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[null,"1.","Record Nr.",null,"UNISA996393068803316"]
[null,null,"Autore",null,"Palmer Herbert <1601-1647.>"]
[null,null,"Titolo",null,"The glasse of Gods providence towards his faithfull ones [[electronic resource]] : Held forth in a sermon preached to the two Houses of Parliament, at Margarets Westminster, Aug. 13. 1644. being an extraordinary day of humiliation. Wherein is discovered the great failings that the best are liable unto; upon which God is provoked sometimes to take vengeance. The whole is applyed specially to a more carefull observation of our late Covenant, and particularly against the ungodly toleration pleaded for under pretence of liberty of conscience. By Herbert Palmer, B.D. minister of Gods Word at Ashwell in Hertford-shire: a member of the Assembly of Divines"]
[null,null,"Pubbl/distr/stampa",null,"London, : Printed by G.M. for Th. Underhill at the Bible in Woodstreet, 1644"]
[null,null,"Descrizione fisica",null,"[6], 66 p"]
[null,null,"Soggetti",null,"Providence and government of God"]
[{"$nulls":4},"Fast-day sermons - 17th century"]
[{"$nulls":4},"Sermons, English - 17th century"]
[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","The first leaf bears an order to print."]
[{"$nulls":4},"Reproduction of the original in the British Library."]
[null,null,null,"Sommario/riassunto","eebo-0018"]
[null,"2.","Record Nr.",null,"UNISA996503471103316"]
[null,null,"Titolo",null,"Intelligent information and database systems . Part I : 14th Asian Conference, ACIIDS 2022, Ho Chi Minh City, Vietnam, November 28-30, 2022, proceeding / / Ngoc Thanh Nguyen [and five others]"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-031-21743-8"]
[null,null,"Descrizione fisica",null,"1 online resource (743 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Database management"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Advanced Data Mining Techniques and Applications -- Textual One-Pass Stream Clustering with Automated Distance Threshold Adaption -- 1 Introduction -- 1.1 Recent Work on Textual Stream Clustering -- 2 Distance Based Clustering with Automatic Threshold Determination (textClust) -- 2.1 Automatic Tresholding During the Online Phase -- 2.2 Algorithm Specification -- 3 Experiments -- 3.1 Benchmarking Datasets -- 3.2 Experimental Setup -- 3.3 Evaluation Metrics -- 3.4 Experimental Results -- 4 Discussion and Future Work -- References -- Using GPUs to Speed Up Genetic-Fuzzy Data Mining with Evaluation on All Large Itemsets -- 1 Introduction -- 2 Related Work -- 3 Components of the Proposed Algorithm -- 3.1 Chromosome Representation -- 3.2 Population Initialization -- 3.3 Fitness Function and Selection -- 3.4 Genetic Operators and Termination -- 4 The Proposed GFM-GPU-LAll Optimization Algorithm -- 5 Experimental Evaluations -- 6 Conclusions and Future Work -- References -- Efficient Classification with Counterfactual Reasoning and Active Learning -- 1 Introduction -- 2 Related Works -- 3 Framework -- 3.1 Problem Definition -- 3.2 Proposed Method CCRAL -- 4 Experiments and Discussions -- 4.1 Datasets -- 4.2 Baselines and Evaluation -- 4.3 Results -- 5 Conclusion -- References -- Visual Localization Based on Deep Learning - Take Southern Branch of the National Palace Museum for Example -- 1 Introduction -- 2 Related Work -- 2.1 "]
[{"$nulls":4},"Convolutional Neural Network -- 2.2 Visual Localization Based on Deep Learning -- 3 Proposed Method -- 3.1 Network Architecture -- 3.2 Loss Function -- 4 Experiments -- 4.1 Pretrained Model -- 4.2 Normalization -- 4.3 Loss Function -- 5 Conclusion and Future Work -- References."]
