| 1. |
- Canovas, Juan-Pedro, et al.
(författare)
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Cooperative object localization using fuzzy logic
- 2003
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Ingår i: Proceedings of the IEEE international conference on methods and models in automation and robotics. ; , s. 773-778
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Konferensbidrag (refereegranskat)abstract
- Cooperative localization of objects is an important challenge in multi-robot systems. We propose a new approach to cooperative object localization by a group of communicating robots. In our approach we see each robot as an expert which provides unreliable information about the location of objects. The information provided by different robots is combined using fuzzy logic techniques, in order to reach agreement between the robots. This contrasts with current techniques, which average the information provided by different robots, and can incur well-known problems when information is unreliable. We have tested our technique on a team of Sony AIBO robots in the RoboCup domain. We present experimental results obtained by sharing information about the location of the ball
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| 2. |
- Canovas, Juan-Pedro, et al.
(författare)
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Robust multi-robot object localization using fuzzy logic
- 2005
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Ingår i: RoboCup 2004. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540250463 ; , s. 247-261
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Konferensbidrag (refereegranskat)abstract
- Cooperative localization of objects is an important challenge in multi-robot systems. We propose a new approach to this problem where we see each robot as an expert which shares unreliable information about object locations. The information provided by different robots is then combined using fuzzy logic techniques, in order to reach a consensus between the robots. This contrasts with most current probabilistic techniques, which average information from different robots in order to obtain a tradeoff, and can thus incur well-known problems when information is unreliable. In addition, our approach does not assume that the robots have accurate self-localization. Instead, uncertainty in the pose of the sensing robot is propagated to object position estimates. We present experimental results obtained on a team of Sony AIBO robots, where we share information about the location of the ball in the RoboCup domain
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| 3. |
- Chivasso, Clara, et al.
(författare)
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Ezrin is a novel protein partner of aquaporin-5 in human salivary glands and shows altered expression and cellular localization in sjögren’s syndrome
- 2021
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Ingår i: International Journal of Molecular Sciences. - : MDPI AG. - 1661-6596 .- 1422-0067. ; 22:17
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Tidskriftsartikel (refereegranskat)abstract
- Sjögren’s syndrome (SS) is an exocrinopathy characterized by the hypofunction of salivary glands (SGs). Aquaporin-5 (AQP5); a water channel involved in saliva formation; is aberrantly dis-tributed in SS SG acini and contributes to glandular dysfunction. We aimed to investigate the role of ezrin in AQP5 mislocalization in SS SGs. The AQP5–ezrin interaction was assessed by immuno-precipitation and proteome analysis and by proximity ligation assay in immortalized human SG cells. We demonstrated, for the first time, an interaction between ezrin and AQP5. A model of the complex was derived by computer modeling and in silico docking; suggesting that AQP5 interacts with the ezrin FERM-domain via its C-terminus. The interaction was also investigated in human minor salivary gland (hMSG) acini from SS patients (SICCA-SS); showing that AQP5–ezrin complexes were absent or mislocalized to the basolateral side of SG acini rather than the apical region compared to controls (SICCA-NS). Furthermore, in SICCA-SS hMSG acinar cells, ezrin immunore-activity was decreased at the acinar apical region and higher at basal or lateral regions, accounting for altered AQP5–ezrin co-localization. Our data reveal that AQP5–ezrin interactions in human SGs could be involved in the regulation of AQP5 trafficking and may contribute to AQP5-altered localization in SS patients.
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| 4. |
- Fresard, Laure, et al.
(författare)
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Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts
- 2019
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Ingår i: Nature Medicine. - : NATURE PUBLISHING GROUP. - 1078-8956 .- 1546-170X. ; 25:6, s. 911-919
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Tidskriftsartikel (refereegranskat)abstract
- It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene(1). The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches(2-5). For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases(6-8). This includes muscle biopsies from patients with undiagnosed rare muscle disorders(6,9), and cultured fibroblasts from patients with mitochondrial disorders(7). However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.
