| 1. |
- Bohlin, Robert, 1972, et al.
(författare)
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Data Flow and Communication Framework Supporting Digital Twin for Geometry Assurance
- 2018
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Ingår i: ASME 2017 International Mechanical Engineering Congress and Exposition. ; 2
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Konferensbidrag (refereegranskat)abstract
- Faster optimization algorithms, increased computer power and amount of available data, can leverage the area of simulation towards real-time control and optimization of products and production systems. This concept — often referred to as Digital Twin — enables real-time geometry assurance and allows moving from mass production to more individualized production. To master the challenges of a Digital Twin for Geometry Assurance the project Smart Assembly 4.0 gathers Swedish researchers within product development, automation, virtual manufacturing, control theory, data analysis and machine learning. The vision of Smart Assembly 4.0 is the autonomous, self-optimizing robotized assembly factory, which maximizes quality and throughput, while keeping flexibility and reducing cost, by a sensing, thinking and acting strategy. The concept is based on active part matching and self-adjusting equipment which improves geometric quality without tightening the tolerances of incoming parts. The goal is to assemble products with higher quality than the incoming parts. The concept utilizes information about individual parts to be joined (sensing), selects the best combination of parts (thinking) and adjust locator positions, clamps, weld/rivet positions and sequences (acting). The project is ongoing, and this paper specifies and highlights the infrastructure, components and data flows necessary in the Digital Twin in order to realize Smart Assembly 4.0. The framework is generic, but the paper focuses on a spot weld station where two robots join two sheet metal parts in an adjustable fixture.
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| 2. |
- Cvijovic, Marija, 1977, et al.
(författare)
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Bridging the gaps in systems biology
- 2014
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Ingår i: Molecular Genetics and Genomics. - : Springer Science and Business Media LLC. - 1617-4615 .- 1617-4623. ; 289:5, s. 727-734
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Tidskriftsartikel (refereegranskat)abstract
- Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding-the elucidation of the basic and presumably conserved "design" and "engineering" principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.
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| 3. |
- Hagmar, Jonas, 1974, et al.
(författare)
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Image analysis in non-linear microscopy
- 2008
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Ingår i: Journal of Optical Society of America. ; 25, s. 2195-2206
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Tidskriftsartikel (refereegranskat)abstract
- The ability to automatically extract quantitative data from non-linear microscopy images is here explored, taking their non-linear character into account. Objects of different degree of complexity were investigated: theoretical images of spherical objects, experimentally collected Coherent Anti-Stokes Raman Scattering images of polystyrene spheres in background generating agar, well-separated lipid droplets in living yeast cells and conglomerations of lipid droplets in living C. elegans nematodes. The in linear microscopy useful measure of Full-Width-at-Half-Maximum (FWHM) was shown to provide inadequate measures of object size due the non-linear density dependence of the signal. Instead, the capability of four state-of-the-art image analysis algorithms was evaluated. Among these Local thresholding was found to be the widest applicable segmentation algorithm.
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| 4. |
- Hagmar, Jonas, 1974, et al.
(författare)
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Image analysis of lipid deposits in living organisms visualized by CARS microscopy
- 2007
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Ingår i: Proc. Soc. Photo-Opt. Instrum. Eng. (SPIE). - 9780819466297 ; 6511:17
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Konferensbidrag (refereegranskat)abstract
- CARS microscopy is a novel technique for imaging bio-molecules in living cells using the molecular vibration as contrast mechanism. Global and local thresholding, state-of-the art image analysis techniques (watersheds, level sets) and a recent technique for anisotropic Gaussian fitting are used to segment lipid droplets in CARS microscopy images of, S. cerevisiae (yeast cells). The ability to extract quantitative information, such as vesicle size, is validated by means of images of polystyrene beads of well-defined size. Theoretical modeling of the CARS signal is performed, linking the physical object to its representation as a CARS microscopy image, as an attempt to take the non-linear relationship into account for refined image analysis. Theoretically modeled images of polystyrene beads correspond well to those experimentally obtained. Of the image analysis tools, it is found that global and local thresholding have limited use for segmentation of CARS microscopy images. Watershed and level set segmentation underestimate the size of a segmented object. Anisotropic Gaussian fitting overestimates the size of the object in the presence of non-resonant background. Reduced overestimation is achieved by background suppression. This emphasizes the importance of background removal in the CARS microscopy images, both experimentally as well as analytically. Automated image analysis of CARS microscopy images of S. cerevisiae is shown to be an excellent approach for in-depth studies of fat deposits in living organisms, with prospects for including human cells. Such a methodology will be of outmost importance for improved understanding of the mechanisms behind the development of obesity.
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| 5. |
- Hagmar, Jonas, 1974, et al.
(författare)
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Optimal parameterization of posterior densities using homotopy
- 2011
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Ingår i: 14th International Conference on Information Fusion, Fusion 2011; Chicago, IL; 5 July 2011 through 8 July 2011. - 9781457702679
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Konferensbidrag (refereegranskat)abstract
- In filtering algorithms, it is often desirable that the prior and posterior densities share a common density parameterization. This can rarely be done exactly. Instead it is necessary to seek a density from the same family as the prior which closely approximates the true posterior. We extend a method for computing the optimal parameter values for representing the posterior within a given parameterization. This is achieved by minimizing the deviation between the parameterized density and a homotopy that deforms the prior density into the posterior density. We derive novel results both for the general case, and for specific choices of measures of deviation. This includes approximate solution methods, that prove useful when we demonstrate how the method can be used with common density parameterizations. For an example with a non-linear measurement model, the method is shown to be more accurate than the Extended, Unscented and Cubature Kalman filters.
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