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TechRxiv 2021年

作者： Le, Viet-Anh Nguyen, Linh Nghiem, Truong X. The School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ86011 United States The School of Engineering Information Technology and Physical Sciences Federation University Australia Churchill VIC3842 Australia

Adaptive sampling in a resource-constrained mobile robotic sensor network for monitoring a spatial phenomenon is a fundamental but challenging problem. In applications where a Gaussian Process is employed to model a spatial field and then to predict the field at unobserved locations, the adaptive sampling problem can be formulated as minimizing the negative log determinant of a predicted covariance matrix, which is a non-convex and highly complex function. Consequently, this optimization problem is typically addressed in a grid-based discrete domain, although it is combinatorial NP-hard and only a near-optimal solution can be obtained. To overcome this challenge, we propose using a proximal alternating direction method of multipliers (PxADMM) technique to solve the adaptive sampling optimization problem in a continuous domain. Numerical simulations using a real-world dataset demonstrate that the proposed PxADMM-based method outperforms a commonly used grid-based greedy method in the final model accuracy. © 2021, CC BY.

关键词： Covariance matrix

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Spatiotemporal forecasting for dengue, chikungunya fever and Zika using machine learning and artificial expert committees based on meta-heuristics

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Research on Biomedical engineering 2022年第2期38卷 499-537页

作者： da Silva, Cecilia Cordeiro de Lima, Clarisse Lins da Silva, Ana Clara Gomes Moreno, Giselle Machado Magalhães Musah, Anwar Aldosery, Aisha Dutra, Livia Ambrizzi, Tercio Borges, Iuri V. G. Tunali, Merve Basibuyuk, Selma Yenigün, Orhan Massoni, Tiago Lima Jones, Kate Campos, Luiza Kostkova, Patty da Silva Filho, Abel Guilhermino dos Santos, Wellington Pinheiro Center for Informatics CIn-UFPE Federal University of Pernambuco Recife Brazil Polytechnique School of the University of Pernambuco Poli-UPE Recife Brazil Department of Biomedical Engineering Federal University of Pernambuco Recife Brazil Department of Atmospheric Sciences IAG-USP University of São Paulo São Paulo Brazil Centre for Digital Public Health and Emergencies Institute for Risk and Disaster Reduction University College London London United Kingdom Institute of Environmental Sciences Boaziçi University Istanbul Turkey Department Systems & Computing Federal University of Campina Grande Campina Grande Brazil Centre for Biodiversity and Environment Research Department of Genetics Evolution and Environment University College London London United Kingdom Department of Civil Environmental & Geomatic Engineering University College London London United Kingdom

Purpose: Dengue is considered one of the biggest public health problems in recent decades. Climate and demographic changes, the disorderly growth of cities and international trade have brought new arboviruses such as chikungunya and Zika. Control of arboviruses depends on control of the vector: the Aedes aegypti mosquito. Objective: In this work, we propose a methodology for building disease predictors capable of predicting infected cases and locations based on machine learning. We also propose an artificial experts committee based on meta-heuristic methods to detect the most relevant risk factors. Method As a case study, we applied the methodology to forecast dengue, chikungunya and Zika, with data from the City of Recife, Brazil, from 2013 to 2016. We used arboviruses cases data and climatic and environmental information: wind speeds, temperatures and precipitation. Results The best prediction results were obtained with 10-tree Random Forest regression, with Pearson’s correlation above 0.99 and RMSE (%) below 6%. Additionally, the artificial experts committee was able to present the most relevant factors for predicting cases in each two-month period. Conclusion: The spatiotemporal prediction results showed the evolution of arboviruses, pointing out as major focuses on both regions richer in urban green areas and low-income neighborhood with irregular water supply. Determining the most relevant factors for prediction, as well as the spatial distribution of cases, can be useful for the planning and execution of public policies aimed at improving the health infrastructure and planning and controlling the vector. © 2022, Sociedade Brasileira de Engenharia Biomedica.

