{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":2,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":46,"n_cols":5,"rows_kept":46,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[11,2,11,3],[12,2,12,3],[12,4,12,5],[13,2,13,3],[13,4,13,5],[14,2,14,3],[15,2,15,3],[16,2,16,3],[17,2,17,3],[18,2,18,3],[19,2,19,3],[20,2,20,3],[32,2,32,3],[33,2,33,3],[36,2,36,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910770701403321"]
[null,null,"Autore",null,"D'Angelo, Paolo <1956- >"]
[null,null,"Titolo",null,"Benedetto Croce : la biografia / Paolo D'Angelo"]
[null,null,"Pubbl/distr/stampa",null,"Bologna, : Il mulino, 2023"]
[null,null,"ISBN",null,"978-88-15-38298-6"]
[null,null,"Descrizione fisica",null,"484 p., [8] carte di tav. : ill. ; 22 cm"]
[null,null,"Locazione",null,"FLFBC"]
[null,null,"Collocazione",null,"192.22 CROB/S 137"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"1.: Gli anni 1866-1918"]
[null,"2.","Record Nr.",null,"UNINA9910483790903321"]
[null,null,"Titolo",null,"Neural Information Processing : 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part IV / / edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, Derong Liu"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016"]
[null,null,"ISBN",null,"3-319-46681-X"]
[null,null,"Edizione",null,"[1st ed. 2016.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XIX, 663 p. 254 illus.)"]
[null,null,"Collana",null,"Theoretical Computer Science and General Issues, , 2512-2029 ; ; 9950"]
[null,null,"Disciplina",null,"006.32"]
[null,null,"Soggetti",null,"Pattern recognition systems"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computer science"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Automated Pattern Recognition"]
[{"$nulls":4},"Computer Vision"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Theory of Computation"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Part IV -- Applications -- Classifying Human Activities with Temporal Extension of Random Forest -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Motivation and Justification -- 3 Temporal Extension of Random Forest -- 3.1 Preliminary -- 3.2 Temporal Sampling Mechanism -- 3.3 Temporal Randomization -- 4 Experimental Evaluation -- 4.1 Data Sets and Experimental Setup -- 4.2 Experimental Results -- 4.3 Performance Comparison -- 5 Conclusion -- References -- Echo State Network Ensemble for Human Motion Data Temporal Phasing: A Case Study on Tennis Forehands -- Abstract -- 1 Introduction -- 1.1 Related Work and Prior Studies -- 1.2 Temporal Phasing Analysis: Sport Science "]
[{"$nulls":4},"and Tennis Backgrounds -- 2 Experimental Setup: Data Collection and Visualisation of Temporal Phasing for Supervised Machine Learning -- 3 Data Analysis and Modelling -- 4 Classification Results and Discussion -- 5 Conclusions, Recommendations and Future Work -- Acknowledgements -- References -- Unregistered Bosniak Classification with Multi-phase Convolutional Neural Networks -- 1 Introduction -- 2 Bosniak Classification Problem -- 3 Algorithm -- 3.1 Data Acquisition -- 3.2 Data Augmentation -- 3.3 Multi-phase Convolutional Neural Network -- 4 Experiment -- 4.1 Single Convolutional Networks -- 4.2 Multi-phase Convolutional Networks -- 4.3 Implementation Details -- 5 Conclusion -- References -- Direct Estimation of Wrist Joint Angular Velocities from Surface EMGs by Using an SDNN Function Approximator -- 1 Introduction -- 2 Selective Desensitization Neural Network -- 3 Proposed Method -- 3.1 Surface EMG Acquisition -- 3.2 Signal Preprocessing -- 3.3 Function Approximation -- 4 Experiment -- 4.1 Method -- 4.2 Results -- 5 Conclusion -- References -- Data Analysis of Correlation Between Project Popularity and Code Change Frequency."]
