LEADER 00956nam0-22002891--450- 001 990008606720403321 005 20080129092010.0 035 $a000860672 035 $aFED01000860672 035 $a(Aleph)000860672FED01 035 $a000860672 100 $a20080129d1903----km-y0itay50------ba 101 0 $aita 102 $aIT 105 $ay-------001yy 200 1 $aAsti e la politica sabauda in Italia al tempo di Guglielmo Ventura secondo nuovi documenti$fFerdinando Gabotto 210 $aPinerolo$ctip. Chiantore-Mascarelli$d1903 215 $a604 p.$d26 cm 225 1 $aBiblioteca della Società storica subalpina$v7 700 1$aGabotto,$bFerdinando$f<1866-1918>$0179652 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990008606720403321 952 $aSDI-XIII F 8$b138$fSDI 959 $aSDI 996 $aAsti e la politica sabauda in Italia al tempo di Guglielmo Ventura secondo nuovi documenti$9711850 997 $aUNINA LEADER 00839nam0-22002651i-450- 001 990000070920403321 005 20080627095054.0 035 $a000007092 035 $aFED01000007092 035 $a(Aleph)000007092FED01 035 $a000007092 100 $a20020821d--------km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aUeber das Elektromotorische Verhalten von Metallen$evon der K. technischen Hochschule zu Mnchen zur Erlangung derWrde eines Doktors der technischen Wissenschaften genehmigte Dissertation$fFritz Fraunberger. 210 $aMnchen$cJ. Fuller$d1904 215 $a40 p.$d22 cm 676 $a546.3 700 1$aFraunberger,$bFritz 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990000070920403321 952 $a23 19 A 08$b2700$fFINAG 959 $aFINAG 997 $aUNINA LEADER 12664nam 22006495 450 001 9910637709903321 005 20251008153557.0 010 $a3-031-09753-X 024 7 $a10.1007/978-3-031-09753-9 035 $a(MiAaPQ)EBC7165913 035 $a(Au-PeEL)EBL7165913 035 $a(CKB)25913961200041 035 $a(DE-He213)978-3-031-09753-9 035 $a(PPN)267815794 035 $a(EXLCZ)9925913961200041 100 $a20221221d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSmart Applications with Advanced Machine Learning and Human-Centred Problem Design /$fby D. Jude Hemanth, Utku Kose, Junzo Watada, Bogdan Patrut 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (801 pages) 225 1 $aEngineering Cyber-Physical Systems and Critical Infrastructures,$x2731-5010 ;$v1 311 08$aPrint version: Hemanth, D. Jude Smart Applications with Advanced Machine Learning and Human-Centred Problem Design Cham : Springer International Publishing AG,c2023 9783031097522 327 $aIntro -- General Committees -- Honorary Chairs -- General Chair -- Conference Chairs -- Organizing Committee -- Secretary and Social Media -- Accommodation and Registration/Venue Desk -- Travel/Transportation -- Web/Design/Conference Session -- Scientific Committee -- Keynote Speaks -- ICAIAME 2021 Keynote Speakers -- Foreword -- Preface -- Contents -- About the Conference -- Scope/Topics -- Conference Scope/Topics (as not limited to) -- Conference Posters -- 1 Implementation of Basic Math Processing Skills with Neural Arithmetic Expressions in One and Two Stage Numbers -- 1.1 Introduction -- 1.1.1 Neural Arithmetic Expressions and Logic Units -- 1.1.2 Long Short-Term Memory Algorithm -- 1.2 Related Work -- 1.3 Proposed Method -- 1.4 Experimental Findings -- 1.5 Conclusions -- References -- 2 An Example Application for Early Diagnosis of Retinal Diseases Using Deep Learning Methods -- 2.1 Introduction -- 2.2 Material and Method -- 2.2.1 Material -- 2.2.2 Method -- 2.3 Research Findings -- 2.4 Discussion -- 2.5 Results -- References -- 3 Autonomous Parking with Continuous Reinforcement Learning -- 3.1 Introduction -- 3.2 Related Works -- 3.2.1 Deep Q Networks -- 3.2.2 Deep Deterministic Policy Gradient Algorithm -- 3.2.3 Twin Delayed Temporal Difference Algorithm -- 3.2.4 Soft Actor Critic Algorithm -- 3.2.5 Hindsight Experience Replay Algorithm -- 3.2.6 Parking Environment Simulation Model -- 3.3 Experiments and Results -- 3.4 Conclusions and Future Work -- References -- 4 Design and Manufacturing of a 3 DOF Robot with Additive Manufacturing Methods -- 4.1 Introduction -- 4.2 Material and Method -- 4.2.1 Material -- 4.3 Method -- 4.4 Findings and Discussion -- 4.5 Conclusion -- References -- 5 Real-Time Mask Detection Based on Artificial Intelligence Using Renewable Energy System Unmanned Aerial Vehicle -- 5.1 Introduction -- 5.2 Related Studies. 