Models of resource allocation optimization when solving the control problems in organizational systems

NASA Astrophysics Data System (ADS)

Menshikh, V.; Samorokovskiy, A.; Avsentev, O.

2018-03-01

The mathematical model of optimizing the allocation of resources to reduce the time for management decisions and algorithms to solve the general problem of resource allocation. The optimization problem of choice of resources in organizational systems in order to reduce the total execution time of a job is solved. This problem is a complex three-level combinatorial problem, for the solving of which it is necessary to implement the solution to several specific problems: to estimate the duration of performing each action, depending on the number of performers within the group that performs this action; to estimate the total execution time of all actions depending on the quantitative composition of groups of performers; to find such a distribution of the existing resource of performers in groups to minimize the total execution time of all actions. In addition, algorithms to solve the general problem of resource allocation are proposed.

A Comparison of Two Mathematics Problem-Solving Strategies: Facilitate Algebra-Readiness

ERIC Educational Resources Information Center

Xin, Yan Ping; Zhang, Dake; Park, Joo Young; Tom, Kinsey; Whipple, Amanda; Si, Luo

2011-01-01

The authors compared a conceptual model-based problem-solving (COMPS) approach with a general heuristic instructional approach for teaching multiplication-division word-problem solving to elementary students with learning problems (LP). The results indicate that only the COMPS group significantly improved, from pretests to posttests, their…

Could HPS Improve Problem-Solving?

NASA Astrophysics Data System (ADS)

Coelho, Ricardo Lopes

2013-05-01

It is generally accepted nowadays that History and Philosophy of Science (HPS) is useful in understanding scientific concepts, theories and even some experiments. Problem-solving strategies are a significant topic, since students' careers depend on their skill to solve problems. These are the reasons for addressing the question of whether problem solving could be improved by means of HPS. Three typical problems in introductory courses of mechanics—the inclined plane, the simple pendulum and the Atwood machine—are taken as the object of the present study. The solving strategies of these problems in the eighteenth and nineteenth century constitute the historical component of the study. Its philosophical component stems from the foundations of mechanics research literature. The use of HPS leads us to see those problems in a different way. These different ways can be tested, for which experiments are proposed. The traditional solving strategies for the incline and pendulum problems are adequate for some situations but not in general. The recourse to apparent weights in the Atwood machine problem leads us to a new insight and a solving strategy for composed Atwood machines. Educational implications also concern the development of logical thinking by means of the variety of lines of thought provided by HPS.

Generalizing Backtrack-Free Search: A Framework for Search-Free Constraint Satisfaction

NASA Technical Reports Server (NTRS)

Jonsson, Ari K.; Frank, Jeremy

2000-01-01

Tractable classes of constraint satisfaction problems are of great importance in artificial intelligence. Identifying and taking advantage of such classes can significantly speed up constraint problem solving. In addition, tractable classes are utilized in applications where strict worst-case performance guarantees are required, such as constraint-based plan execution. In this work, we present a formal framework for search-free (backtrack-free) constraint satisfaction. The framework is based on general procedures, rather than specific propagation techniques, and thus generalizes existing techniques in this area. We also relate search-free problem solving to the notion of decision sets and use the result to provide a constructive criterion that is sufficient to guarantee search-free problem solving.

Math Ties: Problem Solving, Logic Teasers, and Math Puzzles All "Tied" to the Math Curriculum. Book A1.

ERIC Educational Resources Information Center

Santi, Terri

This book contains a classroom-tested approach to the teaching of problem solving to all students in Grades 4-6, regardless of ability. Information on problem solving in general is provided, then mathematical problems on logic, whole numbers, number theory, fractions, decimals, geometry, ratio, proportion, percent, probability, sets, and…

CHEMEX; Understanding and Solving Problems in Chemistry. A Computer-Assisted Instruction Program for General Chemistry.

ERIC Educational Resources Information Center

Lower, Stephen K.

A brief overview of CHEMEX--a problem-solving, tutorial style computer-assisted instructional course--is provided and sample problems are offered. In CHEMEX, students receive problems in advance and attempt to solve them before moving through the computer program, which assists them in overcoming difficulties and serves as a review mechanism.…

Could HPS Improve Problem-Solving?

ERIC Educational Resources Information Center

Coelho, Ricardo Lopes

2013-01-01

It is generally accepted nowadays that History and Philosophy of Science (HPS) is useful in understanding scientific concepts, theories and even some experiments. Problem-solving strategies are a significant topic, since students' careers depend on their skill to solve problems. These are the reasons for addressing the question of whether problem…

Linking attentional processes and conceptual problem solving: visual cues facilitate the automaticity of extracting relevant information from diagrams

PubMed Central

Rouinfar, Amy; Agra, Elise; Larson, Adam M.; Rebello, N. Sanjay; Loschky, Lester C.

2014-01-01

This study investigated links between visual attention processes and conceptual problem solving. This was done by overlaying visual cues on conceptual physics problem diagrams to direct participants’ attention to relevant areas to facilitate problem solving. Participants (N = 80) individually worked through four problem sets, each containing a diagram, while their eye movements were recorded. Each diagram contained regions that were relevant to solving the problem correctly and separate regions related to common incorrect responses. Problem sets contained an initial problem, six isomorphic training problems, and a transfer problem. The cued condition saw visual cues overlaid on the training problems. Participants’ verbal responses were used to determine their accuracy. This study produced two major findings. First, short duration visual cues which draw attention to solution-relevant information and aid in the organizing and integrating of it, facilitate both immediate problem solving and generalization of that ability to new problems. Thus, visual cues can facilitate re-representing a problem and overcoming impasse, enabling a correct solution. Importantly, these cueing effects on problem solving did not involve the solvers’ attention necessarily embodying the solution to the problem, but were instead caused by solvers attending to and integrating relevant information in the problems into a solution path. Second, this study demonstrates that when such cues are used across multiple problems, solvers can automatize the extraction of problem-relevant information extraction. These results suggest that low-level attentional selection processes provide a necessary gateway for relevant information to be used in problem solving, but are generally not sufficient for correct problem solving. Instead, factors that lead a solver to an impasse and to organize and integrate problem information also greatly facilitate arriving at correct solutions. PMID:25324804

Linking attentional processes and conceptual problem solving: visual cues facilitate the automaticity of extracting relevant information from diagrams.

PubMed

Rouinfar, Amy; Agra, Elise; Larson, Adam M; Rebello, N Sanjay; Loschky, Lester C

2014-01-01

This study investigated links between visual attention processes and conceptual problem solving. This was done by overlaying visual cues on conceptual physics problem diagrams to direct participants' attention to relevant areas to facilitate problem solving. Participants (N = 80) individually worked through four problem sets, each containing a diagram, while their eye movements were recorded. Each diagram contained regions that were relevant to solving the problem correctly and separate regions related to common incorrect responses. Problem sets contained an initial problem, six isomorphic training problems, and a transfer problem. The cued condition saw visual cues overlaid on the training problems. Participants' verbal responses were used to determine their accuracy. This study produced two major findings. First, short duration visual cues which draw attention to solution-relevant information and aid in the organizing and integrating of it, facilitate both immediate problem solving and generalization of that ability to new problems. Thus, visual cues can facilitate re-representing a problem and overcoming impasse, enabling a correct solution. Importantly, these cueing effects on problem solving did not involve the solvers' attention necessarily embodying the solution to the problem, but were instead caused by solvers attending to and integrating relevant information in the problems into a solution path. Second, this study demonstrates that when such cues are used across multiple problems, solvers can automatize the extraction of problem-relevant information extraction. These results suggest that low-level attentional selection processes provide a necessary gateway for relevant information to be used in problem solving, but are generally not sufficient for correct problem solving. Instead, factors that lead a solver to an impasse and to organize and integrate problem information also greatly facilitate arriving at correct solutions.

The Convergence of Intelligences

NASA Astrophysics Data System (ADS)

Diederich, Joachim

Minsky (1985) argued an extraterrestrial intelligence may be similar to ours despite very different origins. ``Problem- solving'' offers evolutionary advantages and individuals who are part of a technical civilisation should have this capacity. On earth, the principles of problem-solving are the same for humans, some primates and machines based on Artificial Intelligence (AI) techniques. Intelligent systems use ``goals'' and ``sub-goals'' for problem-solving, with memories and representations of ``objects'' and ``sub-objects'' as well as knowledge of relations such as ``cause'' or ``difference.'' Some of these objects are generic and cannot easily be divided into parts. We must, therefore, assume that these objects and relations are universal, and a general property of intelligence. Minsky's arguments from 1985 are extended here. The last decade has seen the development of a general learning theory (``computational learning theory'' (CLT) or ``statistical learning theory'') which equally applies to humans, animals and machines. It is argued that basic learning laws will also apply to an evolved alien intelligence, and this includes limitations of what can be learned efficiently. An example from CLT is that the general learning problem for neural networks is intractable, i.e. it cannot be solved efficiently for all instances (it is ``NP-complete''). It is the objective of this paper to show that evolved intelligences will be constrained by general learning laws and will use task-decomposition for problem-solving. Since learning and problem-solving are core features of intelligence, it can be said that intelligences converge despite very different origins.

Math Ties: Problem Solving, Logic Teasers, and Math Puzzles All "Tied" To the Math Curriculum. Book B1.

ERIC Educational Resources Information Center

Santi, Terri

This book contains a classroom-tested approach to the teaching of problem solving to all students in Grades 6-8, regardless of ability. Information on problem solving in general is provided, then mathematical problems on logic, exponents, fractions, pre-algebra, algebra, geometry, number theory, set theory, ratio, proportion, percent, probability,…

Teachers' ICT and Problem-Solving Skills: Competencies and Needs. Education Indicators in Focus. No. 40

ERIC Educational Resources Information Center

OECD Publishing, 2016

2016-01-01

The education sector performs well for information and communication technology (ICT) and problem-solving skills, although it still lags behind the professional, scientific and technical activities sector. Primary and secondary teachers have better ICT and problem-solving skills than the general population, and similar skills to other…

Effects of Problem Solving after Worked Example Study on Secondary School Children's Monitoring Accuracy

ERIC Educational Resources Information Center

Baars, Martine; van Gog, Tamara; de Bruin, Anique; Paas, Fred

2017-01-01

Monitoring accuracy, measured by judgements of learning (JOLs), has generally been found to be low to moderate, with students often displaying overconfidence, and JOLs of problem solving are no exception. Recently, primary school children's overconfidence was shown to diminish when they practised problem solving after studying worked examples. The…

Early Childhood Educators' Meta-Cognitive Knowledge of Problem-Solving Strategies and Quality of Childcare Curriculum Implementation

ERIC Educational Resources Information Center

Kim, Yeon Ha

2016-01-01

This study aims to explore the impact of early childhood educators' meta-cognitive knowledge on the quality of their childcare curriculum implementation, and to gain insights regarding successful problem-solving strategies associated with early education and care. Early childhood educators' implementation of general problem-solving strategies in…

Cognitive Science: Problem Solving And Learning For Physics Education

NASA Astrophysics Data System (ADS)

Ross, Brian H.

2007-11-01

Cognitive Science has focused on general principles of problem solving and learning that might be relevant for physics education research. This paper examines three selected issues that have relevance for the difficulty of transfer in problem solving domains: specialized systems of memory and reasoning, the importance of content in thinking, and a characterization of memory retrieval in problem solving. In addition, references to these issues are provided to allow the interested researcher entries to the literatures.

A New Approach for Solving the Generalized Traveling Salesman Problem

NASA Astrophysics Data System (ADS)

Pop, P. C.; Matei, O.; Sabo, C.

The generalized traveling problem (GTSP) is an extension of the classical traveling salesman problem. The GTSP is known to be an NP-hard problem and has many interesting applications. In this paper we present a local-global approach for the generalized traveling salesman problem. Based on this approach we describe a novel hybrid metaheuristic algorithm for solving the problem using genetic algorithms. Computational results are reported for Euclidean TSPlib instances and compared with the existing ones. The obtained results point out that our hybrid algorithm is an appropriate method to explore the search space of this complex problem and leads to good solutions in a reasonable amount of time.

Social problem-solving deficits and hopelessness, depression, and suicidal risk in college students and psychiatric inpatients.

PubMed

D'Zurilla, T J; Chang, E C; Nottingham, E J; Faccini, L

1998-12-01

The Social Problem-Solving Inventory-Revised was used to examine the relations between problem-solving abilities and hopelessness, depression, and suicidal risk in three different samples: undergraduate college students, general psychiatric inpatients, and suicidal psychiatric inpatients. A similar pattern of results was found in both college students and psychiatric patients: a negative problem orientation was most highly correlated with all three criterion variables, followed by either a positive problem orientation or an avoidance problem-solving style. Rational problem-solving skills emerged as an important predictor variable in the suicidal psychiatric sample. Support was found for a prediction model of suicidal risk that includes problem-solving deficits and hopelessness, with partial support being found for including depression in the model as well.

On the solution of the generalized wave and generalized sine-Gordon equations

NASA Technical Reports Server (NTRS)

Ablowitz, M. J.; Beals, R.; Tenenblat, K.

1986-01-01

The generalized wave equation and generalized sine-Gordon equations are known to be natural multidimensional differential geometric generalizations of the classical two-dimensional versions. In this paper, a system of linear differential equations is associated with these equations, and it is shown how the direct and inverse problems can be solved for appropriately decaying data on suitable lines. An initial-boundary value problem is solved for these equations.

Robot computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.

1972-01-01

Continuing research is reported in a program aimed at the development of a robot computer problem solving system. The motivation and results are described of a theoretical investigation concerning the general properties of behavioral systems. Some of the important issues which a general theory of behavioral organization should encompass are outlined and discussed.

Deaf and Hard of Hearing Students' Problem-Solving Strategies with Signed Arithmetic Story Problems

ERIC Educational Resources Information Center

Pagliaro, Claudia M.; Ansell, Ellen

2011-01-01

The use of problem-solving strategies by 59 deaf and hard of hearing children, grades K-3, was investigated. The children were asked to solve 9 arithmetic story problems presented to them in American Sign Language. The researchers found that while the children used the same general types of strategies that are used by hearing children (i.e.,…

Solving a class of generalized fractional programming problems using the feasibility of linear programs.

PubMed

Shen, Peiping; Zhang, Tongli; Wang, Chunfeng

2017-01-01

This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.

Use of Invariant Manifolds for Transfers Between Three-Body Systems

NASA Technical Reports Server (NTRS)

Beckman, Mark; Howell, Kathleen

2003-01-01

The Lunar L1 and L2 libration points have been proposed as gateways granting inexpensive access to interplanetary space. To date, only individual solutions to the transfer between three-body systems have been found. The methodology to solve the problem for arbitrary three-body systems and entire families of orbits does not exist. This paper presents the initial approaches to solve the general problem for single and multiple impulse transfers. Two different methods of representing and storing 7-dimensional invariant manifold data are presented. Some particular solutions are presented for the transfer problem, though the emphasis is on developing methodology for solving the general problem.

Representations of Invariant Manifolds for Applications in Three-Body Systems

NASA Technical Reports Server (NTRS)

Howell, K.; Beckman, M.; Patterson, C.; Folta, D.

2004-01-01

The Lunar L1 and L2 libration points have been proposed as gateways granting inexpensive access to interplanetary space. To date, only individual solutions to the transfer between three-body systems have been found. The methodology to solve the problem for arbitrary three-body systems and entire families of orbits is currently being studied. This paper presents an initial approach to solve the general problem for single and multiple impulse transfers. Two different methods of representing and storing the invariant manifold data are presented. Some particular solutions are presented for two types of transfer problems, though the emphasis is on developing the methodology for solving the general problem.

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Fikes, R. E.; Chaitin, L. J.; Hart, P. E.; Duda, R. O.; Nilsson, N. J.

1971-01-01

A program of research in the field of artificial intelligence is presented. The research areas discussed include automatic theorem proving, representations of real-world environments, problem-solving methods, the design of a programming system for problem-solving research, techniques for general scene analysis based upon television data, and the problems of assembling an integrated robot system. Major accomplishments include the development of a new problem-solving system that uses both formal logical inference and informal heuristic methods, the development of a method of automatic learning by generalization, and the design of the overall structure of a new complete robot system. Eight appendices to the report contain extensive technical details of the work described.

The contribution of general cognitive abilities and number abilities to different aspects of mathematics in children.

PubMed

Träff, Ulf

2013-10-01

This study examined the relative contributions of general cognitive abilities and number abilities to word problem solving, calculation, and arithmetic fact retrieval in a sample of 134 children aged 10 to 13 years. The following tasks were administered: listening span, visual matrix span, verbal fluency, color naming, Raven's Progressive Matrices, enumeration, number line estimation, and digit comparison. Hierarchical multiple regressions demonstrated that number abilities provided an independent contribution to fact retrieval and word problem solving. General cognitive abilities contributed to problem solving and calculation. All three number tasks accounted for a similar amount of variance in fact retrieval, whereas only the number line estimation task contributed unique variance in word problem solving. Verbal fluency and Raven's matrices accounted for an equal amount of variance in problem solving and calculation. The current findings demonstrate, in accordance with Fuchs and colleagues' developmental model of mathematical learning (Developmental Psychology, 2010, Vol. 46, pp. 1731-1746), that both number abilities and general cognitive abilities underlie 10- to 13-year-olds' proficiency in problem solving, whereas only number abilities underlie arithmetic fact retrieval. Thus, the amount and type of cognitive contribution to arithmetic proficiency varies between the different aspects of arithmetic. Furthermore, how closely linked a specific aspect of arithmetic is to the whole number representation systems is not the only factor determining the amount and type of cognitive contribution in 10- to 13-year-olds. In addition, the mathematical complexity of the task appears to influence the amount and type of cognitive support. Copyright © 2013 Elsevier Inc. All rights reserved.

The Effects of Duration of Exposure to the REAPS Model in Developing Students' General Creativity and Creative Problem Solving in Science

ERIC Educational Resources Information Center

Alhusaini, Abdulnasser Alashaal F.

2016-01-01

The Real Engagement in Active Problem Solving (REAPS) model was developed in 2004 by C. June Maker and colleagues as an intervention for gifted students to develop creative problem solving ability through the use of real-world problems. The primary purpose of this study was to examine the effects of the REAPS model on developing students' general…

Discovering Steiner Triple Systems through Problem Solving

ERIC Educational Resources Information Center

Sriraman, Bharath

2004-01-01

An attempt to implement problem solving as a teacher of ninth grade algebra is described. The problems selected were not general ones, they involved combinations and represented various situations and were more complex which lead to the discovery of Steiner triple systems.

Effects of Cognitive Strategy Interventions and Cognitive Moderators on Word Problem Solving in Children at Risk for Problem Solving Difficulties

ERIC Educational Resources Information Center

Swanson, H. Lee; Lussier, Cathy; Orosco, Michael

2013-01-01

This study investigated the role of strategy instruction and cognitive abilities on word problem solving accuracy in children with math difficulties (MD). Elementary school children (N = 120) with and without MD were randomly assigned to 1 of 4 conditions: general-heuristic (e.g., underline question sentence), visual-schematic presentation…

The Interrelationship of Sex, Visual Spatial Abilities, and Mathematical Problem Solving Ability in Grade Seven. Parts 1, 2, and 3.

ERIC Educational Resources Information Center

Schonberger, Ann Koch

This three-volume report deals with the hypothesis that males are more successful at solving mathematical and spatial problems than females. The general relationship between visual spatial abilities and mathematical problem-solving ability is also investigated. The research sample consisted of seventh graders. Each pupil took five spatial tests…

The Motivation of Problem-Based Teaching and Learning in Translation

ERIC Educational Resources Information Center

Yingxue, Zheng

2013-01-01

Problem-Based Learning (PBL) has been one of the popular pedagogical strategies these years. PBL is about students connecting disciplinary knowledge to real-world problems--the motivation to solve a problem. To recognize general elements and typological differences of language in translation is the motivation to solve real problems such as…

Solution of monotone complementarity and general convex programming problems using a modified potential reduction interior point method

DOE PAGES

Huang, Kuo -Ling; Mehrotra, Sanjay

2016-11-08

We present a homogeneous algorithm equipped with a modified potential function for the monotone complementarity problem. We show that this potential function is reduced by at least a constant amount if a scaled Lipschitz condition (SLC) is satisfied. A practical algorithm based on this potential function is implemented in a software package named iOptimize. The implementation in iOptimize maintains global linear and polynomial time convergence properties, while achieving practical performance. It either successfully solves the problem, or concludes that the SLC is not satisfied. When compared with the mature software package MOSEK (barrier solver version 6.0.0.106), iOptimize solves convex quadraticmore » programming problems, convex quadratically constrained quadratic programming problems, and general convex programming problems in fewer iterations. Moreover, several problems for which MOSEK fails are solved to optimality. In addition, we also find that iOptimize detects infeasibility more reliably than the general nonlinear solvers Ipopt (version 3.9.2) and Knitro (version 8.0).« less

ALPS: A Linear Program Solver

NASA Technical Reports Server (NTRS)

Ferencz, Donald C.; Viterna, Larry A.

1991-01-01

ALPS is a computer program which can be used to solve general linear program (optimization) problems. ALPS was designed for those who have minimal linear programming (LP) knowledge and features a menu-driven scheme to guide the user through the process of creating and solving LP formulations. Once created, the problems can be edited and stored in standard DOS ASCII files to provide portability to various word processors or even other linear programming packages. Unlike many math-oriented LP solvers, ALPS contains an LP parser that reads through the LP formulation and reports several types of errors to the user. ALPS provides a large amount of solution data which is often useful in problem solving. In addition to pure linear programs, ALPS can solve for integer, mixed integer, and binary type problems. Pure linear programs are solved with the revised simplex method. Integer or mixed integer programs are solved initially with the revised simplex, and the completed using the branch-and-bound technique. Binary programs are solved with the method of implicit enumeration. This manual describes how to use ALPS to create, edit, and solve linear programming problems. Instructions for installing ALPS on a PC compatible computer are included in the appendices along with a general introduction to linear programming. A programmers guide is also included for assistance in modifying and maintaining the program.

Students’ Algebraic Reasonsing In Solving Mathematical Problems With Adversity Quotient

NASA Astrophysics Data System (ADS)

Aryani, F.; Amin, S. M.; Sulaiman, R.

2018-01-01

Algebraic reasoning is a process in which students generalize mathematical ideas from a set of particular instances and express them in increasingly formal and age-appropriate ways. Using problem solving approach to develop algebraic reasoning of mathematics may enhace the long-term learning trajectory of the majority students. The purpose of this research was to describe the algebraic reasoning of quitter, camper, and climber junior high school students in solving mathematical problems. This research used qualitative descriptive method. Subjects were determined by purposive sampling. The technique of collecting data was done by task-based interviews.The results showed that the algebraic reasoning of three students in the process of pattern seeking by identifying the things that are known and asked in a similar way. But three students found the elements of pattern recognition in different ways or method. So, they are generalize the problem of pattern formation with different ways. The study of algebraic reasoning and problem solving can be a learning paradigm in the improve students’ knowledge and skills in algebra work. The goal is to help students’ improve academic competence, develop algebraic reasoning in problem solving.

Solving the Problem of Linear Viscoelasticity for Piecewise-Homogeneous Anisotropic Plates

NASA Astrophysics Data System (ADS)

Kaloerov, S. A.; Koshkin, A. A.

2017-11-01

An approximate method for solving the problem of linear viscoelasticity for thin anisotropic plates subject to transverse bending is proposed. The method of small parameter is used to reduce the problem to a sequence of boundary problems of applied theory of bending of plates solved using complex potentials. The general form of complex potentials in approximations and the boundary conditions for determining them are obtained. Problems for a plate with elliptic elastic inclusions are solved as an example. The numerical results for a plate with one, two elliptical (circular), and linear inclusions are analyzed.

Automated Test Assembly Using lp_Solve Version 5.5 in R

ERIC Educational Resources Information Center

Diao, Qi; van der Linden, Wim J.

2011-01-01

This article reviews the use of the software program lp_solve version 5.5 for solving mixed-integer automated test assembly (ATA) problems. The program is freely available under Lesser General Public License 2 (LGPL2). It can be called from the statistical language R using the lpSolveAPI interface. Three empirical problems are presented to…

Effects of the Multiple Solutions and Question Prompts on Generalization and Justification for Non-Routine Mathematical Problem Solving in a Computer Game Context

ERIC Educational Resources Information Center

Lee, Chun-Yi; Chen, Ming-Jang; Chang, Wen-Long

2014-01-01

The aim of this study is to investigate the effects of solution methods and question prompts on generalization and justification of non-routine problem solving for Grade 9 students. The learning activities are based on the context of the frog jumping game. In addition, related computer tools were used to support generalization and justification of…

An Ada Based Expert System for the Ada Version of SAtool II. Volume 1 and 2

DTIC Science & Technology

1991-06-06

Integrated Computer-Aided Manufacturing (ICAM) (20). In fact, IDEF 0 stands for ICAM Definition Method Zero . IDEF0 defines a subset of SA that omits...reasoning that has been programmed). An expert’s knowledge is specific to one problem domain as opposed to knowledge about general problem-solving...techniques. General problem domains are medicine, finance, science or engineering and so forth in which an expert can solve specific problems very well

Using Student-Developed, Inquiry-Based Experiments to Investigate the Contributions of Ca and Mg to Water Hardness

ERIC Educational Resources Information Center

Yang, Shui-Ping; Li, Chung-Chia

2009-01-01

This study provided a challenging opportunity for general chemistry students to mimic the scientific research process by solving a water-quality problem concerning individual calcium and magnesium concentrations. We found that general chemistry students were able to develop their own experiments to solve real-world, multivariable problems through…

The Effect of Using the TI-92 on Basic College Algebra Students' Ability To Solve Word Problems.

ERIC Educational Resources Information Center

Runde, Dennis C.

As part of an effort to improve community college algebra students' ability to solve word problems, a study was undertaken at Florida's Manatee Community College to determine the effects of using heuristic instruction (i.e., providing general rules for solving different types of math problems) in combination with the TI-92 calculator. The TI-92…

Is Word-Problem Solving a Form of Text Comprehension?

ERIC Educational Resources Information Center

Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.; Hamlett, Carol L.; Wang, Amber Y.

2015-01-01

This study's hypotheses were that (a) word-problem (WP) solving is a form of text comprehension that involves language comprehension processes, working memory, and reasoning, but (b) WP solving differs from other forms of text comprehension by requiring WP-specific language comprehension as well as general language comprehension. At the start of…

Design concepts for the development of cooperative problem-solving systems

NASA Technical Reports Server (NTRS)

Smith, Philip J.; Mccoy, Elaine; Layton, Chuck; Bihari, Tom

1992-01-01

There are many problem-solving tasks that are too complex to fully automate given the current state of technology. Nevertheless, significant improvements in overall system performance could result from the introduction of well-designed computer aids. We have been studying the development of cognitive tools for one such problem-solving task, enroute flight path planning for commercial airlines. Our goal was two-fold. First, we were developing specific systems designs to help with this important practical problem. Second, we are using this context to explore general design concepts to guide in the development of cooperative problem-solving systems. These designs concepts are described.

Diagrams benefit symbolic problem-solving.

PubMed

Chu, Junyi; Rittle-Johnson, Bethany; Fyfe, Emily R

2017-06-01

The format of a mathematics problem often influences students' problem-solving performance. For example, providing diagrams in conjunction with story problems can benefit students' understanding, choice of strategy, and accuracy on story problems. However, it remains unclear whether providing diagrams in conjunction with symbolic equations can benefit problem-solving performance as well. We tested the impact of diagram presence on students' performance on algebra equation problems to determine whether diagrams increase problem-solving success. We also examined the influence of item- and student-level factors to test the robustness of the diagram effect. We worked with 61 seventh-grade students who had received 2 months of pre-algebra instruction. Students participated in an experimenter-led classroom session. Using a within-subjects design, students solved algebra problems in two matched formats (equation and equation-with-diagram). The presence of diagrams increased equation-solving accuracy and the use of informal strategies. This diagram benefit was independent of student ability and item complexity. The benefits of diagrams found previously for story problems generalized to symbolic problems. The findings are consistent with cognitive models of problem-solving and suggest that diagrams may be a useful additional representation of symbolic problems. © 2017 The British Psychological Society.

Functional Techniques for Data Analysis

NASA Technical Reports Server (NTRS)

Tomlinson, John R.

1997-01-01

This dissertation develops a new general method of solving Prony's problem. Two special cases of this new method have been developed previously. They are the Matrix Pencil and the Osculatory Interpolation. The dissertation shows that they are instances of a more general solution type which allows a wide ranging class of linear functional to be used in the solution of the problem. This class provides a continuum of functionals which provide new methods that can be used to solve Prony's problem.

Cognitive Principles of Problem Solving and Instruction. Final Report.

ERIC Educational Resources Information Center

Greeno, James G.; And Others

Research in this project studied cognitive processes involved in understanding and solving problems used in instruction in the domain of mathematics, and explored implications of these cognitive analyses for the design of instruction. Three general issues were addressed: knowledge required for understanding problems, knowledge of the conditions…

Social problem solving strategies and posttraumatic stress disorder in the aftermath of intimate partner violence.

PubMed

Reich, Catherine M; Blackwell, Náthali; Simmons, Catherine A; Beck, J Gayle

2015-05-01

Social factors are often associated with the development or maintenance of posttraumatic stress disorder (PTSD) in the aftermath of interpersonal traumas. However, social problem solving strategies have received little attention. The current study explored the role of social problem solving styles (i.e., rational approaches, impulsive/careless strategies, or avoidance strategies) as intermediary variables between abuse exposure and PTSD severity among intimate partner violence survivors. Avoidance problem solving served as an intermediating variable for the relationship between three types of abuse and PTSD severity. Rational and impulsive/careless strategies were not associated with abuse exposure. These findings extend the current understanding of social problem solving among interpersonal trauma survivors and are consistent with more general avoidance coping research. Future research might examine whether avoidance problem solving tends to evolve in the aftermath of trauma or whether it represents a longstanding risk factor for PTSD development. Published by Elsevier Ltd.

Problem solving and decisionmaking: An integration

NASA Technical Reports Server (NTRS)

Dieterly, D. L.

1980-01-01

An attempt was made to redress a critical fault of decisionmaking and problem solving research-a lack of a standard method to classify problem or decision states or conditions. A basic model was identified and expanded to indicate a possible taxonomy of conditions which may be used in reviewing previous research or for systematically pursuing new research designs. A generalization of the basic conditions was then made to indicate that the conditions are essentially the same for both concepts, problem solving and decisionmaking.

Smoothed low rank and sparse matrix recovery by iteratively reweighted least squares minimization.

PubMed

Lu, Canyi; Lin, Zhouchen; Yan, Shuicheng

2015-02-01

This paper presents a general framework for solving the low-rank and/or sparse matrix minimization problems, which may involve multiple nonsmooth terms. The iteratively reweighted least squares (IRLSs) method is a fast solver, which smooths the objective function and minimizes it by alternately updating the variables and their weights. However, the traditional IRLS can only solve a sparse only or low rank only minimization problem with squared loss or an affine constraint. This paper generalizes IRLS to solve joint/mixed low-rank and sparse minimization problems, which are essential formulations for many tasks. As a concrete example, we solve the Schatten-p norm and l2,q-norm regularized low-rank representation problem by IRLS, and theoretically prove that the derived solution is a stationary point (globally optimal if p,q ≥ 1). Our convergence proof of IRLS is more general than previous one that depends on the special properties of the Schatten-p norm and l2,q-norm. Extensive experiments on both synthetic and real data sets demonstrate that our IRLS is much more efficient.

Sleep Does Not Promote Solving Classical Insight Problems and Magic Tricks

PubMed Central

Schönauer, Monika; Brodt, Svenja; Pöhlchen, Dorothee; Breßmer, Anja; Danek, Amory H.; Gais, Steffen

2018-01-01

During creative problem solving, initial solution attempts often fail because of self-imposed constraints that prevent us from thinking out of the box. In order to solve a problem successfully, the problem representation has to be restructured by combining elements of available knowledge in novel and creative ways. It has been suggested that sleep supports the reorganization of memory representations, ultimately aiding problem solving. In this study, we systematically tested the effect of sleep and time on problem solving, using classical insight tasks and magic tricks. Solving these tasks explicitly requires a restructuring of the problem representation and may be accompanied by a subjective feeling of insight. In two sessions, 77 participants had to solve classical insight problems and magic tricks. The two sessions either occurred consecutively or were spaced 3 h apart, with the time in between spent either sleeping or awake. We found that sleep affected neither general solution rates nor the number of solutions accompanied by sudden subjective insight. Our study thus adds to accumulating evidence that sleep does not provide an environment that facilitates the qualitative restructuring of memory representations and enables problem solving. PMID:29535620

Do job demands and job control affect problem-solving?

PubMed

Bergman, Peter N; Ahlberg, Gunnel; Johansson, Gun; Stoetzer, Ulrich; Aborg, Carl; Hallsten, Lennart; Lundberg, Ingvar

2012-01-01

The Job Demand Control model presents combinations of working conditions that may facilitate learning, the active learning hypothesis, or have detrimental effects on health, the strain hypothesis. To test the active learning hypothesis, this study analysed the effects of job demands and job control on general problem-solving strategies. A population-based sample of 4,636 individuals (55% women, 45% men) with the same job characteristics measured at two times with a three year time lag was used. Main effects of demands, skill discretion, task authority and control, and the combined effects of demands and control were analysed in logistic regressions, on four outcomes representing general problem-solving strategies. Those reporting high on skill discretion, task authority and control, as well as those reporting high demand/high control and low demand/high control job characteristics were more likely to state using problem solving strategies. Results suggest that working conditions including high levels of control may affect how individuals cope with problems and that workplace characteristics may affect behaviour in the non-work domain.

Fostering Persistence: 3D Printing and the Unforeseen Impact on Equity

ERIC Educational Resources Information Center

FitzPatrick, Daniel L.; Dominguez, Victoria S.

2017-01-01

Teaching persistence and problem solving must begin with selecting a problem that can be solved mathematically, that allows for multiple methods of solving, and that generally captures the attention and curiosity of the student (Marcus and Fey 2003; NCTM 1991; Van de Walle 2003). This article shows how a STEM three-dimensional (3D) printing…

PowerPlay: Training an Increasingly General Problem Solver by Continually Searching for the Simplest Still Unsolvable Problem

PubMed Central

Schmidhuber, Jürgen

2013-01-01

Most of computer science focuses on automatically solving given computational problems. I focus on automatically inventing or discovering problems in a way inspired by the playful behavior of animals and humans, to train a more and more general problem solver from scratch in an unsupervised fashion. Consider the infinite set of all computable descriptions of tasks with possibly computable solutions. Given a general problem-solving architecture, at any given time, the novel algorithmic framework PowerPlay (Schmidhuber, 2011) searches the space of possible pairs of new tasks and modifications of the current problem solver, until it finds a more powerful problem solver that provably solves all previously learned tasks plus the new one, while the unmodified predecessor does not. Newly invented tasks may require to achieve a wow-effect by making previously learned skills more efficient such that they require less time and space. New skills may (partially) re-use previously learned skills. The greedy search of typical PowerPlay variants uses time-optimal program search to order candidate pairs of tasks and solver modifications by their conditional computational (time and space) complexity, given the stored experience so far. The new task and its corresponding task-solving skill are those first found and validated. This biases the search toward pairs that can be described compactly and validated quickly. The computational costs of validating new tasks need not grow with task repertoire size. Standard problem solver architectures of personal computers or neural networks tend to generalize by solving numerous tasks outside the self-invented training set; PowerPlay’s ongoing search for novelty keeps breaking the generalization abilities of its present solver. This is related to Gödel’s sequence of increasingly powerful formal theories based on adding formerly unprovable statements to the axioms without affecting previously provable theorems. The continually increasing repertoire of problem-solving procedures can be exploited by a parallel search for solutions to additional externally posed tasks. PowerPlay may be viewed as a greedy but practical implementation of basic principles of creativity (Schmidhuber, 2006a, 2010). A first experimental analysis can be found in separate papers (Srivastava et al., 2012a,b, 2013). PMID:23761771

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Kuo -Ling; Mehrotra, Sanjay

We present a homogeneous algorithm equipped with a modified potential function for the monotone complementarity problem. We show that this potential function is reduced by at least a constant amount if a scaled Lipschitz condition (SLC) is satisfied. A practical algorithm based on this potential function is implemented in a software package named iOptimize. The implementation in iOptimize maintains global linear and polynomial time convergence properties, while achieving practical performance. It either successfully solves the problem, or concludes that the SLC is not satisfied. When compared with the mature software package MOSEK (barrier solver version 6.0.0.106), iOptimize solves convex quadraticmore » programming problems, convex quadratically constrained quadratic programming problems, and general convex programming problems in fewer iterations. Moreover, several problems for which MOSEK fails are solved to optimality. In addition, we also find that iOptimize detects infeasibility more reliably than the general nonlinear solvers Ipopt (version 3.9.2) and Knitro (version 8.0).« less

Enroute flight planning: Evaluating design concepts for the development of cooperative problem-solving systems

NASA Technical Reports Server (NTRS)

Smith, Philip J.

