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[null,"1.","Record Nr.",null,"UNINA9910460376503321"]
[null,null,"Autore",null,"Barnett Paul"]
[null,null,"Titolo",null,"Shopper marketing : a how-to business story / / Paul Barnett"]
[null,null,"Pubbl/distr/stampa",null,"New York, New York (222 East 46th Street, New York, NY 10017) : , : Business Expert Press, , 2016"]
[null,null,"ISBN",null,"1-63157-358-6"]
[null,null,"Edizione",null,"[First edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (xiv, 261 pages) : illustrations"]
[null,null,"Collana",null,"Consumer behavior collection, , 2163-937X"]
[null,null,"Disciplina",null,"658.8"]
[null,null,"Soggetti",null,"Marketing"]
[{"$nulls":4},"Consumer behavior"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (pages 233-254) and index."]
[null,null,null,"Sommario/riassunto","The book outlines a practical approach to shopper marketing in order to grow both revenue and brand equity. A story runs through the book in the first part of each chapter, so that it is easier to connect the theory and tools in the second part of each chapter, with a real-world scenario. The book follows the story of the Big Beverage Company, who receive a call from their biggest customer one afternoon asking for their help in getting the coffee category growing again. This sets the Big Beverage Company and their management team on a journey from being a brand-focused business, to one that understands how a broader emphasis on the category and its shoppers can lead to greater growth for themselves and their retail partners. The book contains over 300 industry and academic references as well as numerous examples from the author's own experience."]
[null,"2.","Record Nr.",null,"UNINA9910760282603321"]
[null,null,"Autore",null,"Xin Bin"]
[null,null,"Titolo",null,"Advanced Computational Intelligence and Intelligent Informatics : 8th International Workshop, IWACIII 2023, Beijing, China, November 3–5, 2023, Proceedings, Part I / / edited by Bin Xin, Naoyuki Kubota, Kewei Chen, Fangyan Dong"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9789819975907"]
[{"$nulls":4},"9819975905"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (375 pages)"]
[null,null,"Collana",null,"Communications in Computer and Information Science, , 1865-0937 ; ; 1931"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Robotics"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Pattern recognition systems"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Vision"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Automated Pattern Recognition"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Intelligent Information Processing -- 3D Point Cloud-Based Lithium Battery Surface Defects Detection Using Region Growing Proposal Approach -- 1 Introduction -- 2 Previous Work -- 3 Methodology -- 3.1 Data Acquisition and Preprocessing -- 3.2 Normals Estimation and Segmentation -- 4 Experiments and Discussion -- 5 Conclusion and Future Work -- References -- Reducing Communication Consumption in Collaborative Visual SLAM with Map Point Selection and Efficient Data Compression -- 1 Introduction -- 2 Proposed Method -- 2.1 Mappoints Culling Strategy -- 2.2 Zstd Compression Algorithm -- 3 Experimental Results -- 3.1 Implementation Details -- 3.2 Evaluation Metric -- 3.3 Performance Evaluation -- 4 Conclusion -- References -- Optimal Information "]
[{"$nulls":4},"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."]
