LEADER 01081nam0-22003131i-450- 001 990002053560403321 005 20090326151109.0 035 $a000205356 035 $aFED01000205356 035 $a(Aleph)000205356FED01 035 $a000205356 100 $a20030910d1978----km-y0itay50------ba 101 0 $afre 200 1 $aDonnees utiles au selectionneur pour ameliorer la resistance des Luzernes a l' egard des maladies et ravageurs$fsous ladirection M. Massenot 210 $aVersailles$cInra$d1978 215 $a59 p.$d22 cm 225 1 $aInra - Etude$v64 610 0 $aLotta Biologica e Integrata 610 0 $aPiante Resistenti 676 $a631.53 702 1$aMassenot,$bM. 710 02$aInstitut national de la recherche agronomique$c$0359881 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990002053560403321 952 $a61 VII B.8/113$b6997 (19/05/1998)$fDAGEN 959 $aDAGEN 996 $aDonnees utiles au selectionneur pour ameliorer la resistance des Luzernes a l' egard des maladies et ravageurs$9406000 997 $aUNINA LEADER 00848nam0-22002771i-450- 001 990002564060403321 035 $a000256406 035 $aFED01000256406 035 $a(Aleph)000256406FED01 035 $a000256406 100 $a20000920d1964----km-y0itay50------ba 101 0 $aENG 200 1 $a<>correlation study of methods of matrix structural analysis$fRichard H. Gallagher. 210 $aOxford$cPergamon Press$d1964. 215 $axi, 113 p.$d24 cm 610 0 $aMetodi matematici, Metodi matematici per la fisica 676 $a530 700 1$aGallagher,$bRichard H.$013872 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990002564060403321 952 $aMXV-A-86$b030658$fMAS 959 $aMAS 996 $aCORRELATION STUDY OF METHODS OF MATRIX STRUCTURAL ANALYSIS$9318629 997 $aUNINA DB $aING01 LEADER 02723oam 2200637I 450 001 9910451738103321 005 20210827225151.0 010 $a1-317-48824-5 010 $a1-315-71020-X 010 $a1-280-12013-4 010 $a9786613524027 010 $a1-84465-483-4 024 7 $a10.4324/9781315710204 035 $a(CKB)2550000000097362 035 $a(EBL)1886890 035 $a(SSID)ssj0000668303 035 $a(PQKBManifestationID)12271711 035 $a(PQKBTitleCode)TC0000668303 035 $a(PQKBWorkID)10697918 035 $a(PQKB)10842310 035 $a(MiAaPQ)EBC1886890 035 $a(OCoLC)958110010 035 $a(EXLCZ)992550000000097362 100 $a20180706e20142010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe solitary self $eDarwin and the selfish gene /$fMary Midgley 210 1$aLondon ;$aNew York :$cRoutledge,$d2014. 215 $a1 online resource (161 p.) 225 1 $aHeretics 300 $aFirst published 2010 by Acumen. 311 $a1-138-16929-3 311 $a1-84465-253-X 320 $aIncludes bibliographical references (pages 145-147) and index. 327 $aCover; Half Title; Title Page; Copyright Page; Table of Contents; Introduction; 1. Pseudo-Darwinism and social atomism; 2. The background: egoism from Hobbes to R. D. Laing; 3. The natural springs of morality; 4. Coming to terms with reason; 5. Darwin's new broom; 6. The self's strange adventures; Conclusion: the wider perspective; Bibliography; Index 330 $aRenowned philosopher Mary Midgley explores the nature of our moral constitution to challenge the view that reduces human motivation to self-interest. Midgley argues cogently and convincingly that simple, one-sided accounts of human motives, such as the 'selfish gene' tendency in recent neo-Darwinian thought, may be illuminating but are always unrealistic. Such neatness, she shows, cannot be imposed on human psychology. She returns to Darwin's original writings to show how the reductive individualism which is now presented as Darwinism does not derive from Darwin but from a wider, Hobbesian tra 410 0$aHeretics (Durham, England) 606 $aPhilosophy$2HILCC 606 $aPhilosophy & Religion$2HILCC 606 $aEthics$2HILCC 608 $aElectronic books. 