327 $a5.3 Material and Method -- 5.3.1 Material -- 5.3.2 Material and Method -- 5.4 Research Findings -- 5.5 Conclusion -- References -- 6 Investigation of Effect of Wrapping Length on the Flexural Properties of Wooden Material in Reinforcement with Aramid FRP -- 6.1 Introduction -- 6.2 Material and Method -- 6.3 Results -- 6.4 Conclusions -- References -- 7 Deep Learning-Based Air Defense System for Unmanned Aerial Vehicles -- 7.1 Introduction -- 7.2 Material and Method -- 7.2.1 Material -- 7.2.2 Method -- 7.3 Research Findings -- 7.3.1 MobileNetV2 Training Results -- 7.3.2 Xception Training Results -- 7.3.3 InceptionV3 Training Results -- 7.4 Results -- References -- 8 Strategic Framework for ANFIS and BIM Use on Risk Management at Natural Gas Pipeline Project -- 8.1 Introduct?on -- 8.2 Literature -- 8.3 Materials and Methods -- 8.3.1 Artificial Neural Networks (ANN) -- 8.3.2 Structure of Artificial Neural Network -- 8.3.3 Fuzzy Inference System -- 8.3.4 Adaptive Neuro-Fuzzy Inference System-ANFIS -- 8.3.5 What is the Building Information Modelling (BIM) -- 8.3.6 Methods -- 8.4 Results -- 8.5 Conclusion -- References -- 9 Predicting Ethereum Price with Machine Learning Algorithms -- 9.1 Introduction -- 9.2 Related Works -- 9.3 Method and Material -- 9.3.1 Used Methods -- 9.3.2 Data Collecting -- 9.3.3 Method -- 9.4 Discussion and Results -- 9.5 Conclusions and Future Work -- References -- 10 Data Mining Approachs for Machine Failures: Real Case Study -- 10.1 Introduct?on -- 10.2 Literature -- 10.3 Methods -- 10.3.1 Re-processing the Data -- 10.3.2 Methods -- 10.4 Results -- 10.5 Conclusion -- References -- 11 Classification of People Both Wearing Medical Mask and Safety Helmet -- 11.1 Introduction -- 11.2 Materials and Methods -- 11.2.1 Dataset -- 11.2.2 Method -- 11.2.3 Single Deep Neural Network -- 11.2.4 Double Deep Neural Network. 327 $a11.3 Conclusions and Future Work -- References -- 12 Anonymization Methods for Privacy-Preserving Data Publishing -- 12.1 Introduction -- 12.2 Big Data Definition -- 12.3 Data Anonymization -- 12.3.1 Protection Methods with Anonymization -- 12.3.2 Anonymization and Protection Models -- 12.4 Literature Review -- 12.5 Comparison of Existing Studies -- 12.6 Conclusion -- References -- 13 Improving Accuracy of Document Image Classification Through Soft Voting Ensemble -- 13.1 Introduction -- 13.2 Related Works -- 13.3 Methodology -- 13.3.1 Document Image Classification -- 13.3.2 Image Pre-processing -- 13.3.3 Convolutional Neural Network -- 13.3.4 Soft Voting -- 13.4 Experiments and Result -- 13.4.1 Dataset -- 13.4.2 Evaluation Metrics -- 13.4.3 Experiments -- 13.5 Conclusion -- References -- 14 Improved Performance of Adaptive UKF SLAM with Scaling Parameter -- 14.1 Introduction -- 14.2 Adaptive UKF SLAM -- 14.3 Simulation Results and Discussions -- 14.4 Conclusion and Suggestions -- References -- 15 An Adaptive EKF Algorithm with Adaptation of Noise Statistic Based on MLE, EM and ICE -- 15.1 Introduction -- 15.2 Methods -- 15.2.1 Extended Kalman Filter (EKF) -- 15.2.2 Unscented Kalman Filter (UKF) -- 15.2.3 Adaptive Extended Kalman Filter (AEKF) -- 15.2.4 Data Association -- 15.2.5 AEKF-SLAM Algorithm -- 15.3 Simulation Results and Discussion -- 15.4 Conclusions and Future Work -- References -- 16 Artificial Intelligence Based Detection of Estrus in Animals Using Pedometer Data -- 16.1 Introduction -- 16.2 Related Works -- 16.3 Method and Material -- 16.3.1 Architectural Design -- 16.3.2 Devices -- 16.3.3 Electronic Circuit Design -- 16.3.4 Proposed Algorithms -- 16.4 Discussion and Result -- 16.5 Conclusions and Future Work -- References -- 17 Enhancing Lexicon Based Sentiment Analysis Using n-gram Approach -- 17.1 Introduction. 327 $a17.2 Sentiment Lexicons -- 17.2.1 Vader -- 17.2.2 TextBlob -- 17.2.3 Afinn -- 17.2.4 SentiWordNet -- 17.3 Proposed Framework -- 17.3.1 Pre-processing Step -- 17.3.2 N-gram Extraction -- 17.3.3 Feature Space Construction -- 17.4 Experimental Results -- 17.5 Conclusion -- References -- 18 A Comparison of Word Embedding Models for Turkish -- 18.1 Introduction -- 18.2 Data and Data Preprocessing Steps -- 18.3 Method -- 18.3.1 Embedding Models -- 18.3.2 Classification Model -- 18.4 Experiments -- 18.5 Conclusion -- References -- 19 The Unfairness of Collaborative Filtering Algorithms' Bias Towards Blockbuster Items -- 19.1 Introduction -- 19.2 Related Works -- 19.3 Description of Blockbuster Items -- 19.4 Blockbuster Bias in User Profiles -- 19.4.1 The Propensities of Users for Blockbuster Items -- 19.4.2 Profile Size and Blockbuster Bias -- 19.5 Different User Groups in Terms of Inclination for Blockbuster -- 19.6 