Search Results - (((((((ant OR wkant) OR semantic) OR wind) OR cantor) OR anne) OR shared) OR hints) algorithms.
Suggested Topics within your search.
Suggested Topics within your search.
- Artificial intelligence 39
- Data processing 31
- Mathematics 29
- Mathematical models 23
- Technological innovations 20
- Data mining 19
- Machine learning 19
- Mathematical optimization 19
- Algorithms 18
- artificial intelligence 18
- algorithms 17
- Computer science 15
- Information technology 15
- Management 15
- Big data 12
- Computer networks 12
- Artificial Intelligence 11
- Computer algorithms 11
- Automatic control 9
- Design and construction 9
- Computational linguistics 8
- Data Mining 8
- Manufacturing processes 8
- Mechatronics 8
- Neural networks (Computer science) 8
- Research 8
- Social aspects 8
- Bioinformatics 7
- Computer programming 7
- Electric power systems 7
Search alternatives:
- ant »
- wkant »
- semantic »
- cantor »
- wind »
-
441
Big data : concepts, technology and architecture
Published 2021Table of Contents: “…143</p> <p>5.2.3HDFS Architecture. 143</p> <p>5.2.4HDFS Read/Write Operation. 146</p> <p>5.2.5Rack Awareness. 148</p> <p>5.2.6Features of HDFS. 149</p> <p>5.2.6.1Cost-effective. 149</p> <p>5.2.6.2Distributed storage. 149</p> <p>5.2.6.3Data Replication. 149</p> <p>5.3 Hadoop Computation. 149</p> <p>5.3.1MapReduce. 149</p> <p>5.3.1.1Mapper. 151</p> <p>5.3.1.2Combiner. 151</p> <p>5.3.1.3 Reducer. 152</p> <p>5.3.1.4 JobTracker and TaskTracker. 153</p> <p>5.3.2 MapReduce Input Formats. 154</p> <p>5.3.3 MapReduce Example. 156</p> <p>5.3.4 MapReduce Processing. 157</p> <p>5.3.5 MapReduce Algorithm.. 160</p> <p>5.3.6 Limitations of MapReduce. 161</p> <p>5.4Hadoop 2.0. 161</p> <p>5.4.1Hadoop 1.0 limitations. 162</p> <p>5.4.2 Features of Hadoop 2.0. 163</p> <p>5.4.3 Yet Another Resource Negotiator (YARN). 164</p> <p>5.4.3 Core components of YARN.. 165</p> <p>5.4.3.1 ResourceManager. 165</p> <p>5.4.3.2 NodeManager. 166</p> <p>5.4.4 YARN Scheduler. 169</p> <p>5.4.4.1 <i>FIFO scheduler</i>. 169</p> <p>5.4.4.2 <i>Capacity Scheduler</i>. 170</p> <p>5.4.4.3 <i>Fair Scheduler</i>. 170</p> <p>5.4.5 Failures in YARN.. 171</p> <p>5.4.5.1ResourceManager failure. 171</p> <p>5.4.5.2 ApplicationMaster failure. 172</p> <p>5.4.5.3 NodeManagerFailure. 172</p> <p>5.4.5.4 Container Failure. 172</p> <p>5.3 HBASE. 173</p> <p>5.4 Apache Cassandra. 176</p> <p>5.5 SQOOP. 177</p> <p>5.6 Flume. 179</p> <p>5.6.1 Flume Architecture. 179</p> <p>5.6.1.1 Event. 180</p> <p>5.6.1.2 Agent. 180</p> <p>5.7 Apache Avro. 181</p> <p>5.8 Apache Pig. 182</p> <p>5.9 Apache Mahout. 183</p> <p>5.10 Apache Oozie. 183</p> <p>5.10.1 Oozie Workflow.. 184</p> <p>5.10.2 Oozie Coordinators. 186</p> <p>5.10.3 Oozie Bundles. 187</p> <p>5.11 Apache Hive. 187</p> <p>5.11 Apache Hive. 187</p> <p>Hive Architecture. 189</p> <p>Hadoop Distributions. 190</p> <p>Chapter 5refresher. 191</p> <p>Conceptual short questions with answers. 194</p> <p>Frequently asked Interview Questions. 199</p> <p>Chapter Objective. 200</p> <p>6.1 Terminologies of Big Data Analytics. 201</p> <p><i>Data Warehouse</i>. 201</p> <p><i>Business Intelligence</i>. 201</p> <p><i>Analytics</i>. 202</p> <p>6.2 Big Data Analytics. 202</p> <p>6.2.1 Descriptive Analytics. 204</p> <p>6.2.2 Diagnostic Analytics. 205</p> <p>6.2.3 Predictive Analytics. 205</p> <p>6.2.4 Prescriptive Analytics. 205</p> <p>6.3 Data Analytics Lifecycle. 207</p> <p>6.3.1 Business case evaluation and Identify the source data. 208</p> <p>6.3.2 Data preparation. 209</p> <p>6.3.3 Data Extraction and Transformation. 210</p> <p>6.3.4 Data Analysis and visualization. 211</p> <p>6.3.5 Analytics application. 212</p> <p>6.4 Big Data Analytics Techniques. 212</p> <p>6.4.1 Quantitative Analysis. 212</p> <p>6.4.3 Statistical analysis. 214</p> <p>6.4.3.1 A/B testing. 214</p> <p>6.4.3.2 Correlation. 215</p> <p>6.4.3.3 Regression. 218</p> <p>6.5 Semantic Analysis. 220</p> <p>6.5.1 Natural Language Processing. 220</p> <p>6.5.2 Text Analytics. 221</p> <p>6.7 Big Data Business Intelligence. 222</p> <p>6.7.1 Online Transaction Processing (OLTP). 223</p> <p>6.7.2 Online Analytical Processing (OLAP). 223</p> <p>6.7.3 Real-Time Analytics Platform (RTAP). 224</p> <p>6.6Big Data Real Time Analytics Processing. 225</p> <p>6.7 Enterprise Data Warehouse. 227</p> <p>Chapter 6 Refresher. 228</p> <p>Concept…”
Full text (MFA users only)
Electronic eBook -
442
Contemporary Ergonomics 1998.
