Relevant bibliographies by topics / Problem solving - Computer programs

Academic literature on the topic 'Problem solving - Computer programs'

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Published: 4 June 2021
Last updated: 19 February 2022

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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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Dissertations / Theses on the topic "Problem solving - Computer programs"

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Almazedi, A. K. R. "A study of learner control programs for teaching problem solving." Thesis, University of Leeds, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.354432.

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DeSa, Colin Joseph. "Distributed problem solving environments for scientific computing." Thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-08042009-040307/.

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PARK, SEUNG YIL. "A GENERALIZED INTELLIGENT PROBLEM SOLVING SYSTEM BASED ON A RELATIONAL MODEL FOR KNOWLEDGE REPRESENTATION (SUPPORT SYSTEMS, EXPERT, DECISION AIDS)." Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/183779.

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Over the past decade, two types of decision aids, i.e., decision support systems (DSS) and expert systems (ES), have been developed along parallel paths, showing some significant differences in their software architectures, capabilities, limitations, and other characteristics. The synergy of DSS and ES, however, has great potential for helping make possible a generalized approach to developing a decision aid that is powerful, intelligent, and friendly. This research establishes a framework for such decision aids in order to determine the elementary components and their interactions. Based on this framework, a generalized intelligent problem solving system (GIPSS) is deveolped as a decision aid generator. A relational model is designed to provide a unified logical view of each type of knowledge including factual data, modeling knowledge, and heuristic rules. In this knowledge model, a currently existing relational DBMS, with some extension, is utilized to manage each type of knowledge. For this purpose a relational resolution inference mechanism has been devised. A prototype GIPSS has been developed based on this framework. Two domain specific decision aids, COCOMO which estimates software development effort and cost, and CAPO which finds optimal process organization, have been implemented by using the GIPSS as a decision aid generator, demonstrating such features as its dynamic modeling capabilities and learning capabilities.
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Perez, y. Perez Rafael. "MEXICA : a computer model of creativity in writing." Thesis, University of Sussex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285399.

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Fox, Harold 1979. "Agent problem solving by inductive and deductive program synthesis." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/45882.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.
Includes bibliographical references (p. 203-206).
How do people learn abstract concepts unsupervised? Psychologists broadly recognize two types of concepts, declarative knowledge and procedural knowledge: know-what and know-how. While much work has focused on unsupervised learning of declarative concepts as clusters of features, there is much less clarity on the representation for procedural concepts and the methods for learning them. In this thesis, I claim that programs are a good representation for procedural knowledge, and that program synthesis is a promising mechanism for procedural learning. Prior attempts at AI program synthesis have taken a purely deductive approach to building provably corrent programs. This approach requires many axioms and non-trivial interaction with a human programmer. In contrast, this thesis introduces a new approach called SSGP (Sample Solve Generalize Prove), which combines inductive and deductive synthesis to autonomously synthesize programs with no extra knowledge outside of the program specification. The approach is to generate examples, solve the examples, generalize from the solutions, and then prove the generalization correct.This thesis presents two systems, Spec2Action and HELPS. Given a logical specification, Spec2Action determines the relations to change to perform simple operations on data structures. The main part of its task is to uncover the recursive structure of the domain from the purely logical input spec. HELPS generates sequential programs with loops and branches using STRIPS actions as the primitive statements. It solves generalizations of classic AI tasks like BlocksWorld. The two systems use SAT solving and other grounded reasoning techniques to solve the examples and generalize the solutions. To prove the abstracted hypotheses, the systems use a novel theorem prover for doing recursive proofs without an explicit induction axiom.
by Harold Fox.
Ph.D.
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Bekmann, Joachim Peter Computer Science &amp Engineering Faculty of Engineering UNSW. "Rapid development of problem-solvers with HeurEAKA! - a heuristic evolutionary algorithm and incremental knowledge acquisition approach." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/25748.

