Search Results - (( Defined contribution pensions plans ) OR ((( Defined ((distributed operating) OR (distributed computing)) a ) OR ( Defined ((distribution erosion) OR (distributed estimation)) plans ))))

User-defined tensor data analysis by Dong, Bin

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Introducing .Net for Apache Spark : distributed processing for massive datasets by Elliott, Ed

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Beginning Apache Pig : big data processing made easy by Vaddeman, Balaswamy

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Cloud networking for big data by Zeng, Deze, Gu, Lin, Guo, Song (Computer scientist)

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Recent innovations in computing : proceedings of ICRIC 2020 ICRIC 2020. by International Conference on Recent Innovations in Computing Jammu, India, SpringerLink (Online service)

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EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing : BDCC 2018 by EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing Coimbatore, India, SpringerLink (Online service)

Contents: “…Intelligent Systems For Volumetric Feature Recognition From Cad Mesh Models -- Chapter 12. Factors Affecting A Mobile Learning System: A Case Study -- Chapter 13. …”
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Big data analytics for sensor-network collected intelligence by ScienceDirect (Online service)

Contents: “…Big Data: A Classification; 1.1. Characteristics of Big Data; 2. …”
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Software architecture for big data and the cloud First edition. by ScienceDirect (Online service)

Contents: “…Note continued: 14.3.Data Intensive Computing -- 14.3.1.Big Compute Versus Big Data -- 14.3.2.Data Intensive Applications -- 14.3.3.Data Intensive Frameworks -- 14.3.4.MapReduce and GFS -- 14.4.Apache Hadoop -- 14.4.1.Hadoop VI -- 14.4.2.Hadoop 2.0 -- 14.5.Apache Spark -- 14.5.1.Resilient Distributed Datasets -- 14.5.2.Data Flow and Programming With Spark -- 14.5.3.Spark Processing Engines -- 14.5.4.Hadoop Ecosystem Taxonomy -- 14.6.The Role of Cloud Computing -- 14.7.The Future of Big Data Platforms -- 14.7.1.Big Data Applications -- 14.7.2.Big Data Frameworks and Hardware -- 14.7.3.Big Data on the Road to Exascale -- 14.8.Conclusion -- References -- ch. 15 A Taxonomy and Survey of Fault-Tolerant Workflow Management Systems in Cloud and Distributed Computing Environments / Rajkumar Buyya -- 15.1.Introduction -- 15.2.Background -- 15.2.1.Workflow Management Systems -- 15.2.2.Workflow Scheduling -- 15.3.Introduction to Fault-Tolerance.…”
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Cloud computing, big data & emerging topics : 10th conference, JCC-BD&ET 2022, La Plata, Argentina, June 28-30, 2022, proceedings by International Conference on Cloud Computing, Big Data & Emerging Topics La Plata, Argentina ; Online, SpringerLink (Online service)

Contents: “…3.2 Labeling of Documents -- 3.3 Email Indexing -- 3.4 Feature Selection Strategies -- 3.5 Retrieval of E-mails -- 3.6 Generation of the Classification Models -- 4 Experiments -- 5 Conclusions -- References -- Applying Game-Learning Environments to Power Capping Scenarios via Reinforcement Learning -- 1 Introduction -- 2 The RLlib and Gym Frameworks -- 2.1 RLlib -- 2.2 Gym -- 3 RL for Resource Management -- 4 Casting a Power Capping Scenario with Gym -- 4.1 Defining States -- 4.2 Defining Actions and Rewards -- 5 Experimental Results -- 5.1 Analysis Under Different Power Caps.…”
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Beginning big data with Power BI and Excel 2013 by Dunlop, Neil

