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SPRINGER BRIEFS IN APPLIED SCIENCES AND TECHNOLOGY  POLIMI SPRINGER BRIEFS Barbara Pernici   Editor Special Topics in Information Technology SpringerBriefs in Applied Sciences and Technology PoliMI SpringerBriefs Editorial Board Barbara Pernici, Politecnico di Milano, Milano, Italy Stefano Della Torre, Politecnico di Milano, Milano, Italy Bianca M. Colosimo, Politecnico di Milano, Milano, Italy Tiziano Faravelli, Politecnico di Milano, Milano, Italy Roberto Paolucci, Politecnico di Milano, Milano, Italy Silvia Piardi, Politecnico di Milano, Milano, Italy More information about this subseries at http://www.springer.com/series/11159 http://www.polimi.it Barbara Pernici Editor Special Topics in Information Technology Editor Barbara Pernici DEIB Politecnico di Milano Milan,Italy ISSN 2191-530X ISSN 2191-5318 (electronic) SpringerBriefs inApplied SciencesandTechnology ISSN 2282-2577 ISSN 2282-2585 (electronic) PoliMI SpringerBriefs ISBN978-3-030-32093-5 ISBN978-3-030-32094-2 (eBook) https://doi.org/10.1007/978-3-030-32094-2 ©TheEditor(s)(ifapplicable)andTheAuthor(s)2020.Thisbookisanopenaccesspublication. Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adap- tation,distributionandreproductioninanymediumorformat,aslongasyougiveappropriatecreditto the originalauthor(s)and the source, providealink tothe CreativeCommonslicense andindicate if changesweremade. The images or other third party material in this book are included in the book’s Creative Commons license,unlessindicatedotherwiseinacreditlinetothematerial.Ifmaterialisnotincludedinthebook’s CreativeCommonslicenseandyourintendeduseisnotpermittedbystatutoryregulationorexceedsthe permitteduse,youwillneedtoobtainpermissiondirectlyfromthecopyrightholder. Theuse ofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc. inthis publi- cationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromthe relevantprotectivelawsandregulationsandthereforefreeforgeneraluse. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained hereinorforanyerrorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregard tojurisdictionalclaimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland Preface This book describes nine of the most promising results from doctoral studies in Information Technology at the Department of Electronics, Information, and BioengineeringofPolitecnicodiMilano.InformationTechnologyhasalwaysbeen interdisciplinary, as many aspects have to be considered in IT systems. The char- acteristicsoftheITPh.D.doctoralstudiesatPolitecnicodiMilanoisanemphasison thisinterdisciplinarynature,thatisbecomingmoreandmoreimportantintherecent technologicaldevelopments,incollaborativeprojectsandintheeducationofyoung researchers. The focus of advanced research is therefore on a rigorous approach to specific research topics starting from a broad background in different aspects of Information Technology, and in particular in the areas of Computer Science and Engineering, Electronics, Systems and Controls, and Telecommunications. Each year, more than 50 doctors are graduated from the program. The present bookcollectstheninebestresultsfromthedefendedthesesin2018–19selectedfor the IT Ph.D. Award. Each of the nine authors provides a chapter summarizing research results, including an introduction, description of methods, main achieve- ments, and future work on the topic. Hence, this book provides a cutting-edge overview of the newest research trends in Information Technology developed at PolitecnicodiMilano,inaneasy-to-readformatforpresentingthemainresultsalso to nonspecialists in the specific field. Milan, Italy Barbara Pernici July 2019 v Introduction The Ph.D. Program in Information Technology A fundamental pillar for the research work in the Department of Electronics, Information, and Bioengineering (DEIB) is its Ph.D. program in Information Technology, with more than 50 doctors graduating each year. The program is characterized by a broad approach to information technology, in the areas of Computer Science and Engineering, Electronics, Systems and Controls, and Telecommunications. ThecharacteristicsoftheITPh.D.doctoralstudiesintheDEIBdepartmentisan emphasis on interdisciplinarity, that is becoming more and more important in the recenttechnologicaldevelopmentsinwhichtheboundariesbetweendisciplinesare becoming increasingly fuzzy in collaborative projects and education of young researchers. Therefore, the focus of the program is on providing a broad doctoral- level educational approach and research environment and at the same time, a rig- orousapproachtothespecificresearchtopicsdevelopedbythePh.D.candidatesin different aspects of Information Technology, based on both on theoretical approaches and on the validation of new ideas in selected application domains. Starting with the present volume, we present