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共 228 条记录，以下是31-40 订阅

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Laboratory Investigation on Wave Characteristics Due to Hammer Impact on Different Types of Soil 7th

Laboratory Investigation on Wave Characteristics Due to Hamm...

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7th international conference on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics, ICRAGEE 2020

作者： Beena, K.S. Neethu, M. Jayakrishnan, Veena Cochin University of Science and Technology Kochi Kerala India

ISBN: (纸本)9789813340008

Pile foundations are suitable when the surface soil is fragile, and the load coming from the superstructures is very high. Direct Mud Circulation (DMC) method of piling was considered as the most reliable piling system all over the world. the chiseling action in DMC piling produces stress waves, and these waves may cause problems to the nearby structures. this paper deals with a laboratory model study to investigate the vibration propagation and attenuation characteristics of different types of soil at various test parameters. the responses of soil surface due to impact load were studied, and results showed that the various factors controlling the wave propagation of soil include the distance of impact from the source, relative density of soil, impact hammer energies. the peak vertical acceleration was measured using a triple-axis accelerometer placed at different positions and with the help of SeismoSignal software version 4.3, the corresponding peak particle velocity and displacements were evaluated. the soil dependent parameters k and n were found out from the peak particle velocity, and an attempt is made to develop an equation to predict vibrations on the tested soils. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wave propagation

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Type-theoretic constructions of the final coalgebra of the finite powerset functor 6

Type-theoretic constructions of the final coalgebra of the f...

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6th international conference on Formal structures for computation and Deduction, FSCD 2021

作者： Veltri, Niccolò Department of Software Science Tallinn University of Technology Estonia

ISBN: (纸本)9783959771917

the finite powerset functor is a construct frequently employed for the specification of nondeterministic transition systems as coalgebras. the final coalgebra of the finite powerset functor, whose elements characterize the dynamical behavior of transition systems, is a well-understood object which enjoys many equivalent presentations in set-theoretic foundations based on classical logic. In this paper, we discuss various constructions of the final coalgebra of the finite powerset functor in constructive type theory, and we formalize our results in the Cubical Agda proof assistant. Using setoids, the final coalgebra of the finite powerset functor can be defined from the final coalgebra of the list functor. Using types instead of setoids, as it is common in homotopy type theory, one can specify the finite powerset datatype as a higher inductive type and define its final coalgebra as a coinductive type. Another construction is obtained by quotienting the final coalgebra of the list functor, but the proof of finality requires the assumption of the axiom of choice. We conclude the paper with an analysis of a classical construction by James Worrell, and show that its adaptation to our constructive setting requires the presence of classical axioms such as countable choice and the lesser limited principle of omniscience. © 2021 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Formal languages

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Quantum entanglement based sentence similarity computation 7

Quantum entanglement based sentence similarity computation

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7th IEEE international conference on Progress in Informatics and Computing, PIC 2020

作者： Yu, Yan Qiu, Dong Yan, Ruiteng Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing China College of Mobile Telecommunications Chongqing University of Posts and Telecom Chongqing China College of Science Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9781728170862

Sentence representation is one of the foundations of natural language processing. A quantum entanglement-based approach is provided to determine the sentence similarity. the sentence embedding based on quantum computation considers the semantic structure of a sentence, tensor product and attentive mechanism. Main components of modifiers of a complete sentence are obtained by using the attentive mechanism combining with quantum entanglement of two consecutive notional words. the semantic features and syntactic structures of sentences are extracted by the tensor product of two consecutive notional words without any big-corpus or prior knowledge. Experimental results implemented on 17 datasets with an excellent effect show that taking the quantum entanglement into the sentence embedding yields improvements on mining semantic relations and syntactic structures. these results shed new light on sentence representation with limited resources, and represent a new step towards the quantum entanglement-based application in natural language processing. © 2020 IEEE.

关键词： Quantum entanglement

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19th international conference on foundations of software science and computation structures, FOSSACS 2016 held as part of the European Joint conferences on theory and Practice of software, ETAPS 2016

19th International Conference on Foundations of Software Sci...

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19th international conference on foundations of software science and computation structures, FOSSACS 2016 and Held as Part of the European Joint conferences on theory and Practice of software, ETAPS 2016

ISBN: (纸本)9783662496299

the proceedings contain 31 papers. the special focus in this conference is on Types, Recursion and Fixed-Points. the topics include: Comprehensive parametric polymorphism;guarded dependent type theory with coinductive types;dependent types and fibred computational effects;game semantics for bounded polymorphism;join inverse categories as models of reversible recursion;a coalgebraic view of bar recursion and bar induction;a new foundation for finitary corecursion;fixed-point elimination in the intuitionistic propositional calculus;contextual approximation and higher-order procedures;a theory of slicing for probabilistic control flow graphs;verification of parameterized communicating automata via split-width;robust equilibria in mean-payoff games;quantifier alternation for infinite words;synchronizing automata over nested words;on freeze LTL with ordered attributes;regular transformations of data words through origin information;trace refinement in labelled markov decision processes;qualitative analysis of VASS-induced MDPs;metric temporal logic with counting;distributed synthesis in continuous time;focused and synthetic nested sequents;reasoning about call-by-need by means of types;coverability trees for petri nets with unordered data;shortest paths in one-counter systems;the invariance problem for matrix semigroups;order-sorted rewriting and congruence closure;towards a formal theory of graded monads and profinite monads, profinite equations, and Reiterman’s theorem.

