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Journal articles on the topic 'Problem solving - Computer programs'
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Erkens, Gijsbert, and Jerry E. B. Andriessen. "Cooperation in problem solving and educational computer programs." Computers in Human Behavior 10, no. 1 (March 1994): 107–25. http://dx.doi.org/10.1016/0747-5632(94)90032-9.
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Kahn, Arthur. "Problem Solving Training — A Factor in Debugging Computer Programs." Proceedings of the Human Factors Society Annual Meeting 29, no. 9 (October 1985): 856–60. http://dx.doi.org/10.1177/154193128502900906.
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Baum, Eric B., and Igor Durdanovic. "Evolution of Cooperative Problem Solving in an Artificial Economy." Neural Computation 12, no. 12 (December 1, 2000): 2743–75. http://dx.doi.org/10.1162/089976600300014700.
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We address the problem of how to reinforce learning in ultracomplex environments, with huge state-spaces, where one must learn to exploit a compact structure of the problem domain. The approach we propose is to simulate the evolution of an artificial economy of computer programs. The economy is constructed based on two simple principles so as to assign credit to the individual programs for collaborating on problem solutions. We find empirically that starting from programs that are random computer code, we can develop systems that solve hard problems. In particular, our economy learned to solve almost all random Blocks World problems with goal stacks that are 200 blocks high. Competing methods solve such problems only up to goal stacks of at most 8 blocks. Our economy has also learned to unscramble about half a randomly scrambled Rubik's cube and to solve several commercially sold puzzles.
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Thilmany, Jean. "Probabilistic Problem Solving." Mechanical Engineering 124, no. 01 (January 1, 2002): 53–55. http://dx.doi.org/10.1115/1.2002-jan-4.
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This article reviews predictive technologies based on a probabilistic method of problem solving. These technologies are gaining a steady foothold as a method of finding answers to engineering and other types of problems. According to the developer of one such technology, these computer programs use mathematical models to predict the probability that something will or won’t happen a particular way in the future. The tools can be used for design, sensitivity analysis, mathematical modeling of complex processes, uncertainty analysis, competitive analysis, and process optimization among other things. The predictive technology from Unipass has been used by the research center to design gas turbines, helicopters, and elevators. The probabilistic method and the newer predictive technologies that use it have some ardent backers. For instance, the probabilistic methods committee of the Society of Automotive Engineers states its mission as: to enable and facilitate rapid deployment of probabilistic technology to enhance the competitiveness of our industries by better, faster, greener, smarter, affordable, and reliable product development.
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COOKE, DANIEL E., and ANN GATES. "ON THE DEVELOPMENT OF A METHOD TO SYNTHESIZE PROGRAMS FROM REQUIREMENTS SPECIFICATIONS." International Journal of Software Engineering and Knowledge Engineering 01, no. 01 (March 1991): 21–38. http://dx.doi.org/10.1142/s0218194091000056.
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This paper reviews the progress that has been made towards the definition of a new generation of computer assisted problem solving tool. When we solve problems with a computer we state the solution in terms of several languages, beginning with a requirements specification language and ending with a program. Beginning with a generalization of a programming language, this paper follows steps towards the removal of control and data structure information in a problem solution. The effort discussed here would result in the requirements specification language being the final language used in problem solving.
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Lamia, Mahnane, and Hafidi Mohamed. "A Problem Solving Using Intelligent Social Network." International Journal of Web-Based Learning and Teaching Technologies 14, no. 3 (July 2019): 28–38. http://dx.doi.org/10.4018/ijwltt.2019070103.
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Nowadays, students are becoming familiar with the computer technology at a very early age. Moreover, the wide availability of the internet gives a new perspective to distance education making e-learning environments crucial to the future of education. Intelligent tutoring systems (ITSs) provide sophisticated tutoring systems using artificial intelligence techniques in computer programs to facilitate instruction. ITSs support problem solving by providing adaptive scaffolding in terms of feedback, guidance, problem selection and other types of help. Little attention has been devoted thus far to the difference between novices and advanced students in learning from social network and ITSs. Furthermore, students can benefit from collaboration in social network environments especially when this is combined with an ITS.
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Titus, S. J., and W. S. Adams. "A Fifth Generation Approach to Problem-Solving in Forest Mensuration and Sampling." Forestry Chronicle 64, no. 3 (June 1, 1988): 186–89. http://dx.doi.org/10.5558/tfc64186-3.
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A new problem-solving methodology, based on fifth generation computer programming languages, is presented for use in forestry or other technically-oriented fields. It is based on the integration of exposition, data, and computer programs into a single document that is processed by the computer to produce a report. With this methodology the report, a text file, provides a central focus for the problem-solving process as it happens rather than being a reconstruction after the fact. The methodology exploits the capability of a fifth generation language, the Nested Interactive Array Language (Nial), to interpret programs and expressions written in a form close to natural language. Nial's powerful general-purpose analysis capabilities facilitate better understanding of the solution process rather than obscuring it, and the ease with which new operations can be defined in a problem-oriented context allows the casual programmer access to powerful tools for solving new problems.
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RUBY, DAVID, and DENNIS KIBLER. "LEARNING STEPPINGSTONES FOR PROBLEM SOLVING." International Journal of Pattern Recognition and Artificial Intelligence 07, no. 03 (June 1993): 527–40. http://dx.doi.org/10.1142/s0218001493000273.
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One goal of Artificial Intelligence is to develop and understand computational mechanisms for solving difficult real-world problems. Unfortunately, domains traditionally used in general problem-solving research lack important characteristics of real-world domains, making it difficult to apply the techniques developed. Most classic AI domains require satisfying a set of Boolean constraints. Real-world problems require finding a solution that meets a set of Boolean constraints and performs well on a set of real-valued constraints. In addition, most classic domains are static while domains from the real world change. In this paper we demonstrate that SteppingStone, a general learning problem solver, is capable of solving problems with these characteristics. SteppingStone heuristically decomposes a problem into simpler subproblems, and then learns to deal with the interactions that arise between the subproblems. In lieu of an agreed upon metric for problem difficulty, we choose significant problems that are difficult for both people and programs as good candidates for evaluating progress. Consequently we adopt the domain of logic synthesis from VLSI design to demonstrate SteppingStone’s capabilities.