[{"$nulls":4},"1 Introduction -- 2 Related Work -- 3 Research Method -- 4 Results and Analysis -- 5 Conclusion -- References -- Hidden Space Neighbourhood Component Analysis for Cancer Classification -- 1 Introduction -- 2 Hidden Space Neighbourhood Components Analysis -- 2.1 Algorithm Description -- 2.2 Hidden Function -- 3 Experiments -- 3.1 Datasets -- 3.2 Experimental Setting and Results -- 4 Conclusions -- References -- Prediction of Bank Telemarketing with Co-training of Mixture-of-Experts and MLP -- Abstract -- 1 Introduction -- 2 Related Works -- 2.1 Co-training -- 2.2 Mixture-of-Experts -- 2.3 Credit Scoring Using Machine Learning -- 3 Global-Local Co-training for Prediction -- 3.1 Global-Local Co-training Algorithm -- 3.2 Measuring Confidence Degree -- 4 Experiments -- 4.1 Bank Telemarketing Data -- 4.2 Experimental Results -- 5 Conclusion -- References -- Prioritising Security Tests on Large-Scale and Distributed Software Development Projects by Using Self-organised Maps -- 1 Introduction -- 2 Theoretical Background -- 2.1 Cyclomatic Complexity -- 2.2 Self-organising Maps -- 3 Contribution -- 4 Experiments -- 5 Conclusion -- References -- Android Malware Detection Method Based on Function Call Graphs -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Extraction of Structural Features of Android Apps -- 4 Malicious Code Detection Model -- 5 Experiments -- 5.1 Data Set Description -- 5.2 Experimental Results -- 6 Conclusion -- Acknowledgment -- References -- Proposal of Singular-Unit Restoration by Focusing on the Spatial Continuity of Topographical Statistics in Spectral Domain -- 1 Introduction -- 2 SU Restoration by Using Compex-Valued Neural Network -- 2.1 Principle of the Proposed Filter -- 2.2 Layered Complex-Valued Neural Network -- 3 Experimental Results -- 4 Conclusion -- References."]
[{"$nulls":4},"Inferring Users' Gender from Interests: A Tag Embedding Approach -- 1 Introduction -- 2 Related Work -- 2.1 Feature Set -- 2.2 Classification Method -- 3 A Conceptual Class Based Method -- 3.1 Building Initial Conceptual Classes -- 3.2 Expanding Conceptual Classes -- 3.3 Condensing Tag Space -- 4 Experimental Evaluation -- 4.1 Baselines -- 4.2 Effects of Parameters k and K -- 4.3 Effects of Three Expansion Strategies -- 4.4 Comparison with Baselines -- 5 Conclusion and Discussions -- References -- Fast Color Quantization via Fuzzy Clustering -- 1 Introduction -- 2 Employed Clustering Algorithms -- 3 Results and Discussion -- 4 Conclusions -- References -- Extended Dependency-Based Word Embeddings for Aspect Extraction -- 1 Introduction -- 2 Extending Dependency-Based Word Embeddings -- "]
[{"$nulls":4},"2.1 Dependency-Based Word Embeddings -- 2.2 Extending Word Embeddings -- 2.3 Recurrent Neural Network Sequence Labeller -- 3 Experiment Settings -- 3.1 Data Set and Metric -- 3.2 Included Features -- 3.3 Word Embeddings -- 3.4 Training Parameters -- 3.5 Baselines -- 4 Results and Discussion -- 4.1 Comparison with Baselines -- 4.2 Comparison of Embeddings -- 4.3 Other Discussion -- 5 Conclusions -- References -- Topological Order Discovery via Deep Knowledge Tracing -- 1 Introduction -- 2 Related Work -- 3 Topological Order Discovery Model -- 3.1 Deep Knowledge Tracing Model -- 3.2 Topological Order Discovery -- 4 Experiments -- 4.1 Datasets -- 4.2 DKT Model Results -- 4.3 Topological Order Discovery Result -- 5 Future Work -- References -- PTR: Phrase-Based Topical Ranking for Automatic Keyphrase Extraction in Scientific Publications -- 1 Introduction -- 2 Methodology -- 2.1 Pre-processing -- 2.2 Topic Model Construction -- 2.3 Phrase-Based Topical Weighted-PageRank -- 2.4 Keyphrase Selection -- 3 Experiments -- 3.1 Datasets -- 3.2 Evaluation."]