Contents: “…Removing Duplicates Input Validation; Working with Data Forms; Selecting Records; Summary; Chapter 3: Pivot Tables and Pivot Charts; Recommended Pivot Tables in Excel 2013; Defining a Pivot Table; Defining Questions; Creating a Pivot Table; Changing the Pivot Table; Creating a Breakdown of Sales by Salesperson for Each Day; Showing Sales by Month; Creating a Pivot Chart; Adjusting Subtotals and Grand Totals; Analyzing Sales by Day of Week; Creating a Pivot Chart of Sales by Day of Week; Using Slicers; Adding a Time Line; Importing Pivot Table Data from the Azure Marketplace.…”
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Advances in data science and artificial intelligence : ICDSAI 2022, IIT Patna, India, April 23-24 by International Conference on Data Science and Artificial Intelligence Patna, India, SpringerLink (Online service)

Contents: “…Sky Detection in Outdoor Spaces (S. Rajguru) -- Defining, Measuring and Utilizing Student's Learning in a course (T. …”
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Future data and security engineering : big data, security and privacy, smart city and Industry 4.0 applications : 10th International Conference, FDSE 2023, Da Nang, Vietnam, Novemb... by FDSE (Conference) Da Nang, Vietnam), SpringerLink (Online service)

Contents: “…An experiment report -- Authenticating Parties in Blockchain-Enabled Inter-Organizational Processes with Configurable Challenge-Sets -- Differential Privacy for Consumer Data in Retail Data Partnerships -- Using transformer technique for intrusion detection -- Machine Learning and Artificial Intelligence for Security and Privacy -- A Siamese-Based Approach for Network Intrusion Detection Systems in Software-Defined Networks -- An Efficient Machine Learning-based Web Application Firewall with Deep Automated Pattern Categorization -- Utilizing InfoGAN and PE Header Features for Synthetic Ransomware Image Generation: An Experimental Study -- Enhancing Detection of Daily-Used Face Swap Applications by Using Focused Landmark Analysis -- Differential Privacy under Membership Inference Attacks -- Smart City and Industry 4.0 Applications -- LAVETTES: Large-scAle-dataset Vietnamese ExTractive TExt Summarization Models -- Exploring Links between Personality Traits and Environmental Attitudes with GreenBig5 System -- Study on Web Based Virtualized Containers for Software Development Lectures in BYOD -- Session-based Recommendation System Approach for Predicting Learning Performance -- A Fuzzy Logic Model for Digital Transformation Assessment of Vietnamese Higher Education Institutions -- Digital Transformation Insights from an AI Solution in Search of a Problem -- Improving Human Resources⁰́₉ Efficiency with A Generative AI-based Resume Analysis Solution -- LORAP: Local Deep Neural Network for Solar Radiation Prediction -- A Digital Therapeutics System for the Diagnosis and Management of Depression: Work in Progress -- BERT-based Sentence Recommendation for Building Vietnamese Universal Dependency Treebank -- Evaluate the Efficiency of Hybrid Model based on Convolutional Neural Network and Long Short-Term Memory in Information Technology Job Graph Network -- A Dataset of Vietnamese Documents for Text Detection -- Data Analytics and Healthcare Systems -- Personalized Stress Detection System Using Physiological Data from Wearable Sensors -- Vision Transformer for Kidney Stone Detection -- Attention Models and Image Pre-Processing For Covid- 19 Detection Based on Lung Ultrasound Images -- Deep Learning Techniques for Segmenting Breast Lesion Regions and Classifying Mammography Images -- Development of a Handwriting Drawings Assessment System for Early Parkinson⁰́₉s Disease Identification with Deep Learning Methods -- Breast Cancer Classification on Mammograms Using Vision Transformer -- Comparing Performance of Linear Regression Models Trained on Systemathic Forest Measurement Datasets to Predict Diameter at Breast Height -- Detection and Segmentation of Brain Tumors on 3D MR images Using 3D U-Net -- Short Papers: Security and Data Engineering -- Towards Automating Semantic Relationship Awareness in Operational Technology Monitoring -- Feature Fool Exploitation for Lightweight Anomaly Detection in Respiratory Sound -- Multiple Vehicles Detection and Tracking using Ground and Aerial Images for Vehicular Management System -- Deep Learning Approach for Tomato Leaf Disease Detection -- Invasive Ductal Carcinoma Classification from Whole Slide Image based on BRISQUE and Convolutional Neural Networks -- Robust and Accurate Automatic License Plate Recognition System -- Community Detection for Personalized Learning Pathway Recommendations on IT E-Learning System -- Improving Warped Planar Object Detection Network for Automatic License Plate Recognition.…”
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Future data and security engineering : big data, security and privacy, smart city and Industry 4.0 applications : 9th International Conference, FDSE 2022, Ho Chi Minh City, Vietnam... by FDSE (Conference) Ho Chi Minh City, Vietnam), SpringerLink (Online service)