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A new approach for the development of problem-solvers for combinatorial problems is proposed in this thesis. The approach combines incremental knowledge acquisition and probabilistic search algorithms, such as evolutionary algorithms, to allow a human to rapidly develop problem-solvers in new domains in a framework called HeurEAKA. The approach addresses a known problem, that is, adapting evolutionary algorithms to the search domain by the introduction of domain knowledge. The development of specialised problem-solvers has historically been labour intensive. Implementing a problem-solver from scratch is very time consuming. Another approach is to adapt a general purpose search strategy to the problem domain. This is motivated by the observation that in order to scale an algorithm to solve complex problems, domain knowledge is needed. At present there is no systematic approach allowing one to efficiently engineer a specialpurpose search strategy for a given search problem. This means that, for example, adapting evolutionary algorithms (which are general purpose algorithms) is often very difficult and has lead some people to refer to their use as a ???black art???. In the HeurEAKA approach, domain knowledge is introduced by incrementally building a knowledge base that controls parts of the evolutionary algorithm. For example, the fitness function and the mutation operators in a genetic algorithm. An evolutionary search algorithm ismonitored by a human whomakes recommendations on search strategy based on individual solution candidates. It is assumed that the human has a reasonable intuition of the search problem. The human adds rules to a knowledge base describing how candidate solutions can be improved, or why they are desirable or undesirable in the search for a good solution. The incremental knowledge acquisition approach is inspired by the idea of (Nested) Ripple Down Rules. This approach sees a human provide exception rules to rules already existing in the knowledge base using concrete examples of inappropriate performance of the existing knowledge base. The Nested Ripple Down Rules (NRDR) approach allows humans to compose rules using concepts that are natural and intuitive to them. In HeurEAKA, NRDR are significantly adapted to form part of a probabilistic search algorithm. The probabilistic search algorithms used in the presented system are a genetic algorithm and a hierarchical bayesian optimization algorithm. The success of the HeurEAKA approach is demonstrated in experiments undertaken on industrially relevant domains. Problem-solvers were developed for detailed channel and switchbox routing in VLSI design and traffic light optimisation for urban road networks. The problem-solvers were developed in a short amount of time, in domains where a large amount of effort has gone into developing existing algorithms. Experiments show that chosen benchmark problems are solved as well or better than existing approaches. Particularly in the traffic light optimisation domain excellent results are achieved.
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Grover, Samir. "Solving layout compaction and wire-balancing problem using linear programming on the Monsoon multiprocessor." Thesis, Connect to online version, 1995. http://0-wwwlib.umi.com.mercury.concordia.ca/cr/concordia/fullcit?pMQ90885.

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Damon, Nolan Brandon. "On the feasibility of Moodle use to assist deaf and hard of hearing Grade 9 learners with mathematics problem-solving." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/96768.

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ENGLISH ABSTRACT: This thesis sets out to examine Moodle use to assist Deaf and Hard of Hearing Grade 9 learners with understanding mathematics problem-solving. The methodology used in this research project is that of formative evaluation. In this qualitative data analysis I worked as a participant-observer with three Deaf and H/H Grade 9 learners from a local school for the Deaf and H/H. These learners engaged in a course constructed in Moodle based on ratio and rate. The course was designed along the lines of a constructivist pedagogical model, different levels of learning as well as including multi representational features. Through the qualitative analysis of the interviews conducted with learners who participated in the research project and observation done by the teacher researcher, three categories emerged i.e. Weaknesses, Potential strengths and Learner suggestions. Although the findings indicate that different factors negatively impact Deaf and H/H learners’ ability to solve mathematics problems, it also highlights the representational features of mathematics content via Moodle, and how it can assist Deaf and H/H learners with the struggle with mathematics problem-solving.
AFRIKAANSE OPSOMMING: Die doel van hierdie navorsingsprojek is om te evaluereer of Moodle gebruik deur Dowe en Hardhorende graad 9 leerders hulle kan help met moeilikhede wat hulle ondervind met wiskunde probleem oplossing. Die navorsing is ‘n formatiewe evaluering. Binne hierdie kwalitatiewe data ontleding werk ek as ‘n deelnemer-navorser met 3 Dowe en Hardhorende graad 9 leerders by ‘n plaaslike skool vir Doof en Hardhorende leerders. Hierdie leerders het deelgeneem in leeraktiwiteite wat ontwerp is in Moodle en wat gebasseer is op verhouding en koers. Die leeraktiwiteite is ontwerp inlyn met ‘n konstruktivistiese pedagogiese model, verskillende vlakke van leer en multi voorstellings formate. Drie kategorieë o.a Tekortkominge, Moontlike Sterkpunte en Leerder voorstelle, het onstaan tydens die kwalitatiewe data ontleding waar onderhoude met die deelnemers gevoer asook observasie wat gedoen is deur die deelnemer-navorser. Alhoewel die bevindinge daarop dui dat verskillende faktore negatief inwerk op Dowe en Hardhorende leerders se vermoë om wiskunde problem op te los, wys dit ook uit die vermoë van Moodle om wiskunde probleme voor te stel en hoe hierdie voorstellings Dowe en Hardhorende leerders kan help met wiskunde probleem oplossing.
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Law, Lai-chong. "Empirical studies of program bugs and debugging strategies of novice BASIC programmers and the transferability of debugging skills to non-programming domains." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1992. http://hub.hku.hk/bib/B29789102.