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IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive Computing (Plenary Panel Report-II) 20

IEEE ICCI*CC Series in Year 20: Latest Advances in Cognitive...

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20th IEEE international conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2021

作者： Kinsner, Witold Zhu, Haibin Baciu, George Luo, Guiming Rubio, Fernando Sui, Jie Huang, Runhe Hiraishi, Hironori Peng, Jun Chen, Liang Univ. of Manitoba FI2CICC Dept of ECE Winnipeg Canada Nipissing University FI2CICC ON Canada Hong Kong Polytechnic University FI2CICC Dept. of Computing Hong Kong Tsinghua University FI2CICC Software Institute Beijing China Complutense Univ. of Madrid FI2CICC Dept. of Computer Systems and Computation Spain Aberdeen University FI2CICC Aberdeen United Kingdom Hosei University FI2CICC Faculty of Computer and Information Sciences Japan Ashikaga University Faculty of Engineering Tochigi326-8558 Japan Chongqing Univ. of Science and Technology FI2CICC School of AI Chongqing China Univ. of Northern British Columbia Dept. of Computer Science BC Canada

ISBN: (纸本)9781665421195

Cognitive Computing (CC) is a contemporary field of fundamental intelligence theories and general AI technologies triggered by the transdisciplinary development in intelligence, computer, brain, knowledge, cognitive, robotic, and cybernetic sciences for engineering implementations. this paper presents a summary of the plenary panel (Part II) on the theoretical foundations of CI/CC and recent breakthroughs in AI engineering reported in the 20th IEEE international ICCI*CC conference (ICCI*CC'21). the latest advances in CI and CC towards general AI are presented by twenty-Two distinguished panelists. Strategic AI engineering applications in CI, CC, and cognitive systems are elaborated for abstract intelligence, cognitive robots, autonomous systems, intelligent vehicles, and safety-And-mission-critical systems. © 2021 IEEE.

关键词： Cognitive systems

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Strongly normalizing higher-order relational queries 5

Strongly normalizing higher-order relational queries

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5th international conference on Formal structures for computation and Deduction, FSCD 2020

作者： Ricciotti, Wilmer Cheney, James Laboratory for Foundations of Computer Science University of Edinburgh United Kingdom

ISBN: (纸本)9783959771559

Language-integrated query is a powerful programming construct allowing database queries and ordinary program code to interoperate seamlessly and safely. Language-integrated query techniques rely on classical results about monadic comprehension calculi, including the conservativity theorem for nested relational calculus. Conservativity implies that query expressions can freely use nesting and unnesting, yet as long as the query result type is a flat relation, these capabilities do not lead to an increase in expressiveness over flat relational queries. Wong showed how such queries can be translated to SQL via a constructive rewriting algorithm, and Cooper and others advocated higher-order nested relational calculi as a basis for language-integrated queries in functional languages such as Links and F#. However there is no published proof of the central strong normalization property for higher-order nested relational queries: a previous proof attempt does not deal correctly with rewrite rules that duplicate subterms. this paper fills the gap in the literature, explaining the difficulty with a previous proof attempt, and showing how to extend the >>-lifting approach of Lindley and Stark to accommodate duplicating rewrites. We also sketch how to extend the proof to a recently-introduced calculus for heterogeneous queries mixing set and multiset semantics. © Wilmer Ricciotti and James Cheney;licensed under Creative Commons License CC-BY 5th international conference on Formal structures for computation and Deduction (FSCD 2020).

关键词： Semantics

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Efficient computation Techniques for a Standard Topology Optimisation Routine 13th

Efficient Computation Techniques for a Standard Topology Opt...

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13th international conference on Telematics and Computing, WITCOM 2024

作者： Hurtado-Pérez, A.B. Hernández-Gómez, J.J. Mata-Rivera, M.F. Yáñez-Casas, G.A. Instituto Politécnico Nacional Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas Mexico City Mexico Instituto Politécnico Nacional Centro de Desarrollo Aeroespacial Mexico City Mexico