1995-01-01

There are many problem-solving tasks that are too complex to fully automate given the current state of technology. Nevertheless, significant improvements in overall system performance could result from the introduction of well-designed computer aids. We have been studying the development of cognitive tools for one such problem-solving task, enroute flight path planning for commercial airlines. Our goal has been two-fold. First, we have been developing specific system designs to help with this important practical problem. Second, we have been using this context to explore general design concepts to guide in the development of cooperative problem-solving systems. These design concepts are described below, along with illustrations of their application.

A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems.

PubMed

Gong, Pinghua; Zhang, Changshui; Lu, Zhaosong; Huang, Jianhua Z; Ye, Jieping

2013-01-01

Non-convex sparsity-inducing penalties have recently received considerable attentions in sparse learning. Recent theoretical investigations have demonstrated their superiority over the convex counterparts in several sparse learning settings. However, solving the non-convex optimization problems associated with non-convex penalties remains a big challenge. A commonly used approach is the Multi-Stage (MS) convex relaxation (or DC programming), which relaxes the original non-convex problem to a sequence of convex problems. This approach is usually not very practical for large-scale problems because its computational cost is a multiple of solving a single convex problem. In this paper, we propose a General Iterative Shrinkage and Thresholding (GIST) algorithm to solve the nonconvex optimization problem for a large class of non-convex penalties. The GIST algorithm iteratively solves a proximal operator problem, which in turn has a closed-form solution for many commonly used penalties. At each outer iteration of the algorithm, we use a line search initialized by the Barzilai-Borwein (BB) rule that allows finding an appropriate step size quickly. The paper also presents a detailed convergence analysis of the GIST algorithm. The efficiency of the proposed algorithm is demonstrated by extensive experiments on large-scale data sets.

Problem-Solving After Traumatic Brain Injury in Adolescence: Associations With Functional Outcomes

PubMed Central

Wade, Shari L.; Cassedy, Amy E.; Fulks, Lauren E.; Taylor, H. Gerry; Stancin, Terry; Kirkwood, Michael W.; Yeates, Keith O.; Kurowski, Brad G.

2017-01-01

Objective To examine the association of problem-solving with functioning in youth with traumatic brain injury (TBI). Design Cross-sectional evaluation of pretreatment data from a randomized controlled trial. Setting Four children’s hospitals and 1 general hospital, with level 1 trauma units. Participants Youth, ages 11 to 18 years, who sustained moderate or severe TBI in the last 18 months (N=153). Main Outcome Measures Problem-solving skills were assessed using the Social Problem-Solving Inventory (SPSI) and the Dodge Social Information Processing Short Stories. Everyday functioning was assessed based on a structured clinical interview using the Child and Adolescent Functional Assessment Scale (CAFAS) and via adolescent ratings on the Youth Self Report (YSR). Correlations and multiple regression analyses were used to examine associations among measures. Results The TBI group endorsed lower levels of maladaptive problem-solving (negative problem orientation, careless/impulsive responding, and avoidant style) and lower levels of rational problem-solving, resulting in higher total problem-solving scores for the TBI group compared with a normative sample (P<.001). Dodge Social Information Processing Short Stories dimensions were correlated (r=.23–.37) with SPSI subscales in the anticipated direction. Although both maladaptive (P<.001) and adaptive (P=.006) problem-solving composites were associated with overall functioning on the CAFAS, only maladaptive problem-solving (P<.001) was related to the YSR total when outcomes were continuous. For the both CAFAS and YSR logistic models, maladaptive style was significantly associated with greater risk of impairment (P=.001). Conclusions Problem-solving after TBI differs from normative samples and is associated with functional impairments. The relation of problem-solving deficits after TBI with global functioning merits further investigation, with consideration of the potential effects of problem-solving interventions on functional outcomes. PMID:28389109

Problem-Solving After Traumatic Brain Injury in Adolescence: Associations With Functional Outcomes.

PubMed

Wade, Shari L; Cassedy, Amy E; Fulks, Lauren E; Taylor, H Gerry; Stancin, Terry; Kirkwood, Michael W; Yeates, Keith O; Kurowski, Brad G

2017-08-01

To examine the association of problem-solving with functioning in youth with traumatic brain injury (TBI). Cross-sectional evaluation of pretreatment data from a randomized controlled trial. Four children's hospitals and 1 general hospital, with level 1 trauma units. Youth, ages 11 to 18 years, who sustained moderate or severe TBI in the last 18 months (N=153). Problem-solving skills were assessed using the Social Problem-Solving Inventory (SPSI) and the Dodge Social Information Processing Short Stories. Everyday functioning was assessed based on a structured clinical interview using the Child and Adolescent Functional Assessment Scale (CAFAS) and via adolescent ratings on the Youth Self Report (YSR). Correlations and multiple regression analyses were used to examine associations among measures. The TBI group endorsed lower levels of maladaptive problem-solving (negative problem orientation, careless/impulsive responding, and avoidant style) and lower levels of rational problem-solving, resulting in higher total problem-solving scores for the TBI group compared with a normative sample (P<.001). Dodge Social Information Processing Short Stories dimensions were correlated (r=.23-.37) with SPSI subscales in the anticipated direction. Although both maladaptive (P<.001) and adaptive (P=.006) problem-solving composites were associated with overall functioning on the CAFAS, only maladaptive problem-solving (P<.001) was related to the YSR total when outcomes were continuous. For the both CAFAS and YSR logistic models, maladaptive style was significantly associated with greater risk of impairment (P=.001). Problem-solving after TBI differs from normative samples and is associated with functional impairments. The relation of problem-solving deficits after TBI with global functioning merits further investigation, with consideration of the potential effects of problem-solving interventions on functional outcomes. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Assessing student written problem solutions: A problem-solving rubric with application to introductory physics

NASA Astrophysics Data System (ADS)

Docktor, Jennifer L.; Dornfeld, Jay; Frodermann, Evan; Heller, Kenneth; Hsu, Leonardo; Jackson, Koblar Alan; Mason, Andrew; Ryan, Qing X.; Yang, Jie

2016-06-01

Problem solving is a complex process valuable in everyday life and crucial for learning in the STEM fields. To support the development of problem-solving skills it is important for researchers and curriculum developers to have practical tools that can measure the difference between novice and expert problem-solving performance in authentic classroom work. It is also useful if such tools can be employed by instructors to guide their pedagogy. We describe the design, development, and testing of a simple rubric to assess written solutions to problems given in undergraduate introductory physics courses. In particular, we present evidence for the validity, reliability, and utility of the instrument. The rubric identifies five general problem-solving processes and defines the criteria to attain a score in each: organizing problem information into a Useful Description, selecting appropriate principles (Physics Approach), applying those principles to the specific conditions in the problem (Specific Application of Physics), using Mathematical Procedures appropriately, and displaying evidence of an organized reasoning pattern (Logical Progression).

Time-domain finite elements in optimal control with application to launch-vehicle guidance. PhD. Thesis

NASA Technical Reports Server (NTRS)

Bless, Robert R.

1991-01-01

A time-domain finite element method is developed for optimal control problems. The theory derived is general enough to handle a large class of problems including optimal control problems that are continuous in the states and controls, problems with discontinuities in the states and/or system equations, problems with control inequality constraints, problems with state inequality constraints, or problems involving any combination of the above. The theory is developed in such a way that no numerical quadrature is necessary regardless of the degree of nonlinearity in the equations. Also, the same shape functions may be employed for every problem because all strong boundary conditions are transformed into natural or weak boundary conditions. In addition, the resulting nonlinear algebraic equations are very sparse. Use of sparse matrix solvers allows for the rapid and accurate solution of very difficult optimization problems. The formulation is applied to launch-vehicle trajectory optimization problems, and results show that real-time optimal guidance is realizable with this method. Finally, a general problem solving environment is created for solving a large class of optimal control problems. The algorithm uses both FORTRAN and a symbolic computation program to solve problems with a minimum of user interaction. The use of symbolic computation eliminates the need for user-written subroutines which greatly reduces the setup time for solving problems.

Use of model analysis to analyse Thai students’ attitudes and approaches to physics problem solving

NASA Astrophysics Data System (ADS)

Rakkapao, S.; Prasitpong, S.

2018-03-01

This study applies the model analysis technique to explore the distribution of Thai students’ attitudes and approaches to physics problem solving and how those attitudes and approaches change as a result of different experiences in physics learning. We administered the Attitudes and Approaches to Problem Solving (AAPS) survey to over 700 Thai university students from five different levels, namely students entering science, first-year science students, and second-, third- and fourth-year physics students. We found that their inferred mental states were generally mixed. The largest gap between physics experts and all levels of the students was about the role of equations and formulas in physics problem solving, and in views towards difficult problems. Most participants of all levels believed that being able to handle the mathematics is the most important part of physics problem solving. Most students’ views did not change even though they gained experiences in physics learning.

The ABCs of Math: A Genetic Analysis of Mathematics and Its Links With Reading Ability and General Cognitive Ability

PubMed Central

Hart, Sara A.; Petrill, Stephen A.; Thompson, Lee A.; Plomin, Robert

2009-01-01

The goal of this first major report from the Western Reserve Reading Project Math component is to explore the etiology of the relationship among tester-administered measures of mathematics ability, reading ability, and general cognitive ability. Data are available on 314 pairs of monozygotic and same-sex dizygotic twins analyzed across 5 waves of assessment. Univariate analyses provide a range of estimates of genetic (h2 = .00 –.63) and shared (c2 = .15–.52) environmental influences across math calculation, fluency, and problem solving measures. Multivariate analyses indicate genetic overlap between math problem solving with general cognitive ability and reading decoding, whereas math fluency shares significant genetic overlap with reading fluency and general cognitive ability. Further, math fluency has unique genetic influences. In general, math ability has shared environmental overlap with general cognitive ability and decoding. These results indicate that aspects of math that include problem solving have different genetic and environmental influences than math calculation. Moreover, math fluency, a timed measure of calculation, is the only measured math ability with unique genetic influences. PMID:20157630

A Study on the Application of Creative Problem Solving Teaching to Statistics Teaching

ERIC Educational Resources Information Center

Hu, Ridong; Xiaohui, Su; Shieh, Chich-Jen

2017-01-01

Everyone would encounter the life issue of solving complicated problems generated by economic behaviors among all activities for making a living. Various life problems encountered therefore could be generalized by economic statistics. In other words, a lot of important events in daily life are related to economic statistics. For this reason,…

Comparative Properties of Collaborative Optimization and Other Approaches to MDO

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia M.; Lewis, Robert Michael

1999-01-01

We, discuss criteria by which one can classify, analyze, and evaluate approaches to solving multidisciplinary design optimization (MDO) problems. Central to our discussion is the often overlooked distinction between questions of formulating MDO problems and solving the resulting computational problem. We illustrate our general remarks by comparing several approaches to MDO that have been proposed.

Comparative Properties of Collaborative Optimization and other Approaches to MDO

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia M.; Lewis, Robert Michael

1999-01-01

We discuss criteria by which one can classify, analyze, and evaluate approaches to solving multidisciplinary design optimization (MDO) problems. Central to our discussion is the often overlooked distinction between questions of formulating MDO problems and solving the resulting computational problem. We illustrate our general remarks by comparing several approaches to MDO that have been proposed.

A hybrid symbolic/finite-element algorithm for solving nonlinear optimal control problems

NASA Technical Reports Server (NTRS)

Bless, Robert R.; Hodges, Dewey H.

1991-01-01

The general code described is capable of solving difficult nonlinear optimal control problems by using finite elements and a symbolic manipulator. Quick and accurate solutions are obtained with a minimum for user interaction. Since no user programming is required for most problems, there are tremendous savings to be gained in terms of time and money.

Conceptual Comparison of Population Based Metaheuristics for Engineering Problems

PubMed Central

Green, Paul

2015-01-01

Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems. Several extensions of differential evolution have been adopted in solving constrained and nonconstrained multiobjective optimization problems, but in this study, the third version of generalized differential evolution (GDE) is used for solving practical engineering problems. GDE3 metaheuristic modifies the selection process of the basic differential evolution and extends DE/rand/1/bin strategy in solving practical applications. The performance of the metaheuristic is investigated through engineering design optimization problems and the results are reported. The comparison of the numerical results with those of other metaheuristic techniques demonstrates the promising performance of the algorithm as a robust optimization tool for practical purposes. PMID:25874265

Conceptual comparison of population based metaheuristics for engineering problems.

PubMed

Adekanmbi, Oluwole; Green, Paul

2015-01-01

Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems. Several extensions of differential evolution have been adopted in solving constrained and nonconstrained multiobjective optimization problems, but in this study, the third version of generalized differential evolution (GDE) is used for solving practical engineering problems. GDE3 metaheuristic modifies the selection process of the basic differential evolution and extends DE/rand/1/bin strategy in solving practical applications. The performance of the metaheuristic is investigated through engineering design optimization problems and the results are reported. The comparison of the numerical results with those of other metaheuristic techniques demonstrates the promising performance of the algorithm as a robust optimization tool for practical purposes.

Multi-level adaptive finite element methods. 1: Variation problems

NASA Technical Reports Server (NTRS)

Brandt, A.

1979-01-01

A general numerical strategy for solving partial differential equations and other functional problems by cycling between coarser and finer levels of discretization is described. Optimal discretization schemes are provided together with very fast general solvers. It is described in terms of finite element discretizations of general nonlinear minimization problems. The basic processes (relaxation sweeps, fine-grid-to-coarse-grid transfers of residuals, coarse-to-fine interpolations of corrections) are directly and naturally determined by the objective functional and the sequence of approximation spaces. The natural processes, however, are not always optimal. Concrete examples are given and some new techniques are reviewed. Including the local truncation extrapolation and a multilevel procedure for inexpensively solving chains of many boundary value problems, such as those arising in the solution of time-dependent problems.

Large-scale studies on the transferability of general problem-solving skills and the pedagogic potential of physics

NASA Astrophysics Data System (ADS)

Mashood, K. K.; Singh, Vijay A.

2013-09-01

Research suggests that problem-solving skills are transferable across domains. This claim, however, needs further empirical substantiation. We suggest correlation studies as a methodology for making preliminary inferences about transfer. The correlation of the physics performance of students with their performance in chemistry and mathematics in highly competitive problem-solving examinations was studied using a massive database. The sample sizes ranged from hundreds to a few hundred thousand. Encouraged by the presence of significant correlations, we interviewed 20 students to explore the pedagogic potential of physics in imparting transferable problem-solving skills. We report strategies and practices relevant to physics employed by these students which foster transfer.

Intuitive Feelings of Warmth and Confidence in Insight and Noninsight Problem Solving of Magic Tricks.

PubMed

Hedne, Mikael R; Norman, Elisabeth; Metcalfe, Janet

2016-01-01

The focus of the current study is on intuitive feelings of insight during problem solving and the extent to which such feelings are predictive of successful problem solving. We report the results from an experiment (N = 51) that applied a procedure where the to-be-solved problems were 32 short (15 s) video recordings of magic tricks. The procedure included metacognitive ratings similar to the "warmth ratings" previously used by Metcalfe and colleagues, as well as confidence ratings. At regular intervals during problem solving, participants indicated the perceived closeness to the correct solution. Participants also indicated directly whether each problem was solved by insight or not. Problems that people claimed were solved by insight were characterized by higher accuracy and higher confidence than noninsight solutions. There was no difference between the two types of solution in warmth ratings, however. Confidence ratings were more strongly associated with solution accuracy for noninsight than insight trials. Moreover, for insight trials the participants were more likely to repeat their incorrect solutions on a subsequent recognition test. The results have implications for understanding people's metacognitive awareness of the cognitive processes involved in problem solving. They also have general implications for our understanding of how intuition and insight are related.

Intuitive Feelings of Warmth and Confidence in Insight and Noninsight Problem Solving of Magic Tricks

PubMed Central

Hedne, Mikael R.; Norman, Elisabeth; Metcalfe, Janet

2016-01-01

The focus of the current study is on intuitive feelings of insight during problem solving and the extent to which such feelings are predictive of successful problem solving. We report the results from an experiment (N = 51) that applied a procedure where the to-be-solved problems were 32 short (15 s) video recordings of magic tricks. The procedure included metacognitive ratings similar to the “warmth ratings” previously used by Metcalfe and colleagues, as well as confidence ratings. At regular intervals during problem solving, participants indicated the perceived closeness to the correct solution. Participants also indicated directly whether each problem was solved by insight or not. Problems that people claimed were solved by insight were characterized by higher accuracy and higher confidence than noninsight solutions. There was no difference between the two types of solution in warmth ratings, however. Confidence ratings were more strongly associated with solution accuracy for noninsight than insight trials. Moreover, for insight trials the participants were more likely to repeat their incorrect solutions on a subsequent recognition test. The results have implications for understanding people's metacognitive awareness of the cognitive processes involved in problem solving. They also have general implications for our understanding of how intuition and insight are related. PMID:27630598

Construct Relevant and Irrelevant Variables in Math Problem Solving Assessment

ERIC Educational Resources Information Center

Birk, Lisa E.

2013-01-01

In this study, I examined the relation between various construct relevant and irrelevant variables and a math problem solving assessment. I used independent performance measures representing the variables of mathematics content knowledge, general ability, and reading fluency. Non-performance variables included gender, socioeconomic status,…

Teaching Thinking and Problem Solving.

ERIC Educational Resources Information Center

Bransford, John; And Others

1986-01-01

This article focuses on two approaches to teaching reasoning and problem solving. One emphasizes the role of domain-specific knowledge; the other emphasizes general strategic and metacognitive knowledge. Many instructional programs are based on the latter approach. The article concludes that these programs can be strengthened by focusing on domain…

Understanding catastrophizing from a misdirected problem-solving perspective.

PubMed

Flink, Ida K; Boersma, Katja; MacDonald, Shane; Linton, Steven J

2012-05-01

The aim is to explore pain catastrophizing from a problem-solving perspective. The links between catastrophizing, problem framing, and problem-solving behaviour are examined through two possible models of mediation as inferred by two contemporary and complementary theoretical models, the misdirected problem solving model (Eccleston & Crombez, 2007) and the fear-anxiety-avoidance model (Asmundson, Norton, & Vlaeyen, 2004). In this prospective study, a general population sample (n= 173) with perceived problems with spinal pain filled out questionnaires twice; catastrophizing and problem framing were assessed on the first occasion and health care seeking (as a proxy for medically oriented problem solving) was assessed 7 months later. Two different approaches were used to explore whether the data supported any of the proposed models of mediation. First, multiple regressions were used according to traditional recommendations for mediation analyses. Second, a bootstrapping method (n= 1000 bootstrap resamples) was used to explore the significance of the indirect effects in both possible models of mediation. The results verified the concepts included in the misdirected problem solving model. However, the direction of the relations was more in line with the fear-anxiety-avoidance model. More specifically, the mediation analyses provided support for viewing catastrophizing as a mediator of the relation between biomedical problem framing and medically oriented problem-solving behaviour. These findings provide support for viewing catastrophizing from a problem-solving perspective and imply a need to examine and address problem framing and catastrophizing in back pain patients. ©2011 The British Psychological Society.

The development and evaluation of a web-based programme to support problem-solving skills following brain injury.

PubMed

Powell, Laurie Ehlhardt; Wild, Michelle R; Glang, Ann; Ibarra, Summer; Gau, Jeff M; Perez, Amanda; Albin, Richard W; O'Neil-Pirozzi, Therese M; Wade, Shari L; Keating, Tom; Saraceno, Carolyn; Slocumb, Jody

2017-10-24

Cognitive impairments following brain injury, including difficulty with problem solving, can pose significant barriers to successful community reintegration. Problem-solving strategy training is well-supported in the cognitive rehabilitation literature. However, limitations in insurance reimbursement have resulted in fewer services to train such skills to mastery and to support generalization of those skills into everyday environments. The purpose of this project was to develop and evaluate an integrated, web-based programme, ProSolv, which uses a small number of coaching sessions to support problem solving in everyday life following brain injury. We used participatory action research to guide the iterative development, usability testing, and within-subject pilot testing of the ProSolv programme. The finalized programme was then evaluated in a between-subjects group study and a non-experimental single case study. Results were mixed across studies. Participants demonstrated that it was feasible to learn and use the ProSolv programme for support in problem solving. They highly recommended the programme to others and singled out the importance of the coach. Limitations in app design were cited as a major reason for infrequent use of the app outside of coaching sessions. Results provide mixed evidence regarding the utility of web-based mobile apps, such as ProSolv to support problem solving following brain injury. Implications for Rehabilitation People with cognitive impairments following brain injury often struggle with problem solving in everyday contexts. Research supports problem solving skills training following brain injury. Assistive technology for cognition (smartphones, selected apps) offers a means of supporting problem solving for this population. This project demonstrated the feasibility of a web-based programme to address this need.

DORA-II Technical Adequacy Brief: Measuring the Process and Outcomes of Team Problem Solving

ERIC Educational Resources Information Center

Algozzine, Bob; Horner, Robert H.; Todd, Anne W.; Newton, J. Stephen; Algozzine, Kate; Cusumano, Dale

2014-01-01

School teams regularly meet to review academic and social problems of individual students, groups of students, or their school in general. While the need for problem solving and recommendations for how to do it are widely documented, there is very limited evidence reflecting the extent to which teams effectively engage in a systematic or effective…

Training generalized improvisation of tools by preschool children1

PubMed Central

Parsonson, Barry S.; Baer, Donald M.

1978-01-01

The development of new, “creative” behaviors was examined in a problem-solving context. One form of problem solving, improvisation, was defined as finding a substitute to replace the specifically designated, but currently unavailable, tool ordinarily used to solve the problem. The study examined whether preschool children spontaneously displayed generalized improvisation skills, and if not, whether they could be trained to do so within different classes of tools. Generalization across different tool classes was monitored but not specifically trained. Five preschool children participated in individual sessions that first probed their skill at improvising tools, and later trained and probed generalized improvisation in one or more of three tool classes (Hammers, Containers, and Shoelaces), using a multiple-baseline design. All five children were trained with Hammers, two were trained in two classes, and two were trained in all three tool classes. Four of the five children improvised little in Baseline. During Training, all five showed increased generalized improvisation within the trained class, but none across classes. Tools fabricated by item combinations were rare in Baseline, but common in Training. Followup probes showed that the training effects were durable. PMID:16795596

Robot, computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.

1972-01-01

The development of a computer problem solving system is reported that considers physical problems faced by an artificial robot moving around in a complex environment. Fundamental interaction constraints with a real environment are simulated for the robot by visual scan and creation of an internal environmental model. The programming system used in constructing the problem solving system for the simulated robot and its simulated world environment is outlined together with the task that the system is capable of performing. A very general framework for understanding the relationship between an observed behavior and an adequate description of that behavior is included.

Mathematical Ability Relies on Knowledge, Too

ERIC Educational Resources Information Center

Sweller, John; Clark, Richard E.; Kirschner, Paul A.

2011-01-01

Recent "reform" curricula both ignore the absence of supporting data and completely misunderstand the role of problem solving in cognition. If, the argument goes, teachers are not really teaching people mathematics but rather are teaching them some form of general problem solving, then mathematical content can be reduced in importance. According…

A non-verbal technique for the assessment of general intellectual ability in selection of aviation personnel.

DOT National Transportation Integrated Search

1971-06-01

A study was conducted in which performance on a non-verbal problem- solving task was correlated with the Otis Quick Scoring Mental Ability Test and the Raven Progressive Matrices Test. The problem-solving task, called 'code- lock' required the subjec...

Enhancing Mathematical Problem Solving for Secondary Students with or at Risk of Learning Disabilities: A Literature Review

ERIC Educational Resources Information Center

Hwang, Jiwon; Riccomini, Paul J.

2016-01-01

Requirements for reasoning, explaining, and generalizing mathematical concepts increase as students advance through the educational system; hence, improving overall mathematical proficiency is critical. Mathematical proficiency requires students to interpret quantities and their corresponding relationships during problem-solving tasks as well as…

Modelling Mathematics Problem Solving Item Responses Using a Multidimensional IRT Model

ERIC Educational Resources Information Center

Wu, Margaret; Adams, Raymond

2006-01-01

This research examined students' responses to mathematics problem-solving tasks and applied a general multidimensional IRT model at the response category level. In doing so, cognitive processes were identified and modelled through item response modelling to extract more information than would be provided using conventional practices in scoring…

Dissociative Conceptual and Quantitative Problem Solving Outcomes across Interactive Engagement and Traditional Format Introductory Physics

ERIC Educational Resources Information Center

McDaniel, Mark A.; Stoen, Siera M.; Frey, Regina F.; Markow, Zachary E.; Hynes, K. Mairin; Zhao, Jiuqing; Cahill, Michael J.

2016-01-01

The existing literature indicates that interactive-engagement (IE) based general physics classes improve conceptual learning relative to more traditional lecture-oriented classrooms. Very little research, however, has examined quantitative problem-solving outcomes from IE based relative to traditional lecture-based physics classes. The present…

Problem-Solving Model for Decision Making with High-Incidence Disabilities: The Minneapolis Experience.

ERIC Educational Resources Information Center

Marston, Doug; Muyskens, Paul; Lau, Matthew; Canter, Andrea

2003-01-01

This article describes the problem-solving model (PSM) used in the Minneapolis Public Schools to guide decisions regarding intervention in general education, special education referral, and evaluation for special education eligibility for high-incidence disabilities. Program evaluation indicates students received special education services earlier…

Mathematical Problem Solving Ability of Eleventh Standard Students

ERIC Educational Resources Information Center

Priya, J. Johnsi

2017-01-01

There is a general assertion among mathematics instructors that learners need to acquire problem solving expertise, figure out how to communicate using mathematics knowledge and aptitude, create numerical reasoning and thinking, to see the interconnectedness amongst mathematics and other subjects. Based on this perspective, the present study aims…

Teaching Personal Finance Mathematical Problem Solving to Individuals with Moderate Intellectual Disability

ERIC Educational Resources Information Center

Root, Jenny; Saunders, Alicia; Spooner, Fred; Brosh, Chelsi

2017-01-01

The ability to solve mathematical problems related to purchasing and personal finance is important in promoting skill generalization and increasing independence for individuals with moderate intellectual disabilities (IDs). Using a multiple probe across participant design, this study investigated the effects of modified schema-based instruction…

Reversible Reasoning and the Working Backwards Problem Solving Strategy

ERIC Educational Resources Information Center

Ramful, Ajay

2015-01-01

Making sense of mathematical concepts and solving mathematical problems may demand different forms of reasoning. These could be either domain-based, such as algebraic, geometric or statistical reasoning, while others are more general such as inductive/deductive reasoning. This article aims at giving visibility to a particular form of reasoning…

Primal-dual techniques for online algorithms and mechanisms

NASA Astrophysics Data System (ADS)

Liaghat, Vahid

An offline algorithm is one that knows the entire input in advance. An online algorithm, however, processes its input in a serial fashion. In contrast to offline algorithms, an online algorithm works in a local fashion and has to make irrevocable decisions without having the entire input. Online algorithms are often not optimal since their irrevocable decisions may turn out to be inefficient after receiving the rest of the input. For a given online problem, the goal is to design algorithms which are competitive against the offline optimal solutions. In a classical offline scenario, it is often common to see a dual analysis of problems that can be formulated as a linear or convex program. Primal-dual and dual-fitting techniques have been successfully applied to many such problems. Unfortunately, the usual tricks come short in an online setting since an online algorithm should make decisions without knowing even the whole program. In this thesis, we study the competitive analysis of fundamental problems in the literature such as different variants of online matching and online Steiner connectivity, via online dual techniques. Although there are many generic tools for solving an optimization problem in the offline paradigm, in comparison, much less is known for tackling online problems. The main focus of this work is to design generic techniques for solving integral linear optimization problems where the solution space is restricted via a set of linear constraints. A general family of these problems are online packing/covering problems. Our work shows that for several seemingly unrelated problems, primal-dual techniques can be successfully applied as a unifying approach for analyzing these problems. We believe this leads to generic algorithmic frameworks for solving online problems. In the first part of the thesis, we show the effectiveness of our techniques in the stochastic settings and their applications in Bayesian mechanism design. In particular, we introduce new techniques for solving a fundamental linear optimization problem, namely, the stochastic generalized assignment problem (GAP). This packing problem generalizes various problems such as online matching, ad allocation, bin packing, etc. We furthermore show applications of such results in the mechanism design by introducing Prophet Secretary, a novel Bayesian model for online auctions. In the second part of the thesis, we focus on the covering problems. We develop the framework of "Disk Painting" for a general class of network design problems that can be characterized by proper functions. This class generalizes the node-weighted and edge-weighted variants of several well-known Steiner connectivity problems. We furthermore design a generic technique for solving the prize-collecting variants of these problems when there exists a dual analysis for the non-prize-collecting counterparts. Hence, we solve the online prize-collecting variants of several network design problems for the first time. Finally we focus on designing techniques for online problems with mixed packing/covering constraints. We initiate the study of degree-bounded graph optimization problems in the online setting by designing an online algorithm with a tight competitive ratio for the degree-bounded Steiner forest problem. We hope these techniques establishes a starting point for the analysis of the important class of online degree-bounded optimization on graphs.

Modifying a Research-Based Problem-Solving Intervention to Improve the Problem-Solving Performance of Fifth and Sixth Graders With and Without Learning Disabilities.

PubMed

Krawec, Jennifer; Huang, Jia

The purpose of the present study was to test the efficacy of a modified cognitive strategy instructional intervention originally developed to improve the mathematical problem solving of middle and high school students with learning disabilities (LD). Fifth and sixth grade general education mathematics teachers and their students of varying ability (i.e., average-achieving [AA] students, low-achieving [LA] students, and students with LD) participated in the research study. Several features of the intervention were modified, including (a) explicitness of instruction, (b) emphasis on meta-cognition, (c) focus on problem-solving prerequisites, (d) extended duration of initial intervention, and (e) addition of visual supports. General education math teachers taught all instructional sessions to their inclusive classrooms. Curriculum-based measures (CBMs) of math problem solving were administered five times over the course of the year. A multilevel model (repeated measures nested within students and students nested within schools) was used to analyze student progress on CBMs. Though CBM scores in the intervention group were initially lower than that of the comparison group, intervention students improved significantly more in the first phase, with no differences in the second phase. Implications for instruction are discussed as well as directions for future research.

Working memory, worry, and algebraic ability.

PubMed

Trezise, Kelly; Reeve, Robert A

2014-05-01

Math anxiety (MA)-working memory (WM) relationships have typically been examined in the context of arithmetic problem solving, and little research has examined the relationship in other math domains (e.g., algebra). Moreover, researchers have tended to examine MA/worry separate from math problem solving activities and have used general WM tasks rather than domain-relevant WM measures. Furthermore, it seems to have been assumed that MA affects all areas of math. It is possible, however, that MA is restricted to particular math domains. To examine these issues, the current research assessed claims about the impact on algebraic problem solving of differences in WM and algebraic worry. A sample of 80 14-year-old female students completed algebraic worry, algebraic WM, algebraic problem solving, nonverbal IQ, and general math ability tasks. Latent profile analysis of worry and WM measures identified four performance profiles (subgroups) that differed in worry level and WM capacity. Consistent with expectations, subgroup membership was associated with algebraic problem solving performance: high WM/low worry>moderate WM/low worry=moderate WM/high worry>low WM/high worry. Findings are discussed in terms of the conceptual relationship between emotion and cognition in mathematics and implications for the MA-WM-performance relationship. Copyright © 2013 Elsevier Inc. All rights reserved.

Solving search problems by strongly simulating quantum circuits

PubMed Central

Johnson, T. H.; Biamonte, J. D.; Clark, S. R.; Jaksch, D.

2013-01-01

Simulating quantum circuits using classical computers lets us analyse the inner workings of quantum algorithms. The most complete type of simulation, strong simulation, is believed to be generally inefficient. Nevertheless, several efficient strong simulation techniques are known for restricted families of quantum circuits and we develop an additional technique in this article. Further, we show that strong simulation algorithms perform another fundamental task: solving search problems. Efficient strong simulation techniques allow solutions to a class of search problems to be counted and found efficiently. This enhances the utility of strong simulation methods, known or yet to be discovered, and extends the class of search problems known to be efficiently simulable. Relating strong simulation to search problems also bounds the computational power of efficiently strongly simulable circuits; if they could solve all problems in P this would imply that all problems in NP and #P could be solved in polynomial time. PMID:23390585

Modeling visual problem solving as analogical reasoning.

PubMed

Lovett, Andrew; Forbus, Kenneth

2017-01-01

We present a computational model of visual problem solving, designed to solve problems from the Raven's Progressive Matrices intelligence test. The model builds on the claim that analogical reasoning lies at the heart of visual problem solving, and intelligence more broadly. Images are compared via structure mapping, aligning the common relational structure in 2 images to identify commonalities and differences. These commonalities or differences can themselves be reified and used as the input for future comparisons. When images fail to align, the model dynamically rerepresents them to facilitate the comparison. In our analysis, we find that the model matches adult human performance on the Standard Progressive Matrices test, and that problems which are difficult for the model are also difficult for people. Furthermore, we show that model operations involving abstraction and rerepresentation are particularly difficult for people, suggesting that these operations may be critical for performing visual problem solving, and reasoning more generally, at the highest level. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Dissociative conceptual and quantitative problem solving outcomes across interactive engagement and traditional format introductory physics

NASA Astrophysics Data System (ADS)

McDaniel, Mark A.; Stoen, Siera M.; Frey, Regina F.; Markow, Zachary E.; Hynes, K. Mairin; Zhao, Jiuqing; Cahill, Michael J.

2016-12-01

The existing literature indicates that interactive-engagement (IE) based general physics classes improve conceptual learning relative to more traditional lecture-oriented classrooms. Very little research, however, has examined quantitative problem-solving outcomes from IE based relative to traditional lecture-based physics classes. The present study included both pre- and post-course conceptual-learning assessments and a new quantitative physics problem-solving assessment that included three representative conservation of energy problems from a first-semester calculus-based college physics course. Scores for problem translation, plan coherence, solution execution, and evaluation of solution plausibility were extracted for each problem. Over 450 students in three IE-based sections and two traditional lecture sections taught at the same university during the same semester participated. As expected, the IE-based course produced more robust gains on a Force Concept Inventory than did the lecture course. By contrast, when the full sample was considered, gains in quantitative problem solving were significantly greater for lecture than IE-based physics; when students were matched on pre-test scores, there was still no advantage for IE-based physics on gains in quantitative problem solving. Further, the association between performance on the concept inventory and quantitative problem solving was minimal. These results highlight that improved conceptual understanding does not necessarily support improved quantitative physics problem solving, and that the instructional method appears to have less bearing on gains in quantitative problem solving than does the kinds of problems emphasized in the courses and homework and the overlap of these problems to those on the assessment.

Psychosocial dimensions of solving an indoor air problem.

PubMed

Lahtinen, Marjaana; Huuhtanen, Pekka; Kähkönen, Erkki; Reijula, Kari

2002-03-01

This investigation focuses on the psychological and social dimensions of managing and solving indoor air problems. The data were collected in nine workplaces by interviews (n = 85) and questionnaires (n = 375). Indoor air problems in office environments have traditionally utilized industrial hygiene or technical expertise. However, indoor air problems at workplaces are often more complex issues to solve. Technical questions are inter-related with the dynamics of the work community, and the cooperation and interaction skills of the parties involved in the solving process are also put to the test. In the present study, the interviewees were very critical of the process of solving the indoor air problem. The responsibility for coordinating the problem-managing process was generally considered vague, as were the roles and functions of the various parties. Communication problems occurred and rumors about the indoor air problem circulated widely. Conflicts were common, complicating the process in several ways. The research focused on examining different ways of managing and resolving an indoor air problem. In addition, reference material on the causal factors of the indoor air problem was also acquired. The study supported the hypothesis that psychosocial factors play a significant role in indoor air problems.

