Publications

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2019
Dawood, Hend. "On Some Algebraic and Order-Theoretic Aspects of Machine Interval Arithmetic." Online Mathematics Journal 1, no. 2 (2019): 1-13. Abstracton_some_algebraic_and_order-theoretic_aspects_of_machine_interval_arithmetic.pdfWebsite

Interval arithmetic is a fundamental and reliable mathematical machinery for scientific computing and for addressing uncertainty in general. In order to apply interval mathematics to real life uncertainty problems, one needs a computerized (machine) version thereof, and so, this article is devoted to some mathematical notions concerning the algebraic system of machine interval arithmetic. After formalizing some purely mathematical ingredients of particular importance for the purpose at hand, we give formal characterizations of the algebras of real intervals and machine intervals along with describing the need for interval computations to cope with uncertainty problems. Thereupon, we prove some algebraic and order-theoretic results concerning the structure of machine intervals.

keywords: Interval mathematics; Machine interval arithmetic; Outward rounding; Floating-point arithmetic; Machine monotonicity; Dense orders; Orderability of intervals; Symmetricity; Singletonicity; Subdistributive semiring; S-semiring.

2018
Revol, Nathalie, Baker R. Kearfott, William Edmonson, Wolff J. von Gudenberg, Guillaume Melquiond, George Corliss, Hend Dawood, Christian Keil, Michel Hack, Ned Nedialkov et al. "IEEE Standard for Interval Arithmetic (Simplified)." IEEE Std 1788.1-2017 (2018): 1-38. AbstractWebsite

This standard is a simplified version and a subset of the IEEE Std 1788TM-2015 for Interval Arithmetic and includes those operations and features of the latter that in the the editors view are most commonly used in practice. IEEE Std 1788.1-2017 specifies interval arithmetic operations based on intervals whose endpoints are IEEE Std 754TM-2008 binary64 floating-point numbers and a decoration system for exception-free computations and propagation of properties of the computed results.A program built on top of an implementation of IEEE Std 1788.1-2017 should compile and run, and give identical output within round off, using an implementation of IEEE Std 1788-2015, or any superset of the former.Compared to IEEE Std 1788-2015, this standard aims to be minimalistic, yet to cover much of the functionality needed for interval computations. As such, it is more accessible and will be much easier to implement, and thus will speed up production of implementations.

Corcoran, John, and Hend Dawood. Applied Logic Flowchart., 2018. Abstractapplied_logic_flowchart.pdf

The dynamically combined deductive and hypothetico-deductive method has been available to objective investigators since ancient times. Only in the last half-century has it been taught in courses on scientific method and critical thinking. The below chart for teaching and applying it is only about thirty years old.

Corcoran, John, and Hend Dawood. Logical Methodology Chart., 2018. Abstractlogical_methodology_chart.pdf

Readers of this chart will note its similarity to another which charts a very different method with very different goals.This method aims at knowledge of validity and invalidity; the other aims at knowledge of truth and falsity.

Dawood, Hend. InCLosure (Interval enCLosure): A Language and Environment for Reliable Scientific Computing. 1.0 ed. Department of Mathematics, Faculty of Science, Cairo University, 2018. AbstractWebsite

InCLosure (Interval enCLosure) is a Language and Environment for Reliable Scientific Computing. InCLosure, provides rigorous and reliable results in arbitrary precision. From its name, InCLosure (abbreviated as "InCL") focuses on "enclosing the exact real result in an interval". The interval result is reliable and can be as narrow as possible.
InCLosure supports arbitrary precision in both real and interval computations. In real arithmetic, the precision is arbitrary in the sense that it is governed only by the computational power of the machine (default is 20 significant digits). The user can change the default precision according to the requirements of the application under consideration. Since interval arithmetic is defined in terms of real arithmetic, interval computations inherit the arbitrary precision of real arithmetic with an added property that the interval subdivision method is provided with an arbitrary number of subdivisions which is also governed only by the computational power of the machine. The user can get tighter and tighter guaranteed interval enclosures by setting the desired number of subdivisions to cope with the problem at hand.
All the computations defined in terms of real and interval arithmetic (e.g., real and interval automatic differentiation) inherit the same arbitrary precision.
InCLosure is written in Lisp, the most powerful and fast language in scientific computations. InCLosure provides easy user interface, detailed documentation, clear and fast results. Anyone can compute with InCLosure.

