01022nam0 22002773i 450 SUN013208620201204120543.49208-01-43513-70.0008-01-48513-4pbk20201204d1988 |0itac50 baitaIT|||| |||||The *geography of moneyBenjamin J. CohenIthacaLondonCornell university1998XV, 229 p.24 cm.GBLondonSUNL000015IthacaSUNL000377Cohen, Benjamin J.SUNV105862237093Cornell universitySUNV001466650ITSOL20201207RICAhttps://books.google.it/books?id=UP67hpdE9rYC&printsec=frontcover&hl=it#v=onepage&q&f=falseSUN0132086UFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI GIURISPRUDENZA00CONS XX.Cb.90 00UBG5854 20201204 Geography of money1762240UNICAMPANIA03831nam 22007692 450 991081233260332120230329000156.01-139-15304-81-107-22231-11-283-34115-897866133411501-139-16060-50-511-99475-31-139-16160-11-139-15603-91-139-15779-51-139-15955-0(CKB)2550000000065926(EBL)807218(OCoLC)767502516(SSID)ssj0000551285(PQKBManifestationID)11318795(PQKBTitleCode)TC0000551285(PQKBWorkID)10525614(PQKB)11536327(UkCbUP)CR9780511994753(Au-PeEL)EBL807218(CaPaEBR)ebr10514122(CaONFJC)MIL334115(MiAaPQ)EBC807218(EXLCZ)99255000000006592620141103d2011|||| uy| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierFatal self-deception slaveholding paternalism in the Old South /Eugene D. Genovese, Elizabeth Fox-Genovese[electronic resource]Cambridge :Cambridge University Press,2011.1 online resource (xvii, 232 pages) digital, PDF file(s)Title from publisher's bibliographic system (viewed on 05 Oct 2015).1-107-60502-4 1-107-01164-7 Includes bibliographical references and index.Machine generated contents note: 1. 'Boisterous passions'; 2. The complete household; 3. Strangers within the gates; 4. Loyal and loving slaves; 5. The blacks' best and most faithful friend; 6. Guardians of a helpless race; 7. Devotion unto death.Slaveholders were preoccupied with presenting slavery as a benign, paternalistic institution in which the planter took care of his family and slaves were content with their fate. In this book, Eugene D. Genovese and Elizabeth Fox-Genovese discuss how slaveholders perpetuated and rationalized this romanticized version of life on the plantation. Slaveholders' paternalism had little to do with ostensible benevolence, kindness and good cheer. It grew out of the necessity to discipline and morally justify a system of exploitation. At the same time, this book also advocates the examination of masters' relations with white plantation laborers and servants - a largely unstudied subject. Southerners drew on the work of British and European socialists to conclude that all labor, white and black, suffered de facto slavery, and they championed the South's 'Christian slavery' as the most humane and compassionate of social systems, ancient and modern.SlaverySouthern StatesHistory19th centuryPlantation ownersSouthern StatesHistory19th centuryPaternalismSouthern StatesHistory19th centuryEnslaved personsSouthern StatesSocial conditions19th centuryPlantation workersSouthern StatesHistory19th centuryWhite peopleSouthern StatesSocial conditions19th centurySlaveryHistoryPlantation ownersHistoryPaternalismHistoryEnslaved personsSocial conditionsPlantation workersHistoryWhite peopleSocial conditions306.3/620975Genovese Eugene D.1930-2012,121460Fox-Genovese Elizabeth1941-2007,UkCbUPUkCbUPBOOK9910812332603321Fatal self-deception4090010UNINA10896nam 22004933 450 991087805630332120240802080341.03-031-66965-7(MiAaPQ)EBC31572270(Au-PeEL)EBL31572270(CKB)33566328600041(EXLCZ)993356632860004120240802d2024 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierRecent Advances on Soft Computing and Data Mining Proceedings of the Sixth International Conference on Soft Computing and Data Mining (SCDM 2024), August 21-22 20241st ed.Cham :Springer,2024.©2024.1 online resource (451 pages)Lecture Notes in Networks and Systems Series ;v.10783-031-66964-9 Intro -- Preface -- Conference Organization -- Contents -- Prediction of OPEC Carbon Dioxide Emissions Using K-Means Clustering and Ensemble Algorithm -- 1 Introduction -- 2 Related Works -- 3 Fuzzy Nearest Neighbor -- 4 Sequential Minimal Optimization -- 5 Logistic Regression -- 6 K-Means Clustering -- 7 Proposed Methodology -- 8 Experimental Setup and Analysis -- 8.1 Assessment Measures -- 8.2 Dataset Description -- 8.3 Simulation Results -- 9 Conclusion -- References -- Detection of Phishing Websites from URLs Using Hybrid Ensemble-Based Machine Learning Technique -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Description of the