An Ontological Framework for Opportunistic Composition of IoT Systems

As the number of connected devices rapidly increases, largely thanks to uptake of IoT technologies, there is significant stimulus to enable opportunistic interactions between different systems that encounter each other at run time. However, this is complicated by diversity in IoT technologies and implementation details that are not known in advance. To achieve such unplanned interactions, we use the concept of a holon to represent a system's services and requirements at a high level. A holon is a self-describing system that appears as a whole when viewed from above whilst potentially comprising multiple sub-systems when viewed from below. In order to realise this world view and facilitate opportunistic system interactions, we propose the idea of using ontologies to define and program a holon. Ontologies offer the ability to classify the concepts of a domain, and use this formalised knowledge to infer new knowledge through reasoning. In this paper, we design a holon ontology and associated code generation tools. We also explore a case study of how programming holons using this approach can aid an IoT system to self-describe and reason about other systems it encounters. As such, developers can develop system composition logic at a high-level without any preconceived notions about low-level implementation details. © 2020 IEEE

Achieving interoperability through semantics-based technologies: the instant messaging case

The success of pervasive computing depends on the ability to compose a multitude of networked applications dynamically in order to achieve user goals. However, applications from different providers are not able to interoperate due to incompatible interaction protocols or disparate data models. Instant messaging is a representative example of the current situation, where various competing applications keep emerging. To enforce interoperability at runtime and in a non-intrusive manner, mediators are used to perform the necessary translations and coordination between the heterogeneous applications. Nevertheless, the design of mediators requires considerable knowledge about each application as well as a substantial development effort. In this paper we present an approach based on ontology reasoning and model checking in order to generate correct-by-construction mediators automatically. We demonstrate the feasibility of our approach through a prototype tool and show that it synthesises mediators that achieve efficient interoperation of instant messaging applications

Climate driven trends in London's urban heat island intensity reconstructed over 70 years using a generalized additive model

Long-term urban heat island (UHI) observations are uncommon and where available, are generally unable to distinguish changing climate drivers from urban expansion; neither driver is treated independently. We overcome this limitation using a generalized additive model to learn the variability in UHI intensity (UHII) at a central London weather station (St James's Park) over a 10-year observation period (2010–2019). We then use the model to reconstruct 70 years (1950–2019) of monthly night-time UHII variability using ERA5 reanalysis data both as a reference in UHII calculation and for the predictors. We find considerable variability both seasonally and annually within the UHII time series (monthly mean maximum UHIIs are 1.4–2.9 °C). Applying extreme value analysis to the time series we show that monthly mean maximum UHIIs are likely to exceed 2.75 °C once every 11 years. Considering that most studies observe or model UHIIs for less than a year, they will likely misrepresent this UHII variability. Nevertheless, despite moving to a warmer background climate, London's UHII has not significantly changed across the period of analysis (1950–2019). The data-driven methods we create in this study are easily transferable to other cities

Automated mediator synthesis: combining behavioural and ontological reasoning

Software systems are increasingly composed of independently developed heterogeneous components. To ensure interoperability, mediators are needed that coordinate actions and translate exchanged messages between the components. We present a technique for automated synthesis of mediators, by means of a quotient operator, that is based on behavioural models of the components and an ontological model of the data domain. By not requiring a specification of the composed system, the method supports both off-line and run-time synthesis. The obtained mediator is the most general component that ensures freedom of both communication mismatches and deadlock in the composition. Validation of the approach is given by implementation of a prototype tool, while applicability is illustrated on heterogeneous holiday booking components

The effect of gamma irradiation on selected growth factors and receptors mRNA in glycerol cryopreserved human amniotic membrane

Human amniotic membrane (HAM), due to its high biocompatibility, low immunogenicity, anti-microbial, anti-viral properties as well as the presence of its growth factors, has been used in various clinical applications. These growth factors are key factors in regulating many cellular processes such as cellular growth, proliferation and cellular differentiation. The current study aimed to explore the effect of glycerol cryopreservation and gamma irradiation on the selected growth factors and receptors mRNA present in HAM. Eight growth factors, namely, EGF, HGF, KGF, TGF-α, TGF-β1, TGF-β2, TGF-β3 and bFGF and two growth factor receptors, HGFR and KGFR were evaluated in this study. The total RNA was extracted and converted to complimentary DNA using commercial kits. Subsequently, the mRNA expressions of these growth factors were evaluated using quantitative PCR and the results were statistically analyzed using REST-MCS software. This study indicated the presence of these growth factors and receptors mRNA in fresh, glycerol cryopreserved and irradiated glycerol cryopreserved HAM. In glycerol cryopreserved HAM, the mRNA expression showed up-regulation of HGF and bFGF and down-regulation of the rest of 8 genes which were EGF, HGFR, KGF, KGFR, TGF-α, TGF-β1, TGF-β2 and TGF-β3. Interestingly, the glycerol cryopreserved HAM radiated with 15 kGy showed up-regulation in the mRNA expression of 7 genes, namely, EGF, HGF, KGF, KGFR, TGF-β1, TGF-β2 and TGF-β3 and down-regulated mRNA expression of HGFR, TGF-α and bFGF. However, these mRNA expressions did not show a statistically significant difference compared to control groups. Thus, it can be concluded that the glycerol cryopreservation did not have an effect on the growth factors’ and receptors’ mRNA expression levels in HAM. Similarly, 15 kGy gamma irradiation did not have an effect on the growth factors’ and receptors’ mRNA expression in glycerol cryopreserved HAM. This finding provides a useful information to clinicians and surgeons to choose the best method for HAM preservation that could benefit patients in their treatment

