Tabla de Contenidos: “…4.15 Reporting Interest on Bonds Bought or Sold -- 4.16 Forfeiture of Interest on Premature Withdrawals -- 4.17 Amortization of Bond Premium -- 4.18 Discount on Bonds -- 4.19 Reporting Original Issue Discount on Your Return -- 4.20 Reporting Income on Market Discount Bonds -- 4.21 Discount on Short-Term Obligations -- 4.22 Stripped Coupon Bonds and Stock -- 4.23 Sale or Retirement of Bonds and Notes -- 4.24 State and City Interest Generally Tax Exempt -- 4.25 Taxable State and City Interest -- 4.26 Tax-Exempt Bonds Bought at a Discount -- 4.27 Treasury Bills, Notes, and Bonds -- 4.28 Interest on United States Savings Bonds -- 4.29 Deferring United States Savings Bond Interest -- 4.30 Minimum Interest Rules -- 4.31 Interest-Free or Below-Market-Interest Loans -- 4.32 Minimum Interest on Seller-Financed Sales -- Chapter 5 Reporting Property Sales -- 5.1 General Tax Rules for Property Sales -- 5.2 How Property Sales Are Classified and Taxed -- 5.3 Capital Gains Rates and Holding Periods -- 5.4 Capital Losses and Carryovers -- 5.5 Capital Losses of Married Couples -- 5.6 Losses May Be Disallowed on Sales to Related Persons -- 5.7 Special Treatment of Gain on Sale of Small Business Stock or Qualified Opportunity Zone Investment -- 5.8 Reporting Capital Asset Sales on Form 8949 and on Schedule D -- 5.9 Counting the Months in Your Holding Period -- 5.10 Holding Period for Securities -- 5.11 Holding Period for Real Estate -- 5.12 Holding Period: Gifts, Inheritances, and Other Property -- 5.13 Calculating Gain or Loss -- 5.14 Amount Realized Is the Total Selling Price -- 5.15 Finding Your Cost -- 5.16 Unadjusted Basis of Your Property -- 5.17 Basis of Property You Inherited or Received as a Gift -- 5.18 Joint Tenancy Basis Rules for Surviving Tenants -- 5.19 Allocating Cost Among Several Assets -- 5.20 How To Find Adjusted Basis…”

Tabla de Contenidos: “…References -- 8 Cybersecurity using artificial intelligence -- 8.1 Introduction -- 8.1.1 Background -- 8.2 Problems with strategy -- 8.2.1 Technical challenges -- 8.2.2 Some nontechnical challenges -- 8.2.3 Some nontechnical challenges -- 8.2.4 Needs to make a good trade-off -- 8.3 Assessment -- 8.4 Conclusions -- References -- Further reading -- 9 Transformers in wildfire detection -- 9.1 Introduction -- 9.1.1 Related works -- 9.1.1.1 Transformers applications -- 9.1.1.1.1 Self-attention for object detection -- 9.1.1.1.2 Self-attention for visual representations -- 9.1.1.1.3 Pretraining and self-training -- 9.1.1.2 Machine learning classification -- 9.2 Methodology -- 9.2.1 Study design -- 9.2.2 The model -- 9.2.3 Feature extraction -- 9.2.4 Feature selection -- 9.2.5 Data acquisition -- 9.2.5.1 Encoder-decoder -- 9.2.6 Method -- 9.2.7 Detection transformer architecture -- 9.3 Results -- 9.4 Conclusion -- References -- 10 Distributed mobile cloud computing services and the internet of things -- 10.1 Introduction -- 10.1.1 Motivation -- 10.1.2 Objectives -- 10.1.3 Scope and organization -- 10.2 Amount of previously published work -- 10.2.1 Internet of Things research -- 10.2.2 Distributed mobile cloud computing research -- 10.2.3 Overall assessment -- 10.3 Internet of things and distributed mobile cloud computing services -- 10.3.1 Experimental setup -- 10.3.1.1 Hardware components -- 10.3.1.2 Software components -- 10.3.1.3 Network infrastructure -- 10.4 Distributed mobile cloud computing and the internet of things -- 10.4.1 Literature review -- 10.4.2 Experimental design -- 10.4.3 Implementation -- 10.4.4 Data collection and analysis -- 10.4.5 Discussion -- 10.5 Results and discussion follow -- 10.5.1 Performance evaluation metrics -- 10.5.1.1 Latency -- 10.5.1.2 Energy consumption -- 10.5.1.3 Computational speed -- 10.5.1.4 Data transfer rate…”

