Refining, Implementing, and Evaluating the Extended Continuous Variable-Specific Resolutions of Feature Interactions

Systems that involve feature-oriented software development suffer from feature interactions, in which features affect one another’s behaviour in surprising ways. As the number of features increases, the complexity of examining feature combinations and fixing undesired interactions increases exponentially, such that the workload of resolving interactions comes to dominate feature development. The Feature Interaction Problem results from aiming resolve feature interaction by providing optimal resolutions. Resolution strategies combat the Feature Interaction Problem by offering default strategies that resolve entire classes of interactions, thereby reducing the work of the developer who is charged with the task of resolving interactions. However, most such approaches employ coarse-grained resolution strategies (e.g., feature priority) or a centralized arbitrator. This thesis focuses on evaluating and refining a proposed architecture that resolves features’ conflicting actions on system’s outputs. In this thesis, we extend a proposed architecture based on variable-specific resolution to enable co-resolution of related outputs and to promote smooth continuous resolutions over execution sequences. We implemented our approach within the PreScan simulator for advanced driver assistance systems, and performed a case study involving 15 automotive features that we implemented. We also devised and implemented three resolution strategies for the features’ outputs. The results of the case study show that the approach produces smooth and continuous resolutions of interactions throughout interesting scenarios

Continuous Variable-Specic Resolutions of Feature Interactions

© ACM 2019 Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected] that are assembled from independently developed features suffer from feature interactions, in which features affect one another's behaviour in surprising ways. The Feature Interaction Problem results from trying to implement an appropriate resolution for each interaction within each possible context, because the number of possible contexts to consider increases exponentially with the number of features in the system. Resolution strategies aim to combat the Feature Interaction Problem by offering default strategies that resolve entire classes of interactions, thereby reducing the work needed to resolve lots of interactions. However most such approaches employ coarse-grained resolution strategies (e.g., feature priority) or a centralized arbitrator. Our work focuses on employing variable-specific default-resolution strategies that aim to resolve at runtime features- conflicting actions on a system's outputs. In this paper, we extend prior work to enable co-resolution of interactions on coupled output variables and to promote smooth continuous resolutions over execution paths. We implemented our approach within the PreScan simulator and performed a case study involving 15 automotive features; this entailed our devising and implementing three resolution strategies for three output variables. The results of the case study show that the approach produces smooth and continuous resolutions of interactions throughout interesting scenarios.NSERC Discovery Grant, 155243-12 || Ontario Research Fund, RE05-044 || NSERC / Automotive Partnership Canada, APCPJ 386797 - 0

Landmark detection in 2D bioimages for geometric morphometrics: a multi-resolution tree-based approach

The detection of anatomical landmarks in bioimages is a necessary but tedious step for geometric morphometrics studies in many research domains. We propose variants of a multi-resolution tree-based approach to speed-up the detection of landmarks in bioimages. We extensively evaluate our method variants on three different datasets (cephalometric, zebrafish, and drosophila images). We identify the key method parameters (notably the multi-resolution) and report results with respect to human ground truths and existing methods. Our method achieves recognition performances competitive with current existing approaches while being generic and fast. The algorithms are integrated in the open-source Cytomine software and we provide parameter configuration guidelines so that they can be easily exploited by end-users. Finally, datasets are readily available through a Cytomine server to foster future research

Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs

In this work we propose a structured prediction technique that combines the virtues of Gaussian Conditional Random Fields (G-CRF) with Deep Learning: (a) our structured prediction task has a unique global optimum that is obtained exactly from the solution of a linear system (b) the gradients of our model parameters are analytically computed using closed form expressions, in contrast to the memory-demanding contemporary deep structured prediction approaches that rely on back-propagation-through-time, (c) our pairwise terms do not have to be simple hand-crafted expressions, as in the line of works building on the DenseCRF, but can rather be `discovered' from data through deep architectures, and (d) out system can trained in an end-to-end manner. Building on standard tools from numerical analysis we develop very efficient algorithms for inference and learning, as well as a customized technique adapted to the semantic segmentation task. This efficiency allows us to explore more sophisticated architectures for structured prediction in deep learning: we introduce multi-resolution architectures to couple information across scales in a joint optimization framework, yielding systematic improvements. We demonstrate the utility of our approach on the challenging VOC PASCAL 2012 image segmentation benchmark, showing substantial improvements over strong baselines. We make all of our code and experiments available at {https://github.com/siddharthachandra/gcrf}Comment: Our code is available at https://github.com/siddharthachandra/gcr

Uncertainty characteristics of generalized quantum measurements

The effects of any quantum measurement can be described by a collection of measurement operators {M_m} acting on the quantum state of the measured system. However, the Hilbert space formalism tends to obscure the relationship between the measurement results and the physical properties of the measured system. In this paper, a characterization of measurement operators in terms of measurement resolution and disturbance is developed. It is then possible to formulate uncertainty relations for the measurement process that are valid for arbitrary input states. The motivation of these concepts is explained from a quantum communication viewpoint. It is shown that the intuitive interpretation of uncertainty as a relation between measurement resolution and disturbance provides a valid description of measurement back action. Possible applications to quantum cryptography, quantum cloning, and teleportation are discussed.Comment: 8 pages, small additions on cloning and on definitions of delta A_mf, et

Long-term and large-scale hydrodynamical simulations of migrating planets

We present a new method that allows long-term and large-scale hydrodynamical simulations of migrating planets over a grid-based Eulerian code. This technique, which consists in a remapping of the disk by tracking the planetary migration, enables runs of migrating planets over a time comparable to the age of protoplanetary disks. This method also has the potential to address efficiently problems related with migration of multi-planet systems in gaseous disks, and to improve current results of migration of massive planets by including global viscous evolution as well as detailed studies of the co-orbital region during migration. We perform different tests using the public code FARGO3D to validate this method and compare its results with those obtained using a classical fixed grid.Comment: Accepted for publication in ApJ. For a movie describing the method, see https://youtu.be/66o0Z2lX8N