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arXiv 2020年

作者： Gautam, Akshat Sit, Muhammed Demir, Ibrahim School of Engineering and Applied Sciences Columbia University Interdisciplinary Graduate Program in Informatics University of Iowa Department of Civil and Environmental Engineering University of Iowa

In this paper, we demonstrated a practical application of realistic river image generation using deep learning. Specifically, we explored a generative adversarial network (GAN) model capable of generating high-resolution and realistic river images that can be used to support modeling and analysis in surface water estimation, river meandering, wetland loss, and other hydrological research studies. First, we have created an extensive repository of overhead river images to be used in training. Second, we incorporated the Progressive Growing GAN (PGGAN), a network architecture that iteratively trains smaller-resolution GANs to gradually build up to a very high resolution to generate high quality (i.e., 1024x1024) synthetic river imagery. With simpler GAN architectures, difficulties arose in terms of exponential increase of training time and vanishing/exploding gradient issues, which the PGGAN implementation seemed to significantly reduce. The results presented in this study show great promise in generating high-quality images and capturing the details of river structure and flow to support hydrological research, which often requires extensive imagery for model performance. Copyright © 2020, The Authors. All rights reserved.

关键词： Rivers

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An unsupervised auditory scene analysis system using incremental low-dimensional embedding

An unsupervised auditory scene analysis system using increme...

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IEEE/SICE International Symposium on System Integration

作者： Kenta Shinzato Ryosuke Kojima Undergraduate School of Informatics and Mathematical Science Undergraduate Course Program of Applied Mathematics and Physics Kyoto University 54 Kawahara-cho Shogoin Sakyo-ku Kyoto Japan Graduate School of Medicine Kyoto University 54 Kawahara-cho Shogoin Sakyo-ku Kyoto Japan

ISBN: (数字)9781728176581

ISBN: (纸本)9781728176598

This paper addresses the low-dimensional embedding of sounds towards unsupervised auditory scene analysis. Summarizing long-time recordings by mapping them into low-dimensional space is an essential task in long-time environmental monitoring. In this paper, we propose a novel low-dimensional embedding system using an incremental embedding algorithm. To analyze long-time recordings, we design an incremental system consisting of recording, feature extraction, low-dimensional embedding, and visualization. Recently, many low-dimensional embedding methods for acoustic scenes have been studied; however, applicability of these methods to the long-time recording is not adequately evaluated. Thus, this paper describes the construction of the scene analysis system and evaluates the performance of this system. In this paper, we especially focus on two important viewpoints in long-time monitoring: incremental methods and effects of noisy data. To realize an incremental system, we use Self-Organizing Nebulous Growths (SONG), which can incrementally construct a low-dimensional embedding space. Also, in our experiments, we apply our system to bird song analysis under noise conditions. By the preliminary experiments using benchmark datasets, we discover noise sensitivity of our system and applicability to environmental monitoring.

关键词： Training Image analysis Feature extraction Birds Real-time systems Environmental monitoring Task analysis

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WaiterBot: Comparison of Fuzzy Logic Approaches for Obstacle Avoidance in Dynamic Unmapped Environments Using a Laser Scanning System (LiDAR)

WaiterBot: Comparison of Fuzzy Logic Approaches for Obstacle...

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IEEE Latin American Robotics Symposium, LARS

作者： Jonathan Cerbaro Dieisson Martinelli André Schneider de Oliveira João Alberto Fabro ederal University of Technology - Paraná (UTFPR) Graduate Program on Electrical Engineering and Applied Informatics (CPGEI) Advanced Laboratory of Embedded Systems and Robotics (LASER) Curitiba Paraná Brazil

ISBN: (数字)9780738111537

ISBN: (纸本)9781665419857

Fuzzy logic is a control technique commonly applied in mobile robotics. This paper contains the analysis of three implementations of control systems for obstacle avoidance of a mobile robot. The simulation environment simulate situations with both fixed and dynamic obstacles - like people walking - aiming to compare the fuzzy control approach most suitable to avoid different kinds of obstacles. The analyzed approaches differ by segmenting the sensor data (provided by a LiDAR sensor) into three regions, five regions or by considering only the position of the nearest obstacle. The three approaches were tested in scenarios containing different obstacles and in a simulation where the robot delivers to tables in a dynamic environment, simulating a social event as an application example of a waiter robot.