关键词： Forecasting

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A Bibliometric Analysis and Research Landscape of Artificial Intelligence in Education

A Bibliometric Analysis and Research Landscape of Artificial...

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IEEE International Conference on Control System, computing and engineering (ICCSCE)

作者： Samuel-Soma M. Ajibade Bayan Issa Muhammed Basheer Jasser Farrukh Hassan Ghassan Saleh ALDharhani Ismail Ahmed Al-Qasem Al-Hadi Kayode Akinlekan Akintoye Almighty Cortezo Tabuena Department of Computing and Information Systems School of Engineering and Technology Sunway University No. 5 Jalan Universiti Bandar Sunway Selangor Darul Ehsan Malaysia Department of Computer Engineering Istanbul Ticaret University Istanbul Turkiye Faculty of Informatics Engineering University of Aleppo Syria Institute of Computer Science and Digital Innovation UCSI University Kuala Lumpur Malaysia Faculty of Information Science and Technology UKM University Bangi Selangor Malaysia Department of Computer Science The Federal Polytechnic Ado Ekiti Ekiti State Nigeria College of Arts and Sciences University of the City of Valenzuela Philippines

ISBN: (数字)9798350364507

ISBN: (纸本)9798350364514

This study examines the academic field of Artificial Intelligence in Education (AI-ED) by examining the publications and indexed documents in Scopus from 2010 to 2023. Consequently, we examined the publishing trends, exemplary articles, and the most engaged participants and funding institutions in the domain of AI-ED research. A bibliometric analysis was performed to examine the network of co-authorships, keywords, and citations in the domain of AIED research. The Scopus search resulted in the discovery of 10,474 published documents on AI-ED. Additionally, trends analysis indicated a significant increase of over 3,000% in publications between 2010 and 2023. Conference papers are the most often utilized document type, including 6757 publications or $64.5 \%$ of the overall amount. The ACM International Conference Proceeding Series is the primary source for published materials, accounting for 675 publications or $6.44 \%$ of the total publications on the topic. The most prolific researchers in the field of AI-ED are Breazeal, C and Chai C.S, each having published 18 documents. Additionally, the two institutions that have produced the highest number of published documents are Carnegie Mellon University (CMU) and the University of NC State University (NCSU). The output of the affiliations active in the topic is primarily attributed to the funders, specifically the National Science Foundation, which is the leading funding institution based in the United States and has contributed to 354 publications. An analysis of keyword co-occurrence revealed 6 main study areas that cover the essential tools, theories, methodologies, and socioeconomic and financial aspects of artificial intelligence in education (AIED). Future research in the field of artificial intelligence in education will focus on employing sophisticated deep learning, machine learning, and neural network algorithms to precisely predict students’ learning patterns.

关键词： Deep learning Education Bibliometrics Neural networks Market research Prediction algorithms Stakeholders Artificial intelligence Socioeconomics Meteorology

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Films from the Future [Book Review]

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IEEE Technology and Society Magazine 2019年第4期38卷 9-10页

作者： Katina Michael School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ

This book is an ambitious collection of well-organized reflections that attempts to explore the technology and morality of twelve science fiction movies. It is intriguing that author has chosen to take away significant positive learnings from cult classics such as Minority Report that would otherwise be considered as backdrops for a dystopian future. Explores how we can learn from science fiction scenarios. To an extent, some of the visions presented by films like Minority Report have come true, despite that the movie completely missed the role that smartphones and social media would play. What all of the science fiction movies that the author has purposely hand-picked for us to engage with have in common is conflict. The author presents an excellent summation of the topics that will invariably always preoccupy humankind. Inherent in this book are issues of control and risk. Students in particular will be served well in interdisciplinary courses that interrogate the subject matter from a variety of lenses — social, technical, ethical, and legal.

关键词： Book reviews Entertainment industry Motion pictures Science - general Publishing

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A Framework for Composable Cellular Automata Devs Modeling, Simulation, and Visualization

A Framework for Composable Cellular Automata Devs Modeling, ...