[{"$nulls":4},"3.3 Influences of Parameters to PTR -- 3.4 Results of Comparing with Baseline Methods -- 4 Conclusion -- References -- Neural Network Based Association Rule Mining from Uncertain Data -- 1 Introduction -- 2 Association Rule Mining in Uncertain Data -- 3 Association Rule Mining on SOM Clusters -- 4 Experimentation and Analysis -- 5 Conclusion and Future Work -- References -- Analysis and Knowledge Discovery by Means of Self-Organizing Maps for Gaia Data Releases -- 1 Introduction -- 2 Self-Organizing Maps -- 3 Classification Tool -- 4 Features -- 5 Conclusion -- References -- Computational and Cognitive Neurosciences -- The Impact of Adaptive Regularization of the Demand Predictor on a Multistage Supply Chain Simulation -- 1 Introduction -- 2 Bullwhip Effect and Inventory Simulation -- 3 Appling Adaptive Regularization Models to Inventory Simulation -- 3.1 Demand Prediction Model in Inventory Simulation -- 3.2 Demand Prediction Using Adaptive Regularization of Weight Vectors -- 4 Experimental -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 4.3 Discussion -- 5 Conclusion -- References -- The Effect of Reward Information on Perceptual Decision-Making -- Abstract -- 1 Introduction -- 2 Materials and Methods -- 2.1 Participants -- 2.2 Stimuli -- 2.3 Experimental Design -- 2.4 Experimental Procedure -- 3 Analysis -- 4 Results -- 4.1 Post Reward Components -- 4.2 Post Stimulus Components -- 4.3 Early and Late Components -- 5 Discussion -- References -- Doubting What to Eat: A Computational Model for Food Choice Using Different Valuing Perspectives -- Abstract -- 1 Introduction -- 2 Background -- 3 The Computational Model -- 4 Simulation Results -- 5 Conclusion -- References -- A Novel Graph Regularized Sparse Linear Discriminant Analysis Model for EEG Emotion Recognition -- 1 Introduction -- 2 GraphSLDA Model -- 2.1 From LDA to LSR."]
[{"$nulls":4},"2.2 GraphSLDA -- 2.3 Optimization -- 2.4 Testing -- 3 Experiments -- 4 Conclusion -- References -- Information Maximization in a Feedforward Network Replicates the Stimulus Preference of the Medial Geniculate and the Auditory Cortex -- 1 Introduction -- 2 Model -- 3 Results -- 3.1 First-Output-Layer Neurons -- 3.2 Second-Output-Layer Neurons -- 4 Discussion -- References -- A Simple Visual Model Accounts for Drift Illusion and Reveals Illusory Patterns -- Abstract -- 1 Introduction -- 2 Reproduce Rotational Illusion Dependent on Background Luminance -- 2.1 Computational Model: Modified Lucas-Kanade Method [4] -- 2.2 Numerical Simulation: Rotational Directions and the Rotational Strength -- 2.3 Discussion -- 3 Model Predictions and Psychological Experiments -- 3.1 Circular Stimulus -- 3.2 Selection "]
[{"$nulls":4},"of Stimuli for Psychological Experiment -- 3.3 Methods -- 3.4 Correlation Between Model Estimation and Psychological Experiment -- 4 Conclusions -- Acknowledgements -- References -- An Internal Model of the Human Hand Affects Recognition of Graspable Tools -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussion -- References -- Perceptual Representation of Material Quality: Adaptation to BRDF-Morphing Images -- Abstract -- 1 Introduction -- 2 Methods -- 2.1 Procedure -- 2.2 Stimuli -- 2.2.1 Selection of BRDF -- 2.2.2 Morphing BRDF -- 3 Expectation -- 4 Results -- 5 Conclusions and Discussion -- Acknowledgements -- References -- GPU-Accelerated Simulations of an Electric Stimulus and Neural Activities in Electrolocation -- 1 Introduction -- 2 Electrolocation -- 3 Methods -- 3.1 Models -- 3.2 Implementation -- 4 Results -- 5 Conclusion -- References -- Analysis of Similarity and Differences in Brain Activities Between Perception and Production of Facial Expressions Using EEG Data and the NeuCube Spiking Neural Network Architecture -- 1 Introduction."]
[{"$nulls":4},"2 The NeuCube Spiking Neural Network Architecture."]
[null,null,null,"Sommario/riassunto","The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms."]