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Armoni, Michal, Judith Gal-Ezer, and Dina Tirosh. "Solving Problems Reductively." Journal of Educational Computing Research 32, no. 2 (March 2005): 113–29. http://dx.doi.org/10.2190/6pcm-447v-wf7b-qeuf.
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Solving problems by reduction is an important issue in mathematics and science education in general (both in high school and in college or university) and particularly in computer science education. Developing reductive thinking patterns is an important goal in any scientific discipline, yet reduction is not an easy subject to cope with. Still, the use of reduction usually is insufficiently reflected in high school mathematics and science programs. Even in academic computer science programs the concept of reduction is mentioned explicitly only in advanced academic courses such as computability and complexity theory. However, reduction can be applied in other courses as well, even on the high school level. Specifically, in the field of computational models, reduction is an important method for solving design and proof problems. This study focuses on high school students studying the unit “computational models”—a unique unit, which is part of the new Israeli computer science high school curriculum. We examined whether high school students tend to solve problems dealing with computational models reductively, and if they do, what is the nature of their reductive solutions. To the best of our knowledge, the tendency to reductive thinking in theoretical computer science has not been studied before. Our findings show that even though many students use reduction, many others prefer non-reductive solutions, even when reduction can significantly decrease the technical complexity of the solution. We discuss these findings and suggest possible ways to improve reductive thinking.
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DiMatteo, Rachel Wing. "Informing Practice: A Model Approach to Problem Solving." Mathematics Teaching in the Middle School 16, no. 3 (October 2010): 132–35. http://dx.doi.org/10.5951/mtms.16.3.0132.
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Students who pursue careers in business, medicine, engineering, or architecture need robust mathematical backgrounds, with a particularly strong emphasis on problem solving. For example, when civil engineers are asked to determine the best placement for a cell phone tower, some of their thinking is related to schoolbased mathematical procedures and concepts. However, for the most part, they problem solve, using computer programs to construct mathematical models that relate the three-dimensional topography of the earth and the availability and cost of property for tower placement.
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Ilyasova, R. A., A. U. Dauletkulova, and D. Ya Tokhtakhunov. "SYSTEMS OF COMPUTER-ORIENTED PROBLEMS IN THE COURSE OF DIFFERENTIAL EQUATIONS." BULLETIN Series of Physics & Mathematical Sciences 69, no. 1 (March 10, 2020): 351–55. http://dx.doi.org/10.51889/2020-1.1728-7901.62.
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The modern period of development of the information society is characterized by the need to modernize the education system. The training of a future mathematics teacher should be organized in such a way that in addition to basic knowledge, future teachers should master various applications of mathematics, be able to model various processes and phenomena, and use modern information technologies in the process of solving mathematical problems. The use of computers and computer programs in the educational process changes the role of learning tools in teaching. In our study, we consider the computer as one of the components of the entire system of learning tools, which, in addition to the computer, includes traditional learning tools that ensure the teaching of an educational subject. This paper shows some advantages and disadvantages of computer mathematics systems in the course of differential equations. Computer programs that allow us to implement numerical, analytical and graphical methods for solving differential equations are considered.
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Zaurebekov, N. S., and А. М. Bodyk. "MAPLE AND MATHCAD PROGRAMMING METHODS FOR SOLVING MATH PROBLEMS." BULLETIN Series of Physics & Mathematical Sciences 69, no. 1 (March 10, 2020): 333–39. http://dx.doi.org/10.51889/2020-1.1728-7901.59.
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The article discusses the features of teaching computer science and mathematics in secondary schools based on interdisciplinary communication. Integration of mathematics and computer science contributes to the algorithmic thinking of students in the process of solving logical, textual, arithmetic, geometric problems. The main didactic task of interdisciplinary communication is to establish a connection between the educational, educational, developing nature of the educational process. The use of computer programs to solve problems related to mathematics, the use of computers to accelerate student learning and teaching them to work independently. His interest in the subject is growing, his talent and personal abilities are developing, as well as the quality of teaching, the speed of the educational process is increasing.
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Ganian, Robert, and Sebastian Ordyniak. "Solving Integer Linear Programs by Exploiting Variable-Constraint Interactions: A Survey." Algorithms 12, no. 12 (November 22, 2019): 248. http://dx.doi.org/10.3390/a12120248.
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Integer Linear Programming (ILP) is among the most successful and general paradigms for solving computationally intractable optimization problems in computer science. ILP is NP-complete, and until recently we have lacked a systematic study of the complexity of ILP through the lens of variable-constraint interactions. This changed drastically in recent years thanks to a series of results that together lay out a detailed complexity landscape for the problem centered around the structure of graphical representations of instances. The aim of this survey is to summarize these recent developments, put them into context and a unified format, and make them more approachable for experts from many diverse backgrounds.
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A.V., Chistyakov. "On improving the efficiency of mathematical modeling of the problem of stability of construction." Artificial Intelligence 25, no. 3 (October 10, 2020): 27–36. http://dx.doi.org/10.15407/jai2020.03.027.
