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Subprograms
Published in Subrata Ray, Fortran 2018 with Parallel Programming, 2019
If the actual argument is a variable name, the corresponding argument is said to have been passed by reference. When an argument is passed by reference, any allowed modifications done within the subprogram are reflected in the corresponding actual argument in the calling program. Consider subroutine exchange once again. subroutine exchange(a,b) integer :: a,b integer :: t … end subroutine exchange program main integer ::ia, ib ia = 3; ib = 4 call exchange(ia,ib) print *,ia,ib end program main
Introduction
Published in Randall L. Eubank, Ana Kupresanin, Statistical Computing in C++ and R, 2011
Randall L. Eubank, Ana Kupresanin
References provide objects that behave in most ways as if they were just alternative names or aliases for the objects they reference. A reference also has the property of a pointer in that if an object is passed under its reference “name” to a function the function can actually alter the object being referenced. A reference can be viewed as being similar to a pointer that can only point to one location in memory: the one that is used when it was initialized. Then, dereferencing is accomplished by simply using the name of the referenced variable.
C
Published in Phillip A. Laplante, Dictionary of Computer Science, Engineering, and Technology, 2017
call-by-reference a mechanism for parameter passing in many languages which states that the value of the actual parameter is not passed to the called function, but rather a reference (memory address) to the value is passed instead. Use of the actual parameter in the function body uses or modifies the value thus referenced. Also called call-by-address. See also call-by-name, call-by-value, call-by-value-result.
A bibliometric analysis and review on reinforcement learning for transportation applications
Published in Transportmetrica B: Transport Dynamics, 2023
Can Li, Lei Bai, Lina Yao, S. Travis Waller, Wei Liu
Specifically, this study provides a summary on applications of RL to address relevant transportation issues and takes advantage of the bibliometric analysis approach to uncover connections among the journals/conferences and use keywords to identify the influential journals/conferences and areas of concern. Several future directions of RL studies in transportation are also discussed. The major transportation topics that involve RL methods discussed in this study include traffic control, taxi and ride-sourcing/sharing, assistant and autonomous driving, routing, public transportation and bike-sharing system, and electric vehicles, which are identified based on an analysis of keywords summarized in Section 3. The detailed classification of topics is shown in Figure 1. In particular, this review has collected over 600 related papers mostly published in the last 13 years in major journals in the transportation domain (e.g. Transportation Research Part B, Part C, IEEE Transactions on Intelligent Transportation Systems, IET Intelligent Transport Systems) and major related conferences in the computer science domain (e.g. AAAI, KDD, WWW, CIKM), which will be further discussed in Section 3. To summarize, this paper provides a reference point to researchers for interdisciplinary Reinforcement Learning research in transportation and computer science.
Kinematical Lie Algebras and Invariant Functions of Algebras
Published in International Journal for Computational Methods in Engineering Science and Mechanics, 2019
J. M. Escobar, J. Núñez, P. Pérez-Fernández
The structure of the paper is as follows. In the next section, we give some preliminaries on Lie algebras in general and filiform Lie algebras in particular, on gradings and on the bi-parameter invariant function of algebras , introduced by ourselves in reference [15]. Section 2 is devoted to recall some aspects on the kinematical Lie algebras of four-dimensional spacetime, introduced by Tolar in reference [2]. In Section 3, we present some new properties of the one-parameter invariant function which is computed in Section 4 for the eight kinematical algebras by Tolar. Finally, in Section 5, we show some conclusions deduced from our research on these cited algebras.
Fused features for no reference image quality assessment
Published in The Imaging Science Journal, 2022
Ajai John Chemmanam, Shahanaz N, Bijoy A Jose
No Reference Image Quality Assessment (NR-IQA), also called Objective-Blind IQA, is the most complex and difficult approach for image quality assessment. There is no reference image, or it's characteristics for comparison or estimation of distortions in the image. NR-IQA technique has to model the reference image characteristics, the effects of distortions imparted and human visual perception. These algorithms compute the statistical features of the image to predict the quality. Blind/Reference-less Image Spatial Quality Evaluator (BRISQUE) [12], Natural Image Quality Evaluator (NIQE) [13], Perception-based Image Quality Evaluator (PIQE) [14] are some of the NRIQA methods previously developed.