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Huang, Angela Tzujui. "Develop heuristics to the popular Minesweeper game." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2545.

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This project describes Automine, a program intended to aid in the solving of the Minesweeper computer game. Automine is based on the Linux xwindow C program with xwindow graphic library. The program uses heuristics and probability statistics to help in determining safe squares and squares concealing mines with the goal of allowing a player to achieve minimal time performance. The source code for Automine and for a game simulation is provided in the appendices.
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Books on the topic "Problem solving - Computer programs"

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Problem solving and programs with C. 3rd ed. Toronto: Nelson Education, 2011.

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Tront, Joseph G. Problem solving with Borland's Eureka. New York: John Wiley, 1987.

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Tront, Joseph G. Problem solving with Borland's Eureka. New York: John Wiley, 1987.

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1957-, Fletcher Bill, and Curtin Dennis P. 1941-, eds. Business problem solving with Excel. Berkeley, Calif: Osborne McGraw-Hill, 1986.

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Frantz, Lynn. Problem solving with PC tools. Radnor, PA: Compute! Books, 1989.

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Savitch, Walter J. Problem solving with C++. 7th ed. Boston: Pearson/Addison Wesley, 2009.

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Problem solving with C++. 6th ed. Boston: Pearson Addison Wesley, 2007.

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Fowler, Sherry L. Problem solving with Microsoft Excel for windows'95. Upper Saddle River,N.J: Prentice-Hall, 1997.

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Ursula, Wolz, ed. Problem solving with Java. Reading, Mass: Addison-Wesley, 1999.

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Gips, James. Mastering Excel: A problem-solving approach. New York: Wiley, 1997.

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Book chapters on the topic "Problem solving - Computer programs"

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Zhou, Jianyang. "A constraint program for solving the job-shop problem." In Lecture Notes in Computer Science, 510–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61551-2_97.

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Sasano, Isao, Zhenjiang Hu, and Masato Takeichi. "Generation of Efficient Programs for Solving Maximum Multi-marking Problems." In Lecture Notes in Computer Science, 72–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44806-3_5.

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De Corte, Erik, Lieven Verschaffel, and Hilde Schrooten. "Cognitive Effects of Learning to Program in Logo: A One-Year Study With Sixth Graders." In Computer-Based Learning Environments and Problem Solving, 207–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77228-3_10.

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Tofte, Mads. "A Type Discipline for Solving Year 2000 Problems in COBOL Programs." In Lecture Notes in Computer Science, 442. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48340-3_40.

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Müller, Wolfgang, and Fritz Wysotzki. "Automatic synthesis of control programs by combination of learning and problem solving methods (Extended abstract)." In Lecture Notes in Computer Science, 323–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-59286-5_78.

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Riedel, Ralph, Ulrike Starker, and Rüdiger von der Weth. "A Multidisciplinary Model of Problem Solving in Complex Production Systems." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 387–94. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-662-44739-0_47.