School Effectiveness: Problem-Solving and Managing Conflict.

ERIC Educational Resources Information Center

Minnesota State Dept. of Education, St. Paul.

This module discusses the theory and practice of school improvement and outlines a nine-step systematic problem-solving process for developing an action plan addressing school improvement goals. The first section describes a general model for the study of the school as a social system, as developed by Getzels and Thelen (1960). The second section…

Problem Solving Learning Environments and Assessment: A Knowledge Space Theory Approach

ERIC Educational Resources Information Center

Reimann, Peter; Kickmeier-Rust, Michael; Albert, Dietrich

2013-01-01

This paper explores the relation between problem solving learning environments (PSLEs) and assessment concepts. The general framework of evidence-centered assessment design is used to describe PSLEs in terms of assessment concepts, and to identify similarities between the process of assessment design and of PSLE design. We use a recently developed…

The Geometric Construction Abilities of Gifted Students in Solving Real-World Problems: A Case from Turkey

ERIC Educational Resources Information Center

Yildiz, Avni

2016-01-01

Geometric constructions have already been of interest to mathematicians. However, studies on geometric construction are not adequate in the relevant literature. Moreover, these studies generally focus on how secondary school gifted students solve non-routine mathematical problems. The present study aims to examine the geometric construction…

Life Skills Coach Training Manual.

ERIC Educational Resources Information Center

Saskatchewan NewStart, Inc., Prince Albert.

Ways of helping coaches to counsel unemployed adults in the solving of their personal problems are explored in this manual. Originally printed as two separate volumes, this reprinting of the study has bound the two together. Volume I involves a general discussion of life's problems and of the need to solve them. This volume contains four parts.…

Knowledge Building and Mathematics: Shifting the Responsibility for Knowledge Advancement and Engagement

ERIC Educational Resources Information Center

Moss, Joan; Beatty, Ruth

2010-01-01

Three classrooms of Grade 4 students from different schools and diverse backgrounds collaborated in early algebra research to solve a series of linear and quadratic generalizing problems. Results revealed that high- and low-achieving students were able to solve problems of recognized difficulty. We discuss Knowledge Building principles and…

No Generalization of Practice for Nonzero Simple Addition

ERIC Educational Resources Information Center

Campbell, Jamie I. D.; Beech, Leah C.

2014-01-01

Several types of converging evidence have suggested recently that skilled adults solve very simple addition problems (e.g., 2 + 1, 4 + 2) using a fast, unconscious counting algorithm. These results stand in opposition to the long-held assumption in the cognitive arithmetic literature that such simple addition problems normally are solved by fact…

Large-Scale Studies on the Transferability of General Problem-Solving Skills and the Pedagogic Potential of Physics

ERIC Educational Resources Information Center

Mashood, K. K.; Singh, Vijay A.

2013-01-01

Research suggests that problem-solving skills are transferable across domains. This claim, however, needs further empirical substantiation. We suggest correlation studies as a methodology for making preliminary inferences about transfer. The correlation of the physics performance of students with their performance in chemistry and mathematics in…

Validation of Predictive Relationship of Creative Problem-Solving Attrubutes with Math Creativity

ERIC Educational Resources Information Center

Pham, Linh Hung

2014-01-01

This study was designed to investigate the predictive relationships of creative problem-solving attributes, which comprise divergent thinking, convergent thinking, motivation, general and domain knowledge and skills, and environment, with mathematical creativity of sixth grade students in Thai Nguyen City, Viet Nam. The study also aims to revise…

Teaching Problem-Solving and Creativity in College Courses. AAHE-ERIC/Higher Education Research Currents.

ERIC Educational Resources Information Center

Whitman, Neal

Courses designed to teach problem-solving and creativity, which are relatively new additions to college curricula, are discussed, along with their intellectual foundations and research on these two processes. The teaching of these processes involves the following course goals: teaching a specific subject, generally useful skills, and professional…

An Alternative Time for Telling: When Conceptual Instruction Prior to Problem Solving Improves Mathematical Knowledge

ERIC Educational Resources Information Center

Fyfe, Emily R.; DeCaro, Marci S.; Rittle-Johnson, Bethany

2014-01-01

Background: The sequencing of learning materials greatly influences the knowledge that learners construct. Recently, learning theorists have focused on the sequencing of instruction in relation to solving related problems. The general consensus suggests explicit instruction should be provided; however, when to provide instruction remains unclear.…

Psychometric properties of the Social Problem Solving Inventory-Revised Short-Form in a South African population.

PubMed

Sorsdahl, Katherine; Stein, Dan J; Myers, Bronwyn

2017-04-01

The Social Problem Solving Inventory-Revised Short-Form (SPSI-R:SF) has been used in several countries to identify problem-solving deficits among clinical and general populations in order to guide cognitive-behavioural interventions. Yet, very few studies have evaluated its psychometric properties. Three language versions of the questionnaire were administered to a general population sample comprising 1000 participants (771 English-, 178 Afrikaans- and 101 Xhosa-speakers). Of these participants, 210 were randomly selected to establish test-retest reliability (70 in each language). Principal component analysis was performed to examine the applicability of the factor structure of the original questionnaire to the South African data. Supplementary psychometric analyses were performed, including internal consistency and test-retest reliability. Collectively, results provide initial evidence of the reliability and validity of the SPSI-R:SF for the assessment of problem solving deficits in South Africa. Further studies that explore how the Afrikaans language version of the SPSI-R:SF can be improved and that establish the predictive validity of scores on the SPSI-R:SF are needed. © 2015 International Union of Psychological Science.

Is Word-Problem Solving a Form of Text Comprehension?

PubMed Central

Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.; Hamlett, Carol L.; Wang, Amber Y.

2015-01-01

This study’s hypotheses were that (a) word-problem (WP) solving is a form of text comprehension that involves language comprehension processes, working memory, and reasoning, but (b) WP solving differs from other forms of text comprehension by requiring WP-specific language comprehension as well as general language comprehension. At the start of the 2nd grade, children (n = 206; on average, 7 years, 6 months) were assessed on general language comprehension, working memory, nonlinguistic reasoning, processing speed (a control variable), and foundational skill (arithmetic for WPs; word reading for text comprehension). In spring, they were assessed on WP-specific language comprehension, WPs, and text comprehension. Path analytic mediation analysis indicated that effects of general language comprehension on text comprehension were entirely direct, whereas effects of general language comprehension on WPs were partially mediated by WP-specific language. By contrast, effects of working memory and reasoning operated in parallel ways for both outcomes. PMID:25866461

Learning from external environments using Soar

NASA Technical Reports Server (NTRS)

Laird, John E.

1989-01-01

Soar, like the previous PRODIGY and Theo, is a problem-solving architecture that attempts to learn from experience; unlike them, it takes a more uniform approach, using a single forward-chaining architecture for planning and execution. Its single learning mechanism, designated 'chunking', is domain-independent. Two developmental approaches have been employed with Soar: the first of these allows the architecture to attempt a problem on its own, while the second involves a degree of external guidance. This learning through guidance is integrated with general problem-solving and autonomous learning, leading to an avoidance of human interaction for simple problems that Soar can solve on its own.

The relationship between family functioning and the crime types in incarcerated children.

PubMed

Teker, Kamil; Topçu, Seda; Başkan, Sevgi; Orhon, Filiz Ş; Ulukol, Betül

2017-06-01

We investigated the relationship between the family functioning and crime types in incarcerated children. One hundred eighty two incarcerated children aged between 13-18 years who were confined in child-youth prisons and child correctional facilities were enrolled into this descriptive study. Participants completed demographic questions and the McMaster Family Assessment Device (Epstein, Baldwin, & Bishop, 1983) (FAD) with face to face interviews. The crime types were theft, assault (bodily injury), robbery, sexual assault, drug trafficker and murder. The socio-demographic characteristics were compared by using FAD scale, and growing up in a nuclear family had statistically significant better scores for problem solving and communication subscales and the children whose parents had their own house had significantly better problem solving scores When we compared the crime types of children by using problem solving, communication and general functioning subscales of FAD, we found statistical lower scores in assault (bodily injury) group than in theft, sexual assault, murder groups and in drug trafficker group than in murder group, also we found lower scores in drug trafficker group than in theft group for problem solving and general functioning sub-scales, also there were lower scores in bodily injury assault group than in robbery, theft groups and in drug trafficker than in theft group for problem solving subscale. The communication and problem solving sub-scales of FAD are firstly impaired scales for the incarcerated children. We mention these sub-scales are found with unplanned and less serious crimes and commented those as cry for help of the children.

An electromagnetism-like metaheuristic for open-shop problems with no buffer

NASA Astrophysics Data System (ADS)

Naderi, Bahman; Najafi, Esmaeil; Yazdani, Mehdi

2012-12-01

This paper considers open-shop scheduling with no intermediate buffer to minimize total tardiness. This problem occurs in many production settings, in the plastic molding, chemical, and food processing industries. The paper mathematically formulates the problem by a mixed integer linear program. The problem can be optimally solved by the model. The paper also develops a novel metaheuristic based on an electromagnetism algorithm to solve the large-sized problems. The paper conducts two computational experiments. The first includes small-sized instances by which the mathematical model and general performance of the proposed metaheuristic are evaluated. The second evaluates the metaheuristic for its performance to solve some large-sized instances. The results show that the model and algorithm are effective to deal with the problem.

Production system chunking in SOAR: Case studies in automated learning

NASA Technical Reports Server (NTRS)

Allen, Robert

1989-01-01

A preliminary study of SOAR, a general intelligent architecture for automated problem solving and learning, is presented. The underlying principles of universal subgoaling and chunking were applied to a simple, yet representative, problem in artificial intelligence. A number of problem space representations were examined and compared. It is concluded that learning is an inherent and beneficial aspect of problem solving. Additional studies are suggested in domains relevant to mission planning and to SOAR itself.

Solving multi-objective optimization problems in conservation with the reference point method

PubMed Central

Dujardin, Yann; Chadès, Iadine

2018-01-01

Managing the biodiversity extinction crisis requires wise decision-making processes able to account for the limited resources available. In most decision problems in conservation biology, several conflicting objectives have to be taken into account. Most methods used in conservation either provide suboptimal solutions or use strong assumptions about the decision-maker’s preferences. Our paper reviews some of the existing approaches to solve multi-objective decision problems and presents new multi-objective linear programming formulations of two multi-objective optimization problems in conservation, allowing the use of a reference point approach. Reference point approaches solve multi-objective optimization problems by interactively representing the preferences of the decision-maker with a point in the criteria (objectives) space, called the reference point. We modelled and solved the following two problems in conservation: a dynamic multi-species management problem under uncertainty and a spatial allocation resource management problem. Results show that the reference point method outperforms classic methods while illustrating the use of an interactive methodology for solving combinatorial problems with multiple objectives. The method is general and can be adapted to a wide range of ecological combinatorial problems. PMID:29293650

Numerical solution to generalized Burgers'-Fisher equation using Exp-function method hybridized with heuristic computation.

PubMed

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems.

Numerical Solution to Generalized Burgers'-Fisher Equation Using Exp-Function Method Hybridized with Heuristic Computation

PubMed Central

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems. PMID:25811858

Associations between conceptual reasoning, problem solving, and adaptive ability in high-functioning autism.

PubMed

Williams, Diane L; Mazefsky, Carla A; Walker, Jon D; Minshew, Nancy J; Goldstein, Gerald

2014-11-01

Abstract thinking is generally highly correlated with problem-solving ability which is predictive of better adaptive functioning. Measures of conceptual reasoning, an ecologically-valid laboratory measure of problem-solving, and a report measure of adaptive functioning in the natural environment, were administered to children and adults with and without autism. The individuals with autism had weaker conceptual reasoning ability than individuals with typical development of similar age and cognitive ability. For the autism group, their flexible thinking scores were significantly correlated with laboratory measures of strategy formation and rule shifting and with reported overall adaptive behavior but not socialization scores. Therefore, in autism, flexibility of thought is potentially more important for adaptive functioning in the natural environment than conceptual reasoning or problem-solving.

[Out of hopelessness--problem solving training in suicide prevention].

PubMed

Perczel Forintos, Dóra; Póos, Judit

2008-01-01

Psychological studies have great importance in suicide prevention since psychological factors belong to the modifiable risk factors in suicide. These are the negative cognitive triad and hopelessness which are related to vague, over-generalized autobiographical memory and lead to poor problem solving abilities. In this paper we review the most relevant clinical psychology studies and models such as the cognitive model of suicide as well as the entrapment theory by Williams (2004). In the second part we describe the frequently used method of problem solving training/therapy which can be used in either individual or group format. We hope that the problem solving skill training will soon become a part of suicide prevention in Hungary also, since short,focused and evidence based interventions are much needed in psychiatric care.

Sociotropic or autonomous personality and problem solving in peritoneal dialysis patients.

PubMed

Demir, S; Tufan, G; Erem, O

2010-01-01

This study investigated the sociotropic and autonomous personality characteristics and perceived problem solving ability of continuous ambulatory peritoneal dialysis (CAPD) patients, and their relationship with quality of life. The study included 14 CAPD patients and 54 healthy volunteers. Sociotropy and autonomy scores were significantly higher in CAPD patients than in the healthy control group. Among CAPD patients, there was a significant correlation between problem solving and serum phosphate, parathormone levels and erythrocyte sedimentation rate. There was a negative correlation between total dialysis time and sociotropy in CAPD patients, and a positive correlation between general health/pain perception and autonomy. Appropriate medical management, time on dialysis and positive self-perception of health were correlated with better problem solving ability and higher autonomous but lower sociotropic personality styles.

A Computer Algebra Approach to Solving Chemical Equilibria in General Chemistry

ERIC Educational Resources Information Center

Kalainoff, Melinda; Lachance, Russ; Riegner, Dawn; Biaglow, Andrew

2012-01-01

In this article, we report on a semester-long study of the incorporation into our general chemistry course, of advanced algebraic and computer algebra techniques for solving chemical equilibrium problems. The method presented here is an alternative to the commonly used concentration table method for describing chemical equilibria in general…

General relativistic hydrodynamics with Adaptive-Mesh Refinement (AMR) and modeling of accretion disks

NASA Astrophysics Data System (ADS)

Donmez, Orhan

We present a general procedure to solve the General Relativistic Hydrodynamical (GRH) equations with Adaptive-Mesh Refinement (AMR) and model of an accretion disk around a black hole. To do this, the GRH equations are written in a conservative form to exploit their hyperbolic character. The numerical solutions of the general relativistic hydrodynamic equations is done by High Resolution Shock Capturing schemes (HRSC), specifically designed to solve non-linear hyperbolic systems of conservation laws. These schemes depend on the characteristic information of the system. We use Marquina fluxes with MUSCL left and right states to solve GRH equations. First, we carry out different test problems with uniform and AMR grids on the special relativistic hydrodynamics equations to verify the second order convergence of the code in 1D, 2 D and 3D. Second, we solve the GRH equations and use the general relativistic test problems to compare the numerical solutions with analytic ones. In order to this, we couple the flux part of general relativistic hydrodynamic equation with a source part using Strang splitting. The coupling of the GRH equations is carried out in a treatment which gives second order accurate solutions in space and time. The test problems examined include shock tubes, geodesic flows, and circular motion of particle around the black hole. Finally, we apply this code to the accretion disk problems around the black hole using the Schwarzschild metric at the background of the computational domain. We find spiral shocks on the accretion disk. They are observationally expected results. We also examine the star-disk interaction near a massive black hole. We find that when stars are grounded down or a hole is punched on the accretion disk, they create shock waves which destroy the accretion disk.

Cognitive Task Analysis: Implications for the Theory and Practice of Instructional Design.

ERIC Educational Resources Information Center

Dehoney, Joanne

Cognitive task analysis grew out of efforts by cognitive psychologists to understand problem-solving in a lab setting. It has proved a useful tool for describing expert performance in complex problem solving domains. This review considers two general models of cognitive task analysis and examines the procedures and results of analyses in three…

General Problem-Solving Styles and Problem-Solving Approaches in Video Games

ERIC Educational Resources Information Center

Hamlen, Karla R.

2018-01-01

Video game play is a pervasive recreational activity, particularly among college students. While there is a large research base focused on educational video game play and uses of games in the classroom, there is much less research focused on cognitive strategies and entertainment video game play. The purpose of this study was to investigate…

An Evaluation of Grades 9 and 10 Mathematics Textbooks vis-a-vis Fostering Problem Solving Skills

ERIC Educational Resources Information Center

Buishaw, Alemayehu; Ayalew, Assaye

2013-01-01

This study sought to evaluate the adequacy of integration of problematic situations and general problem-solving strategies (heuristics) in grades 9 and 10 mathematics textbooks. Grade 9 and grade 10 mathematics textbooks were used for analysis. Document analysis and interview were used as data gathering instruments. Document analysis was carried…

Peer Instruction in Chemistry Education: Assessment of Students' Learning Strategies, Conceptual Learning and Problem Solving

ERIC Educational Resources Information Center

Gok, Tolga; Gok, Ozge

2016-01-01

The aim of this research was to investigate the effects of peer instruction on learning strategies, problem solving performance, and conceptual understanding of college students in a general chemistry course. The research was performed students enrolled in experimental and control groups of a chemistry course were selected. Students in the…

Using a Problem-Solving Strategy to Prevent Work-Related Accidents Due to Unsafe Worker Behavior.

ERIC Educational Resources Information Center

Martella, Ronald C.; And Others

1992-01-01

A two-stage problem-solving strategy involving cue cards and their gradual withdrawal was used to teach nine sheltered workshop employees how to prevent work-related accidents. Results indicated that participants used the strategy appropriately and generalized their skills to similar and dissimilar situations up to eight weeks after training.…

Mobile App Development to Increase Student Engagement and Problem Solving Skills

ERIC Educational Resources Information Center

Dekhane, Sonal; Xu, Xin; Tsoi, Mai Yin

2013-01-01

This paper describes a project designed to promote problem solving and critical thinking skills in a general education, computing course at an open access institution. A visual programming tool, GameSalad, was used to enable students to create educational apps for mobile platforms. The students worked on a game development project for the entire…

The Study on Network Examinational Database based on ASP Technology

NASA Astrophysics Data System (ADS)

Zhang, Yanfu; Han, Yuexiao; Zhou, Yanshuang

This article introduces the structure of the general test base system based on .NET technology, discussing the design of the function modules and its implementation methods. It focuses on key technology of the system, proposing utilizing the WEB online editor control to solve the input problem and regular expression to solve the problem HTML code, making use of genetic algorithm to optimize test paper and the automated tools of WORD to solve the problem of exporting papers and others. Practical effective design and implementation technology can be used as reference for the development of similar systems.

The use of Lanczos's method to solve the large generalized symmetric definite eigenvalue problem

NASA Technical Reports Server (NTRS)

Jones, Mark T.; Patrick, Merrell L.

1989-01-01

The generalized eigenvalue problem, Kx = Lambda Mx, is of significant practical importance, especially in structural enginering where it arises as the vibration and buckling problem. A new algorithm, LANZ, based on Lanczos's method is developed. LANZ uses a technique called dynamic shifting to improve the efficiency and reliability of the Lanczos algorithm. A new algorithm for solving the tridiagonal matrices that arise when using Lanczos's method is described. A modification of Parlett and Scott's selective orthogonalization algorithm is proposed. Results from an implementation of LANZ on a Convex C-220 show it to be superior to a subspace iteration code.

Analysis of random point images with the use of symbolic computation codes and generalized Catalan numbers

NASA Astrophysics Data System (ADS)

Reznik, A. L.; Tuzikov, A. V.; Solov'ev, A. A.; Torgov, A. V.

2016-11-01

Original codes and combinatorial-geometrical computational schemes are presented, which are developed and applied for finding exact analytical formulas that describe the probability of errorless readout of random point images recorded by a scanning aperture with a limited number of threshold levels. Combinatorial problems encountered in the course of the study and associated with the new generalization of Catalan numbers are formulated and solved. An attempt is made to find the explicit analytical form of these numbers, which is, on the one hand, a necessary stage of solving the basic research problem and, on the other hand, an independent self-consistent problem.

Fast Combinatorial Algorithm for the Solution of Linearly Constrained Least Squares Problems

DOEpatents

Van Benthem, Mark H.; Keenan, Michael R.

2008-11-11

A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.

Therapeutic effects of problem-solving training and play-reading groups.

PubMed

Coché, E; Douglas, A A

1977-07-01

Twenty-five adult patients of a private psychiatric hospital participated in small groups that convened for eight sessions in order to increase skills in interpersonal problem solving. The groups repeatedly went through the steps of (a) bringing up a problem; (b) clarifying it; (c) proposing solutions; and(d) weighing the solutions. A control grop of 29 patients did not receive problem-solving training. A "placebo" sample of 21 Ss also met in small groups, but their task was to read comedies together. The results obtained through a series of analyses of covariance showed that the experimental condition was more successful than the other two in improving people's impulse control, self-esteem and feeling of competence. The play-reading condition was found to be as helpful as the problem-solving groups in reducing depression and general psychopathology. Control patients showed significantly less improvement than did patients in the other conditions.

Effects of Preventative Tutoring on the Mathematical Problem Solving of Third-Grade Students With Math and Reading Difficulties.

PubMed

Fuchs, Lynn S; Seethaler, Pamela M; Powell, Sarah R; Fuchs, Douglas; Hamlett, Carol L; Fletcher, Jack M

2008-01-01

This study assessed the effects of preventative tutoring on the math problem solving of third-grade students with math and reading difficulties. Students (n = 35) were assigned randomly to continue in their general education math program or to receive secondary preventative tutoring 3 times per week, 30 min per session, for 12 weeks. Schema-broadening tutoring taught students to (a) focus on the mathematical structure of 3 problem types; (b) recognize problems as belonging to those 3 problem-type schemas; (c) solve the 3 word-problem types; and (d) transfer solution methods to problems that include irrelevant information, 2-digit operands, missing information in the first or second positions in the algebraic equation, or relevant information in charts, graphs, and pictures. Also, students were taught to perform the calculation and algebraic skills foundational for problem solving. Analyses of variance revealed statistically significant effects on a wide range of word problems, with large effect sizes. Findings support the efficacy of the tutoring protocol for preventing word-problem deficits among third-grade students with math and reading deficits.

Effects of Preventative Tutoring on the Mathematical Problem Solving of Third-Grade Students With Math and Reading Difficulties

PubMed Central

Fuchs, Lynn S.; Seethaler, Pamela M.; Powell, Sarah R.; Fuchs, Douglas; Hamlett, Carol L.; Fletcher, Jack M.

2009-01-01

This study assessed the effects of preventative tutoring on the math problem solving of third-grade students with math and reading difficulties. Students (n = 35) were assigned randomly to continue in their general education math program or to receive secondary preventative tutoring 3 times per week, 30 min per session, for 12 weeks. Schema-broadening tutoring taught students to (a) focus on the mathematical structure of 3 problem types; (b) recognize problems as belonging to those 3 problem-type schemas; (c) solve the 3 word-problem types; and (d) transfer solution methods to problems that include irrelevant information, 2-digit operands, missing information in the first or second positions in the algebraic equation, or relevant information in charts, graphs, and pictures. Also, students were taught to perform the calculation and algebraic skills foundational for problem solving. Analyses of variance revealed statistically significant effects on a wide range of word problems, with large effect sizes. Findings support the efficacy of the tutoring protocol for preventing word-problem deficits among third-grade students with math and reading deficits. PMID:20209074

Deaf and hard of hearing students' problem-solving strategies with signed arithmetic story problems.

PubMed

Pagliaro, Claudia M; Ansell, Ellen

2012-01-01

The use of problem-solving strategies by 59 deaf and hard of hearing children, grades K-3, was investigated. The children were asked to solve 9 arithmetic story problems presented to them in American Sign Language. The researchers found that while the children used the same general types of strategies that are used by hearing children (i.e., modeling, counting, and fact-based strategies), they showed an overwhelming use of counting strategies for all types of problems and at all ages. This difference may have its roots in language or instruction (or in both), and calls attention to the need for conceptual rather than procedural mathematics instruction for deaf and hard of hearing students.

Heuristic algorithms for solving of the tool routing problem for CNC cutting machines

NASA Astrophysics Data System (ADS)

Chentsov, P. A.; Petunin, A. A.; Sesekin, A. N.; Shipacheva, E. N.; Sholohov, A. E.

2015-11-01

The article is devoted to the problem of minimizing the path of the cutting tool to shape cutting machines began. This problem can be interpreted as a generalized traveling salesman problem. Earlier version of the dynamic programming method to solve this problem was developed. Unfortunately, this method allows to process an amount not exceeding thirty circuits. In this regard, the task of constructing quasi-optimal route becomes relevant. In this paper we propose options for quasi-optimal greedy algorithms. Comparison of the results of exact and approximate algorithms is given.

A quasi-Newton approach to optimization problems with probability density constraints. [problem solving in mathematical programming

NASA Technical Reports Server (NTRS)

Tapia, R. A.; Vanrooy, D. L.

1976-01-01

A quasi-Newton method is presented for minimizing a nonlinear function while constraining the variables to be nonnegative and sum to one. The nonnegativity constraints were eliminated by working with the squares of the variables and the resulting problem was solved using Tapia's general theory of quasi-Newton methods for constrained optimization. A user's guide for a computer program implementing this algorithm is provided.

An Initial Model of Requirements Traceability an Empirical Study

DTIC Science & Technology

1992-09-22

procedures have been used extensively in the study of human problem-solving, including such areas as general problem-solving behavior, physics problem...heen doing unless you have traceability." " Humans don’t go back to the requirements enough." "Traceabi!ity should be extremely helpful with...by constraints on its usage: ("Traceability needs to be something that humans can work with, not just a whip held over people." "Traceability should

Assessment regarding the use of the computer aided analytical models in the calculus of the general strength of a ship hull

NASA Astrophysics Data System (ADS)

Hreniuc, V.; Hreniuc, A.; Pescaru, A.

2017-08-01

Solving a general strength problem of a ship hull may be done using analytical approaches which are useful to deduce the buoyancy forces distribution, the weighting forces distribution along the hull and the geometrical characteristics of the sections. These data are used to draw the free body diagrams and to compute the stresses. The general strength problems require a large amount of calculi, therefore it is interesting how a computer may be used to solve such problems. Using computer programming an engineer may conceive software instruments based on analytical approaches. However, before developing the computer code the research topic must be thoroughly analysed, in this way being reached a meta-level of understanding of the problem. The following stage is to conceive an appropriate development strategy of the original software instruments useful for the rapid development of computer aided analytical models. The geometrical characteristics of the sections may be computed using a bool algebra that operates with ‘simple’ geometrical shapes. By ‘simple’ we mean that for the according shapes we have direct calculus relations. In the set of ‘simple’ shapes we also have geometrical entities bounded by curves approximated as spline functions or as polygons. To conclude, computer programming offers the necessary support to solve general strength ship hull problems using analytical methods.

Mathematical improvement of the Hopfield model for feasible solutions to the traveling salesman problem by a synapse dynamical system.

PubMed

Takahashi, Y

1998-01-01

It is well known that the Hopfield Model (HM) for neural networks to solve the Traveling Salesman Problem (TSP) suffers from three major drawbacks. (1) It can converge on nonoptimal locally minimum solutions. (2) It can converge on infeasible solutions. (3) Results are very sensitive to the careful tuning of its parameters. A number of methods have been proposed to overcome (a) well. In contrast, work on (b) and (c) has not been sufficient; techniques have not been generalized to more general optimization problems. Thus this paper mathematically resolves (b) and (c) to such an extent that the resolution can be applied to solving with some general network continuous optimization problems including the Hopfield version of the TSP. It first constructs an Extended HM (E-HM) that overcomes both (b) and (c). Fundamental techniques of the E-HM lie in the addition of a synapse dynamical system cooperated with the current HM unit dynamical system. It is this synapse dynamical system that makes the TSP constraint hold at any final states for whatever choices of the IIM parameters and an initial state. The paper then generalizes the E-HM further to a network that can solve a class of continuous optimization problems with a constraint equation where both of the objective function and the constraint function are nonnegative and continuously differentiable.

Problem Solving Model for Science Learning

NASA Astrophysics Data System (ADS)

Alberida, H.; Lufri; Festiyed; Barlian, E.

2018-04-01

This research aims to develop problem solving model for science learning in junior high school. The learning model was developed using the ADDIE model. An analysis phase includes curriculum analysis, analysis of students of SMP Kota Padang, analysis of SMP science teachers, learning analysis, as well as the literature review. The design phase includes product planning a science-learning problem-solving model, which consists of syntax, reaction principle, social system, support system, instructional impact and support. Implementation of problem-solving model in science learning to improve students' science process skills. The development stage consists of three steps: a) designing a prototype, b) performing a formative evaluation and c) a prototype revision. Implementation stage is done through a limited trial. A limited trial was conducted on 24 and 26 August 2015 in Class VII 2 SMPN 12 Padang. The evaluation phase was conducted in the form of experiments at SMPN 1 Padang, SMPN 12 Padang and SMP National Padang. Based on the development research done, the syntax model problem solving for science learning at junior high school consists of the introduction, observation, initial problems, data collection, data organization, data analysis/generalization, and communicating.

When Does Changing Representation Improve Problem-Solving Performance?

NASA Technical Reports Server (NTRS)

Holte, Robert; Zimmer, Robert; MacDonald, Alan

1992-01-01

The aim of changing representation is the improvement of problem-solving efficiency. For the most widely studied family of methods of change of representation it is shown that the value of a single parameter, called the expulsion factor, is critical in determining (1) whether the change of representation will improve or degrade problem-solving efficiency and (2) whether the solutions produced using the change of representation will or will not be exponentially longer than the shortest solution. A method of computing the expansion factor for a given change of representation is sketched in general and described in detail for homomorphic changes of representation. The results are illustrated with homomorphic decompositions of the Towers of Hanoi problem.

Talk aloud problem solving: Exploration of acquisition and frequency building in science text

NASA Astrophysics Data System (ADS)

Dembek, Ginny

Discovering new ways to help students attain higher levels of scientific knowledge and to think critically is a national goal (Educate to Innovate campaign). Despite the best intentions, many students struggle to achieve a basic level of science knowledge (NAEP, 2011). The present study examined Talk Aloud Pair Problem Solving and frequency building with five students who were diagnosed with a disability and receive specialized reading instruction in a special education setting. Acquisition was obtained through scripted lessons and frequency building or practice strengthened the student's verbal repertoire making the problem solving process a durable behavior. Overall, students all demonstrated improvements in problem solving performance when compared to baseline. Students became more significantly accurate in performance and maintenance in learning was demonstrated. Generalization probes indicated improvement in student performance. Implications for practice and future research are discussed.

Life stress, social support, and problem-solving skills predictive of depressive symptoms, hopelessness, and suicide ideation in an Asian student population: a test of a model.

PubMed

Yang, B; Clum, G A

1994-01-01

The present study tested both a stress-problem-solving model and a stress-social support model in the etiology of depressive symptoms, hopelessness, and suicide ideation for a group of Asian international students in the United States. Problem-solving skills and social support were hypothesized as two mediators between life stress and depressive symptoms, hopelessness, and suicide ideation. The results from a series of stepwise regression analyses and a path analysis support the hypotheses, indicating that these models generalized to a sample of Asian international students. The roles of social support and problem-solving skills in depressive symptoms and hopelessness are discussed. The results also suggest that hopelessness may serve as a cognitive factor directly affecting depressive symptoms and indirectly affecting suicide ideation.

Firing the Executive: When an Analytic Approach to Problem Solving Helps and Hurts

ERIC Educational Resources Information Center

Aiello, Daniel A.; Jarosz, Andrew F.; Cushen, Patrick J.; Wiley, Jennifer

2012-01-01

There is a general assumption that a more controlled or more focused attentional state is beneficial for most cognitive tasks. However, there has been a growing realization that creative problem solving tasks, such as the Remote Associates Task (RAT), may benefit from a less controlled solution approach. To test this hypothesis, in a 2x2 design,…

Comparison of Types of Generalizations and Problem-Solving Schemas Used to Solve a Mathematical Problem

ERIC Educational Resources Information Center

Hodnik Cadež, Tatjana; Manfreda Kolar, Vida

2015-01-01

A cognitive schema is a mechanism which allows an individual to organize her/his experiences in such a way that a new similar experience can easily be recognised and dealt with successfully. Well-structured schemas provide for the knowledge base for subsequent mathematical activities. A new experience can be assimilated into a previously existing…

Analysis of 4th Grade Students' Problem Solving Skills in Terms of Several Variables

ERIC Educational Resources Information Center

Sungur, Gülcan; Bal, Pervin Nedim

2016-01-01

The aim of this study is to examine if the level of primary school students in solving problems differs according to some demographic variables. The research is descriptive type in the general survey method, it was carried out with quantitative research techniques. The sample of the study consisted of 587 primary school students in Grade 4. The…

Development of a Test for an Experimental Research Program in Creative Problem Solving. Final Report.

ERIC Educational Resources Information Center

Miles, David T.

The purpose of this first phase of a continuing research program was the development of a test of creative problem solving in general design. A design class of 186 members was divided into an experimental and control group; a non-design control group (an educational psychology class) of 45 was also tested. Multivariate interpretation of creative…

Linking Complex Problem Solving and General Mental Ability to Career Advancement: Does a Transversal Skill Reveal Incremental Predictive Validity?

ERIC Educational Resources Information Center

Mainert, Jakob; Kretzschmar, André; Neubert, Jonas C.; Greiff, Samuel

2015-01-01

Transversal skills, such as complex problem solving (CPS) are viewed as central twenty-first-century skills. Recent empirical findings have already supported the importance of CPS for early academic advancement. We wanted to determine whether CPS could also contribute to the understanding of career advancement later in life. Towards this end, we…

The Computer-Based Assessment of Complex Problem Solving and How It Is Influenced by Students' Information and Communication Technology Literacy

ERIC Educational Resources Information Center

Greiff, Samuel; Kretzschmar, André; Müller, Jonas C.; Spinath, Birgit; Martin, Romain

2014-01-01

The 21st-century work environment places strong emphasis on nonroutine transversal skills. In an educational context, complex problem solving (CPS) is generally considered an important transversal skill that includes knowledge acquisition and its application in new and interactive situations. The dynamic and interactive nature of CPS requires a…

The Role of Cognitive Processes, Foundational Math Skill, and Calculation Accuracy and Fluency in Word-Problem Solving versus Prealgebraic Knowledge

ERIC Educational Resources Information Center

Fuchs, Lynn S.; Gilbert, Jennifer K.; Powell, Sarah R.; Cirino, Paul T.; Fuchs, Douglas; Hamlett, Carol L.; Seethaler, Pamela M.; Tolar, Tammy D.

2016-01-01

The purpose of this study was to examine child-level pathways in development of prealgebraic knowledge versus word-problem solving, while evaluating the contribution of calculation accuracy and fluency as mediators of foundational skills/processes. Children (n = 962; mean 7.60 years) were assessed on general cognitive processes and early…

Professional or administrative value patterns? Clinical pathways in medical problem-solving processes.

PubMed

Holmberg, Leif

2007-11-01

A health-care organization simultaneously belongs to two different institutional value patterns: a professional and an administrative value pattern. At the administrative level, medical problem-solving processes are generally perceived as the efficient application of familiar chains of activities to well-defined problems; and a low task uncertainty is therefore assumed at the work-floor level. This assumption is further reinforced through clinical pathways and other administrative guidelines. However, studies have shown that in clinical practice such administrative guidelines are often considered inadequate and difficult to implement mainly because physicians generally perceive task uncertainty to be high and that the guidelines do not cover the scope of encountered deviations. The current administrative level guidelines impose uniform structural features that meet the requirement for low task uncertainty. Within these structural constraints, physicians must organize medical problem-solving processes to meet any task uncertainty that may be encountered. Medical problem-solving processes with low task uncertainty need to be organized independently of processes with high task uncertainty. Each process must be evaluated according to different performance standards and needs to have autonomous administrative guideline models. Although clinical pathways seem appropriate when there is low task uncertainty, other kinds of guidelines are required when the task uncertainty is high.