Published 1998Table of Contents: “…Development of a questionnaire to measure attitudes towards virtual reality -- Orientation of blind users on the World Wide Web -- F̃lash, splash and crash:̃ Human factors and the implementation of innovative Web technologies -- Determining ergonomic factors in stress from work demands of nurses -- A risk assessment and control cycle approach to managing workplace stress -- Teleworking: Assessing the risks -- Evaluating teleworking -- case study -- Team organisational mental models: an integrative framework for research -- The impact of ITT on virtual team working in the European automotive industry -- The effect of communication processes upon workers and job efficiency -- A case study of job design in a steel plant -- The effects of age and habitual physical activity on the adjustment to nocturnal shiftwork -- Job design for university technicians: work activity and allocation of function -- Allocation of functions and manufacturing job design based on knowledge requirements -- The need to specify cognition within system requirements -- Analysis of complex communication tasks -- Health and safety as the basis for specifying information systems design requirements -- Cognitive algorithms -- Rapid prototyping in foam of 3D anthropometric computer models in functional postures -- The use of high and low level prototyping methods for product user interfaces -- Creative collaboration in engineering design teams -- Pleasure and product semantics -- A survey of usability practice and needs in Europe -- Cultural influence in usability assessment -- Interface display designs based on operator knowledge requirements -- Understanding what makes icons effective: how subjective ratings can inform design -- Representing uncertainty in decision support systems: the state of the art.…”
Full text (MFA users only)
Electronic eBook -
443
Pediatric incontinence : evaluation and clinical management
Published 2015Full text (MFA users only)
Electronic eBook -
444
Knowledge mining using intelligent agents
Published 2011Full text (MFA users only)
Electronic eBook -
445
Corporate strategy for dramatic productivity surge
Published 2013Table of Contents: “…Instantaneous and spontaneous information sharing / Hiromichi Yasuoka -- ch. 7. The development of a three-minute battery charger / Toru Fujii -- ch. 8. …”
Full text (MFA users only)
Electronic eBook -
446
Accelerating MATLAB with GPU computing : a primer with examples
Published 2014Full text (MFA users only)
Electronic eBook -
447
Swift 2 design patterns : build robust and scalable iOS and Mac OS X game applications
Published 2015Full text (MFA users only)
Electronic eBook -
448
Digitalization of Society and Socio-Political Issues. 1, Digital, Communication, and Culture
Published 2019Table of Contents: “…The Digitalization of Cultural Policies in France 149; Anne BELLON 14.1.…”
Full text (MFA users only)
Electronic eBook -
449
Tumor board review : guideline and case reviews in oncology
Published 2015Full text (MFA users only)
Electronic eBook -
450
Concise encyclopaedia of bioinformatics and computational biology 2e
Published 2014Table of Contents: “….; Akaike Information Criterion; Pedro Larranaga and Concha Bielza; Algorithm; Matthew He; Alignment (Domain Alignment, Repeats Alignment); Jaap Heringa; Alignment Score; Laszlo Patthy; Allele-Sharing Methods (Non-parametric Linkage Analysis).…”
Full text (MFA users only)
Electronic eBook -
451
Networks-on-chip : from implementations to programming paradigms
Published 2014Table of Contents: “…Front Cover; Networks-on-Chip: From Implementations to Programming Paradigms; Copyright; Contents in Brief; Contents; Preface; About the Editor-in-Chief and Authors; Editor-in-Chief; Authors; Part I: Prologue; Chapter 1: Introduction; 1.1 The dawn of the many-core era; 1.2 Communication-centric cross-layer optimizations; 1.3 A baseline design space exploration of NoCs; 1.3.1 Topology; 1.3.2 Routing algorithm; 1.3.3 Flow control; 1.3.4 Router microarchitecture; 1.3.5 Performance metric; 1.4 Review of NoC research; 1.4.1 Research on topologies; 1.4.2 Research on unicast routing.…”
Full text (MFA users only)
Electronic eBook -
452
Optimized cloud resource management and scheduling : theories and practice
Published 2015Full text (MFA users only)
Electronic eBook -
453
Open science by design : realizing a vision for 21st century research
Published 2018Full text (MFA users only)
Electronic eBook -
454
Large Scale Network-Centric Distributed Systems
Published 2014Full text (MFA users only)
Electronic eBook -
455
Machine Learning in Chemical Safety and Health : Fundamentals with Applications.