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Belyaeva, I. N., N. A. Chekanov, A. A. Gusev, V. A. Rostovtsev, Yu A. Ukolov, Y. Uwano, and S. I. Vinitsky. "A MAPLE Symbolic-Numeric Program for Solving the 2D-Eigenvalue Problem by a Self-consistent Basis Method." In Computer Algebra in Scientific Computing, 32–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11555964_3.

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Wallace, Tracey D., and John T. Morris. "SwapMyMood: User-Centered Design and Development of a Mobile App to Support Executive Function." In Lecture Notes in Computer Science, 259–65. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58805-2_31.

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AbstractThis paper describes the research and development of the SwapMyMood smartphone application designed to support use of evidence-based executive function strategies by people with traumatic brain injury. Executive dysfunction is a common sequela of traumatic brain injury (TBI) resulting in diminished cognitive-behavioral functioning. Problem-solving and emotion regulation are cognitive-behavioral functions that are often disrupted by changes in the executive control system. SwapMyMood is an electronic version of the Executive Plus/STEP program, a set of clinical techniques taught to people living with brain injury to help them 1) identify and implement solutions to problems encountered in daily life and 2) to utilize the emotion cycle to understand and regulate emotional responses to these problems. The Executive Plus/STEP program has until now relied on paper-based instruction and use. Input from target users – people with brain injury and clinical professionals who teach this program to their patients – has contributed to key refinements of features and functioning of the mobile app. Data gathered from target user participation in the user-centered design process are presented. Future directions for ongoing development of technologies to support executive function strategies are also discussed.
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Unno, Hiroshi, Tachio Terauchi, and Eric Koskinen. "Constraint-Based Relational Verification." In Computer Aided Verification, 742–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81685-8_35.

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AbstractIn recent years they have been numerous works that aim to automate relational verification. Meanwhile, although Constrained Horn Clauses ($$\mathrm {CHCs}$$ CHCs ) empower a wide range of verification techniques and tools, they lack the ability to express hyperproperties beyond k-safety such as generalized non-interference and co-termination.This paper describes a novel and fully automated constraint-based approach to relational verification. We first introduce a new class of predicate Constraint Satisfaction Problems called $$\mathrm {pfwCSP}$$ pfwCSP where constraints are represented as clauses modulo first-order theories over predicate variables of three kinds: ordinary, well-founded, or functional. This generalization over $$\mathrm {CHCs}$$ CHCs permits arbitrary (i.e., possibly non-Horn) clauses, well-foundedness constraints, functionality constraints, and is capable of expressing these relational verification problems. Our approach enables us to express and automatically verify problem instances that require non-trivial (i.e., non-sequential and non-lock-step) self-composition by automatically inferring appropriate schedulers (or alignment) that dictate when and which program copies move. To solve problems in this new language, we present a constraint solving method for $$\mathrm {pfwCSP}$$ pfwCSP based on stratified CounterExample-Guided Inductive Synthesis (CEGIS) of ordinary, well-founded, and functional predicates.We have implemented the proposed framework and obtained promising results on diverse relational verification problems that are beyond the scope of the previous verification frameworks.
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Weik, Martin H. "problem solving." In Computer Science and Communications Dictionary, 1337. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_14719.

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Conference papers on the topic "Problem solving - Computer programs"

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Bright, Curtis, Kevin K. H. Cheung, Brett Stevens, Ilias Kotsireas, and Vijay Ganesh. "Unsatisfiability Proofs for Weight 16 Codewords in Lam's Problem." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/203.

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In the 1970s and 1980s, searches performed by L. Carter, C. Lam, L. Thiel, and S. Swiercz showed that projective planes of order ten with weight 16 codewords do not exist. These searches required highly specialized and optimized computer programs and required about 2,000 hours of computing time on mainframe and supermini computers. In 2010, these searches were verified by D. Roy using an optimized C program and 16,000 hours on a cluster of desktop machines. We performed a verification of these searches by reducing the problem to the Boolean satisfiability problem (SAT). Our verification uses the cube-and-conquer SAT solving paradigm, symmetry breaking techniques using the computer algebra system Maple, and a result of Carter that there are ten nonisomorphic cases to check. Our searches completed in about 30 hours on a desktop machine and produced nonexistence proofs of about 1 terabyte in the DRAT (deletion resolution asymmetric tautology) format.
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Morgan, A. P., and C. W. Wampler. "Solving a Planar Four-Bar Design Problem Using Continuation." In ASME 1989 Design Technical Conferences. American Society of Mechanical Engineers, 1989. http://dx.doi.org/10.1115/detc1989-0153.