A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm

PubMed Central

El-Qulity, Said Ali; Mohamed, Ali Wagdy

2016-01-01

This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness. PMID:26819583

A Generalized National Planning Approach for Admission Capacity in Higher Education: A Nonlinear Integer Goal Programming Model with a Novel Differential Evolution Algorithm.

PubMed

El-Qulity, Said Ali; Mohamed, Ali Wagdy

2016-01-01

This paper proposes a nonlinear integer goal programming model (NIGPM) for solving the general problem of admission capacity planning in a country as a whole. The work aims to satisfy most of the required key objectives of a country related to the enrollment problem for higher education. The system general outlines are developed along with the solution methodology for application to the time horizon in a given plan. The up-to-date data for Saudi Arabia is used as a case study and a novel evolutionary algorithm based on modified differential evolution (DE) algorithm is used to solve the complexity of the NIGPM generated for different goal priorities. The experimental results presented in this paper show their effectiveness in solving the admission capacity for higher education in terms of final solution quality and robustness.

A continuous glucose monitoring and problem-solving intervention to change physical activity behavior in women with type 2 diabetes: a pilot study.

PubMed

Allen, Nancy; Whittemore, Robin; Melkus, Gail

2011-11-01

Diabetes technology has the potential to provide useful data for theory-based behavioral counseling. The aims of this study are to evaluate the feasibility, acceptability, and preliminary efficacy of a continuous glucose monitoring and problem-solving counseling intervention to change physical activity (PA) behavior in women with type 2 diabetes. Women (n=29) with type 2 diabetes were randomly assigned to one of two treatment conditions: continuous glucose counseling and problem-solving skills or continuous glucose monitoring counseling and general diabetes education. Feasibility data were obtained on intervention dose, implementation, and satisfaction. Preliminary efficacy data were collected at baseline and 12 weeks on the following measures: PA amount and intensity, diet, problem-solving skills, self-efficacy for PA, depression, hemogoloin A1c, weight, and blood pressure. Demographic and implementation variables were described using frequency distributions and summary statistics. Satisfaction data were analyzed using Wilcoxon rank. Differences between groups were analyzed using linear mixed-modeling. Women were mostly white/non-Latina with a mean age of 53 years, a 6.5-year history of diabetes, and suboptimal glycemic control. Continuous glucose monitoring plus problem-solving group participants had significantly greater problem-solving skills and had greater, although not statistically significant, dietary adherence, moderate activity minutes, weight loss, and higher intervention satisfaction pre- to post-intervention than did participants in the continuous glucose monitoring plus education group. A continuous glucose monitoring plus problem-solving intervention was feasible and acceptable, and participants had greater problem-solving skills than continuous glucose monitoring plus education group participants.

Problem solving with genetic algorithms and Splicer

NASA Technical Reports Server (NTRS)

Bayer, Steven E.; Wang, Lui

1991-01-01

Genetic algorithms are highly parallel, adaptive search procedures (i.e., problem-solving methods) loosely based on the processes of population genetics and Darwinian survival of the fittest. Genetic algorithms have proven useful in domains where other optimization techniques perform poorly. The main purpose of the paper is to discuss a NASA-sponsored software development project to develop a general-purpose tool for using genetic algorithms. The tool, called Splicer, can be used to solve a wide variety of optimization problems and is currently available from NASA and COSMIC. This discussion is preceded by an introduction to basic genetic algorithm concepts and a discussion of genetic algorithm applications.

Visuo–spatial working memory is an important source of domain-general vulnerability in the development of arithmetic cognition

PubMed Central

Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Metcalfe, Arron W.S.; Swigart, Anna G.; Menon, Vinod

2014-01-01

The study of developmental disorders can provide a unique window into the role of domain-general cognitive abilities and neural systems in typical and atypical development. Mathematical disabilities (MD) are characterized by marked difficulty in mathematical cognition in the presence of preserved intelligence and verbal ability. Although studies of MD have most often focused on the role of core deficits in numerical processing, domain-general cognitive abilities, in particular working memory (WM), have also been implicated. Here we identify specific WM components that are impaired in children with MD and then examine their role in arithmetic problem solving. Compared to typically developing (TD) children, the MD group demonstrated lower arithmetic performance and lower visuo-spatial working memory (VSWM) scores with preserved abilities on the phonological and central executive components of WM. Whole brain analysis revealed that, during arithmetic problem solving, left posterior parietal cortex, bilateral dorsolateral and ventrolateral prefrontal cortex, cingulate gyrus and precuneus, and fusiform gyrus responses were positively correlated with VSWM ability in TD children, but not in the MD group. Additional analyses using a priori posterior parietal cortex regions previously implicated in WM tasks, demonstrated a convergent pattern of results during arithmetic problem solving. These results suggest that MD is characterized by a common locus of arithmetic and VSWM deficits at both the cognitive and functional neuroanatomical levels. Unlike TD children, children with MD do not use VSWM resources appropriately during arithmetic problem solving. This work advances our understanding of VSWM as an important domain-general cognitive process in both typical and atypical mathematical skill development. PMID:23896444

Local Conjecturing Process in the Solving of Pattern Generalization Problem

ERIC Educational Resources Information Center

Sutarto; Nusantara, Toto; Subanji; Sisworo

2016-01-01

This aim of this study is to describe the process of local conjecturing in generalizing patterns based on Action, Process, Object, Schema (APOS) theory. The subjects were 16 grade 8 students from a junior high school. Data collection used Pattern Generalization Problem (PGP) and interviews. In the first stage, students completed PGP; in the second…

Total variation regularization of the 3-D gravity inverse problem using a randomized generalized singular value decomposition

NASA Astrophysics Data System (ADS)

Vatankhah, Saeed; Renaut, Rosemary A.; Ardestani, Vahid E.

2018-04-01

We present a fast algorithm for the total variation regularization of the 3-D gravity inverse problem. Through imposition of the total variation regularization, subsurface structures presenting with sharp discontinuities are preserved better than when using a conventional minimum-structure inversion. The associated problem formulation for the regularization is nonlinear but can be solved using an iteratively reweighted least-squares algorithm. For small-scale problems the regularized least-squares problem at each iteration can be solved using the generalized singular value decomposition. This is not feasible for large-scale, or even moderate-scale, problems. Instead we introduce the use of a randomized generalized singular value decomposition in order to reduce the dimensions of the problem and provide an effective and efficient solution technique. For further efficiency an alternating direction algorithm is used to implement the total variation weighting operator within the iteratively reweighted least-squares algorithm. Presented results for synthetic examples demonstrate that the novel randomized decomposition provides good accuracy for reduced computational and memory demands as compared to use of classical approaches.

An investigation of aviator problem-solving skills as they relate to amount of total flight time

NASA Astrophysics Data System (ADS)

Guilkey, James Elwood, Jr.

As aircraft become increasingly more reliable, safety issues have shifted towards the human component of flight, the pilot. Jensen (1995) indicated that 80% of all General Aviation (GA) accidents are the result, at least in part, of errors committed by the aviator. One major focus of current research involves aviator decision making (ADM). ADM combines a broad range of psychological factors including personality, attitude, and motivation. This approach fails to isolate certain key components such as aviator problem-solving (APS) which are paramount to safe operations. It should be noted that there is a clear delineation between problem-solving and decision making and not assume that they are homogenous. For years, researchers, industry, and the Federal Aviation Administration (FAA) have depended on total flight hours as the standard by which to judge aviator expertise. A pilot with less than a prescribed number of hours is considered a novice while those above that mark are considered experts. The reliance on time as a predictor of performance may be accurate when considering skills which are required on every flight (i.e., takeoff and landing) but we can't assume that this holds true for all aspects of aviator expertise. Complex problem-solving for example, is something that is rarely faced during the normal course of flying. In fact, there are a myriad of procedures and FAA mandated regulations designed to assist pilots in avoiding problems. Thus, one should not assume that aviator problem-solving skills will increase over time. This study investigated the relationship between problem-solving skills of general aviation pilots and total number of flight hours. It was discovered that flight time is not a good predictor of problem-solving performance. There were two distinct strategies that were identified in the study. The first, progressive problem solving (PPS) was characterized by a stepwise method in which pilots gathered information, formulated hypotheses, and evaluated outcomes. Both high time as well as low time pilots demonstrated this approach. The second method, termed knee-jerk decision making was distinguished by a lack of problem-solving abilities and involved an almost immediate decision with little if any supporting information. Again both high and low time pilots performed in this manner. The result of these findings is a recommendation that the FAA adopt new training methods which will allow pilots to develop the skills required to handle critical inflight situations.

Aiming to complete the matrix: Eye-movement analysis of processing strategies in children's relational thinking.

PubMed

Chen, Zhe; Honomichl, Ryan; Kennedy, Diane; Tan, Enda

2016-06-01

The present study examines 5- to 8-year-old children's relation reasoning in solving matrix completion tasks. This study incorporates a componential analysis, an eye-tracking method, and a microgenetic approach, which together allow an investigation of the cognitive processing strategies involved in the development and learning of children's relational thinking. Developmental differences in problem-solving performance were largely due to deficiencies in engaging the processing strategies that are hypothesized to facilitate problem-solving performance. Feedback designed to highlight the relations between objects within the matrix improved 5- and 6-year-olds' problem-solving performance, as well as their use of appropriate processing strategies. Furthermore, children who engaged the processing strategies early on in the task were more likely to solve subsequent problems in later phases. These findings suggest that encoding relations, integrating rules, completing the model, and generalizing strategies across tasks are critical processing components that underlie relational thinking. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A genetic algorithm used for solving one optimization problem

NASA Astrophysics Data System (ADS)

Shipacheva, E. N.; Petunin, A. A.; Berezin, I. M.

2017-12-01

A problem of minimizing the length of the blank run for a cutting tool during cutting of sheet materials into shaped blanks is discussed. This problem arises during the preparation of control programs for computerized numerical control (CNC) machines. A discrete model of the problem is analogous in setting to the generalized travelling salesman problem with limitations in the form of precursor conditions determined by the technological features of cutting. A certain variant of a genetic algorithm for solving this problem is described. The effect of the parameters of the developed algorithm on the solution result for the problem with limitations is investigated.

Virtual and concrete manipulatives: a comparison of approaches for solving mathematics problems for students with autism spectrum disorder.

PubMed

Bouck, Emily C; Satsangi, Rajiv; Doughty, Teresa Taber; Courtney, William T

2014-01-01

Students with autism spectrum disorder (ASD) are included in general education classes and expected to participate in general education content, such as mathematics. Yet, little research explores academically-based mathematics instruction for this population. This single subject alternating treatment design study explored the effectiveness of concrete (physical objects that can be manipulated) and virtual (3-D objects from the Internet that can be manipulated) manipulatives to teach single- and double-digit subtraction skills. Participants in this study included three elementary-aged students (ages ranging from 6 to 10) diagnosed with ASD. Students were selected from a clinic-based setting, where all participants received medically necessary intensive services provided via one-to-one, trained therapists. Both forms of manipulatives successfully assisted students in accurately and independently solving subtraction problem. However, all three students demonstrated greater accuracy and faster independence with the virtual manipulatives as compared to the concrete manipulatives. Beyond correctly solving the subtraction problems, students were also able to generalize their learning of subtraction through concrete and virtual manipulatives to more real-world applications.

Generalized Lagrange Jacobi Gauss-Lobatto (GLJGL) Collocation Method for Solving Linear and Nonlinear Fokker-Planck Equations

NASA Astrophysics Data System (ADS)

Parand, K.; Latifi, S.; Moayeri, M. M.; Delkhosh, M.

2018-05-01

In this study, we have constructed a new numerical approach for solving the time-dependent linear and nonlinear Fokker-Planck equations. In fact, we have discretized the time variable with Crank-Nicolson method and for the space variable, a numerical method based on Generalized Lagrange Jacobi Gauss-Lobatto (GLJGL) collocation method is applied. It leads to in solving the equation in a series of time steps and at each time step, the problem is reduced to a problem consisting of a system of algebraic equations that greatly simplifies the problem. One can observe that the proposed method is simple and accurate. Indeed, one of its merits is that it is derivative-free and by proposing a formula for derivative matrices, the difficulty aroused in calculation is overcome, along with that it does not need to calculate the General Lagrange basis and matrices; they have Kronecker property. Linear and nonlinear Fokker-Planck equations are given as examples and the results amply demonstrate that the presented method is very valid, effective, reliable and does not require any restrictive assumptions for nonlinear terms.

Direct Method Transcription for a Human-Class Translunar Injection Trajectory Optimization

NASA Technical Reports Server (NTRS)

Witzberger, Kevin E.; Zeiler, Tom

2012-01-01

This paper presents a new trajectory optimization software package developed in the framework of a low-to-high fidelity 3 degrees-of-freedom (DOF)/6-DOF vehicle simulation program named Mission Analysis Simulation Tool in Fortran (MASTIF) and its application to a translunar trajectory optimization problem. The functionality of the developed optimization package is implemented as a new "mode" in generalized settings to make it applicable for a general trajectory optimization problem. In doing so, a direct optimization method using collocation is employed for solving the problem. Trajectory optimization problems in MASTIF are transcribed to a constrained nonlinear programming (NLP) problem and solved with SNOPT, a commercially available NLP solver. A detailed description of the optimization software developed is provided as well as the transcription specifics for the translunar injection (TLI) problem. The analysis includes a 3-DOF trajectory TLI optimization and a 3-DOF vehicle TLI simulation using closed-loop guidance.

Memory inhibition as a critical factor preventing creative problem solving.

PubMed

Gómez-Ariza, Carlos J; Del Prete, Francesco; Prieto Del Val, Laura; Valle, Tania; Bajo, M Teresa; Fernandez, Angel

2017-06-01

The hypothesis that reduced accessibility to relevant information can negatively affect problem solving in a remote associate test (RAT) was tested by using, immediately before the RAT, a retrieval practice procedure to hinder access to target solutions. The results of 2 experiments clearly showed that, relative to baseline, target words that had been competitors during selective retrieval were much less likely to be provided as solutions in the RAT, demonstrating that performance in the problem-solving task was strongly influenced by the predetermined accessibility status of the solutions in memory. Importantly, this was so even when participants were unaware of the relationship between the memory and the problem-solving procedures in the experiments. This finding is consistent with an inhibitory account of retrieval-induced forgetting effects and, more generally, constitutes support for the idea that the activation status of mental representations originating in a given task (e.g., episodic memory) can unwittingly have significant consequences for a different, unrelated task (e.g., problem solving). (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The effect of problem structure on problem-solving: an fMRI study of word versus number problems.

PubMed

Newman, Sharlene D; Willoughby, Gregory; Pruce, Benjamin

2011-09-02

It has long been thought that word problems are more difficult to solve than number/equation problems. However, recent findings have begun to bring this broadly believed idea into question. The current study examined the processing differences between these two types of problems. The behavioral results presented here failed to show an overwhelming advantage for number problems. In fact, there were more errors for the number problems than the word problems. The neuroimaging results reported demonstrate that there is significant overlap in the processing of what, on the surface, appears to be completely different problems that elicit different problem-solving strategies. Word and number problems rely on a general network responsible for problem-solving that includes the superior posterior parietal cortex, the horizontal segment of the intraparietal sulcus which is hypothesized to be involved in problem representation and calculation as well as the regions that have been linked to executive aspects of working memory such as the pre-SMA and basal ganglia. While overlap was observed, significant differences were also found primarily in language processing regions such as Broca's and Wernicke's areas for the word problems and the horizontal segment of the intraparietal sulcus for the number problems. Copyright © 2011 Elsevier B.V. All rights reserved.

Design and Diagnosis Problem Solving with Multifunctional Technical Knowledge Bases

DTIC Science & Technology

1992-09-29

STRUCTURE METHODOLOGY Design problem solving is a complex activity involving a number of subtasks. and a number of alternative methods potentially available...Conference on Artificial Intelligence. London: The British Computer Society, pp. 621-633. Friedland, P. (1979). Knowledge-based experimental design ...Computing Milieuxl: Management of Computing and Information Systems- -ty,*m man- agement General Terms: Design . Methodology Additional Key Words and Phrases

The development of a culture of problem solving with secondary students through heuristic strategies

NASA Astrophysics Data System (ADS)

Eisenmann, Petr; Novotná, Jarmila; Přibyl, Jiří; Břehovský, Jiří

2015-12-01

The article reports the results of a longitudinal research study conducted in three mathematics classes in Czech schools with 62 pupils aged 12-18 years. The pupils were exposed to the use of selected heuristic strategies in mathematical problem solving for a period of 16 months. This was done through solving problems where the solution was the most efficient if heuristic strategies were used. The authors conducted a two-dimensional classification of the use of heuristic strategies based on the work of Pólya (2004) and Schoenfeld (1985). We developed a tool that allows for the description of a pupil's ability to solve problems. Named, the Culture of Problem Solving (CPS), this tool consists of four components: intelligence, text comprehension, creativity and the ability to use existing knowledge. The pupils' success rate in problem solving and the changes in some of the CPS factors pre- and post-experiment were monitored. The pupils appeared to considerably improve in the creativity component. In addition, the results indicate a positive change in the students' attitude to problem solving. As far as the teachers participating in the experiment are concerned, a significant change was in their teaching style to a more constructivist, inquiry-based approach, as well as their willingness to accept a student's non-standard approach to solving a problem. Another important outcome of the research was the identification of the heuristic strategies that can be taught via long-term guided solutions of suitable problems and those that cannot. Those that can be taught include systematic experimentation, guess-check-revise and introduction of an auxiliary element. Those that cannot be taught (or can only be taught with difficulty) include the strategies of specification and generalization and analogy.

The influence of open goals on the acquisition of problem-relevant information.

PubMed

Moss, Jarrod; Kotovsky, Kenneth; Cagan, Jonathan

2007-09-01

There have been a number of recent findings indicating that unsolved problems, or open goals more generally, influence cognition even when the current task has no relation to the task in which the goal was originally set. It was hypothesized that open goals would influence what information entered the problem-solving process. Three studies were conducted to establish the effect of open goals on the acquisition of problem-relevant information. It was found that problem-relevant information, or hints, presented implicitly in a 2nd task in between attempts at solving problems aided problem solving. This effect cannot be attributed to strategic behavior after participants caught on to the manipulation, as most participants were not aware of the relationship. The implications of this research are discussed, including potential contributions to our understanding of insight, incubation, transfer, and creativity. 2007 APA

Development and Evaluation of a Casualty Evacuation Model for a European Conflict.

DTIC Science & Technology

1985-12-01

EVAC, the computer code which implements our technique, has been used to solve a series of test problems in less time and requiring less memory than...the order of 1/K the amount of main memory for a K-commodity problem, so it can solve significantly larger problems than MCNF. I . 10 CHAPTER II A...technique may require only half the memory of the general L.P. package [6]. These advances are due to the efficient data structures which have been

On unified modeling, theory, and method for solving multi-scale global optimization problems

NASA Astrophysics Data System (ADS)

Gao, David Yang

2016-10-01

A unified model is proposed for general optimization problems in multi-scale complex systems. Based on this model and necessary assumptions in physics, the canonical duality theory is presented in a precise way to include traditional duality theories and popular methods as special applications. Two conjectures on NP-hardness are proposed, which should play important roles for correctly understanding and efficiently solving challenging real-world problems. Applications are illustrated for both nonconvex continuous optimization and mixed integer nonlinear programming.

Much ado about aha!: Insight problem solving is strongly related to working memory capacity and reasoning ability.

PubMed

Chuderski, Adam; Jastrzębski, Jan

2018-02-01

A battery comprising 4 fluid reasoning tests as well as 13 working memory (WM) tasks that involved storage, recall, updating, binding, and executive control, was applied to 318 adults in order to evaluate the true relationship of reasoning ability and WM capacity (WMC) to insight problem solving, measured using 40 verbal, spatial, math, matchstick, and remote associates problems (insight problems). WMC predicted 51.8% of variance in insight problem solving and virtually explained its almost isomorphic link to reasoning ability (84.6% of shared variance). The strong link between WMC and insight pertained generally to most WM tasks and insight problems, was identical for problems solved with and without reported insight, was linear throughout the ability levels, and was not mediated by age, motivation, anxiety, psychoticism, and openness to experience. In contrast to popular views on the sudden and holistic nature of insight, the solving of insight problems results primarily from typical operations carried out by the basic WM mechanisms that are responsible for the maintenance, retrieval, transformation, and control of information in the broad range of intellectual tasks (including fluid reasoning). Little above and beyond WM is unique about insight. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The testing effect and analogical problem-solving.

PubMed

Peterson, Daniel J; Wissman, Kathryn T

2018-06-25

Researchers generally agree that retrieval practice of previously learned material facilitates subsequent recall of same material, a phenomenon known as the testing effect. There is debate, however, about when such benefits transfer to related (though not identical) material. The current study examines the phenomenon of transfer in the domain of analogical problem-solving. In Experiments 1 and 2, learners were presented a source text describing a problem and solution to read which was subsequently either restudied or recalled. Following a short (Experiment 1) or long (Experiment 2) delay, learners were given a new target text and asked to solve a problem. The two texts shared a common structure such that the provided solution for the source text could be applied to solve the problem in the target text. In a combined analysis of both experiments, learners in the retrieval practice condition were more successful at solving the problem than those in the restudy condition. Experiment 3 explored the degree to which retrieval practice promotes cued versus spontaneous transfer by manipulating whether participants were provided with an explicit hint that the source and target texts were related. Results revealed no effect of retrieval practice.

The development and nature of problem-solving among first-semester calculus students

NASA Astrophysics Data System (ADS)

Dawkins, Paul Christian; Mendoza Epperson, James A.

2014-08-01

This study investigates interactions between calculus learning and problem-solving in the context of two first-semester undergraduate calculus courses in the USA. We assessed students' problem-solving abilities in a common US calculus course design that included traditional lecture and assessment with problem-solving-oriented labs. We investigate this blended instruction as a local representative of the US calculus reform movements that helped foster it. These reform movements tended to emphasize problem-solving as well as multiple mathematical registers and quantitative modelling. Our statistical analysis reveals the influence of the blended traditional/reform calculus instruction on students' ability to solve calculus-related, non-routine problems through repeated measures over the semester. The calculus instruction in this study significantly improved students' performance on non-routine problems, though performance improved more regarding strategies and accuracy than it did for drawing conclusions and providing justifications. We identified problem-solving behaviours that characterized top performance or attrition in the course. Top-performing students displayed greater algebraic proficiency, calculus skills, and more general heuristics than their peers, but overused algebraic techniques even when they proved cumbersome or inappropriate. Students who subsequently withdrew from calculus often lacked algebraic fluency and understanding of the graphical register. The majority of participants, when given a choice, relied upon less sophisticated trial-and-error approaches in the numerical register and rarely used the graphical register, contrary to the goals of US calculus reform. We provide explanations for these patterns in students' problem-solving performance in view of both their preparation for university calculus and the courses' assessment structure, which preferentially rewarded algebraic reasoning. While instruction improved students' problem-solving performance, we observe that current instruction requires ongoing refinement to help students develop multi-register fluency and the ability to model quantitatively, as is called for in current US standards for mathematical instruction.

The effects of duration of exposure to the REAPS model in developing students' general creativity and creative problem solving in science

NASA Astrophysics Data System (ADS)

Alhusaini, Abdulnasser Alashaal F.

The Real Engagement in Active Problem Solving (REAPS) model was developed in 2004 by C. June Maker and colleagues as an intervention for gifted students to develop creative problem solving ability through the use of real-world problems. The primary purpose of this study was to examine the effects of the REAPS model on developing students' general creativity and creative problem solving in science with two durations as independent variables. The long duration of the REAPS model implementation lasted five academic quarters or approximately 10 months; the short duration lasted two quarters or approximately four months. The dependent variables were students' general creativity and creative problem solving in science. The second purpose of the study was to explore which aspects of creative problem solving (i.e., generating ideas, generating different types of ideas, generating original ideas, adding details to ideas, generating ideas with social impact, finding problems, generating and elaborating on solutions, and classifying elements) were most affected by the long duration of the intervention. The REAPS model in conjunction with Amabile's (1983; 1996) model of creative performance provided the theoretical framework for this study. The study was conducted using data from the Project of Differentiation for Diverse Learners in Regular Classrooms (i.e., the Australian Project) in which one public elementary school in the eastern region of Australia cooperated with the DISCOVER research team at the University of Arizona. All students in the school from first to sixth grade participated in the study. The total sample was 360 students, of which 115 were exposed to a long duration and 245 to a short duration of the REAPS model. The principal investigators used a quasi-experimental research design in which all students in the school received the treatment for different durations. Students in both groups completed pre- and posttests using the Test of Creative Thinking-Drawing Production (TCT-DP) and the Test of Creative Problem Solving in Science (TCPS-S). A one-way analysis of covariance (ANCOVA) was conducted to control for differences between the two groups on pretest results. Statistically significant differences were not found between posttest scores on the TCT-DP for the two durations of REAPS model implementation. However, statistically significant differences were found between posttest scores on the TCPS-S. These findings are consistent with Amabile's (1983; 1996) model of creative performance, particularly her explanation that domain-specific creativity requires knowledge such as specific content and technical skills that must be learned prior to being applied creatively. The findings are also consistent with literature in which researchers have found that longer interventions typically result in expected positive growth in domain-specific creativity, while both longer and shorter interventions have been found effective in improving domain-general creativity. Change scores were also calculated between pre- and posttest scores on the 8 aspects of creativity (Maker, Jo, Alfaiz, & Alhusaini, 2015a), and a binary logistic regression was conducted to assess which were the most affected by the long duration of the intervention. The regression model was statistically significant, with aspects of generating ideas, adding details to ideas, and finding problems being the most affected by the long duration of the intervention. Based on these findings, the researcher believes that the REAPS model is a useful intervention to develop students' creativity. Future researchers should implement the model for longer durations if they are interested in developing students' domain-specific creative problem solving ability.

The Role of Cognitive Processes, Foundational Math Skill, and Calculation Accuracy and Fluency in Word-Problem Solving versus Pre-Algebraic Knowledge

PubMed Central

Fuchs, Lynn S.; Gilbert, Jennifer K.; Powell, Sarah R.; Cirino, Paul T.; Fuchs, Douglas; Hamlett, Carol L.; Seethaler, Pamela M.; Tolar, Tammy D.

2016-01-01

The purpose of this study was to examine child-level pathways in development of pre-algebraic knowledge versus word-problem solving, while evaluating the contribution of calculation accuracy and fluency as mediators of foundational skills/processes. Children (n = 962; mean 7.60 years) were assessed on general cognitive processes and early calculation, word-problem, and number knowledge at start of grade 2; calculation accuracy and calculation fluency at end of grade 2; and pre-algebraic knowledge and word-problem solving at end of grade 4. Important similarities in pathways were identified, but path analysis also indicated that language comprehension is more critical for later word-problem solving than pre-algebraic knowledge. We conclude that pathways in development of these forms of 4th-grade mathematics performance are more alike than different, but demonstrate the need to fine-tune instruction for strands of the mathematics curriculum in ways that address individual students’ foundational mathematics skills or cognitive processes. PMID:27786534

Efficient dual approach to distance metric learning.

PubMed

Shen, Chunhua; Kim, Junae; Liu, Fayao; Wang, Lei; van den Hengel, Anton

2014-02-01

Distance metric learning is of fundamental interest in machine learning because the employed distance metric can significantly affect the performance of many learning methods. Quadratic Mahalanobis metric learning is a popular approach to the problem, but typically requires solving a semidefinite programming (SDP) problem, which is computationally expensive. The worst case complexity of solving an SDP problem involving a matrix variable of size D×D with O(D) linear constraints is about O(D(6.5)) using interior-point methods, where D is the dimension of the input data. Thus, the interior-point methods only practically solve problems exhibiting less than a few thousand variables. Because the number of variables is D(D+1)/2, this implies a limit upon the size of problem that can practically be solved around a few hundred dimensions. The complexity of the popular quadratic Mahalanobis metric learning approach thus limits the size of problem to which metric learning can be applied. Here, we propose a significantly more efficient and scalable approach to the metric learning problem based on the Lagrange dual formulation of the problem. The proposed formulation is much simpler to implement, and therefore allows much larger Mahalanobis metric learning problems to be solved. The time complexity of the proposed method is roughly O(D(3)), which is significantly lower than that of the SDP approach. Experiments on a variety of data sets demonstrate that the proposed method achieves an accuracy comparable with the state of the art, but is applicable to significantly larger problems. We also show that the proposed method can be applied to solve more general Frobenius norm regularized SDP problems approximately.

Is Trait Rumination Associated with the Ability to Generate Effective Problem Solving Strategies? Utilizing Two Versions of the Means-Ends Problem-Solving Test.

PubMed

Hasegawa, Akira; Nishimura, Haruki; Mastuda, Yuko; Kunisato, Yoshihiko; Morimoto, Hiroshi; Adachi, Masaki

This study examined the relationship between trait rumination and the effectiveness of problem solving strategies as assessed by the Means-Ends Problem-Solving Test (MEPS) in a nonclinical population. The present study extended previous studies in terms of using two instructions in the MEPS: the second-person, actual strategy instructions, which has been utilized in previous studies on rumination, and the third-person, ideal-strategy instructions, which is considered more suitable for assessing the effectiveness of problem solving strategies. We also replicated the association between rumination and each dimension of the Social Problem-Solving Inventory-Revised Short Version (SPSI-R:S). Japanese undergraduate students ( N  = 223) completed the Beck Depression Inventory-Second Edition, Ruminative Responses Scale (RRS), MEPS, and SPSI-R:S. One half of the sample completed the MEPS with the second-person, actual strategy instructions. The other participants completed the MEPS with the third-person, ideal-strategy instructions. The results showed that neither total RRS score, nor its subscale scores were significantly correlated with MEPS scores under either of the two instructions. These findings taken together with previous findings indicate that in nonclinical populations, trait rumination is not related to the effectiveness of problem solving strategies, but that state rumination while responding to the MEPS deteriorates the quality of strategies. The correlations between RRS and SPSI-R:S scores indicated that trait rumination in general, and its brooding subcomponent in particular are parts of cognitive and behavioral responses that attempt to avoid negative environmental and negative private events. Results also showed that reflection is a part of active problem solving.

How do video-based demonstration assessment tasks affect problem-solving process, test anxiety, chemistry anxiety and achievement in general chemistry students?

NASA Astrophysics Data System (ADS)

Terrell, Rosalind Stephanie

2001-12-01

Because paper-and-pencil testing provides limited knowledge about what students know about chemical phenomena, we have developed video-based demonstrations to broaden measurement of student learning. For example, students might be shown a video demonstrating equilibrium shifts. Two methods for viewing equilibrium shifts are changing the concentration of the reactants and changing the temperature of the system. The students are required to combine the data collected from the video and their knowledge of chemistry to determine which way the equilibrium shifts. Video-based demonstrations are important techniques for measuring student learning because they require students to apply conceptual knowledge learned in class to a specific chemical problem. This study explores how video-based demonstration assessment tasks affect problem-solving processes, test anxiety, chemistry anxiety and achievement in general chemistry students. Several instruments were used to determine students' knowledge about chemistry, students' test and chemistry anxiety before and after treatment. Think-aloud interviews were conducted to determine students' problem-solving processes after treatment. The treatment group was compared to a control group and a group watching video demonstrations. After treatment students' anxiety increased and achievement decreased. There were also no significant differences found in students' problem-solving processes following treatment. These negative findings may be attributed to several factors that will be explored in this study.

Modelling human problem solving with data from an online game.

PubMed

Rach, Tim; Kirsch, Alexandra

2016-11-01

Since the beginning of cognitive science, researchers have tried to understand human strategies in order to develop efficient and adequate computational methods. In the domain of problem solving, the travelling salesperson problem has been used for the investigation and modelling of human solutions. We propose to extend this effort with an online game, in which instances of the travelling salesperson problem have to be solved in the context of a game experience. We report on our effort to design and run such a game, present the data contained in the resulting openly available data set and provide an outlook on the use of games in general for cognitive science research. In addition, we present three geometrical models mapping the starting point preferences in the problems presented in the game as the result of an evaluation of the data set.

Satisfiability Test with Synchronous Simulated Annealing on the Fujitsu AP1000 Massively-Parallel Multiprocessor

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Biswas, Rupak

1996-01-01

Solving the hard Satisfiability Problem is time consuming even for modest-sized problem instances. Solving the Random L-SAT Problem is especially difficult due to the ratio of clauses to variables. This report presents a parallel synchronous simulated annealing method for solving the Random L-SAT Problem on a large-scale distributed-memory multiprocessor. In particular, we use a parallel synchronous simulated annealing procedure, called Generalized Speculative Computation, which guarantees the same decision sequence as sequential simulated annealing. To demonstrate the performance of the parallel method, we have selected problem instances varying in size from 100-variables/425-clauses to 5000-variables/21,250-clauses. Experimental results on the AP1000 multiprocessor indicate that our approach can satisfy 99.9 percent of the clauses while giving almost a 70-fold speedup on 500 processors.

Numerical techniques in radiative heat transfer for general, scattering, plane-parallel media

NASA Technical Reports Server (NTRS)

Sharma, A.; Cogley, A. C.

1982-01-01

The study of radiative heat transfer with scattering usually leads to the solution of singular Fredholm integral equations. The present paper presents an accurate and efficient numerical method to solve certain integral equations that govern radiative equilibrium problems in plane-parallel geometry for both grey and nongrey, anisotropically scattering media. In particular, the nongrey problem is represented by a spectral integral of a system of nonlinear integral equations in space, which has not been solved previously. The numerical technique is constructed to handle this unique nongrey governing equation as well as the difficulties caused by singular kernels. Example problems are solved and the method's accuracy and computational speed are analyzed.

Work Strategies: The Development and Testing of a Model.

DTIC Science & Technology

1986-03-01

strategies (e.g., Craik & Lockhart , 1972); hemispheric process - -7 ing differences (e.g., Seamon & Gazzaniga, 1973); problem-solving strategies (e.g...Charness, N. (1931). Aging and skilled problem solving. 3ournal of Experimental Psychology: General, 110, 21-38. Craik , F. I. \\., & Lockhart , R. S...1972). Levels of processing : A framework for memory research. Journal of Verbal Learning and Verbal Behavior, L1, 671-684. 3ansereau, D. F., McDonald

Computation of rotor-stator interaction using the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Whitfield, David L.; Chen, Jen-Ping

1995-01-01

The numerical scheme presented belongs to a family of codes known as UNCLE (UNsteady Computation of fieLd Equations) as reported by Whitfield (1995), that is being used to solve problems in a variety of areas including compressible and incompressible flows. This derivation is specifically developed for general unsteady multi-blade-row turbomachinery problems. The scheme solves the Reynolds-averaged N-S equations with the Baldwin-Lomax turbulence model.

The Effects of a Modified Learning Strategy on the Multiple Step Mathematical Word Problem Solving Ability of Middle School Students with High-Functioning Autism or Asperger's Syndrome

ERIC Educational Resources Information Center

Schaefer Whitby, Peggy J.

2009-01-01

Children with HFA/AS are outperformed by their neuro-typical peers on mathematical problem solving skills even though they have average-to-above-average intelligence (Dickerson Mayes & Calhoun, 2003b); have average-to-above-average computation skills (Chiang & Lin, 2007); and, are educated in the general education setting (Twenty Eighth…

Improving problem solving in primary school students: The effect of a training programme focusing on metacognition and working memory.

PubMed

Cornoldi, Cesare; Carretti, Barbara; Drusi, Silvia; Tencati, Chiara

2015-09-01

Despite doubts voiced on their efficacy, a series of studies has been carried out on the capacity of training programmes to improve academic and reasoning skills by focusing on underlying cognitive abilities and working memory in particular. No systematic efforts have been made, however, to test training programmes that involve both general and specific underlying abilities. If effective, these programmes could help to increase students' motivation and competence. This study examined the feasibility of improving problem-solving skills in school children by means of a training programme that addresses general and specific abilities involved in problem solving, focusing on metacognition and working memory. The project involved a sample of 135 primary school children attending eight classes in the third, fourth, and fifth grades (age range 8-10 years). The classes were assigned to two groups, one attending the training programme in the first 3 months of the study (Training Group 1) and the other serving as a waiting-list control group (Training Group 2). In the second phase of the study, the role of the two groups was reversed, with Training Group 2 attending the training instead of Training Group 1. The training programme led to improvements in both metacognitive and working memory tasks, with positive-related effects on the ability to solve problems. The gains seen in Training Group 1 were also maintained at the second post-test (after 3 months). Specific activities focusing on metacognition and working memory may contribute to modifying arithmetical problem-solving performance in primary school children. © 2015 The British Psychological Society.

