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Image Classification of Cyanobacteria Microcystis Aeruginosa in raw Water Samples in Curitiba's Region

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Image Classification of Cyanobacteria Microcystis Aeruginosa...

Annual IEEE Symposium on computer-Based Medical Systems

作者： Geisla de Albuquerque Melo Antonio Carlos Sobieranski Thelma Alvim Veiga Ludwig Lucas Ferrari de Oliveira Informatics Dept. Federal University of Parana Curitiba Brazil Computer Engineering Dept. Federal University of Santa Catarina Ararangua Brazil Federal University of Parana Curitiba Brazil

ISBN: (数字)9781728194295

ISBN: (纸本)9781728194301

Surveys studies carried out in different countries demonstrated that about 75% of lake water samples contain toxic cyanobacteria [4, 5]. The toxin that is must recurrent in Brazilian water bodies are the microcystin [6]. Microcystins are hepatotoxins produced by some species of cyanobacteria, and act by inflicting damage to cells from the liver and other organs [7]. Cases around the world have been reported over time, including health injuries by contact direct or not with contaminated water, as well livestock and humans deaths [4]. Due to its sanitary importance, the water that the population consumes needs regular monitoring in order to avoid contact and possible adverse effects. The objective of this work is to propose a computational approach for the identification of Microcystis aeruginosa from images, in raw water reservoirs, automatically, using artificial intelligence techniques. The identification was developed using convolutional neural networks (CNN), where two distinct model were compared. The obtained results demonstrated the effectiveness of the proposed approach to solve the problem of recognizing cyanobacterias.

关键词： Training Microscopy Water pollution Convolutional neural networks Reservoirs Organisms

Defining Network Switch Preference by Network Traffic Using Stable Marriage Problem 21

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Defining Network Switch Preference by Network Traffic Using ...

21st International Electronics Symposium, IES 2019

作者： Alimudin, Akhmad Winarno, Idris Ishida, Yoshiteru Politeknik Elektronika Negeri Surabaya Dept. of Multimedia Creative Technology Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Dept. of Computer and Informatics Surabaya Indonesia Toyohashi University of Technology Dept. of Computer Science and Engineering Toyohashi Japan

ISBN: (纸本)9781728144498

A network switch is an important network device on a computer network, the role of a switch can determine the good and bad of a network service. In a data center, sometimes it has several switch devices with different capabilities (diversity). For this reason, we need a strategy to carry out the effectiveness of using switch devices on computer networks. One way that can be done to realize this is by choosing the right partner between switches and hosts. The matching theory makes it possible to overcome this problem. In this study, it was simulated using the Stable Marriage Problem (SMP) method. The initial state to determine the ranking of pairs is done by using several attributes that are owned by each switch and host such as interfaces, services on the host, and data traffic on the device. Simulations are performed on mininet using Software-defined networking (SDN). © 2019 IEEE.

关键词： Interface states

Dynamic Resilient Graph Games for State-Dependent Jamming Attacks Analysis on Multi-Agent Systems

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IFAC-PapersOnLine 2020年第2期53卷 3421-3426页

作者： Yurid Nugraha Ahmet Cetinkaya Tomohisa Hayakawa Hideaki Ishii Quanyan Zhu Dept. of Systems and Control Engineering Tokyo Institute of Technology Tokyo 152-8552 Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo 101-8430 Japan Dept. of Computer Science Tokyo Insitute of Technology Yokohama 226-8502 Japan Dept. of Electrical and Computer Engineering New York University Brooklyn NY 11201 USA

A cybersecurity problem for a multi-agent consensus problem is investigated through a dynamic game formulation. Specifically, we consider a game repeatedly played between a jamming attacker and a defender. The attacker attempts to jam the links between a number of agents to delay their consensus. On the other hand, the defender tries to maintain the connection between agents by attempting to recover some of the jammed links with the goal of achieving faster consensus. In each game, the players decide which links to attack/recover and for how long to continue doing so based on a Lyapunov-like function representing the largest difference between the states of the agents. We analyze the subgame perfect equilibrium of the game and obtain an upper bound of the consensus time that is influenced by the strategies of the players. The results are illustrated with a numerical example.