Algorithmic Propagation of Blockbuster Bias -- 19.6.1 Blockbuster Bias in Recommendations for Different User Groups -- 19.7 Conclusion and Future Work -- References -- 20 Improved Gradient-Based Optimizer with Dynamic Fitness Distance Balance for Global Optimization Problems -- 20.1 Introduction -- 20.2 Related Works -- 20.2.1 GBO -- 20.2.2 Dynamic Fitness-Distance Balance (dFDB) -- 20.2.3 Improved GBO with Dynamic Fitness Distance Balance -- 20.3 Experimental Study -- 20.3.1 Settings -- 20.3.2 Benchmark Problems -- 20.3.3 Constrained Engineering Design Problems -- 20.4 Analyze Results -- 20.4.1 Statistical Analysis Results -- 20.4.2 Convergence Analysis Results -- 20.4.3 Results for Engineering Design Problems -- 20.5 Conclusions and Future Work -- References -- 21 TR-SUM: An Automatic Text Summarization Tool for Turkish -- 21.1 Introduction -- 21.2 Literature Review -- 21.2.1 Related Studies in Turkish -- 21.2.2 Datasets in Turkish. 327 $a21.3 TR-SUM: A Text Summarization Tool for Turkish -- 21.3.1 General Overview of "TR-SUM: A Text Summarization Tool for Turkish" -- 21.3.2 TR-NEWS-SUM Dataset -- 21.3.3 Data Pre-processing -- 21.3.4 The Proposed Neural Network Models for Turkish Text Summarization -- 21.4 Discussion and Results -- 21.5 Conclusion and Future Work -- References -- 22 Automatic and Semi-automatic Bladder Volume Detection in Ultrasound Images -- 22.1 Introduction -- 22.2 Related Works -- 22.3 Method and Material -- 22.3.1 Data Set -- 22.3.2 Method -- 22.4 Discussion and Results -- 22.5 Conclusions and Future Work -- References -- 23 Effects of Variable UAV Speed on Optimization of Travelling Salesman Problem with Drone (TSP-D) -- 23.1 Introduction -- 23.2 Problem Definition -- 23.3 Methodology -- 23.3.1 Truck-Drone Algorithm Approach -- 23.4 Experimental Studies -- 23.4.1 Settings -- 23.4.2 Experimental Studies and Results -- 23.5 Discussions and Conclusion -- References -- 24 Improved Phasor Particle Swarm Optimization with Fitness Distance Balance for Optimal Power Flow Problem of Hybrid AC/DC Power Grids -- 24.1 Introduction -- 24.2 Mathematical Formulation of Optimal Power Flow Problem of Hybrid AC/DC Power Grids -- 24.2.1 State and Control Variables -- 24.2.2 Constraints -- 24.2.3 Objective Functions -- 24.3 Method -- 24.3.1 Fitness-Distance Balance Method -- 24.3.2 Overview of Phasor Particle Swarm Optimization (PPSO) Algorithm -- 24.3.3 Proposed FDBPPSO Algorithm -- 24.4 Experimental Settings -- 24.5 Results and Analysis -- 24.5.1 Determining the Best FDBPPSO Variant on CEC 2020 Test Suite -- 24.5.2 Application of the Proposed FDBPPSO Method for Optimal Power Flow Problem of Hybrid AC/DC Power Grids -- 24.6 Conclusions -- References. 327 $a25 Development of an FDB-Based Chimp Optimization Algorithm for Global Optimization and Determination of the Power System Stabilizer Parameters. 330 $aThis book brings together the most recent, quality research papers accepted and presented in the 3rd International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2021) held in Antalya, Turkey between 1-3 October 2021. Objective of the content is to provide important and innovative research for developments-improvements within different engineering fields, which are highly interested in using artificial intelligence and applied mathematics. As a collection of the outputs from the ICAIAME 2021, the book is specifically considering research outcomes including advanced use of machine learning and careful problem designs on human-centred aspects. In this context, it aims to provide recent applications for real-world improvements making life easier and more sustainable for especially humans. The book targets the researchers, degree students, and practitioners from both academia and the industry. 410 0$aEngineering Cyber-Physical Systems and Critical Infrastructures,$x2731-5010 ;$v1 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aEngineering$xData processing 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aData Engineering 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aEngineering$xData processing. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aData Engineering. 676 $a016.403 676 $a006.3 700 $aHemanth$b D. Jude$01208278 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910637709903321 996 $aSmart applications with advanced machine learning and human-centred problem design$93089413 997 $aUNINA