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Algorithmic software for mathematical modeling of structural stability is considered, which is reduced to solving a partial generalized eigenvalues problem of sparse matrices, with automatic parallelization of calculations on modern parallel computers with graphics processors. Peculiarities of realization of parallel algorithms for different structures of sparse matrices are presented. The times of solving the problem of stability of composite materialsusing a three-dimensional model of "finite size fibers" on computers of different architectures are given. In mathematical modeling of physical and technical processes in many cases there is a need to solve problems of algebraic problem of eigenvalues (APVZ) with sparse matrices of large volumes. In particular, such problems arise in the analysis of the strength of structures in civil and industrial construction, aircraft construction, electric welding, etc. The solving to these problems is to determine the eigenvalues and eigenvectors of sparse matrices of different structure. The efficiency of solving these problems largely depends on the effectiveness of mathematical modeling of the problem as a whole. Continuous growth of task parameters, calculation of more complete models of objects and processes on computers require an increase in computer productivity. High-performance computing requirements are far ahead of traditional parallel computing, even with multicore processors. High-performance computing requirements are far ahead of traditional parallel computing, even with multicore processors. Today, this problem is solved by using powerful supercomputers of hybrid architecture, such as computers with multicore processors (CPUs) and graphics processors (GPUs), which combine MIMD and SIMD architectures. But the potential of high-performance computers can be used to the fullest only with algorithmic software that takes into account both the properties of the task and the features of the hybrid architecture. Complicating the architecture of modern high-performance supercomputers of hybrid architecture, which are actively used for mathematical modeling (increasing the number of computer processors and cores, different types of computer memory, different programming technologies, etc.) means a significant complication of efficient use of these resources in creating parallel algorithms and programs. here are problems with the creation of algorithmic software with automatic execution of stages of work, which are associated with the efficient use of computing resources, ways to store and process sparse matrices, analysis of the reliability of computer results. This makes it possible to significantly increase the efficiency of mathematical modeling of practical problems on modern high-performance computers, as well as free users from the problems of parallelization of complex problems. he developed algorithmic software automatically implements all stages of parallel computing and processing of sparse matrices on a hybrid computer. It was used at the Institute of Mechanics named after S.P. Tymoshenko NAS of Ukraine in modeling the strength problems of composite material. A significant improvement in the time characteristics of mathematical modeling was obtained. Problems of mathematical modeling of the properties of composite materials has an important role in designing the processes of deformation and destruction of products in various subject areas. Algorithmic software for mathematical modeling of structural stability is considered, which is reduced to solving a partial generalized problem of eigen values of sparse matrices of different structure of large orders, with automatic parallelization of calculations on modern parallel computers with graphics processors. The main methodological principles and features of implementation of parallel algorithms for different structures of sparse matrices are presented, which ensure effective implementation of multilevel parallelism of a hybrid system and reduce data exchange time during the computational process. As an example of these approaches, a hybrid algorithm of the iteration method in subspace for tape and block-diagonal matrices with a frame for computers of hybrid architecture is given. Peculiarities of data decomposition for matrices of profile structure at realization of parallel algorithms are considered. The proposed approach provides automatic determination of the required topology of the hybrid computer and the optimal amount of resources for the organization of an efficient computational process. The results of testing the developed algorithmic software for problems from the collection of the University of Florida, as well as the times of solving the problem of stability of composite materials using a three-dimensional model of "finite size fibers" on computers of different architectures. The results show a significant improvement in the time characteristics of solving problems.
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Stadler, Matthias, Katharina Herborn, Maida Mustafić, and Samuel Greiff. "Computer-Based Collaborative Problem Solving in PISA 2015 and the Role of Personality." Journal of Intelligence 7, no. 3 (July 1, 2019): 15. http://dx.doi.org/10.3390/jintelligence7030015.
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Collaborative problem solving (CPS) is an essential 21st century skill at the intersection of social collaboration and cognitive problem solving, and is increasingly integrated in educational programs, such as the influential Programme for International Student Assessment (PISA). As research has identified the impact of the Big Five personality traits either on cognitive ability or social collaboration skills in groups, this study firstly identified their impact on the conjoint construct of CPS. Results from structural equation modelling (N = 483) found openness to experience and agreeableness as predictors for CPS performance. The results are embedded in the lifelong learning and investment model by Ackermann and provide implications for PISA 2015, as original PISA 2015 CPS tasks were used.
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Reznik, A. L., A. A. Soloviev, and A. V. Torgov. "Programs of Recursive Analytical Calculations in Problems of Random Point Images Analysis." Izvestiya of Altai State University, no. 4(114) (September 9, 2020): 112–16. http://dx.doi.org/10.14258/izvasu(2020)4-18.
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The paper discusses an approach to solving complex probabilistic combinatorial problems. The approach is based on the use of specialized software systems for analytical transformations for computing systems. One of the problems associated with the partition of the interval (which arises in the study of the reliability of reading discrete-point fields and digital images) is considered in the paper, and new previously unknown analytical formulas have been successfully obtained. The efficiency of the developed software systems is ensured by two factors: firstly, the development of high-speed specialized recursive-combinatorial algorithms; secondly, the software implementation on high-performance computing clusters using modern programming and development tools (such as C ++ and MPI).
Examples of particular solutions to the described problem that are obtained with the help of constructed computer systems are presented. An effective approach to solving complex probabilistic combinatorial problems is demonstrated. For the proposed approach, a computer is not just a powerful "calculator", but is an effective assistant with a wide range of algorithms and programs for complex and branched analytical transformations.
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EITER, THOMAS, and AXEL POLLERES. "Towards automated integration of guess and check programs in answer set programming: a meta-interpreter and applications." Theory and Practice of Logic Programming 6, no. 1-2 (January 2006): 23–60. http://dx.doi.org/10.1017/s1471068405002577.
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Answer set programming (ASP) with disjunction offers a powerful tool for declaratively representing and solving hard problems. Many NP-complete problems can be encoded in the answer set semantics of logic programs in a very concise and intuitive way, where the encoding reflects the typical “guess and check” nature of NP problems: The property is encoded in a way such that polynomial size certificates for it correspond to stable models of a program. However, the problem-solving capacity of full disjunctive logic programs (DLPs) is beyond NP, and captures a class of problems at the second level of the polynomial hierarchy. While these problems also have a clear “guess and check” structure, finding an encoding in a DLP reflecting this structure may sometimes be a non-obvious task, in particular if the “check” itself is a co-NP-complete problem; usually, such problems are solved by interleaving separate guess and check programs, where the check is expressed by inconsistency of the check program. In this paper, we present general transformations of head-cycle free (extended) disjunctive logic programs into stratified and positive (extended) disjunctive logic programs based on meta-interpretation techniques. The answer sets of the original and the transformed program are in simple correspondence, and, moreover, inconsistency of the original program is indicated by a designated answer set of the transformed program. Our transformations facilitate the integration of separate “guess” and “check” programs, which are often easy to obtain, automatically into a single disjunctive logic program. Our results complement recent results on meta-interpretation in ASP, and extend methods and techniques for a declarative “guess and check” problem solving paradigm through ASP.