ISBN: (纸本)9783031772894

Topology Optimisation (TO) is a powerful optimisation technique that is used mainly in research and engineering areas to derive optimal and sometimes innovative material layouts, the main objective of TO usually concerns the reduction of material volume (weight) while trying to improve mechanical performance without compromising its structural resistance to imposed loads. this can be achieved by systematically re-distributing material contained in a specific design space, this technique often results in intricate and complex geometries that may be two-dimensional or three-dimensional depending on the specific application. Such a technique requires a way to link a physical model with a computational representation, in this sense, the always popular, Finite Element Method (FEM) provides the necessary computational framework to evaluate the mechanical properties of optimised designs, in further detail, FEM is utilised to model the behaviour of structures (any structure is valid) subjected to external forces (which can be of very different nature), enabling practitioners to simulate and analyse complex systems. FEM works on meshes of simple discrete elements and their corresponding nodes, while elasticity theory and mathematical modelling allow the obtention of the structural response to mechanical loads. Such response is then used as the basis over which TO routines work. Many TO methods can be used to obtain optimal designs, however, direct programming of them often requires elaborated codes that are not always accessible or even easy to understand. Some authors leave cumbersome FEM codes to third-party software, others, offer practical simpler codes to allow beginners to understand the basic TO method. In this second approach we revise one code implementation, that, despite solving the TO problem using a discrete TO approach, it leaves the practitioner with an antiquated, slow, resource consuming and often non-scalable implementation. the main objective of this work

关键词： Topology

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Structure Preserved Graph Reordering for Fast Graph Processing without the Pain 22

Structure Preserved Graph Reordering for Fast Graph Processi...

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22nd IEEE international conference on High Performance Computing and Communications, 18th IEEE international conference on Smart City and 6th IEEE international conference on Data science and Systems, HPCC-SmartCity-DSS 2020

作者： Huang, Baofu Liu, Zhidan Wu, Kaishun Shenzhen University College of Computer Science and Software Engineering China

ISBN: (纸本)9781728176499

By optimizing the data layout ahead-of-Time, graph reordering can effectively improve the memory access locality in graph processing. the reordered graphs derived by sophisticated graph reordering approaches can greatly speedup the executions of most graph algorithms, while they incur huge computation overheads. Although lightweight approaches indeed reduce the reordering costs, they cannot achieve the best speedup performances. this is because they merely operate vertices of high-degrees and inadvertently destroy the community structures hidden in the graph. In this paper, we thus propose Sorder to balance the speedup performance and the reordering overhead. Sorder achieves better locality by preserving structural properties of graphs. Specifically, it mainly exploits neighborhood relations to renumber vertices and preferentially reorders vertices of high-degree ahead of the other vertices. We further enhance the design with the hypernode concept, which gathers neighboring vertices of low-degree to form a virtual vertex. therefore, Sorder can consecutively rearrange more neighboring vertices, such that protecting the community structures. Extensive experiments with 5 representative graph algorithms and 7 real-world graphs demonstrate that Sorder can achieve comparable speedup performance as Gorder, the state-of-the-Art approach, while significantly reducing the reordering overhead. © 2020 IEEE.

关键词： Graph algorithms

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foundations of software science and computation structures: 18th international conference, FOSSACS 2015 held as part of the European joint conferences on theory and practice of software, ETAPS 2015 London, UK, april 11–18, 2015 proceedings 18th

Foundations of software science and computation structures: ...

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18th international conference on foundations of software science and computation structures, FoSSaCS 2015 Held as Part of the European Joint conferences on theory and Practice of software, ETAPS 2015

作者： Pitts, Andrew University of Cambridge Cambridge United Kingdom

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4th international Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th international Workshop on Mathematical foundations of computational Anatomy, MFCA 2019, held in conjunction with the 22nd international conference on Medical Imaging and Computer Assisted Intervention, MICCAI 2019

4th International Workshop on Multimodal Brain Image Analysi...

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4th international Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th international Workshop on Mathematical foundations of computational Anatomy, MFCA 2019, held in conjunction with the 22nd international conference on Medical Imaging and Computer Assisted Intervention, MICCAI 2019

ISBN: (纸本)9783030332259

the proceedings contain 23 papers. the special focus in this conference is on Multimodal Brain Image Analysis. the topics include: Biological Knowledge Guided Deep Neural Network for Brain Genotype-Phenotype Association Study;Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network;CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation;brainPainter: A software for the Visualisation of Brain structures, Biomarkers and Associated Pathological Processes;structural Similarity Based Anatomical and Functional Brain Imaging Fusion;multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution;prioritizing Amyloid Imaging Biomarkers in Alzheimer’s Disease via Learning to Rank;diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models;3D Mapping of Serial Histology Sections with Anomalies Using a Novel Robust Deformable Registration Algorithm;spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development;An Edge Enhanced SRGAN for MRI Super Resolution in Slice-Selection Direction;surface Foliation Based Brain Morphometry Analysis;mixture Probabilistic Principal Geodesic Analysis;a Geodesic Mixed Effects Model in Kendall’s Shape Space;An As-Invariant-As-Possible GL+(3) -Based Statistical Shape Model;exploring Functional Connectivity Biomarker in Autism Using Group-Wise Sparse Representation;classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding;mapping the Spatio-Temporal Functional Coherence in the Resting Brain;Species-Preserved Structural Connections Revealed by Sparse Tensor CCA;identification of Abnormal Cortical 3-Hinge Folding Patterns on Autism Spectral Brains;exploring Brain Hemodynamic Response Patterns via Deep Recurrent Autoencoder;3D Convolutional Long-Short Term Memory Network for Spatiotemporal Modeling of fMRI Data.

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