Academic literature on the topic 'FORTRAN IV (Computer programming language)'
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Journal articles on the topic "FORTRAN IV (Computer programming language)"
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Galassi, Giuseppe, and Richard V. Mattessich. "Some Clarification to the Evolution of the Electronic Spreadsheet." Journal of Emerging Technologies in Accounting 11, no. 1 (December 1, 2014): 99–104. http://dx.doi.org/10.2308/jeta-51114.
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ABSTRACT As early as 1961 Mattessich suggested (in an article in The Accounting Review) to use budget simulation in form of a computerized spreadsheet. This was followed up by him in a mathematical model, outlined in his book Accounting and Analytical Methods (Mattessich 1964a) with a corresponding computer program (in FORTRAN IV on mainframe computers), including illustrations in a companion volume (Simulation of the Firm through a Budget Computer Program, Mattessich 1964b). Five years later (in 1969) Rene Pardo and Remy Landau co-presented “LANPAR” (LANguage for Programming Arrays at Random) at Random Corporation. This electronic spreadsheet type was also used on mainframe computers for budgeting at Bell Canada, AT&T, Bell operating companies, and General Motors. In 1978, Dan Bricklin and Robert Frankston introduced VisiCalc, the first commercialized spreadsheet program for personal desktop (Apple) computers. This program became the trailblazer for future developments of electronic spreadsheets.
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Van Snyder, W. "Scientific Programming in Fortran." Scientific Programming 15, no. 1 (2007): 3–8. http://dx.doi.org/10.1155/2007/930816.
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The Fortran programming language was designed by John Backus and his colleagues at IBM to reduce the cost of programming scientific applications. IBM delivered the first compiler for its model 704 in 1957. IBM's competitors soon offered incompatible versions. ANSI (ASA at the time) developed a standard, largely based on IBM's Fortran IV in 1966. Revisions of the standard were produced in 1977, 1990, 1995 and 2003. Development of a revision, scheduled for 2008, is under way. Unlike most other programming languages, Fortran is periodically revised to keep pace with developments in language and processor design, while revisions largely preserve compatibility with previous versions. Throughout, the focus on scientific programming, and especially on efficient generated programs, has been maintained.
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Foster, I. T., and K. M. Chandy. "FORTRAN M - A Language for Modular Parallel Programming." Journal of Parallel and Distributed Computing 26, no. 1 (April 1995): 24–35. http://dx.doi.org/10.1006/jpdc.1995.1044.
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Cheng, H. H. "Extending C and FORTRAN for Design Automation." Journal of Mechanical Design 117, no. 3 (September 1, 1995): 390–95. http://dx.doi.org/10.1115/1.2826691.
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The CH programming language is designed to be a superset of C. CH bridges the gap between C and FORTRAN; it encompasses all the programming capabilities of FORTRAN 77 and consists of features of many other programming languages and software packages. Unlike other general-purpose programming languages, CH is designed to be especially suitable for applications in mechanical systems engineering. Because of our research interests, many programming features in CH have been implemented for design automation, although they are useful in other applications as well. In this paper we will describe these new programming features for design automation, as they are currently implemented in CH in comparison with C and FORTRAN 77.
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Nofre, David. "The Politics of Early Programming Languages." Historical Studies in the Natural Sciences 51, no. 3 (June 1, 2021): 379–413. http://dx.doi.org/10.1525/hsns.2021.51.3.379.
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There probably has never been such a controversial programming language as Algol. In the early 1960s the disciplinary success of the so-called Algol project in helping to forge the discipline of computer science was not matched by a significant adoption of the Algol language, in any of its three versions. This contrast is even more striking when considering the contemporary success of IBM’s Fortran, a language that, like Algol, was also conceived for scientific computation, but unlike Algol, initially only available for IBM computers. Through extensive archival research, this article shows how the relentless pursuit of a still better language that came to dominate the agenda of the Algol project brought to the fore the tension between the research-driven dimension of the project and the goal of developing a reliable programming language. Such a strong research-oriented agenda increased IBM’s doubts about a project that the firm already felt little urge to support. Yet IBM did not want to appear as obstructing the development of either Algol or Cobol, even if these “common languages” posed a clear risk to the firm’s marketing model. The US Department of Defense’s endorsement of Cobol and the rising popularity of Algol in Europe convinced IBM to push for the use of Fortran in Western Europe in order to protect the domestic market. IBM’s action in support of Fortran reminds us of the power imbalances that have shaped computer science.