Algebraic Reasoning in Solving Mathematical Problem Based on Learning Style

NASA Astrophysics Data System (ADS)

Indraswari, N. F.; Budayasa, I. K.; Ekawati, R.

2018-01-01

This study aimed to describe algebraic reasoning of secondary school’s pupils with different learning styles in solving mathematical problem. This study begins by giving the questionnaire to find out the learning styles and followed by mathematical ability test to get three subjects of 8th-grade whereas the learning styles of each pupil is visual, auditory, kinesthetic and had similar mathematical abilities. Then it continued with given algebraic problems and interviews. The data is validated using triangulation of time. The result showed that in the pattern of seeking indicator, subjects identified the things that were known and asked based on them observations. The visual and kinesthetic learners represented the known information in a chart, whereas the auditory learner in a table. In addition, they found the elements which makes the pattern and made a relationship between two quantities. In the pattern recognition indicator, they created conjectures on the relationship between two quantities and proved it. In the generalization indicator, they were determining the general rule of pattern found on each element of pattern using algebraic symbols and created a mathematical model. Visual and kinesthetic learners determined the general rule of equations which was used to solve problems using algebraic symbols, but auditory learner in a sentence.

Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving

PubMed Central

Maisto, Domenico; Donnarumma, Francesco; Pezzulo, Giovanni

2015-01-01

It has long been recognized that humans (and possibly other animals) usually break problems down into smaller and more manageable problems using subgoals. Despite a general consensus that subgoaling helps problem solving, it is still unclear what the mechanisms guiding online subgoal selection are during the solution of novel problems for which predefined solutions are not available. Under which conditions does subgoaling lead to optimal behaviour? When is subgoaling better than solving a problem from start to finish? Which is the best number and sequence of subgoals to solve a given problem? How are these subgoals selected during online inference? Here, we present a computational account of subgoaling in problem solving. Following Occam's razor, we propose that good subgoals are those that permit planning solutions and controlling behaviour using less information resources, thus yielding parsimony in inference and control. We implement this principle using approximate probabilistic inference: subgoals are selected using a sampling method that considers the descriptive complexity of the resulting sub-problems. We validate the proposed method using a standard reinforcement learning benchmark (four-rooms scenario) and show that the proposed method requires less inferential steps and permits selecting more compact control programs compared to an equivalent procedure without subgoaling. Furthermore, we show that the proposed method offers a mechanistic explanation of the neuronal dynamics found in the prefrontal cortex of monkeys that solve planning problems. Our computational framework provides a novel integrative perspective on subgoaling and its adaptive advantages for planning, control and learning, such as for example lowering cognitive effort and working memory load. PMID:25652466

Operator priming and generalization of practice in adults' simple arithmetic.

PubMed

Chen, Yalin; Campbell, Jamie I D

2016-04-01

There is a renewed debate about whether educated adults solve simple addition problems (e.g., 2 + 3) by direct fact retrieval or by fast, automatic counting-based procedures. Recent research testing adults' simple addition and multiplication showed that a 150-ms preview of the operator (+ or ×) facilitated addition, but not multiplication, suggesting that a general addition procedure was primed by the + sign. In Experiment 1 (n = 36), we applied this operator-priming paradigm to rule-based problems (0 + N = N, 1 × N = N, 0 × N = 0) and 1 + N problems with N ranging from 0 to 9. For the rule-based problems, we found both operator-preview facilitation and generalization of practice (e.g., practicing 0 + 3 sped up unpracticed 0 + 8), the latter being a signature of procedure use; however, we also found operator-preview facilitation for 1 + N in the absence of generalization, which implies the 1 + N problems were solved by fact retrieval but nonetheless were facilitated by an operator preview. Thus, the operator preview effect does not discriminate procedure use from fact retrieval. Experiment 2 (n = 36) investigated whether a population with advanced mathematical training-engineering and computer science students-would show generalization of practice for nonrule-based simple addition problems (e.g., 1 + 4, 4 + 7). The 0 + N problems again presented generalization, whereas no nonzero problem type did; but all nonzero problems sped up when the identical problems were retested, as predicted by item-specific fact retrieval. The results pose a strong challenge to the generality of the proposal that skilled adults' simple addition is based on fast procedural algorithms, and instead support a fact-retrieval model of fast addition performance. (c) 2016 APA, all rights reserved).

A Simple Label Switching Algorithm for Semisupervised Structural SVMs.

PubMed

Balamurugan, P; Shevade, Shirish; Sundararajan, S

2015-10-01

In structured output learning, obtaining labeled data for real-world applications is usually costly, while unlabeled examples are available in abundance. Semisupervised structured classification deals with a small number of labeled examples and a large number of unlabeled structured data. In this work, we consider semisupervised structural support vector machines with domain constraints. The optimization problem, which in general is not convex, contains the loss terms associated with the labeled and unlabeled examples, along with the domain constraints. We propose a simple optimization approach that alternates between solving a supervised learning problem and a constraint matching problem. Solving the constraint matching problem is difficult for structured prediction, and we propose an efficient and effective label switching method to solve it. The alternating optimization is carried out within a deterministic annealing framework, which helps in effective constraint matching and avoiding poor local minima, which are not very useful. The algorithm is simple and easy to implement. Further, it is suitable for any structured output learning problem where exact inference is available. Experiments on benchmark sequence labeling data sets and a natural language parsing data set show that the proposed approach, though simple, achieves comparable generalization performance.

Projective-Dual Method for Solving Systems of Linear Equations with Nonnegative Variables

NASA Astrophysics Data System (ADS)

Ganin, B. V.; Golikov, A. I.; Evtushenko, Yu. G.

2018-02-01

In order to solve an underdetermined system of linear equations with nonnegative variables, the projection of a given point onto its solutions set is sought. The dual of this problem—the problem of unconstrained maximization of a piecewise-quadratic function—is solved by Newton's method. The problem of unconstrained optimization dual of the regularized problem of finding the projection onto the solution set of the system is considered. A connection of duality theory and Newton's method with some known algorithms of projecting onto a standard simplex is shown. On the example of taking into account the specifics of the constraints of the transport linear programming problem, the possibility to increase the efficiency of calculating the generalized Hessian matrix is demonstrated. Some examples of numerical calculations using MATLAB are presented.

Effect of interfacial stresses in an elastic body with a nanoinclusion

NASA Astrophysics Data System (ADS)

Vakaeva, Aleksandra B.; Grekov, Mikhail A.

2018-05-01

The 2-D problem of an infinite elastic solid with a nanoinclusion of a different from circular shape is solved. The interfacial stresses are acting at the interface. Contact of the inclusion with the matrix satisfies the ideal conditions of cohesion. The generalized Laplace - Young law defines conditions at the interface. To solve the problem, Gurtin - Murdoch surface elasticity model, Goursat - Kolosov complex potentials and the boundary perturbation method are used. The problem is reduced to the solution of two independent Riemann - Hilbert's boundary problems. For the circular inclusion, hypersingular integral equation in an unknown interfacial stress is derived. The algorithm of solving this equation is constructed. The influence of the interfacial stress and the dimension of the circular inclusion on the stress distribution and stress concentration at the interface are analyzed.

Very Large Scale Optimization

NASA Technical Reports Server (NTRS)

Vanderplaats, Garrett; Townsend, James C. (Technical Monitor)

2002-01-01

The purpose of this research under the NASA Small Business Innovative Research program was to develop algorithms and associated software to solve very large nonlinear, constrained optimization tasks. Key issues included efficiency, reliability, memory, and gradient calculation requirements. This report describes the general optimization problem, ten candidate methods, and detailed evaluations of four candidates. The algorithm chosen for final development is a modern recreation of a 1960s external penalty function method that uses very limited computer memory and computational time. Although of lower efficiency, the new method can solve problems orders of magnitude larger than current methods. The resulting BIGDOT software has been demonstrated on problems with 50,000 variables and about 50,000 active constraints. For unconstrained optimization, it has solved a problem in excess of 135,000 variables. The method includes a technique for solving discrete variable problems that finds a "good" design, although a theoretical optimum cannot be guaranteed. It is very scalable in that the number of function and gradient evaluations does not change significantly with increased problem size. Test cases are provided to demonstrate the efficiency and reliability of the methods and software.

Visual Representations in Mathematics Teaching: An Experiment with Students

ERIC Educational Resources Information Center

Debrenti, Edith

2015-01-01

General problem-solving skills are of central importance in school mathematics achievement. Word problems play an important role not just in mathematical education, but in general education as well. Meaningful learning and understanding are basic aspects of all kinds of learning and it is even more important in the case of learning mathematics. In…

Hybrid General Pattern Search and Simulated Annealing for Industrail Production Planning Problems

NASA Astrophysics Data System (ADS)

Vasant, P.; Barsoum, N.

2010-06-01

In this paper, the hybridization of GPS (General Pattern Search) method and SA (Simulated Annealing) incorporated in the optimization process in order to look for the global optimal solution for the fitness function and decision variables as well as minimum computational CPU time. The real strength of SA approach been tested in this case study problem of industrial production planning. This is due to the great advantage of SA for being easily escaping from trapped in local minima by accepting up-hill move through a probabilistic procedure in the final stages of optimization process. Vasant [1] in his Ph. D thesis has provided 16 different techniques of heuristic and meta-heuristic in solving industrial production problems with non-linear cubic objective functions, eight decision variables and 29 constraints. In this paper, fuzzy technological problems have been solved using hybrid techniques of general pattern search and simulated annealing. The simulated and computational results are compared to other various evolutionary techniques.

Developing Metacognitive and Problem-Solving Skills through Problem Manipulation

ERIC Educational Resources Information Center

Parker Siburt, Claire J.; Bissell, Ahrash N.; Macphail, Richard A.

2011-01-01

In a collaborative effort between the our university's department of chemistry and the academic resource center, we designed a model for general chemistry recitation based on a problem manipulation method in which students actively assess the skills and knowledge used to answer a chemical problem and then manipulate the problem to create a new…

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

Cognitive arithmetic and problem solving: a comparison of children with specific and general mathematics difficulties.

PubMed

Jordan, N C; Montani, T O

1997-01-01

This study examined problem-solving and number-fact skills in two subgroups of third-grade children with mathematics difficulties (MD): MD-specific (n = 12) and MD-general (n = 12). The MD-specific group had difficulties in mathematics but not in reading, and the MD-general group had difficulties in reading as well as in mathematics. A comparison group of nonimpaired children (n = 24) also was included. The findings showed that on both story and number-fact problems, the MD-specific group performed worse than the nonimpaired group in timed conditions but not in untimed conditions. The MD-general group, on the other hand, performed worse than the nonimpaired group, regardless of whether tasks were timed or not. An analysis of children's strategies in untimed conditions showed that both the MD-specific and the MD-general groups relied more on backup strategies than the nonimpaired group. However, children in the MD-specific group executed backup strategies more skillfully than children in the MD-general group, allowing them to achieve parity with children in the nonimpaired group when tasks were not timed. The findings suggest that children with specific MD have circumscribed deficits associated with fact retrieval, whereas children with general MD have more basic delays associated with problem conceptualization and execution of calculation procedures.

The deep play of medicine: discursive and collaborative processing of evidence in medical problem solving.

PubMed

Måseide, Per

2006-01-01

Ethnographic research was conducted in the thoracic ward of a Norwegian university hospital in order to study collaborative medical problem solving. As a general principle, evidence-based medicine is supposed to lead the process of medical problem solving. However, medical problem solving also requires evidence of a different kind. This is the more concrete form of evidence, such as X rays and other representations, that guides medical practice and makes sure that decisions are grounded in sound empirical facts and knowledge. In medicine, 'evidence' is on the one hand an abstract category; on the other hand, it is a tool that is practically enacted during the problem-solving work. Medical evidence does not 'show itself'. As such it has an emergent quality. Medical evidence has to be established and made practically useful in the collaborative settings by the participants in order to make conclusions about diagnoses and treatment. Hence, evidence is an interactional product; it is discursively generated and its applicability requires discourse. In addition, the production of medical evidence requires more than medical discourse and professional considerations. This paper looks at the production processes and use of medical evidence and the ambiguous meaning of this term in practical medicine.

New Operational Matrices for Solving Fractional Differential Equations on the Half-Line

PubMed Central

2015-01-01

In this paper, the fractional-order generalized Laguerre operational matrices (FGLOM) of fractional derivatives and fractional integration are derived. These operational matrices are used together with spectral tau method for solving linear fractional differential equations (FDEs) of order ν (0 < ν < 1) on the half line. An upper bound of the absolute errors is obtained for the approximate and exact solutions. Fractional-order generalized Laguerre pseudo-spectral approximation is investigated for solving nonlinear initial value problem of fractional order ν. The extension of the fractional-order generalized Laguerre pseudo-spectral method is given to solve systems of FDEs. We present the advantages of using the spectral schemes based on fractional-order generalized Laguerre functions and compare them with other methods. Several numerical examples are implemented for FDEs and systems of FDEs including linear and nonlinear terms. We demonstrate the high accuracy and the efficiency of the proposed techniques. PMID:25996369

New operational matrices for solving fractional differential equations on the half-line.

PubMed

Bhrawy, Ali H; Taha, Taha M; Alzahrani, Ebraheem O; Alzahrani, Ebrahim O; Baleanu, Dumitru; Alzahrani, Abdulrahim A

2015-01-01

In this paper, the fractional-order generalized Laguerre operational matrices (FGLOM) of fractional derivatives and fractional integration are derived. These operational matrices are used together with spectral tau method for solving linear fractional differential equations (FDEs) of order ν (0 < ν < 1) on the half line. An upper bound of the absolute errors is obtained for the approximate and exact solutions. Fractional-order generalized Laguerre pseudo-spectral approximation is investigated for solving nonlinear initial value problem of fractional order ν. The extension of the fractional-order generalized Laguerre pseudo-spectral method is given to solve systems of FDEs. We present the advantages of using the spectral schemes based on fractional-order generalized Laguerre functions and compare them with other methods. Several numerical examples are implemented for FDEs and systems of FDEs including linear and nonlinear terms. We demonstrate the high accuracy and the efficiency of the proposed techniques.

A comparison of Heuristic method and Llewellyn’s rules for identification of redundant constraints

NASA Astrophysics Data System (ADS)

Estiningsih, Y.; Farikhin; Tjahjana, R. H.

2018-03-01

Important techniques in linear programming is modelling and solving practical optimization. Redundant constraints are consider for their effects on general linear programming problems. Identification and reduce redundant constraints are for avoidance of all the calculations associated when solving an associated linear programming problems. Many researchers have been proposed for identification redundant constraints. This paper a compararison of Heuristic method and Llewellyn’s rules for identification of redundant constraints.

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments.

PubMed

Fisicaro, G; Genovese, L; Andreussi, O; Marzari, N; Goedecker, S

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.

A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisicaro, G., E-mail: giuseppe.fisicaro@unibas.ch; Goedecker, S.; Genovese, L.

2016-01-07

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and themore » linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.« less

How doctors learn: the role of clinical problems across the medical school-to-practice continuum.

PubMed

Slotnick, H B

1996-01-01

The author proposes a theory of how physicians learn that uses clinical problem solving as its central feature. His theory, which integrates insights from Maslow, Schön, Norman, and others, claims that physicians-in-training and practicing physicians learn largely by deriving insights from clinical experience. These insights allow the learner to solve future problems and thereby address the learner's basic human needs for security, affiliation, and self-esteem. Ensuring that students gain such insights means that the proper roles of the teacher are (1) to select problems for students to solve and offer guidance on how to solve them, and (2) to serve as a role model of how to reflect on the problem, its solution, and the solution's effectiveness. Three principles guide instruction within its framework for learning: (1) learners, whether physicians-in-training or practicing physicians, seek to solve problems they recognize they have; (2) learners want to be involved in their own learning; and (3) instruction must both be time-efficient and also demonstrate the range of ways in which students can apply what they learn. The author concludes by applying the theory to an aspect of undergraduate education and to the general process of continuing medical education.

Using Perturbed QR Factorizations To Solve Linear Least-Squares Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Avron, Haim; Ng, Esmond G.; Toledo, Sivan

2008-03-21

We propose and analyze a new tool to help solve sparse linear least-squares problems min{sub x} {parallel}Ax-b{parallel}{sub 2}. Our method is based on a sparse QR factorization of a low-rank perturbation {cflx A} of A. More precisely, we show that the R factor of {cflx A} is an effective preconditioner for the least-squares problem min{sub x} {parallel}Ax-b{parallel}{sub 2}, when solved using LSQR. We propose applications for the new technique. When A is rank deficient we can add rows to ensure that the preconditioner is well-conditioned without column pivoting. When A is sparse except for a few dense rows we canmore » drop these dense rows from A to obtain {cflx A}. Another application is solving an updated or downdated problem. If R is a good preconditioner for the original problem A, it is a good preconditioner for the updated/downdated problem {cflx A}. We can also solve what-if scenarios, where we want to find the solution if a column of the original matrix is changed/removed. We present a spectral theory that analyzes the generalized spectrum of the pencil (A*A,R*R) and analyze the applications.« less

A systematic linear space approach to solving partially described inverse eigenvalue problems

NASA Astrophysics Data System (ADS)

Hu, Sau-Lon James; Li, Haujun

2008-06-01

Most applications of the inverse eigenvalue problem (IEP), which concerns the reconstruction of a matrix from prescribed spectral data, are associated with special classes of structured matrices. Solving the IEP requires one to satisfy both the spectral constraint and the structural constraint. If the spectral constraint consists of only one or few prescribed eigenpairs, this kind of inverse problem has been referred to as the partially described inverse eigenvalue problem (PDIEP). This paper develops an efficient, general and systematic approach to solve the PDIEP. Basically, the approach, applicable to various structured matrices, converts the PDIEP into an ordinary inverse problem that is formulated as a set of simultaneous linear equations. While solving simultaneous linear equations for model parameters, the singular value decomposition method is applied. Because of the conversion to an ordinary inverse problem, other constraints associated with the model parameters can be easily incorporated into the solution procedure. The detailed derivation and numerical examples to implement the newly developed approach to symmetric Toeplitz and quadratic pencil (including mass, damping and stiffness matrices of a linear dynamic system) PDIEPs are presented. Excellent numerical results for both kinds of problem are achieved under the situations that have either unique or infinitely many solutions.

Surveying college introductory physics students’ attitudes and approaches to problem solving

NASA Astrophysics Data System (ADS)

Mason, Andrew J.; Singh, Chandralekha

2016-09-01

Students’ attitudes and approaches to problem solving in physics can greatly impact their actual problem solving practices and also influence their motivation to learn and ultimately the development of expertise. We developed and validated an attitudes and approaches to problem solving (AAPS) survey and administered it to students in the introductory physics courses in a typical large research university in the US. Here, we discuss the development and validation of the survey and analysis of the student responses to the survey questions in introductory physics courses. The introductory physics students’ responses to the survey questions were also compared with those of physics faculty members and physics PhD students. We find that introductory students are in general less expert-like than the physics faculty members and PhD students. Moreover, on some AAPS survey questions, the responses of students and faculty have unexpected trends. Those trends were interpreted via individual interviews, which helped clarify reasons for those survey responses.

Anticipating students' reasoning and planning prompts in structured problem-solving lessons

NASA Astrophysics Data System (ADS)

Vale, Colleen; Widjaja, Wanty; Doig, Brian; Groves, Susie

2018-02-01

Structured problem-solving lessons are used to explore mathematical concepts such as pattern and relationships in early algebra, and regularly used in Japanese Lesson Study research lessons. However, enactment of structured problem-solving lessons which involves detailed planning, anticipation of student solutions and orchestration of whole-class discussion of solutions is an ongoing challenge for many teachers. Moreover, primary teachers have limited experience in teaching early algebra or mathematical reasoning actions such as generalising. In this study, the critical factors of enacting the structured problem-solving lessons used in Japanese Lesson Study to elicit and develop primary students' capacity to generalise are explored. Teachers from three primary schools participated in two Japanese Lesson Study teams for this study. The lesson plans and video recordings of teaching and post-lesson discussion of the two research lessons along with students' responses and learning are compared to identify critical factors. The anticipation of students' reasoning together with preparation of supporting and challenging prompts was critical for scaffolding students' capacity to grasp and communicate generality.

Games that Enlist Collective Intelligence to Solve Complex Scientific Problems.

PubMed

Burnett, Stephen; Furlong, Michelle; Melvin, Paul Guy; Singiser, Richard

2016-03-01

There is great value in employing the collective problem-solving power of large groups of people. Technological advances have allowed computer games to be utilized by a diverse population to solve problems. Science games are becoming more popular and cover various areas such as sequence alignments, DNA base-pairing, and protein and RNA folding. While these tools have been developed for the general population, they can also be used effectively in the classroom to teach students about various topics. Many games also employ a social component that entices students to continue playing and thereby to continue learning. The basic functions of game play and the potential of game play as a tool in the classroom are discussed in this article.

Social problem solving in chronic pain: An integrative model of coping predicts mental health in chronic pain patients.

PubMed

Suso-Ribera, Carlos; Camacho-Guerrero, Laura; McCracken, Lance M; Maydeu-Olivares, Alberto; Gallardo-Pujol, David

2016-06-01

Despite several models of coping have been proposed in chronic pain, research is not integrative and has not yet identified a reliable set of beneficial coping strategies. We intend to offer a comprehensive view of coping using the social problem-solving model. Participants were 369 chronic pain patients (63.78% women; mean age 58.89 years; standard deviation = 15.12 years). Correlation analyses and the structural equation model for mental health revealed potentially beneficial and harmful problem-solving components. This integrative perspective on general coping could be used to promote changes in the way patients deal with stressful conditions other than pain. © The Author(s) 2014.

Games that Enlist Collective Intelligence to Solve Complex Scientific Problems

PubMed Central

Burnett, Stephen; Furlong, Michelle; Melvin, Paul Guy; Singiser, Richard

2016-01-01

There is great value in employing the collective problem-solving power of large groups of people. Technological advances have allowed computer games to be utilized by a diverse population to solve problems. Science games are becoming more popular and cover various areas such as sequence alignments, DNA base-pairing, and protein and RNA folding. While these tools have been developed for the general population, they can also be used effectively in the classroom to teach students about various topics. Many games also employ a social component that entices students to continue playing and thereby to continue learning. The basic functions of game play and the potential of game play as a tool in the classroom are discussed in this article. PMID:27047610

The role of cognitive processes, foundational math skill, and calculation accuracy and fluency in word-problem solving versus prealgebraic knowledge.

PubMed

Fuchs, Lynn S; Gilbert, Jennifer K; Powell, Sarah R; Cirino, Paul T; Fuchs, Douglas; Hamlett, Carol L; Seethaler, Pamela M; Tolar, Tammy D

2016-12-01

The purpose of this study was to examine child-level pathways in development of prealgebraic knowledge versus word-problem solving, while evaluating the contribution of calculation accuracy and fluency as mediators of foundational skills/processes. Children (n = 962; mean 7.60 years) were assessed on general cognitive processes and early calculation, word-problem, and number knowledge at start of Grade 2; calculation accuracy and calculation fluency at end of Grade 2; and prealgebraic knowledge and word-problem solving at end of Grade 4. Important similarities in pathways were identified, but path analysis also indicated that language comprehension is more critical for later word-problem solving than prealgebraic knowledge. We conclude that pathways in development of these forms of 4th-grade mathematics performance are more alike than different, but demonstrate the need to fine-tune instruction for strands of the mathematics curriculum in ways that address individual students' foundational mathematics skills or cognitive processes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Strategic Development for Middle School Students Struggling With Fractions: Assessment and Intervention.

PubMed

Zhang, Dake; Stecker, Pamela; Huckabee, Sloan; Miller, Rhonda

2016-09-01

Research has suggested that different strategies used when solving fraction problems are highly correlated with students' problem-solving accuracy. This study (a) utilized latent profile modeling to classify students into three different strategic developmental levels in solving fraction comparison problems and (b) accordingly provided differentiated strategic training for students starting from two different strategic developmental levels. In Study 1 we assessed 49 middle school students' performance on fraction comparison problems and categorized students into three clusters of strategic developmental clusters: a cross-multiplication cluster with the highest accuracy, a representation strategy cluster with medium accuracy, and a whole-number strategy cluster with the lowest accuracy. Based on the strategic developmental levels identified in Study 1, in Study 2 we selected three students from the whole-number strategy cluster and another three students from the representation strategy cluster and implemented a differentiated strategic training intervention within a multiple-baseline design. Results showed that both groups of students transitioned from less advanced to more advanced strategies and improved their problem-solving accuracy during the posttest, the maintenance test, and the generalization test. © Hammill Institute on Disabilities 2014.

Analog "neuronal" networks in early vision.

PubMed Central

Koch, C; Marroquin, J; Yuille, A

1986-01-01

Many problems in early vision can be formulated in terms of minimizing a cost function. Examples are shape from shading, edge detection, motion analysis, structure from motion, and surface interpolation. As shown by Poggio and Koch [Poggio, T. & Koch, C. (1985) Proc. R. Soc. London, Ser. B 226, 303-323], quadratic variational problems, an important subset of early vision tasks, can be "solved" by linear, analog electrical, or chemical networks. However, in the presence of discontinuities, the cost function is nonquadratic, raising the question of designing efficient algorithms for computing the optimal solution. Recently, Hopfield and Tank [Hopfield, J. J. & Tank, D. W. (1985) Biol. Cybern. 52, 141-152] have shown that networks of nonlinear analog "neurons" can be effective in computing the solution of optimization problems. We show how these networks can be generalized to solve the nonconvex energy functionals of early vision. We illustrate this approach by implementing a specific analog network, solving the problem of reconstructing a smooth surface from sparse data while preserving its discontinuities. These results suggest a novel computational strategy for solving early vision problems in both biological and real-time artificial vision systems. PMID:3459172

Divide et impera: subgoaling reduces the complexity of probabilistic inference and problem solving.

PubMed

Maisto, Domenico; Donnarumma, Francesco; Pezzulo, Giovanni

2015-03-06

It has long been recognized that humans (and possibly other animals) usually break problems down into smaller and more manageable problems using subgoals. Despite a general consensus that subgoaling helps problem solving, it is still unclear what the mechanisms guiding online subgoal selection are during the solution of novel problems for which predefined solutions are not available. Under which conditions does subgoaling lead to optimal behaviour? When is subgoaling better than solving a problem from start to finish? Which is the best number and sequence of subgoals to solve a given problem? How are these subgoals selected during online inference? Here, we present a computational account of subgoaling in problem solving. Following Occam's razor, we propose that good subgoals are those that permit planning solutions and controlling behaviour using less information resources, thus yielding parsimony in inference and control. We implement this principle using approximate probabilistic inference: subgoals are selected using a sampling method that considers the descriptive complexity of the resulting sub-problems. We validate the proposed method using a standard reinforcement learning benchmark (four-rooms scenario) and show that the proposed method requires less inferential steps and permits selecting more compact control programs compared to an equivalent procedure without subgoaling. Furthermore, we show that the proposed method offers a mechanistic explanation of the neuronal dynamics found in the prefrontal cortex of monkeys that solve planning problems. Our computational framework provides a novel integrative perspective on subgoaling and its adaptive advantages for planning, control and learning, such as for example lowering cognitive effort and working memory load. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

TRUMP. Transient & S-State Temperature Distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elrod, D.C.; Turner, W.D.

1992-03-03

TRUMP solves a general nonlinear parabolic partial differential equation describing flow in various kinds of potential fields, such as fields of temperature, pressure, or electricity and magnetism; simultaneously, it will solve two additional equations representing, in thermal problems, heat production by decomposition of two reactants having rate constants with a general Arrhenius temperature dependence. Steady-state and transient flow in one, two, or three dimensions are considered in geometrical configurations having simple or complex shapes and structures. Problem parameters may vary with spatial position, time, or primary dependent variables, temperature, pressure, or field strength. Initial conditions may vary with spatial position,more » and among the criteria that may be specified for ending a problem are upper and lower limits on the size of the primary dependent variable, upper limits on the problem time or on the number of time-steps or on the computer time, and attainment of steady state.« less

A Generalized Fast Frequency Sweep Algorithm for Coupled Circuit-EM Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rockway, J D; Champagne, N J; Sharpe, R M

2004-01-14

Frequency domain techniques are popular for analyzing electromagnetics (EM) and coupled circuit-EM problems. These techniques, such as the method of moments (MoM) and the finite element method (FEM), are used to determine the response of the EM portion of the problem at a single frequency. Since only one frequency is solved at a time, it may take a long time to calculate the parameters for wideband devices. In this paper, a fast frequency sweep based on the Asymptotic Wave Expansion (AWE) method is developed and applied to generalized mixed circuit-EM problems. The AWE method, which was originally developed for lumped-loadmore » circuit simulations, has recently been shown to be effective at quasi-static and low frequency full-wave simulations. Here it is applied to a full-wave MoM solver, capable of solving for metals, dielectrics, and coupled circuit-EM problems.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elrod, D.C.; Turner, W.D.

TRUMP solves a general nonlinear parabolic partial differential equation describing flow in various kinds of potential fields, such as fields of temperature, pressure, or electricity and magnetism; simultaneously, it will solve two additional equations representing, in thermal problems, heat production by decomposition of two reactants having rate constants with a general Arrhenius temperature dependence. Steady-state and transient flow in one, two, or three dimensions are considered in geometrical configurations having simple or complex shapes and structures. Problem parameters may vary with spatial position, time, or primary dependent variables, temperature, pressure, or field strength. Initial conditions may vary with spatial position,more » and among the criteria that may be specified for ending a problem are upper and lower limits on the size of the primary dependent variable, upper limits on the problem time or on the number of time-steps or on the computer time, and attainment of steady state.« less

A General-Purpose Optimization Engine for Multi-Disciplinary Design Applications

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Hopkins, Dale A.; Berke, Laszlo

1996-01-01

A general purpose optimization tool for multidisciplinary applications, which in the literature is known as COMETBOARDS, is being developed at NASA Lewis Research Center. The modular organization of COMETBOARDS includes several analyzers and state-of-the-art optimization algorithms along with their cascading strategy. The code structure allows quick integration of new analyzers and optimizers. The COMETBOARDS code reads input information from a number of data files, formulates a design as a set of multidisciplinary nonlinear programming problems, and then solves the resulting problems. COMETBOARDS can be used to solve a large problem which can be defined through multiple disciplines, each of which can be further broken down into several subproblems. Alternatively, a small portion of a large problem can be optimized in an effort to improve an existing system. Some of the other unique features of COMETBOARDS include design variable formulation, constraint formulation, subproblem coupling strategy, global scaling technique, analysis approximation, use of either sequential or parallel computational modes, and so forth. The special features and unique strengths of COMETBOARDS assist convergence and reduce the amount of CPU time used to solve the difficult optimization problems of aerospace industries. COMETBOARDS has been successfully used to solve a number of problems, including structural design of space station components, design of nozzle components of an air-breathing engine, configuration design of subsonic and supersonic aircraft, mixed flow turbofan engines, wave rotor topped engines, and so forth. This paper introduces the COMETBOARDS design tool and its versatility, which is illustrated by citing examples from structures, aircraft design, and air-breathing propulsion engine design.

The Use of Efficient Broadcast Protocols in Asynchronous Distributed Systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Schmuck, Frank Bernhard

1988-01-01

Reliable broadcast protocols are important tools in distributed and fault-tolerant programming. They are useful for sharing information and for maintaining replicated data in a distributed system. However, a wide range of such protocols has been proposed. These protocols differ in their fault tolerance and delivery ordering characteristics. There is a tradeoff between the cost of a broadcast protocol and how much ordering it provides. It is, therefore, desirable to employ protocols that support only a low degree of ordering whenever possible. This dissertation presents techniques for deciding how strongly ordered a protocol is necessary to solve a given application problem. It is shown that there are two distinct classes of application problems: problems that can be solved with efficient, asynchronous protocols, and problems that require global ordering. The concept of a linearization function that maps partially ordered sets of events to totally ordered histories is introduced. How to construct an asynchronous implementation that solves a given problem if a linearization function for it can be found is shown. It is proved that in general the question of whether a problem has an asynchronous solution is undecidable. Hence there exists no general algorithm that would automatically construct a suitable linearization function for a given problem. Therefore, an important subclass of problems that have certain commutativity properties are considered. Techniques for constructing asynchronous implementations for this class are presented. These techniques are useful for constructing efficient asynchronous implementations for a broad range of practical problems.

Families Affected by Huntington's Disease Report Difficulties in Communication, Emotional Involvement, and Problem Solving.

PubMed

Jona, Celine M H; Labuschagne, Izelle; Mercieca, Emily-Clare; Fisher, Fiona; Gluyas, Cathy; Stout, Julie C; Andrews, Sophie C

2017-01-01

Family functioning in Huntington's disease (HD) is known from previous studies to be adversely affected. However, which aspects of family functioning are disrupted is unknown, limiting the empirical basis around which to create supportive interventions. The aim of the current study was to assess family functioning in HD families. We assessed family functioning in 61 participants (38 HD gene-expanded participants and 23 family members) using the McMaster Family Assessment Device (FAD; Epstein, Baldwin and Bishop, 1983), which provides scores for seven domains of functioning: Problem Solving; Communication; Affective Involvement; Affective Responsiveness; Behavior Control; Roles; and General Family Functioning. The most commonly reported disrupted domain for HD participants was Affective Involvement, which was reported by 39.5% of HD participants, followed closely by General Family Functioning (36.8%). For family members, the most commonly reported dysfunctional domains were Affective Involvement and Communication (both 52.2%). Furthermore, symptomatic HD participants reported more disruption to Problem Solving than pre-symptomatic HD participants. In terms of agreement between pre-symptomatic and symptomatic HD participants and their family members, all domains showed moderate to very good agreement. However, on average, family members rated Communication as more disrupted than their HD affected family member. These findings highlight the need to target areas of emotional engagement, communication skills and problem solving in family interventions in HD.

Families Affected by Huntington’s Disease Report Difficulties in Communication, Emotional Involvement, and Problem Solving

PubMed Central

Jona, Celine M.H.; Labuschagne, Izelle; Mercieca, Emily-Clare; Fisher, Fiona; Gluyas, Cathy; Stout, Julie C.; Andrews, Sophie C.

2017-01-01

Background: Family functioning in Huntington’s disease (HD) is known from previous studies to be adversely affected. However, which aspects of family functioning are disrupted is unknown, limiting the empirical basis around which to create supportive interventions. Objective: The aim of the current study was to assess family functioning in HD families. Methods: We assessed family functioning in 61 participants (38 HD gene-expanded participants and 23 family members) using the McMaster Family Assessment Device (FAD; Epstein, Baldwin and Bishop, 1983), which provides scores for seven domains of functioning: Problem Solving; Communication; Affective Involvement; Affective Responsiveness; Behavior Control; Roles; and General Family Functioning. Results: The most commonly reported disrupted domain for HD participants was Affective Involvement, which was reported by 39.5% of HD participants, followed closely by General Family Functioning (36.8%). For family members, the most commonly reported dysfunctional domains were Affective Involvement and Communication (both 52.2%). Furthermore, symptomatic HD participants reported more disruption to Problem Solving than pre-symptomatic HD participants. In terms of agreement between pre-symptomatic and symptomatic HD participants and their family members, all domains showed moderate to very good agreement. However, on average, family members rated Communication as more disrupted than their HD affected family member. Conclusion: These findings highlight the need to target areas of emotional engagement, communication skills and problem solving in family interventions in HD. PMID:28968240

Multiobjective optimization in a pseudometric objective space as applied to a general model of business activities

NASA Astrophysics Data System (ADS)

Khachaturov, R. V.