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Petrov, K., N. Petrov, and M. Mikrenska. "A computer program for solving Signorini's contact problem with friction." Advances in Engineering Software 19, no. 2 (January 1994): 97–108. http://dx.doi.org/10.1016/0965-9978(94)90063-9.
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Goel, Ashok K., Spencer Rugaber, and Swaroop Vattam. "Structure, behavior, and function of complex systems: The structure, behavior, and function modeling language." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 23, no. 1 (December 16, 2008): 23–35. http://dx.doi.org/10.1017/s0890060409000080.
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AbstractTeleological modeling is fundamental to understanding and explaining many complex systems, especially engineered systems. Research on engineering design and problem solving has developed several ontologies for expressing teleology, for example, functional representation, function–behavior–structure, and structure–behavior–function (SBF). In this paper, we view SBF as a programming language. SBF models of engineering systems have been used in several computer programs for automated design and problem solving. The SBF language captures the expressive power of the earlier programs and provides a basis for interactive construction of SBF models. We provide a precise specification of the SBF language. We also describe an interactive model construction tool called SBFAuthor.
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Yurgaytis, Alexey, and Kamol Kamolov. "Automation of production programs by setting conditions of stabilization of the planned system." E3S Web of Conferences 258 (2021): 09062. http://dx.doi.org/10.1051/e3sconf/202125809062.
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Formation of a production program is a time-consuming variable problem. To solve it, many conditions and constraints must be taken into account. Computer power allows one to quickly and accurately solve problems with many variables, unlike a person who relies on his intuition and experience. The following materials and methods were used: collection and analysis of data from construction companies of various sizes, mathematical modeling of the processes of distributing labor resources, graphic interpretation of information, computer modeling. The stages of the problem statement: description of the organizational and technological problem of distributing labor resources, mathematical formulation, modeling and algorithmization using well-known metaheuristic approaches. In the course of solving the problem, a genetic algorithm was used that allows one to quickly find solutions in equations with many variables. The following constraints were determined: deadlines, maximum and minimum number of workers at the facility, minimum number of transfer of resources, minimum involvement of a subcontractor. As a result, all the necessary mathematical models and initial data for the development of a computer program for the automated distribution of labor resources among the facilities of the production program of the construction and installation organization were obtained.
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Shi, Hai He, and Hai Peng Shi. "Deductive Synthesis of Algorithms in Human-Computer Interaction." Applied Mechanics and Materials 610 (August 2014): 312–15. http://dx.doi.org/10.4028/www.scientific.net/amm.610.312.
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Deductive synthesis is a method of software development where an algorithm is derived from a formal problem specification which guarantees the reliability of final product. The paper introduces a program synthesis method PAR most of whose synthesis steps are mechanical and some of them can be done interactively by human-computer interaction, and formally synthesizes a dependable algorithm for a selection problem supported by PAR method and PAR platform. Program synthesis based on PAR covers a number of classical algorithm design tactics, develops algorithmic programs together with their proof of correctness, and makes the algorithm more reliable and solving idea more understandable.
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Ryan, Kevin, Shabbir Ahmed, Santanu S. Dey, Deepak Rajan, Amelia Musselman, and Jean-Paul Watson. "Optimization-Driven Scenario Grouping." INFORMS Journal on Computing 32, no. 3 (July 2020): 805–21. http://dx.doi.org/10.1287/ijoc.2019.0924.
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Scenario decomposition algorithms for stochastic programs compute bounds by dualizing all nonanticipativity constraints and solving individual scenario problems independently. We develop an approach that improves on these bounds by reinforcing a carefully chosen subset of nonanticipativity constraints, effectively placing scenarios into groups. Specifically, we formulate an optimization problem for grouping scenarios that aims to improve the bound by optimizing a proxy metric based on information obtained from evaluating a subset of candidate feasible solutions. We show that the proposed grouping problem is NP-hard in general, identify a polynomially solvable case, and present two formulations for solving the problem: a matching formulation for a special case and a mixed-integer programming formulation for the general case. We use the proposed grouping scheme as a preprocessing step for a particular scenario decomposition algorithm and demonstrate its effectiveness in solving standard test instances of two-stage 0–1 stochastic programs. Using this approach, we are able to prove optimality for all previously unsolved instances of a standard test set. Additionally, we implement this scheme as a preprocessing step for PySP, a publicly available and widely used implementation of progressive hedging, and compare this grouping approach with standard grouping approaches on large-scale stochastic unit commitment instances. Finally, the idea is extended to propose a finitely convergent algorithm for two-stage stochastic programs with a finite feasible region.
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Pratama, Heri, Sofika Enggari, and Irzal Arief Wisky. "Sistem Pakar Deteksi Kerusakan Truk Mitsubishi Fuso Berbasis Desktop." Jurnal Teknologi 11, no. 1 (April 12, 2021): 1–4. http://dx.doi.org/10.35134/jitekin.v11i1.23.
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An expert system is a computer program that can mimic the thought process and expert knowledge in solving a particular problem. The implementation of this expert system is widely used in the field of artificial intelligence because expert systems are seen as a way of storing expert knowledge in certain fields in computer programs so that decisions can be made in making intelligent reasoning on a specific problem in this case the problem of detecting damage to Mitsubishi trucks. Fuso at Berdikari Motor Sibolga workshop.
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Browning, Mark E., and James D. Lehman. "Identification of student misconceptions in genetics problem solving via computer program." Journal of Research in Science Teaching 25, no. 9 (December 1988): 747–61. http://dx.doi.org/10.1002/tea.3660250905.
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Jelinek, Jan Amos. "Strategies of solving tasks while using the multimedia computer program by 7-year-old students." International Journal of Pedagogy, Innovation and New Technologies 3, no. 2 (December 29, 2016): 38–46. http://dx.doi.org/10.5604/01.3001.0009.5098.