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2020 Spring Simulation Conference, SpringSim 2020

作者： Zhang, Chao Sarjoughian, Hessam S. Gi Seok, Moon Arizona State University Arizona Center for Integrative Modeling and Simulation Schl. of Computing Informatics and Decision Sys. Engr. TempeAZ85261-8809 United States Nanyang Technical University School of Computer Science and Engineering Singapore639798 Singapore

ISBN: (数字)9781565553705

ISBN: (纸本)9781565553705

The concept of cellular automata is one of the cornerstones of scientific and engineering pursuit with wide applicability in various domains. The rise of system complexity points to developing frameworks that can aid in developing composable models at multiple spatiotemporal levels. Toward this goal, an input/output mod-ular discrete-event cellular automata framework based on the Discrete Event System Specification (DEVS) is proposed. It is adapted from a Composable Cellular Automata (CCA) formalism that is defined in terms of a multicomponent discrete time system specification. The resulting Composable Cellular Automata DEVS (CCA-DEVS) framework is built using the Cellular Automata DEVS that is a part of the DEVS-Suite simulator. The approach and realization of the proposed CCA-DEVS framework are detailed. The framework is used to develop an example model composed of CCA-DEVS agent and partial differential equation models. © 2020 SCS.

关键词： Cellular automata

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Falsification of Temporal Logic Requirements Using Gradient Based Local Search in Space and Time

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IFAC-PapersOnLine 2018年第16期51卷 103-108页

作者： Yaghoubi, Shakiba Fainekos, Georgios School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States

We study the problem of computing input signals that produce system behaviors that falsify requirements written in temporal logic. We provide a method to automatically search for falsifying time varying uncertain inputs for nonlinear and possibly hybrid systems. The input to the system is parametrized using piecewise constant signals with varying switch times. By applying small perturbations to the system input in space and time, and by using gradient descent approach, we try to converge to the worst local system behavior. The experimental results on non-trivial benchmarks demonstrate that this local search can significantly improve the rate of finding falsifying counterexamples. © 2018

关键词： Computer circuits Crime Cyber Physical System Embedded systems Hybrid systems Local search (optimization) Optimization Temporal logic Testing Gradient based Gradient descent Local system Piece wise constants Small perturbations Space and time System behaviors Time varying

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Dual-mode broadcast encryption

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Science China(Information Sciences) 2018年第11期61卷 226-228页

作者： Yan ZHU Ruyun YU E CHEN Dijiang HUANG School of Computer and Communication Engineering University of Science and Technology Beijing School of Computing Informatics and Decision Systems Engineering Arizona State University

Broadcast encryption (BE) is a technique to implement secure group-oriented communication. The concept of broadcast encryption was firstly introduced by Fiat and Naor [1]. In a BE system, a broadcaster firstly chooses a receiver set and encrypts messages, and then broadcasts the ciphertext to all the users in the system while only the users in the chosen set can decrypt the ***. The existing broadcast encryption system can be divided into two categories:

关键词： BE

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Multiplexed quantum repeaters based on dual-species trapped-ion systems

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Physical Review A 2022年第2期105卷 022623-022623页

作者： Prajit Dhara Norbert M. Linke Edo Waks Saikat Guha Kaushik P. Seshadreesan Wyant College of Optical Sciences University of Arizona Tucson Arizona 85721 USA Joint Quantum Institute and Department of Physics University of Maryland College Park Maryland 20742 USA Joint Quantum Institute and Department of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Department of Informatics and Networked Systems School of Computing and Information University of Pittsburgh Pittsburgh Pennsylvania 15260 USA