2016-09-01

It is shown that finding the equivalence set for solving multiobjective discrete optimization problems is advantageous over finding the set of Pareto optimal decisions. An example of a set of key parameters characterizing the economic efficiency of a commercial firm is proposed, and a mathematical model of its activities is constructed. In contrast to the classical problem of finding the maximum profit for any business, this study deals with a multiobjective optimization problem. A method for solving inverse multiobjective problems in a multidimensional pseudometric space is proposed for finding the best project of firm's activities. The solution of a particular problem of this type is presented.

Auxiliary principle technique and iterative algorithm for a perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems.

PubMed

Rahaman, Mijanur; Pang, Chin-Tzong; Ishtyak, Mohd; Ahmad, Rais

2017-01-01

In this article, we introduce a perturbed system of generalized mixed quasi-equilibrium-like problems involving multi-valued mappings in Hilbert spaces. To calculate the approximate solutions of the perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems, firstly we develop a perturbed system of auxiliary generalized multi-valued mixed quasi-equilibrium-like problems, and then by using the celebrated Fan-KKM technique, we establish the existence and uniqueness of solutions of the perturbed system of auxiliary generalized multi-valued mixed quasi-equilibrium-like problems. By deploying an auxiliary principle technique and an existence result, we formulate an iterative algorithm for solving the perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems. Lastly, we study the strong convergence analysis of the proposed iterative sequences under monotonicity and some mild conditions. These results are new and generalize some known results in this field.

PDE-based geophysical modelling using finite elements: examples from 3D resistivity and 2D magnetotellurics

NASA Astrophysics Data System (ADS)

Schaa, R.; Gross, L.; du Plessis, J.

2016-04-01

We present a general finite-element solver, escript, tailored to solve geophysical forward and inverse modeling problems in terms of partial differential equations (PDEs) with suitable boundary conditions. Escript’s abstract interface allows geoscientists to focus on solving the actual problem without being experts in numerical modeling. General-purpose finite element solvers have found wide use especially in engineering fields and find increasing application in the geophysical disciplines as these offer a single interface to tackle different geophysical problems. These solvers are useful for data interpretation and for research, but can also be a useful tool in educational settings. This paper serves as an introduction into PDE-based modeling with escript where we demonstrate in detail how escript is used to solve two different forward modeling problems from applied geophysics (3D DC resistivity and 2D magnetotellurics). Based on these two different cases, other geophysical modeling work can easily be realized. The escript package is implemented as a Python library and allows the solution of coupled, linear or non-linear, time-dependent PDEs. Parallel execution for both shared and distributed memory architectures is supported and can be used without modifications to the scripts.

A new weak Galerkin finite element method for elliptic interface problems

DOE PAGES

Mu, Lin; Wang, Junping; Ye, Xiu; ...

2016-08-26

We introduce and analyze a new weak Galerkin (WG) finite element method in this paper for solving second order elliptic equations with discontinuous coefficients and interfaces. Comparing with the existing WG algorithm for solving the same type problems, the present WG method has a simpler variational formulation and fewer unknowns. Moreover, the new WG algorithm allows the use of finite element partitions consisting of general polytopal meshes and can be easily generalized to high orders. Optimal order error estimates in both H1 and L2 norms are established for the present WG finite element solutions. We conducted extensive numerical experiments inmore » order to examine the accuracy, flexibility, and robustness of the proposed WG interface approach. In solving regular elliptic interface problems, high order convergences are numerically confirmed by using piecewise polynomial basis functions of high degrees. Moreover, the WG method is shown to be able to accommodate very complicated interfaces, due to its flexibility in choosing finite element partitions. Finally, in dealing with challenging problems with low regularities, the piecewise linear WG method is capable of delivering a second order of accuracy in L∞ norm for both C1 and H2 continuous solutions.« less

A new weak Galerkin finite element method for elliptic interface problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mu, Lin; Wang, Junping; Ye, Xiu

We introduce and analyze a new weak Galerkin (WG) finite element method in this paper for solving second order elliptic equations with discontinuous coefficients and interfaces. Comparing with the existing WG algorithm for solving the same type problems, the present WG method has a simpler variational formulation and fewer unknowns. Moreover, the new WG algorithm allows the use of finite element partitions consisting of general polytopal meshes and can be easily generalized to high orders. Optimal order error estimates in both H1 and L2 norms are established for the present WG finite element solutions. We conducted extensive numerical experiments inmore » order to examine the accuracy, flexibility, and robustness of the proposed WG interface approach. In solving regular elliptic interface problems, high order convergences are numerically confirmed by using piecewise polynomial basis functions of high degrees. Moreover, the WG method is shown to be able to accommodate very complicated interfaces, due to its flexibility in choosing finite element partitions. Finally, in dealing with challenging problems with low regularities, the piecewise linear WG method is capable of delivering a second order of accuracy in L∞ norm for both C1 and H2 continuous solutions.« less

Comparison of three newton-like nonlinear least-squares methods for estimating parameters of ground-water flow models

USGS Publications Warehouse

Cooley, R.L.; Hill, M.C.

1992-01-01

Three methods of solving nonlinear least-squares problems were compared for robustness and efficiency using a series of hypothetical and field problems. A modified Gauss-Newton/full Newton hybrid method (MGN/FN) and an analogous method for which part of the Hessian matrix was replaced by a quasi-Newton approximation (MGN/QN) solved some of the problems with appreciably fewer iterations than required using only a modified Gauss-Newton (MGN) method. In these problems, model nonlinearity and a large variance for the observed data apparently caused MGN to converge more slowly than MGN/FN or MGN/QN after the sum of squared errors had almost stabilized. Other problems were solved as efficiently with MGN as with MGN/FN or MGN/QN. Because MGN/FN can require significantly more computer time per iteration and more computer storage for transient problems, it is less attractive for a general purpose algorithm than MGN/QN.

Evaluation of a transfinite element numerical solution method for nonlinear heat transfer problems

NASA Technical Reports Server (NTRS)

Cerro, J. A.; Scotti, S. J.

1991-01-01

Laplace transform techniques have been widely used to solve linear, transient field problems. A transform-based algorithm enables calculation of the response at selected times of interest without the need for stepping in time as required by conventional time integration schemes. The elimination of time stepping can substantially reduce computer time when transform techniques are implemented in a numerical finite element program. The coupling of transform techniques with spatial discretization techniques such as the finite element method has resulted in what are known as transfinite element methods. Recently attempts have been made to extend the transfinite element method to solve nonlinear, transient field problems. This paper examines the theoretical basis and numerical implementation of one such algorithm, applied to nonlinear heat transfer problems. The problem is linearized and solved by requiring a numerical iteration at selected times of interest. While shown to be acceptable for weakly nonlinear problems, this algorithm is ineffective as a general nonlinear solution method.

Solving a novel confinement problem by spartaeine salticids that are predisposed to solve problems in the context of predation.

PubMed

Cross, Fiona R; Jackson, Robert R

2015-03-01

Intricate predatory strategies are widespread in the salticid subfamily Spartaeinae. The hypothesis we consider here is that the spartaeine species that are proficient at solving prey-capture problems are also proficient at solving novel problems. We used nine species from this subfamily in our experiments. Eight of these species (two Brettus, one Cocalus, three Cyrba, two Portia) are known for specialized invasion of other spiders' webs and for actively choosing other spiders as preferred prey ('araneophagy'). Except for Cocalus, these species also use trial and error to derive web-based signals with which they gain dynamic fine control of the resident spider's behaviour ('aggressive mimicry').The ninth species, Paracyrba wanlessi, is not araneophagic and instead specializes at preying on mosquitoes. We presented these nine species with a novel confinement problem that could be solved by trial and error. The test spider began each trial on an island in a tray of water, with an atoll surrounding the island. From the island, the spider could choose between two potential escape tactics (leap or swim), but we decided at random before the trial which tactic would fail and which tactic would achieve partial success. Our findings show that the seven aggressive-mimic species are proficient at solving the confinement problem by repeating 'correct' choices and by switching to the alternative tactic after making an 'incorrect' choice. However, as predicted, there was no evidence of C. gibbosus or P. wanlessi, the two non-aggressive-mimic species, solving the confinement problem. We discuss these findings in the context of an often-made distinction between domain-specific and domain-general cognition.

Structural design using equilibrium programming formulations

NASA Technical Reports Server (NTRS)

Scotti, Stephen J.

1995-01-01

Solutions to increasingly larger structural optimization problems are desired. However, computational resources are strained to meet this need. New methods will be required to solve increasingly larger problems. The present approaches to solving large-scale problems involve approximations for the constraints of structural optimization problems and/or decomposition of the problem into multiple subproblems that can be solved in parallel. An area of game theory, equilibrium programming (also known as noncooperative game theory), can be used to unify these existing approaches from a theoretical point of view (considering the existence and optimality of solutions), and be used as a framework for the development of new methods for solving large-scale optimization problems. Equilibrium programming theory is described, and existing design techniques such as fully stressed design and constraint approximations are shown to fit within its framework. Two new structural design formulations are also derived. The first new formulation is another approximation technique which is a general updating scheme for the sensitivity derivatives of design constraints. The second new formulation uses a substructure-based decomposition of the structure for analysis and sensitivity calculations. Significant computational benefits of the new formulations compared with a conventional method are demonstrated.

Autobiographical memory, interpersonal problem solving, and suicidal behavior in adolescent inpatients.

PubMed

Arie, Miri; Apter, Alan; Orbach, Israel; Yefet, Yael; Zalsman, Gil; Zalzman, Gil

2008-01-01

The aim of the study was to test Williams' (Williams JMG. Depression and the specificity of autobiographical memory. In: Rubin D, ed. Remembering Our Past: Studies in Autobiographical Memory. London: Cambridge University Press; 1996:244-267.) theory of suicidal behavior in adolescents and young adults by examining the relationship among suicidal behaviors, defective ability to retrieve specific autobiographical memories, impaired interpersonal problem solving, negative life events, repression, and hopelessness. Twenty-five suicidal adolescent and young adult inpatients (16.5 y +/- 2.5) were compared with 25 nonsuicidal adolescent and young adult inpatients (16.5 y +/- 2.5) and 25 healthy controls. Autobiographical memory was tested by a word association test; problem solving by the means-ends problem solving technique; negative life events by the Coddington scale; repression by the Life Style Index; hopelessness by the Beck scale; suicidal risk by the Plutchik scale, and suicide attempt by clinical history. Impairment in the ability to produce specific autobiographical memories, difficulties with interpersonal problem solving, negative life events, and repression were all associated with hopelessness and suicidal behavior. There were significant correlations among all the variables except for repression and negative life events. These findings support Williams' notion that generalized autobiographical memory is associated with deficits in interpersonal problem solving, negative life events, hopelessness, and suicidal behavior. The finding that defects in autobiographical memory are associated with suicidal behavior in adolescents and young adults may lead to improvements in the techniques of cognitive behavioral therapy in this age group.

Innovation and behavioral flexibility in wild redfronted lemurs (Eulemur rufifrons).

PubMed

Huebner, Franziska; Fichtel, Claudia

2015-05-01

Innovations and problem-solving abilities can provide animals with important ecological advantages as they allow individuals to deal with novel social and ecological challenges. Innovation is a solution to a novel problem or a novel solution to an old problem, with the latter being especially difficult. Finding a new solution to an old problem requires individuals to inhibit previously applied solutions to invent new strategies and to behave flexibly. We examined the role of experience on cognitive flexibility to innovate and to find new problem-solving solutions with an artificial feeding task in wild redfronted lemurs (Eulemur rufifrons). Four groups of lemurs were tested with feeding boxes, each offering three different techniques to extract food, with only one technique being available at a time. After the subjects learned a technique, this solution was no longer successful and subjects had to invent a new technique. For the first transition between task 1 and 2, subjects had to rely on their experience of the previous technique to solve task 2. For the second transition, subjects had to inhibit the previously learned technique to learn the new task 3. Tasks 1 and 2 were solved by most subjects, whereas task 3 was solved by only a few subjects. In this task, besides behavioral flexibility, especially persistence, i.e., constant trying, was important for individual success during innovation. Thus, wild strepsirrhine primates are able to innovate flexibly, suggesting a general ecological relevance of behavioral flexibility and persistence during innovation and problem solving across all primates.

Coping, problem solving, depression, and health-related quality of life in patients receiving outpatient stroke rehabilitation.

PubMed

Visser, Marieke M; Heijenbrok-Kal, Majanka H; Spijker, Adriaan Van't; Oostra, Kristine M; Busschbach, Jan J; Ribbers, Gerard M

2015-08-01

To investigate whether patients with high and low depression scores after stroke use different coping strategies and problem-solving skills and whether these variables are related to psychosocial health-related quality of life (HRQOL) independent of depression. Cross-sectional study. Two rehabilitation centers. Patients participating in outpatient stroke rehabilitation (N=166; mean age, 53.06±10.19y; 53% men; median time poststroke, 7.29mo). Not applicable. Coping strategy was measured using the Coping Inventory for Stressful Situations; problem-solving skills were measured using the Social Problem Solving Inventory-Revised: Short Form; depression was assessed using the Center for Epidemiologic Studies Depression Scale; and HRQOL was measured using the five-level EuroQol five-dimensional questionnaire and the Stroke-Specific Quality of Life Scale. Independent samples t tests and multivariable regression analyses, adjusted for patient characteristics, were performed. Compared with patients with low depression scores, patients with high depression scores used less positive problem orientation (P=.002) and emotion-oriented coping (P<.001) and more negative problem orientation (P<.001) and avoidance style (P<.001). Depression score was related to all domains of both general HRQOL (visual analog scale: β=-.679; P<.001; utility: β=-.009; P<.001) and stroke-specific HRQOL (physical HRQOL: β=-.020; P=.001; psychosocial HRQOL: β=-.054, P<.001; total HRQOL: β=-.037; P<.001). Positive problem orientation was independently related to psychosocial HRQOL (β=.086; P=.018) and total HRQOL (β=.058; P=.031). Patients with high depression scores use different coping strategies and problem-solving skills than do patients with low depression scores. Independent of depression, positive problem-solving skills appear to be most significantly related to better HRQOL. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

An extension of the QZ algorithm for solving the generalized matrix eigenvalue problem

NASA Technical Reports Server (NTRS)

Ward, R. C.

1973-01-01

This algorithm is an extension of Moler and Stewart's QZ algorithm with some added features for saving time and operations. Also, some additional properties of the QR algorithm which were not practical to implement in the QZ algorithm can be generalized with the combination shift QZ algorithm. Numerous test cases are presented to give practical application tests for algorithm. Based on results, this algorithm should be preferred over existing algorithms which attempt to solve the class of generalized eigenproblems where both matrices are singular or nearly singular.

A numerical scheme to solve unstable boundary value problems

NASA Technical Reports Server (NTRS)

Kalnay Derivas, E.

1975-01-01

A new iterative scheme for solving boundary value problems is presented. It consists of the introduction of an artificial time dependence into a modified version of the system of equations. Then explicit forward integrations in time are followed by explicit integrations backwards in time. The method converges under much more general conditions than schemes based in forward time integrations (false transient schemes). In particular it can attain a steady state solution of an elliptical system of equations even if the solution is unstable, in which case other iterative schemes fail to converge. The simplicity of its use makes it attractive for solving large systems of nonlinear equations.

Rule-governed Approaches to Physics--Newton's Third Law.

ERIC Educational Resources Information Center

Maloney, David P.

1984-01-01

Describes an approach to assessing the use of rules in solving problems related to Newton's third law of motion. Discusses the problems used, method of questioning, scoring of problem sets, and a general overview of the use of the technique in aiding the teacher in dealing with student's conceptual levels. (JM)

Turning Muddy Problems into Clear Solutions

ERIC Educational Resources Information Center

Neil, Thomas C.

1975-01-01

Author discusses some aspects of counseling process. Makes suggestions of how to sift through maze of distractions and generalizations counselees present as problems and how to change latter into concrete statements that reflect their true nature and indicate how to resolve them. Finally, author describes strategies that help solve problems. (SE)

Solution Strategies for Constant Acceleration Problems

ERIC Educational Resources Information Center

Wheaton, S. M.; Binder, P.-M.

2017-01-01

We discuss strategies for the general solution of single-step 1D constant acceleration problems. In a slightly restricted form, these problems have five variables (?"x," "v[subscript 0]," "v," "a" and "t") and two independent equations, so three variables must be given to solve for the other two,…

A Problem on Optimal Transportation

ERIC Educational Resources Information Center

Cechlarova, Katarina

2005-01-01

Mathematical optimization problems are not typical in the classical curriculum of mathematics. In this paper we show how several generalizations of an easy problem on optimal transportation were solved by gifted secondary school pupils in a correspondence mathematical seminar, how they can be used in university courses of linear programming and…

How Students Process Equations in Solving Quantitative Synthesis Problems? Role of Mathematical Complexity in Students' Mathematical Performance

ERIC Educational Resources Information Center

Ibrahim, Bashirah; Ding, Lin; Heckler, Andrew F.; White, Daniel R.; Badeau, Ryan

2017-01-01

We examine students' mathematical performance on quantitative "synthesis problems" with varying mathematical complexity. Synthesis problems are tasks comprising multiple concepts typically taught in different chapters. Mathematical performance refers to the formulation, combination, and simplification of equations. Generally speaking,…

Afterthoughts, or What to Do?

ERIC Educational Resources Information Center

Connell, David B.

1982-01-01

General systems theory provides a theoretical framework for understanding stress and formulating problem-solving strategies. Both individuals and schools are systems, and general systems theory enables one to ask whether they are operating harmoniously and communicating effectively. (Author/RW)

Increasing mathematical problem-solving performance through relaxation training

NASA Astrophysics Data System (ADS)

Sharp, Conni; Coltharp, Hazel; Hurford, David; Cole, Amykay

2000-04-01

Two intact classes of 30 undergraduate students enrolled in the same general education mathematics course were each administered the IPSP Mathematics Problem Solving Test and the Mathematics Anxiety Rating Scale at the beginning and end of the semester. Both groups experienced the same syllabus, lectures, course requirements, and assessment techniques; however, one group received relaxation training during an initial class meeting and during the first 5 to 7 minutes of each subsequent class. The group which had received relaxation training had significantly lower mathematics anxiety and significantly higher mathematics performance at the end of the course. The results suggest that relaxation training may be a useful tool for treating anxiety in undergraduate general education mathematics students.

HEAP: Heat Energy Analysis Program, a computer model simulating solar receivers. [solving the heat transfer problem

NASA Technical Reports Server (NTRS)

Lansing, F. L.

1979-01-01

A computer program which can distinguish between different receiver designs, and predict transient performance under variable solar flux, or ambient temperatures, etc. has a basic structure that fits a general heat transfer problem, but with specific features that are custom-made for solar receivers. The code is written in MBASIC computer language. The methodology followed in solving the heat transfer problem is explained. A program flow chart, an explanation of input and output tables, and an example of the simulation of a cavity-type solar receiver are included.

Cost effective campaigning in social networks

NASA Astrophysics Data System (ADS)

Kotnis, Bhushan; Kuri, Joy

2016-05-01

Campaigners are increasingly using online social networking platforms for promoting products, ideas and information. A popular method of promoting a product or even an idea is incentivizing individuals to evangelize the idea vigorously by providing them with referral rewards in the form of discounts, cash backs, or social recognition. Due to budget constraints on scarce resources such as money and manpower, it may not be possible to provide incentives for the entire population, and hence incentives need to be allocated judiciously to appropriate individuals for ensuring the highest possible outreach size. We aim to do the same by formulating and solving an optimization problem using percolation theory. In particular, we compute the set of individuals that are provided incentives for minimizing the expected cost while ensuring a given outreach size. We also solve the problem of computing the set of individuals to be incentivized for maximizing the outreach size for given cost budget. The optimization problem turns out to be non trivial; it involves quantities that need to be computed by numerically solving a fixed point equation. Our primary contribution is, that for a fairly general cost structure, we show that the optimization problems can be solved by solving a simple linear program. We believe that our approach of using percolation theory to formulate an optimization problem is the first of its kind.

Students’ conceptions and problem-solving ability on topic chemical thermodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diawati, Chansyanah, E-mail: chansyanahd@yahoo.com

The enthalpy concept and its change were introduced to describe the forms of internal energy transfer in chemical reactions. Likewise, the concepts of exothermic and endothermic reactions introduced as a consequence of heat transfer form. In the heat measurement process at constant pressure, work is often ignored. The exothermic or endothermic reactions, usually only based on the increase or decrease of the reaction temperature, without associated with the internal energy. Depictions of enthalpy and its change assumed closely related to students’ problem-solving ability. Therefore, the study to describe pre-service chemistry teacher student’s conceptions and problem-solving ability on topic chemical thermodynamicsmore » has been done. This research was a case study of chemical education course in Provinsi Lampung. The subjects of this study were 42 students who attend the chemical thermodynamics course. Questions about exothermic and endothermic reactions, enthalpy and its change, as well as internal energy and its change were given in the form of an essay exam questions. Answers related to conception qualitatively categorized, while problem solving answers were scored and assessed. The results showed that, in general, students were having problems in enthalpy and describe the changes in the form of heat and work. The highest value of problem solving ability obtained 26.67 from the maximum value of 100. The lowest value was 0, and the average value was 14.73. These results show that the problem-solving ability of pre-service chemistry teacher students was low. The results provide insight to researchers, and educators to develop learning or lab work on this concept.« less

Emotional intensity reduces later generalized anxiety disorder symptoms when fear of anxiety and negative problem-solving appraisal are low.

PubMed

Sugiura, Yoshinori; Sugiura, Tomoko

2015-08-01

While research based on the emotion dysregulation model indicates a positive relationship between intense emotions and generalized anxiety disorder (GAD) symptoms, emotion-focused intervention involves the use of techniques to enhance emotional experiences, based on the notion that GAD patients are engaging in avoidance strategies. To reveal the conditions under which intense emotions lead to reduced GAD symptoms, we designed a longitudinal study to monitor changes in GAD symptoms among students (N = 129) over 3 months. Our focus was on possible moderators of the effect of emotional intensity. Results indicated that when fear of emotions and negative appraisals about problem solving were low, negative emotional intensity reduced later GAD symptoms. Moreover, under the condition of high responsibility to continue thinking, emotional intensity tended to reduce later GAD symptoms. Results suggest that reduced fear of emotions and reduced negative appraisals about problem solving may enhance the use of emotional processing techniques (e.g., emotional exposure). The interaction between responsibility to continue thinking and emotional intensity requires further examination. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

An Investigation of Generalized Differential Evolution Metaheuristic for Multiobjective Optimal Crop-Mix Planning Decision

PubMed Central

Olugbara, Oludayo

2014-01-01

This paper presents an annual multiobjective crop-mix planning as a problem of concurrent maximization of net profit and maximization of crop production to determine an optimal cropping pattern. The optimal crop production in a particular planting season is a crucial decision making task from the perspectives of economic management and sustainable agriculture. A multiobjective optimal crop-mix problem is formulated and solved using the generalized differential evolution 3 (GDE3) metaheuristic to generate a globally optimal solution. The performance of the GDE3 metaheuristic is investigated by comparing its results with the results obtained using epsilon constrained and nondominated sorting genetic algorithms—being two representatives of state-of-the-art in evolutionary optimization. The performance metrics of additive epsilon, generational distance, inverted generational distance, and spacing are considered to establish the comparability. In addition, a graphical comparison with respect to the true Pareto front for the multiobjective optimal crop-mix planning problem is presented. Empirical results generally show GDE3 to be a viable alternative tool for solving a multiobjective optimal crop-mix planning problem. PMID:24883369

An investigation of generalized differential evolution metaheuristic for multiobjective optimal crop-mix planning decision.

PubMed

Adekanmbi, Oluwole; Olugbara, Oludayo; Adeyemo, Josiah

2014-01-01

This paper presents an annual multiobjective crop-mix planning as a problem of concurrent maximization of net profit and maximization of crop production to determine an optimal cropping pattern. The optimal crop production in a particular planting season is a crucial decision making task from the perspectives of economic management and sustainable agriculture. A multiobjective optimal crop-mix problem is formulated and solved using the generalized differential evolution 3 (GDE3) metaheuristic to generate a globally optimal solution. The performance of the GDE3 metaheuristic is investigated by comparing its results with the results obtained using epsilon constrained and nondominated sorting genetic algorithms-being two representatives of state-of-the-art in evolutionary optimization. The performance metrics of additive epsilon, generational distance, inverted generational distance, and spacing are considered to establish the comparability. In addition, a graphical comparison with respect to the true Pareto front for the multiobjective optimal crop-mix planning problem is presented. Empirical results generally show GDE3 to be a viable alternative tool for solving a multiobjective optimal crop-mix planning problem.

Can I cut the Gordian tnok? The impact of pronounceability, actual solvability, and length on intuitive problem assessments of anagrams.

PubMed

Topolinski, Sascha; Bakhtiari, Giti; Erle, Thorsten M

2016-01-01

When assessing a problem, many cues can be used to predict solvability and solving effort. Some of these cues, however, can be misleading. The present approach shows that a feature of a problem that is actually related to solving difficulty is used as a cue for solving ease when assessing the problem in the first place. For anagrams, it is an established effect that easy-to-pronounce anagrams (e.g., NOGAL) take more time to being solved than hard-to-pronounce anagrams (e.g., HNWEI). However, when assessing an anagram in the first place, individuals use the feature of pronounceability to predict solving ease, because pronounceability is an instantiation of the general mechanism of processing fluency. Participants (total N=536) received short and long anagrams and nonanagrams and judged solvability and solving ease intuitively without actually solving the items. Easy-to-pronounce letter strings were more frequently judged as being solvable than hard-to-pronounce letters strings (Experiment 1), and were estimated to require less effort (Experiments 2, 4-7) and time to be solved (Experiment 3). This effect was robust for short and long items, anagrams and nonanagrams, and presentation timings from 4 down to 0.5s, and affected novices and experts alike. Spontaneous solutions did not mediate this effect. Participants were sensitive to actual solvability even for long anagrams (6-11 letters long) presented only for 500 ms. Copyright © 2015 Elsevier B.V. All rights reserved.

Toward Modeling the Intrinsic Complexity of Test Problems

ERIC Educational Resources Information Center

Shoufan, Abdulhadi

2017-01-01

The concept of intrinsic complexity explains why different problems of the same type, tackled by the same problem solver, can require different times to solve and yield solutions of different quality. This paper proposes a general four-step approach that can be used to establish a model for the intrinsic complexity of a problem class in terms of…

Table-sized matrix model in fractional learning

NASA Astrophysics Data System (ADS)

Soebagyo, J.; Wahyudin; Mulyaning, E. C.

2018-05-01

This article provides an explanation of the fractional learning model i.e. a Table-Sized Matrix model in which fractional representation and its operations are symbolized by the matrix. The Table-Sized Matrix are employed to develop problem solving capabilities as well as the area model. The Table-Sized Matrix model referred to in this article is used to develop an understanding of the fractional concept to elementary school students which can then be generalized into procedural fluency (algorithm) in solving the fractional problem and its operation.

On the efficacy of stochastic collocation, stochastic Galerkin, and stochastic reduced order models for solving stochastic problems

DOE PAGES

Richard V. Field, Jr.; Emery, John M.; Grigoriu, Mircea Dan

2015-05-19

The stochastic collocation (SC) and stochastic Galerkin (SG) methods are two well-established and successful approaches for solving general stochastic problems. A recently developed method based on stochastic reduced order models (SROMs) can also be used. Herein we provide a comparison of the three methods for some numerical examples; our evaluation only holds for the examples considered in the paper. The purpose of the comparisons is not to criticize the SC or SG methods, which have proven very useful for a broad range of applications, nor is it to provide overall ratings of these methods as compared to the SROM method.more » Furthermore, our objectives are to present the SROM method as an alternative approach to solving stochastic problems and provide information on the computational effort required by the implementation of each method, while simultaneously assessing their performance for a collection of specific problems.« less

Contact and crack problems for an elastic wedge. [stress concentration in elastic half spaces

NASA Technical Reports Server (NTRS)

Erdogan, F.; Gupta, G. D.

1974-01-01

The contact and the crack problems for an elastic wedge of arbitrary angle are considered. The problem is reduced to a singular integral equation which, in the general case, may have a generalized Cauchy kernel. The singularities under the stamp as well as at the wedge apex were studied, and the relevant stress intensity factors are defined. The problem was solved for various wedge geometries and loading conditions. The results may be applicable to certain foundation problems and to crack problems in symmetrically loaded wedges in which cracks initiate from the apex.

Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

PubMed

Yang, S; Wang, D

2000-01-01

This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.

Insightful problem solving in an Asian elephant.

PubMed

Foerder, Preston; Galloway, Marie; Barthel, Tony; Moore, Donald E; Reiss, Diana

2011-01-01

The "aha" moment or the sudden arrival of the solution to a problem is a common human experience. Spontaneous problem solving without evident trial and error behavior in humans and other animals has been referred to as insight. Surprisingly, elephants, thought to be highly intelligent, have failed to exhibit insightful problem solving in previous cognitive studies. We tested whether three Asian elephants (Elephas maximus) would use sticks or other objects to obtain food items placed out-of-reach and overhead. Without prior trial and error behavior, a 7-year-old male Asian elephant showed spontaneous problem solving by moving a large plastic cube, on which he then stood, to acquire the food. In further testing he showed behavioral flexibility, using this technique to reach other items and retrieving the cube from various locations to use as a tool to acquire food. In the cube's absence, he generalized this tool utilization technique to other objects and, when given smaller objects, stacked them in an attempt to reach the food. The elephant's overall behavior was consistent with the definition of insightful problem solving. Previous failures to demonstrate this ability in elephants may have resulted not from a lack of cognitive ability but from the presentation of tasks requiring trunk-held sticks as potential tools, thereby interfering with the trunk's use as a sensory organ to locate the targeted food.

Closed loop problems in biomechanics. Part II--an optimization approach.

PubMed

Vaughan, C L; Hay, J G; Andrews, J G

1982-01-01

A closed loop problem in biomechanics may be defined as a problem in which there are one or more closed loops formed by the human body in contact with itself or with an external system. Under certain conditions the problem is indeterminate--the unknown forces and torques outnumber the equations. Force transducing devices, which would help solve this problem, have serious drawbacks, and existing methods are inaccurate and non-general. The purposes of the present paper are (1) to develop a general procedure for solving closed loop problems; (2) to illustrate the application of the procedure; and (3) to examine the validity of the procedure. A mathematical optimization approach is applied to the solution of three different closed loop problems--walking up stairs, vertical jumping and cartwheeling. The following conclusions are drawn: (1) the method described is reasonably successful for predicting horizontal and vertical reaction forces at the distal segments although problems exist for predicting the points of application of these forces; (2) the results provide some support for the notion that the human neuromuscular mechanism attempts to minimize the joint torques and thus, to a certain degree, the amount of muscular effort; (3) in the validation procedure it is desirable to have a force device for each of the distal segments in contact with a fixed external system; and (4) the method is sufficiently general to be applied to all classes of closed loop problems.

Fast, Nonlinear, Fully Probabilistic Inversion of Large Geophysical Problems

NASA Astrophysics Data System (ADS)

Curtis, A.; Shahraeeni, M.; Trampert, J.; Meier, U.; Cho, G.

2010-12-01

Almost all Geophysical inverse problems are in reality nonlinear. Fully nonlinear inversion including non-approximated physics, and solving for probability distribution functions (pdf’s) that describe the solution uncertainty, generally requires sampling-based Monte-Carlo style methods that are computationally intractable in most large problems. In order to solve such problems, physical relationships are usually linearized leading to efficiently-solved, (possibly iterated) linear inverse problems. However, it is well known that linearization can lead to erroneous solutions, and in particular to overly optimistic uncertainty estimates. What is needed across many Geophysical disciplines is a method to invert large inverse problems (or potentially tens of thousands of small inverse problems) fully probabilistically and without linearization. This talk shows how very large nonlinear inverse problems can be solved fully probabilistically and incorporating any available prior information using mixture density networks (driven by neural network banks), provided the problem can be decomposed into many small inverse problems. In this talk I will explain the methodology, compare multi-dimensional pdf inversion results to full Monte Carlo solutions, and illustrate the method with two applications: first, inverting surface wave group and phase velocities for a fully-probabilistic global tomography model of the Earth’s crust and mantle, and second inverting industrial 3D seismic data for petrophysical properties throughout and around a subsurface hydrocarbon reservoir. The latter problem is typically decomposed into 104 to 105 individual inverse problems, each solved fully probabilistically and without linearization. The results in both cases are sufficiently close to the Monte Carlo solution to exhibit realistic uncertainty, multimodality and bias. This provides far greater confidence in the results, and in decisions made on their basis.

Doctoral training in behavior analysis: Training generalized problem-solving skills

PubMed Central

Chase, Philip N.; Wylie, Ruth G.

1985-01-01

This essay provides guidelines for designing a doctoral program in behavior analysis. First, we propose a general accomplishment for all behavior analytic doctoral students: that they be able to solve problems concerning individual behavior within a range of environments. Second, in order to achieve this goal, we propose that students be trained in conceptual and experimental analysis of behavior, the application of behavioral principles and the administration of behavioral programs. This training should include class work, but it should emphasize the immersion of students in a variety of environments in which they are required to use behavior analytic strategies. Third, we provide an example of a hypothetical graduate program that involves the proposed training. Finally, an evaluation plan is suggested for determining whether a training program is in fact producing students who are generalized problem-solvers. At each step, we justify our point of view from a perspective that combines principles from behavior analysis and educational systems design. PMID:22478633

Working with low back pain: problem-solving orientation and function.

PubMed

Shaw, W S; Feuerstein, M; Haufler, A J; Berkowitz, S M; Lopez, M S

2001-08-01

A number of ergonomic, workplace and individual psychosocial factors and health behaviors have been associated with the onset, exacerbation and/or maintenance of low back pain (LBP). The functional impact of these factors may be influenced by how a worker approaches problems in general. The present study was conducted to determine whether problem-solving orientation was associated with physical and mental health outcomes in fully employed workers (soldiers) reporting a history of LBP in the past year. The sample consisted of 475 soldiers (446 male, 29 female; mean age 24.5 years) who worked in jobs identified as high risk for LBP-related disability and reported LBP symptoms in the past 12 months. The Social Problem-Solving Inventory and the Standard Form-12 (SF-12) were completed by all subjects. Hierarchical multiple regression analyses were used to predict the SF-12 physical health summary scale from interactions of LBP symptoms with each of five problem-solving subscales. Low scores on positive problem-solving orientation (F(1,457)=4.49), and high scores on impulsivity/carelessness (F(1,457)=9.11) were associated with a steeper gradient in functional loss related to LBP. Among those with a longer history of low-grade LBP, an avoidant approach to problem-solving was also associated with a steeper gradient of functional loss (three-way interaction; F(1,458)=4.58). These results suggest that the prolonged impact of LBP on daily function may be reduced by assisting affected workers to conceptualize LBP as a problem that can be overcome and using strategies that promote taking an active role in reducing risks for LBP. Secondary prevention efforts may be improved by addressing these factors.

A weak Galerkin generalized multiscale finite element method

DOE PAGES

Mu, Lin; Wang, Junping; Ye, Xiu

2016-03-31

In this study, we propose a general framework for weak Galerkin generalized multiscale (WG-GMS) finite element method for the elliptic problems with rapidly oscillating or high contrast coefficients. This general WG-GMS method features in high order accuracy on general meshes and can work with multiscale basis derived by different numerical schemes. A special case is studied under this WG-GMS framework in which the multiscale basis functions are obtained by solving local problem with the weak Galerkin finite element method. Convergence analysis and numerical experiments are obtained for the special case.

A weak Galerkin generalized multiscale finite element method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mu, Lin; Wang, Junping; Ye, Xiu

In this study, we propose a general framework for weak Galerkin generalized multiscale (WG-GMS) finite element method for the elliptic problems with rapidly oscillating or high contrast coefficients. This general WG-GMS method features in high order accuracy on general meshes and can work with multiscale basis derived by different numerical schemes. A special case is studied under this WG-GMS framework in which the multiscale basis functions are obtained by solving local problem with the weak Galerkin finite element method. Convergence analysis and numerical experiments are obtained for the special case.

