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Work-in-Progress: Using the PerFECt Framework to Design and Implement Blended Learning Activities to Introduce the Binary System in Primary School Students

Work-in-Progress: Using the PerFECt Framework to Design and ...

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9th International Conference on Interactive Collaborative and Blended Learning, ICBL 2020

作者： Moumoutzis, Nektarios Rigas, Nikolaos Apostolos Xanthaki, Chara Maragkoudakis, Yiannis Christodoulakis, Christina Paneva-Marinova, Desislava Pavlova, Lilia Laboratory of Distributed Multimedia Information Systems and Applications School of Electrical and Computer Engineering Technical University of Crete Chania Crete73100 Greece Institute of Mathematics and Informatics Bulgarian Academy of Sciences Sofia1113 Bulgaria Directorate of Secondary Education Chania Crete Greece Department of Computer Science University of Toronto Toronto Canada Laboratory of Telematics Bulgarian Academy of Sciences Sofia1113 Bulgaria

ISBN: (纸本)9783030672089

This paper presents how the PerFECt framework is employed to enable innovative teaching and learning mathematics in schools using drama-based approaches. The topic addressed lies in the cross-section between mathematics and computer science: teaching and learning the binary system of arithmetic that constitutes the basis of modern computing. The work builds on previous research efforts targeting gamification of mathematics and is seen under new light offered by the Theatre in Mathematics (TIM) Methodology. The result is an engaging game to teach the binary system to children using their bodies and simple rules for interacting with each other. Following these simple rules the participants enact the operation of a calculator that is able to transform integers into their binary representations and compute the result of the four arithmetic operations (addition, subtraction, multiplication and division). The game can be combined with online activities using a simulator of the game, so that learners can explore it for themselves and discover how the arithmetic operations are done, even when they are not in the same physical space with their peers. This way, an effective blended learning approach is ultimately offered combining face-to-face and online activities. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Learning systems

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Reference-Plane Invariant Free Space Dielectric Material Characterization up to 330 GHz

Reference-Plane Invariant Free Space Dielectric Material Cha...

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URSI Atlantic Radio Science Conference (URSI AT-RASC)

作者： Salvador Moreno-Rodríguez Mario Pérez-Escribano Sergio Ortiz-Ruiz Antonio Alex-Amor Borja Plaza-Gallardo Francisco G. Ruiz Carlos Molero Department of Signal Theory Telematics and Communications Research Centre for Information and Communication Technologies (CITIC-UGR) University of Granada Granada Spain Telecommunication Research Institute (TELMA) Universidad de Málaga E.T.S. Ingeniería de Telecomunicación Málaga Spain Department of Electronics and Computer Science Pervasive Electronics Advanced Research Laboratory (PEARL) University of Granada Granada Spain Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia Pennsylvania United States Radiofrequency Area National Institute for Aerospace Technology (INTA) Madrid Spain

ISBN: (数字)9789463968102

ISBN: (纸本)9798350360257

This paper describes the process followed to implement a system to characterize the complex permittivity of materials in the 10-330 GHz frequency band. Firstly, the method used and the system’s calibration process are shown, consisting of a double calibration TRL (Thru-Reflect-Line) and GRL (Gated-Reflect-Line). Subsequently, a smoothing technique is used to improve the accuracy of the results. Finally, a test is performed on quartz and glass fiber samples, showing that the results are quite reliable over the entire measured bandwidth.

关键词： Accuracy Smoothing methods Permittivity measurement Glass Bandwidth Position measurement Reflection

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A Machine Learning-Based Framework to Estimate the Lifetime of Network Line Cards

A Machine Learning-Based Framework to Estimate the Lifetime ...

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IEEE Symposium on Network Operations and Management

作者： Juan Luis Herrera Marco Polverini Jaime Galán-Jiménez Department of Computer Systems and Telematics Engineering University of Extremadura Spain DIET Department University of Rome "Sapienza" Rome Italy

ISBN: (数字)9781728149738

ISBN: (纸本)9781728149745

With the increasing tendency on data rates in forthcoming communication networks, availability is a crucial aspect to guarantee Quality of Service (QoS) requirements. The possibility of predicting the lifetime of networking hardware can be a key to improve the overall network QoS. This paper proposes a generic Machine Learning (ML) based framework that learns how to mimic the mathematical model behind the lifetime of network line cards. Results show that a good precision (85%) and recall (close to 100%) on the estimation can be achieved regardless the type of line cards the network is composed of.

