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1

Saleem, Nada, and Mohammad Hamdy. "Programming Mobile Applications." AL-Rafidain Journal of Computer Sciences and Mathematics 10, no. 2 (2013): 189–202. http://dx.doi.org/10.33899/csmj.2013.163494.

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2

Burnham, W. D., A. R. Hall, and Ramachandran Bharath. "Prolog Programming and Applications." IEEE Expert 1, no. 3 (1986): 108. http://dx.doi.org/10.1109/mex.1986.4306988.

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3

Wilson, W. G. "Prolog for applications programming." IBM Systems Journal 25, no. 2 (1986): 190–206. http://dx.doi.org/10.1147/sj.252.0190.

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4

Gupta, Omprakash K. "Applications of Quadratic Programming." Journal of Information and Optimization Sciences 16, no. 1 (1995): 177–94. http://dx.doi.org/10.1080/02522667.1995.10699213.

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5

Vandenberghe, Lieven, and Stephen Boyd. "Applications of semidefinite programming." Applied Numerical Mathematics 29, no. 3 (1999): 283–99. http://dx.doi.org/10.1016/s0168-9274(98)00098-1.

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6

Kalashnikov, Vyacheslav V., Stephan Dempe, Gerardo A. Pérez-Valdés, Nataliya I. Kalashnykova, and José-Fernando Camacho-Vallejo. "Bilevel Programming and Applications." Mathematical Problems in Engineering 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/310301.

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A great amount of new applied problems in the area of energy networks has recently arisen that can be efficiently solved only as mixed-integer bilevel programs. Among them are the natural gas cash-out problem, the deregulated electricity market equilibrium problem, biofuel problems, a problem of designing coupled energy carrier networks, and so forth, if we mention only part of such applications. Bilevel models to describe migration processes are also in the list of the most popular new themes of bilevel programming, as well as allocation, information protection, and cybersecurity problems. Th
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7

Nilesh, Jagnik. "Building Reactive Applications with Kotlin Flows." Journal of Scientific and Engineering Research 8, no. 2 (2021): 250–52. https://doi.org/10.5281/zenodo.13950723.

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Reactive programming can be used to make programs faster and more responsive. The support for reactive programming is available in many languages with ReactiveX libraries. However, the learning curve and code complexity remain the main drawbacks of these libraries. Kotlin introduces a simple, out of the box language feature for reactive programming called Flows. In this paper we present the benefits of using reactive programming in general and discuss the use of Kotlin Flows to apply the reactive paradigm to software pipelines.
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8

Ying Wang, Ying Wang. "Applications of an Improved PSO in Integer Linear Programming." 電腦學刊 32, no. 6 (2021): 098–106. http://dx.doi.org/10.53106/199115992021123206008.

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9

Kim, Gi-Hwan, Jong-Cheol Park, Jae-Hong Kim, and Choong-Shik Park. "Programming Accounting Applications using BRMS." Journal of the Korean Institute of Information and Communication Engineering 14, no. 6 (2010): 1359–64. http://dx.doi.org/10.6109/jkiice.2010.14.6.1359.

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10

István, Fekete, Gregorics Tibor, Kovácsné Pusztai Kinga, and Veszprémi Anna. "Programming Theorems and Their Applications." Teaching Mathematics and Computer Science 17, no. 2 (2020): 213–41. http://dx.doi.org/10.5485/tmcs.2019.0466.

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11

Dangerfield, Janet, and J. K. Strayer. "Linear Programming and Its Applications." Mathematical Gazette 74, no. 470 (1990): 402. http://dx.doi.org/10.2307/3618167.

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12

McKay, A. C. "Linear Programming Applications on Microcomputers." Journal of the Operational Research Society 36, no. 7 (1985): 633. http://dx.doi.org/10.2307/2582484.

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13

Erdem, Esra, Michael Gelfond, and Nicola Leone. "Applications of Answer Set Programming." AI Magazine 37, no. 3 (2016): 53–68. http://dx.doi.org/10.1609/aimag.v37i3.2678.

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ASP has been applied fruitfully to a wide range of areas in AI and in other fields, both in academia and in industry, thanks to the expressive representation languages of ASP and the continuous improvement of ASP solvers. We present some of these ASP applications, in particular, in knowledge representation and reasoning, robotics, bioinformatics and computational biology as well as some industrial applications. We discuss the challenges addressed by ASP in these applications and emphasize the strengths of ASP as a useful AI paradigm.
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14

Wood, Kevin, and Vincent A. Sposito. "Linear Programming With Statistical Applications." Journal of the American Statistical Association 85, no. 409 (1990): 265. http://dx.doi.org/10.2307/2289574.

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15

Yelick, Katherine A. "Programming models for irregular applications." ACM SIGPLAN Notices 28, no. 1 (1993): 28–31. http://dx.doi.org/10.1145/156668.156680.

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16

Bales, Scott A., and Mark A. Shifman,. "Database Programming for Laboratory Applications." Laboratory Medicine 18, no. 4 (1987): 256–58. http://dx.doi.org/10.1093/labmed/18.4.256.