Problem Solving in Physics: Undergraduates' Framing, Procedures, and Decision Making

NASA Astrophysics Data System (ADS)

Modir, Bahar

In this dissertation I will start with the broad research question of what does problem solving in upper division physics look like? My focus in this study is on students' problem solving in physics theory courses. Some mathematical formalisms are common across all physics core courses such as using the process of separation of variables, doing Taylor series, or using the orthogonality properties of mathematical functions to set terms equal to zero. However, there are slight differences in their use of these mathematical formalisms across different courses, possibly because of how students map different physical systems to these processes. Thus, my first main research question aims to answer how students perform these recurring processes across upper division physics courses. I break this broad question into three particular research questions: What knowledge pieces do students use to make connections between physics and procedural math? How do students use their knowledge pieces coherently to provide reasoning strategies in estimation problems? How do students look ahead into the problem to read the information out of the physical scenario to align their use of math in physics? Building on the previous body of the literature, I will use the theory family of Knowledge in Pieces and provide evidence to expand this theoretical foundation. I will compare my study with previous studies and provide suggestions on how to generalize these theory expansions for future use. My experimental data mostly come from video-based classroom data. Students in groups of 2-4 students solve in-class problems in quantum mechanics and electromagnetic fields 1 courses collaboratively. In addition, I will analyze clinical interviews to demonstrate how a single case study student plays an epistemic game to estimate the total energy in a hurricane. My second research question is more focused on a particular instructional context. How do students frame problem solving in quantum mechanics? I will lay out a new theoretical framework based in epistemic framing that separates the problem solving space into four frames divided along two axes. The first axis models students' framing in math and physics, expanded through the second axis of conceptual problem solving and algorithmic problem solving. I use this framework to show how students navigate problem solving. Lastly, I will use this developed framework to interpret existing difficulties in quantum mechanics.

Problems and solutions for patients with fibromyalgia: Building new helping relationships.

PubMed

Montesó-Curto, Pilar; García-Martinez, Montserrat; Romaguera, Sara; Mateu, María Luisa; Cubí-Guillén, María Teresa; Sarrió-Colas, Lidia; Llàdser, Anna Núria; Bradley, Stephen; Panisello-Chavarria, María Luisa

2018-02-01

The aim of this study was to identify the main biological, psychological and sociological problems and potential solutions for patients diagnosed with fibromyalgia by use of Group Problem-Solving Therapy. Group Problem-Solving Therapy is a technique for identifying and solving problems, increasing assertiveness, self-esteem and eliminating negative thoughts. Qualitative phenomenological interpretive design: Group Problem-Solving Therapy sessions conducted with patients suffering fibromyalgia were studied; participants recruited via the Rheumatology Department at a general hospital and associations in Catalonia, Spain with sessions conducted in nearby university setting. The study included 44 people diagnosed with fibromyalgia (43 female, 1 male) from 6 Group Problem-Solving Therapy sessions. Data collected from March-June 2013. A total of 24 sessions were audio recorded, all with prior informed consent. Data were transcribed and then analysed in accordance with established methods of inductive thematic analysis, via a process of reduction to manage and classify data. Five themes were identified: (1) Current problems are often related to historical trauma; (2) There are no "one size fits all" solutions; (3) Fibromyalgia is life-changing; (4) Fibromyalgia is widely misunderstood; (5) Statistically Significant impacts on physical, psychological and social are described. The majority of patients' problems were associated with their previous history and the onset of fibromyalgia; which may be related to trauma in adolescence, early adulthood or later. The solutions provided during the groups appeared to be accepted by the participants. These findings can improve the self-management of fibromyalgia patients by helping to enhance adaptive behaviours and incorporating the female gender approach. © 2017 John Wiley & Sons Ltd.

Linear solver performance in elastoplastic problem solution on GPU cluster

NASA Astrophysics Data System (ADS)

Khalevitsky, Yu. V.; Konovalov, A. V.; Burmasheva, N. V.; Partin, A. S.

2017-12-01

Applying the finite element method to severe plastic deformation problems involves solving linear equation systems. While the solution procedure is relatively hard to parallelize and computationally intensive by itself, a long series of large scale systems need to be solved for each problem. When dealing with fine computational meshes, such as in the simulations of three-dimensional metal matrix composite microvolume deformation, tens and hundreds of hours may be needed to complete the whole solution procedure, even using modern supercomputers. In general, one of the preconditioned Krylov subspace methods is used in a linear solver for such problems. The method convergence highly depends on the operator spectrum of a problem stiffness matrix. In order to choose the appropriate method, a series of computational experiments is used. Different methods may be preferable for different computational systems for the same problem. In this paper we present experimental data obtained by solving linear equation systems from an elastoplastic problem on a GPU cluster. The data can be used to substantiate the choice of the appropriate method for a linear solver to use in severe plastic deformation simulations.

A taxonomy of inductive problems.

PubMed

Kemp, Charles; Jern, Alan

2014-02-01

Inductive inferences about objects, features, categories, and relations have been studied for many years, but there are few attempts to chart the range of inductive problems that humans are able to solve. We present a taxonomy of inductive problems that helps to clarify the relationships between familiar inductive problems such as generalization, categorization, and identification, and that introduces new inductive problems for psychological investigation. Our taxonomy is founded on the idea that semantic knowledge is organized into systems of objects, features, categories, and relations, and we attempt to characterize all of the inductive problems that can arise when these systems are partially observed. Recent studies have begun to address some of the new problems in our taxonomy, and future work should aim to develop unified theories of inductive reasoning that explain how people solve all of the problems in the taxonomy.

New algorithms for solving third- and fifth-order two point boundary value problems based on nonsymmetric generalized Jacobi Petrov–Galerkin method

PubMed Central

Doha, E.H.; Abd-Elhameed, W.M.; Youssri, Y.H.

2014-01-01

Two families of certain nonsymmetric generalized Jacobi polynomials with negative integer indexes are employed for solving third- and fifth-order two point boundary value problems governed by homogeneous and nonhomogeneous boundary conditions using a dual Petrov–Galerkin method. The idea behind our method is to use trial functions satisfying the underlying boundary conditions of the differential equations and the test functions satisfying the dual boundary conditions. The resulting linear systems from the application of our method are specially structured and they can be efficiently inverted. The use of generalized Jacobi polynomials simplify the theoretical and numerical analysis of the method and also leads to accurate and efficient numerical algorithms. The presented numerical results indicate that the proposed numerical algorithms are reliable and very efficient. PMID:26425358

Do New Caledonian crows solve physical problems through causal reasoning?

PubMed Central

Taylor, A.H.; Hunt, G.R.; Medina, F.S.; Gray, R.D.

2008-01-01

The extent to which animals other than humans can reason about physical problems is contentious. The benchmark test for this ability has been the trap-tube task. We presented New Caledonian crows with a series of two-trap versions of this problem. Three out of six crows solved the initial trap-tube. These crows continued to avoid the trap when the arbitrary features that had previously been associated with successful performances were removed. However, they did not avoid the trap when a hole and a functional trap were in the tube. In contrast to a recent primate study, the three crows then solved a causally equivalent but visually distinct problem—the trap-table task. The performance of the three crows across the four transfers made explanations based on chance, associative learning, visual and tactile generalization, and previous dispositions unlikely. Our findings suggest that New Caledonian crows can solve complex physical problems by reasoning both causally and analogically about causal relations. Causal and analogical reasoning may form the basis of the New Caledonian crow's exceptional tool skills. PMID:18796393

Schizotypy and Performance on an Insight Problem-Solving Task: The Contribution of Persecutory Ideation.

PubMed

Cosgrave, Jan; Haines, Ross; Golodetz, Stuart; Claridge, Gordon; Wulff, Katharina; van Heugten-van der Kloet, Dalena

2018-01-01

Insight problem solving is thought to underpin creative thought as it incorporates both divergent (generating multiple ideas and solutions) and convergent (arriving at the optimal solution) thinking approaches. The current literature on schizotypy and creativity is mixed and requires clarification. An alternate approach was employed by designing an exploratory web-based study using only correlates of schizotypal traits (paranoia, dissociation, cognitive failures, fantasy proneness, and unusual sleep experiences) and examining which (if any) predicted optimal performance on an insight problem-solving task. One hundred and twenty-one participants were recruited online from the general population and completed the number reduction task. The discovery of the hidden rule (HR) was used as a measure of insight. Multivariate logistic regression analyses highlighted persecutory ideation to best predict the discovery of the HR (OR = 1.05; 95% CI 1.01-1.10, p = 0.017), with a one-point increase in persecutory ideas corresponding to the participant being 5% more likely to discover the HR. This result suggests that persecutory ideation, above other schizotypy correlates, may be involved in insight problem solving.

Summer Proceedings 2016: The Center for Computing Research at Sandia National Laboratories

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carleton, James Brian; Parks, Michael L.

Solving sparse linear systems from the discretization of elliptic partial differential equations (PDEs) is an important building block in many engineering applications. Sparse direct solvers can solve general linear systems, but are usually slower and use much more memory than effective iterative solvers. To overcome these two disadvantages, a hierarchical solver (LoRaSp) based on H2-matrices was introduced in [22]. Here, we have developed a parallel version of the algorithm in LoRaSp to solve large sparse matrices on distributed memory machines. On a single processor, the factorization time of our parallel solver scales almost linearly with the problem size for three-dimensionalmore » problems, as opposed to the quadratic scalability of many existing sparse direct solvers. Moreover, our solver leads to almost constant numbers of iterations, when used as a preconditioner for Poisson problems. On more than one processor, our algorithm has significant speedups compared to sequential runs. With this parallel algorithm, we are able to solve large problems much faster than many existing packages as demonstrated by the numerical experiments.« less

Solving the Swath Segment Selection Problem

NASA Technical Reports Server (NTRS)

Knight, Russell; Smith, Benjamin

2006-01-01

Several artificial-intelligence search techniques have been tested as means of solving the swath segment selection problem (SSSP) -- a real-world problem that is not only of interest in its own right, but is also useful as a test bed for search techniques in general. In simplest terms, the SSSP is the problem of scheduling the observation times of an airborne or spaceborne synthetic-aperture radar (SAR) system to effect the maximum coverage of a specified area (denoted the target), given a schedule of downlinks (opportunities for radio transmission of SAR scan data to a ground station), given the limit on the quantity of SAR scan data that can be stored in an onboard memory between downlink opportunities, and given the limit on the achievable downlink data rate. The SSSP is NP complete (short for "nondeterministic polynomial time complete" -- characteristic of a class of intractable problems that can be solved only by use of computers capable of making guesses and then checking the guesses in polynomial time).

Solving Quantum Ground-State Problems with Nuclear Magnetic Resonance

PubMed Central

Li, Zhaokai; Yung, Man-Hong; Chen, Hongwei; Lu, Dawei; Whitfield, James D.; Peng, Xinhua; Aspuru-Guzik, Alán; Du, Jiangfeng

2011-01-01

Quantum ground-state problems are computationally hard problems for general many-body Hamiltonians; there is no classical or quantum algorithm known to be able to solve them efficiently. Nevertheless, if a trial wavefunction approximating the ground state is available, as often happens for many problems in physics and chemistry, a quantum computer could employ this trial wavefunction to project the ground state by means of the phase estimation algorithm (PEA). We performed an experimental realization of this idea by implementing a variational-wavefunction approach to solve the ground-state problem of the Heisenberg spin model with an NMR quantum simulator. Our iterative phase estimation procedure yields a high accuracy for the eigenenergies (to the 10−5 decimal digit). The ground-state fidelity was distilled to be more than 80%, and the singlet-to-triplet switching near the critical field is reliably captured. This result shows that quantum simulators can better leverage classical trial wave functions than classical computers PMID:22355607

Solving a supply chain scheduling problem with non-identical job sizes and release times by applying a novel effective heuristic algorithm

NASA Astrophysics Data System (ADS)

Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin

2016-03-01

Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.

Use of a Computer Language in Teaching Dynamic Programming. Final Report.

ERIC Educational Resources Information Center

Trimble, C. J.; And Others

Most optimization problems of any degree of complexity must be solved using a computer. In the teaching of dynamic programing courses, it is often desirable to use a computer in problem solution. The solution process involves conceptual formulation and computational Solution. Generalized computer codes for dynamic programing problem solution…

Hands Together! An Analog Clock Problem

ERIC Educational Resources Information Center

Earnest, Darrell; Radtke, Susan; Scott, Siri

2017-01-01

In this article, the authors first present the Hands Together! task. The mathematics in this problem concerns the relationship of hour and minute durations as reflected in the oft-overlooked proportional movements of the two hands of an analog clock. The authors go on to discuss the importance of problem solving in general. They then consider…

An E-Learning Environment for Algorithmic: Toward an Active Construction of Skills

ERIC Educational Resources Information Center

Babori, Abdelghani; Fassi, Hicham Fihri; Hariri, Abdellah; Bideq, Mustapha

2016-01-01

Assimilating an algorithmic course is a persistent problem for many undergraduate students. The major problem faced by students is the lack of problem solving ability and flexibility. Therefore, students are generally passive, unmotivated and unable to mobilize all the acquired knowledge (loops, test, variables, etc.) to deal with new encountered…

A truncated generalized singular value decomposition algorithm for moving force identification with ill-posed problems

NASA Astrophysics Data System (ADS)

Chen, Zhen; Chan, Tommy H. T.

2017-08-01

This paper proposes a new methodology for moving force identification (MFI) from the responses of bridge deck. Based on the existing time domain method (TDM), the MFI problem eventually becomes solving the linear algebraic equation in the form Ax = b . The vector b is usually contaminated by an unknown error e generating from measurement error, which often called the vector e as ''noise''. With the ill-posed problems that exist in the inverse problem, the identification force would be sensitive to the noise e . The proposed truncated generalized singular value decomposition method (TGSVD) aims at obtaining an acceptable solution and making the noise to be less sensitive to perturbations with the ill-posed problems. The illustrated results show that the TGSVD has many advantages such as higher precision, better adaptability and noise immunity compared with TDM. In addition, choosing a proper regularization matrix L and a truncation parameter k are very useful to improve the identification accuracy and to solve ill-posed problems when it is used to identify the moving force on bridge.

Active subspace: toward scalable low-rank learning.

PubMed

Liu, Guangcan; Yan, Shuicheng

2012-12-01

We address the scalability issues in low-rank matrix learning problems. Usually these problems resort to solving nuclear norm regularized optimization problems (NNROPs), which often suffer from high computational complexities if based on existing solvers, especially in large-scale settings. Based on the fact that the optimal solution matrix to an NNROP is often low rank, we revisit the classic mechanism of low-rank matrix factorization, based on which we present an active subspace algorithm for efficiently solving NNROPs by transforming large-scale NNROPs into small-scale problems. The transformation is achieved by factorizing the large solution matrix into the product of a small orthonormal matrix (active subspace) and another small matrix. Although such a transformation generally leads to nonconvex problems, we show that a suboptimal solution can be found by the augmented Lagrange alternating direction method. For the robust PCA (RPCA) (Candès, Li, Ma, & Wright, 2009 ) problem, a typical example of NNROPs, theoretical results verify the suboptimality of the solution produced by our algorithm. For the general NNROPs, we empirically show that our algorithm significantly reduces the computational complexity without loss of optimality.

General Intelligence Predicts Reasoning Ability Even for Evolutionarily Familiar Content

ERIC Educational Resources Information Center

Kaufman, Scott Barry; DeYoung, Colin G.; Reis, Deidre L.; Gray, Jeremy R.

2011-01-01

The existence of general-purpose cognitive mechanisms related to intelligence, which appear to facilitate all forms of problem solving, conflicts with the strong modularity view of the mind espoused by some evolutionary psychologists. The current study assessed the contribution of general intelligence ("g") to explaining variation in…

Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com

We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.

Interior point techniques for LP and NLP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Evtushenko, Y.

By using surjective mapping the initial constrained optimization problem is transformed to a problem in a new space with only equality constraints. For the numerical solution of the latter problem we use the generalized gradient-projection method and Newton`s method. After inverse transformation to the initial space we obtain the family of numerical methods for solving optimization problems with equality and inequality constraints. In the linear programming case after some simplification we obtain Dikin`s algorithm, affine scaling algorithm and generalized primal dual interior point linear programming algorithm.

Three-dimensional finite element analysis for high velocity impact. [of projectiles from space debris

NASA Technical Reports Server (NTRS)

Chan, S. T. K.; Lee, C. H.; Brashears, M. R.

1975-01-01

A finite element algorithm for solving unsteady, three-dimensional high velocity impact problems is presented. A computer program was developed based on the Eulerian hydroelasto-viscoplastic formulation and the utilization of the theorem of weak solutions. The equations solved consist of conservation of mass, momentum, and energy, equation of state, and appropriate constitutive equations. The solution technique is a time-dependent finite element analysis utilizing three-dimensional isoparametric elements, in conjunction with a generalized two-step time integration scheme. The developed code was demonstrated by solving one-dimensional as well as three-dimensional impact problems for both the inviscid hydrodynamic model and the hydroelasto-viscoplastic model.

Counselor-Assisted Problem Solving (CAPS) Improves Behavioral Outcomes in Older Adolescents with Complicated Mild to Severe TBI

PubMed Central

Wade, Shari L.; Stancin, Terry; Kirkwood, Michael; Brown, Tanya Maines; Rochester, Mayo Clinic; McMullen, Kendra M.; Taylor, H. Gerry

2013-01-01

Objective To test the efficacy of Counselor-Assisted Problem Solving (CAPS) versus an internet resources comparison (IRC) condition in reducing behavior problems in adolescents following traumatic brain injury (TBI). Design Randomized clinical trial with interviewers naïve to treatment condition. Setting Three large tertiary children's hospitals and two general hospitals with pediatric commitment. Participants 132 children ages 12-17 years hospitalized during the previous 6 months for moderate to severe TBI. Interventions Participants in CAPS (n = 65) completed 8-12 online modules providing training in problem solving, communication skills, and self-regulation and subsequent synchronous videoconferences with a therapist. Participants in the IRC group (n = 67) received links to internet resources about pediatric TBI. Main Outcome Measures Child Behavior Checklist (CBCL) administered before and after completion of treatment (i.e., approximately six months after treatment initiation). Results Post hoc analysis of covariance (ANCOVA), controlling for pre-treatment scores, was used to examine group differences in behavior problems in the entire sample and among older (n=59) and younger adolescents (n=53). Among older but not younger adolescents, CAPS resulted in greater improvements on multiple dimensions of externalizing behavior problems than did IRC. Conclusion Online problem-solving therapy may be effective in reducing behavior problems in older adolescent survivors of moderate-severe TBI. PMID:23640543

Boundary conditions and transmission reflection of electron spin in a quantum well

NASA Astrophysics Data System (ADS)

Dargys, A.

2012-04-01

Boundary conditions for a spinor at the interface of hetero- and homobarrier in the presence of spin-orbit interaction are briefly reviewed and generalized. Then they are applied to 2D electron in the presence of a discontinuity of physical parameters in a quantum well. It is shown that in general case under oblique electron incidence, the problem can be solved analytically and the Fresnel-type formulae for polarization can be obtained if, in addition, the Gröbner basis algorithm is addressed to solve the problem. It is observed that the transmitted and reflected spin polarization may strongly depend on values of spin-orbit constants on both sides of the homobarrier in the quantum well.

Generalizations of Tikhonov's regularized method of least squares to non-Euclidean vector norms

NASA Astrophysics Data System (ADS)

Volkov, V. V.; Erokhin, V. I.; Kakaev, V. V.; Onufrei, A. Yu.

2017-09-01

Tikhonov's regularized method of least squares and its generalizations to non-Euclidean norms, including polyhedral, are considered. The regularized method of least squares is reduced to mathematical programming problems obtained by "instrumental" generalizations of the Tikhonov lemma on the minimal (in a certain norm) solution of a system of linear algebraic equations with respect to an unknown matrix. Further studies are needed for problems concerning the development of methods and algorithms for solving reduced mathematical programming problems in which the objective functions and admissible domains are constructed using polyhedral vector norms.

Solving complex band structure problems with the FEAST eigenvalue algorithm

NASA Astrophysics Data System (ADS)

Laux, S. E.

2012-08-01

With straightforward extension, the FEAST eigenvalue algorithm [Polizzi, Phys. Rev. B 79, 115112 (2009)] is capable of solving the generalized eigenvalue problems representing traveling-wave problems—as exemplified by the complex band-structure problem—even though the matrices involved are complex, non-Hermitian, and singular, and hence outside the originally stated range of applicability of the algorithm. The obtained eigenvalues/eigenvectors, however, contain spurious solutions which must be detected and removed. The efficiency and parallel structure of the original algorithm are unaltered. The complex band structures of Si layers of varying thicknesses and InAs nanowires of varying radii are computed as test problems.

Steady state solutions to dynamically loaded periodic structures

NASA Technical Reports Server (NTRS)

Kalinowski, A. J.

1980-01-01

The general problem of solving for the steady state (time domain) dynamic response (i.e., NASTRAN rigid format-8) of a general elastic periodic structure subject to a phase difference loading of the type encountered in traveling wave propagation problems was studied. Two types of structural configurations were considered; in the first type, the structure has a repeating pattern over a span that is long enough to be considered, for all practical purposes, as infinite; in the second type, the structure has structural rotational symmetry in the circumferential direction. The theory and a corresponding set of DMAP instructions which permits the NASTRAN user to automatically alter the rigid format-8 sequence to solve the intended class of problems are presented. Final results are recovered as with any ordinary rigid format-8 solution, except that the results are only printed for the typical periodic segment of the structure. A simple demonstration problem having a known exact solution is used to illustrate the implementation of the procedure.

A generalized network flow model for the multi-mode resource-constrained project scheduling problem with discounted cash flows

NASA Astrophysics Data System (ADS)

Chen, Miawjane; Yan, Shangyao; Wang, Sin-Siang; Liu, Chiu-Lan

2015-02-01

An effective project schedule is essential for enterprises to increase their efficiency of project execution, to maximize profit, and to minimize wastage of resources. Heuristic algorithms have been developed to efficiently solve the complicated multi-mode resource-constrained project scheduling problem with discounted cash flows (MRCPSPDCF) that characterize real problems. However, the solutions obtained in past studies have been approximate and are difficult to evaluate in terms of optimality. In this study, a generalized network flow model, embedded in a time-precedence network, is proposed to formulate the MRCPSPDCF with the payment at activity completion times. Mathematically, the model is formulated as an integer network flow problem with side constraints, which can be efficiently solved for optimality, using existing mathematical programming software. To evaluate the model performance, numerical tests are performed. The test results indicate that the model could be a useful planning tool for project scheduling in the real world.

General-purpose abductive algorithm for interpretation

NASA Astrophysics Data System (ADS)

Fox, Richard K.; Hartigan, Julie

1996-11-01

Abduction, inference to the best explanation, is an information-processing task that is useful for solving interpretation problems such as diagnosis, medical test analysis, legal reasoning, theory evaluation, and perception. The task is a generative one in which an explanation comprising of domain hypotheses is assembled and used to account for given findings. The explanation is taken to be an interpretation as to why the findings have arisen within the given situation. Research in abduction has led to the development of a general-purpose computational strategy which has been demonstrated on all of the above types of problems. This abduction strategy can be performed in layers so that different types of knowledge can come together in deriving an explanation at different levels of description. Further, the abduction strategy is tractable and offers a very useful tradeoff between confidence in the explanation and completeness of the explanation. This paper will describe this computational strategy for abduction and demonstrate its usefulness towards perceptual problems by examining problem-solving systems in speech recognition and natural language understanding.

Replicating the benefits of Deutschian closed timelike curves without breaking causality

NASA Astrophysics Data System (ADS)

Yuan, Xiao; Assad, Syed M.; Thompson, Jayne; Haw, Jing Yan; Vedral, Vlatko; Ralph, Timothy C.; Lam, Ping Koy; Weedbrook, Christian; Gu, Mile

2015-11-01

In general relativity, closed timelike curves can break causality with remarkable and unsettling consequences. At the classical level, they induce causal paradoxes disturbing enough to motivate conjectures that explicitly prevent their existence. At the quantum level such problems can be resolved through the Deutschian formalism, however this induces radical benefits—from cloning unknown quantum states to solving problems intractable to quantum computers. Instinctively, one expects these benefits to vanish if causality is respected. Here we show that in harnessing entanglement, we can efficiently solve NP-complete problems and clone arbitrary quantum states—even when all time-travelling systems are completely isolated from the past. Thus, the many defining benefits of Deutschian closed timelike curves can still be harnessed, even when causality is preserved. Our results unveil a subtle interplay between entanglement and general relativity, and significantly improve the potential of probing the radical effects that may exist at the interface between relativity and quantum theory.

STARS: An integrated general-purpose finite element structural, aeroelastic, and aeroservoelastic analysis computer program

NASA Technical Reports Server (NTRS)

Gupta, Kajal K.

1991-01-01

The details of an integrated general-purpose finite element structural analysis computer program which is also capable of solving complex multidisciplinary problems is presented. Thus, the SOLIDS module of the program possesses an extensive finite element library suitable for modeling most practical problems and is capable of solving statics, vibration, buckling, and dynamic response problems of complex structures, including spinning ones. The aerodynamic module, AERO, enables computation of unsteady aerodynamic forces for both subsonic and supersonic flow for subsequent flutter and divergence analysis of the structure. The associated aeroservoelastic analysis module, ASE, effects aero-structural-control stability analysis yielding frequency responses as well as damping characteristics of the structure. The program is written in standard FORTRAN to run on a wide variety of computers. Extensive graphics, preprocessing, and postprocessing routines are also available pertaining to a number of terminals.

An Integrated Planning Representation Using Macros, Abstractions, and Cases

NASA Technical Reports Server (NTRS)

Baltes, Jacky; MacDonald, Bruce

1992-01-01

Planning will be an essential part of future autonomous robots and integrated intelligent systems. This paper focuses on learning problem solving knowledge in planning systems. The system is based on a common representation for macros, abstractions, and cases. Therefore, it is able to exploit both classical and case based techniques. The general operators in a successful plan derivation would be assessed for their potential usefulness, and some stored. The feasibility of this approach was studied through the implementation of a learning system for abstraction. New macros are motivated by trying to improve the operatorset. One heuristic used to improve the operator set is generating operators with more general preconditions than existing ones. This heuristic leads naturally to abstraction hierarchies. This investigation showed promising results on the towers of Hanoi problem. The paper concludes by describing methods for learning other problem solving knowledge. This knowledge can be represented by allowing operators at different levels of abstraction in a refinement.

Case Studies in School Communication.

ERIC Educational Resources Information Center

Texas School Public Relations Association.

This two-part source book offers administrators both general information for effective communications in public education and case studies describing methods used by individual Texas school districts to solve communications problems. General articles include guidelines for working with the news media, producing school newsletters, developing a…

Best candidates for cognitive treatment of illness perceptions in chronic low back pain: results of a theory-driven predictor study.

PubMed

Siemonsma, Petra C; Stuvie, Ilse; Roorda, Leo D; Vollebregt, Joke A; Lankhorst, Gustaaf J; Lettinga, Ant T

2011-04-01

The aim of this study was to identify treatment-specific predictors of the effectiveness of a method of evidence-based treatment: cognitive treatment of illness perceptions. This study focuses on what treatment works for whom, whereas most prognostic studies focusing on chronic non-specific low back pain rehabilitation aim to reduce the heterogeneity of the population of patients who are suitable for rehabilitation treatment in general. Three treatment-specific predictors were studied in patients with chronic non-specific low back pain receiving cognitive treatment of illness perceptions: a rational approach to problem-solving, discussion skills and verbal skills. Hierarchical linear regression analysis was used to assess their predictive value. Short-term changes in physical activity, measured with the Patient-Specific Functioning List, were the outcome measure for cognitive treatment of illness perceptions effect. A total of 156 patients with chronic non-specific low back pain participated in the study. Rational problem-solving was found to be a significant predictor for the change in physical activity. Discussion skills and verbal skills were non-significant. Rational problem-solving explained 3.9% of the total variance. The rational problem-solving scale results are encouraging, because chronic non-specific low back pain problems are complex by nature and can be influenced by a variety of factors. A minimum score of 44 points on the rational problem-solving scale may assist clinicians in selecting the most appropriate candidates for cognitive treatment of illness perceptions.

The Influence of Open Goals on the Acquisition of Problem-Relevant Information

ERIC Educational Resources Information Center

Moss, Jarrod; Kotovsky, Kenneth; Cagan, Jonathan

2007-01-01

There have been a number of recent findings indicating that unsolved problems, or open goals more generally, influence cognition even when the current task has no relation to the task in which the goal was originally set. It was hypothesized that open goals would influence what information entered the problem-solving process. Three studies were…

Supporting Valid Decision Making: Uses and Misuses of Assessment Data within the Context of RtI

ERIC Educational Resources Information Center

Ball, Carrie R.; Christ, Theodore J.

2012-01-01

Within an RtI problem-solving context, assessment and decision making generally center around the tasks of problem identification, problem analysis, progress monitoring, and program evaluation. We use this framework to discuss the current state of the literature regarding curriculum based measurement, its technical properties, and its utility for…

Preliminary Study on the Role of Alternative Educational Pathways in Promoting the Use of Problem-Focused Coping Strategies

ERIC Educational Resources Information Center

Shankland, Rebecca; Franca, Lionel Riou; Genolini, Christophe M.; Guelfi, Julien-Daniel; Ionescu, Serban

2009-01-01

Coping styles are generally considered to be environmentally driven. Up to now, research has mainly focused on family influences. However, some studies underline the effect of educational settings on the development of problem-focused coping strategies. Consistently with previous reports on the enhancement of autonomy and problem-solving in…

Attitude Differences and Task Performance for Black and White Naval Recruits in Problem-Solving Groups of Differing Size and Racial Composition.

DTIC Science & Technology

A field study was made in which 288 black and white naval personnel (224 recruits and 64 squad leaders) in groups of varying size and racial composition performed two problem-solving tasks (knot tying and ship-routing). Black and white leaders, subordinates and group types (25% black tetrads, 75% black tetrads, racially balanced dyads and tetrads) were compared in measures of self - esteem , duration of speech, locus of control, job and general satisfaction, Bales IPA behavior, and performance on the tasks.

General relativistic radiative transfer code in rotating black hole space-time: ARTIST

NASA Astrophysics Data System (ADS)

Takahashi, Rohta; Umemura, Masayuki

2017-02-01

We present a general relativistic radiative transfer code, ARTIST (Authentic Radiative Transfer In Space-Time), that is a perfectly causal scheme to pursue the propagation of radiation with absorption and scattering around a Kerr black hole. The code explicitly solves the invariant radiation intensity along null geodesics in the Kerr-Schild coordinates, and therefore properly includes light bending, Doppler boosting, frame dragging, and gravitational redshifts. The notable aspect of ARTIST is that it conserves the radiative energy with high accuracy, and is not subject to the numerical diffusion, since the transfer is solved on long characteristics along null geodesics. We first solve the wavefront propagation around a Kerr black hole that was originally explored by Hanni. This demonstrates repeated wavefront collisions, light bending, and causal propagation of radiation with the speed of light. We show that the decay rate of the total energy of wavefronts near a black hole is determined solely by the black hole spin in late phases, in agreement with analytic expectations. As a result, the ARTIST turns out to correctly solve the general relativistic radiation fields until late phases as t ˜ 90 M. We also explore the effects of absorption and scattering, and apply this code for a photon wall problem and an orbiting hotspot problem. All the simulations in this study are performed in the equatorial plane around a Kerr black hole. The ARTIST is the first step to realize the general relativistic radiation hydrodynamics.

A function space framework for structural total variation regularization with applications in inverse problems

NASA Astrophysics Data System (ADS)

Hintermüller, Michael; Holler, Martin; Papafitsoros, Kostas

2018-06-01

In this work, we introduce a function space setting for a wide class of structural/weighted total variation (TV) regularization methods motivated by their applications in inverse problems. In particular, we consider a regularizer that is the appropriate lower semi-continuous envelope (relaxation) of a suitable TV type functional initially defined for sufficiently smooth functions. We study examples where this relaxation can be expressed explicitly, and we also provide refinements for weighted TV for a wide range of weights. Since an integral characterization of the relaxation in function space is, in general, not always available, we show that, for a rather general linear inverse problems setting, instead of the classical Tikhonov regularization problem, one can equivalently solve a saddle-point problem where no a priori knowledge of an explicit formulation of the structural TV functional is needed. In particular, motivated by concrete applications, we deduce corresponding results for linear inverse problems with norm and Poisson log-likelihood data discrepancy terms. Finally, we provide proof-of-concept numerical examples where we solve the saddle-point problem for weighted TV denoising as well as for MR guided PET image reconstruction.

An investigation of successful and unsuccessful students' problem solving in stoichiometry

NASA Astrophysics Data System (ADS)

Gulacar, Ozcan

In this study, I investigated how successful and unsuccessful students solve stoichiometry problems. I focus on three research questions: (1) To what extent do the difficulties in solving stoichiometry problems stem from poor understanding of pieces (domain-specific knowledge) versus students' inability to link those pieces together (conceptual knowledge)? (2) What are the differences between successful and unsuccessful students in knowledge, ability, and practice? (3) Is there a connection between students' (a) cognitive development levels, (b) formal (proportional) reasoning abilities, (c) working memory capacities, (d) conceptual understanding of particle nature of matter, (e) understanding of the mole concept, and their problem-solving achievement in stoichiometry? In this study, nine successful students and eight unsuccessful students participated. Both successful and unsuccessful students were selected among the students taking a general chemistry course at a mid-western university. The students taking this class were all science, non-chemistry majors. Characteristics of successful and unsuccessful students were determined through tests, audio and videotapes analyses, and subjects' written works. The Berlin Particle Concept Inventory, the Mole Concept Achievement Test, the Test of Logical Thinking, the Digits Backward Test, and the Longeot Test were used to measure students' conceptual understanding of particle nature of matter and mole concept, formal (proportional) reasoning ability, working memory capacity, and cognitive development, respectively. Think-aloud problem-solving protocols were also used to better explore the differences between successful and unsuccessful students' knowledge structures and behaviors during problem solving. Although successful students did not show significantly better performance on doing pieces (domain-specific knowledge) and solving exercises than unsuccessful counterparts did, they appeared to be more successful in linking the pieces (conceptual knowledge) and solving complex problems than the unsuccessful student did. Successful students also appeared to be different in how they approach problems, what strategies they use, and in making fewer algorithmic mistakes when compared to unsuccessful students. Successful students, however, did not seem to be statistically significantly different from the unsuccessful students in terms of quantitatively tested cognitive abilities except formal (proportional) reasoning ability and in the understanding of mole concept.

A Model for General Parenting Skill is Too Simple: Mediational Models Work Better.

ERIC Educational Resources Information Center

Patterson, G. R.; Yoerger, K.

A study was designed to determine whether mediational models of parenting patterns account for significantly more variance in academic achievement than more general models. Two general models and two mediational models were considered. The first model identified five skills: (1) discipline; (2) monitoring; (3) family problem solving; (4) positive…

An Integer Programming Model For Solving Heterogeneous Vehicle Routing Problem With Hard Time Window considering Service Choice

NASA Astrophysics Data System (ADS)

Susilawati, Enny; Mawengkang, Herman; Efendi, Syahril

2018-01-01

Generally a Vehicle Routing Problem with time windows (VRPTW) can be defined as a problem to determine the optimal set of routes used by a fleet of vehicles to serve a given set of customers with service time restrictions; the objective is to minimize the total travel cost (related to the travel times or distances) and operational cost (related to the number of vehicles used). In this paper we address a variant of the VRPTW in which the fleet of vehicle is heterogenic due to the different size of demand from customers. The problem, called Heterogeneous VRP (HVRP) also includes service levels. We use integer programming model to describe the problem. A feasible neighbourhood approach is proposed to solve the model.

Genetic algorithm parameters tuning for resource-constrained project scheduling problem

NASA Astrophysics Data System (ADS)

Tian, Xingke; Yuan, Shengrui

2018-04-01

Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.

Effective optimization using sample persistence: A case study on quantum annealers and various Monte Carlo optimization methods

NASA Astrophysics Data System (ADS)

Karimi, Hamed; Rosenberg, Gili; Katzgraber, Helmut G.

