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Navigating the Maize: Cyclic and conditional computational graphs for molecular simulation

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arXiv 2024年

作者： Löhr, Thomas Assante, Michele Dodds, Michael Cao, Lili Kabeshov, Mikhail Janet, Jon-Paul Klähn, Marco Engkvist, Ola Molecular AI Discovery Sciences R&D AstraZeneca Gothenburg431 50 Sweden Innovation Centre in Digital Molecular Technologies Department of Chemistry University of Cambridge Lensfield Rd CambridgeCB2 1EW United Kingdom Compound Synthesis & Management The Discovery Centre AstraZeneca 1 Francis Crick Avenue Cambridge Biomedical Campus CambridgeCB2 0AA United Kingdom University of St Andrews St AndrewsKY16 9AJ United Kingdom Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden

Many computational chemistry and molecular simulation workflows can be expressed as graphs. This abstraction is useful to modularize and potentially reuse existing components, as well as provide parallelization and ease reproducibility. Existing tools represent the computation as a directed acyclic graph (DAG), thus allowing efficient execution by parallelization of concurrent branches. These systems can, however, generally not express cyclic and conditional workflows. We therefore developed Maize, a workflow manager for cyclic and conditional graphs based on the principles of flow-based programming. By running each node of the graph concurrently in separate processes and allowing communication at any time through dedicated inter-node channels, arbitrary graph structures can be executed. We demonstrate the effectiveness of the tool on a dynamic active learning task in computational drug design, involving the use of a small molecule generative model and an associated scoring system, and on a reactivity prediction pipeline using quantum-chemistry and semiempirical approaches. © 2024, CC BY-NC-ND.

关键词： Flow graphs

Towards a Model of Testers' Cognitive Processes: Software Testing as a Problem Solving Approach

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arXiv 2020年

作者： Enoiu, Eduard Tukseferi, Gerald Feldt, Robert Software Testing Laboratory Mälardalen University Västerås Sweden Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden

Software testing is a complex, intellectual activity based (at least) on analysis, reasoning, decision making, abstraction and collaboration performed in a highly demanding environment. Naturally, it uses and allocates multiple cognitive resources in software testers. However, while a cognitive psychology perspective is increasingly used in the general software engineering literature, it has yet to find its place in software testing. To the best of our knowledge, no theory of software testers' cognitive processes exists. Here, we take the first step towards such a theory by presenting a cognitive model of software testing based on how problem solving is conceptualized in cognitive psychology. Our approach is to instantiate a general problem solving process for the specific problem of creating test cases. We then propose an experiment for testing our cognitive test design model. The experiment makes use of verbal protocol analysis to understand the mechanisms by which human testers choose, design, implement and evaluate test cases. An initial evaluation was then performed with five software engineering master students as subjects. The results support a problem solving-based model of test design for capturing testers' cognitive processes. Copyright © 2020, The Authors. All rights reserved.

关键词： Software testing

Model properties for efficient synthesis of nonblocking modular supervisors

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arXiv 2020年

作者： Goorden, Martijn van de Mortel-Fronczak, Joanna Reniers, Michel Fabian, Martin Fokkink, Wan Rooda, Jacobus Department of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands Department of Electrical Engineering Chalmers University of Technology Göteborg Sweden Department of Computer Science Vrije Universiteit Amsterdam Amsterdam Netherlands

Supervisory control theory provides means to synthesize supervisors for systems with discrete-event behavior from models of the uncontrolled plant and of the control requirements. The applicability of supervisory control theory often fails due to a lack of scalability of the algorithms. This paper proposes a format for the requirements and a method to ensure that the crucial properties of controllability and nonblockingness directly hold, thus avoiding the most computationally expensive parts of synthesis. The method consists of creating a control problem dependency graph and verifying whether it is acyclic. Vertices of the graph are modular plant components, and edges are derived from the requirements. In case of a cyclic graph, potential blocking issues can be localized, so that the original control problem can be reduced to only synthesizing supervisors for smaller partial control problems. The strength of the method is illustrated on two case studies: a production line and a roadway tunnel. Copyright © 2020, The Authors. All rights reserved.