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17

Bratko, Ivan, and Stephen Muggleton. "Applications of inductive logic programming." Communications of the ACM 38, no. 11 (1995): 65–70. http://dx.doi.org/10.1145/219717.219771.

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18

McKay, A. C. "Linear Programming Applications on Microcomputers." Journal of the Operational Research Society 36, no. 7 (1985): 633–35. http://dx.doi.org/10.1057/jors.1985.110.

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19

Pukacki, Juliusz, Michał Kosiedowski, Rafał Mikołajczak, et al. "Programming Grid Applications with Gridge." Computational Methods in Science and Technology 12, no. 1 (2006): 47–68. http://dx.doi.org/10.12921/cmst.2006.12.01.47-68.

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20

Iyengar, Garud, and Wanmo Kang. "Inverse conic programming with applications." Operations Research Letters 33, no. 3 (2005): 319–30. http://dx.doi.org/10.1016/j.orl.2004.04.007.

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21

Brooks, Daniel G. "Linear Programming With Statistical Applications." Technometrics 32, no. 3 (1990): 355–56. http://dx.doi.org/10.1080/00401706.1990.10484707.

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22

Sette, S., and L. Boullart. "Genetic programming: principles and applications." Engineering Applications of Artificial Intelligence 14, no. 6 (2001): 727–36. http://dx.doi.org/10.1016/s0952-1976(02)00013-1.

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23

Lev, Ben. "Applications of mathematical programming models." European Journal of Operational Research 160, no. 1 (2005): 1–2. http://dx.doi.org/10.1016/j.ejor.2003.06.016.

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24

Haridi, Seif, Peter Van Roy, Per Brand, and Christian Schulte. "Programming languages for distributed applications." New Generation Computing 16, no. 3 (1998): 223–61. http://dx.doi.org/10.1007/bf03037481.

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25

Shin, Wan S. "Linear Programming with Statistical Applications." Journal of Quality Technology 22, no. 1 (1990): 83–84. http://dx.doi.org/10.1080/00224065.1990.11979216.

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26

Kalva, Hari, Aleksandar Colic, Adriana Garcia, and Borko Furht. "Parallel programming for multimedia applications." Multimedia Tools and Applications 51, no. 2 (2010): 801–18. http://dx.doi.org/10.1007/s11042-010-0656-2.

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27

Jajuga, Krzysztof, and Vincent A. Sposito. "Linear Programming with Statistical Applications." Statistician 39, no. 4 (1990): 467. http://dx.doi.org/10.2307/2349092.

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28

Farnum, Rob. "Applications programming interface for Windows." StandardView 4, no. 2 (1996): 100–103. http://dx.doi.org/10.1145/234999.235003.

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29

Bratko, Ivan, and Ross King. "Applications of inductive logic programming." ACM SIGART Bulletin 5, no. 1 (1994): 43–49. http://dx.doi.org/10.1145/181668.181678.

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30

Rommelfanger, Heinrich. "Fuzzy linear programming and applications." European Journal of Operational Research 92, no. 3 (1996): 512–27. http://dx.doi.org/10.1016/0377-2217(95)00008-9.

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31

Lloyd, J. W., and K. S. Ng. "Declarative programming for agent applications." Autonomous Agents and Multi-Agent Systems 23, no. 2 (2010): 224–72. http://dx.doi.org/10.1007/s10458-010-9138-1.

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32

Arsham, H. "Linear programming methods and applications." European Journal of Operational Research 48, no. 1 (1990): 165–66. http://dx.doi.org/10.1016/0377-2217(90)90076-n.

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33

Dübel, S. "Programming antibodies for novel applications." Chemie Ingenieur Technik 90, no. 9 (2018): 1248. http://dx.doi.org/10.1002/cite.201855255.

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34

Wallace, Mark. "Practical applications of constraint programming." Constraints 1, no. 1-2 (1996): 139–68. http://dx.doi.org/10.1007/bf00143881.

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35

Liu, Yuhan. "Uncertain random programming with applications." Fuzzy Optimization and Decision Making 12, no. 2 (2012): 153–69. http://dx.doi.org/10.1007/s10700-012-9149-2.

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36

Shen, Hua, Guo Shun Zhou, and Hui Qi Yan. "A Study of Parallelization and Performance Optimizations Based on OpenMP." Applied Mechanics and Materials 321-324 (June 2013): 2933–37. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.2933.

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The primary consequence of the transition to multicore processors is that applications will increasingly need to be parallelized to improve application's throughput, responsiveness and latency. Multithreading is becoming increasingly important for modern programming. Unfortunately, parallel programming is no doubt much more tedious and error-prone than serial programming. Although modern compilers can manage threads well, but in practice, synchronization errors (such as: data race errors, deadlocks) required careful management and good optimization method. This paper presents a preliminary stu
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37

Abdelaziz, Fouad Ben. "Multiple objective programming and goal programming: New trends and applications." European Journal of Operational Research 177, no. 3 (2007): 1520–22. http://dx.doi.org/10.1016/j.ejor.2005.12.023.