[{"$nulls":4},"3.2 Model Structure Ablation Experiment -- 3.3 Performance Comparison of Different Models -- 4 Conclusion -- References -- Novel Fault Diagnosis Method Integrating D-L2-FDA and AdaBoost -- 1 Introduction -- 2 Related Methods -- 2.1 Fisher Discriminant Analysis -- 2.2 Ensemble Learning Method AdaBoost -- 3 The Proposed Method -- 3.1 D-L2-FDA for Feature Extraction -- 3.2 AdaBoost for Fault Diagnosis -- 4 Cases Study -- 4.1 Tennessee Eastman Process -- 4.2 Faults Selection -- 4.3 Confusion Matrix -- 4.4 Comparison with Other Methods -- 5 Conclusions -- References -- Structural Health Monitoring of Similar Gantry Crane Based on Federated Learning Algorithm -- 1 Introduction -- 2 Monitoring Model and Fault Simulation -- 2.1 Monitoring Model and Damage Detection -- 2.2 Wireless Edge Gateway Data Acquisition System -- 2.3 Design and Measurement of Load Excitation -- 3 Federated Learning Algorithm for Fault Identification of Gantry Crane -- 3.1 Algorithm Overview -- 3.2 Unsupervised Neural Network USAD Algorithm -- 3.3 FedAvg -- 3.4 XGBoost -- 4 Experiment -- 4.1 Federated Learning Based Anomaly Detection -- 4.2 Abnormal Classification of Gantry Cranes -- 5 Conclusion -- References -- Accelerated Lifetime Experiment of Maximum Current Ratio Based on Charge and Discharge Capacity Confinement -- 1 Introduction -- 2 Principle of Maximum Current Rate Acceleration Life Experiment -- 3 Constant Current Rate Acceleration -- 4 Variable Current Rate Acceleration -- 4.1 Fixed Time Length Segmentation Acceleration -- 4.2 The Granularity D is Optimized by the Charge Throughput Constraint -- 5 Conclusion -- References -- Adaptive Design of Uni-Variate Alarm Systems Based on Statistical Distance Measures -- 1 Introduction -- 2 Problem Formulation -- 2.1 Detecting Alarm States -- 2.2 Abrupt Faults -- 3 Safe Designed Alarm System -- 4 Statistical Difference Values."]
[{"$nulls":4},"5 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 "]
[{"$nulls":4},"Processing of Data -- 2.5 Knowledge Extraction -- 2.6 Knowledge Graph Construction Method -- 3 Results -- 3.1 Pattern Layer Graph -- 3.2 Data Layer Graph -- 4 Application of Professor Wang's Knowledge Graph for the Diagnosis and Treatment of Pediatric Pulmonary Diseases -- 5 Conclusion -- References -- A Novel SEIAISRD Model to Evaluate Pandemic Spreading -- 1 Introduction -- 2 Methods -- 2.1 The SEIAISRD Model -- 2.2 Estimating the Effective Reproduction Number -- 2.3 Data-Fitting and Sensitivity Analysis -- 3 Results -- 3.1 Model Formulation and Validation -- 3.2 Case Studies for the Representative Countries -- 4 Conclusion -- References -- Keyword-based Research Field Discovery with External Knowledge Aware Hierarchical Co-clustering -- 1 Introduction -- 2 Background -- 2.1 Co-clustering -- 2.2 HICCAM -- 3 Method -- 3.1 Dataset Preparation -- 3.2 Auxiliary Knowledge Preparation -- 3.3 Clustering -- 3.4 Parameter Tuning -- 4 Results and Discussion -- 4.1 Parameter Study -- 4.2 Case Study -- 5 Conclusion."]
[{"$nulls":4},"References -- 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."]
[{"$nulls":4},"3 Proposed Method -- 3.1 Dynamic Context Features -- 3.2 Recommendation System -- 4 Experiments -- 4.1 Outline -- 4.2 Results -- 5 Conclusion -- References -- Method to Control Embedded Representation of Piece of Music in Playlists -- 1 Introduction -- 1.1 Notations -- 2 Related Work -- 2.1 Distributed Representation -- 2.2 Music Recommendation -- 3 Proposed Method and Investigation -- 3.1 Investigation on Embeddings -- 3.2 Proposed Method to Reduce Bias -- 4 Conclusion -- References -- Design and Implementation of ANFIS on FPGA and Verification with Class Classification Problem -- 1 Introduction -- 2 Applying AFIS to the Iris Classification -- 3 Hardware Program Design for 16bit ANFIS -- 4 Results and Comparison -- 5 Conclusions and Future Work -- References -- Intelligent Optimization "]
[{"$nulls":4},"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."]
[{"$nulls":4},"An Improved Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization."]
[null,null,null,"Sommario/riassunto","This 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."]