关键词： Directed graphs

Self-stabilizing Uniform Reliable Broadcast (preliminary version)

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arXiv 2020年

作者： Lundström, Oskar Raynal, Michel Schiller, Elad M. Department of Computer Science and Engineering Chalmers University of Technology GothenburgSE-412 96 Sweden Institut Universitaire de France IRISA ISTIC Université de Rennes Rennes Cedex35042 France Department of Computing Polytechnic University Hong Kong Department of Computer Science and Engineering Chalmers University of Technology GothenburgSE-412 96 Sweden

We study a well-known communication abstraction called Uniform Reliable Broadcast (URB). URB is central in the design and implementation of fault-tolerant distributed systems, as many non-trivial fault-tolerant distributed applications require communication with provable guarantees on message deliveries. Our study focuses on fault-tolerant implementations for time-free message-passing systems that are prone to node-failures. Moreover, we aim at the design of an even more robust communication abstraction. We do so through the lenses of self-stabilization—a very strong notion of fault-tolerance. In addition to node and communication failures, self-stabilizing algorithms can recover after the occurrence of arbitrary transient faults;these faults represent any violation of the assumptions according to which the system was designed to operate (as long as the algorithm code stays intact). This work proposes the first self-stabilizing URB solution for time-free message-passing systems that are prone to node-failures. The proposed algorithm has an O(bufferUnitSize) stabilization time (in terms of asynchronous cycles) from arbitrary transient faults, where bufferUnitSize is a predefined constant that can be set according to the available memory. Moreover, the communication costs of our algorithm are similar to the ones of the non-self-stabilizing state-of-the-art. The main differences are that our proposal considers repeated gossiping of O(1) bits messages and deals with bounded space (which is a prerequisite for self-stabilization). Specifically, each node needs to store up to bufferUnitSize · n records and each record is of size O(ν + n log n) bits, where n is the number of nodes in the system and ν is the number of bits needed to encode a single URB instance. Copyright © 2020, The Authors. All rights reserved.

关键词： Fault tolerance

Hierarchical compressed sensing

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arXiv 2021年

作者： Eisert, J. Flinth, A. Groß, B. Roth, Ingo Wunder, G. Center for Complex Quantum Systems Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany Institute for Electrical Engineering Chalmers University of Technology Gothenburg Sweden Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany Quantum Research Centre Technology Innovation Institute Abu Dhabi UAE. Dahlem Center for Complex Quantum Systems Freie Universität Berlin Berlin Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany

Compressed sensing is a paradigm within signal processing that provides the means for recovering structured signals from linear measurements in a highly efficient manner. Originally devised for the recovery of sparse signals, it has become clear that a similar methodology would also carry over to a wealth of other classes of structured signals. In this work, we provide an overview over the theory of compressed sensing for a particularly rich family of such signals, namely those of hierarchically structured signals. Examples of such signals are constituted by blocked vectors, with only few non-vanishing sparse blocks. We present recovery algorithms based on efficient hierarchical hard-thresholding. The algorithms are guaranteed to converge, in a stable fashion both with respect to measurement noise as well as to model mismatches, to the correct solution provided the measurement map acts isometrically restricted to the signal class. We then provide a series of results establishing the required condition for large classes of measurement ensembles. Building upon this machinery, we sketch practical applications of this framework in machine-type communications and quantum tomography. Copyright © 2021, The Authors. All rights reserved.

关键词： Compressed sensing

Photoluminescence Mapping of Mid-Wave Infrared Inas/Gasb Type Ii Superlattice: Influence of Materials and Processes on In-Plane Optoelectronic Uniformity

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SSRN

SSRN 2022年

作者： Shi, Zhangyong Yan, Dingyu Zhang, Yanchao Zhang, Fan Chen, Yimin Gu, Chenjie Chen, Xiren Shao, Jun Wang, Shumin Shen, Xiang Laboratory of Infrared Materials and Devices Key Laboratory of Photoelectric Detection Materials and Devices of Zhejiang Province Research Institute of Advanced Technology Ningbo University Ningbo315211 China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China Zhejiang Supermat Sen-Ray Optoelectronics Co. Ltd. Ningbo315400 China Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg41296 Sweden State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chinese Academy of Sciences Shanghai200083 China

The imaging performance of infrared focal plane array (FPA) is largely limited by the non-uniformity of in-plane photoelectric response of InAs/GaSb type II superlattices (T2SL) consisting of a new hundred or more thin layers. Fundamentally, the non-uniformity results from the materials property variation as well as process fluctuations over the area of centimeter square. Thus, in order to improve the imaging performance of an FPA detector, it is necessary to accurately detect and evaluate the influence of materials and processes on the uniformity of internal photoelectric response. In this work, the spatially resolved photoluminescence (PL) was implemented to detect the micro-scale mesa pixels, and the effects of materials and processes on the photoelectric uniformity within the plane were studied for the first time. And the modulated PL-mapping technology based on step scanning Fourier transform infrared (ssFTIR) spectrometer is used to extract parameters from each test spectrum, such as PL peak energy, linewidth, integral intensity, and then they are analyzed in the form of two-dimensional spatial mapping. The result shows that the variation of T2SL material properties accounts for 29% of the non-uniformity, and the rest 71% results from the process fluctuation. Especially, the etching process has a great influence on the uniformity. It reveals that the non-uniformity of the integral intensity of the sample after etching is increased by 2.44 times compared with that before the etching. Thereafter, a layer of SiO2 film was deposited to passivate the surface, it shows that the non-uniformity returns to the level before the etching, which directly proves that the passivation process can improve the photoelectric response uniformity of the infrared FPA detector. © 2022, The Authors. All rights reserved.