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Schreiber, Robert. "High Performance Fortran, Version 2." Parallel Processing Letters 07, no. 04 (December 1997): 437–49. http://dx.doi.org/10.1142/s0129626497000425.
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This paper introduces the ideas that underly the data-parallel language High Performance Fortran (HPF) and the new ideas in version 2 of HPF. It first reviews HPF's key language elements. It discusses the meaning of data parallelism and the limitations of HPF version 1 as a data-parallel programming language. The second part of the paper is a review of the development of version 2 of HPF. The extended language, under development in 1996, includes a richer data mapping capability; an extension to the independent loop that allows reduction operations in the loop range; a means for directing the mapping of computation as well as data; and a way to specify concurrent execution of several parallel tasks on disjoint subsets of processors.
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Reina, Reina, and Josef Bernadi Gautama. "Perbandingan Bubble Sort dengan Insertion Sort pada Bahasa Pemrograman C dan Fortran." ComTech: Computer, Mathematics and Engineering Applications 4, no. 2 (December 1, 2013): 1106. http://dx.doi.org/10.21512/comtech.v4i2.2553.
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Sorting is a basic algorithm studied by students of computer science major. Sorting algorithm is the basis of other algorithms such as searching algorithm, pattern matching algorithm. Bubble sort is a popular basic sorting algorithm due to its easiness to be implemented. Besides bubble sort, there is insertion sort. It is lesspopular than bubble sort because it has more difficult algorithm. This paper discusses about process time between insertion sort and bubble sort with two kinds of data. First is randomized data, and the second is data of descending list. Comparison of process time has been done in two kinds of programming language that is C programming language and FORTRAN programming language. The result shows that bubble sort needs more time than insertion sort does.
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Raman, K. V. "Some Features of Java Language Illustrated through Examples from Chemistry." Mapana - Journal of Sciences 1, no. 2 (July 3, 2003): 22–56. http://dx.doi.org/10.12723/mjs.2.5.
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Computer programming has been used effectively by theoretical chemists and organic chemists to solve various types of problem in chemistry. Initially the languages used for computations in chemistry were FORTRAN and BASIC. Later the Pascal language was used for solving problems in chemistry and physics. Recently the languages C and C++ and Java have been used to solve problems in chemistry. In this paper I will illustrate features of C, C++ choosing examples from chemistry. Computer programming has been used effectively by theoretical chemists and organic chemists to solve various types of problem in chemistry. Initially the languages used for computations in chemistry were FORTRAN and BASIC. Later the Pascal language was used for solving problems in chemistry and physics. Recently the languages C and C++ and Java have been used to solve problems in chemistry. In this paper I will illustrate features of C, C++ choosing examples from chemistry. Some examples presented in this these languages are Program to calculate reduced mass of homo diatomic or hetero diatomic Program to calculate the molecular weight of a tetra atomic system ABCD Program to calculate NMR frequencies of spin 1/2 nuclei only Program to calculate NMR and ESR frequencies The examples presented in Java 2 are Program to calculate unit cell dimension of a crystal Program to generate the chair form and boat form of cyclohexane. The examples presented in this monograph will help researchers in theoretical chemistry and organic chemistry to develop their own software.
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Piekarska, W., M. Kubiak, Z. Saternus, and K. Rek. "Computer Modelling of Thermomechanical Phenomena in Pipes Welded using a Laser Beam." Archives of Metallurgy and Materials 58, no. 4 (December 1, 2013): 1237–42. http://dx.doi.org/10.2478/amm-2013-0156.