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A performance-based tabular approach for joint systematic improvement of risk control and resilience applied to telecommunication grid, gas network, and ultrasound localization system

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Environment systems and Decisions 2021年第2期41卷 286-329页

作者： Häring, Ivo Fehling-Kaschek, Mirjam Miller, Natalie Faist, Katja Ganter, Sebastian Srivastava, Kushal Jain, Aishvarya Kumar Fischer, Georg Fischer, Kai Finger, Jörg Stolz, Alexander Leismann, Tobias Hiermaier, Stefan Carli, Marco Battisti, Federica Makri, Rodoula Celozzi, Giuseppe Belesioti, Maria Sfakianakis, Evangelos Agrafioti, Evita Chalkidou, Anastasia Papadakis, George Fuggini, Clemente Bolletta, Fabio Neri, Alberto Giunta, Guiseppe Scheithauer, Hermann Höflinger, Fabian Schott, Dominik J. Schindelhauer, Christian Köhler, Sven Linkov, Igor Fraunhofer Institute for High-Speed Dynamics Ernst-Mach-Institut EMI Freiburg Germany Department of Engineering Roma Tre University Rome Italy Institute of Communication and Computer Systems (ICCS) of the National Technical University of Athens Athens Greece Ericsson Telecomunicazioni S.P.A. Pagani SA Italy Hellenic Telecommunications Organization (OTE) S.A. Maroussi Athens Greece Gap Analysis Crete Greece RINA Consulting Rozzano Italy Leonardo Company Rome Italy ENI San Donato Milanese Italy Hahn-Schickard Villingen-Schwenningen Germany Department of Microsystems Engineering IMTEK University of Freiburg Freiburg Germany Computer Networks and Telematics University of Freiburg Freiburg Germany Engineering Research and Development Center US Army Corps of Engineers Concord MA United States

Organizational and technical approaches have proven successful in increasing the performance and preventing risks at socio-technical systems at all scales. Nevertheless, damaging events are often unavoidable due to a wide and dynamic threat landscape and enabled by the increasing complexity of modern systems. For overall performance and risk control at the system level, resilience can be a versatile option, in particular for reducing resources needed for system development, maintenance, reuse, or disposal. This paper presents a framework for a resilience assessment and management process that builds on existing risk management practice before, during, and after potential and real events. It leverages tabular and matrix correlation methods similar as standardized in the field of risk analysis to fulfill the step-wise resilience assessment and management for critical functions of complex systems. We present data needs for the method implementation and output generation, in particular regarding the assessment of threats and the effects of counter measures. Also included is a discussion of how the results contribute to the advancement of functional risk control and resilience enhancement at system level as well as related practical implications for its efficient implementation. The approach is applied in the domains telecommunication, gas networks, and indoor localization systems. Results and implications are further discussed. © 2021, The Author(s).

关键词： engineering of resilience ISO 31000 Joint risk and resilience analysis and management process Resilience dimensions Socio-technical system System performance function Tabular and matrix approach

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Recognition of food-texture attributes using an in-ear microphone

arXiv

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arXiv 2021年

作者： Mars, Monica Diou, Christos Papapanagiotou, Vasileios van den Boer, Janet Delopoulos, Anastasios Multimedia Understanding Group Dpt. Electrical and Computer Engineering Faculty of Engineering Aristotle University of Thessaloniki Greece Department of Informatics and Telematics Harokopio University of Athens Greece Dpt. of Biomedical Signals and Systems Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Division of Human Nutrition and Health Wageningen University Netherlands

Food texture is a complex property;various sensory attributes such as perceived crispiness and wetness have been identified as ways to quantify it. Objective and automatic recognition of these attributes has applications in multiple fields, including health sciences and food engineering. In this work we use an in-ear microphone, commonly used for chewing detection, and propose algorithms for recognizing three food-texture attributes, specifically crispiness, wetness (moisture), and chewiness. We use binary SVMs, one for each attribute, and propose two algorithms: one that recognizes each texture attribute at the chew level and one at the chewing-bout level. We evaluate the proposed algorithms using leave-one-subject-out cross-validation on a dataset with 9 subjects. We also evaluate them using leave-one-food-type-out cross-validation, in order to examine the generalization of our approach to new, unknown food types. Our approach performs very well in recognizing crispiness (0.95 weighted accuracy on new subjects and 0.93 on new food types) and demonstrates promising results for objective and automatic recognition of wetness and chewiness. Copyright © 2021, The Authors. All rights reserved.