关键词： Robot sensing systems Robots Collision avoidance Robot kinematics Laser radar Fuzzy logic Input variables

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Perspectives on risk prioritization of data center vulnerabilities using rank aggregation and multi-objective optimization

arXiv

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arXiv 2022年

作者： Grisci, Bruno Iochins Kuhn, Gabriela Colombelli, Felipe Matter, Vítor Kehl Lima, Leomar Heinen, Karine Pegoraro, Mauricio Borges, Marcio Rigo, Sandro José Barbosa, Jorge Luis Victória da Rosa Righi, Rodrigo da Costa, Cristiano André de Oliveira Ramos, Gabriel Software Innovation Laboratory - Softwarelab Graduate Program in Applied Computing Universidade do Vale do Rio dos Sinos Av. Unisinos 950 RS São Leopoldo93022-750 Brazil Institute of Informatics Federal University of Rio Grande do Sul Av. Bento Gonçalves 9500 RS Porto Alegre91501-970 Brazil Dell Technologies Brazil Av. Industrial Belgraf 400 Eldorado do Sul RS 92990-000 Brazil

Nowadays, data has become an invaluable asset to entities and companies, and keeping it secure represents a major challenge. Data centers are responsible for storing data provided by software applications. Nevertheless, the number of vulnerabilities has been increasing every day. Managing such vulnerabilities is essential for building a reliable and secure network environment. Releasing patches to fix security flaws in software is a common practice to handle these vulnerabilities. However, prioritization becomes crucial for organizations with an increasing number of vulnerabilities since time and resources to fix them are usually limited. This review intends to present a survey of vulnerability ranking techniques and promote a discussion on how multi-objective optimization could benefit the management of vulnerabilities risk prioritization. The state-of-the-art approaches for risk prioritization were reviewed, intending to develop an effective model for ranking vulnerabilities in data centers. The main contribution of this work is to point out multi-objective optimization as a not commonly explored but promising strategy to prioritize vulnerabilities, enabling better time management and increasing security. Copyright © 2022, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Protein Folding as a Jamming Transition

PRX Life

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PRX Life 2025年第1期3卷 013018-013018页

作者： Alex T. Grigas Zhuoyi Liu Jack A. Logan Mark D. Shattuck Corey S. O'Hern Graduate Program in Computational Biology and Biomedical Informatics Yale University New Haven Connecticut 06520 USA Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven Connecticut 06520 USA Department of Mechanical Engineering Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA

Proteins fold to a specific functional conformation with a densely packed core that controls their stability. Despite their importance, we lack a quantitative explanation for why all protein cores, regardless of their overall fold, possess the same average packing fraction 〈ϕ〉≈0.55. However, important developments in the physics of jamming in particulate systems can shed light on the packing of protein cores. Here, we extend the framework of jamming to describe core packing in collapsed polymers, as well as in all-atom models of folded proteins. First, we show in a spherical bead-spring polymer model (with and without bond-angle constraints) that as the hydrophobic interactions increase relative to thermal fluctuations, a jamming-like transition occurs when the core packing fraction exceeds ϕc with the same power-law scaling behavior for the potential energy Vr, excess contact number ΔN, and characteristic frequency of the vibrational density of states ω* versus Δϕ=ϕ−ϕc as that for jammed particulate systems. Then, we develop an all-atom model for proteins and find that, above ϕc∼0.55, protein cores undergo a jamming-like transition, but with anomalous power-law scaling for Vr, ΔN, and ω* versus Δϕ. The all-atom protein model remains close to the native protein structure during jamming and accurately refolds from partially unfolded states.

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POS-515 MONITOR OF BIOCHEMICAL PARAMETERS OF PATIENTS IN HEMODIALYSIS IN BRAZIL: A MOBILE TOOL IN KIDNEY HEALTH ESSENTIAL FOR PATIENTS’ MONITORING

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Kidney International Reports 2021年第4期6卷 S224-S224页

作者： E. Maria Rodrigues de Araújo A.C. Rattacaso Marinho de Matos Albuquerque R. Almeida de Freitas Filho L. Cunha Matos J. Gomes Ramalho de Oliveira G. Da Silva Jr. University of Fortaleza Medical Sciences Graduate Program Fortaleza Brazil University of Fortaleza Public Health Graduate Program Fortaleza Brazil University of Fortaleza Applied Informatics Graduate Program Fortaleza Brazil University of Fortaleza Marketing School Fortaleza Brazil University of Fortaleza School of Medicine/Medical Sciences and Public Health Graduate Programs Fortaleza Brazil

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Application of future 6G technology to support heavy data traffic in highly mobile networks

Application of future 6G technology to support heavy data tr...

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2020 First International Conference of Smart Systems and Emerging Technologies (SMARTTECH)

作者： Rafael Kunst Edison Pignaton Ting Zhou Honglin Hu Applied Computing Graduate Program University of Rio dos Sinos Valley (Unisinos) Sao Leopoldo Brazil Informatics Institute Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China

ISBN: (数字)9781728174075

ISBN: (纸本)9781728174082

SG technology is becoming a reality, with several deployments appearing around the world. Despite bringing improvements, 5G technology may not adequately support many envisaged applications that will demand large amounts of network resources. Thus, studies on the next generation, the 6G, are highly desirable. Observing this landscape, in this paper, we present a seminal study about the potential usage of 6G to support such highly demanding applications. Towards this study, we model a 6G system at the simulation level and conduct a case study exploring an application of high-definition video monitoring, applying the concepts of drone-swarm based surveillance. This scenario demands the transmission of large amounts of video data through the network. The acquired results present evidence that 6G can address these high network traffic demands.