Tabla de Contenidos: “…5.9.4 Study Conclusions and EC Policy Recommendations -- Bibliography -- Chapter 6 - Securing the Internet of Things - Security and Privacy in a HyperconnectedWorld -- 6.1 Introduction -- 6.2 End-to-End Security and Privacy by Design -- 6.3 Physical IoT Security -- 6.3.1 Selected Low-Cost Attacks -- 6.3.2 Key Extraction Attacks and Countermeasures -- 6.4 On Device Security and Privacy -- 6.4.1 Mediated Device Access for Security and Privacy -- 6.4.2 Encryption -- 6.4.3 Integrity -- 6.4.4 Data Minimisation -- 6.5 Unobservable Communication -- 6.5.1 Resisting Network Traffic Analysis -- 6.6 Access Control Based on Policy Management -- 6.7 Security and Privacy in the IoT Cloud -- 6.7.1 Verifiable and Authenticity Preserving Data Processing -- 6.7.2 Structural Integrity and Certification of Virtualized Infrastructure -- 6.7.3 Privacy Preserving Service Usage and Data Handling -- 6.7.4 Confidentiality of (Un-)structured Data -- 6.7.5 Long Term Security and Everlasting Privacy -- 6.7.6 Conclusion -- 6.8 Outlook -- Acknowledgment -- Bibliography -- Chapter 7 - IoT Analytics: Collect, Process, Analyze, and Present Massive Amounts of Operational Data - Research and Innovation Challenges -- 7.1 Introduction -- 7.2 Deep Internet of Things Data Analytics -- 7.2.1 Introduction -- 7.2.2 Designing for Real World Problems -- 7.2.3 Real World Data -- 7.2.4 Data Interoperability -- 7.2.5 Deep Data Analytics Methods -- 7.2.6 Conclusions -- 7.3 Cloud-Based IoT Big Data Platform -- 7.3.1 Introduction -- 7.3.2 Big Data in the Context of IoT -- 7.3.3 Applications of IoT Big Data Analytics -- 7.3.4 Requirements of IoT Big Data Analytic Platform -- 7.3.4.1 Intelligent and dynamic -- 7.3.4.2 Distributed -- 7.3.4.3 Scalable and elastic -- 7.3.4.4 Real-time -- 7.3.4.5 Heterogeneous (unified) -- 7.3.4.6 Security and privacy -- 7.3.5 Cloud-Based IoT Analytic Platform…”

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Tabla de Contenidos: “…Front Cover -- Heat Recovery Steam Generator Technology -- Copyright Page -- Contents -- List of contributors -- 1 Introduction -- Chapter outline -- 1.1 Gas turbine-based power plants -- 1.1.1 Advantages -- 1.1.2 History -- 1.1.3 Outlook -- 1.2 Heat recovery steam generator (HRSG) -- 1.2.1 Role of the HRSG in the power plant -- 1.2.2 Characteristics -- 1.2.3 Types of HRSGs -- 1.2.3.1 Horizontal gas flow, vertical tube, natural circulation design -- 1.2.3.2 Vertical gas flow, horizontal tube, forced circulation design -- 1.2.3.3 Vertical gas flow, horizontal tube, natural circulation design -- 1.2.3.4 Small once-through design -- 1.2.3.5 Large once-through design -- 1.2.3.6 Benson design -- 1.2.3.7 Enhanced oil recovery design -- 1.2.3.8 Very high fired design -- 1.3 Focus and structure of book -- References -- 2 The combined cycle and variations that use HRSGs -- Chapter outline -- 2.1 Introduction -- 2.2 Combining the Brayton and Rankine cycles -- 2.3 The central role of HRSGs in combined cycle design -- 2.3.1 Pressure levels -- 2.3.2 Reheat -- 2.3.3 Other decisions affecting heat recovery -- 2.3.3.1 Amount of surface area -- 2.3.3.2 Surface area sequencing -- 2.3.3.3 Supplementary firing -- 2.3.3.4 Stack temperature -- 2.4 Power cycle variations that use HRSGs -- 2.4.1 Cogeneration -- 2.4.2 Steam power augmentation -- 2.4.3 Integrated gasification combined cycle -- 2.4.4 Solar hybrid -- 2.5 Conclusion -- Reference -- 3 Fundamentals -- Chapter outline -- Nomenclature -- Subscripts -- 3.1 Thermal design -- 3.1.1 Energy balance -- 3.1.2 Economizer -- 3.1.3 Superheater -- 3.1.4 Supplemental firing -- 3.1.5 Split superheater -- 3.1.6 Multiple pressure systems -- 3.1.7 Heat exchanger design -- 3.1.7.1 Pressure drop -- 3.1.7.2 Finned tubing -- 3.1.7.3 Tube arrangement -- 3.1.7.4 Two-phase flow -- 3.1.7.5 Evaporation and circulation…”