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| 5. |
- Herrero-Perez, D., et al.
(författare)
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Fuzzy uncertainty modeling for grid based localization of mobile robots
- 2010
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Ingår i: International Journal of Approximate Reasoning. - Amsterdam : Elsevier. - 0888-613X. ; , s. 912-932
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a localization method using fuzzy logic to represent the different facets of uncertainty present in sensor data. Our method follows the typical predict-update cycle of recursive state estimators to estimate the robot's location. The method is implemented on a fuzzy position grid, and several simplifications are introduced to reduce computational complexity. The main advantages of this fuzzy logic method compared to most current ones are: (i) only an approximate sensor model is required, (ii) several facets of location uncertainty can be represented, and (iii) ambiguities in the sensor information are directly represented, thus avoiding having to solve the data association problem separately. Our method has been validated experimentally on two different platforms, a legged robot equipped with vision and a wheeled robot equipped with range sensors. The experiments show that our method can solve both the tracking and the global localization problem. They also show that this method can successfully cope with ambiguous observations, when several features may be associated to the same observation, and with robot kidnapping situations. Additional experiments are presented that compare our approach with a state-of-the-art probabilistic method. (C) 2010 Elsevier Inc. All rights reserved.
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| 6. |
- Hubert, D., et al.
(författare)
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Ground-based assessment of the bias and long-term stability of 14 limb and occultation ozone profile data records
- 2016
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Ingår i: Atmospheric Measurement Techniques. - : Copernicus GmbH. - 1867-1381 .- 1867-8548. ; 9:6, s. 2497-2534
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Tidskriftsartikel (refereegranskat)abstract
- The ozone profile records of a large number of limb and occultation satellite instruments are widely used to address several key questions in ozone research. Further progress in some domains depends on a more detailed understanding of these data sets, especially of their long-term stability and their mutual consistency. To this end, we made a systematic assessment of 14 limb and occultation sounders that, together, provide more than three decades of global ozone profile measurements. In particular, we considered the latest operational Level-2 records by SAGE II, SAGE III, HALOE, UARS MLS, Aura MLS, POAM II, POAM III, OSIRIS, SMR, GOMOS, MIPAS, SCIAMACHY, ACE-FTS and MAESTRO. Central to our work is a consistent and robust analysis of the comparisons against the ground-based ozonesonde and stratospheric ozone lidar networks. It allowed us to investigate, from the troposphere up to the stratopause, the following main aspects of satellite data quality: long-term stability, overall bias and short-term variability, together with their dependence on geophysical parameters and profile representation. In addition, it permitted us to quantify the overall consistency between the ozone profilers. Generally, we found that between 20 and 40km the satellite ozone measurement biases are smaller than ±5%, the short-term variabilities are less than 5-12% and the drifts are at most ±5%decade-1 (or even ±3%decade-1 for a few records). The agreement with ground-based data degrades somewhat towards the stratopause and especially towards the tropopause where natural variability and low ozone abundances impede a more precise analysis. In part of the stratosphere a few records deviate from the preceding general conclusions; we identified biases of 10% and more (POAM II and SCIAMACHY), markedly higher single-profile variability (SMR and SCIAMACHY) and significant long-term drifts (SCIAMACHY, OSIRIS, HALOE and possibly GOMOS and SMR as well). Furthermore, we reflected on the repercussions of our findings for the construction, analysis and interpretation of merged data records. Most notably, the discrepancies between several recent ozone profile trend assessments can be mostly explained by instrumental drift. This clearly demonstrates the need for systematic comprehensive multi-instrument comparison analyses.