关键词： Wearable technology

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The Service Node Placement Problem in Software-Defined Fog Networks

The Service Node Placement Problem in Software-Defined Fog N...

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IEEE Symposium on computers and Communications (ISCC)

作者： Juan Luis Herrera Luca Foschini Jaime Galán-Jiménez Javier Berrocal Department of Computer Systems and Telematics Engineering University of Extremadura Spain Dipartamento di Informatica-Scienza e Ingegneria University of Bologna Italy

ISBN: (数字)9781728180861

ISBN: (纸本)9781728180878

Nowadays, cloud computing has become a key paradigm in distributed applications thanks to the rise of low-power Internet-connected devices as commonplace. However, stringent Quality of Service (QoS) requirements are complicated to achieve when a pure cloud computing paradigm is applied, due to the physical distance between end devices and cloud servers. This motivated the appearance of fog computing, a paradigm that adds computation and storage resources, named fog nodes, closer to the end devices in order to reduce response time and latency. However, the placement of fog nodes, as well as the relative placement of the end devices each fog node serves, can affect the QoS obtained. This can be crucial to those services that have stringent QoS requirements. In this work, we analyze the effects that different placements of fog nodes have on QoS and present the problem of placing fog nodes to obtain an optimal QoS, with a focus on the Industrial Internet of Things domain because of its strict QoS requirements. We conclude that an optimized placement of the fog nodes can minimize latency to support the QoS requirements of IIoT applications.

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Deep Learning Based Single Image Super-resolution:A Survey

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International Journal of Automation and computing 2019年第4期16卷 413-426页

作者： Viet Khanh Ha Jin-Chang Ren Xin-Ying Xu Sophia Zhao Gang Xie Valentin Masero Amir Hussain Department of Electronic and Electrical Engineering University of Strathclyde Glasgow G1 1XW UK College of Information Engineering Taiyuan University of Technology Taiyuan 030024 China School of Electronic Information Engineering Taiyuan University of Science and Technology Taiyuan 030024 China Department of Computer Systems and Telematics Engineering University of Extremadura Badajoz 06006 Spain School of Computing Edinburgh Napier University Edinburgh EH10 5DT UK School of Computer Science and Technology Anhui University Anhui 230039 China

Single image super-resolution has attracted increasing attention and has a wide range of applications in satellite imaging, medical imaging, computer vision, security surveillance imaging, remote sensing, objection detection, and recognition. Recently, deep learning techniques have emerged and blossomed, producing " the state-of-the-art” in many domains. Due to their capability in feature extraction and mapping, it is very helpful to predict high-frequency details lost in low-resolution images. In this paper, we give an overview of recent advances in deep learning-based models and methods that have been applied to single image super-resolution tasks. We also summarize, compare and discuss various models from the past and present for comprehensive understanding and finally provide open problems and possible directions for future research.

关键词： Image super-resolution convolutional neural network high-resolution image low-resolution image deep learning

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Dynamic In-Network Classification for Service Function Chaining ready SDN networks

Dynamic In-Network Classification for Service Function Chain...

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International Conference on the Network of the Future (NOF)

作者： Marco Polverini Jaime Galán-Jiménez Francesco G. Lavacca Antonio Cianfrani Vincenzo Eramo DIET Department University of Rome "Sapienza" Rome Italy Department of Computer Systems and Telematics Engineering University of Extremadura Spain Fondazione Ugo Bordoni Italy