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Abstract The problem of synthesizing a planar 4-bar with given pivots such that the coupler curve passes through live precision points is considered. It is shown that the design parameters must satisfy a system of 4 fourth-degree polynomial equations in 4 unknowns which has at most 36 nonzero real solutions. This polynomial system is solved using a continuation method, which thereby generates the collection of all designs that meet the precision-point specification. A computer program that implements this continuation method has been tested on a number of problems. It is reliable and fast enough for the purposes of design. The approach to kinematic design represented by this work is completely general, subject only to computer-time limitations that may arise for problems with many design elements.
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White, Mark, and Greg Epelbaum. "Problem Solving Tools in Waste-to-Energy Systems." In 14th Annual North American Waste-to-Energy Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/nawtec14-3194.

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Covanta is using a multifaceted approach to problem solving in Waste-to-Energy systems which combines several types of computer modeling with physical cold flow models, field testing, and engineering experience. This problem-solving approach is applied to boiler corrosion, gas and particulate flow patterns, reagent injection, and APC system issues. Our goals are to bring the most appropriate tools to each issue and incorporate results back into the engineering approach in order to continually improve our technical capabilities. Several types of computer modeling are used. A commercially available energy balance program is used for steam cycle evaluations and boiler energy balance and heat transfer calculations. Computational Fluid Dynamics (CFD) models are developed to investigate temperature and flow patterns where local conditions must be understood in detail. We have made extensive use of cold flow models to improve performance of APC systems, and to evaluate overfire air mixing in furnaces, and flow distribution through tube banks in boilers. Field testing is used to investigate temperature fluctuations and distributions, flow stratification, corrosion rates, and to validate modeling or analytical results. Each of these approaches has its own set of advantages, disadvantages, and limitations, and must always be combined with a healthy dose of operating and engineering experience. Analytical work is done by, or in close cooperation with, our operations and engineering staff with many years of experience operating, designing, and modifying boilers, APC systems, and related equipment. This integrated approach has yielded significant improvements in many cases and is being used in increasingly complex applications.
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Shoup, Terry E., and Thomas Shanks. "The Ethics Toolkit: A Computer Program for Teaching Ethics to Engineering Students." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/cie-4441.

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Abstract This paper describes a new computer application known as the Ethics Toolkit that is useful in enabling engineering students to learn about ethical problem solving. The application runs in a Windows environment and implements five different approaches to ethical problem solving found in the literature. Although the application does not provide absolute answers to ethical problems, it does facilitate the automation, organization and prioritization of solution possibilities.
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Cai, R. "An Engineering Method for Solving Axial Flow Cascade Inverse Problem." In ASME 1987 International Gas Turbine Conference and Exhibition. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/87-gt-147.

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The full inverse problem of axial flow cascade, to design an axial flow cascade with prescribed velocity distribution along the cascade blade, is solved with the Mean-Stream-Line Method (MSLM) originally proposed by Wu and Brown (1952). The selection of initial condition, the approach of iteration, the smoothing technique of calculation data, the determination of pitch/chord ratio and the applicable range of this method are discussed. Since this method is extremely simple and rapid, it is able to design a cascade very quickly and to program a design computer code with a very small computer. Some calculation examples are given and the calculation results are compared with other methods.
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Bzymek, Zbigniew M., and Teresa Lally. "The Brief Theory of Inventive Problem Solving: Practicality of Software Support." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-70438.

