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Network Management devices in an SDN environment

Network Management devices in an SDN environment

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International Conference on control Systems and computer science (CSCS)

作者： Diyar Jamal Hamad Khirota Gorgees Yalda Nicolae Tapus Ibrahim Taner Okumus Faculty of Automatic Control and Computer Science Politehnica University of Bucharest Bucharest Romania Soran Technical college Erbil Polytechnic University Iraq Erbil Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

Network optimization and continued availability depend on a number of capabilities that are part of network management. The Maintenance, operating and also offering a safeguarded interaction network is very complicated. It calls for the network operators to grapple with low-level vendor particular arrangements to execute the high degree network policies which are complicated. A method for monitoring networks with OpenFlow controller is presented in this paper in two separate functions for the same networks. Bandwidth utilization, Meter values, charts and statistics are provided by the method to extend controller monitoring capabilities. The method architecture and implementation will be introduced in order to present the feature set. Additionally, softswitches are used as a switch and Mininet to evaluate a virtualized network. This analysis shows whether Meters or ports value is better for network management.

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Continual Learning of a Time Series Model Using a Mixture of HMMs with Application to the IoT Fuel Sensor Verification 18

Continual Learning of a Time Series Model Using a Mixture of...

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18th Conference on computer science and Intelligence Systems, FedCSIS 2023

作者： Glomb, Przemyslaw Cholewa, Michal Foszner, Pawel Bularz, Jakub Institute of Theoretical and Applied Informatics Polish Academy of Sciences Batycka 5 Gliwice44-100 Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland Aiut Sp. Z O.o. ul. Wyczókowskiego 113 Gliwice44-109 Poland

ISBN: (纸本)9788396744784

This paper presents an application of a mixture of Hidden Markov Models (HMMs) as a tool for verification of IoT fuel sensors. The IoT fuel sensors report the level of fuel in tanks of a petrol station, and are a key component for monitoring system reliability (billing), safety (fuel/oil leak detection) and security (theft prevention). We propose an algorithm for learning a mixture of HMMs based on a continual learning principle, i.e. it adapts the model while monitoring a sensor over time, signalling unexpected or anomalous sensor reports. We have tested the proposed approach on a real-life data of 15 fuel tanks being monitored with the FuelPrime system, where it has shown a very good performance (average area under ROC curve of 0.94) of detecting anomalies in the sensor data. Additionally we show that the proposed method can be used for trend monitoring and present qualitative analysis of the short and long term learning performance. The proposed method has promising performance score, the resulting model has a high degree of explainability, limited memory and computation requirements and can be easily generalized to other domains of sensor verification. © 2023 Polish Information Processing Society.

关键词： Hidden Markov models

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A Survey on Security Issues in Cloud Systems

A Survey on Security Issues in Cloud Systems

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Roedunet International Conference (RoEduNet)

作者： Diyar Jamal Hamad Khirota Gorgees Yalda Nicolae Tapus Ibrahim Taner Okumus Faculty of Automatic Control and Computer Science Politehnica University of Bucharest Bucharest Romania Soran Technical college Erbil Polytechnic University Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

“The cloud“ points out to servers, the databases and software that run on those servers. The Internet has always been constructed of infrastructure, servers and clients. Clients send their requests to servers, and servers reply, but cloud computing is distinct in the form that cloud servers are not just replying to requests with on-demand processing but they are saving data and running programs instead of the client. Cloud computing is a technology that is crossing a great expansion today. In cloud computing you can dynamically expand resources without knowledge of a new infrastructure, without developing new software or preparing new staff and to access such great technology the only things that are asked for are an Internet connection and an Internet browser. The goal of this survey is to present the different cloud security threats and recognize the proper security mechanism used to reduce them.

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Attitude Dynamics Modelling: Fractional Consensus Approach

Attitude Dynamics Modelling: Fractional Consensus Approach

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IEEE Conference on Decision and control

作者： Jerzy Baranowski Waldemar Bauer Karolina Dukała Dorota Mozyrska Małgorzata Wyrwas Department of Automatic Control and Robotics AGH University of Science & Technology Kraków Poland SWPS University of Social Sciences and Humanities Katowice Poland Faculty of Computer Science Bialystok University of Technology Bialystok Poland

In this paper we propose a consensus model using fractional calculus, which is an emerging topic in multi-agent modeling. Fractional models have infinite memory and can be understood as a relatively simple extension of traditional calculus. We propose a model structure motivating it by psychological research. For such model we also provide a stability analysis allowing results on possibilities of consensus arising in the modelled group of agents. To achieve this, we use fractional difference equations, which illustrate our considerations for agent groups of increasing complexity.