Trapped ions form an advanced technology platform for quantum information processing with long qubit coherence times, high-fidelity quantum logic gates, optically active qubits, and a potential to scale up in size while preserving a high level of connectivity between qubits. These traits make them attractive not only for quantum computing, but also for quantum networking. Dedicated, special-purpose trapped-ion processors in conjunction with suitable interconnecting hardware can be used to form quantum repeaters that enable high-rate quantum communications between distant trapped-ion quantum computers in a network. In this regard, hybrid traps with two distinct species of ions, where one ion species can generate ion-photon entanglement that is useful for optically interfacing with the network and the other has long memory lifetimes, useful for qubit storage, have been proposed for entanglement distribution. We consider an architecture for a repeater based on such dual-species trapped-ion systems. We propose and analyze a protocol based on spatial and temporal mode multiplexing for entanglement distribution across a line network of such repeaters. Our protocol offers enhanced rates compared to rates previously reported for such repeaters. We determine the ion resources required at the repeaters to attain the enhanced rates, and the best rates attainable when constraints are placed on the number of repeaters and the number of ions per repeater. Our results bolster the case for near-term trapped-ion systems as quantum repeaters for long distance quantum communications.

关键词： Quantum communication Quantum information architectures & platforms Quantum repeaters

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Percolation theory of self-exciting temporal processes

arXiv

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arXiv 2021年

作者： Notarmuzi, Daniele Castellano, Claudio Flammini, Alessandro Mazzilli, Dario Radicchi, Filippo Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Via dei Taurini 19 RomaI-00185 Italy

We investigate how the properties of inhomogeneous patterns of activity, appearing in many natural and social phenomena, depend on the temporal resolution used to define individual bursts of activity. To this end, we consider time series of microscopic events produced by a self-exciting Hawkes process, and leverage a percolation framework to study the formation of macroscopic bursts of activity as a function of the resolution parameter. We find that the very same process may result in different distributions of avalanche size and duration, which are understood in terms of the competition between the 1D percolation and the branching process universality class. Pure regimes for the individual classes are observed at specific values of the resolution parameter corresponding to the critical points of the percolation diagram. A regime of crossover characterized by a mixture of the two universal behaviors is observed in a wide region of the diagram. The hybrid scaling appears to be a likely outcome for an analysis of the time series based on a reasonably chosen, but not precisely adjusted, value of the resolution parameter. Copyright © 2021, The Authors. All rights reserved.

关键词： Solvents

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A Multimodal Monitoring Approach to Predicting the Onset of Physiological Incidents Using Machine Learning

A Multimodal Monitoring Approach to Predicting the Onset of ...

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IEEE Signal Processing in Medicine and Biology Symposium (SPMB)

作者： E. Moyer I. Isozaki D. Moberg Moberg Analytics Ambler Pennsylvania USA School of Biomedical Engineering Science and Health Systems Drexel University Philadelphia Pennsylvania USA College of Computing and Informatics Drexel University Philadelphia Pennsylvania USA

ISBN: (纸本)9781665428989

Traumatic Brain Injury (TBI) is a complex, heterogeneous disease affecting millions of people in the U.S. each year [1]. Multimodal monitoring (MMM) is a relatively new attempt to access and monitor the brain post injury by incorporating multiple sources of information recorded in the intensive care unit (ICU) [2]. As a result, MMM has led to the creation of exhaustive datasets, allowing for the integration of many different signals and modalities pertaining to the management of severe TBI [2]–[4]. One of the most pressing questions about a TBI patient is whether an incident, or an event, will occur in the near future [5]. Additionally, clinicians require sufficient time before the onset of an event to administer a drug to the patient to avoid the oncoming event. Therefore, the aim of this work is to detect whether physiological events will occur in the future using the multimodal physiological data as features. In this study, we leverage both the breath and resolution of physiological data to predict the onset of physiological incidents 30 minutes before their onset. Specifically, we focus on three physiological events, namely high intercranial pressure (ICP), out of range diastolic arterial blood pressure (ABP), and out of range systolic ABP, using seven relevant modalities.

关键词： Drugs Pressing Machine learning Signal processing Feature extraction Biology Biomedical monitoring

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