[{"$nulls":4},"SimCPSR: Simple Contrastive Learning for Paper Submission Recommendation System -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Contrastive Learning -- 3.2 Modeling -- 3.3 Evaluation Metrics -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Datasets -- 4.3 Training Details -- 4.4 Results -- 5 Conclusion and Further Works -- References -- Frequent Closed Subgraph Mining: A Multi-thread Approach -- 1 Introduction -- 2 Related Work -- 3 Definitions -- 4 Proposed Method -- 5 Experimental Results -- 6 Conclusion and Future Work -- References -- Decision Support and Control Systems -- Complement Naive Bayes Classifier for Sentiment Analysis of Internet Movie Database -- 1 Introduction -- 2 Related Work -- 2.1 Sentiment Analysis (SA) -- 2.2 Complement Naïve Bayes Classifier -- 2.3 Analysis Metrics -- 3 Methodology -- 3.1 Research Workflow -- 3.2 Internet Movie Database (IMDB) -- 4 Experiment and Result -- 4.1 Experiment Results -- 5 Conclusions -- References -- Portfolio Investments in the Forex Market -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 The Investing Process -- 4 Numerical Experiments -- 5 Conclusions -- References -- Detecting True and Declarative Facial Emotions by Changes in Nonlinear Dynamics of Eye Movements -- 1 Introduction -- 2 Methods -- 3 Results -- 4 Discussions -- 5 Conclusions -- References -- Impact of Radiomap Interpolation on Accuracy of Fingerprinting Algorithms -- 1 Introduction -- 2 Related Work -- 2.1 Fingerprinting Localization -- 2.2 Dynamic Radiomap -- 2.3 Interpolation Algorithms -- 3 Experimental Scenario and Achieved Results -- 4 Conclusions -- References -- Rough Set Rules (RSR) Predominantly Based on Cognitive Tests Can Predict Alzheimer's Related Dementia -- 1 Introduction -- 2 Methods -- 2.1 Theoretical Basis -- 3 Results -- 3.1 Statistical Results."]
[{"$nulls":4},"3.2 RSR for Reference of Model1 Group -- 3.3 RSR for Reference of Model2 Group -- 4 Discussion -- References -- Experiments with Solving Mountain Car Problem Using State Discretization and Q-Learning -- 1 Introduction -- 2 Related Works -- 3 Modeling the Mountain Car Problem -- 3.1 Physics of the Mountain Car Problem -- 3.2 Model Exploration Using Random Walk and Numerical Simulation -- 4 Optimal Control Using State Discretization and Q-Learning -- 4.1 Q-Learning and SARSA Algorithms -- 4.2 State Discretization -- 4.3 Experimental Results -- 5 Conclusions and Future Work -- References -- A Stable Method for Detecting Driver Maneuvers Using a Rule Classifier -- 1 Introduction -- 2 Data Logging -- 2.1 Data Stream Forming -- 2.2 Data Collection -- 3 Evaluation of the Model -- 4 Conclusions and Further Work -- References -- Deep Learning Models -- Using Deep Transformer Based Models to Predict Ozone Levels -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Baseline Models -- 3.2 Performance Evaluation Metrics -- 4 Problem Description and Our Model -- 4.1 Problem Description -- 4.2 Deep Transformer Based Models -- 4.3 MLP and LSTM Networks -- 5 Experiments -- 5.1 Comparison Between Models -- 5.2 Hyperparameters Optimisation -- 6 Conclusions and Future Work -- References -- An Ensemble Based Deep Learning Framework to Detect and Deceive XSS and SQL Injection Attacks -- 1 Introduction -- 1.1 Background Study -- 2 Proposed Detection and Deception Technique -- 2.1 Data Preparation and Feature Selection -- 2.2 Using the Ensemble Based Deep Learning "]
[{"$nulls":4},"Classifiers -- 2.3 State Maintenance Module -- 2.4 Deception Module to Lure/Engage Attackers -- 3 Discussion, Performance Analysis and Testing -- 3.1 Comparative Analysis -- 4 Conclusion and Future Work -- References -- An Image Pixel Interval Power (IPIP) Method Using Deep Learning Classification Models."]