关键词： Multi-agent systems Consensus problem Game theory Cybersecurity

Software-Defined Network Design driven by Availability Requirements

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Software-Defined Network Design driven by Availability Requi...

International Workshop on Design of Reliable Communication Networks (DRCN)

作者： Dorabella Santos Teresa Gomes David Tipper INESC Coimbra Coimbra Portugal Dept. of Electrical and Computer Engineering University of Coimbra Coimbra Portugal Department of Informatics and Networked Systems University of Pittsburgh Pittsburgh PA

ISBN: (数字)9781728163000

ISBN: (纸本)9781728163017

In Software Defined Networking (SDN), the controller locations are mainly constrained by delays between switches and controllers, and between the controllers themselves. In addition to the delay requirements, the availability of the connections between switches and controllers is also a key issue for control plane performance. Here, we explore the idea of having a spanning tree substructure called the spine, whose links can be upgraded to have high availability in order to support availability requirements for the control paths (routing paths between switches and controllers). We formulate an optimization model of the joint controller placement and spine design problem for SDN networks, under delay, availability and path redundancy requirements. Numerical results are presented showing the trade-offs between the number of controllers, delay requirements and upgrade cost.

关键词： Control systems Delays Redundancy Routing Optimization Reliability engineering

An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works

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arXiv 2021年

作者： Shoeibi, Afshin Moridian, Parisa Khodatars, Marjane Ghassemi, Navid Jafari, Mahboobeh Alizadehsani, Roohallah Kong, Yinan Gorriz, Juan Manuel Ramírez, Javier Khosravi, Abbas Nahavandi, Saeid Acharya, U. Rajendra Data Science and Computational Intelligence Institute University of Granada Spain Faculty of Engineering Science and Research Branch Islamic Azad University Tehran Iran Department of Medical Engineering Mashhad Branch Islamic Azad University Mashhad Iran Computer Engineering department Ferdowsi University of Mashhad Mashhad Iran Electrical and Computer Engineering Faculty Semnan University Semnan Iran Deakin University VIC3217 Australia School of Engineering Macquarie University Sydney2109 Australia Department of Signal Theory Networking and Communications Universidad de Granada Spain Ngee Ann Polytechnic Singapore599489 Singapore Dept. of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan Dept. of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore

Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements. Epileptic seizure detection methods involve neurological exams, blood tests, neuropsychological tests, and neuroimaging modalities. Among these, neuroimaging modalities have received considerable attention from specialist physicians. One method to facilitate the accurate and fast diagnosis of epileptic seizures is to employ computer-aided diagnosis systems (CADS) based on deep learning (DL) and neuroimaging modalities. This paper has studied a comprehensive overview of DL methods employed for epileptic seizures detection and prediction using neuroimaging modalities. First, DL-based CADS for epileptic seizures detection and prediction using neuroimaging modalities are discussed. Also, descriptions of various datasets, preprocessing algorithms, and DL models which have been used for epileptic seizures detection and prediction have been included. Then, research on rehabilitation tools has been presented, which contains brain-computer interface (BCI), cloud computing, internet of things (IoT), hardware implementation of DL techniques on field-programmable gate array (FPGA), etc. In the discussion section, a comparison has been carried out between research on epileptic seizure detection and prediction. The challenges in epileptic seizures detection and prediction using neuroimaging modalities and DL models have been described. In addition, possible directions for future works in this field, specifically for solving challenges in datasets, DL, rehabilitation, and hardware models, have been proposed. The final section is dedicated to the conclusion which summarizes the significant findings of the paper. © 2021, CC BY-NC-ND.

