LEADER 00706nam a2200217 i 4500 001 991001881829707536 005 20020503154542.0 008 990406s1933 it ||| | ita 035 $ab10285908-39ule_inst 035 $aEXGIL93031$9ExL 040 $aBiblioteca Interfacoltà$bita 100 1 $aDàuli, Gian$0394478 245 14$aGli assetati 260 $aMilano :$bLucchi,$c1933 300 $a398 p. 907 $a.b10285908$b02-04-14$c27-06-02 912 $a991001881829707536 945 $aLE002 Fondo Giudici M 455$g1$iLE002G-455$lle002$o-$pE0.00$q-$rn$so $t0$u0$v0$w0$x0$y.i1033841x$z27-06-02 996 $aAssetati$9210064 997 $aUNISALENTO 998 $ale002$b01-01-99$cm$da $e-$fita$git $h4$i1 LEADER 13486nam 22006255 450 001 9910586623503321 005 20250701050216.0 010 $a3-031-14627-1 024 7 $a10.1007/978-3-031-14627-5 035 $a(MiAaPQ)EBC7074398 035 $a(Au-PeEL)EBL7074398 035 $a(CKB)24655622700041 035 $a(PPN)264194055 035 $a(DE-He213)978-3-031-14627-5 035 $a(EXLCZ)9924655622700041 100 $a20220816d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Intelligent Networking and Collaborative Systems $eThe 14th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2022) /$fedited by Leonard Barolli, Hiroyoshi Miwa 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (513 pages) 225 1 $aLecture Notes in Networks and Systems,$x2367-3389 ;$v527 311 08$aPrint version: Barolli, Leonard Advances in Intelligent Networking and Collaborative Systems Cham : Springer International Publishing AG,c2022 9783031146268 320 $aIncludes bibliographical references and index. 327 $aIntro -- Welcome Message from the INCoS-2022 Organizing Committee -- INCoS-2022 Organizing Committee -- Honorary Chair -- General Co-chairs -- Program Co-chairs -- International Advisory Committee -- International Liaison Co-chairs -- Award Co-chairs -- Web Administrator Co-chairs -- Local Arrangement Co-chair -- Finance Chair -- Steering Committee Chair -- Track Areas and PC Members -- Track 1: Data Mining, Machine Learning and Collective Intelligence -- Track Co-chairs -- TPC Members -- Track 2: Intelligent Systems and Knowledge Management -- Track Co-chairs -- TPC Members -- Track 3: Wireless and Sensor Systems for Intelligent Networking -- Track Co-chairs -- TPC Members -- Track 4: Service-based Systems -- Track Co-chairs -- TPC Members -- Track 5: Networking Security and Privacy -- Track Co-chairs -- TPC Members -- Track 6: E-Learning and Web-based Systems -- Track Co-chairs -- TPC Members -- Track 7: Cloud Computing: Services, Storage, Security and Privacy -- Track Co-chairs -- TPC Members -- Track 8: Social Networking and Collaborative Systems -- Track Co-chairs -- TPC Members -- Track 9: Intelligent and Collaborative Systems for e-Health -- Track Co-chairs -- TPC Members -- Track 10: Big Data Analytics for Networking and Collaborative Systems -- Track Co-chairs -- TPC Members -- INCoS-2022 Reviewers -- INCoS-2022 Keynote Talks -- Sec44 -- Fundamental Model of Online User Dynamics Based on a Causal Framework -- Big Data Analytics on COVID-19 Epidemiological Data -- Contents -- User's Emotion Profiling in Web Browsing Behavior -- 1 Introduction -- 2 Related Work -- 2.1 Emotion Analysis and Emotion Model -- 2.2 Web Browsing Behavior -- 3 Motivating Example -- 4 Proposed Method -- 4.1 Overview -- 4.2 Web Browsing Behavior -- 4.3 Emotion Profiling -- 4.4 Gap Calculation Function -- 5 Conclusion -- References. 327 $aA Comparison Study of FC-RDVM and LDVM Router Placement Methods for WMNs by WMN-PSOHC Simulation System Considering Different Instances -- 1 Introduction -- 2 Intelligent Algorithms -- 2.1 Particle Swarm Optimization -- 2.2 Hill Climbing -- 3 WMN-PSOHC Hybrid Simulation System and FC-RDVM -- 4 Simulation Results -- 5 Conclusions -- References -- Stochastic Computing-Based Baseband Processing for Resource Constraint IoT Devices -- 1 Introduction -- 2 Background on SC, FIR Filter and Synchronization -- 2.1 Stochastic Computing (SC) -- 2.2 Finite Impulse Response (FIR) Filter -- 2.3 Synchronization -- 3 Related Work -- 4 Proposed SC-based Designs -- 4.1 2-By-2 Fast FIR Algorithm (FFA2) -- 4.2 3-By-3 FFA FIR Filter Design (FFA3) -- 4.3 Propose SC-Based FIR and Synchronization Designs -- 5 Performance Evaluation -- 5.1 Comparative Numerical Analysis -- 5.2 Simulation -- 5.3 Gate Counts and Energy Consumptions -- 6 Conclusion -- References -- Comparative Road State Decision Making Results by Various Environmental Sensors on Public Winter Road -- 1 Introduction -- 2 Related Works -- 3 Wide