Machine Learning Classifiers -- 3.2 Dataset Description -- 3.3 Model Construction -- 4 Performance Evaluation Metrics -- 5 Result -- 6 Conclusion -- 7 Future Work -- References -- Minimal Data for Maximum Impact: An Indonesian Part-of-Speech Tagging Case Study -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Semi-supervised Learning Preprocessing -- 3.3 Feature Selection -- 3.4 Classification -- 3.5 Evaluation -- 4 Result and Discussion -- 5 Conclusion -- 5.1 Summary -- 5.2 Future Work -- References -- Alleviating Sparsity to Enhance Group Recommendation with Cross-Linked Domain Model -- 1 Introduction -- 2 Literature Review -- 2.1 Group Recommender System -- 2.2 Cross-Domain Recommender System -- 2.3 Linked Open Data -- 3 Methodology -- 3.1 Experiment Setup -- 4 Result and Discussion -- 5 Conclusion and Recommendation -- References -- Evaluating Deep Transfer Learning Models for Detecting Various Face Mask Wearings -- 1 Introduction -- 2 Literature Review -- 2.1 Deep Learning -- 2.2 Transfer Learning -- 2.3 Existing Works -- 3 Methodology -- 4 Results and Discussion -- 5 Conclusions -- References.Classification of Stunting Events: Case Study in West Java, Indonesia -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Dataset Collection -- 3.2 Data Pre-processing -- 3.3 Model Comparison -- 3.4 Model Implementation -- 3.5 Model Evaluation -- 4 Results and Discussion -- 5 Conclusion -- References -- The Effects of Data Reduction Using Rough Set Theory on Logistic Regression Model -- 1 Introduction -- 2 The Basic Theories and Methodology -- 2.1 Rough Set Theory (RST) -- 2.2 Logistic Regression Model -- 3 Implementation Hybrid Classification Approach with LR Analysis and RST -- 3.1 Implementation Hybrid Model on Anemia Data Set -- 3.2 Implementation Hybrid Model on Diabetes Data Set -- 3.3 Discussion -- 4 Conclusion -- References -- Robust Heart Disease Prognosis: Integrating Extended Isolation Forest Outlier Detection with Advanced Prediction Models -- 1 Introduction -- 2 Methodology -- 2.1 Summary of Dataset -- 2.2 Data Preprocessing -- 2.3 Machine Learning Techniques -- 2.4 Deep Learning Algorithm -- 2.5 Evaluation Parameters -- 3 Results Evaluation -- 3.1 Implementing the First Strategy, Which Involves Neither Feature Selection nor Outlier Detection -- 3.2 Implementing the 2nd Strategy: Feature Selection Without Outlier Detection -- 3.3 Employing the 3rd Strategy (Feature Selection and Detection of Outliers) -- 4 Conclusion -- References -- Overlapping Granular Clustering: Application in Fuzzy Rule-Based Classification -- 1 Introduction -- 2 GrC-Fuzzy Logic Models -- 2.1 Granular Clustering -- 2.2 Formation of Fuzzy Logic Rule Base -- 3 Overlapping GrC -- 3.1 R-Value -- 3.2 A New Overlapping Measure During the Iterative Data Granulation -- 4 Case Study and Simulation Results -- 5 Interpretability Index -- 6 Conclusion -- References -- Improved Rough-Multiple Regression for Unemployment Rate Model in Indonesia -- 1 Introduction.2 Variable Framework and Methods -- 2.1 Multiple Linear Regression -- 2.2 Rough Sets Theory -- 3 Results and Discussion -- 3.1 Descriptive Statistics for Unemployment Rate and Its Variables -- 3.2 Multiple Linear Regression Model for Unemployment Rate -- 3.3 Rough-Multiple Regression Model for Unemployment Rate -- 3.4 Comparison Multiple Regression and Rough-Multiple Regression -- 4 Conclusion -- References -- Utilizing Machine Learning for Gene Expression Data: Incorporating Gene Sequencing, K-Mer Counting and Asymmetric N-Grams Features -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Pre-processing -- 2.2 Classification Model -- 2.3 Performance Metrics -- 3 Result and Discussion -- 4 Conclusion and Future Work -- References -- Text Sentiment Analysis on VIX's Impact on Market Sentiment Dynamics -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Sentiment Analysis of SnowNLP -- 3.3 Sentiment Index -- 3.4 Pearson's Correlation -- 3.5 Linear Correlation -- 3.6 Granger Causality Test -- 4 Empirical Result and Analysis -- 4.1 Data Description and Cleaning -- 4.2 Text Sentiment Index -- 4.3 Pearson's Correlation -- 4.4 Linear Correlation -- 4.5 Granger Causality Test -- 4.6 Test for Chinese Market -- 5 Conclusion -- References -- Multilevel Monte Carlo Simulation Model for Air Pollution Index Prediction of a Smart Network -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Monte Carlo Simulation -- 3.2 