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Towards Automated Detection of Adversarial Attacks on Tabular Data 18

Towards Automated Detection of Adversarial Attacks on Tabula...

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18th Conference on computer science and Intelligence Systems, FedCSIS 2023

作者： Biczyk, Piotr Wawrowski, Lukasz Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka Gliwice44-100 Poland Ukasiewicz Research Network Institute of Innovative Technologies Emag Ul. Leopolda 31 Katowice40-189 Poland Qed Software Sp. Z O.o. Mazowiecka 11/49 Warsaw00-052 Poland

ISBN: (纸本)9788396744784

The paper presents a novel approach to investigating adversarial attacks on machine learning classification models operating on tabular data. The employed method involves using diagnostic parameters calculated on an approximated representation of a model under attack and analyzing differences in these diagnostic parameters over time. The hypothesis researched by the authors is that adversarial attack techniques, even if attempting a low-profile modification of input data, influence those diagnostic attributes in a statistically significant way. Thus, changes in diagnostic attributes can be used for detecting attack events. Three attack approaches on real-world datasets were investigated. The experiments confirm the approach as a promising technique to be further developed for detecting adversarial attacks. © 2023 Polish Information Processing Society.

关键词： Information use

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Improving the detection of noisy labels in image datasets using modified Confidence Learning

Improving the detection of noisy labels in image datasets us...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Adam Popowicz Krystian Radlak Slawomir Lasota Karolina Szczepankiewicz Michal Szczepankiewicz Faculty of Automatic Control Silesian University of Technology Electronics and Computer Science Gliwice Poland Warsaw University of Technology Warsaw Poland

ISBN: (数字)9781665468589

ISBN: (纸本)9781665468596

The effectiveness of machine learning algorithms, including deep neural networks (DNN) for classifying image data, depends on proper preparation of the training dataset. Erroneously labeled images in the training data will degrade algorithmic efficiency and cause unpredictable model behavior, thus reduce its safety. Verifying labels in the numerous available databases remains a complicated and laborious task. In this article, we present a MultiNET approach that allows for efficient verification of labeled image datasets. We adapt a state-of-the-art technique, namely Confidence Learning, extending its flexibility and improving the effectiveness by combining outcomes from various DNN architectures. Thanks to the proposed modification, it is possible to automatically detect incorrect labels while minimizing the number of false positives, thus making the verification process much less burdensome. The technique may be of use for researchers and software engineers dealing with externally supplied image datasets.

关键词： Deep learning Training Machine learning algorithms Databases Training data computer architecture Data models

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Detection of Early Pregnancy in Ultrasound Images Using YOLOv3 *

Detection of Early Pregnancy in Ultrasound Images Using YOLO...

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Mediterranean Conference on control and Automation (MED)

作者： Oana Mihaela Teodor Monica Mihaela Cirstoiu Loretta Ichim Dan Popescu Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania Carol Davila University of Medicine and Pharmacy Bucharest

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

automatic interpretation of morphological metrics recently gained great interest in medical imaging applications. For ultrasound image analysis various artificial intelligence algorithms emerged with the aim to overcome drawbacks related to measurement variability and image quality. Advanced methods of automatic analysis can meet the need to centralize a large amount of information from these images, to accurately interpret the medical data, and to minimize the rate of human error. In the current paper, we propose a solution designed for automating the detection of early pregnancy from endovaginal ultrasound scans. A YOLOv3 convolutional neural network was configured to detect the gestational sac, the yolk sac, and the embryo given the potential to facilitate ultrasound diagnostic in obstetrics by automating the detection of these early pregnancy elements. The database created for this research included 349 images evaluating incipient pregnancies with gestational age ranging from 40 to 70 days. The results obtained support the use of YOLOv3 for the precise detection of ultrasound elements specific to an incipient pregnancy.

关键词： Pregnancy Image quality Ultrasonic imaging Embryo Databases Ultrasonic variables measurement Current measurement

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Cyber Physical Systems Architecture for Collaborative Services 23

Cyber Physical Systems Architecture for Collaborative Servic...

