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[null,"1.","Record Nr.",null,"UNISA996464395203316"]
[null,null,"Titolo",null,"Advances in artificial intelligence : 15th conference of the Spanish Association for Artificial Intelligence, CAEPIA 2013 Madrid, Spain, September 17-20, 2013, proceedings / / edited by Enrique Alba [and nine others]"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-030-85713-1"]
[null,null,"Descrizione fisica",null,"1 online resource (280 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science ; ; v.12882"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Information storage and retrieval systems"]
[{"$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,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents -- Machine Learning -- Prediction of Epiretinal Membrane from Retinal Fundus Images Using Deep Learning -- 1 Introduction -- 2 Dataset -- 3 Training Procedures -- 4 Results and Discussion -- 5 Interpretability Considerations -- 6 Conclusions and Further Work -- References -- LabelDetection: Simplifying the Use and Construction of Deep Detection Models -- 1 Introduction -- 2 Background -- 2.1 Object Detection Libraries -- 2.2 Test-Time Augmentation -- 2.3 Data Distillation -- 3 LabelDetection -- 3.1 LabelDetection for Training Models -- 3.2 LabelDetection for Object Detection -- 4 Case Study -- 5 Conclusions and Further Work -- References -- A Proposal to Integrate Deep Q-Learning with Automated Planning to Improve the Performance of a Planning-Based Agent -- 1 Introduction -- 2 Background -- 3 The Planning and Acting Architecture -- 4 Goal Selection Learning -- 5 Experiments and Analysis of Results -- 6 Related Work -- 7 Conclusions and Future Work -- References -- ReLU-Based Activations: Analysis and Experimental Study for Deep Learning -- 1 Introduction -- 2 ReLU-Based Activation Functions -- 2.1 Leaky Rectified Linear Unit -- 2.2 Parametric Rectified Linear Unit -- 2.3 Elastic Rectified Linear Unit -- 2.4 Randomised Leaky Rectified Linear Unit -- 2.5 Sloped Rectified Linear Unit -- 2.6 Paired Rectified Linear Unit -- 2.7 Randomly Translational Rectified Linear Unit -- 3 Design of the Experiments -- "]
[{"$nulls":4},"3.1 Datasets -- 3.2 Model and Training Process -- 4 Results and Analysis -- 5 Conclusions -- References -- Studying the Effect of Different Lp Norms in the Context of Time Series Ordinal Classification -- 1 Introduction -- 2 Background -- 2.1 Time Series -- 2.2 Effect of the Lp Norm -- 3 Experimental Results and Discussion -- 3.1 Experimental Settings -- 3.2 Experimental Results -- 4 Conclusions."]
[{"$nulls":4},"References -- STree: A Single Multi-class Oblique Decision Tree Based on Support Vector Machines -- 1 Introduction -- 2 Related Work -- 3 Proposed Method: STree -- 4 Experimental Evaluation -- 4.1 Benchmark -- 4.2 Algorithms -- 4.3 Results and Analysis -- 5 Conclusion -- References -- Deep Reinforcement and Imitation Learning for Self-driving Tasks -- 1 Introduction -- 2 Background -- 3 Setup -- 3.1 Simulation and Sensors -- 3.2 Computer Vision System -- 3.3 Human Expert Demonstrations -- 3.4 AI Agents -- 4 Experiments -- 4.1 Experiment 1 -- 4.2 Experiment 2 -- 5 Conclusions -- References -- Human Activity Recognition with Capsule Networks -- 1 Introduction -- 2 Related Work -- 3 HAR Capsules -- 3.1 Sequence Cutting -- 3.2 Image Embedding -- 3.3 Capsule Network -- 4 Experiments -- 4.1 Data Sets -- 4.2 Results and Discussion -- 5 Conclusions -- References -- Towards Fairness in Classification: Comparison of Methods to Decrease Bias -- 1 Introduction -- 2 Background -- 3 Selected Methods -- 3.1 Decoupled Classifiers -- 3.2 Fairness Constraints -- 3.3 Adversarial Learning -- 4 Fairness Metrics -- 5 Experimental Setup -- 5.1 Databases -- 5.2 Classifier Implementation -- 5.3 Performance Measuring -- 6 Results -- 7 Conclusions -- References -- Hypothesis Scoring and Model Refinement Strategies for FM-Based RANSAC -- 1 Introduction -- 2 Overview of RANSAC and Some Variants -- 3 On Fuzzy Metrics and RANSAC -- 4 FM-Based RANSAC -- 5 Experimental Results -- 5.1 Experimental Setup -- 5.2 Results and Discussion -- 6 Conclusions -- References -- Evaluation of the Transformer Architecture for Univariate Time Series Forecasting -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Attention-Based Deep Neural Network -- 3.2 Experimental Study -- 4 Results and Discussion -- 4.1 Forecasting Accuracy -- 4.2 Computation Time -- 5 Conclusions."]