关键词： Etching

Physical limitations of phased array antennas

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arXiv 2020年

作者： Ludvig-Osipov, Andrei Hannula, Jari-Matti Naccachian, Patricia Jonsson, B.L.G. The School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-10044 Sweden The Department of Electrical Engineering Chalmers University of Technology GöteborgSE-41296 Sweden The Department of Electrical and Computer Engineering American University of Beirut Beirut Lebanon

In this paper, the bounds on the Q-factor, a quantity inversely proportional to bandwidth, are derived and investigated for narrow-band phased array antennas. Arrays in free space and above a ground plane are considered. The Q-factor bound is determined by solving a minimization problem over the electric current density. The support of these current densities is on an element-enclosing region, and the bound holds for lossless antenna elements enclosed in this region. The Q-factor minimization problem is formulated as a quadratically constrained quadratic optimization problem that is solved either by a semidefinite relaxation or an eigenvalue-based method. We illustrate numerically how these bounds can be used to determine trade-off relations between the Q-factor and other design specifications: element form-factor, size, efficiency, scanning capabilities, and polarization purity. Copyright © 2020, The Authors. All rights reserved.

关键词： Quadratic programming

IMAGE-TO-IMAGE TRANSLATION for ENHANCED FEATURE MATCHING, IMAGE RETRIEVAL and VISUAL LOCALIZATION 1

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IMAGE-TO-IMAGE TRANSLATION for ENHANCED FEATURE MATCHING, IM...

1st Photogrammetric Image Analysis and Munich Remote Sensing Symposium, PIA 2019+MRSS 2019

作者： Mueller, M.S. Sattler, T. Pollefeys, M. Jutzi, B. Institute of Photogrammetry and Remote Sensing Karlsruhe Institute of Technology Germany Department of Electrical Engineering Chalmers University of Technology Sweden Department of Computer Science ETH Zurich Switzerland Microsoft

The performance of machine learning and deep learning algorithms for image analysis depends significantly on the quantity and quality of the training data. The generation of annotated training data is often costly, time-consuming and laborious. Data augmentation is a powerful option to overcome these drawbacks. Therefore, we augment training data by rendering images with arbitrary poses from 3D models to increase the quantity of training images. These training images usually show artifacts and are of limited use for advanced image analysis. Therefore, we propose to use image-to-image translation to transform images from a rendered domain to a captured domain. We show that translated images in the captured domain are of higher quality than the rendered images. Moreover, we demonstrate that image-to-image translation based on rendered 3D models enhances the performance of common computer vision tasks, namely feature matching, image retrieval and visual localization. The experimental results clearly show the enhancement on translated images over rendered images for all investigated tasks. In addition to this, we present the advantages utilizing translated images over exclusively captured images for visual localization. © 2019 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information sciences. All rights reserved.

关键词： Image analysis

Parallel capsule networks for classification of white blood cells

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arXiv 2021年

作者： Vigueras-Guillén, Juan P. Patra, Arijit Engkvist, Ola Seeliger, Frank CVRM Safety Clinical Pharmacology and Safety Science BioPharmaceuticals R&D AstraZeneca Gothenburg Sweden Digitisation and AI Clinical Pharmacology and Safety Science BioPharmaceuticals R&D AstraZeneca Cambridge United Kingdom Molecular AI Discovery Science BioPharmaceuticals R&D AstraZeneca Gothenburg Sweden Department of Computer Science & Engineering Chalmers University of Technology Gothenburg Sweden

Capsule Networks (CapsNets) is a machine learning architecture proposed to overcome some of the shortcomings of convolutional neural networks (CNNs). However, CapsNets have mainly outperformed CNNs in datasets where images are small and/or the objects to identify have minimal background noise. In this work, we present a new architecture, parallel CapsNets, which exploits the concept of branching the network to isolate certain capsules, allowing each branch to identify different entities. We applied our concept to the two current types of CapsNet architectures, studying the performance for networks with different layers of capsules. We tested our design in a public, highly unbalanced dataset of acute myeloid leukaemia images (15 classes). Our experiments showed that conventional CapsNets show similar performance than our baseline CNN (ResNeXt-50) but depict instability problems. In contrast, parallel CapsNets can outperform ResNeXt-50, is more stable, and shows better rotational invariance than both, conventional CapsNets and ResNeXt-50. © 2021, CC BY-NC-SA.

关键词： Convolutional neural networks