Search Results - computer programs testing data processing.

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Table of Contents: “...Hypercube Supercomputing; Introduction; Design Issues for Multiprocessor Computers; The Hypercube Multiprocessor Computer; Hardware, Operating System, Software; The Hypercube Interconnection Network; Programming the Hypercube; Partitioning Techniques; Application Examples; Application Programs; Seismic Data Processing Example; Conclusions; References; Chapter 8. ...”
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Table of Contents: “...Unifying Data for CAD-Frames and Testing --...”
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Table of Contents: “...Game -- 7.3.2 The Active Object Design -- 7.3.3 The Implementation -- 7.3.4 The Port for ARM Cortex-M3 -- 7.3.5 Testing -- 7.4 Summary -- Chapter 8 Design of QF -- 8.1 Handling Errors and Exceptional Conditions -- 8.2 Memory Management -- 8.3 Mutual Exclusion and Blocking -- 8.4 Active Objects -- 8.5 Event Management in QF -- 8.6 Event Delivery Mechanisms in QF -- 8.9 Deferring and Recalling Events in QF -- 8.7 Time Events -- 8.8 Summary -- Chapter 9 Implementation of QF -- 9.1 Code Organization -- 9.2 Critical Section in QF -- 9.3 General QF Policies Enforced by Assertions -- 9.4 Active Object class -- 9.5 Native QF Event Queue -- 9.6 Native QF Memory Pool -- 9.7 Native QF Priority Set -- 9.8 Native QF Scheduler -- Chapter 10 Porting QF -- 10.1 QF Porting Guide -- 10.2 QF on Bare-Metal Targets (the Vanilla Port) -- 10.3 Using QF with a preemptive Real-Time Kernel (æC/OS-II) -- 10.4 QF port to a POSIX-Compliant OS (Linux) -- 10.5 Summary -- Chapter 11 Conclusion -- 11.2 Rules for Developing Event-Driven Embedded Applications -- 11.3 Heuristics -- 11.4 Sizing Event Queues and Event Pools -- 11.5 System Integration -- 11.6 Summary of Key Elements -- 11.7 An Invitation -- Appendix A QK: A Single-Stack Preemptive Kernel -- A.2 Run-to-Completion Processing -- A.3 Synchronous and Asynchronous Preemptions -- A.4 Stack Utilization -- A.4 Comparison with a Traditional RTOS -- A.5 Summary -- Appendix B QS: Software Tracing for Event Driven Systems -- B.1 Software Tracing Concepts -- B.2 Structure of QS Trace Records -- B.3 QS Filters -- B.4 QS Data Protocol -- B.5 QS Trace Buffer -- B.6 Configuring and Porting QS -- B.7 Summary -- Appendix C Inheriting Entire State Models in C++ -- C.1 Statechart Refinement Example in C++ -- C.3 Caveats -- C.4 Summary -- Appendix D Guide to Notation -- D.1 Class Diagrams -- D.2 Statechart Diagrams -- D.3 Sequence Diagrams -- D.4 Timing Diagrams -- Appendix E CD-ROM -- E.1 Source Code Structure -- E.2 Installation -- E.3 Licensing -- E.4 Answers to the Exercises -- E.5 QP Reference Guide (Doxygen) -- E.6 Resources -- Bibliography -- Index....”
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Table of Contents: “...Paper-based patient records -- Computer-based patient records -- Aims of a patient data management process -- Data, information, and knowledge -- Single tables and their limitations -- Multiple tables : where to put the data, relationships among tables, and creating a database -- Relational database management systems : normalization (Codd's rules) -- From data model to database software -- Integrity : anticipating and preventing data accuracy problems -- Queries, forms, and reports -- Programming for greater software control -- Turning ideas into a useful tool : eNICU, point of care database software for the NICU -- Making eNICU serve your own needs -- Single versus multiple users -- Backup and recovery : assuring your data persists -- Security : controlling access and protecting patient confidentiality -- Asking questions of a data set : crafting a conceptual framework and testable hypothesis -- Stata : a software tool to analyze data and produce graphical displays -- Preparing to analyze data -- Variable types -- Measurement values vary : describing their distribution and summarizing them quantitatively -- Data from all versus some : populations and samples -- Estimating population parameters : confidence intervals -- Comparing two sample means and testing a hypothesis -- Type I and type II error in a hypothesis test, power, and sample size -- Comparing proportions : introduction to rates and odds -- Stratifying the analysis of dichotomous outcomes : confounders and effect modifiers; the Mantel-Haenszel method -- Ways to measure and compare the frequency of outcomes, and standardization to compare rates -- Comparing the means of more than two samples -- Assuming little about the data : nonparametric methods of hypothesis testing -- Correlation : measuring the relationship between two continuous variables -- Predicting continuous outcomes : univariate and multivariate linear regression -- Predicting dichotomous outcomes : logistic regression, and receiver operating characteristic -- Predicting outcomes over time : survival analysis -- Choosing variables and hypotheses : practical considerations....”