Area Road States Information Platform -- 4 Previous Version of Road Sensor Unit (RSU-1) -- 5 New Version of Road Sensor Unit (RSU-2) -- 5.1 Prototype and Performance Evaluation -- 6 Conclusions -- References -- A Movement Adjustment Method for DQN-Based Autonomous Aerial Vehicle Mobility: Performance Evaluation of AAV Mobility Control Method in Corner Environment -- 1 Introduction -- 2 DQN Based AAV Testbed -- 2.1 Quadrotor for AAV -- 2.2 DQN for AAV Mobility -- 3 Proposed Method -- 3.1 LiDAR Based Mobile Area Decision Method -- 3.2 TLS-DQN -- 3.3 Movement Adjustment Method -- 4 Performance Evaluation -- 4.1 Results of LiDAR Based Decision Method -- 4.2 Simulation Results of TLS-DQN -- 4.3 Results of Movement Adjustment Method -- 5 Conclusions -- References. 327 $aPersonalized Security Solutions in Dispersed Computing -- 1 Introduction -- 2 Personalized Secret Sharing Techniques -- 3 DNA-Based Visual Steganography -- 4 Conclusions -- References -- Obstacle Detection Support System Using Monocular Camera -- 1 Introduction -- 2 Previous Research -- 3 Obstacle Detection Support System Using Monocular Camera -- 3.1 Proposed System and Method -- 3.2 Detection of Obstacles by Depth Map -- 3.3 Detection of Obstacles by Deep Learning -- 4 Performance Evaluation -- 4.1 Detection of Obstacles by Depth Map -- 4.2 Detection of Obstacles by Deep Learning -- 5 Conclusions -- References -- Chatbot at University, a Communication Tool to Increase Work Productivity -- 1 Chatbot, a Tool for Effective Communication -- 2 Chatbot Types -- 2.1 Knowledge Domain Access -- 2.2 Type of Service Provided -- 2.3 Goals -- 2.4 Method of Input Processing and Response Generation -- 2.5 Method of Development -- 3 CASE Study -- 3.1 Analysis of Input Conditions -- 3.2 Time and Financial Analysis of the Selected Process (Question - Answer) -- 4 Conclusion -- References -- CoPoi: A Collaborative Framework to Optimize the Approach Towards Points of Interest -- 1 Introduction -- 2 Related Works -- 3 The Collaborative Framework -- 3.1 Dataset Generation -- 3.2 Time Contraction -- 3.3 Feedback Results -- 4 Valuation -- 4.1 Dataset Generation -- 4.2 Time Contraction and Feedback Results -- 5 Conclusions and Future Hints -- References -- Self-positioning Method Based on Similarity Between Environmental Map and Information of Image and Point Cloud -- 1 Introduction -- 2 Previous Research -- 3 Self-positioning Methods -- 3.1 Self-positioning Method Based on Similarity of Point Clouds -- 3.2 Self-positioning Method Based on Image -- 4 Performance Evaluation -- 4.1 Evaluation of Self-positioning Method Based on Similarity of Point Clouds. 327 $a4.2 Evaluation of Self-positioning Method Based on Image -- 5 Conclusions -- References -- Fake Listing or Truth? Using Pre-trained Deep Learning Model with Data Augmentation to Detect the Imposter -- 1 Introduction -- 2 Related Works -- 2.1 Re-sampling Data To Detect Auction Fraud -- 2.2 ResNet Model -- 2.3 FLAIR Model -- 2.4 BERT Model -- 3 Data and Methodology -- 3.1 Data Collection -- 3.2 Data Preparation -- 4 Results -- 4.1 Exploratory Data Analysis -- 4.2 Machine Learning Model -- 5 Discussion -- 6 Conclusion -- References -- Data Analytics for Parking Facility Management -- 1 Introduction and Related Works -- 2 Background -- 2.1 Auto-regressive Integrated Moving Average (ARIMA) Model -- 2.2 Neural Network-Based Time Series Prediction -- 3 Our Parking Data Analytics System -- 3.1 Prediction Period -- 3.2 Weighted Ensemble Prediction -- 3.3 Our Time Series Prediction Algorithm -- 4 Evaluation -- 4.1 Setup -- 4.2 Evaluation Metrics -- 4.3 Individual Results -- 4.4 Ensemble Results -- 5 Conclusions -- References -- OCR Error Correction for Vietnamese OCR Text with Different Edit Distances -- 1 Introduction -- 2 Candidate Generation Algorithm -- 2.1 Character Edit Operations -- 2.2 Candidate Generation Algorithm -- 3 Dataset and Experimental Results -- 3.1 Dataset -- 3.2 Experimental Results and Discussions -- 4 Conclusions -- References -- A Fuzzy-Based System for Assessment of Fog Computing Resources in SDN-VANETs Considering Service Migration Speed as a New Parameter -- 1 Introduction -- 2 Cloud-Fog-Edge SDN-VANETs -- 3 Proposed FL-Based System -- 4 Simulation Results -- 5 Conclusions -- References -- Performance Evaluation Experiments of Bitcoin SV Scaling Test Network -- 1 Introduction -- 2 Related Works -- 2.1 Calculation of Blockchain Split Probability -- 2.2 Theory of Priority Queuing -- 3 Bitcoin SV Scaling Test Network. 