[{"$nulls":4},"1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Baseline Method -- 4.3 Training Setup -- 4.4 Evaluation Metrics -- 4.5 Experimental Results and Discussions -- 5 Conclusion -- References -- Meta-learning and Personalization Layer in Federated Learning -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 4 Numerical Experiments -- 5 Results and Discussion -- 6 Conclusion -- A Experimental Details -- A.1 Model Architecture -- A.2 Hyper-parameters Searching -- References -- ETop3PPE: EPOCh's Top-Three Prediction Probability Ensemble Method for Deep Learning Classification Models -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Training Setup -- 4.3 Evaluation Metrics -- 4.4 Experiment Results and Discussions -- 5 Conclusions -- References -- Embedding Model with Attention over Convolution Kernels and Dynamic Mapping Matrix for Link Prediction -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Dynamic Convolution -- 3.2 TransD Model -- 4 The Proposed Model -- 5 Experiments and Result Analysis -- 5.1 Benchmark Datasets -- 5.2 Experimental Setup -- 5.3 Results -- 6 Conclusion and Future Research Directions -- References -- Employing Generative Adversarial Network in COVID-19 Diagnosis -- 1 Introduction -- 2 Proposed Framework -- 2.1 Data Augmentation -- 2.2 Transfer Learning -- 3 Experimental Evaluation -- 3.1 Using GAN to Generate Synthetic Images -- 3.2 Transfer Learning -- 4 Conclusion -- References -- SDG-Meter: A Deep Learning Based Tool for Automatic Text Classification of the Sustainable Development Goals -- 1 Introduction -- 2 State-of-the-Art -- 3 Multi-labeled Text Classification with BERT -- 3.1 BERT: Bidirectional Encoder Representations from Transformers -- 3.2 SDG-Meter Tool -- 4 Experimentation."]
[{"$nulls":4},"4.1 Dataset -- 4.2 Test and Results -- 5 Conclusion -- References -- The Combination of Background Subtraction and Convolutional Neural Network for Product Recognition -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Background Subtraction and Skin Removal -- 3.2 Product Classification -- 3.3 Product Tracking and Counting -- 4 Experiment -- 4.1 Experimental Setup -- 4.2 Training Classifier -- 4.3 Result and Discussion -- 5 Conclusions -- References -- Strategy and Feasibility Study for the Construction of High Resolution Images Adversarial Against Convolutional Neural Networks -- 1 Introduction -- 1.1 Attacks in the R Domain -- 1.2 Three Challenges Faced by Attacks in the H Domain -- 1.3 Our Contribution: A Strategy and a Feasibility Study -- 2 CNNs and the Target Scenario -- 2.1 The Target Scenario -- 2.2 The Target Scenario Lifted to HR Images -- 3 Attack Strategy for the Target Scenario on HR Images -- 3.1 Construction of Adversarial Images in H -- 3.2 Indicators: The Loss Function L and L2-distances -- 4 Feasibility Study -- 4.1 The Evolutionary Algorithm EAtarget,C -- 4.2 Running the Strategy to Get Adversarial Images with the EA -- 4.3 Visual Quality -- 5 Conclusion -- References -- Using Deep Learning to Detect Anomalies in Traffic Flow -- 1 Introduction -- 2 Problem Description -- 2.1 Data -- 2.2 Scenarios -- 3 Auto-encoder Models -- 3.1 CNN Auto-encoder Model -- 3.2 BiLSTM Auto-encoder Model -- 4 Experiments -- 4.1 Basic Scenario -- 4.2 Guided Scenario -- 5 Conclusions and Future Work -- References -- A Deep Convolution Generative Adversarial Network for the Production of Images of Human "]
[{"$nulls":4},"Faces -- 1 Introduction -- 2 A Recall of the Genarative Adversial Networks (GAN) -- 3 Related Works Concerning the Variants of GANs -- 3.1 Architecture-Variant -- 3.2 Loss-Variant."]
[{"$nulls":4},"4 Deep Convolutional GAN: A Method Adopted for Human Faces Images Producing."]
[null,"3.","Record Nr.",null,"UNIORUON00234221"]
[null,null,"Autore",null,"ILIEVSKI, Petar Hr."]
[null,null,"Titolo",null,"Zivotot na mikencite vo nivnite pismeni svedostva so poseben osvrt kon onomastickite i prosopografski izvodi / Petar Hp. Ilievski"]
[null,null,"Pubbl/distr/stampa",null,"Skopje, : Makedonska akademija na naukite i umetnostite, 2000"]
[null,null,"ISBN",null,"99-89649-68-5"]
[null,null,"Descrizione fisica",null,"419 p. ; 24 cm."]
[null,null,"Lingua di pubblicazione",null,"Macedonian"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]