Published 2022Table of Contents: “…Chapter 3 Flammability Characteristics Prediction Using QSPR Modeling -- 3.1 Introduction -- 3.1.1 Flammability Characteristics -- 3.1.2 QSPR Application -- 3.1.2.1 Concept of QSPR -- 3.1.2.2 Trends and Characteristics of QSPR -- 3.2 Flowchart for Flammability Characteristics Prediction -- 3.2.1 Dataset Preparation -- 3.2.2 Structure Input and Molecular Simulation -- 3.2.3 Calculation of Molecular Descriptors -- 3.2.4 Preliminary Screening of Molecular Descriptors -- 3.2.5 Descriptor Selection and Modeling -- 3.2.6 Model Validation -- 3.2.6.1 Model Fitting Ability Evaluation -- 3.2.6.2 Model Stability Analysis -- 3.2.6.3 Model Predictivity Evaluation -- 3.2.7 Model Mechanism Explanation -- 3.2.8 Summary of QSPR Process -- 3.3 QSPR Review for Flammability Characteristics -- 3.3.1 Flammability Limits -- 3.3.1.1 LFLT and LFL -- 3.3.1.2 UFLT and UFL -- 3.3.2 Flash Point -- 3.3.3 Auto-ignition Temperature -- 3.3.4 Heat of Combustion -- 3.3.5 Minimum Ignition Energy -- 3.3.6 Gas-liquid Critical Temperature -- 3.3.7 Other Properties -- 3.4 Limitations -- 3.5 Conclusions and Future Prospects -- References -- Chapter 4 Consequence Prediction Using Quantitative Property-Consequence Relationship Models -- 4.1 Introduction -- 4.2 Conventional Consequence Prediction Methods -- 4.2.1 Empirical Method -- 4.2.2 Computational Fluid Dynamics (CFD) Method -- 4.2.3 Integral Method -- 4.3 Machine Learning and Deep Learning-Based Consequence Prediction Models -- 4.4 Quantitative Property-Consequence Relationship Models -- 4.4.1 Consequence Database -- 4.4.2 Property Descriptors -- 4.4.3 Machine Learning and Deep Learning Algorithms -- 4.5 Challenges and Future Directions -- References -- Chapter 5 Machine Learning in Process Safety and Asset Integrity Management -- 5.1 Opportunities and Threats -- 5.2 State-of-the-Art Reviews -- 5.2.1 Artificial Neural Networks (ANNs).…”
Full text (MFA users only)
Electronic eBook -
456
Theoretical Computer Science : Proceedings of the 10th Italian Conference on ICTCS '07.
Published 2007Full text (MFA users only)
Electronic eBook -
457
Banking and finance issues in emerging markets.
Published 2018Full text (MFA users only)
Electronic eBook -
458
Symbolic computation and education
Published 2007Full text (MFA users only)
Electronic Conference Proceeding eBook -
459
Progress reports on impedance spectroscopy : measurements, modeling, and application
Published 2017Full text (MFA users only)
Electronic eBook -
460
Stochastic filtering with applications in finance
Published 2010Table of Contents: “…Economic convergence in a filtering framework. 3.3. Ex-ante equity risk premium. 3.4. Concluding remarks -- 4. …”
Full text (MFA users only)
Electronic eBook