327 $a4 Performance Evaluation Experiments -- 4.1 Experiment 1: Estimating the Occupancy Rate of Approving Transactions in STN -- 4.2 Experiment 2: Estimating BC Split Probability -- 4.3 Experiment 3: Testing Transaction Processing Performance -- 5 Conclusion -- References -- The Emerging Challenges of Big Data Lakes, and a Real-Life Framework for Representing, Managing and Supporting Machine Learning on Big Arctic Data -- 1 Introduction -- 2 Related Work -- 3 ArcticDL: A Real-Life Framework for Representing, Managing and Supporting Machine Learning on Big Arctic Data -- 3.1 Data Sources -- 3.2 Front End -- 3.3 Back End -- 3.4 Metadata Design for the Back End -- 4 Challenges and Future Directions in Big Data Lake Research -- 5 Conclusions and Future Work -- References -- Data Ingestion for Data-Driven Service Platform: Royal Project Foundation Case Study -- 1 Introduction -- 1.1 The Royal Project Foundation -- 2 Related Works -- 2.1 Data Generation -- 2.2 Data Acquisition -- 2.3 REDCap -- 3 Data Management -- 3.1 Requirement Management -- 3.2 Data Collection -- 3.3 Data Collection in Action -- 3.4 Data Quality -- 4 Conclusion -- References -- A Study on an Autonomous Adaptive Mechanism for the Robustness of the User's Location-Aware Resource Assignment Against Demand Fluctuation -- 1 Introduction -- 2 Autonomous Decentralized Resource Assignment Method -- 2.1 System Model -- 2.2 Formulation of Assignment Problem -- 2.3 Autonomous Resource Assignment for Entities -- 2.4 Characteristics -- 3 Autonomous Adaptive Mechanism for Control Parameter -- 4 Simulation Result -- 4.1 Setting -- 4.2 Result -- 5 Conclusion and Future Work -- References -- Mesh Routers Placement by WMN-PSODGA Hybrid Intelligent System Considering Stadium Distribution and RDVM: A Comparison Study for Different Crossover Methods -- 1 Introduction. 327 $a2 Intelligent Algorithms for Proposed Hybrid Simulation System. 330 $aWith the fast development of the Internet, we are experiencing a shift from the traditional sharing of information and applications as the main purpose of the Web to an emergent paradigm, which locates people at the very center of networks and exploits the value of people's connections, relations, and collaboration. Social networks are also playing a major role in the dynamics and structure of intelligent Web-based networking and collaborative systems. Virtual campuses, virtual communities, and organizations strongly leverage intelligent networking and collaborative systems by a great variety of formal and informal electronic relations, such as business-to-business, peer-to-peer, and many types of online collaborative learning interactions, including the emerging e-learning systems. This has resulted in entangled systems that need to be managed efficiently and in an autonomous way. In addition, latest and powerful technologies based on grid and wireless infrastructure as well as cloud computing are currently enhancing collaborative and networking applications a great deal but also facing new issues and challenges. The principal purpose of the research and development community is to stimulate research that will lead to the creation of responsive environments for networking and, at longer-term, the development of adaptive, secure, mobile, and intuitive intelligent systems for collaborative work and learning. The aim of the book ?Advances on Intelligent Networking and Collaborative Systems? is to provide latest research findings, innovative research results, methods, and development techniques from both theoretical and practical perspectives related to intelligent social networks and collaborative systems, intelligent networking systems, mobile collaborative systems, secure intelligent cloud systems, and so on as well as to reveal synergies among various paradigms in such a multi-disciplinary field intelligentcollaborative systems. 410 0$aLecture Notes in Networks and Systems,$x2367-3389 ;$v527 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a004.6782 676 $a004.6 702 $aBarolli$b Leonard 702 $aMiwa$b Hiroyoshi 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910586623503321 996 $aAdvances in Intelligent Networking and Collaborative Systems$92542795 997 $aUNINA