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Both in the classroom as well as on the computer screen pupils can apply similar strategies of dealing with tasks (with difficult situation). For this reason multimedia programs for learning mathematics treated are as educational alternative manner of the forming amongst children abilities of solving problems. Domain of computer programs is better adapting the level of difficulty of tasks to individual possibilities of each of users. It seems that contemporary multimedia programs are effective (Kaczmarek, 2003; Watoła, 2006; Raszka, 2008). However from conducted research which are taking into account behavior of pupils while using the computer is pointing out to the uncertainty in this belief. It turns out that abilities acquired while using the multimedia program of children aren't transferring for solving problems in tasks of the paper-pencil type (Kengfeng, 2008).
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Abboud, May C. "Problem Solving and Program Design: A Pedagogical Approach." Computer Science Education 5, no. 1 (January 1994): 63–83. http://dx.doi.org/10.1080/0899340940050105.
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KESH, DEEPANJAN, and SHASHANK K. MEHTA. "GENERALIZED REDUCTION TO COMPUTE TORIC IDEALS." Discrete Mathematics, Algorithms and Applications 02, no. 01 (March 2010): 45–59. http://dx.doi.org/10.1142/s1793830910000462.
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Toric ideals have many applications including solving integer programs. Several algorithms for computing the toric ideal of an integer matrix are available in the literature. Since it is an NP hard problem the present approaches can only solve relatively small problems. We propose a new approach which improves upon a well known technique to compute ideal saturation, which leads to a faster algorithm to compute toric ideals.
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Glivenko, E. V., and A. S. Fomochkina. "COMPARISON STUDY OF GEOMETRIC METHODS FOR SOLVING EQUATION SYSTEMS." Issues of radio electronics, no. 5 (June 8, 2019): 116–23. http://dx.doi.org/10.21778/2218-5453-2019-5-116-123.
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The paper proposes a comparison of computational methods for solving nonlinear systems of equations on the example of the problem of calculating the spatial trajectory of a horizontal well. The difference of the proposed methods is the geometric approach to the formulation and solution of the problem. Brief algorithms and descriptions of computer programs of three geometric methods are presented: the «exit into (n + 1)‑dimensional space» method, the method using the fixed‑point properties and the unifying method. The application of each of these algorithms to the problem of calculating the spatial trajectory of a horizontal well resulted in obtaining identical solutions that coincide with the results of calculations using classical numerical methods. The disadvantages and limitations of each of the three geometric methods for solving systems of equations are noted.
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Junaedi, Nanang, and Candra Budi Susila. "Pelatihan Microsoft Office 2007 di Desa Sukosari, Kecamatan Dagangan, Kabupaten Madiun." JURNAL DAYA-MAS 5, no. 1 (June 2, 2020): 22–26. http://dx.doi.org/10.33319/dymas.v5i1.37.
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Information Technology has grown rapidly in Indonesia. Almost all problems can be handled by a computer. For this reason, every level of society must be ready and able to follow along with the development of technology. After the development of information technology, typewriter users moved to the computer. Because of its more efficient performance. Now almost all people must have switched from being manually switched to computers, nowadays performance is demanded to be faster in solving a problem. Correspondence is a problem that is often handled by computer administrators in order to become faster, the making of letters or reports at the village level government should be using a computer. But in reality, there are still many village officials who cannot yet use computers, especially older employee. Even though in making letters or reports, village administrators are required to work faster. By referring to these problems, at this time service will be conducted a training aimed at village officials about their understanding of information technology, especially the ability of village officials to understand the making of letters or reports using Microsoft Office 2007. Microsoft Word 2007 and Microsoft Excel 2007, this programs is often used when making reports. In the future it is expected that all village administrators can understand the use of this application correctly and precisely. Keywords—: Microsoft Office 2007; Correspondence; Village Administrator.
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Horst, R., T. Q. Phong, Ng V. Thoai, and J. de Vries. "On solving a D.C. programming problem by a sequence of linear programs." Journal of Global Optimization 1, no. 2 (June 1991): 183–203. http://dx.doi.org/10.1007/bf00119991.
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Nuraida, Ida, Hamdan Sugilar, Rahayu Kariadinata, Juariah Juariah, and Nunung Sobarningsih. "Solving the heart curve with geogebra." MATEC Web of Conferences 197 (2018): 01001. http://dx.doi.org/10.1051/matecconf/201819701001.
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Heart symbols are used as expressions of love. There are several mathematical explanations that can produce a curve in the shape of a heart symbol, the most famous of which is cardioid. Graphs that look exotic like cardioid and limacon can be solved using polar coordinates. Polar equations r = a ± b cos θ and r = a ± b sin θ, with a and b positive are called limacon curves, for the special case a = b is called the cardiod. Computer technology is an alternative that can be used to help this. One of the computer programs that can be utilized as a medium of mathematics learning especially in drawing the heart curve is GeoGebra. GeoGebra is a dynamic mathematical software that combines geometry, algebra, and calculus. GeoGebra program serves as a learning medium that provides a visual experience to students in interacting with the concept of polar coordinates in solving the problem of the heart curve.
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Clement, Catherine A., D. Midian Kurland, Ronald Mawby, and Roy D. Pea. "Analogical Reasoning and Computer Programming." Journal of Educational Computing Research 2, no. 4 (November 1986): 473–86. http://dx.doi.org/10.2190/dfh5-e0pg-1ml4-m34j.
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Investigations of the cognitive demands of programming can inform teaching and validate claims that important cognitive skills are inherent in programming. Given reports of experts' use of analogical problem solving in programming, the study reported here related analogical reasoning to Logo programming mastery among high school students. Correlational analyses related pretests of analogical reasoning to posttests of programming mastery. As predicted, a significant correlation was found between analogical reasoning and the ability to write subprocedures which can be reused for several different programs. This sophisticated programming skill requires recognition of structural similarities among distinct programming tasks. A final, general discussion considers analogical reasoning skill as a cognitive demand and consequence of programming.
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Cai, Lei, Shuai Tang, Jingben Yin, Zhisong Hou, and Hongwei Jiao. "An Out Space Accelerating Algorithm for Generalized Affine Multiplicative Programs Problem." Journal of Control Science and Engineering 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/5249160.