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Abstract This study concerns numerical modelling and computer simulation of thermomechanical phenomena accompanying spiral welding of pipes made of stainless steel X5CrNi18-10 using a laser beam. Based on Abaqus FEA software, 3D numerical analysis was performed. Power distribution of spirally moving heat source was implemented into additional DFLUX subroutine, written in Fortran programming language. Thermomechanical properties of steel changing with temperature were taken into account in the analysis. The efficiency of material melting by different welding sources as well as the influence of heat load on the shape of melted zone, deformation of welded pipe and residual stress were examined.
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Watanobe, Yutaka, and Nikolay Mirenkov. "Algorithmic Transparency of Large-Scale *AIDA Programs." International Journal of Software Engineering and Knowledge Engineering 30, no. 09 (September 2020): 1263–88. http://dx.doi.org/10.1142/s0218194020500345.
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Programming in pictures is an approach where pictures and moving pictures are used as super-characters to represent the features of computational algorithms and data structures, as well as for explaining the models and application methods involved. *AIDA is a computer language that supports programming in pictures. This language and its environment have been developed and promoted as a testbed for various innovations in information technology (IT) research and implementation, including exploring the compactness of the programs and their adaptive software systems, and obtaining better understanding of information resources. In this paper, new features of the environment and methods of their implementation are presented. They are considered within a case study of a large-scale module of a nuclear safety analysis system to demonstrate that *AIDA language is appropriate for developing efficient codes of serious applications and for providing support, based on folding/unfolding techniques, enhancing the readability, maintainability and algorithmic transparency of programs. Features of this support and the code efficiency are presented through the results of a computational comparison with a FORTRAN equivalent.
Dissertations / Theses on the topic "FORTRAN IV (Computer programming language)"
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Borbinha, Jorge Cebola. "Organ Dose Estimates in Thorax CT: Voxel Phantom Organ Matching With Individual Patient Anatomy." Master's thesis, 2017. http://hdl.handle.net/10362/29982.
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Given the continuous usage and spread of computed tomography (CT), the potential
harmful e↵ects and the radiation dose to the patient have become high interest topics
among the scientific community.
The main objective of this investigation was to modify existing three-dimensional (3D)
voxel phantom models to resemble real patients as much as possible, trying to progress the concept of a more personalized patient dosimetry. This work focused essentially in one of the biggest and most radiosensitive organs in the thorax, the lungs. Additionally, the variations of organ doses when a standard phantom is used instead were studied.
During the course of this work a FORTRAN-based program was developed, which is
able to semi-automatically modify the volumetric information of organs of interest in a
standard voxel phantom (Female ICRP Adult Reference). The voxel resolution was also
altered so the phantom’s diameters match the patient’s ones. Monte Carlo (MC) PENELOPE simulation code was used to mimic CT scan conditions and, therefore, generate 2D projections, used for visual organ matching with clinical patient CT images, and access organ dose in both phantoms (ICRP standard and ICRP modified).
The main results reported that matching the voxel phantom’s size and lungs provides
organ dose values significantly di↵erent from the ones measured in the ICRP reference
phantom. Voxel models matched to patients’ size and overall anatomy allow increased
accuracy in organ dose estimation, which, as reported by this study, can su↵er from up
to 20% underestimation and 40% overestimation.
This study demonstrates that voxel phantoms developed using single patient data
provide a better and more precise organ dose assessment by MC methods than a standard phantom. The presented methodology should be of interest for dose optimization studies and quick enough for routine clinical use.
Books on the topic "FORTRAN IV (Computer programming language)"
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Rodman, James P. FORTRAN IV programming for microcomputers. [Alliance, OH]: J.P. Rodman, 1986.
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McKeown, Patrick G. Structured programming using WATFIV. San Diego: Harcourt Brace Jovanovich, 1985.
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B, Moore John. Structured Fortran with WATFIV: Text and reference. 3rd ed. Reston, Va: Reston Pub. Co., 1985.
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WATFIV: Structured programming and problem solving. Menlo Park, Calif: Benjamin/Cummings Pub. Co., 1985.
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Evett, Jack B. Fortran programming. 2nd ed. San Jose, Calif: Engineering Press, 1987.
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R, Philips Ivor, and Lahey Thomas M, eds. Fortran 90 programming. Wokingham, England: Addison-Wesley, 1994.
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Joyce, Calderbank Valerie, ed. Programming in FORTRAN. 3rd ed. London: Chapman and Hall, 1989.