Dawood, Hend. InCLosure (Interval enCLosure): A Language and Environment for Reliable Scientific Computing. 2.0 ed. Department of Mathematics, Faculty of Science, Cairo University, 2018. AbstractWebsite

InCLosure (Interval enCLosure) is a Language and Environment for Reliable Scientific Computing. InCLosure, provides rigorous and reliable results in arbitrary precision. From its name, InCLosure (abbreviated as "InCL") focuses on "enclosing the exact real result in an interval". The interval result is reliable and can be as narrow as possible.
InCLosure supports arbitrary precision in both real and interval computations. In real arithmetic, the precision is arbitrary in the sense that it is governed only by the computational power of the machine (default is 20 significant digits). The user can change the default precision according to the requirements of the application under consideration. Since interval arithmetic is defined in terms of real arithmetic, interval computations inherit the arbitrary precision of real arithmetic with an added property that the interval subdivision method is provided with an arbitrary number of subdivisions which is also governed only by the computational power of the machine. The user can get tighter and tighter guaranteed interval enclosures by setting the desired number of subdivisions to cope with the problem at hand.
All the computations defined in terms of real and interval arithmetic (e.g., real and interval automatic differentiation) inherit the same arbitrary precision.
InCLosure is written in Lisp, the most powerful and fast language in scientific computations. InCLosure provides easy user interface, detailed documentation, clear and fast results. Anyone can compute with InCLosure.

2017
Dawood, Hend, and Yasser Dawood. Investigations into a Formalized Theory of Interval Differentiation. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2017.
Dawood, Hend, and Yasser Dawood. On the Mathematical Foundations of Algorithmic Differentiation. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2017.
2016
Dawood, Hend, and Yasser Dawood. The Form of the Uncertain: On the Mathematical Structures of Uncertainty. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2016.
Dawood, Hend, and Yasser Dawood. Interval Algerbras: A Formalized Treatment. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2016.
2015
Revol, Nathalie, Baker R. Kearfott, William Edmonson, Wolff J. von Gudenberg, Guillaume Melquiond, George Corliss, Hend Dawood, Christian Keil, Michel Hack, Ned Nedialkov et al. "IEEE Standard for Interval Arithmetic." IEEE Std 1788-2015 (2015): 1-97. AbstractWebsite

This standard specifies basic interval arithmetic (IA) operations selecting and following one of the commonly used mathematical interval models. This standard supports the IEEE 754 floating point formats of practical use in interval computations. Exception conditions are defined, and standard handling of these conditions is specified. Consistency with the interval model is tempered with practical considerations based on input from representatives of vendors, developers and maintainers of existing systems. The standard provides a layer between the hardware and the programming language levels. It does not mandate that any operations be implemented in hardware. It does not define any realization of the basic operations as functions in a programming language.

2014
Dawood, Hend, and Yasser Dawood. On Some Order-theoretic Aspects of Interval Algebras. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2014.
Dawood, Hend. "Interval Mathematics as a Potential Weapon against Uncertainty." In Mathematics of Uncertainty Modeling in the Analysis of Engineering and Science Problems. Hershey, PA: IGI Global, 2014. Abstractinterval_mathematics_as_a_potential_weapon_against_uncertainty.pdf

This chapter is devoted to introducing the theories of interval algebra to people who are interested in applying the interval methods to uncertainty analysis in science and engineering. In view of this purpose, we shall introduce the key concepts of the algebraic theories of intervals that form the foundations of the interval techniques as they are now practised, provide a historical and epistemological background of interval mathematics and uncertainty in science and technology, and finally describe some typical applications that clarify the need for interval computations to cope with uncertainty in a wide variety of scientific disciplines.

Keywords: Interval mathematics, Uncertainty, Quantitative Knowledge, Reliability, Complex interval arithmetic, Machine interval arithmetic, Interval automatic differentiation, Computer graphics, Ray tracing, Interval root isolation.