关键词： 6G mobile communication 5G mobile communication Surveillance Telecommunication traffic Next generation networking

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Inter-comparison of multiple Global Climate Model (GCM) data based on spatial pattern of rainfall over Indonesia 5

Inter-comparison of multiple Global Climate Model (GCM) data...

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5th International Symposium on LAPAN-IPB Satellite for Food Security and Environmental Monitoring 2018, LISAT-FSEM 2018

作者： Aflahah, Elania Latifah, Arnida Lailatul Hidayat, Rahmat Hidayati, Rini Ihwan, Andi Applied Climatology Study Program Graduate School Bogor Agricultural University Bogor16680 Indonesia Laboratorium of High-Performance Computing Research Center for Informatics Indonesian Institute of Sciences West Java Bogor16916 Indonesia Department of Geophysics and Meteorology Bogor Agricultural University Bogor16680 Indonesia

The Coupled Model Inter-comparison Project Phase 5 (CMIP5) is the output of many coupled atmosphere-ocean of global climate models (GCMs) and widely used for climate research, especially for driving regional climate model. There are more than 40 CMIP5 GCMs data available, but no single model can be considered as the best for every region. The use of CMIP5 GCMs data for rainfall projection in Indonesia is important to improve the accuracy of the monthly and seasonal rainfall forecast. Then, this study evaluates the capability of the CMIP5 GCMs data for Indonesia region by quantitatively comparing the spatial pattern of the precipitation mean and standard deviation of the CMIP5 data against GPCP, GPCC, and CRU data in the period 1980-2005. Furthermore, the composite analysis is conducted to observe the model performance in reproducing the precipitation characteristic over some areas in Indonesia. In conclusion, the models NorESM1-M, NorESM1-ME, GFDL-ESM2M, CSIRO-MK3-6-0 perform the rainfall mean better than others, while the standard deviation of the rainfall show that the models NorESM1-M, BNU-ESM, CMCC-CMS are superior in which NorESM1-M gives the best performance. The annual precipitation pattern of the model NorESM1-M over various areas in Indonesia is also highly correlated with the observations. Thus, the most suitable model for Indonesia region is NorESM1-M. © Published under licence by IOP Publishing Ltd.

关键词： Climate models

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A Secure and Fault-Tolerant Architecture for LoRaWAN Based on Blockchain

A Secure and Fault-Tolerant Architecture for LoRaWAN Based o...

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Cyber Security in Networking Conference (CSNet)

作者： Victor Ribeiro Raimir Holanda Filho Alex Ramos Graduate Program in Applied Informatics University of Fortaleza (UNIFOR) Fortaleza Brazil Computer Science Department Federal Institute of Ceará (IFCE) Fortaleza Brazil

ISBN: (数字)9781728139494

ISBN: (纸本)9781728139500

The Internet of Things (IoT) paradigm aims to bring continuous interaction between small embedded devices and humans. The IoT has the potential to affect our daily lives and bring many benefits to society. Low-Power Wide-Area Networks (LPWAN) is a new IoT technology that offers long distance connectivity for a massive number of devices. LPWAN is a promising solution to enable complex IoT scenarios, such as smart cities and smart healthcare. LoRa is currently one of the leading LPWAN solutions available for public use. Due to the great number of connected devices and, in some cases, sensitive data transmitted in IoT networks, security is one of the main concerns in LPWAN. In this paper, we focus on the issues of key management in LoRaWAN. We propose a secure architecture for key management based on private blockchain and smart contracts in order to increase the levels of security and availability in LoRaWAN environments. In order to show the feasibility of the proposed architecture, a working prototype was implemented using open-source tools and commodity hardware.

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Retraction Note: REHAB FUN: an assistive technology in neurological motor disorders rehabilitation of children with cerebral palsy

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Neural Computing and Applications 2024年第28期36卷 17757-17757页

作者： de Oliveira, Juliana M. Munoz, Roberto Ribeiro, Sidarta Wu, Wanqing de Albuquerque, Victor Hugo C. Graduate Program in Applied Informatics Laboratory of Bioinformatics University of Fortaleza Fortaleza Brazil Escuela de Ingeniería Civil Informática Centro de Investigación y Desarrollo en Ingeniería en Salud Universidad de Valparaíso Valparaíso Chile Brain Institute Federal University of Rio Grande do Norte (UFRN) Natal Brazil CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology-Chinese Academy of Sciences (SIAT-CAS) Shenzhen China

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