| 1. |
- Gulkis, Samuel, et al.
(författare)
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Subsurface properties and early activity of comet 67P/Churyumov-Gerasimenko
- 2015
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 347:6220
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Tidskriftsartikel (refereegranskat)abstract
- Heat transport and ice sublimation in comets are interrelated processes reflecting properties acquired at the time of formation and during subsequent evolution. The Microwave Instrument on the Rosetta Orbiter (MIRO) acquired maps of the subsurface temperature of comet 67P/Churyumov-Gerasimenko, at 1.6 mm and 0.5 mm wavelengths, and spectra of water vapor. The total H2O production rate varied from 0.3 kg s(-1) in early June 2014 to 1.2 kg s(-1) in late August and showed periodic variations related to nucleus rotation and shape. Water outgassing was localized to the "neck" region of the comet. Subsurface temperatures showed seasonal and diurnal variations, which indicated that the submillimeter radiation originated at depths comparable to the diurnal thermal skin depth. A low thermal inertia (similar to 10 to 50 J K-1 m(-2) s(-0.5)), consistent with a thermally insulating powdered surface, is inferred.
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| 2. |
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Advances in Practical Applications of Cyber-Physical Multi-Agent Systems : 15th International Conference, PAAMS 2017, Porto, Portugal, June 21-23, 2017, Proceedings
- 2017. - 1
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Proceedings (redaktörskap) (refereegranskat)abstract
- This book constitutes the refereed proceedings of the 15th International Conference on Practical Applications of Scalable Multi-Agent Systems, PAAMS 2017, held in Porto, Portugal, in June 2017.The 11 revised full papers, 11 short papers, and 17 Demo papers were carefully reviewed and selected from 63 submissions. The papers report on the application and validation of agent-based models, methods, and technologies in a number of key application areas, including day life and real world, energy and networks, human and trust, markets and bids, models and tools, negotiation and conversation, scalability and resources.
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| 3. |
- Alawadi, Sadi, et al.
(författare)
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A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings
- 2020
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Ingår i: Energy Systems, Springer Verlag. - : Springer. - 1868-3967 .- 1868-3975. ; 13, s. 689-705
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Tidskriftsartikel (refereegranskat)abstract
- The international community has largely recognized that the Earth's climate is changing. Mitigating its global effects requires international actions. The European Union (EU) is leading several initiatives focused on reducing the problems. Specifically, the Climate Action tries to both decrease EU greenhouse gas emissions and improve energy efficiency by reducing the amount of primary energy consumed, and it has pointed to the development of efficient building energy management systems as key. In traditional buildings, households are responsible for continuously monitoring and controlling the installed Heating, Ventilation, and Air Conditioning (HVAC) system. Unnecessary energy consumption might occur due to, for example, forgetting devices turned on, which overwhelms users due to the need to tune the devices manually. Nowadays, smart buildings are automating this process by automatically tuning HVAC systems according to user preferences in order to improve user satisfaction and optimize energy consumption. Towards achieving this goal, in this paper, we compare 36 Machine Learning algorithms that could be used to forecast indoor temperature in a smart building. More specifically, we run experiments using real data to compare their accuracy in terms of R-coefficient and Root Mean Squared Error and their performance in terms of Friedman rank. The results reveal that the ExtraTrees regressor has obtained the highest average accuracy (0.97%) and performance (0,058%) over all horizons.
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| 4. |
- Alkhabbas, Fahed, et al.
(författare)
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A Commitment-Based Approach to Realize Emergent Configurations in the Internet of Things
- 2017
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Ingår i: Software Architecture Workshops (ICSAW), 2017 IEEE International Conference on. - : IEEE. ; , s. 88-91
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Konferensbidrag (refereegranskat)abstract
- The Internet of Things (IoT) involves intelligent, heterogeneous, autonomous and often distributed things which interact and collaborate to achieve common goals. A useful concept for supporting this effort is Emergent Configuration (EC), which consists of a dynamic set of things, with their functionalities and services, that cooperate temporarily to achieve a goal. In this paper we introduce a commitment-based approach that exploits the concept of commitments to realize ECs. More specifically, (i) we present a conceptual model for commitment-based ECs, (ii) we use the smart meeting room scenario to illustrate how ECs are realized via commitments.