关键词： Forecasting

Moment-based spectrum sensing under generalized noise channels

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arXiv 2020年

作者： Miridakis, Nikolaos I. Tsiftsis, Theodoros A. Yang, Guanghua Institute of Physical Internet School of Intelligent Systems Science & Engineering Jinan University Zhuhai Campus Zhuhai519070 China Dept. of Informatics and Computer Engineering University of West Attica Aegaleo12243 Greece

A new spectrum sensing detector is proposed and analytically studied, when it operates under generalized noise channels. Particularly, the McLeish distribution is used to model the underlying noise, which is suitable for both non-Gaussian (impulsive) as well as classical Gaussian noise modeling. The introduced detector adopts a moment-based approach, whereas it is not required to know the transmit signal and channel fading statistics (i.e., blind detection). Important performance metrics are presented in closed forms, such as the false-alarm probability, detection probability and decision threshold. Analytical and simulation results are cross-compared validating the accuracy of the proposed approach. Finally, it is demonstrated that the proposed approach outperforms the conventional energy detector in the practical case of noise uncertainty, yet introducing a comparable computational complexity. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

Generalized energy detection under generalized noise channels

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arXiv 2020年

Generalized energy detection (GED) is analytically studied when operates under fast-faded channels and in the presence of generalized noise. For the first time, the McLeish distribution is used to model the underlying noise, which is suitable for both non-Gaussian (impulsive) as well as classical Gaussian noise channels. Important performance metrics are presented in closed forms, such as the false-alarm and detection probabilities as well as the decision threshold. Analytical and simulation results are cross-compared validating the accuracy of the proposed approach in the entire signal-to-noise ratio regime. Finally, useful outcomes are extracted with respect to GED system settings under versatile noise environments and when noise uncertainty is present. Copyright © 2020, The Authors. All rights reserved.

关键词： Cognitive radio

A Survey on the E-learning platforms used during COVID-19 11

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A Survey on the E-learning platforms used during COVID-19

11th Annual IEEE Information Technology, Electronics and Mobile Communication Conference, IEMCON 2020

作者： Wang, Xianping Chen, Weiru Qiu, Hao Eldurssi, Awad Xie, Fei Shen, Jiayue Purdue University Northwest Dept of Computer Information Science and Graphics HammondIN46323 United States Old Dominion University Dept of Information Technology and Decision Sciences NorfolkVA23529 United States Fort Valley State University Dept of Engineering Technology Fort ValleyGA31030 United States Fort Valley State University Dept of Engineering Technology Fort ValleyGA31030 United States School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAR86011 United States College of Engineering Suny Polytechnic Institute UticaNY13502 United States

ISBN: (纸本)9781728184166

E-learning is globalized in a short period of time due to the physical distancing requirement for curbing the spread of COVID-19. There are two major challenges imposed by the migration from face-To-face learning to E-learning: live lecturing and lab sessions. In this survey, we studied the E-learning platforms used in the COVID-19 pandemic: learning management systems or course management systems, tools for live-lecturing and tools for lab sessions. We found that this migration is quite smooth with contemporary technologies and the Internet. Prescriptive suggestions are also provided for this migration. For the future trend of education, it is expected that E-learning will become a preferable education and learning style in the future, especially for self-study and life-long learning. © 2020 IEEE.

关键词： COVID-19

Investigating the effect of emoji in opinion classification of Uzbek movie review comments

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arXiv 2020年

作者： Rabbimov, Ilyos Mporas, Iosif Simaki, Vasiliki Kobilov, Sami Applied Mathematics and Informatics Dept Samarkand State University Uzbekistan School of Engineering and Computer Science University of Hertfordshire United Kingdom Centre for Languages and Literature Lund University Sweden

Opinion mining on social media posts has become more and more popular. Users often express their opinion on a topic not only with words but they also use image symbols such as emoticons and emoji. In this paper, we investigate the effect of emoji-based features in opinion classification of Uzbek texts, and more specifically movie review comments from YouTube. Several classification algorithms are tested, and feature ranking is performed to evaluate the discriminative ability of the emoji-based features. Copyright © 2020, The Authors. All rights reserved.

关键词： Sentiment analysis