Contents: “…Invited Keynotes -- Towards a Foundation of Web3 -- In-Memory Computing Architectures for Big data and Machine Learning Applications -- Secure and Efficient Implementation of Electronic Money -- Managing the Quality of Data and Metadata for Biobanks -- Big Data Analytics and Distributed Systems -- Towards A Privacy, Secured and Distributed Clinical Data Warehouse Architecture -- Improving the Storage Utilization of 0-Complete Trees as Index Structures -- Implement the Data Conversion System by using Lightweight Coreset for Validation Process -- Content Selection Methods Using User Interest Prediction Based on Similarities of Web Activities -- ImageNet Challenging Classification with the Raspberry Pis: A Federated Learning Algorithm of Local Stochastic Gradient Descent Models -- Covid-19 Detection Based on Lung Lesion Signs in Big Data Processing Environment -- Predicting Loan Repayment Using A Hybrid of Genetic Algorithms, Logistic Regression, and Artificial Neural Networks -- Performance Evaluation of Regular Decomposition and Benchmark Clustering Methods -- Security and Privacy Engineering -- Authentication of Luxury Products Identifying Key Requirements from a Seller and Consumer Perspective -- Analysis of A New Practical SPN-based Scheme in the Luby-Rackoff Model -- Authorization and Access Control for Different Database Models: Requirements and Current State of the Art -- A Hierarchical Deterministic Wallet using Ed25519 Digital Signature Scheme -- A Secure Framework for Internet of Medical Things Security Based System using Lightweight Cryptography enabled Blockchain -- Signature Algorithms on Non-commutative Algebras over Finite Fields of Characteristic Two -- Design a Smart Lock System Using Fingerprint and Password for Enhancing Security -- Machine Learning and Artificial Intelligence for Security and Privacy -- Towards an Attention-based Threat Detection System for IoT Networks -- Security and Privacy Issues and Solutions in Federated Learning for Digital Healthcare -- pPATE: A Pragmatic Private Aggregation of Teacher Ensembles Framework by Sparse Vector Technique based Differential Privacy, Paillier Cryptosystem and Human-in-the-loop -- Vietnamese Texts Writing Styles Based Authorship Identification Model -- Application of Machine Learning in Malware Detection -- Smart City and Industry 4.0 Applications -- Text Classification Models and Topic Models: An Overall Picture and A Case Study in Vietnamese -- Deep Hybrid Models for Forecasting Stock Midprices from the High-Frequency Limit Order Book -- An Image Denoising Model based on Nonlinear Partial Diferential Equation Using Deep Learning -- Recommendations in E-Commerce Systems based on Deep Matrix Factorization -- AttendanceKit: A set of Role-based Mobile Applications for Automatic Attendance Checking with UHF RFID using Realtime Firebase and Face Recognition -- Poses Classification in a Taekwondo Lesson using Skeleton Data extracted from Videos with Shallow and Deep Learning Architectures -- Social Distancing Violation Detection in Video using ChessBoard and Bird's-eye Perspective -- 3D-FaultSeg-UNet: 3D Fault Segmentation in Seismic Data Using Bi-stream U-Net -- Applying Artificial Intelligence to Plan Flight Paths for Aircraft at Subsonic Speeds -- Capacity Building in Government: Towards Developing A Standard for A Functional Specialist in AI for Public Services -- On the Feasibility of Machine Learning Models for Customer Spending Prediction Problem -- Forecasting the Opening and Closing Price Trends of Stock Using Hybrid Models and Artificial Intelligence Algorithm -- Artificial Intelligence Use in e-Government Services: A Systematic Interdisciplinary Literature Review -- Face Recognition based on Deep Learning and Data Augmentation -- An Approach for Similarity Vietnamese Documents Detection from English Documents -- Combine Clasification Algorithm and Centernet Model to Predict Trafic Density -- Data Analytics and Healthcare Systems -- Comparison of Health Indicators Construction for Concrete Structure Using Acoustic Emission Hit and Kullback-Leibler Divergence -- Lung and Colon Tumor Classification Based on Transfer Learning-Based Techniques -- An Enhanced Diabetes Mellitus Prediction using Feature Selection-Based Type-2 Fuzzy Model -- A Novel Approach of Using Neural Circuit Policies for COVID-19 Classification on CT-images -- Lung Lesions Segmentation and Classification with Deep Neural Networks -- Security and Data Engineering -- Image Denoising using Fully Connected Network with Reinforcement Learning -- Energy Harvesting Aware for Delay-efficient Data Aggregation in Battery-free IoT Sensors -- Deep Models for Mispronounce Prediction for Vietnamese Learners of English -- An Approach to Hummed-tune and Song Sequences Matching -- 84 Birds Classification using Transfer Learning and EfficientNetB2 -- A Session-based Recommender System for Learning Resources -- A Drowsiness Detection System Based on Eye Landmarks Using IoT -- A Novel Approach for Vietnamese Speech Recognition Using Conformer -- Enhancing obfuscated malware detection with machine learning techniques -- Detecting Intrusion using Multiple Datasets in Software-Defined Networks -- Detecting Exams Fraud Using Transfer Learning and Fine-tuning for ResNet50 -- Shape of Pill Recognition Using Mask R-CNN.…”
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Handbook of big geospatial data by SpringerLink (Online service)