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| 5. |
- Alkhabbas, Fahed, et al.
(författare)
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A Goal driven Approach for Deploying Self-adaptive IoT Systems
- 2020
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Ingår i: Proceedings. - 9781728146591 - 9781728146607 ; , s. 146-156
-
Konferensbidrag (refereegranskat)abstract
- Engineering Internet of Things (IoT) systems is a challenging task partly due to the dynamicity and uncertainty of the environment including the involvement of the human in the loop. Users should be able to achieve their goals seamlessly in different environments, and IoT systems should be able to cope with dynamic changes. Several approaches have been proposed to enable the automated formation, enactment, and self-adaptation of goal-driven IoT systems. However, they do not address deployment issues. In this paper, we propose a goal-driven approach for deploying self-adaptive IoT systems in the Edge-Cloud continuum. Our approach supports the systems to cope with the dynamicity and uncertainty of the environment including changes in their deployment topologies, i.e., the deployment nodes and their interconnections. We describe the architecture and processes of the approach and the simulations that we conducted to validate its feasibility. The results of the simulations show that the approach scales well when generating and adapting the deployment topologies of goal-driven IoT systems in smart homes and smart buildings.
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| 6. |
- Alkhabbas, Fahed, et al.
(författare)
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Activity Recognition and User Preference Learning for Automated Configuration of IoT Environments
- 2020
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Ingår i: IoT '20. - New York, United States : ACM Digital Library. - 9781450387583 ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- Internet of Things (IoT) environments encompass different types of devices and objects that offer a wide range of services. The dynamicity and uncertainty of those environments, including the mobility of users and devices, make it hard to foresee at design time available devices, objects, and services. For the users to benefit from such environments, they should be proposed services that are relevant to the specific context and can be provided by available things. Moreover, environments should be configured automatically based on users' preferences. To address these challenges, we propose an approach that leverages Artificial Intelligence techniques to recognize users' activities and provides relevant services to support users to perform their activities. Moreover, our approach learns users' preferences and configures their environments accordingly by dynamically forming, enacting, and adapting goal-driven IoT systems. In this paper, we present a conceptual model, a multi-tier architecture, and processes of our approach. Moreover, we report about how we validated the feasibility and evaluated the scalability of the approach through a prototype that we developed and used.
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| 7. |
- Alkhabbas, Fahed, et al.
(författare)
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An Agent-based Approach to Realize Emergent Configurationsin the Internet of Things
- 2020
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Ingår i: Electronics. - : MDPI. - 2079-9292. ; 9:9
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Tidskriftsartikel (refereegranskat)abstract
- The Internet of Things (IoT) has enabled physical objects and devices, often referred to as things, to connect and communicate. This has opened up for the development of novel types of services that improve the quality of our daily lives. The dynamicity and uncertainty of IoT environments, including the mobility of users and devices, make it hard to foresee at design time available things and services. Further, users should be able to achieve their goals seamlessly in arbitrary environments. To address these challenges, we exploit Artificial Intelligence (AI) to engineer smart IoT systems that can achieve user goals and cope with the dynamicity and uncertainty of their environments. More specifically, the main contribution of this paper is an approach that leverages the notion of Belief-Desire-Intention agents and Machine Learning (ML) techniques to realize Emergent Configurations (ECs) in the IoT. An EC is an IoT system composed of a dynamic set of things that connect and cooperate temporarily to achieve a user goal. The approach enables the distributed formation, enactment, adaptation of ECs, and conflict resolution among them. We present a conceptual model of the entities of the approach, its underlying processes, and the guidelines for using it. Moreover, we report about the simulations conducted to validate the feasibility of the approach and evaluate its scalability. View Full-Text
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| 8. |
- Alkhabbas, Fahed, et al.