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The ongoing challenge of research in Engineering Design is to develop a tool that can support the most difficult phase: solving problems with contradictions. The Brief Theory of Inventive Problem Solving (BTIPS) is a prospective method for performing such a task. Derived from TRIZ, TSIP, and TIPS, BTIPS differs from those methods. The Principles, Effects and Prediction modules in BTIPS are enhanced to meet the newest challenges of technology, engineering practice and pedagogy. New principles were also added to BTIPS and technological effects were enriched with new developments based on nanotechnology and biotechnology. In addition the Virtual Element procedure approach was added. The tests of functions’ separation are also the new additions. This paper includes the results of research done on the effectiveness of software that could support BTIPS in the individual studies that include applications of the available computer programs. The advantages of using BTIPS with supporting software, such as Invention Machine™, TechOptimizer™, and Goldfire™, are pointed out. Some examples are given, but others could not be discussed because of the licensing constraints. The software, if it is used during the solving process, could speed up the search for the Ideal Solution and make BTIPS even more effective in education, and even in research, and practice.
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Hight, Timothy K., Lee E. Hornberger, Elizabeth Lawrence, and Matthew W. Gawlowski. "Hypermedia Programs for Mechanical Engineering." In ASME 1994 International Computers in Engineering Conference and Exhibition and the ASME 1994 8th Annual Database Symposium collocated with the ASME 1994 Design Technical Conferences. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/cie1994-0472.

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Abstract Engineers need to absorb and learn large amounts of new technical information. Effective methods of receiving this information are needed. Hypermedia stacks are one emerging avenue for information transmittal. This paper discusses two programs that have been created to address two distinct requirements for information transmittal — description of new technology in an easily accessible form, and guiding novices in developing skills and gaining insights in solving a particular type of problem. The first program was developed using a HyperCard stack and a Macintosh computer and describes current techniques available for rapid prototyping. Professional engineers and engineering students are largely unaware of these technologies because information on the subject is new. The second program is being developed using ToolBook under Windows and deals with the problem of sizing an idler shaft under given loads and operating conditions. This is a standard type of problem that might be given in a junior level machine design course. It draws on knowledge from statics and strength of materials and so acts as a review of fundamentals as well as a test of deeper understanding. This second program is at an earlier stage of development.
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Cuteri, Bernardo, Carmine Dodaro, Francesco Ricca, and Peter Schüller. "Overcoming the Grounding Bottleneck Due to Constraints in ASP Solving: Constraints Become Propagators." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/234.

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Answer Set Programming (ASP) is a well-known formalism for Knowledge Representation and Reasoning, successfully employed to solve many AI problems, also thanks to the availability of efficient implementations. Traditionally, ASP systems are based on the ground&solve approach, where the grounding transforms a general input program into its propositional counterpart, whose stable models are then computed by the solver using the CDCL algorithm. This approach suffers an intrinsic limitation: the grounding of one or few constraints may be unaffordable from a computational point of view; a problem known as grounding bottleneck. In this paper, we develop an innovative approach for evaluating ASP programs, where some of the constraints of the input program are not grounded but automatically translated into propagators of the CDCL algorithm that work on partial interpretations. We implemented the new approach on top of the solver WASP and carried out an experimental analysis on different benchmarks. Results show that our approach consistently outperforms state-of-the-art ASP systems by overcoming the grounding bottleneck.
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Wellington, Carol A., Rebecca Ward, and Alice Armstrong. "Work in progress — Using Video Phenomenography to investigate problem solving skill development in Computer Science I." In 2010 IEEE Frontiers in Education Conference (FIE). IEEE, 2010. http://dx.doi.org/10.1109/fie.2010.5673367.

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Soni, A. H., and Y. Weng. "Computer Aided Synthesis Equation Derivation for Mechanisms Design Automation." In ASME 1987 Design Technology Conferences. American Society of Mechanical Engineers, 1987. http://dx.doi.org/10.1115/detc1987-0024.

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Abstract EQ-1, an algebraic equation derivation system for a variety of mechanism synthesis motion programs, is presented in the paper. This project is considered as part of the automated mechanism design procedure. The applied Artificial Intelligence techniques are introduced to the mechanism design area. The blackboard model for problem solving is adopted in the system for organizing reasoning steps and domain knowledge to construct a solution to a specified mechanism configuration. A frame-like data structure is demonstrated in the system. The domain knowledge is kept in several independent knowledge sources. Meanwhile, the path propagation method is addressed to control the knowledge application.
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Reports on the topic "Problem solving - Computer programs"

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White, Steven, and John Lyman. Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada238949.

