| 1. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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A Symbolic Approach for Explaining Errors in Image Classification Tasks
- 2018
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Conference paper (peer-reviewed)abstract
- Machine learning algorithms, despite their increasing success in handling object recognition tasks, still seldom perform without error. Often the process of understanding why the algorithm has failed is the task of the human who, using domain knowledge and contextual information, can discover systematic shortcomings in either the data or the algorithm. This paper presents an approach where the process of reasoning about errors emerging from a machine learning framework is automated using symbolic techniques. By utilizing spatial and geometrical reasoning between objects in a scene, the system is able to describe misclassified regions in relation to its context. The system is demonstrated in the remote sensing domain where objects and entities are detected in satellite images.
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| 2. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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An ontology-based context-aware system for smart homes : E-care@home
- 2017
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In: Sensors. - Basel : MDPI AG. - 1424-8220. ; 17:7
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Journal article (peer-reviewed)abstract
- Smart home environments have a significant potential to provide for long-term monitoring of users with special needs in order to promote the possibility to age at home. Such environments are typically equipped with a number of heterogeneous sensors that monitor both health and environmental parameters. This paper presents a framework called E-care@home, consisting of an IoT infrastructure, which provides information with an unambiguous, shared meaning across IoT devices, end-users, relatives, health and care professionals and organizations. We focus on integrating measurements gathered from heterogeneous sources by using ontologies in order to enable semantic interpretation of events and context awareness. Activities are deduced using an incremental answer set solver for stream reasoning. The paper demonstrates the proposed framework using an instantiation of a smart environment that is able to perform context recognition based on the activities and the events occurring in the home.
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| 3. |
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| 4. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring
- 2017
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In: Sensors. - : M D P I AG. - 1424-8220. ; 17:11
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Journal article (peer-reviewed)abstract
- This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.
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| 5. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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Automated reasoning using abduction for interpretation of medical signals
- 2014
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In: Journal of Biomedical Semantics. - : BioMed Central. - 2041-1480. ; 5
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Journal article (peer-reviewed)abstract
- This paper proposes an approach to leverage upon existing ontologies in order to automate the annotation of time series medical data. The annotation is achieved by an abductive reasoner using parsimonious covering theorem in order to determine the best explanation or annotation for specific user defined events in the data. The novelty of this approach resides in part by the system’s flexibility in how events are defined by users and later detected by the system. This is achieved via the use of different ontologies which find relations between medical, lexical and numerical concepts. A second contribution resides in the application of an abductive reasoner which uses the online and existing ontologies to provide annotations. The proposed method is evaluated on datasets collected from ICU patients and the generated annotations are compared against those given by medical experts.
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| 6. |
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| 7. |
- Alirezaie, Marjan, 1980-
(author)
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Bridging the Semantic Gap between Sensor Data and Ontological Knowledge
- 2015
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Doctoral thesis (other academic/artistic)abstract
- The rapid growth of sensor data can potentially enable a better awareness of the environment for humans. In this regard, interpretation of data needs to be human-understandable. For this, data interpretation may include semantic annotations that hold the meaning of numeric data. This thesis is about bridging the gap between quantitative data and qualitative knowledge to enrich the interpretation of data. There are a number of challenges which make the automation of the interpretation process non-trivial. Challenges include the complexity of sensor data, the amount of available structured knowledge and the inherent uncertainty in data. Under the premise that high level knowledge is contained in ontologies, this thesis investigates the use of current techniques in ontological knowledge representation and reasoning to confront these challenges. Our research is divided into three phases, where the focus of the first phase is on the interpretation of data for domains which are semantically poor in terms of available structured knowledge. During the second phase, we studied publicly available ontological knowledge for the task of annotating multivariate data. Our contribution in this phase is about applying a diagnostic reasoning algorithm to available ontologies. Our studies during the last phase have been focused on the design and development of a domain-independent ontological representation model equipped with a non-monotonic reasoning approach with the purpose of annotating time-series data. Our last contribution is related to coupling the OWL-DL ontology with a non-monotonic reasoner. The experimental platforms used for validation consist of a network of sensors which include gas sensors whose generated data is complex. A secondary data set includes time series medical signals representing physiological data, as well as a number of publicly available ontologies such as NCBO Bioportal repository.
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| 8. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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Context Recognition : Towards Automatic Query Generation
- 2015
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In: Ambient Intelligence. - Cham : Springer. - 9783319260044 - 9783319260051 ; , s. 205-218
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Conference paper (peer-reviewed)abstract
- In this paper, we present an ontology-based approach in designing knowledge model for context recognition (CR) systems. The main focus in this paper is on the use of an ontology to facilitate the generation of user-based queries to the CR system. By leveraging from the ontology, users need not know about sensor details and the structure of the ontology in expressing queries related to events of interest. To validate the approach and demonstrate the flexibility of the ontology for query generation, the ontology has been integrated in two separate application domains. The first domain considers a health care system implemented for the GiraffPlus project where the query generation process is automated to request information about activities of daily living. The second application uses the same ontology for an air quality monitoring application in the home. Since these two systems are independently developed for different purposes, the ease of applying the ontology upon them can be considered as a credit for its generality.
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| 9. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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Exploiting Context and Semantics for UAV Path-finding in an Urban Setting
- 2017
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In: Proceedings of the 1st International Workshop on Application of Semantic Web technologies in Robotics (AnSWeR 2017), Portoroz, Slovenia, May 29th, 2017. - : Technical University Aachen. ; , s. 11-20
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Conference paper (peer-reviewed)abstract
- In this paper we propose an ontology pattern that represents paths in a geo-representation model to be used in an aerial path planning processes. This pattern provides semantics related to constraints (i.e., ight forbidden zones) in a path planning problem in order to generate collision free paths. Our proposed approach has been applied on an ontology containing geo-regions extracted from satellite imagery data from a large urban city as an illustrative example.
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| 10. |
- Alirezaie, Marjan, 1980-, et al.
(author)
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Knowing without telling : integrating sensing and mapping for creating an artificial companion
- 2016
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In: Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450345897 ; , s. 11:1-11:4
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Conference paper (peer-reviewed)abstract
- This paper depicts a sensor-based map navigation approach which targets users, who due to disabilities or lack of technical knowledge are currently not in the focus of map system developments for personalized information. What differentiates our approach from the state-of-art mostly integrating localized social media data, is that our vision is to integrate real time sensor generated data that indicates the situation of dfferent phenomena (such as the physiological functions of the body) related to the user. The challenge hereby is mainly related to knowledge representation and integration. The tentative impact of our vision for future navigation systems is re ected within a scenario.
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