different JVM languages. As a result, we identify several traits in the non‐Java workloads that represent potential opportunities for optimization. © 2015 The Authors. Software: Practice and Experience Published by John Wiley & Sons Ltd.     

Modelling of speech using primarily prosodic parameters

Hidden Markov Models are used in an experiment to investigate how state occupancy corresponds to prosodic parameters and spectral balance. In order to define separate sub-classes in the data using a maximum likelihood approach, modelling was performed using a single model where individual states correspond to different categories without assuming the structure of the data, rather than manually segmenting the data and modelling each predefined category separately.The results indicate a significant content of segmental information in the prosodic parameters, but the results based on the time-alignment of the model states with the feature vectors are in a form which is not directly usable in a recognition environment. The classification of various phonetic categories is particularly consistent for vowels and nasals and is generally better for voiced than unvoiced speech. The classification is also robust to influences of segmental effects on the data, with consistent alignments with segments regardless of the type of neighbouring phenemes.     

Experimentelle und numerische Untersuchungen zum Tragverhalten von Stahlbetondecken mit kugelförmigen Hohlkörpern

Massive Flachdecken erweisen sich in Hoch‐ und Industriebau häufig als insgesamt überlegenes Deckensystem. Die hohe Eigenlast dieser Decken kann ihren Anwendungsbereich jedoch einschränken. Eine sinnvolle Abhilfe schafft dann die Integration von Hohlkörpern in der neutralen Zone, weil hierdurch eine spürbare Gewichtsreduktion eintritt. Neben der Eigenlast wird auch der Verbrauch der unter ökologischen Gesichtspunkten wesentlichen Ressourcen Betonstahl und Zement deutlich verringert. Die Hohlräume beeinflussen vor allem die Querkrafttragfähigkeit solcher Decken. Vier Versuchsserien, die mit kugelförmigen Hohlkörperdecken des Systems “cobiax” durchgeführt wurden, werden in diesem Beitrag beschrieben. Aus den Versuchen wird ein Abminderungsfaktor zur Beschreibung des Querkrafttragverhaltens abgeleitet, der auch in die kürzlich erteilte allgemeine bauaufsichtliche Zulassung des Deckensystems eingegangen ist. Die Nachrechnung der Versuche mit der Finite‐Elemente‐Methode zeigt eine gute Übereinstimmung von Numerik und Experiment, so dass in der Weiterentwicklung Parameterstudien auf dieser Grundlage zur Ergänzung von Versuchen hilfreich sein werden. Experimental and Numerical Investigation of the Bearing Behaviour of Hollow Core Slabs Massive flat slabs have proven to be the most appropriate ceiling system for structural and industrial engineering. However the high dead load of these slabs might reduce their field of application. This problem can be solved by void formers that are placed in the neutral zone. These block‐outs cause a noticeable reduction of weight. Furthermore, the masses of ecologically important resources like reinforcement steel and cement can be reduced as well. The shear bearing capacity is significantly influenced by these block‐outs. This article describes four test series with spherical void former floors of the system “cobiax”. A reduction factor for the shear bearing capacity is derived from these tests. That factor was also introduced in the technical approval for this slab system which has been issued recently. A comparison to a calculation with the finite element method shows that the numerical results and the results of the tests are quite similar. In future research, parameter studies based on the finite element method might be helpful additional to further tests.