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Lyman, John, and Carla J. Conaway. Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication. Fort Belvoir, VA: Defense Technical Information Center, June 1991. http://dx.doi.org/10.21236/ada242797.

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Dierolf, David A., and Karen J. Richter. Computer-Aided Group Problem Solving for Unified Life Cycle Engineering (ULCE). Fort Belvoir, VA: Defense Technical Information Center, February 1989. http://dx.doi.org/10.21236/ada209446.

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Morehead, Leslie. Determining the Factors Influential in the Validation of Computer-based Problem Solving Systems. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.1244.

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Foreit, Karen. From problem-solving to research utilization: How operations research and program evaluation can make programs better. Population Council, 2013. http://dx.doi.org/10.31899/hiv10.1005.

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Henrick, Erin, Steven McGee, Lucia Dettori, Troy Williams, Andrew Rasmussen, Don Yanek, Ronald Greenberg, and Dale Reed. Research-Practice Partnership Strategies to Conduct and Use Research to Inform Practice. The Learning Partnership, April 2021. http://dx.doi.org/10.51420/conf.2021.3.

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This study examines the collaborative processes the Chicago Alliance for Equity in Computer Science (CAFÉCS) uses to conduct and use research. The CAFÉCS RPP is a partnership between Chicago Public Schools (CPS), Loyola University Chicago, The Learning Partnership, DePaul University, and University of Illinois at Chicago. Data used in this analysis comes from three years of evaluation data, and includes an analysis of team documents, meeting observations, and interviews with 25 members of the CAFÉCS RPP team. The analysis examines how three problems are being investigated by the partnership: 1) student failure rate in an introductory computer science course, 2) teachers’ limited use of discussion techniques in an introductory computer science class, and 3) computer science teacher retention. Results from the analysis indicate that the RPP engages in a formalized problem-solving cycle. The problem-solving cycle includes the following steps: First, the Office of Computer Science (OCS) identifies a problem. Next, the CAFÉCS team brainstorms and prioritizes hypotheses to test. Next, data analysis clarifies the problem and the research findings are shared and interpreted by the entire team. Finally, the findings are used to inform OCS improvement strategies and next steps for the CAFÉCS research agenda. There are slight variations in the problem-solving cycle, depending on the stage of understanding of the problem, which has implications for the mode of research (e.g hypothesis testing, research and design, continuous improvement, or evaluation).
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O’Brien, Tom, Deanna Matsumoto, Diana Sanchez, Caitlin Mace, Elizabeth Warren, Eleni Hala, and Tyler Reeb. Southern California Regional Workforce Development Needs Assessment for the Transportation and Supply Chain Industry Sectors. Mineta Transportation Institute, October 2020. http://dx.doi.org/10.31979/mti.2020.1921.

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COVID-19 brought the public’s attention to the critical value of transportation and supply chain workers as lifelines to access food and other supplies. This report examines essential job skills required of the middle-skill workforce (workers with more than a high school degree, but less than a four-year college degree). Many of these middle-skill transportation and supply chain jobs are what the Federal Reserve Bank defines as “opportunity occupations” -- jobs that pay above median wages and can be accessible to those without a four-year college degree. This report lays out the complex landscape of selected technological disruptions of the supply chain to understand the new workforce needs of these middle-skill workers, followed by competencies identified by industry. With workplace social distancing policies, logistics organizations now rely heavily on data management and analysis for their operations. All rungs of employees, including warehouse workers and truck drivers, require digital skills to use mobile devices, sensors, and dashboards, among other applications. Workforce training requires a focus on data, problem solving, connectivity, and collaboration. Industry partners identified key workforce competencies required in digital literacy, data management, front/back office jobs, and in operations and maintenance. Education and training providers identified strategies to effectively develop workforce development programs. This report concludes with an exploration of the role of Institutes of Higher Education in delivering effective workforce education and training programs that reimagine how to frame programs to be customizable, easily accessible, and relevant.
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