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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Pop, Eugen Gifu, Daniela Stanescu, Aurelian Mihai Moisescu, Mihnea Alexandru Sacala, Ioan Stefan RandD Institute for Automation IPA SA ICT Department Bucharest Romania Alexandru Ioan Cuza University of Iasi Institute of Computer Science Romanian Academy Faculty of Computer Science Iasi Branch Romania Politehnica University of Bucharest Faculty of Automatic Control and Computers Romania

ISBN: (纸本)9781665439398

Cyber Physical Systems (CPS) represents an autonomous system which integrates sensing devices, actuators, hardware equipments and software applications, having also communication functionality. A CPS can realize data transmission and cooperation with remote systems and IoT networks. Within smart factories, having the ability of involving business scenarios, CPS autonomously exchange data, control and monitor processes, perform actions in the Industry 4.0 context. Correlated with CPS interoperability capabilities, a new paradigm in manufacturing appeared, based on collaborative, service-oriented, customer-centric industries. Various new business models involve a large, exponentially growing number, of interconnected devices. In this paper is presented a CPS services framework, which integrates an e-business service group within a collaborative infrastructure, thus offering to the users the possibility to valorify on the market, through services integration and collaboration, the remarkable technical advantages of CPS. As e-business example, an e-payment service, developed in a Service Oriented Architecture (SOA), is considered. The data transactions are realized on mobile and wireless communication channels, through Soap and Rest Web services, which are accessed by mobile client software application, installed on Android OS Smartphones. © 2021 IEEE.

关键词： Cyber Physical System

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HISTORIAE, history of socio-cultural transformation as linguistic data science. A humanities use case 3

HISTORIAE, history of socio-cultural transformation as lingu...

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3rd Conference on Language, Data and Knowledge, LDK 2021

作者： Armaselu, Florentina Apostol, Elena-Simona Khan, Anas Fahad Liebeskind, Chaya McGillivray, Barbara Truică, Ciprian-Octavian Oleškevičiene, Giedre Valūnaite University of Luxembourg Luxembourg Department of Computer Science and Engineering Faculty of Automatic Control and Computer University Politehnica of Bucharest Romania Institute for Computational Linguistics «A. Zampolli» National Research Council of Italy Pisa Italy Department of Computer Science Jerusalem College of Technology Israel Theoretical and Applied Linguistics Faculty of Modern and Medieval Languages and Linguistics University of Cambridge United Kingdom The Alan Turing Institute London United Kingdom Department of Computer Science and Engineering Faculty of Automatic Control and ComputerUniversity Politehnica of Bucharest Romania Institute of Humanities Mykolas Romeris University Vilnius Lithuania

ISBN: (纸本)9783959771993

The paper proposes an interdisciplinary approach including methods from disciplines such as history of concepts, linguistics, natural language processing (NLP) and Semantic Web, to create a comparative framework for detecting semantic change in multilingual historical corpora and generating diachronic ontologies as linguistic linked open data (LLOD). Initiated as a use case (UC4.2.1) within the COST Action Nexus Linguarum, European network for Web-centred linguistic data science, the study will explore emerging trends in knowledge extraction, analysis and representation from linguistic data science, and apply the devised methodology to datasets in the humanities to trace the evolution of concepts from the domain of socio-cultural transformation. The paper will describe the main elements of the methodological framework and preliminary planning of the intended workflow. © Florentina Armaselu, Elena-Simona Apostol, Anas Fahad Khan, Chaya Liebeskind, Barbara McGillivray, Ciprian-Octavian Truică, and Giedre Valūnaite Oleškevičien e;licensed under Creative Commons License CC-BY 4.0

关键词： Linguistics

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ELSA: Euler-Lagrange Skeletal Animations - Novel and Fast Motion Model Applicable to VR/AR Devices 21st

ELSA: Euler-Lagrange Skeletal Animations - Novel and Fast Mo...

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21st International Conference on Computational science, ICCS 2021

作者： Wereszczyński, Kamil Michalczuk, Agnieszka Foszner, Pawel Golba, Dominik Cogiel, Michal Staniszewski, Michal Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland KP Labs Gliwice Poland

ISBN: (纸本)9783030779764

Euler Lagrange Skeletal Animation (ELSA) is the novel and fast model for skeletal animation, based on the Euler Lagrange equations of motion and configuration and phase space notion. Single joint’s animation is an integral curve in the vector field generated by those PDEs. Considering the point in the phase space belonging to the animation at current time, by adding the vector pinned to this point and multiplied by the elapsed time, one can designate the new point in the phase space. It defines the state, especially the position (or rotation) of the joint after this time elapses. Starting at time 0 and repeating this procedure N times, there is obtained the approximation, and if the N→ ∞ the integral curve itself. Applying above, to all joint in the skeletal model constitutes ELSA. © 2021, Springer Nature Switzerland AG.

关键词： Animation

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