Multilevel Monte Carlo Simulation -- 3.3 Air Pollution Dataset -- 3.4 Performance Evaluation Metrics -- 4 Results and Discussion -- 4.1 Correlation Analysis -- 5 Conclusion -- References -- An In-Depth Strategy using Deep Generative Adversarial Networks for Addressing the Cold Start in Movie Recommendation Systems -- 1 Introduction -- 2 Related Works -- 3 Research Methodology -- 3.1 Data Preparation.3.2 Collaborative Filtering with Singular Value Decomposition (CF-SVD) -- 3.3 Generative Adversarial Networks (GANs) -- 3.4 Collaborative Filtering (CF) with SVD and GANs -- 3.5 Content Based Filtering (CB) -- 4 Results -- 5 Conclusion -- References -- Predicting Undergraduate Academic Success with Machine Learning Approaches -- 1 Introduction -- 2 Related Work -- 3 Research Design and Methodology -- 3.1 Dataset Source -- 3.2 Exploratory Data Analysis -- 3.3 Data Preprocessing -- 3.4 Classification Algorithms -- 4 Results and Discussion -- 4.1 Evaluations of Classifiers Using Default Parameters -- 4.2 Model Parameter Optimization by Hyperparameter Tuning -- 5 Conclusion -- References -- Comparative Assessment of Facial Expression Recognition Models for Unraveling Emotional Signals with Convolutional Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Dataset Description -- 4 Methodology -- 4.1 Pre-processing -- 4.2 Feature Extraction -- 4.3 CNN Architecture -- 5 Results -- 6 Discussions and Future Work -- References -- Evaluating Path-Finding Algorithms for Real-Time Route Recommendation System Built using FreeRTOS -- 1 Introduction -- 2 Related Work -- 3 Research Design and Methodology -- 3.1 Adjacency Matrix -- 3.2 Path Finding Algorithms -- 3.3 Real-Time Operating System (RTOS) -- 3.4 Functional Diagram of the Simulated System using FreeRTOS -- 4 Results and Discussion -- 4.1 Validate the accuracy of the recommended route -- 4.2 Performance Evaluation -- 5 Conclusion -- References -- Machine Learning-Based Phishing Website Detection: A Comparative Analysis and Web Application Development -- 1 Introduction -- 2 Literature Review -- 3 Research Design -- 3.1 Dataset Overview -- 3.2 Feature Selection -- 3.3 Detection Techniques Implementation -- 3.4 Performance Evaluation and Comparison -- 3.5 Web Application Development.4 Results and Discussion -- 5 Conclusion -- References -- Comparative Performance of Multi-level Pre-trained Embeddings on CNN, LSTM and CNN-LSTM for Hate Speech and Offensive Language Detection -- 1 Introduction -- 2 The Architecture of HSOLC Detection Model -- 2.1 Text Embedding Layer -- 2.2 Representation Layer -- 2.3 Output Layer -- 3 Experimental Setup -- 4 Dataset and Results -- 4.1 Results and Discussion -- 5 Conclusion -- References -- Improved Classifier Chain Method Based on Particle Swarm Optimization and Genetic Algorithm for Multilabel Classification Problem -- 1 Introduction -- 1.1 Motivation -- 1.2 Random Label Sequence Ordering (RLSO) -- 2 Related Work -- 3 Method -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 Classification (Proposed Model) -- 3.4 Performance Measures -- 4 Results and Discussion -- 5 Conclusion -- References -- Sentiment Analysis on Umrah Packages Review in Malaysia -- 1 Introduction -- 2 Sentiment Analysis on Social Media -- 2.1 Related Works of Similar -- 2.2 Mobile Phone Reviews from Amazon Using Support Vector Machine -- 2.3 Sentiment Classification of Online Consumer Reviews Using Word Vector Representation -- 2.4 Online Reviews of Hospitality Services Using Naïve Bayes -- 2.5 Customer Satisfaction Towards Umrah Travel Agencies in Malaysia -- 3 Methodology -- 3.1 Preliminary Study -- 3.2 Data Analysis -- 3.3 Interface and Architecture Design -- 3.4 System Development -- 4 Analysis and Discussions -- 4.1 Naïve Bayes - Gaussian -- 4.2 Naïve Bayes - Multinomial -- 4.3 Support Vector Machine -- 4.4 Random Forest -- 4.5 Analysis -- 5 Conclusion and Recommendations -- References -- Opinion Mining System for Influence Detection Using Machine Learning to Secure Business Reputation -- 1 Introduction -- 2 Related Works -- 2.1 Sentiment Analysis -- 2.2 Supervised Machine Learning Approach -- 3 Methodology.3.1 Data Preprocessing and Feature Extraction.Lecture Notes in Networks and Systems SeriesGhazali Rozaida1762055Nawi Nazri Mohd1762056Deris Mustafa Mat1762057Abawajy Jemal H1429336Arbaiy Nureize1762058MiAaPQMiAaPQMiAaPQBOOK9910878056303321Recent Advances on Soft Computing and Data Mining4201772UNINA