615 7$aPhilosophy 615 7$aPhilosophy & Religion 615 7$aEthics 676 $a231.7652 700 $aMidgley$b Mary$f1919-2018,$0850195 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910451738103321 996 $aThe solitary self$92064951 997 $aUNINA LEADER 12615nam 22007935 450 001 9910760282603321 005 20251113174709.0 010 $a9789819975907 010 $a9819975905 024 7 $a10.1007/978-981-99-7590-7 035 $a(MiAaPQ)EBC30832466 035 $a(Au-PeEL)EBL30832466 035 $a(DE-He213)978-981-99-7590-7 035 $a(PPN)272915254 035 $a(CKB)28572700500041 035 $a(OCoLC)1407316041 035 $a(EXLCZ)9928572700500041 100 $a20231029d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Computational Intelligence and Intelligent Informatics $e8th International Workshop, IWACIII 2023, Beijing, China, November 3?5, 2023, Proceedings, Part I /$fedited by Bin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (375 pages) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v1931 311 08$aPrint version: Xin, Bin Advanced Computational Intelligence and Intelligent Informatics Singapore : Springer,c2023 9789819975891 327 $aIntro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Intelligent Information Processing -- 3D Point Cloud-Based Lithium Battery Surface Defects Detection Using Region Growing Proposal Approach -- 1 Introduction -- 2 Previous Work -- 3 Methodology -- 3.1 Data Acquisition and Preprocessing -- 3.2 Normals Estimation and Segmentation -- 4 Experiments and Discussion -- 5 Conclusion and Future Work -- References -- Reducing Communication Consumption in Collaborative Visual SLAM with Map Point Selection and Efficient Data Compression -- 1 Introduction -- 2 Proposed Method -- 2.1 Mappoints Culling Strategy -- 2.2 Zstd Compression Algorithm -- 3 Experimental Results -- 3.1 Implementation Details -- 3.2 Evaluation Metric -- 3.3 Performance Evaluation -- 4 Conclusion -- References -- Optimal Information Fusion Descriptor Fractional Order Kalman Filter -- 1 Introduction -- 2 Problem Formulation -- 3 Kalman Filter for Single Sensor Generalized Fractional Order System -- 4 Observational Fusion Kalman Filter for Generalized Fractional-Order Systems -- 5 Simulation Study -- 6 Conclusions -- References -- Multi-sensor Data Fusion Algorithm for Indoor Fire Detection Based on Ensemble Learning -- 1 Introduction -- 2 Data Selection and Analysis -- 2.1 Data Seletion -- 2.2 Data Processing and Analysis -- 3 Algorithm Analysis and Evaluation -- 3.1 Architechture of Algorithm -- 3.2 Research Methodology -- 3.3 Evaluation Index -- 3.4 Experimental Results -- 4 Conclusion -- References -- Research on Water Surface Environment Perception Method Based on Visual and Positional Information Fusion -- 1 Introduction -- 2 Swan-Net -- 2.1 Feature Extraction Module -- 2.2 Position Information Feature Encoding -- 2.3 Feature Fusion Module -- 2.4 Loss Function -- 3 Experimental Methods and Analysis of Results -- 3.1 Training Dataset. 327 $a3.2 Model Structure Ablation Experiment -- 3.3 Performance Comparison of Different Models -- 4 Conclusion -- References -- Novel Fault Diagnosis Method Integrating D-L2-FDA and AdaBoost -- 1 Introduction -- 2 Related Methods -- 2.1 Fisher Discriminant Analysis -- 2.2 Ensemble Learning Method AdaBoost -- 3 The Proposed Method -- 3.1 D-L2-FDA for Feature Extraction -- 3.2 AdaBoost for Fault Diagnosis -- 4 Cases Study -- 4.1 Tennessee Eastman Process -- 4.2 Faults Selection -- 4.3 Confusion Matrix -- 4.4 Comparison with Other Methods -- 5 Conclusions -- References -- Structural Health Monitoring of Similar Gantry Crane Based on Federated Learning Algorithm -- 1 Introduction -- 2 Monitoring Model and Fault Simulation -- 2.1 Monitoring Model and Damage Detection -- 2.2 Wireless Edge Gateway Data Acquisition System -- 2.3 Design and Measurement of Load Excitation -- 3 Federated Learning Algorithm for Fault Identification of Gantry Crane -- 3.1 Algorithm Overview -- 3.2 Unsupervised Neural Network USAD Algorithm -- 3.3 FedAvg -- 3.4 XGBoost -- 4 Experiment -- 4.1 Federated Learning Based Anomaly Detection -- 4.2 Abnormal Classification of Gantry Cranes -- 5 Conclusion -- References -- Accelerated Lifetime Experiment of Maximum Current Ratio Based on Charge and Discharge