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38

Inda Figueroa, Paulina, Daniela Miranda Silva, Yahely Rangel Meza, and Gustavo Peraza Polanco. "Potenciando el aprendizaje de programación en estudiantes de educación básica: explorando aplicaciones innovadoras." Revista de Investigación en Tecnologías de la Información 12, no. 25 (2024): 11–25. http://dx.doi.org/10.36825/riti.12.25.002.

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This documentary research aims to analyze and discuss the literature published from 2018 to 2022 and commercial applications found in the Android and iOS virtual stores, released from 2013 to 2021, aimed at developing learning programming for basic education students. A qualitative approach, exploratory level, and documentary method were used. The main result is a classification of the selected applications, with the application's name, developer, and purpose. In addition to a table with application development reports, publication titles, country, and year. After analyzing the selected public
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39

Hawłas, H. J. "Teaching Assembler for Mechatronics Applications." Advanced Materials Research 222 (April 2011): 337–40. http://dx.doi.org/10.4028/www.scientific.net/amr.222.337.

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This paper explains and demonstrates how teaching programming in assembler is organized at Faculty of Mechatronics (WUT). Presented teaching technique shows how to overcome students' animosity to assembler and how to make programming interesting.
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40

Aneva, Stefka, and Elena Todorova. "Using Visual Basic for Excel Applications for Developing Students’ Programming Skills." Mathematics and Informatics 67, no. 6 (2024): 640–60. https://doi.org/10.53656/math2024-6-5-usi.

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The paper presents an approach for developing and refining the students’ practical and applied skills in programming by using the capabilities of Visual Basic for Excel Applications. Five problems are given along with their solutions and are realized through integrated features for programming in Excel. These examples help facilitate the execution of the following activities – determining the number of even and odd numbers in a finite set of elements and extracting the corresponding lists; finding all prime numbers in a given interval; merging the elements of two ordered one-dimension arrays w
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41

Largina, A. M. "On the parallel real-time applications." Science and Transport Progress, no. 42 (December 25, 2012): 176–80. http://dx.doi.org/10.15802/stp2012/9391.

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42

Anochie, E. U., O. J. Jacob, E. M. Okoroafor, et al. "Linear Programming: Characteristics, Theory, Methods and Applications." Research Journal of Management Practice 4, no. 8 (2024): 13–21. https://doi.org/10.5281/zenodo.13912017.

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<em>Linear programming is a mathematical method that is used to determine the best possible outcome or solution from a given set of parameters or list of requirements, which are represented in the form of linear relationships. Characteristics of linear programming include constraints, objective&rsquo;s function, linearity, finiteness, non- negativity, decision variables and data. The theory of linear programming is known as &ldquo;The General representation Theorem&rdquo; which will be clearly understood by taking note of the following definitions: &ldquo;A hyper plane H in R ̃&nbsp;&nbsp; is
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43

Fateman, Richard J., and John Gray. "Mastering Mathematica: Programming Methods and Applications." Mathematics of Computation 64, no. 210 (1995): 903. http://dx.doi.org/10.2307/2153469.

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44

LaLonde, Steven M., and Frank C. DiIorio. "SAS Applications Programming, a Gentle Introduction." Technometrics 34, no. 3 (1992): 366. http://dx.doi.org/10.2307/1270061.

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45

Yerekesheva, M., and A. Beder. "DEVELOPMENT OF APPLICATIONS FOR LEARNING PROGRAMMING." BULLETIN Series of Physics & Mathematical Sciences 70, no. 2 (2020): 211–15. http://dx.doi.org/10.51889/2020-2.1728-7901.33.

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Most modern students are ready to use mobile technology in the learning process, and understand the need to consider new opportunities for the best use of the potential of mobile devices and technologies. The solution of this task requires the introduction of mobile learning strategies, forms and methods in the educational process of universities. Currently, the development of mobile applications is one of the most popular tasks in the field of information technology. Applications can now analyze information from multiple sources and help the user make decisions, control processes, and solve o
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46

Wand, I. C. "Book Review: Ada Programming with Applications." International Journal of Electrical Engineering & Education 26, no. 3 (1989): 280–81. http://dx.doi.org/10.1177/002072098902600338.

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47

Varatharajan, R., Muthu Senthil, and Perumal sankar. "Memetic Programming Approach for Floorplanning Applications." International Journal of Information Engineering and Electronic Business 4, no. 4 (2012): 39–45. http://dx.doi.org/10.5815/ijieeb.2012.04.06.

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48

Tofallis, C., and I. M. Stancu-Minasian. "Fractional Programming: Theory, Methods and Applications." Journal of the Operational Research Society 49, no. 8 (1998): 895. http://dx.doi.org/10.2307/3009971.

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49

LeGuernic, P., T. Gautier, M. Le Borgne, and C. Le Maire. "Programming real-time applications with SIGNAL." Proceedings of the IEEE 79, no. 9 (1991): 1321–36. http://dx.doi.org/10.1109/5.97301.

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50

Badia, Rosa M., Jesús Labarta, Raül Sirvent, Josep M. Pérez, José M. Cela, and Rogeli Grima. "Programming Grid Applications with GRID Superscalar." Journal of Grid Computing 1, no. 2 (2003): 151–70. http://dx.doi.org/10.1023/b:grid.0000024072.93701.f3.

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