ISBN: (数字)9781728144450

ISBN: (纸本)9781728144467

Service Function Chaining (SFC) paradigm consists in steering traffic flows through an ordered set of Service Functions (SFs) so that to realize complex end to end services. SFC architecture introduces all the logical functions that need to be developed in order to provide the required service. The SFC overlay infrastructure can be built on top of many different underlay network technologies. The high flexibility and centrally controlled feature of Software Defined Networking (SDN), make SDN networks to be a perfect underlay to build the SFC architecture. Due to Ternary Content Address Memory (TCAM) limited size, SDN switches have a limitation in the number of flow rules that can be hosted. This constraint is particularly penalizing in case of the SFC classifier function, since it requires to manage a high number of different flows. The limitation imposed by the TCAM size on the SFC classifier can be a bottleneck for the number of SFC requests that the SDN-based SFC architecture can handle. In this paper we define the Dynamic Chain Request Classification Offloading (D-CRCO) problem, as the one of maximizing the number of accepted SFC requests, having the possibility of: i) implement the SFC classifier also in a node that is internal to the SDN-based SFC domain, and ii) install classification rules in a reactive fashion. Furthermore, we propose the Dynamic Nearest Node (DNN) heuristic to solve the D-CRCO problem. Performance evaluation shows that by using DNN heuristic it is possible to triple the number of accepted requests, with respect to existing solutions.

关键词： computer architecture IP networks Bandwidth Performance evaluation Routing Servers Software

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Heavy-Hitter Flow Identification in Data Centre Networks Using Packet Size Distribution and Template Matching

Heavy-Hitter Flow Identification in Data Centre Networks Usi...

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Conference on Local computer Networks (LCN)

作者： Alejandra Duque-Torres Adrian Pekar Winston K.G. Seah Oscar Mauricio Caicedo Rendon Department of Telematics Engineering University of Cauca Popayan Colombia Department of Networked Systems and Services Budapest University of Technology and Economics Hungary School of Engineering and Computer Science Victoria University of Wellington New Zealand

Data Centre Networks (DCNs) handle large volumes of data transmission that can consume a lot of bandwidth in short bursts or over prolonged periods of time. One class of traffic that constantly poses a challenge is Heavy-Hitter (HH) flows - large-volume flows that consume considerably more network resources than other flows combined. The identification of such flows is critical to prevent network congestion and overall network performance degradation. Most of the existing methods to identify HHs are based on thresholds, i.e., if the flow exceeds a predefined threshold, it will be marked as a HH; otherwise, it will be classified as a non-HH. However, these approaches present two significant issues. First, there is no consistent and accepted threshold that would reliably classify flows. Second, the existing threshold approaches use counters (duration, packets, and bytes); thus their accuracy depends on how complete the flow information is. In this paper, we address those issues using per-flow packet size distribution which can capture the behaviour and dynamics of network traffic flow more accurately than the counters in the early stage of the flow. We then propose the use of the template matching technique to identify HHs and achieved a classification accuracy of 96% using only the first 14 packets of a flow.

关键词： Probability density function Reliability Random variables Data centers Estimation Quality of service Generators

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A subject syllabus similarity analysis to address students mobility issue 12

A subject syllabus similarity analysis to address students m...

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12th International Multi-Conference on Society, Cybernetics and Informatics, IMSCI 2018

作者： Saquicela, Victor Baculima, Fernando Orellana, Gerardo Orellana, Marcos Piedra, Nelson Espinoza, Mauricio Vanegas, Pablo Computer Science Department University of Cuenca Cuenca Azuay010150 Ecuador School of Systems Engineering and Telematics University of Azuay Cuenca Azuay010150 Ecuador Computer Science Department Technical University of Loja Cuenca Azuay010150 Ecuador

ISBN: (纸本)9781941763858

Currently, students' mobility in Higher Education has become very common and frequent. Although the transitioning process could be thought to be smooth and quick, students moving from one institution to another must go through rigorous and unfortunately, non-standardized academic validation processes. Usually, most part of the process, including credits recognition and syllabi comparison are manually performed, consuming excessive time and massive human effort. Some of these academic processes however, could be optimized by means of computer technologies, which support data processing and help solving real-life problems usually found in the academic field. In the specific case of Ecuador, we have identified that each Higher Education Institution (HEI) manages customized curricular information management systems which include non-standard syllabi structured documents. The existence of custom made formats at every HEI has originate a large variety of data models. In this work, we propose to address these problems by identifying similarities between different current syllabi of Ecuadorian HEIs, aiming to the optimization, integration and improvement of the academic activities related to the students' mobility processes, such as credits recognition. This proposal relies on the definition of a standard data model, which is used to describe the academic syllabus and that allows the implementation of a computer-based system focused on similarities detection through the use of semantic web technologies and text mining tools. Copyright © 2018 by the International Institute of Informatics and Systemics.

关键词： Students

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