Capacity Confinement -- 1 Introduction -- 2 Principle of Maximum Current Rate Acceleration Life Experiment -- 3 Constant Current Rate Acceleration -- 4 Variable Current Rate Acceleration -- 4.1 Fixed Time Length Segmentation Acceleration -- 4.2 The Granularity D is Optimized by the Charge Throughput Constraint -- 5 Conclusion -- References -- Adaptive Design of Uni-Variate Alarm Systems Based on Statistical Distance Measures -- 1 Introduction -- 2 Problem Formulation -- 2.1 Detecting Alarm States -- 2.2 Abrupt Faults -- 3 Safe Designed Alarm System -- 4 Statistical Difference Values. 327 $a5 Simulated Example -- 6 Conclusion -- References -- Correlation Analysis Between Insomnia Severity and Depressive Symptoms of College Students Based on Pseudo-Siamese Network -- 1 Introduction -- 2 Methodology -- 2.1 Data -- 2.2 Evaluation Methodology -- 2.3 Statistical Analysis of Correlation Model Based on Pseudo-Siamese Network -- 2.4 Data Processing -- 2.5 Correlation Model Establishment and Test Plan -- 3 Results -- 3.1 General Demographic Characteristics -- 3.2 Mediation Effect Analysis -- 3.3 Physical Activity Impact -- 4 Discussion -- References -- Construction and Research of Pediatric Pulmonary Disease Diagnosis and Treatment Experience Knowledge Graph Based on Professor Wang Lie's Experience -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Sources -- 2.2 Inclusion Criteria -- 2.3 Exclusion Criteria -- 2.4 Standardized Processing of Data -- 2.5 Knowledge Extraction -- 2.6 Knowledge Graph Construction Method -- 3 Results -- 3.1 Pattern Layer Graph -- 3.2 Data Layer Graph -- 4 Application of Professor Wang's Knowledge Graph for the Diagnosis and Treatment of Pediatric Pulmonary Diseases -- 5 Conclusion -- References -- A Novel SEIAISRD Model to Evaluate Pandemic Spreading -- 1 Introduction -- 2 Methods -- 2.1 The SEIAISRD Model -- 2.2 Estimating the Effective Reproduction Number -- 2.3 Data-Fitting and Sensitivity Analysis -- 3 Results -- 3.1 Model Formulation and Validation -- 3.2 Case Studies for the Representative Countries -- 4 Conclusion -- References -- Keyword-based Research Field Discovery with External Knowledge Aware Hierarchical Co-clustering -- 1 Introduction -- 2 Background -- 2.1 Co-clustering -- 2.2 HICCAM -- 3 Method -- 3.1 Dataset Preparation -- 3.2 Auxiliary Knowledge Preparation -- 3.3 Clustering -- 3.4 Parameter Tuning -- 4 Results and Discussion -- 4.1 Parameter Study -- 4.2 Case Study -- 5 Conclusion. 327 $aReferences -- An End-to-End Intent Recognition Method for Combat Drone Swarm -- 1 Introduction -- 2 Related Work -- 3 General Framework of the End-to-End Intent Recognition Method -- 3.1 Problem Definition -- 3.2 Model Architecture -- 3.3 Mapping Method -- 3.4 Feature Extraction Module -- 3.5 Intent Prediction Module -- 4 Experiments -- 4.1 Data and Environment -- 4.2 Evaluation Metric -- 4.3 Baseline -- 4.4 Result -- 5 Conclusion -- References -- An Attention Detection System Based on Gaze Estimation Using Self-supervised Learning -- 1 Introduction -- 2 Framework of Gaze Estimation -- 2.1 Contrastive Learning Pre-training -- 2.2 Gaze Estimation -- 3 Attention Detection System -- 4 Experiments -- 5 Conclusion -- References -- Effects of Pseudo Labels in Pose Estimation Models Using Semi-supervised Learning -- 1 Introduction -- 2 Related Works -- 2.1 Semi-supervised Learning -- 3 Proposal Learning Procedure -- 4 Experiments -- 4.1 Dataset -- 4.2 Parameter Setup -- 4.3 Epochs Normalization -- 4.4 Evaluation -- 5 Experimental Results and Discussions -- 6 Conclusions and Future Works -- References -- Sequential Masking Imitation Learning for Handling Causal Confusion in Autonomous Driving -- 1 Introduction -- 2 Related Work -- 2.1 Pipelines of Autonomous Driving -- 2.2 Confusion in Imitation -- 3 SEMI Methodology -- 3.1 Semantic Encoder -- 3.2 Masking Semantic Objects in Sequential Setting -- 3.3 Behavior Cloning with Imbalanced Dataset -- 4 Experiment -- 4.1 Network Structure -- 4.2 Simulation Environment and Data Collection -- 4.3 Contrast Experiment -- 5 Results -- 5.1 Evaluation Procedure -- 5.2 Discussion -- 5.3 Analysis -- 6 Conclusion -- References -- Proposal of Timestamp-Based Dynamic Context Features for Music Recommendation -- 1 Introduction -- 2 Related Work -- 2.1 Music Recommender System -- 2.2 Context-Aware Music Recommender System. 