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| 7. |
- LeBlanc, Kevin
(författare)
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Cooperative anchoring : sharing information about objects in multi-robot systems
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In order to perform most tasks, robots must perceive or interact with physicalobjects in their environment; often, they must also communicate and reasonabout objects and their properties. Information about objects is typically produced,represented and used in different ways in various robotic sub-systems. Inparticular, high-level sub-systems often reason with object names and descriptions,while low-level sub-systems often use representations based on sensordata. In multi-robot systems, object representations are also distributed acrossrobots. Matters are further complicated by the fact that the sets of objects consideredby each robot and each sub-system often differ.Anchoring is the process of creating and maintaining associations betweendescriptions and perceptual information corresponding to the same physicalobjects. To illustrate, imagine you are asked to fetch “the large blue book fromthe bookshelf”. To accomplish this task, you must somehow associate the descriptionof the book you have in your mind with the visual representation ofthe appropriate book. Cooperative anchoring deals with associations betweendescriptions and perceptual information which are distributed across multipleagents. Unlike humans, robots can exchange both descriptions and perceptualinformation; in a sense, they are able to “see the world through each other’seyes”. Again, imagine you are asked to fetch a particular book, this time fromthe library. But now, in addition to your own visual representations, you alsohave access to information about books observed by others. This can allow youto find the correct book without searching through the entire library yourself.This thesis proposes an anchoring framework for both single-robot andcooperative anchoring that addresses a number of limitations in existing approaches.The framework represents information using conceptual spaces, allowingvarious types of object descriptions to be associated with uncertainand heterogeneous perceptual information. An implementation is describedwhich uses fuzzy logic to represent, compare and combine information. Theimplementation also includes a cooperative object localisation method whichtakes uncertainty in both observations and self-localisation into account. Experimentsusing simulated and real robots are used to validate the proposedframework and the cooperative object localisation method.
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| 8. |
- LeBlanc, Kevin, et al.
(författare)
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Cooperative anchoring in heterogeneous multi-robot systems
- 2008
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Ingår i: IEEE international conference on robotics and automation, ICRA 2008. - New York : IEEE. - 9781424416462 ; , s. 3308-3314
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Konferensbidrag (refereegranskat)abstract
- Highly heterogeneous robotic systems are becoming increasingly common, as are robotic systems integrated with smart environments. In such distributed systems, there are many different sources and types of information, which need to be coordinated and combined effectively. The problem of \emph{cooperative anchoring} is (roughly) the problem of, in a distributed system, determining which items of information refer to the same objects, and combining these items accordingly. In this paper, we define a general computational framework for cooperative anchoring inspired by work on conceptual spaces and (single-robot) perceptual anchoring. We also discuss an implementation of this framework which uses tools from fuzzy logic, and we present an illustrative experiment.
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| 9. |
- LeBlanc, Kevin, et al.
(författare)
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Cooperative information fusion in a network robot system
- 2007
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Ingår i: Proceedings of the 1st international conference on robot communication and coordination, RoboComm '07. - Piscataway, NJ : IEEE press. - 9789639799080 ; , s. Article no 42-
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Konferensbidrag (refereegranskat)abstract
- The vision of network robot systems involves robots embedded in smart environments, with which they can collaborate and communicate. In such systems, robots have access to many different sources and types of information, which need to be coordinated and combined effectively. In this work, we propose a framework which addresses the problem of combining heterogeneous information in a network robot system. The approach is inspired by work on conceptual spaces and perceptual anchoring, and is implemented using tools from fuzzy logic.
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| 10. |
- LeBlanc, Kevin, et al.
(författare)
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Issues of perceptual anchoring in ubiquitous robotic systems
- 2007
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Konferensbidrag (refereegranskat)abstract
- In ubiquitous robotic systems, robots are immersed in an environment containing an abundance of sensors, actuators and smart objects. In such a system, a robot can acquire information about an object from many different sources, possibly including the object itself. While this richness of information opens a new landscape of opportunities, it also adds the fundamental challenge of how to coordinate and integrate all the different types of information which are available. In this paper, we define a general computational framework to address this problem. Our framework is based on an extension of the concept of single-robot perceptual anchoring to the multi-robot case, and it can be applied to any ubiquitous robotics system. To make the framework more tangible, we apply it to a specific type of ubiquitous robotic system, called Ecology of Physically Embedded Intelligent Systems, or PEIS-Ecology. We also describe a sample implementation based on fuzzy logic, and present some illustrative experiments.
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