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Ribar, L. John. FORTRAN programming for Windows. Berkeley, Calif: Osborne McGraw-Hill, 1993.
Find full textBook chapters on the topic "FORTRAN IV (Computer programming language)"
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Sakagami, Hitoshi. "Three-Dimensional Fluid Code with XcalableMP." In XcalableMP PGAS Programming Language, 165–79. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7683-6_6.
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AbstractIn order to adapt parallel computers to general convenient tools for computational scientists, a high-level and easy-to-use portable parallel programming paradigm is mandatory. XcalableMP, which is proposed by the XcalableMP Specification Working Group, is a directive-based language extension for Fortran and C to easily describe parallelization in programs for distributed memory parallel computers. The Omni XcalableMP compiler, which is provided as a reference XcalableMP compiler, is currently implemented as a source-to-source translator. It converts XcalableMP programs to standard MPI programs, which can be easily compiled by the native Fortran compiler and executed on most of parallel computers. A three-dimensional Eulerian fluid code written in Fortran is parallelized by XcalableMP using two different programming models with the ordinary domain decomposition method, and its performances are measured on the K computer. Programs converted by the Omni XcalableMP compiler prevent native Fortran compiler optimizations and show lower performance than that of hand-coded MPI programs. Finally almost the same performances are obtained by using specific compiler options of the native Fortran compiler in the case of a global-view programming model, but performance degradation is not improved by specifying any native compiler options when the code is parallelized by a local-view programming model.
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Fehr, Hans, and Fabian Kindermann. "Fortran 90: A simple programming language." In Introduction to Computational Economics Using Fortran. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198804390.003.0004.
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Before diving into the art of solving economic problems on a computer, we want to give a short introduction into the syntax and semantics of Fortran 90. As describing all features of the Fortran language would probably fill some hundred pages, we concentrate on the basic features that will be needed to follow the rest of this textbook. Nevertheless, there are various Fortran tutorials on the Internet that can be used as complementary literature. Fortran is pretty old; it is actually considered the first known higher programming language. Going back to a proposal made by John W. Backus, an IBM programmer, in 1953, the term Fortran is derived from The IBM Formula Translation System. Before the release of the first Fortran compiler in April 1957, people used to use assembly languages. The introduction of a higher programming language compiler tremendously reduced the number of code lines needed to write a program. Therefore, the first release of the Fortran programming language grew pretty fast in popularity. From 1957 on, several versions followed the initial Fortran version, namely FORTRAN II and FORTRAN III in 1958, and FORTRAN IV in 1961. In 1966, the American Standards Association (now known as the ANSI) approved a standardized American Standard Fortran. The programming language defined on this standard was called FORTRAN 66. Approving an updated standard in 1977, the ANSI paved the way for a new version of Fortran known as FORTRAN 77. This version became popular in computational economics during the late 80s and early 90s. More than 13 years later, the Fortran 90 standard was released by both the International Organization for Standardization (ISO) and ANSI consecutively. With Fortran 90, the fixed format standard was exchanged by a free format standard and, in addition, many new features like modules, recursive procedures, derived data types, and dynamic memory allocation made the language much more flexible. From Fortran 90 on, there has only been one major revision, in 2003, which introduced object oriented programming features into the Fortran language. However, as object-oriented programming will not be needed and Fortran 90 is by far the more popular language, we will focus on the 1990 version in this book.
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Petersen, Wesley, and Peter Arbenz. "Applications." In Introduction to Parallel Computing. Oxford University Press, 2004. http://dx.doi.org/10.1093/oso/9780198515760.003.0007.
