| 1. |
- Diniz Caldas, Ricardo, 1994, et al.
(författare)
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A hybrid approach combining control theory and AI for engineering self-adaptive systems
- 2020
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Ingår i: Proceedings - 2020 IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2020. - New York, NY, USA : ACM. ; , s. 9-19
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Konferensbidrag (refereegranskat)abstract
- Control theoretical techniques have been successfully adopted as methods for self-adaptive systems design to provide formal guarantees about the effectiveness and robustness of adaptation mechanisms. However, the computational effort to obtain guarantees poses severe constraints when it comes to dynamic adaptation. In order to solve these limitations, in this paper, we propose a hybrid approach combining software engineering, control theory, and AI to design for software self-adaptation. Our solution proposes a hierarchical and dynamic system manager with performance tuning. Due to the gap between high-level requirements specification and the internal knob behavior of the managed system, a hierarchically composed components architecture seek the separation of concerns towards a dynamic solution. Therefore, a two-layered adaptive manager was designed to satisfy the software requirements with parameters optimization through regression analysis and evolutionary meta-heuristic. The optimization relies on the collection and processing of performance, effectiveness, and robustness metrics w.r.t control theoretical metrics at the offline and online stages. We evaluate our work with a prototype of the Body Sensor Network (BSN) in the healthcare domain, which is largely used as a demonstrator by the community. The BSN was implemented under the Robot Operating System (ROS) architecture, and concerns about the system dependability are taken as adaptation goals. Our results reinforce the necessity of performing well on such a safety-critical domain and contribute with substantial evidence on how hybrid approaches that combine control and AI-based techniques for engineering self-adaptive systems can provide effective adaptation.
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| 2. |
- Gil, Eric Bernd, et al.
(författare)
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Body Sensor Network: A Self-Adaptive System Exemplar in the Healthcare Domain
- 2021
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Ingår i: 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). - 2157-2321. - 9781665402897
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Konferensbidrag (refereegranskat)abstract
- Recent worldwide events shed light on the need of human-centered systems engineering in the healthcare domain. These systems must be prepared to evolve quickly but safely, according to unpredicted environments and ever-changing pathogens that spread ruthlessly. Such scenarios suffocate hospitals' infrastructure and disable healthcare systems that are not prepared to deal with unpredicted environments without costly re-engineering. In the face of these challenges, we offer the SA-BSN - Self-Adaptive Body Sensor Network - prototype to explore the rather dynamic patient's health status monitoring. The exemplar is focused on self-adaptation and comes with scenarios that hinder an interplay between system reliability and battery consumption that is available after each execution. Also, we provide: (i) a noise injection mechanism, (ii) file-based patient profiles' configuration, (iii) six healthcare sensor simulations, and (iv) an extensible/reusable controller implementation for self-adaptation. The artifact is implemented in ROS (Robot Operating System), which embraces principles such as ease of use and relies on an active open source community support
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| 3. |
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| 4. |
- Rodrigues, Arthur, et al.
(författare)
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Enhancing Context Specifications for Dependable Adaptive Systems: A Data Mining Approach
- 2019
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Ingår i: Information and Software Technology. - : Elsevier BV. - 0950-5849. ; 112, s. 115-131
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Tidskriftsartikel (refereegranskat)abstract
- Context: Adaptive systems are expected to cater for various operational contexts by having multiple strategies in achieving their objectives and the logic for matching strategies to an actual context. The prediction of relevant contexts at design time is paramount for dependability. With the current trend on using data mining to support the requirements engineering process, this task of understanding context for adaptive system at design time can benefit from such techniques as well. Objective: The objective is to provide a method to refine the specification of contextual variables and their relation to strategies for dependability. This refinement shall detect dependencies between such variables, priorities in monitoring them, and decide on their relevance in choosing the right strategy in a decision tree. Method: Our requirements-driven approach adopts the contextual goal modelling structure in addition to the operationalization values of sensed information to map contexts to the system’s behaviour. We propose a design time analysis process using a subset of data mining algorithms to extract a list of relevant contexts and their related variables, tasks, and/or goals. Results: We experimentally evaluated our proposal on a Body Sensor Network system (BSN), simulating 12 resources that could lead to a variability space of 4096 possible context conditions. Our approach was able to elicit subtle contexts that would significantly affect the service provided to assisted patients and relations between contexts, assisting the decision on their need, and priority in monitoring. Conclusion: The use of some data mining techniques can mitigate the lack of precise definition of contexts and their relation to system strategies for dependability. Our method is practical and supportive to traditional requirements specification methods, which typically require intense human intervention.