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This paper presents an out space branch-and-bound algorithm for solving generalized affine multiplicative programs problem. Firstly, by introducing new variables and constraints, we transform the original problem into an equivalent nonconvex programs problem. Secondly, by utilizing new linear relaxation technique, we establish the linear relaxation programs problem of the equivalent problem. Thirdly, based on the out space partition and the linear relaxation programs problem, we construct an out space branch-and-bound algorithm. Fourthly, to improve the computational efficiency of the algorithm, an out space reduction operation is employed as an accelerating device for deleting a large part of the investigated out space region. Finally, the global convergence of the algorithm is proved, and numerical results demonstrate the feasibility and effectiveness of the proposed algorithm.
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Hasan, M. Babul, and SM Asaduzzaman. "A Computer Program for Solving LP Problems by 2-Basic Variables Replacement at Each Simplex Iteration." Dhaka University Journal of Science 61, no. 1 (May 27, 2013): 13–18. http://dx.doi.org/10.3329/dujs.v61i1.15090.
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In this paper, we develop a computer technique to implement the existing 2-basic variable replacement method of Paranjape for solving linear programming (LP) problems. To our knowledge there is no such computer oriented program which implemented Paranjapes method. Our computer oriented program is a faster method for solving linear programs. A number of numerical examples are illustrated to demonstrate our algorithm. Dhaka Univ. J. Sci. 61(1): 13-18, 2013 (January) DOI: http://dx.doi.org/10.3329/dujs.v61i1.15090
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Baggio, Andrea, Margarida Carvalho, Andrea Lodi, and Andrea Tramontani. "Multilevel Approaches for the Critical Node Problem." Operations Research 69, no. 2 (March 2021): 486–508. http://dx.doi.org/10.1287/opre.2020.2014.
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Multilevel programming can provide the right mathematical formulations for modeling sequential decision-making problems. In such cases, it is implicit that each level anticipates the optimal reaction of the subsequent ones. Defender–attacker–defender trilevel programs are a particular case of interest that encompasses a fortification strategy, followed by an attack, and a consequent recovery defensive strategy. In “Multilevel Approaches for the Critical Node Problem,” Baggio, Carvalho, Lodi, and Tramontani study a combinatorial sequential game between a defender and an attacker that takes place in a network. The authors propose an exact algorithmic framework. This work highlights the significant improvements that the defender can achieve by taking the three-stage game into account instead of considering fortification and recovery as isolated. Simultaneously, the paper contributes to advancing the methodologies for solving trilevel programs.
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EITER, THOMAS, MICHAEL FINK, THOMAS KRENNWALLNER, and CHRISTOPH REDL. "Conflict-driven ASP solving with external sources." Theory and Practice of Logic Programming 12, no. 4-5 (July 2012): 659–79. http://dx.doi.org/10.1017/s1471068412000233.
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AbstractAnswer Set Programming (ASP) is a well-known problem solving approach based on nonmonotonic logic programs and efficient solvers. To enable access to external information,hex-programs extend programs withexternal atoms, which allow for a bidirectional communication between the logic program and external sources of computation (e.g., description logic reasoners and Web resources). Current solvers evaluatehex-programs by a translation to ASP itself, in which values of external atoms are guessed and verified after the ordinary answer set computation. This elegant approach does not scale with the number of external accesses in general, in particular in presence of nondeterminism (which is instrumental for ASP). In this paper, we present a novel, native algorithm for evaluatinghex-programs which uses learning techniques. In particular, we extend conflict-driven ASP solving techniques, which prevent the solver from running into the same conflict again, from ordinary tohex-programs. We show how to gain additional knowledge from external source evaluations and how to use it in a conflict-driven algorithm. We first target the uninformed case, i.e., when we have no extra information on external sources, and then extend our approach to the case where additional meta-information is available. Experiments show that learning from external sources can significantly decrease both the runtime and the number of considered candidate compatible sets.
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Ahmadi, Amir Ali, and Bachir El Khadir. "Time-Varying Semidefinite Programs." Mathematics of Operations Research 46, no. 3 (August 2021): 1054–80. http://dx.doi.org/10.1287/moor.2020.1117.
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We study time-varying semidefinite programs (TV-SDPs), which are semidefinite programs whose data (and solutions) are functions of time. Our focus is on the setting where the data vary polynomially with time. We show that under a strict feasibility assumption, restricting the solutions to also be polynomial functions of time does not change the optimal value of the TV-SDP. Moreover, by using a Positivstellensatz (positive locus theorem) on univariate polynomial matrices, we show that the best polynomial solution of a given degree to a TV-SDP can be found by solving a semidefinite program of tractable size. We also provide a sequence of dual problems that can be cast as SDPs and that give upper bounds on the optimal value of a TV-SDP (in maximization form). We prove that under a boundedness assumption, this sequence of upper bounds converges to the optimal value of the TV-SDP. Under the same assumption, we also show that the optimal value of the TV-SDP is attained. We demonstrate the efficacy of our algorithms on a maximum-flow problem with time-varying edge capacities, a wireless coverage problem with time-varying coverage requirements, and on biobjective semidefinite optimization where the goal is to approximate the Pareto curve in one shot.
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Gogodze, Joseph. "Ranking Methods for Multicriteria Decision-Making: Application to Benchmarking of Solvers and Problems." Scientific Programming 2021 (July 11, 2021): 1–14. http://dx.doi.org/10.1155/2021/5513860.
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Evaluating the performance assessments of solvers (e.g., for computation programs), known as the solver benchmarking problem, has become a topic of intense study, and various approaches have been discussed in the literature. Such a variety of approaches exist because a benchmark problem is essentially a multicriteria problem. In particular, the appropriate multicriteria decision-making problem can correspond naturally to each benchmark problem and vice versa. In this study, to solve the solver benchmarking problem, we apply the ranking-theory method recently proposed for solving multicriteria decision-making problems. The benchmarking problem of differential evolution algorithms was considered for a case study to illustrate the ability of the proposed method. This problem was solved using ranking methods from different areas of origin. The comparisons revealed that the proposed method is competitive and can be successfully used to solve benchmarking problems and obtain relevant engineering decisions. This study can help practitioners and researchers use multicriteria decision-making approaches for benchmarking problems in different areas, particularly software benchmarking.