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IoT solutions in Microsoft's Azure IoT suite : data acquisition and analysis in the real world by Klein, Scott, 1966-

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Big data and the internet of things : enterprise information architecture for a new age by Stackowiak, Robert, Licht, Art, Mantha, Venu, Nagode, Louis

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Modern enterprise business intelligence and data management : a roadmap for IT directors, managers, and architects by Simon, Alan, 1958-

Contents: “…Cover; Title Page; Copyright Page; Table of contents; Preface; Terminology; Defining "Enterprise"; Defining "Data"; Defining "Enterprise Data Management"; Defining "Business Intelligence"; About the author; Chapter 1 -- The Rebirth of Enterprise Data Management; 1.1 -- In the beginning: how we got to where we are today; 1.1.1 -- 1960s and 1970s; 1.1.2 -- 1980s; 1.1.2.1 -- Enterprise Data Models; 1.1.2.2 -- Distributed Database Management Systems (DDBMSs); 1.1.3 -- 1990s; 1.1.3.1 -- Data Warehousing; 1.1.3.2 -- Read-Only Distributed Data Access; 1.1.4 -- 2000s; 1.1.5 -- Today.…”
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Big data analytics using Splunk by Zadrozny, Peter

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Cognitive networked sensing and big data by Qiu, Robert C., 1966-, Wicks, Michael

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The data science handbook by Cady, Field, 1984-