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Linear algebra is often the kernel of most numerical computations. It deals with vectors and matrices and simple operations like addition and multiplication on these objects. Vectors are one-dimensional arrays of say n real or complex numbers x0, x1, . . . , xn−1. We denote such a vector by x and think of it as a column vector, On a sequential computer, these numbers occupy n consecutive memory locations. This is also true, at least conceptually, on a shared memory multiprocessor computer. On distributed memory multicomputers, the primary issue is how to distribute vectors on the memory of the processors involved in the computation. Matrices are two-dimensional arrays of the form The n · m real (complex) matrix elements aij are stored in n · m (respectively 2 · n ·m if complex datatype is available) consecutive memory locations. This is achieved by either stacking the columns on top of each other or by appending row after row. The former is called column-major, the latter row-major order. The actual procedure depends on the programming language. In Fortran, matrices are stored in column-major order, in C in row-major order. There is no principal difference, but for writing efficient programs one has to respect how matrices are laid out. To be consistent with the libraries that we will use that are mostly written in Fortran, we will explicitly program in column-major order. Thus, the matrix element aij of the m×n matrix A is located i+j · m memory locations after a00. Therefore, in our C codes we will write a[i+j*m]. Notice that there is no such simple procedure for determining the memory location of an element of a sparse matrix. In Section 2.3, we outline data descriptors to handle sparse matrices. In this and later chapters we deal with one of the simplest operations one wants to do with vectors and matrices: the so-called saxpy operation (2.3). In Tables 2.1 and 2.2 are listed some of the acronyms and conventions for the basic linear algebra subprograms discussed in this book.
Conference papers on the topic "FORTRAN IV (Computer programming language)"
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Thompson, Sean, and Harry H. Cheng. "Computer-Aided Displacement Analysis of Spatial Mechanisms." In ASME 1994 Design Technical Conferences collocated with the ASME 1994 International Computers in Engineering Conference and Exhibition and the ASME 1994 8th Annual Database Symposium. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/detc1994-0052.
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Abstract Recently, Cheng (1993) introduced the CH programming language. CH is designed to be a superset of ANSI C with all programming features of FORTRAN. Many programming features in CH are specifically designed and implemented for design automation. Handling dual number as a basic built-in data type in the language is one example. Formulas with dual numbers can be translated into CH programming statements as easily as formulas with real and complex numbers. In this paper we will show that both formulation and programming with dual numbers are remarkably simple for analysis of complicated spatial mechanisms within the programming paradigm of CH. With computational capabilities for dual formulas in mind, formulas for analysis of spatial mechanisms are derived differently from those intended for implementation in computer programming languages without dual data type. We will demonstrate some formulation and programming techniques in the programming paradigm of CH through a displacement analysis of the RCRCR five-link spatial mechanism. A CH program that can obtain both numerical and graphical results for complete displacement analysis of the RCRCR mechanism will be presented.
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Pasch, Jim, Tom Conboy, Darryn Fleming, Matt Carlson, and Gary Rochau. "Steady State Supercritical Carbon Dioxide Recompression Closed Brayton Cycle Operating Point Comparison With Predictions." In ASME Turbo Expo 2014: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/gt2014-25777.
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The U.S. Department of Energy Office of Nuclear Energy (DOE-NE) supercritical carbon dioxide recompression closed Brayton cycle (RCBC) test assembly (TA) construction has been completed to its original design and resides at Sandia National Laboratories, New Mexico. Commissioning tests were completed in July 2012, followed by a number of tests in both the recompression CBC configuration, and in a bottoming cycle configuration that is proprietary to a current customer. While the test assembly has been developed and installed to support testing, a computer model of the loop, written in Fortran programming language, has also been developed. The purpose of this iterative model is to facilitate data interpretation, guide test assembly design modifications, develop control schemes, and serve as a foundation from which to develop a transient model. Of central utility is its modular nature, which has already been leveraged to develop a customer’s bottoming cycle configuration. Verification that the model uses appropriate physical representations of components and processes, is performing as intended, and validation that the model accurately reproduces test data, are necessary activities. Completion of the model’s verification and validation (V&V) supports the long-term goal of commercializing the RCBC for a sodium fast reactor. This paper presents verification results of certain subprocesses of the iterative computer model. Verification of these subprocesses was completed with positive results. While an adequate range of data for complete and thorough validation do not yet exist, comparison of subprocess predictions with data from a single, representative operating point are presented as are explanations for differences. Recommendations for activities necessary to complete subprocess and model validation are given. The RCBC iterative computer model V&V process should be revisited following completion of these recommended actions and the generation of steady state data while operating near the test assembly design point.