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[null,"1.","Record Nr.",null,"UNINA9910706895703321"]
[null,null,"Autore",null,"Bell Conor K."]
[null,null,"Titolo",null,"OpCost : an open-source system for estimating costs of stand-level forest operations / / Conor K. Bell, Robert F. Keefe, and Jeremy S. Fried"]
[null,null,"Pubbl/distr/stampa",null,"Portland, OR : , : U.S. Department of Agriculture, Pacific Northwest Research Station, , 2017"]
[null,null,"Descrizione fisica",null,"1 online resource (23 pages) : color illustrations"]
[null,null,"Collana",null,"General technical report PNW ; ; GTR-960"]
[null,null,"Soggetti",null,"Logging - Cost control - Computer programs"]
[{"$nulls":4},"Logging - Economic aspects - Simulation methods"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","\"October 2017.\""]
[{"$nulls":4},"\"2017 - 576-460 / 00633 Region No. 10.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (pages 20-[24])."]
[null,"2.","Record Nr.",null,"UNISA996546853603316"]
[null,null,"Titolo",null,"Knowledge Science, Engineering and Management [[electronic resource] ] : 16th International Conference, KSEM 2023, Guangzhou, China, August 16–18, 2023, Proceedings, Part I / / edited by Zhi Jin, Yuncheng Jiang, Robert Andrei Buchmann, Yaxin Bi, Ana-Maria Ghiran, Wenjun Ma"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"3-031-40283-9"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XXIV, 457 p. 124 illus., 108 illus. in color.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 14117"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Computers"]
[{"$nulls":4},"Social sciences - Data processing"]
[{"$nulls":4},"Computer science"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Engineering and Networks"]
[{"$nulls":4},"Computing Milieux"]
[{"$nulls":4},"Computer Application in Social and Behavioral Sciences"]
[{"$nulls":4},"Computer Science"]
[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,"Knowledge Science with Learning and AI -- Joint Feature Selection and Classifier Parameter Optimization: A Bio-inspired Approach -- Automatic Gaussian Bandwidth Selection for Kernel Principal Component Analysis -- Boosting LightWeight Depth Estimation Via Knowledge Distillation -- Graph Neural Network with Neighborhood Reconnection -- Critical Node Privacy Protection Based on Random Pruning of Critical Trees -- DSEAformer: Forecasting by De-stationary Autocorrelation with Edgebound -- Multitask-based Cluster Transmission for Few-Shot Text Classification -- Hyperplane Knowledge Graph Embedding with Path Neighborhoods and Mapping Properties -- RTAD-TP: Real- Time Anomaly Detection Algorithm for Univariate Time Series Data Based on Two- Parameter Estimation -- Multi-Sampling Item Response Ranking Neural Cognitive Diagnosis with "]
[{"$nulls":4},"Bilinear Feature Interaction -- A Sparse Matrix Optimization Method for Graph Neural Networks Training -- Dual-dimensional Refinement of Knowledge Graph Embedding Representation -- Contextual Information Augmented Few-Shot Relation Extraction -- Dynamic and Static Feature-aware Microservices Decomposition via Graph Neural Networks -- An Enhanced Fitness-distance Balance Slime Mould Algorithm and Its Application in Feature Selection -- Low Redundancy Learning for Unsupervised Multi-view Feature Selection -- Dynamic Feed-Forward LSTM -- Black-box Adversarial Attack on Graph Neural Networks Based on Node Domain Knowledge -- Role and Relationship-Aware Representation Learning for Complex Coupled Dynamic Heterogeneous Networks -- Twin Graph Attention Network with Evolution Pattern Learner for Few-Shot Temporal Knowledge Graph Completion -- Subspace Clustering with Feature Grouping for Categorical Data -- Learning Graph Neural Networks on Feature-Missing Graphs -- Dealing with Over-reliance on Background Graph for Few-shot Knowledge Graph Completion -- Kernel-based feature extraction for time series clustering -- Cluster Robust Inference for embedding-based Knowledge Graph Completion -- Community-enhanced Contrastive Siamese networks for Graph Representation Learning -- Distant Supervision Relation Extraction with Improved PCNN and Multi-level Attention -- Enhancing Adversarial Robustness via Anomaly-aware Adversarial Training -- An Improved Cross-Validated Adversarial Validation Method -- EACCNet: Enhanced Auto-Cross Correlation Network for Few-Shot Classification -- Joint Label-Structure Estimation from Multifaceted Graph Data -- Dual Channel Knowledge Graph Embedding with Ontology Guided Data Augmentation -- Multi-Dimensional Graph Rule Learner -- MixUNet: A Hybrid Retinal Vessels Segmentation Model Combining The Latest CNN and MLPs -- Robust Few-shot Graph Anomaly Detection via Graph Coarsening -- An Evaluation Metric for Prediction Stability with Imprecise Data -- Reducing The Teacher-Student Gap Via Elastic Student."]
[null,null,null,"Sommario/riassunto","This volume set constitutes the refereed proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, KSEM 2023, which was held in Guangzhou, China, during August 16–18, 2023. The 114 full papers and 30 short papers included in this book were carefully reviewed and selected from 395 submissions. They were organized in topical sections as follows: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management systems; and emerging technologies for knowledge science, engineering and management. ."]
[null,"3.","Record Nr.",null,"UNINA9910770262003321"]
[null,null,"Autore",null,"Ifrim Georgiana"]
[null,null,"Titolo",null,"Advanced Analytics and Learning on Temporal Data : 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers / / edited by Georgiana Ifrim, Romain Tavenard, Anthony Bagnall, Patrick Schaefer, Simon Malinowski, Thomas Guyet, Vincent Lemaire"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023"]
[null,null,"ISBN",null,"9783031498961"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (315 pages)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 14343"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[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,"Human Activity Segmentation Challenge -- Human Activity Segmentation Challenge@ECML/PKDD’23 -- Change points detection in multivariate signal applied to human activity segmentation -- Change Point Detection via Synthetic Signals -- Oral Presentation -- Clustering time series with k-medoids based algorithms -- Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting -- RED CoMETS: an ensemble classifier for symbolically represented multivariate time series -- Deep Long Term Prediction for Semantic Segmentation in Autonomous Driving -- Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression -- ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter Averaging -- Poster Presentation -- Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks -- Evaluating Explanation Methods for Multivariate Time Series Classification -- tGLAD: A sparse graph recovery based approach for multivariate time series segmentation -- Designing a New Search Space for Multivariate Time-Series Neural Architecture Search -- Back to Basics: A Sanity Check on Modern Time Series Classification Algorithms -- Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Behaviours and Detect Health Issues -- Exploiting Context and Attention with Recurrent Neural Network for Sensor Time Series Prediction -- Rail Crack Propagation Forecasting Using Multi-"]
[{"$nulls":4},"horizons RNNs -- Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies -- Time-aware Predictions of Moments of Change in Longitudinal User Posts on Social Media."]
[null,null,null,"Sommario/riassunto","This volume LNCS 14343 constitutes the refereed proceedings of the 8th ECML PKDD Workshop, AALTD 2023, in Turin, Italy, in September 2023. The 20 full papers were carefully reviewed and selected from 28 submissions. They are organized in the following topical section as follows: Machine Learning; Data Mining; Pattern Analysis; Statistics to Share their Challenges and Advances in Temporal Data Analysis. ."]