Tabla de Contenidos: “…8.2.2 Continuous Probability Distributions -- 8.2.3 Mathematical Expectation and Moments -- 8.2.4 Return Period -- 8.2.5 Common Probability Functions -- 8.2.5.1 Binomial distribution -- 8.2.5.2 Geometric distribution -- 8.2.5.3 Poisson distribution -- 8.2.5.4 Exponential distribution -- 8.2.5.5 Gamma/Pearson Type III distribution -- 8.2.5.6 Normal distribution -- 8.2.5.7 Log-normal distribution -- 8.2.5.8 Uniform distribution -- 8.2.5.9 Extreme-value distributions -- 8.2.5.10 Chi-square distribution -- 8.3 Analysis of Hydrologic Data -- 8.3.1 Estimation of Population Distribution -- 8.3.1.1 Probability distribution of observed data -- 8.3.1.2 Hypothesis tests -- 8.3.1.3 Model selection criteria -- 8.3.2 Estimation of Population Parameters -- 8.3.2.1 Method of moments -- 8.3.2.2 Maximum-likelihood method -- 8.3.2.3 Method of L-moments -- 8.3.3 Frequency Analysis -- 8.3.3.1 Normal distribution -- 8.3.3.2 Log-normal distribution -- 8.3.3.3 Gamma/Pearson Type III distribution -- 8.3.3.4 Log-Pearson Type III distribution -- 8.3.3.5 Extreme-value Type I distribution -- 8.3.3.6 General extreme-value (GEV) distribution -- 8.4 Uncertainty Analysis -- Problems -- 9 Fundamentals of Surface-Water Hydrology I: Rainfall and Abstractions -- 9.1 Introduction -- 9.2 Rainfall -- 9.2.1 Measurement of Rainfall -- 9.2.2 Statistics of Rainfall Data -- 9.2.2.1 Rainfall statistics in the United States -- 9.2.2.2 Secondary estimation of IDF curves -- 9.2.3 Spatial Averaging and Interpolation of Rainfall -- 9.2.4 Design Rainfall -- 9.2.4.1 Return period -- 9.2.4.2 Rainfall duration -- 9.2.4.3 Rainfall depth -- 9.2.4.4 Temporal distribution -- 9.2.4.5 Spatial distribution -- 9.2.5 Extreme Rainfall -- 9.2.5.1 Rational estimation method -- 9.2.5.2 Statistical estimation method -- 9.2.5.3 World-record precipitation amounts -- 9.2.5.4 Probable maximum storm…”

“…The tax reduction amounted up to EUR 14.6 per megawatt hour, about 80% of the full tax rate. …”

“…Gonzalo, Pepe y Rafa son tres hombres que no se conocen entre sí pero que están unidos por un vínculo común: Ramona. Ramonas es una espléndida mujer de unos veintitantos años, alegre y comprensiva, un poco ese ideal que todo hombre busca en su vida. …”

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“…Advancing the science of medicine by targeting a disease more precisely with treatment specific to each patient relies on access to that patient's genomics information and the ability to process massive amounts of genomics data quickly. Although genomics data is becoming a critical source for precision medicine, it is expected to create an expanding data ecosystem. …”

“…Pivot Tables is an essential Excel skill for jobs that involve analyzing and visualizing large amounts of data. Pivot Tables are an interactive way of quickly summarizing large amounts of data by grouping and aggregating data sets and analyzing data clearly and effectively. …”