the ongoing research work in doctoral studies in the department, through a collection of summaries illustrating theresultsofthebestPh.D.thesesdefendedintheacademicyear 2018–19.Inthis chapter, the coordinators of each of the areas are going to introduce the four areas of the Ph.D. program in Information Technology, namely Computer Science and Engineering, Electronics, Systems and Controls, and Telecommunications, and provide a short introduction to the papers selected for the volume. vii viii Introduction Telecommunications Area The research carried out by the Ph.D. graduates within Telecommunications Engineering span heterogeneous disciplines, which include information theory, communication networks, signal processing, and microwaves and photonics. The two theses selected to be part of this volume address two different aspects and applications of digital signal processing. The contribution on “Advances in Wave Digital Modeling of Linear and Nonlinear Systems” advances the theory of wave digital modeling, that is, the construction of digital representation of analog systems. The thesis re-vitalizes and extends the theory of Wave Digital Filters (WDF) of the late 70s by proposing novel approaches, which can be applied to generic physical systems provided that they can be described by an equivalent electric circuit. The contributions provided in the work have relevant implications notonlyinthefieldofnumericalsimulationofphysicalphenomena,butalsointhe field of digital audio signal processing, as it allows to model different kinds of processing structures in a unified fashion. The second contribution comes from the Ph.D. thesis “Interference Mitigation Techniques in Hybrid Wired-Wireless Communications Systems for Cloud Radio Access Networks with Analog Fronthauling”; the work addresses the fifth gener- ation(5G)ofradiomobilenetworkswiththegoalofimprovingtheindoorcoverage of5Gnetworks.Thekeycontributionoftheworkisanovelarchitecturetoprovide coverage indoors by leveraging preexisting copper-based cables connections. The thesis first theoretically demonstrates the feasibility and efficiency of the proposed solution, and finally also describes the realization and performance evaluation of a prototype platform, which experimentally proves the capability of the proposed architecture to notably extend indoor coverage. Electronics Area ThePh.D.focusedinElectronicsexplorestheenablingfrontierscenariosofcurrent and future era technologies of information, communication, control, automation, energy, and mobility. Design and innovation of devices, circuits and electronic systems continue to provide the fundamental building blocks necessary for modern life in all its per- spectives, including its most recent declinations “smart-” (smart cyberphysical- systems,smartindustries,smartmanufacturing,smartliving, smartmobility,smart lighting, smart cities, smart aging, etc.) and “autonomous-” (autonomous driving, autonomous vehicles, autonomous-manufacturing, autonomous agents, etc.), so pervasive in modern daily human activities. Forinstance,thenewconceptofsmartmobilityfindsoneofthemostsignificant declinations in self and highly assisted driving, where the continuous-wave frequency-modulated (FMCW) radar is a key element. This short-range measuring Introduction ix radarsetcapableofdeterminingdistanceincreasesreliabilitybyprovidingdistance measurement along with speed measurement, which is essential in modern auto- motiveapplications.DmytroCherniakhasgivenastrongcontributiontothefieldof integrated FMCW radar. These innovations support the emerging market for autonomous vehicles, which will rely heavily on radar and wireless sensing to achieve reliable all-weather mobility. High performance and low-power con- sumption meet in the first implemented digital PLL-based FMCW modulator prototype fabricated in 65-nm CMOS technology that demonstrates the above-state-of-the-art performance of fast chirp synthesis, also developed and fabricated in 28-nm CMOS technology focusing on low-fractional spur operation. From a completely different perspective, the human brain is a marvelous machine,whichiscapableofsolvingchallengingproblemsinaveryshorttimeand withsmallenergyconsumption.Recognizingaface,learningtowalk,andtakinga quick decision under a large number of stimuli are generally straightforward functionsformankind.However,recreatingthistypeofcomputationinsiliconwith the same speed, energy consumption, and hardware resources is practically impossiblewiththecurrentmicroelectronictechnology.TheworkbyValerioMilo addressesthesechallenges,byshowingthatanewtypeofdevicesandarchitecture is needed if we want to mimic the brain computation. It is shown that synaptic devices made of inorganic materials, such as metal oxides, show the same type of plasticity that is observed in biological synapses. By taking advantage of such