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Shi, Dongwei, Jingben Yin, and Chunyang Bai. "An Effective Global Optimization Algorithm for Quadratic Programs with Quadratic Constraints." Symmetry 11, no. 3 (March 22, 2019): 424. http://dx.doi.org/10.3390/sym11030424.
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This paper will present an effective algorithm for globally solving quadratic programs with quadratic constraints. In this algorithm, we propose a new linearization method for establishing the linear programming relaxation problem of quadratic programs with quadratic constraints. The proposed algorithm converges with the global optimal solution of the initial problem, and numerical experiments show the computational efficiency of the proposed algorithm.
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AIBA, AKIRA, KAZUMASA YOKOTA, and HIROSHI TSUDA. "HETEROGENEOUS DISTRIBUTED COOPERATIVE PROBLEM SOLVING SYSTEM HELIOS AND ITS COOPERATION MECHANISMS." International Journal of Cooperative Information Systems 04, no. 04 (December 1995): 369–85. http://dx.doi.org/10.1142/s0218843095000160.
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For advanced and complicated knowledge processing, we need to integrate various kinds of problem-solvers such as constraint solvers, databases, and application programs. A heterogeneous distributed cooperative problem solving system HELIOS achieves this integration by introducing capsule and environment modules. To integrate heterogeneous problem-solvers that may be implemented in different languages and may have different knowledge representations, those heterogeneity should be absorbed. Capsules and environments are introduced into HELIOS for this purpose. A capsule surrounds each problem-solver and translates the contents of communication to and from the internal representation and a common representation. We call an encapsulated problem-solver an agent. An environment is a module which provides a field giving common representation, and agents communicate and cooperate with each other in each environment. Since an encapsulated environment with its agents can be considered as an agent, agent-environment structures can be nested in HELIOS. For negotiation between agents, negotiation protocol can be defined in each environment. A negotiation strategy that suits the given negotiation protocol can be defined in each capsule of an agent. In this framework, we define a transaction-based negotiation protocol. To check the validity of HELIOS design and its implementation model on computers connected by network, we implemented an experimental version of HELIOS on UNIX workstations.
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Bouajjani, Ahmed, Javier Esparza, and Tayssir Touili. "A Generic Approach to the Static Analysis of Concurrent Programs with Procedures." International Journal of Foundations of Computer Science 14, no. 04 (August 2003): 551–82. http://dx.doi.org/10.1142/s0129054103001893.
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We present a generic aproach to the static analysis of concurrent programs with procedures. We model programs as communicating pushdown systems. It is known that typical dataflow problems for this model are undecidable, because the emptiness problem for the intersection of context-free languages, which is undecidable, can be reduced to them. In this paper we propose an algebraic framework for defining abstractions (upper approximations) of context-free languages. We consider two classes of abstractions: finite-chain abstractions, which are abstractions whose domains do not contain any infinite chains, and commutative abstractions corresponding to classes of languages that contain a word if and only if they contain all its permutations. We show how to compute such approximations by combining automata theoretic techniques with algorithms for solving systems of polynomial inequations in Kleene algebras.
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Jordaan, Annelie, and Dawid Jordaan. "A logical and structural thinking development tool (LST) to enhance fundamental problem-solving skills of learners of information technology." Journal for Transdisciplinary Research in Southern Africa 1, no. 1 (May 17, 2005): 18. http://dx.doi.org/10.4102/td.v1i1.303.
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The role of information technology in modern education has increased significantly over the past two decades [14]. The opportunity to develop an interactive software system with the aim of enhancing fundamental problem-solving skills of learners enrolled for the Computer Science, Information Technology and Mathematics programs at tertiary institutions is possible with object-oriented programming techniques and multi-dimensional graphic design. The definition of fundamental problem-solving skills includes cognitive functional skills such as logical thinking, conceptualism with prior knowledge, relationship forming and objective analysis. Experiments done for this research indicate that given the right educational tools, cognitive functional skills of learners can be stimulated, developed and enhanced. This, in turn, may lead to an increase in the graduation rates of learners enrolled for the Computer Science, Information Technology and Mathematics program and ultimately contribute to the reshaping of the educational experience.
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Holoubek, Josef, and Petr Zach. "Using Excel to reduce a Square Matrix." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 60, no. 4 (2012): 109–14. http://dx.doi.org/10.11118/actaun201260040109.
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When solving operations research problems, one can use either specialised computer programs such as Lingo, Lindo, Storm or more universal programs such Excel, Matlab, and R. To obtain the input data, one can use either a program’s own editor or other programs commonly available such as Excel. While the problem-solving methods, being part of various programs, are the subjects of numerous publications (such as Gros, 2003; Jablonský, 2002; Plevný – Žižka, 2007; Stevenson – Ozgur, 2009), the way the input data are obtained, recorded, and processed receives far less attention although this part of problem-solving requires considerable effort and, if the method for data recording is inadequate, may cause subsequent difficulties in their further processing. A problem known as “the travelling salesman problem” (TSP) may serve as an example. Here, the input data form a “square matrix of distances”. This paper is concerned with some Excel tools that can be used to obtain and subsequently modify such a square matrix. Given a square m × m matrix, an ordinary user might want to reduce it to an i × i square matrix (where i < m) without having to copy data from the matrix, skip some of its rows and/or columns or write a program to implement such a reduction.In her degree project, Kourková, 2009 was looking for an efficient method of reducing an Excel matrix. She had found no relevant papers on this subject concluding that the authors of the commercial program had not considered this. Therefore, she offered her own solution unconventionally using the contingency table menu option. Although this had resulted in the desired submatrix, some of its parts were superfluous and even baffling for the user.For this reason, the authors analyse the method of representing an m × m matrix and the way of its reduction. Finally, a better option is offered to achieve the desired objective as well as other methods of obtaining the required submatrix that even users without sufficient programming skills can use.
