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IEEE International Conference on Bioinf.rmatics and Biomedicine (BIBM)

作者： Sufang Li Jun Wang Maozu Guo Xiangliang Zhang College of Computer and Information Sciences Southwest University Chongqing China Joint SDU-NTU Centre for Artificial Intelligence Research Shandong University Jinan China College of Elec. &Inf. Eng. Beijing University of Civil Engineering & Architecture Beijing China CEMSE King Abdullah University of Science and Technology Thuwal SA

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Identifying driver pathway is a critical step to uncover the natural laws of the occurrence and progression of disease. Many studies show that multiple pathways often function cooperatively in carcinogenesis. However, how to computationally identify cooperative driver pathways of cancers is not well studied yet. Existing cooperative driver pathway identification methods either suffer from single type of genetic inf.rmation source or computation difficulty. In this paper, we proposed a method (CDPLP) based on hierarchical clustering and link prediction. CDPLP firstly devises a new similarity metric to quantity the exclusivity and co-expression of two gene modules, and thus to obtain gene sets with exclusivity by hierarchical clustering. Next, it uses link prediction on the pathway-pathway interaction network to replenish the interactions between pathways. After that, CDPLP combines the gene sets and updated pathway network to discover the pathway pairs with high functional interaction and occurrence as cooperative pathways. CDPLP can make full use of multiple genetic inf.rmation sources such as the mutation data, gene-gene interaction data and pathway-pathway network, and facilitate the optimization solution. We evaluated the performance of CDPLP on TCGA breast cancer (BRCA) dataset and compared it with other popular methods. The results show that cooperative driver pathways identified by CDPLP are highly associated with the target cancer, and are involved with carcinogenesis and several key biological processes.

关键词： Cancer Measurement Heterogeneous networks Bioinf.rmatics Tumors Optimization Genomics

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DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks

arXiv

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arXiv 2021年

作者： Chopra, Ayush Raskar, Ramesh Gel, Esma S. Subramanian, Jayakumar Krishnamurthy, Balaji Romero-Brufau, Santiago Pasupathy, Kalyan S. Kingsley, Thomas C. Wilson, James R. Media Lab Massachusetts Institute of Technology 75 Amherst St CambridgeMA02139 United States School of Comp. Inf. and Decision Systems Eng. Arizona State University 699 S Mill Avenue TempeAZ85281 United States Media and Data Science Research Lab Adobe Block A Uttar Pradesh Noida201304 India Department of Healthcare Systems Engineering Mayo Clinic 200 1st St SW RochesterMN55905 United States Alix School of Science and Medicine Mayo Clinic 200 1st St SW RochesterMN55905 United States Department of Industrial and Systems Engineering North Carolina State University

We introduce DeepABM, a framework for agent-based modeling that leverages geometric message passing of graph neural networks for simulating action and interactions over large agent populations. Using DeepABM allows scaling simulations to large agent populations in real-time and running them efficiently on GPU architectures. To demonstrate the effectiveness of DeepABM, we build DeepABM-COVID simulator to provide support for various non-pharmaceutical interventions (quarantine, exposure notification, vaccination, testing) for the COVID-19 pandemic, and can scale to populations of representative size in real-time on a GPU. Specifically, DeepABM-COVID can model 200 million interactions (over 100,000 agents across 180 time-steps) in 90 seconds, and is made available online to help researchers with modeling and analysis of various interventions. We explain various components of the framework and discuss results from one research study to evaluate the impact of delaying the second dose of the COVID-19 vaccine in collaboration with clinical and public health experts. While we simulate COVID-19 spread, the ideas introduced in the paper are generic and can be easily extend to other forms of agent-based simulations. Furthermore, while beyond scope of this document, DeepABM enables inverse agent-based simulations which can be used to learn physical parameters in the (micro) simulations using gradient-based optimization with large-scale real-world (macro) data. We are optimistic that the current work can have interesting implications for bringing ABM and AI communities closer. © 2021, CC BY.

关键词： Vaccines

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Operation Dependencies in Loop Pipelining for High-Level Synthesis

Operation Dependencies in Loop Pipelining for High-Level Syn...