(författare)
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Architecting Emergent Configurations in the Internet of Things
- 2017
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Ingår i: Proceedings. - : IEEE. ; , s. 221-224
-
Konferensbidrag (refereegranskat)abstract
- The Internet of Things (IoT) has a great potential to change our lives. Billions of heterogeneous, distributed, intelligent, and sometimes mobile devices, will be connected and offer new types of applications and ways to interact. The dynamic environment of the IoT, the involvement of the human in the loop, and the runtime interactions among devices and applications, put additional requirements on the systems' architecture. In this paper, we use the Emergent Configurations (ECs) concept as a way to engineer IoT systems and propose an architecture for ECs. More specifically, we discuss (i) how connected devices and applications form ECs to achieve users' goals and (ii) how applications are run and adapted in response to runtime context changes including, e.g., the sudden unavailability of devices, by exploiting the Smart Meeting Room case.
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| 9. |
- Alkhabbas, Fahed, et al.
(författare)
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ART4FL : An Agent-Based Architectural Approach for Trustworthy Federated Learning in the IoT
- 2023
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Ingår i: 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350316971 - 9798350316988
-
Konferensbidrag (refereegranskat)abstract
- The integration of the Internet of Things (IoT) and Machine Learning (ML) technologies has opened up for the development of novel types of systems and services. Federated Learning (FL) has enabled the systems to collaboratively train their ML models while preserving the privacy of the data collected by their IoT devices and objects. Several FL frameworks have been developed, however, they do not enable FL in open, distributed, and heterogeneous IoT environments. Specifically, they do not support systems that collect similar data to dynamically discover each other, communicate, and negotiate about the training terms (e.g., accuracy, communication latency, and cost). Towards bridging this gap, we propose ART4FL, an end-to-end framework that enables FL in open IoT settings. The framework enables systems' users to configure agents that participate in FL on their behalf. Those agents negotiate and make commitments (i.e., contractual agreements) to dynamically form federations. To perform FL, the framework deploys the needed services dynamically, monitors the training rounds, and calculates agents' trust scores based on the established commitments. ART4FL exploits a blockchain network to maintain the trust scores, and it provides those scores to negotiating agents' during the federations' formation phase.
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| 10. |
- Alkhabbas, Fahed, et al.
(författare)
-
ART4FL : An Agent-based Architectural Approach for Trustworthy Federated Learning in the IoT
- 2023
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Ingår i: 8th International Conference on Fog and Mobile Edge Computing, FMEC 2023. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350316971 - 9798350316988 ; , s. 270-275
-
Konferensbidrag (refereegranskat)abstract
- The integration of the Internet of Things (IoT) and Machine Learning (ML) technologies has opened up for the development of novel types of systems and services. Federated Learning (FL) has enabled the systems to collaboratively train their ML models while preserving the privacy of the data collected by their IoT devices and objects. Several FL frameworks have been developed, however, they do not enable FL in open, distributed, and heterogeneous IoT environments. Specifically, they do not support systems that collect similar data to dynamically discover each other, communicate, and negotiate about the training terms (e.g., accuracy, communication latency, and cost). Towards bridging this gap, we propose ART4FL, an end-to-end framework that enables FL in open IoT settings. The framework enables systems’ users to configure agents that participate in FL on their behalf. Those agents negotiate and make commitments (i.e., contractual agreements) to dynamically form federations. To perform FL, the framework deploys the needed services dynamically, monitors the training rounds, and calculates agents’ trust scores based on the established commitments. ART4FL exploits a blockchain network to maintain the trust scores, and it provides those scores to negotiating agents’ during the federations’ formation phase. © 2023 IEEE.
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