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Chugreyev, Vsevolod, Vadim Kaikov, and Tatiana Kapitonova. "Graphic programming by elements of nonstandard structural forms." SHS Web of Conferences 44 (2018): 00024. http://dx.doi.org/10.1051/shsconf/20184400024.
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The article describes one of the variants for solving the actual practical problem on information building modeling with application of several computer programs. The authors showed the relationship between graphic programming and model parameterization using specifications. The main purpose of the work was to show the algorithm for designing an architectural and construction object from the choice of the conceptual form to obtaining the information required for the industrial production of parts. The authors note the importance of studying similar problems in the framework of training courses of architecture and civil engineering universities.
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Louër, Michèle, and Daniel Louër. "The Use of PCs for AB Initio Structure Determination From Powder Diffraction Data." Advances in X-ray Analysis 37 (1993): 21–25. http://dx.doi.org/10.1154/s0376030800015470.
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The determination ab initio of crystal structures from powder diffraction data has been the most striking advance of modern powder crystallography. It is a consequence of the major developments occurred in instrument resolution, powder pattern indexing and Fitting techniques, e.g. the problem of peak overlap resulting from the collapse of the three dimensional pattern into one dimensional powder diffraction data has been circumvented by the advent of the Rietveld method. A structure analysis starting from scratch involves successive stages from the collection of high quality powder diffraction data to the refinement of the atomic coordinates by the Rietveld method. Since the pioneering work by Werner and co-workers a number of crystal structures solved from powder diffraction data, collected with synchrotron and conventional sources have been reported. With the growing development of this important application of the powder method, integrated softwares for solving crystal structures are now of interest, and a number of programs are available for the analysis of the different stages of a structural study. These programs combine computer routines for the treatment of powder diffraction data and routines used in conventional structure determination from single crystal data. Most of these programs have been listed in the Powder Diffraction Program Information 1990 Program List. Owing to the efficiency of modern personal computers, solving a crystal structure ab initio from powder diffraction data can now be carried out with a desk computer.
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Hay, Ian, and George Booker. "Teachers’ Perceptions and Classroom Application of Mathematical Computer Software." Journal of Cognitive Education and Psychology 6, no. 1 (January 2006): 61–71. http://dx.doi.org/10.1891/194589506787382350.
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Mathematics teachers from elementary and secondary school settings reported that the main advantage of instructional software pertained to enhancing students’ motivation and educational experiences, whereas the main disadvantage pertained to the poor content and sequencing of much of the available software. Teachers typically used software as a supplemental activity but wanted more programs that encouraged students’ cognitive reasoning, problem-solving and higher-order thinking skills in mathematics. These findings support the notion that although use of computer software has the potential to motivate, provide practice, and facilitate students’ learning and thinking in mathematics, students still require appropriate teacher-led instruction to enhance their mathematics knowledge as they interact with the software.
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Kanika, Shampa Chakraverty, and Pinaki Chakraborty. "Tools and Techniques for Teaching Computer Programming: A Review." Journal of Educational Technology Systems 49, no. 2 (May 27, 2020): 170–98. http://dx.doi.org/10.1177/0047239520926971.
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Courses on computer programming are included in the curricula of almost all engineering disciplines. We surveyed the research literature and identified the techniques that are commonly used by instructors for teaching these courses. We observed that visual programming and game-based learning can enhance computational thinking and problem-solving skills in students and may be used to introduce them to programming. Robot programming may be used to attract students to programming, but the success of this technique is subjected to the availability of robots. Pair and collaborative programming allows students to learn from one another and write efficient programs. Assessment systems help instructors in evaluating programs written by students and provide them with timely feedback. Furthermore, an analysis of citations showed that Scratch is the most researched tool for teaching programming. We discuss how these techniques may be used to teach introductory courses, advanced courses, and massive open online courses on programming.
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PELÁEZ, IGNACIO, FRANCISCO ALMEIDA, and DANIEL GONZÁLEZ. "HIGH LEVEL PARALLEL SKELETONS FOR DYNAMIC PROGRAMMING." Parallel Processing Letters 18, no. 01 (March 2008): 133–47. http://dx.doi.org/10.1142/s0129626408003272.
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Dynamic Programming is an important problem-solving technique used for solving a wide variety of optimization problems. Dynamic Programming programs are commonly designed as individual applications and software tools are usually tailored to specific classes of recurrences and methodologies. That contrasts with some other algorithmic techniques where a single generic program may solve all the instances. We have developed a general skeleton tool providing support for a wide range of dynamic programming methodologies on different parallel architectures. Genericity, flexibility and efficiency are basic issues of the design strategy. Parallelism is supplied to the user in a transparent manner through a common sequential interface. A set of test problems representative of different classes of Dynamic Programming formulations has been used to validate our skeleton on an IBM-SP.
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Smith, Mike U. "Comment on “identification of student misconceptions in genetics problem solving via computer program”." Journal of Research in Science Teaching 28, no. 4 (April 1991): 383–84. http://dx.doi.org/10.1002/tea.3660280410.
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Qiu, Yongjian, Yuming Zhu, and Jingben Yin. "Branch-and-Reduction Algorithm for Indefinite Quadratic Programming Problem." Complexity 2021 (March 30, 2021): 1–14. http://dx.doi.org/10.1155/2021/5578427.
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This paper presents a rectangular branch-and-reduction algorithm for globally solving indefinite quadratic programming problem (IQPP), which has a wide application in engineering design and optimization. In this algorithm, first of all, we convert the IQPP into an equivalent bilinear optimization problem (EBOP). Next, a novel linearizing technique is presented for deriving the linear relaxation programs problem (LRPP) of the EBOP, which can be used to obtain the lower bound of the global optimal value to the EBOP. To obtain a global optimal solution of the EBOP, the main computational task of the proposed algorithm involves the solutions of a sequence of LRPP. Moreover, the global convergent property of the algorithm is proved, and numerical experiments demonstrate the higher computational performance of the algorithm.