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2018 South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA_CECNSM 2018

作者： Dimitriou, Georgios Dossis, Michael Stamoulis, Georgios Dept. of Computer Science University of Thessaly Lamia Greece Dept. of Inf. Engineering TEI of W. Macedonia Kastoria Greece Dept. of Electrical and Computer Engineering University of Thessaly Volos Greece

ISBN: (纸本)9786188331419

Research and industry interest in high-level synthesis has been renewed in the last few years, proven by the introduction of new tools or improved versions of existing tools. Academic tools like Gaut or CCC have recently appeared in new versions with expanded functionality in order to cover increased hardware design requirements. Likewise, industrial tools like Xilinx VivadoHLS or, more recently, Cadence Stratus have appeared and are continuously evolving in their effort to succeed in the market. One technology that high-level synthesis tools have chosen to invest on is compiler-driven code optimizations, which are a promising means to improve efficiency of automatically generated hardware. Loop transformations are among the most popular compiler optimizations, for both software and hardware targets. Loop unrolling and loop pipelining, coupled with careful instruction reordering, can deliver highly optimized output. Instruction dependencies play a significant role in such optimizations, limiting performance improvement for the final code. In this paper, we discuss the issue of dependencies among loop body operations, especially those forming cycles, and their impact on high-level synthesis. We present results from experiments with several benchmarks on the CCC and VivadoHLS tools, showing that CCC can deliver better output than VivadoHLS in the presence of complex operation dependence cycles. © 2018 Tei of Western Macedonia.

关键词： High level synthesis

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New Parallel Algorithms for All Pairwise Computation on Large HPC Clusters

New Parallel Algorithms for All Pairwise Computation on Larg...

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IEEE International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

作者： Tao Tang Hao Wu Wei Bao Pengyi Yang Dong Yuan Bing Bing Zhou Faculty of Engineering and IT University of Technology Sydney Sydney Australia School of Computer Science University of Sydney Sydney Australia School of Mathematics & Statistics University of Sydney Sydney Australia School of Elec. & Inf. Engineering University of Sydney Sydney Australia

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

All pairwise computation is defined as performing computation between every pair of the elements in a given dataset. It is often a necessary first step in a number of bioinf.rmatics applications. Many of such applications require multiple terabytes of main memory and take multiple peta floating point operations to complete the computation. Therefore, large HPC clusters are needed to tackle these large-scale computational problems. Conventionally designed parallel algorithms using data partitioning may have a scalability issue, i.e., for a given problem of fixed size the efficiency may decrease if the number of compute nodes is increased (Amdahl's law). In this paper we introduce a new method for parallel algorithm design. Using this method we first design an efficient one-dimensional (1D) ring algorithm and then a two-dimensional (2D) algorithm based on the 1D ring for all pairwise computation. When increasing the compute nodes, instead of reducing the block size, we make multiple copies of the original data blocks in the 1D ring and distribute them across the added compute nodes in the other dimension. By properly organizing the compute nodes the communication overhead can be reduced to a minimum in this two-dimensional setting. Experiments on a Cray XC40 HPC supercomputer show that our new algorithms are very efficient and scalable for large-scale all pairwise computation on large HPC clusters.

关键词： Parallel algorithms Clustering algorithms Australia Two dimensional displays Partitioning algorithms Task analysis Correlation

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Prosodic entrainment and trust in human-computer interaction 9

Prosodic entrainment and trust in human-computer interaction

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9th International Conference on Speech Prosody, SP 2018

作者： Beňuš, Štefan Trnka, Marian Kuric, Eduard Martá, Lukáš Gravano, Agustín Hirschberg, Julia Levitan, Rivka Constantine the Philosopher University in Nitra Slovakia Institute of Informatics Slovak Academy of Sciences Bratislava Slovakia Faculty of Informatics and Inf. Technologies Slovak Univ of Technology Bratislava Slovakia Depart. de Computación FCEyN Universidad de Buenos Aires & CONICET-UBA Argentina Department of Computer Science Columbia University New York United States Department of Computer and Information Science Brooklyn College CUNY United States

Despite the prevalence of findings supporting the positive relationship between entrainment and social aspects, previous research does not provide a clearly converging picture and several recent studies stress the importance of disentrainment for smooth spoken interactions. We have developed a novel scenario design to explore how prosodic entrainment relates to the trust of a human user in an avatar's ability to provide good advice. Our results with Slovak subjects suggest that 1) applications might need to boost the entrainment effect to affect trust of humans towards avatars, 2) user’s sex plays a role in developing the relationship between trust and entrainment, and 3) females tend to prefer the advice of disentrainning avatars. © 2018, International Speech Communications Association. All Rights Reserved.