2013
Dawood, Hend, and Yasser Dawood. A Dependency-Aware Interval Algebra. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2013.
Dawood, Hend, and Yasser Dawood. Logical Aspects of Interval Dependency. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2013.
2012
Dawood, Hend. Interval Mathematics: Foundations, Algebraic Structures, and Applications. Cairo: Cairo University, 2012. Abstractinterval_mathematics_msc_thesis_by_hend_dawood.pdf

We begin by constructing the algebra of classical intervals and prove that it is a nondistributive abelian semiring. Next, we formalize the notion of interval dependency, along with discussing the algebras of two alternate theories of intervals: modal intervals, and constraint intervals. With a view to treating some problems of the present interval theories, we present an alternate theory of intervals, namely the "theory of optimizational intervals", and prove that it constitutes a rich S-field algebra, which extends the ordinary field of the reals, then we construct an optimizational complex interval algebra. Furthermore, we define an order on the set of interval numbers, then we present the proofs that it is a total order, compatible with the interval operations, dense, and weakly Archimedean. Finally, we prove that this order extends the usual order on the reals, Moore's partial order, and Kulisch's partial order on interval numbers.

Keywords:
Classical interval arithmetic, Machine interval arithmetic, Interval dependency, Constraint intervals, Modal intervals, Classical complex intervals, Optimizational intervals, Optimizational complex intervals, S-field algebra, Ordering subsets of the reals, Interval arithmetic, Ordering interval numbers, Ordinal power, Total order, Well order, Order compatibilty, Weak Archimedeanity, Dedekind completeness, Interval lattice, Interval order topology, Moore's partial order, Kulisch's partial order.

2011
Dawood, Hend. Theories of Interval Arithmetic: Mathematical Foundations and Applications. Saarbr├╝cken: LAP Lambert Academic Publishing, 2011. Abstractexcerptoftheoriesofintervalarithmeticlap2011-henddawood.pdfWebsite

Reviews

"This new book by Hend Dawood is a fresh introduction to some of the basics of interval computation. It stops short of discussing the more complicated subdivision methods for converging to ranges of values, however it provides a bit of perspective about complex interval arithmetic, constraint intervals, and modal intervals, and it does go into the design of hardware operations for interval arithmetic, which is something still to be done by computer manufacturers."
   - Ramon E. Moore, (The Founder of Interval Computations)
   Professor Emeritus of Computer and Information Science, Department of Mathematics, The Ohio State University, Columbus, U.S.A.

"A popular math-oriented introduction to interval computations and its applications. This short book contains an explanation of the need for interval computations, a brief history of interval computations, and main interval computation techniques. It also provides an impressive list of main practical applications of interval techniques."
   - Vladik Kreinovich, (International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems)
   Professor of Computer Science, University of Texas at El Paso, El Paso, Texas, U.S.A.

"I am delighted to see one more Egyptian citizen re-entering the field of interval mathematics invented in this very country thousands years ago."
   - Marek W. Gutowski,
   Institute of Physics, Polish Academy of Sciences, Warszawa, Poland

Book Description

Scientists are, all the time, in a struggle with uncertainty which is always a threat to a trustworthy scientific knowledge. A very simple and natural idea, to defeat uncertainty, is that of enclosing uncertain measured values in real closed intervals. On the basis of this idea, interval arithmetic is constructed. The idea of calculating with intervals is not completely new in mathematics: the concept has been known since Archimedes, who used guaranteed lower and upper bounds to compute his constant Pi. Interval arithmetic is now a broad field in which rigorous mathematics is associated with scientific computing. This connection makes it possible to solve uncertainty problems that cannot be efficiently solved by floating-point arithmetic. Today, application areas of interval methods include electrical engineering, control theory, remote sensing, experimental and computational physics, chaotic systems, celestial mechanics, signal processing, computer graphics, robotics, and computer-assisted proofs. The purpose of this book is to be a concise but informative introduction to the theories of interval arithmetic as well as to some of their computational and scientific applications.

2010
Dawood, Hend, and Yasser Dawood. On the Metamathematics of the Theory of Interval Numbers. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2010.
2009
Dawood, Hend. Interval Arithmetic: A History against Uncertainty. Giza: Cairo University Interval Arithmetic Research Group (CUIA), Cairo University, 2009.
2007
Dawood, Hend. Interval Arithmetic: Accurate Self-Validating Arithmetic for Digital Computing. Giza: Department of Mathematics, Faculty of Science, Cairo University, 2007.