327 $a3 Proposed Method -- 3.1 Dynamic Context Features -- 3.2 Recommendation System -- 4 Experiments -- 4.1 Outline -- 4.2 Results -- 5 Conclusion -- References -- Method to Control Embedded Representation of Piece of Music in Playlists -- 1 Introduction -- 1.1 Notations -- 2 Related Work -- 2.1 Distributed Representation -- 2.2 Music Recommendation -- 3 Proposed Method and Investigation -- 3.1 Investigation on Embeddings -- 3.2 Proposed Method to Reduce Bias -- 4 Conclusion -- References -- Design and Implementation of ANFIS on FPGA and Verification with Class Classification Problem -- 1 Introduction -- 2 Applying AFIS to the Iris Classification -- 3 Hardware Program Design for 16bit ANFIS -- 4 Results and Comparison -- 5 Conclusions and Future Work -- References -- Intelligent Optimization and Decision-Making -- Beacon Localization Method Based on Flower Pollination-Fireworks Algorithm -- 1 Introduction -- 1.1 Wireless Sensor Positioning Technology -- 1.2 Main Research Content -- 2 Beacon Positioning Model -- 2.1 UWB Beacon -- 2.2 Basic Principles of Beacon Positioning -- 2.3 Factors Affecting Beacon Positioning -- 3 RSSI Localization Algorithm Based on Flower Pollination-Fireworks Algorithm -- 3.1 RSSI Localization Algorithm -- 3.2 Fireworks Algorithm -- 3.3 Improved Fireworks Algorithm Based on Flower Pollination -- 3.4 The Algorithm Flow of FP-FWA -- 4 Simulation Experiments and Results Analysis -- 4.1 Preparations Before the Algorithm Experiments -- 4.2 Localization Algorithm Experiment -- 5 Conclusion -- References -- Parameter Identification for Fictitious Play Algorithm in Repeated Games -- 1 Introduction -- 2 Problem Formulation -- 3 The Identification for Parameters in the FP Algorithm -- 3.1 The Identification Algorithm for Assessment Parameter K -- 3.2 The Identification for Irrational 21 -- 4 Conclusions and Future Work -- References. 327 $aAn Improved Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization. 330 $aThis two-volume set constitutes the refereed proceedings of the 8th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2023, held in Beijing, China, in November 2023. The 56 papers presented were thoroughly reviewed and selected from the 118 qualifies submissions. They are organized in the topical sections on intelligent information processing; intelligent optimization and decision-making; pattern recognition and computer vision; advanced control; multi-agent systems; robotics. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v1931 606 $aArtificial intelligence 606 $aComputer vision 606 $aRobotics 606 $aMachine learning 606 $aPattern recognition systems 606 $aArtificial Intelligence 606 $aComputer Vision 606 $aRobotics 606 $aMachine Learning 606 $aAutomated Pattern Recognition 615 0$aArtificial intelligence. 615 0$aComputer vision. 615 0$aRobotics. 615 0$aMachine learning. 615 0$aPattern recognition systems. 615 14$aArtificial Intelligence. 615 24$aComputer Vision. 615 24$aRobotics. 615 24$aMachine Learning. 615 24$aAutomated Pattern Recognition. 676 $a006.3 700 $aXin$b Bin$01437759 701 $aKubota$b Naoyuki$01437760 701 $aChen$b Kewei$0652031 701 $aDong$b Fangyan$01437761 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910760282603321 996 $aAdvanced Computational Intelligence and Intelligent Informatics$93598642 997 $aUNINA