Contents: “…-- 16.2 The Great Divide: Language versus Statistics -- 16.3 Example: Sentiment Analysis on Stock Market Articles -- 16.4 Software and Datasets -- 16.5 Tokenization -- 16.6 Central Concept: Bag-of-Words -- 16.7 Word Weighting: TF-IDF -- 16.8 n-Grams -- 16.9 Stop Words -- 16.10 Lemmatization and Stemming 16.11 Synonyms -- 16.12 Part of Speech Tagging -- 16.13 Common Problems -- 16.14 Advanced NLP: Syntax Trees, Knowledge, and Understanding -- 16.15 Further Reading -- 16.16 Glossary -- Chapter 17 Time Series Analysis -- 17.1 Example: Predicting Wikipedia Page Views -- 17.2 A Typical Workflow -- 17.3 Time Series versus Time-Stamped Events -- 17.4 Resampling an Interpolation -- 17.5 Smoothing Signals -- 17.6 Logarithms and Other Transformations -- 17.7 Trends and Periodicity -- 17.8 Windowing -- 17.9 Brainstorming Simple Features -- 17.10 Better Features: Time Series as Vectors -- 17.11 Fourier Analysis: Sometimes a Magic Bullet -- 17.12 Time Series in Context: The Whole Suite of Features -- 17.13 Further Reading -- 17.14 Glossary -- Chapter 18 Probability -- 18.1 Flipping Coins: Bernoulli Random Variables -- 18.2 Throwing Darts: Uniform Random Variables -- 18.3 The Uniform Distribution and Pseudorandom Numbers -- 18.4 Nondiscrete, Noncontinuous Random Variables -- 18.5 Notation, Expectations, and Standard Deviation -- 18.6 Dependence, Marginal and Conditional Probability -- 18.7 Understanding the Tails -- 18.8 Binomial Distribution -- 18.9 Poisson Distribution -- 18.10 Normal Distribution -- 18.11 Multivariate Gaussian -- 18.12 Exponential Distribution -- 18.13 Log-Normal Distribution -- 18.14 Entropy 18.15 Further Reading -- 18.16 Glossary -- Chapter 19 Statistics -- 19.1 Statistics in Perspective -- 19.2 Bayesian versus Frequentist: Practical Tradeoffs and Differing Philosophies -- 19.3 Hypothesis Testing: Key Idea and Example -- 19.4 Multiple Hypothesis Testing -- 19.5 Parameter Estimation -- 19.6 Hypothesis Testing: t-Test -- 19.7 Confidence Intervals -- 19.8 Bayesian Statistics -- 19.9 Naive Bayesian Statistics -- 19.10 Bayesian Networks -- 19.11 Choosing Priors: Maximum Entropy or Domain Knowledge -- 19.12 Further Reading -- 19.13 Glossary -- Chapter 20 Programming Language Concepts -- 20.1 Programming Paradigms -- 20.2 Compilation and Interpretation -- 20.3 Type Systems -- 20.4 Further Reading -- 20.5 Glossary -- Chapter 21 Performance and Computer Memory -- 21.1 Example Script -- 21.2 Algorithm Performance and Big-O Notation -- 21.3 Some Classic Problems: Sorting a List and Binary Search -- 21.4 Amortized Performance and Average Performance -- 21.5 Two Principles: Reducing Overhead and Managing Memory -- 21.6 Performance Tip: Use Numerical Libraries When Applicable -- 21.7 Performance Tip: Delete Large Structures You Don't Need -- 21.8 Performance Tip: Use Built-In Functions When Possible -- 21.9 Performance Tip: Avoid Superfluous Function Calls -- 21.10 Performance Tip: Avoid Creating Large New Objects -- 21.11 Further Reading -- 21.12 Glossary -- Part III Specialized or Advanced Topics -- Chapter 22 Computer Memory and Data Structures -- 22.1 Virtual Memory, the Stack, and the Heap -- 22.2 Example C Program -- 22.3 Data Types and Arrays in Memory -- 22.4 Structs -- 22.5 Pointers, the Stack, and the Heap -- 22.6 Key Data Structures -- 22.7 Further Reading -- 22.8 Glossary -- Chapter 23 Maximum Likelihood Estimation and Optimization -- 23.1 Maximum Likelihood Estimation -- 23.2 A Simple Example: Fitting a Line -- 23.3 Another Example: Logistic Regression -- 23.4 Optimization -- 23.5 Gradient Descent and Convex Optimization -- 23.6 Convex Optimization -- 23.7 Stochastic Gradient Descent -- 23.8 Further Reading -- 23.9 Glossary -- Chapter 24 Advanced Classifiers -- 24.1 A Note on Libraries -- 24.2 Basic Deep Learning -- 24.3 Convolutional Neural Networks -- 24.4 Different Types of Layers.…”
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