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| 5. |
- Gomes Marques, Inês, et al.
(författare)
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The ADnet Bayesian belief network for alder decline : integrating empirical data and expert knowledge
- 2024
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Ingår i: Science of the Total Environment. - : Elsevier. - 0048-9697 .- 1879-1026. ; 947
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Tidskriftsartikel (refereegranskat)abstract
- The globalization in plant material trading has caused the emergence of invasive pests in many ecosystems, such as the alder pathogen Phytophthora ×alni in European riparian forests. Due to the ecological importance of alder to the functioning of rivers and the increasing incidence of P. ×alni-induced alder decline, effective and accessible decision tools are required to help managers and stakeholders control the disease. This study proposes a Bayesian belief network methodology to integrate diverse information on the factors affecting the survival and infection ability of P. ×alni in riparian habitats to help predict and manage disease incidence. The resulting Alder Decline Network (ADnet) management tool integrates information about alder decline from scientific literature, expert knowledge and empirical data. Expert knowledge was gathered through elicitation techniques that included 19 experts from 12 institutions and 8 countries. An original dataset was created covering 1189 European locations, from which P. ×alni occurrence was modeled based on bioclimatic variables. ADnet uncertainty was evaluated through its sensitivity to changes in states and three scenario analyses. The ADnet tool indicated that mild temperatures and high precipitation are key factors favoring pathogen survival. Flood timing, water velocity, and soil type have the strongest influence on disease incidence. ADnet can support ecosystem management decisions and knowledge transfer to address P. ×alni-induced alder decline at local or regional levels across Europe. Management actions such as avoiding the planting of potentially infected trees or removing man-made structures that increase the flooding period in disease-affected sites could decrease the incidence of alder disease in riparian forests and limit its spread. The coverage of the ADnet tool can be expanded by updating data on the pathogen's occurrence, particularly from its distributional limits. Research on the role of genetic variability in alder susceptibility and pathogen virulence may also help improve future ADnet versions.
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| 6. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 7. |
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| 8. |
- Zamora, Juan Carlos, et al.
(författare)
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Considerations and consequences of allowing DNA sequence data as types of fungal taxa
- 2018
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Ingår i: IMA Fungus. - : INT MYCOLOGICAL ASSOC. - 2210-6340 .- 2210-6359. ; 9:1, s. 167-185
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Tidskriftsartikel (refereegranskat)abstract
- Nomenclatural type definitions are one of the most important concepts in biological nomenclature. Being physical objects that can be re-studied by other researchers, types permanently link taxonomy (an artificial agreement to classify biological diversity) with nomenclature (an artificial agreement to name biological diversity). Two proposals to amend the International Code of Nomenclature for algae, fungi, and plants (ICN), allowing DNA sequences alone (of any region and extent) to serve as types of taxon names for voucherless fungi (mainly putative taxa from environmental DNA sequences), have been submitted to be voted on at the 11th International Mycological Congress (Puerto Rico, July 2018). We consider various genetic processes affecting the distribution of alleles among taxa and find that alleles may not consistently and uniquely represent the species within which they are contained. Should the proposals be accepted, the meaning of nomenclatural types would change in a fundamental way from physical objects as sources of data to the data themselves. Such changes are conducive to irreproducible science, the potential typification on artefactual data, and massive creation of names with low information content, ultimately causing nomenclatural instability and unnecessary work for future researchers that would stall future explorations of fungal diversity. We conclude that the acceptance of DNA sequences alone as types of names of taxa, under the terms used in the current proposals, is unnecessary and would not solve the problem of naming putative taxa known only from DNA sequences in a scientifically defensible way. As an alternative, we highlight the use of formulas for naming putative taxa (candidate taxa) that do not require any modification of the ICN.
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