biological plasticity rules within artificial spiking neural networks, it is possible to learn, make associations, and take decisions, which are some of the most funda- mental cognitive functions of the human brain. Although the work is at the very early stages, the results are very promising for supporting the grand challenge of bio-inspired circuits that can compute as the brain, and even illuminate about the biological processes of learning in our brain. Computer Science and Engineering Area The Computer Science and Engineering Area covers five different research lines, ranging from System Architectures, to Data, Web and Society, to Artificial IntelligenceandRobotics,toAdvancedSoftwareArchitecturesandMethodologies, and Information Systems. Research on these lines are covering both foundational aspectsaswellasapplication-drivenaspects.ThegroupofSystemArchitecturesis active on several research topics, including security, performance evaluation, dependability, electronic design automation, processor and multiprocessor archi- tectures, operating systems, embedded systems, computational intelligence, wire- less sensor networks, enterprise digital infrastructures, and high-performance computing. The research in the area of Data, Web, and Society addresses tech- nologies, design methods, and tools for data management systems, information management and querying on the Web, and multimedia and multichannel com- munication. The research group on Artificial Intelligence and Robotics also covers x Introduction the areas of autonomous agents, computational intelligence, machine learning, autonomousrobotics,computervision,includingrelatedphilosophicalaspects.The research group on Software Architectures and Methodologies addresses topics on dependable evolvable software engineering, compiler technologies, and natural language processing and accessibility. Finally, the research line on Information Systems focuses on the following sectors: design of adaptive information systems, dataandinformationquality,BigDataanddataanalysis,socialmediaintelligence, information security and security analysis, service quality and green information systems, and design and monitoring of multiparty business processes integrated with smart objects. The four Ph.D. theses selected in the Computer Science and Engineering Area fallintheSystemArchitecturesresearchline,buttheyareaddressingfourdifferent and challenging research problems. ThePh.D.thesis“LearningandAdaptationtoDetectChangesandAnomaliesin High-DimensionalData”byDiegoCarrerainvestigatestheproblemofmonitoringa datastreamanddetectingwhetherthedatageneratingprocesschanges,fromnormal tonovelandpossiblyanomalousconditions,hasrelevantapplicationsinmanyreal scenarios, suchashealthmonitoring andqualityinspectionofindustrial processes. In the first part, the thesis models data as realization of random vectors, as it is customaryinthestatisticalliterature.Inthissetting,thethesisfocusesonthechange detection problem, where thegoalis to detect whether the datastream permanently departs from normal conditions. The thesis theoretically proves the intrinsic diffi- culty of this problem when the data dimension increases and propose a novel nonparametric and multivariate change detectionalgorithm. In the second part, the thesis focuses on data having complex structure and adopts dictionaries yielding sparse representations to model normal data. Novel algorithms are proposed to detect anomalies in such datastreams and to adapt the learned model when the process generating normal data changes. The Ph.D. thesis titled “Enhancing Video Recommendation Using Multimedia Content”byYashar Deldjooisfocusedonhowtoimprove video recommendation systems by using complex multimedia content and learning form multimodal sources. The Ph.D. thesis investigates the possibility of uncovering relationships betweenmodalitiesandobtaininganin-depthunderstandingofnaturalphenomena occurring in a video. The thesis studies the automated extraction of multimedia informationfromvideosandtheirintegration withvideorecommendersystems.In the thesis, a variety of tasks related to movie recommendation using multimedia content have been studied, implemented, and evaluated. The results of this thesis confirm the fact that recommender system research can benefit from knowledge in multimedia signal processing and machine learning over the past years for solving various recommendation tasks. The Ph.D. thesis titled “Dynamic Application Autotuning for Self-aware Approximate Computing” by Davide Gadioli addresses the problem of software application autotuning to support self-aware approximate computing in several scenarios, from embedded systems to high-performance computing. To improve computation efficiency, this thesis focuses on a software-level methodology to

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