关键词： Human computer interaction

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Compression with the tudocomp framework 16

Compression with the tudocomp framework

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16th Symposium on Experimental Algorithms, SEA 2017

作者： Dinklage, Patrick Fischer, Johannes Köppl, Dominik Lobel, Marvin Sadakane, Kunihiko Department of Computer Science TU Dortmund Dortmund Germany Grad. School of Inf. Science and Technology University of Tokyo Tokyo Japan

ISBN: (纸本)9783959770361

We present a framework facilitating the implementation and comparison of text compression algorithms. We evaluate its features by a case study on two novel compression algorithms based on the Lempel-Ziv compression schemes that perform well on highly repetitive texts. © Patrick Dinklage, Johannes Fischer, Dominik Koppl, Marvin Lobel, and Kunihiko Sadakane.

关键词： Algorithm engineering Application of string algorithms Compression framework Compression library Lossless compression

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Author Correction: Perceived match between own and observed models' bodies: inf.uence of face, viewpoints, and body size

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Scientific reports 2020年第1期10卷 17120页

作者： Lize De Coster Pablo Sánchez-Herrero Carlos Aliaga Miguel A Otaduy Jorge López-Moreno Ana Tajadura-Jiménez DEI Interactive Systems Group Department of Computer Science and Engineering Universidad Carlos III de Madrid Avenida de la Universidad 30 28911 Leganés Madrid Spain. lcoster@inf.uc3m.es. Seddi Labs Madrid Spain. Modeling and Virtual Reality Group Department of Computer Science Universidad Rey Juan Carlos Madrid Spain. Multimodal Simulation Lab Department of Computer Science and Architecture Computer Systems and Languages Statistics and Operative Investigation Universidad Rey Juan Carlos Madrid Spain. DEI Interactive Systems Group Department of Computer Science and Engineering Universidad Carlos III de Madrid Avenida de la Universidad 30 28911 Leganés Madrid Spain.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Granger causality on horizontal sum of Boolean algebras

arXiv

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arXiv 2018年

作者： Bohdalová, Mária Kalina, Martin Nánásiová, Olga Dept. of Inf. Systems Faculty of Management Comenius University Bratislava Dept. of Mathematics Faculty of Civil Engineering Slovak University of Technology Bratislava Institute of Computer Science and Mathematics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava

The intention of this paper is to discuss the mathematical model of causality introduced by C.W.J. Granger in 1969. The Granger's model of causality has become well-known and often used in various econometric models describing causal systems, e.g., between commodity prices and exchange rates. Our paper presents a new mathematical model of causality between two measured objects. We have slightly modified the well-known Kol-mogorovian probability model. In particular, we use the horizontal sum of set σ-algebras instead of their direct *** Codes 03G12, 06C15, 81P10 Copyright © 2018, The Authors. All rights reserved.

关键词： Statistical tests

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Graph-Based Technique for Extracting Keyphrases in a Single-Document (GTEK)

Graph-Based Technique for Extracting Keyphrases in a Single-...

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International Conference on Promising Electronic Technologies (ICPET)

作者： Mahmoud R. Alfarra Abdalfattah Alfarra Computer Science and Information Technology Department University College of Science and Technology Khan Younis Palestine Comput. Sci. & Inf. Technol. Dept. Univ. Coll. of Sci. & Technol. Khan Younis Palestinian Authority

In this paper, a novel Graph-based Technique for Extracting Keyphrases in a single document (GTEK) is introduced to be used in extractive summarization of text. GTEK is based on the graph-based representation of text, which depends on terms and phrase numeration in sentences rather than some structural document features. GTEK considers the impact of the sentence on the phrases in a document, motivated by the fact that a phrase may be important if it appears in the most important sentences in the document. The Graph-based Growing Self-Organizing Map (G-GSOM) is used to group the sentences into graph-based clusters. TextRank algorithm is applied on graphs of clusters under the assumption that the top-ranked nodes should represent the most important sentences, where the most frequent phrases in these sentences are selected as document keyphrases. Experimental results show that our innovative technique extracts the most keyphrases of two datasets.

关键词： Clustering algorithms Feature extraction Data mining Task analysis Semantics Indexes computer science

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Compression with the tudocomp framework

arXiv

引用

arXiv 2017年

作者： Dinklage, Patrick Fischer, Johannes Köppl, Dominik Löbel, Marvin Sadakane, Kunihiko Department of Computer Science TU Dortmund Germany Grad. School of Inf. Science and Technology University of Tokyo Japan

We present a framework facilitating the implementation and comparison of text compression algorithms. We evaluate its features by a case study on two novel compression algorithms based on the Lempel-Ziv compression schemes that perform well on highly repetitive texts. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning

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