Characterization of Adaptable Interpreted-DSML

Abstract. One of the main goals of model-driven engineering (MDE) is the manipulation of models as exclusive software artifacts. Model ex-ecution is in particular a means to substitute models for code. More precisely, as models of a dedicated domain-specific modeling language (DSML) are interpreted through an execution engine, such a DSML is called interpreted-DSML (i-DSML for short). On another way, MDE is a promising discipline for building adaptable systems based on models at runtime. When the model is directly executed, the system becomes the model: This is the model that is adapted. In this paper, we propose a characterization of adaptable i-DSML where a single model is executed and directly adapted at runtime. If model execution only modifies the dy-namical elements of the model, we show that the adaptation can modify each part of the model and that the execution and adaptation semantics can be changed at runtime

Machine learning for emergent middleware

Highly dynamic and heterogeneous distributed systems are challenging today's middleware technologies. Existing middleware paradigms are unable to deliver on their most central promise, which is offering interoperability. In this paper, we argue for the need to dynamically synthesise distributed system infrastructures according to the current operating environment, thereby generating "Emergent Middleware'' to mediate interactions among heterogeneous networked systems that interact in an ad hoc way. The paper outlines the overall architecture of Enablers underlying Emergent Middleware, and in particular focuses on the key role of learning in supporting such a process, spanning statistical learning to infer the semantics of networked system functions and automata learning to extract the related behaviours of networked systems

Automatic service categorisation through machine learning in emergent middleware

The modern environment of mobile, pervasive, evolving services presents a great challenge to traditional solutions for enabling interoperability. Automated solutions appear to be the only way to achieve interoperability with the needed level of flexibility and scalability. While necessary, the techniques used to determine compatibility, as a precursor to interaction, come at a substantial computational cost, especially when checks are performed between systems in unrelated domains. To overcome this, we apply machine learning to extract high-level functionality information through text categorisation of a system's interface description. This categorisation allows us to restrict the scope of compatibility checks, giving an overall performance gain when conducting matchmaking between systems. We have evaluated our approach on a corpus of web service descriptions, where even with moderate categorisation accuracy, a substantial performance benefit can be found. This in turn improves the applicability of our overall approach for achieving interoperability in the Connect project

Search for displaced vertices arising from decays of new heavy particles in 7 TeV pp collisions at ATLAS

We present the results of a search for new, heavy particles that decay at a significant distance from their production point into a final state containing charged hadrons in association with a high-momentum muon. The search is conducted in a pp-collision data sample with a center-of-mass energy of 7 TeV and an integrated luminosity of 33 pb^-1 collected in 2010 by the ATLAS detector operating at the Large Hadron Collider. Production of such particles is expected in various scenarios of physics beyond the standard model. We observe no signal and place limits on the production cross-section of supersymmetric particles in an R-parity-violating scenario as a function of the neutralino lifetime. Limits are presented for different squark and neutralino masses, enabling extension of the limits to a variety of other models.Comment: 8 pages plus author list (20 pages total), 8 figures, 1 table, final version to appear in Physics Letters

Measurement of the polarisation of W bosons produced with large transverse momentum in pp collisions at sqrt(s) = 7 TeV with the ATLAS experiment

This paper describes an analysis of the angular distribution of W->enu and W->munu decays, using data from pp collisions at sqrt(s) = 7 TeV recorded with the ATLAS detector at the LHC in 2010, corresponding to an integrated luminosity of about 35 pb^-1. Using the decay lepton transverse momentum and the missing transverse energy, the W decay angular distribution projected onto the transverse plane is obtained and analysed in terms of helicity fractions f0, fL and fR over two ranges of W transverse momentum (ptw): 35 < ptw < 50 GeV and ptw > 50 GeV. Good agreement is found with theoretical predictions. For ptw > 50 GeV, the values of f0 and fL-fR, averaged over charge and lepton flavour, are measured to be : f0 = 0.127 +/- 0.030 +/- 0.108 and fL-fR = 0.252 +/- 0.017 +/- 0.030, where the first uncertainties are statistical, and the second include all systematic effects.Comment: 19 pages plus author list (34 pages total), 9 figures, 11 tables, revised author list, matches European Journal of Physics C versio