[{"$nulls":4},"References -- Optimization and Search -- Automatic Generation of Interrelated Organisms on Virtual Environments -- 1 Introduction -- 2 Related Works -- 3 Automatic Generation of Interrelated Organisms -- 3.1 Overall Description -- 3.2 Representation: Morphology and Parameters -- 3.3 Evolutionary Operators -- 3.4 Fitness Evaluation -- 3.5 Species Exploration -- 3.6 Output -- 4 Experimental Evaluation -- 4.1 Methodology and Experiments -- 4.2 Parameters Setting -- 4.3 Results -- 5 Conclusions and Future Work -- References -- Asynchronous Vector Iteration in Multi-objective Markov Decision Processes -- 1 Introduction -- 2 Antecedents -- 3 Algorithms -- 4 Experimental Results and Discussion -- 5 Conclusions and Future Work -- References -- Influence of the Alternative Objective Functions in the Optimization of the Cyclic Cutwidth Minimization Problem -- 1 Introduction -- 2 Alternative Evaluation Functions for the CCMP -- 3 Algorithmic Evaluation Strategy -- 4 Experimental Results -- 5 Conclusions -- References -- A Similarity Measure of Gaussian Process Predictive Distributions -- 1 Introduction -- 2 Gaussian Processes -- 3 The Similarity Measure -- 4 Experiments -- 5 Conclusions -- References -- Towards Automatic Bayesian Optimization: A First Step Involving Acquisition Functions -- 1 Introduction -- 2 BO Issues for Automatic Optimization -- 3 Heuristic Driven Bayesian Optimization -- 4 Experiments -- 4.1 Benchmark Experiments -- 4.2 Real Experiment -- 5 Conclusions and Further Work -- References -- Solving "]
[{"$nulls":4},"the Permutation Heijunka Flow Shop Scheduling Problem with Non-unit Demands for Jobs -- 1 Preliminaries -- 2 Heijunka  Fm/prmu/Cmax /di -- 3 MS-LS: A metaheuristic for Heijunka  Fm/prmu/Cmax /di -- 3.1 Phase 1: Multi-start for the Construction of a Quota Sequence -- 3.2 Phase 2: Improvement of the Quota Sequence Through Local Search."]
[{"$nulls":4},"4 Case Study: Nissan BCN Engine Plant -- 5 Conclusions -- References -- Real-World Applications -- Nearest Neighbors-Based Forecasting for Electricity Demand Time Series in Streaming -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Experimental Results -- 4.1 Dataset and Experimental Setup -- 4.2 Results -- 5 Conclusions -- References -- Towards Combining Object Detection and Text Classification Models for Form Entity Recognition -- 1 Introduction -- 2 Related Work -- 3 FUNSD Dataset -- 4 Vision Models for Detecting Form Entities -- 5 Text Classification of Form Entities -- 6 Conclusions and Further Work -- References -- A Collaborative Platform for the Detection of Non-inclusive Situations in Smart Cities -- 1 Introduction -- 2 Related Work -- 2.1 Detection of Non-inclusive Needs in Smart Cities -- 2.2 Analysis of the Information Collected from the Citizen Interaction -- 3 DColbici3: Collaborative Platform for the Identification of Non-inclusive Situations in Smart Cities -- 3.1 Design of Visual Novels as a Collaborative Platform -- 3.2 NLP for Collaborative Information Analysis -- 3.3 Experimental Set-Up -- 3.4 Results -- 4 Conclusions and Future Work -- References -- Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results -- 4.1 Dataset Description -- 4.2 Experimental Setting -- 4.3 Analysis of Results -- 5 Conclusions -- References -- Recognition of Teaching Activities from University Lecture Transcriptions -- 1 Introduction -- 2 Spoken Academic Lecture -- 3 Data Segmentation and Labeling -- 3.1 Academic Labels -- 4 Text Classification -- 5 Experimental Results -- 6 Conclusions and Future Work -- References -- Train Route Planning as a Multi-agent Path Finding Problem -- 1 Introduction -- 2 Problem Definition."]
[{"$nulls":4},"3 Graph Representation of the Railway Network -- 4 The trtp as a mapf Problem -- 5 Evaluation -- 6 Conclusions and Future Work -- References -- Citizen Centric Optimal Electric Vehicle Charging Stations Locations in a Full City: Case of Malaga -- 1 Introduction -- 2 Efficient Full City EV Charging Station Locations -- 3 Metaheuristics for Efficient EV-CSL -- 3.1 Algorithms -- 3.2 Implementation Details -- 4 Experimental Settings -- 4.1 Scenarios -- 4.2 Implementation and Hardware Platform -- 4.3 Parameter Settings -- 5 Experimental Analysis -- 5.1 Optimization Results Comparison -- 5.2 Improvement on Travel Distance over the Real Layout of Stations -- 6 Conclusion -- References -- Modeling Administrative Discretion Using Goal-Directed Answer Set Programming -- 1 Introduction -- 2 Goal-Directed Answer Set Programming -- 3 Administrative and Judicial Discretion Reasoner -- 3.1 Patterns to Translate Law into ASP -- 3.2 Description of s(LAW) -- 4 Reasoning and Deduction with Real Use-Cases -- 5 Related Work -- 6 Conclusions -- References -- Author Index."]
[null,"2.","Record Nr.",null,"UNINA9910958551203321"]
[null,null,"Autore",null,"Barski-Carrow Barbara"]
[null,null,"Titolo",null,"When trauma survivors return to work / / Barbara Barski-Carrow"]
[null,null,"Pubbl/distr/stampa",null,"Lanham, Md., : University Press of America, 2010"]
[null,null,"ISBN",null,"0-7618-8491-2"]
[{"$nulls":4},"1-282-56189-8"]
[{"$nulls":4},"9786612561894"]
[{"$nulls":4},"0-7618-5031-7"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (302 p.)"]
[null,null,"Disciplina",null,"150"]
[{"$nulls":4},"300"]
[{"$nulls":4},"616.852106"]
[null,null,"Soggetti",null,"Psychic trauma"]
[{"$nulls":4},"Psychic trauma - Treatment"]
[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","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. 165-169)."]
[null,null,"Nota di contenuto",null,"pt. 1. Understanding the traumatic life experience (TLE) -- pt. 2. Taking practical steps -- pt. 3. Some special circumstances."]
[null,null,null,"Sommario/riassunto","This book explains how managers and co-workers can help foster-and not hinder-the process of emotional recovery for employees who have been traumatized and are returning to work."]