2017-10-01

We present and apply a general-purpose, multistart algorithm for improving the performance of low-energy samplers used for solving optimization problems. The algorithm iteratively fixes the value of a large portion of the variables to values that have a high probability of being optimal. The resulting problems are smaller and less connected, and samplers tend to give better low-energy samples for these problems. The algorithm is trivially parallelizable since each start in the multistart algorithm is independent, and could be applied to any heuristic solver that can be run multiple times to give a sample. We present results for several classes of hard problems solved using simulated annealing, path-integral quantum Monte Carlo, parallel tempering with isoenergetic cluster moves, and a quantum annealer, and show that the success metrics and the scaling are improved substantially. When combined with this algorithm, the quantum annealer's scaling was substantially improved for native Chimera graph problems. In addition, with this algorithm the scaling of the time to solution of the quantum annealer is comparable to the Hamze-de Freitas-Selby algorithm on the weak-strong cluster problems introduced by Boixo et al. Parallel tempering with isoenergetic cluster moves was able to consistently solve three-dimensional spin glass problems with 8000 variables when combined with our method, whereas without our method it could not solve any.

A novel optimization algorithm for MIMO Hammerstein model identification under heavy-tailed noise.

PubMed

Jin, Qibing; Wang, Hehe; Su, Qixin; Jiang, Beiyan; Liu, Qie

2018-01-01

In this paper, we study the system identification of multi-input multi-output (MIMO) Hammerstein processes under the typical heavy-tailed noise. To the best of our knowledge, there is no general analytical method to solve this identification problem. Motivated by this, we propose a general identification method to solve this problem based on a Gaussian-Mixture Distribution intelligent optimization algorithm (GMDA). The nonlinear part of Hammerstein process is modeled by a Radial Basis Function (RBF) neural network, and the identification problem is converted to an optimization problem. To overcome the drawbacks of analytical identification method in the presence of heavy-tailed noise, a meta-heuristic optimization algorithm, Cuckoo search (CS) algorithm is used. To improve its performance for this identification problem, the Gaussian-mixture Distribution (GMD) and the GMD sequences are introduced to improve the performance of the standard CS algorithm. Numerical simulations for different MIMO Hammerstein models are carried out, and the simulation results verify the effectiveness of the proposed GMDA. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Developing Air Force Systems Engineers - a Flight Path

DTIC Science & Technology

2012-12-01

to viewing problems from different perspectives. Specialists generally see the world through the lens of their own specialty. To paraphrase Abraham ... Maslow : If all you have is a hammer, everything looks like a nail. Systems engineers are supposed to take a different approach to problem solving

Quantum solvability of a general ordered position dependent mass system: Mathews-Lakshmanan oscillator

NASA Astrophysics Data System (ADS)

Karthiga, S.; Chithiika Ruby, V.; Senthilvelan, M.; Lakshmanan, M.

2017-10-01

In position dependent mass (PDM) problems, the quantum dynamics of the associated systems have been understood well in the literature for particular orderings. However, no efforts seem to have been made to solve such PDM problems for general orderings to obtain a global picture. In this connection, we here consider the general ordered quantum Hamiltonian of an interesting position dependent mass problem, namely, the Mathews-Lakshmanan oscillator, and try to solve the quantum problem for all possible orderings including Hermitian and non-Hermitian ones. The other interesting point in our study is that for all possible orderings, although the Schrödinger equation of this Mathews-Lakshmanan oscillator is uniquely reduced to the associated Legendre differential equation, their eigenfunctions cannot be represented in terms of the associated Legendre polynomials with integral degree and order. Rather the eigenfunctions are represented in terms of associated Legendre polynomials with non-integral degree and order. We here explore such polynomials and represent the discrete and continuum states of the system. We also exploit the connection between associated Legendre polynomials with non-integral degree with other orthogonal polynomials such as Jacobi and Gegenbauer polynomials.

Robust Adaptive Modified Newton Algorithm for Generalized Eigendecomposition and Its Application

NASA Astrophysics Data System (ADS)

Yang, Jian; Yang, Feng; Xi, Hong-Sheng; Guo, Wei; Sheng, Yanmin

2007-12-01

We propose a robust adaptive algorithm for generalized eigendecomposition problems that arise in modern signal processing applications. To that extent, the generalized eigendecomposition problem is reinterpreted as an unconstrained nonlinear optimization problem. Starting from the proposed cost function and making use of an approximation of the Hessian matrix, a robust modified Newton algorithm is derived. A rigorous analysis of its convergence properties is presented by using stochastic approximation theory. We also apply this theory to solve the signal reception problem of multicarrier DS-CDMA to illustrate its practical application. The simulation results show that the proposed algorithm has fast convergence and excellent tracking capability, which are important in a practical time-varying communication environment.

Cognitive and behavioral knowledge about insulin-dependent diabetes among children and parents.

PubMed

Johnson, S B; Pollak, R T; Silverstein, J H; Rosenbloom, A L; Spillar, R; McCallum, M; Harkavy, J

1982-06-01

Youngster's knowledge about insulin-dependent diabetes was assessed across three domains: (1) general information; (2) problem solving and (3) skill at urine testing and self-injection. These youngster's parents completed the general information and problem-solving components of the assessment battery. All test instruments were showed good reliability. The test of problem solving was more difficult than the test of general information for both parents and patients. Mothers were more knowledgeable than fathers and children. Girls performed more accurately than boys, and older children obtained better scores than did younger children. Nevertheless, more than 80% of the youngsters made significant errors on urine testing and almost 40% made serious errors in self-injection. A number of other knowledge deficits were also noted. Duration of diabetes was not related to any of the knowledge measures. Intercorrelations between scores on the assessment instruments indicated that skill at urine testing or self-injection was not highly related to other types of knowledge about diabetes. Furthermore, knowledge in one content are was not usually predictive of knowledge in another content area. The results of this study emphasize the importance of measuring knowledge from several different domains. Patient variables such as sex and age need to be given further consideration in the development and use of patient educational programs. Regular assessment of patients' and parents' knowledge of all critical aspects of diabetes home management seems essential.

How are things adding up? Neural differences between arithmetic operations are due to general problem solving strategies.

PubMed

Tschentscher, Nadja; Hauk, Olaf

2014-05-15

A number of previous studies have interpreted differences in brain activation between arithmetic operation types (e.g. addition and multiplication) as evidence in favor of distinct cortical representations, processes or neural systems. It is still not clear how differences in general task complexity contribute to these neural differences. Here, we used a mental arithmetic paradigm to disentangle brain areas related to general problem solving from those involved in operation type specific processes (addition versus multiplication). We orthogonally varied operation type and complexity. Importantly, complexity was defined not only based on surface criteria (for example number size), but also on the basis of individual participants' strategy ratings, which were validated in a detailed behavioral analysis. We replicated previously reported operation type effects in our analyses based on surface criteria. However, these effects vanished when controlling for individual strategies. Instead, procedural strategies contrasted with memory retrieval reliably activated fronto-parietal and motor regions, while retrieval strategies activated parietal cortices. This challenges views that operation types rely on partially different neural systems, and suggests that previously reported differences between operation types may have emerged due to invalid measures of complexity. We conclude that mental arithmetic is a powerful paradigm to study brain networks of abstract problem solving, as long as individual participants' strategies are taken into account. Copyright © 2014 Elsevier Inc. All rights reserved.

Code Development of Three-Dimensional General Relativistic Hydrodynamics with AMR (Adaptive-Mesh Refinement) and Results from Special and General Relativistic Hydrodynamics

NASA Astrophysics Data System (ADS)

Dönmez, Orhan

2004-09-01

In this paper, the general procedure to solve the general relativistic hydrodynamical (GRH) equations with adaptive-mesh refinement (AMR) is presented. In order to achieve, the GRH equations are written in the conservation form to exploit their hyperbolic character. The numerical solutions of GRH equations are obtained by high resolution shock Capturing schemes (HRSC), specifically designed to solve nonlinear hyperbolic systems of conservation laws. These schemes depend on the characteristic information of the system. The Marquina fluxes with MUSCL left and right states are used to solve GRH equations. First, different test problems with uniform and AMR grids on the special relativistic hydrodynamics equations are carried out to verify the second-order convergence of the code in one, two and three dimensions. Results from uniform and AMR grid are compared. It is found that adaptive grid does a better job when the number of resolution is increased. Second, the GRH equations are tested using two different test problems which are Geodesic flow and Circular motion of particle In order to do this, the flux part of GRH equations is coupled with source part using Strang splitting. The coupling of the GRH equations is carried out in a treatment which gives second order accurate solutions in space and time.

Analysis of problem solving on project based learning with resource based learning approach computer-aided program

NASA Astrophysics Data System (ADS)

Kuncoro, K. S.; Junaedi, I.; Dwijanto

2018-03-01

This study aimed to reveal the effectiveness of Project Based Learning with Resource Based Learning approach computer-aided program and analyzed problem-solving abilities in terms of problem-solving steps based on Polya stages. The research method used was mixed method with sequential explanatory design. The subject of this research was the students of math semester 4. The results showed that the S-TPS (Strong Top Problem Solving) and W-TPS (Weak Top Problem Solving) had good problem-solving abilities in each problem-solving indicator. The problem-solving ability of S-MPS (Strong Middle Problem Solving) and (Weak Middle Problem Solving) in each indicator was good. The subject of S-BPS (Strong Bottom Problem Solving) had a difficulty in solving the problem with computer program, less precise in writing the final conclusion and could not reflect the problem-solving process using Polya’s step. While the Subject of W-BPS (Weak Bottom Problem Solving) had not been able to meet almost all the indicators of problem-solving. The subject of W-BPS could not precisely made the initial table of completion so that the completion phase with Polya’s step was constrained.

Analytical solutions for sequentially coupled one-dimensional reactive transport problems Part I: Mathematical derivations

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Clement, T. P.

2008-02-01

Multi-species reactive transport equations coupled through sorption and sequential first-order reactions are commonly used to model sites contaminated with radioactive wastes, chlorinated solvents and nitrogenous species. Although researchers have been attempting to solve various forms of these reactive transport equations for over 50 years, a general closed-form analytical solution to this problem is not available in the published literature. In Part I of this two-part article, we derive a closed-form analytical solution to this problem for spatially-varying initial conditions. The proposed solution procedure employs a combination of Laplace and linear transform methods to uncouple and solve the system of partial differential equations. Two distinct solutions are derived for Dirichlet and Cauchy boundary conditions each with Bateman-type source terms. We organize and present the final solutions in a common format that represents the solutions to both boundary conditions. In addition, we provide the mathematical concepts for deriving the solution within a generic framework that can be used for solving similar transport problems.

An efficient computational method for solving nonlinear stochastic Itô integral equations: Application for stochastic problems in physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heydari, M.H., E-mail: heydari@stu.yazd.ac.ir; The Laboratory of Quantum Information Processing, Yazd University, Yazd; Hooshmandasl, M.R., E-mail: hooshmandasl@yazd.ac.ir

Because of the nonlinearity, closed-form solutions of many important stochastic functional equations are virtually impossible to obtain. Thus, numerical solutions are a viable alternative. In this paper, a new computational method based on the generalized hat basis functions together with their stochastic operational matrix of Itô-integration is proposed for solving nonlinear stochastic Itô integral equations in large intervals. In the proposed method, a new technique for computing nonlinear terms in such problems is presented. The main advantage of the proposed method is that it transforms problems under consideration into nonlinear systems of algebraic equations which can be simply solved. Errormore » analysis of the proposed method is investigated and also the efficiency of this method is shown on some concrete examples. The obtained results reveal that the proposed method is very accurate and efficient. As two useful applications, the proposed method is applied to obtain approximate solutions of the stochastic population growth models and stochastic pendulum problem.« less

"Effects of a Web-Based Intervention on Family Functioning Following Pediatric Traumatic Brain Injury"

PubMed Central

Minich, Nori; Taylor, H. Gerry; Kirkwood, Michael; Brown, Tanya Maines; Stancin, Terry; Wade, Shari L

2015-01-01

Objective Investigate effectiveness of an online Counselor-Assisted Problem-Solving (CAPS) intervention on family functioning after traumatic brain injury (TBI). Methods Participants were randomized to CAPS (n = 65) or internet resource comparison (IRC; n = 67). CAPS is a counselor-assisted web-based program. IRC was given access to online resources. Outcomes were examined 6 months, 12 months, and 18 months after baseline. Injury severity, age, and SES were examined as moderators. Results A main effect of time was noted for teen-reported conflict and parent-reported problem solving. CAPS had decreased parent-reported conflict and a reduction in parental effective communication. Effects were specific to subsets of the sample. Conclusions CAPS, a family-based problem-solving intervention designed to address problem behaviors, had modest effects on some aspects of family functioning, when compared to IRC. Effects were generally limited to subsets of the families and were not evident across all follow-up assessments. PMID:26461100

Validation of a High-Order Prefactored Compact Scheme on Nonlinear Flows with Complex Geometries

NASA Technical Reports Server (NTRS)

Hixon, Ray; Mankbadi, Reda R.; Povinelli, L. A. (Technical Monitor)

2000-01-01

Three benchmark problems are solved using a sixth-order prefactored compact scheme employing an explicit 10th-order filter with optimized fourth-order Runge-Kutta time stepping. The problems solved are the following: (1) propagation of sound waves through a transonic nozzle; (2) shock-sound interaction; and (3) single airfoil gust response. In the first two problems, the spatial accuracy of the scheme is tested on a stretched grid, and the effectiveness of boundary conditions is shown. The solution stability and accuracy near a shock discontinuity is shown as well. Also, 1-D nonlinear characteristic boundary conditions will be evaluated. In the third problem, a nonlinear Euler solver will be used that solves the equations in generalized curvilinear coordinates using the chain rule transformation. This work, continuing earlier work on flat-plate cascades and Joukowski airfoils, will focus mainly on the effect of the grid and boundary conditions on the accuracy of the solution. The grids were generated using a commercially available grid generator, GridPro/az3000.

Linear and nonlinear dynamic analysis by boundary element method. Ph.D. Thesis, 1986 Final Report

NASA Technical Reports Server (NTRS)

Ahmad, Shahid

1991-01-01

An advanced implementation of the direct boundary element method (BEM) applicable to free-vibration, periodic (steady-state) vibration and linear and nonlinear transient dynamic problems involving two and three-dimensional isotropic solids of arbitrary shape is presented. Interior, exterior, and half-space problems can all be solved by the present formulation. For the free-vibration analysis, a new real variable BEM formulation is presented which solves the free-vibration problem in the form of algebraic equations (formed from the static kernels) and needs only surface discretization. In the area of time-domain transient analysis, the BEM is well suited because it gives an implicit formulation. Although the integral formulations are elegant, because of the complexity of the formulation it has never been implemented in exact form. In the present work, linear and nonlinear time domain transient analysis for three-dimensional solids has been implemented in a general and complete manner. The formulation and implementation of the nonlinear, transient, dynamic analysis presented here is the first ever in the field of boundary element analysis. Almost all the existing formulation of BEM in dynamics use the constant variation of the variables in space and time which is very unrealistic for engineering problems and, in some cases, it leads to unacceptably inaccurate results. In the present work, linear and quadratic isoparametric boundary elements are used for discretization of geometry and functional variations in space. In addition, higher order variations in time are used. These methods of analysis are applicable to piecewise-homogeneous materials, such that not only problems of the layered media and the soil-structure interaction can be analyzed but also a large problem can be solved by the usual sub-structuring technique. The analyses have been incorporated in a versatile, general-purpose computer program. Some numerical problems are solved and, through comparisons with available analytical and numerical results, the stability and high accuracy of these dynamic analysis techniques are established.

FAST TRACK COMMUNICATION Solving the ultradiscrete KdV equation

NASA Astrophysics Data System (ADS)

Willox, Ralph; Nakata, Yoichi; Satsuma, Junkichi; Ramani, Alfred; Grammaticos, Basile

2010-12-01

We show that a generalized cellular automaton, exhibiting solitonic interactions, can be explicitly solved by means of techniques first introduced in the context of the scattering problem for the KdV equation. We apply this method to calculate the phase-shifts caused by interactions between the solitonic and non-solitonic parts into which arbitrary initial states separate in time.

Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTEGE-II to protocol-based decision support.

PubMed

Tu, S W; Eriksson, H; Gennari, J H; Shahar, Y; Musen, M A

1995-06-01

PROTEGE-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTEGE-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTEGE-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTEGE-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.

A general CPL-AdS methodology for fixing dynamic parameters in dual environments.

PubMed

Huang, De-Shuang; Jiang, Wen

2012-10-01

The algorithm of Continuous Point Location with Adaptive d-ary Search (CPL-AdS) strategy exhibits its efficiency in solving stochastic point location (SPL) problems. However, there is one bottleneck for this CPL-AdS strategy which is that, when the dimension of the feature, or the number of divided subintervals for each iteration, d is large, the decision table for elimination process is almost unavailable. On the other hand, the larger dimension of the features d can generally make this CPL-AdS strategy avoid oscillation and converge faster. This paper presents a generalized universal decision formula to solve this bottleneck problem. As a matter of fact, this decision formula has a wider usage beyond handling out this SPL problems, such as dealing with deterministic point location problems and searching data in Single Instruction Stream-Multiple Data Stream based on Concurrent Read and Exclusive Write parallel computer model. Meanwhile, we generalized the CPL-AdS strategy with an extending formula, which is capable of tracking an unknown dynamic parameter λ in both informative and deceptive environments. Furthermore, we employed different learning automata in the generalized CPL-AdS method to find out if faster learning algorithm will lead to better realization of the generalized CPL-AdS method. All of these aforementioned contributions are vitally important whether in theory or in practical applications. Finally, extensive experiments show that our proposed approaches are efficient and feasible.

On the eigenfrequencies of elastic shear waves propagating in an inhomogeneous layer

NASA Astrophysics Data System (ADS)

Khachatryan, V. M.

2018-04-01

In this work, we consider the problem of eigenfrequencies of elastic shear waves propagating in a layer whose Young’s modulus and density are functions of the longitudinal coordinate. Taking into account the material inhomogeneity makes the problem of the eigenfrequencies of the waves propagating in the layer more complicated. In this paper, the problem of pure shear is considered. To solve the problem, we use an integral formula which allows us to represent the general solution of the original equation with variable coefficients in terms of the general solution of the accompanying equation with constant coefficients.

The piecewise-linear predictor-corrector code - A Lagrangian-remap method for astrophysical flows

NASA Technical Reports Server (NTRS)

Lufkin, Eric A.; Hawley, John F.

1993-01-01

We describe a time-explicit finite-difference algorithm for solving the nonlinear fluid equations. The method is similar to existing Eulerian schemes in its use of operator-splitting and artificial viscosity, except that we solve the Lagrangian equations of motion with a predictor-corrector and then remap onto a fixed Eulerian grid. The remap is formulated to eliminate errors associated with coordinate singularities, with a general prescription for remaps of arbitrary order. We perform a comprehensive series of tests on standard problems. Self-convergence tests show that the code has a second-order rate of convergence in smooth, two-dimensional flow, with pressure forces, gravity, and curvilinear geometry included. While not as accurate on idealized problems as high-order Riemann-solving schemes, the predictor-corrector Lagrangian-remap code has great flexibility for application to a variety of astrophysical problems.

Homotopy approach to optimal, linear quadratic, fixed architecture compensation

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1991-01-01

Optimal linear quadratic Gaussian compensators with constrained architecture are a sensible way to generate good multivariable feedback systems meeting strict implementation requirements. The optimality conditions obtained from the constrained linear quadratic Gaussian are a set of highly coupled matrix equations that cannot be solved algebraically except when the compensator is centralized and full order. An alternative to the use of general parameter optimization methods for solving the problem is to use homotopy. The benefit of the method is that it uses the solution to a simplified problem as a starting point and the final solution is then obtained by solving a simple differential equation. This paper investigates the convergence properties and the limitation of such an approach and sheds some light on the nature and the number of solutions of the constrained linear quadratic Gaussian problem. It also demonstrates the usefulness of homotopy on an example of an optimal decentralized compensator.

A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.

PubMed

Liu, Qingshan; Guo, Zhishan; Wang, Jun

2012-02-01

In this paper, a one-layer recurrent neural network is proposed for solving pseudoconvex optimization problems subject to linear equality and bound constraints. Compared with the existing neural networks for optimization (e.g., the projection neural networks), the proposed neural network is capable of solving more general pseudoconvex optimization problems with equality and bound constraints. Moreover, it is capable of solving constrained fractional programming problems as a special case. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds. Numerical examples with simulation results illustrate the effectiveness and characteristics of the proposed neural network. In addition, an application for dynamic portfolio optimization is discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

The “Cocktail Party Problem”: What Is It? How Can It Be Solved? And Why Should Animal Behaviorists Study It?

PubMed Central

Bee, Mark A.; Micheyl, Christophe

2009-01-01

Animals often use acoustic signals to communicate in groups or social aggregations in which multiple individuals signal within a receiver's hearing range. Consequently, receivers face challenges related to acoustic interference and auditory masking that are not unlike the human “cocktail party problem,” which refers to the problem of perceiving speech in noisy social settings. Understanding the sensory solutions to the cocktail party problem has been a goal of research on human hearing and speech communication for several decades. Despite a general interest in acoustic signaling in groups, animal behaviorists have devoted comparatively less attention toward understanding how animals solve problems equivalent to the human cocktail party problem. After illustrating how humans and non-human animals experience and overcome similar perceptual challenges in cocktail-party-like social environments, this article reviews previous psychophysical and physiological studies of humans and non-human animals to describe how the cocktail party problem can be solved. This review also outlines several basic and applied benefits that could result from studies of the cocktail party problem in the context of animal acoustic communication. PMID:18729652

The use of multiple representations and visualizations in student learning of introductory physics: An example from work and energy

NASA Astrophysics Data System (ADS)

Zou, Xueli

In the past three decades, physics education research has primarily focused on student conceptual understanding; little work has been conducted to investigate student difficulties in problem solving. In cognitive science and psychology, however, extensive studies have explored the differences in problem solving between experts and naive students. A major finding indicates that experts often apply qualitative representations in problem solving, but that novices use an equation-centered method. This dissertation describes investigations into the use of multiple representations and visualizations in student understanding and problem solving with the concepts of work and energy. A multiple-representation strategy was developed to help students acquire expertise in solving work-energy problems. In this approach, a typical work-energy problem is considered as a physical process. The process is first described in words-the verbal representation of the process. Next, a sketch or a picture, called a pictorial representation, is used to represent the process. This is followed by work-energy bar charts-a physical representation of the same processes. Finally, this process is represented mathematically by using a generalized work-energy equation. In terms of the multiple representations, the goal of solving a work- energy problem is to represent the physical process the more intuitive pictorial and diagrammatic physical representations. Ongoing assessment of student learning indicates that this multiple-representation technique is more effective than standard instruction methods in student problem solving. visualize this difficult-to-understand concept, a guided- inquiry learning activity using a pair of model carts and an experiment problem using a sandbag were developed. Assessment results have shown that these research-based materials are effective in helping students visualize this concept and give a pictorial idea of ``where the kinetic energy goes'' during inelastic collisions. The research and curriculum development was conducted in the context of the introductory calculus-based physics course. Investigations were carried out using common physics education research tools, including open-ended surveys, written test questions, and individual student interviews.

A Portfolio of Energy Ideas: Science.

ERIC Educational Resources Information Center

Clark, Richard C., Ed.

Ten units which focus on subject-matter knowledge about energy and on the logic and strategy of problem-solving within science are provided in this user's guide. Each unit includes: a detailed summary of unit problems and activities; recommended grade levels and subject areas; possible learner outcomes and general goals; teacher background…

Some Aspects of Science Education in European Context

ERIC Educational Resources Information Center

Naumescu, Adrienne Kozan; Pasca, Roxana-Diana

2008-01-01

Some up-to-date problems in science education in European context are treated in this paper. The characteristics of science education across Europe are presented. Science teachers' general competencies are underlined. An example of problem-solving as teaching method in chemistry is studied in knowledge based society. Transforming teacher practice…

Modelling Mathematical Reasoning in Physics Education

ERIC Educational Resources Information Center

Uhden, Olaf; Karam, Ricardo; Pietrocola, Mauricio; Pospiech, Gesche

2012-01-01

Many findings from research as well as reports from teachers describe students' problem solving strategies as manipulation of formulas by rote. The resulting dissatisfaction with quantitative physical textbook problems seems to influence the attitude towards the role of mathematics in physics education in general. Mathematics is often seen as a…

Network planning under uncertainties

NASA Astrophysics Data System (ADS)

Ho, Kwok Shing; Cheung, Kwok Wai

2008-11-01

One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a generic framework for solving the network planning problem under uncertainties. In addition to reviewing the various network planning problems involving uncertainties, we also propose that a unified framework based on robust optimization can be used to solve a rather large segment of network planning problem under uncertainties. Robust optimization is first introduced in the operations research literature and is a framework that incorporates information about the uncertainty sets for the parameters in the optimization model. Even though robust optimization is originated from tackling the uncertainty in the optimization process, it can serve as a comprehensive and suitable framework for tackling generic network planning problems under uncertainties. In this paper, we begin by explaining the main ideas behind the robust optimization approach. Then we demonstrate the capabilities of the proposed framework by giving out some examples of how the robust optimization framework can be applied to the current common network planning problems under uncertain environments. Next, we list some practical considerations for solving the network planning problem under uncertainties with the proposed framework. Finally, we conclude this article with some thoughts on the future directions for applying this framework to solve other network planning problems.

SDG Fermion-Pair Algebraic SO(12) and Sp(10) Models and Their Boson Realizations

NASA Astrophysics Data System (ADS)

Navratil, P.; Geyer, H. B.; Dobes, J.; Dobaczewski, J.

1995-11-01

It is shown how the boson mapping formalism may be applied as a useful many-body tool to solve a fermion problem. This is done in the context of generalized Ginocchio models for which we introduce S-, D-, and G-pairs of fermions and subsequently construct the sdg-boson realizations of the generalized Dyson type. The constructed SO(12) and Sp(10) fermion models are solved beyond the explicit symmetry limits. Phase transitions to rotational structures are obtained also in situations where there is no underlying SU(3) symmetry.

Empirical results on scheduling and dynamic backtracking

NASA Technical Reports Server (NTRS)

Boddy, Mark S.; Goldman, Robert P.

1994-01-01

At the Honeywell Technology Center (HTC), we have been working on a scheduling problem related to commercial avionics. This application is large, complex, and hard to solve. To be a little more concrete: 'large' means almost 20,000 activities, 'complex' means several activity types, periodic behavior, and assorted types of temporal constraints, and 'hard to solve' means that we have been unable to eliminate backtracking through the use of search heuristics. At this point, we can generate solutions, where solutions exist, or report failure and sometimes why the system failed. To the best of our knowledge, this is among the largest and most complex scheduling problems to have been solved as a constraint satisfaction problem, at least that has appeared in the published literature. This abstract is a preliminary report on what we have done and how. In the next section, we present our approach to treating scheduling as a constraint satisfaction problem. The following sections present the application in more detail and describe how we solve scheduling problems in the application domain. The implemented system makes use of Ginsberg's Dynamic Backtracking algorithm, with some minor extensions to improve its utility for scheduling. We describe those extensions and the performance of the resulting system. The paper concludes with some general remarks, open questions and plans for future work.

The Role of Hellinger Processes in Mathematical Finance

NASA Astrophysics Data System (ADS)

Choulli, T.; Hurd, T. R.

2001-09-01

This paper illustrates the natural role that Hellinger processes can play in solving problems from ¯nance. We propose an extension of the concept of Hellinger process applicable to entropy distance and f-divergence distances, where f is a convex logarithmic function or a convex power function with general order q, 0 6= q < 1. These concepts lead to a new approach to Merton's optimal portfolio problem and its dual in general L¶evy markets.

Learning to Solve Problems by Searching for Macro-Operators

DTIC Science & Technology

1983-07-01

executing generalized robot plans. Aritificial Intelligence 3:25 1-288, 1972. [Frey 821 Frey, Alexander Ii. Jr., and David Singmaster. Handbook of Cubik...and that searching for macros may be a useful general learning paradigm. 1.1. Introduction One view of die die field of artificial intelligence is that... intelligence literature [Schofield 67, Gaschnig 79, Ericsson 761 and provides one of the simplest examples of the operation of the Macro Problem Solver. It

Generalized vector calculus on convex domain

NASA Astrophysics Data System (ADS)

Agrawal, Om P.; Xu, Yufeng

2015-06-01

In this paper, we apply recently proposed generalized integral and differential operators to develop generalized vector calculus and generalized variational calculus for problems defined over a convex domain. In particular, we present some generalization of Green's and Gauss divergence theorems involving some new operators, and apply these theorems to generalized variational calculus. For fractional power kernels, the formulation leads to fractional vector calculus and fractional variational calculus for problems defined over a convex domain. In special cases, when certain parameters take integer values, we obtain formulations for integer order problems. Two examples are presented to demonstrate applications of the generalized variational calculus which utilize the generalized vector calculus developed in the paper. The first example leads to a generalized partial differential equation and the second example leads to a generalized eigenvalue problem, both in two dimensional convex domains. We solve the generalized partial differential equation by using polynomial approximation. A special case of the second example is a generalized isoperimetric problem. We find an approximate solution to this problem. Many physical problems containing integer order integrals and derivatives are defined over arbitrary domains. We speculate that future problems containing fractional and generalized integrals and derivatives in fractional mechanics will be defined over arbitrary domains, and therefore, a general variational calculus incorporating a general vector calculus will be needed for these problems. This research is our first attempt in that direction.

Quality-assurance study of the special - purpose finite-element program - SPECTROM: I. Thermal, thermoelastic, and viscoelastic problems. [Comparison with MARC-CDC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagner, R.A.

1980-12-01

This comparison study involves a preliminary verification of finite element calculations. The methodology of the comparison study consists of solving four example problems with both the SPECTROM finite element program and the MARC-CDC general purpose finite element program. The results show close agreement for all example problems.

Are Individual Differences in Performance on Perceptual and Cognitive Optimization Problems Determined by General Intelligence?

ERIC Educational Resources Information Center

Burns, Nicholas R.; Lee, Michael D.; Vickers, Douglas

2006-01-01

Studies of human problem solving have traditionally used deterministic tasks that require the execution of a systematic series of steps to reach a rational and optimal solution. Most real-world problems, however, are characterized by uncertainty, the need to consider an enormous number of variables and possible courses of action at each stage in…

The solution of private problems for optimization heat exchangers parameters

NASA Astrophysics Data System (ADS)

Melekhin, A.

2017-11-01

The relevance of the topic due to the decision of problems of the economy of resources in heating systems of buildings. To solve this problem we have developed an integrated method of research which allows solving tasks on optimization of parameters of heat exchangers. This method decides multicriteria optimization problem with the program nonlinear optimization on the basis of software with the introduction of an array of temperatures obtained using thermography. The author have developed a mathematical model of process of heat exchange in heat exchange surfaces of apparatuses with the solution of multicriteria optimization problem and check its adequacy to the experimental stand in the visualization of thermal fields, an optimal range of managed parameters influencing the process of heat exchange with minimal metal consumption and the maximum heat output fin heat exchanger, the regularities of heat exchange process with getting generalizing dependencies distribution of temperature on the heat-release surface of the heat exchanger vehicles, defined convergence of the results of research in the calculation on the basis of theoretical dependencies and solving mathematical model.

DESCRIPTION OF THE ENIAC CONVERTER CODE

DTIC Science & Technology

The report is intended as a working manual for personnel preparing problems for the ENIAC . It should also serve as a guide to those groups who have...computing problems that could be solved on the ENIAC . The report discusses the ENIAC from the point of view of the coder, describing its memory as well...accomplishes as well as how to use each instruction. A few remarks are made on the more general subject of problem preparation for large scale computers in general based on the experience of operating the ENIAC . (Author)

Stereoscopic image production: live, CGI, and integration

NASA Astrophysics Data System (ADS)

Criado, Enrique

2006-02-01

This paper shortly describes part of the experience gathered in more than 10 years of stereoscopic movie production, some of the most common problems found and the solutions, with more or less fortune, we applied to solve those problems. Our work is mainly focused in the entertainment market, theme parks, museums, and other cultural related locations and events. In our movies, we have been forced to develop our own devices to permit correct stereo shooting (stereoscopic rigs) or stereo monitoring (real-time), and to solve problems found with conventional film editing, compositing and postproduction software. Here, we discuss stereo lighting, monitoring, special effects, image integration (using dummies and more), stereo-camera parameters, and other general 3-D movie production aspects.

Computer Graphics-aided systems analysis: application to well completion design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Detamore, J.E.; Sarma, M.P.

1985-03-01

The development of an engineering tool (in the form of a computer model) for solving design and analysis problems related with oil and gas well production operations is discussed. The development of the method is based on integrating the concepts of ''Systems Analysis'' with the techniques of ''Computer Graphics''. The concepts behind the method are very general in nature. This paper, however, illustrates the application of the method in solving gas well completion design problems. The use of the method will save time and improve the efficiency of such design and analysis problems. The method can be extended to othermore » design and analysis aspects of oil and gas wells.« less

Moneymed: a game to develop management skills in general practice

PubMed Central

Essex, B.; Jackson, R. N.

1981-01-01

A game has been developed to train people in the financial and administrative skills needed for effective general practice management. These skills cover a wide range of legal, economic, administrative and personnel problems encountered in general practice. Thirty-four trainees and six trainers showed a highly significant improvement in knowledge and problem-solving skills after playing the game. The format and design of the game allow the problem type, complexity and solution to vary and to be readily updated. So far, this seems to be one of the most effective instruments yet developed for learning these skills. Imagesp736-a PMID:7338867

Toward Solving the Problem of Problem Solving: An Analysis Framework

ERIC Educational Resources Information Center

Roesler, Rebecca A.

2016-01-01

Teaching is replete with problem solving. Problem solving as a skill, however, is seldom addressed directly within music teacher education curricula, and research in music education has not examined problem solving systematically. A framework detailing problem-solving component skills would provide a needed foundation. I observed problem solving…

Advances in optimal routing through computer networks

NASA Technical Reports Server (NTRS)

Paz, I. M.

1977-01-01

The optimal routing problem is defined. Progress in solving the problem during the previous decade is reviewed, with special emphasis on technical developments made during the last few years. The relationships between the routing, the throughput, and the switching technology used are discussed and their future trends are reviewed. Economic aspects are also briefly considered. Modern technical approaches for handling the routing problems and, more generally, the flow control problems are reviewed.

Flight control with adaptive critic neural network

NASA Astrophysics Data System (ADS)

Han, Dongchen

2001-10-01

In this dissertation, the adaptive critic neural network technique is applied to solve complex nonlinear system control problems. Based on dynamic programming, the adaptive critic neural network can embed the optimal solution into a neural network. Though trained off-line, the neural network forms a real-time feedback controller. Because of its general interpolation properties, the neurocontroller has inherit robustness. The problems solved here are an agile missile control for U.S. Air Force and a midcourse guidance law for U.S. Navy. In the first three papers, the neural network was used to control an air-to-air agile missile to implement a minimum-time heading-reverse in a vertical plane corresponding to following conditions: a system without constraint, a system with control inequality constraint, and a system with state inequality constraint. While the agile missile is a one-dimensional problem, the midcourse guidance law is the first test-bed for multiple-dimensional problem. In the fourth paper, the neurocontroller is synthesized to guide a surface-to-air missile to a fixed final condition, and to a flexible final condition from a variable initial condition. In order to evaluate the adaptive critic neural network approach, the numerical solutions for these cases are also obtained by solving two-point boundary value problem with a shooting method. All of the results showed that the adaptive critic neural network could solve complex nonlinear system control problems.

Multiexponential models of (1+1)-dimensional dilaton gravity and Toda-Liouville integrable models

NASA Astrophysics Data System (ADS)

de Alfaro, V.; Filippov, A. T.

2010-01-01

We study general properties of a class of two-dimensional dilaton gravity (DG) theories with potentials containing several exponential terms. We isolate and thoroughly study a subclass of such theories in which the equations of motion reduce to Toda and Liouville equations. We show that the equation parameters must satisfy a certain constraint, which we find and solve for the most general multiexponential model. It follows from the constraint that integrable Toda equations in DG theories generally cannot appear without accompanying Liouville equations. The most difficult problem in the two-dimensional Toda-Liouville (TL) DG is to solve the energy and momentum constraints. We discuss this problem using the simplest examples and identify the main obstacles to solving it analytically. We then consider a subclass of integrable two-dimensional theories where scalar matter fields satisfy the Toda equations and the two-dimensional metric is trivial. We consider the simplest case in some detail. In this example, we show how to obtain the general solution. We also show how to simply derive wavelike solutions of general TL systems. In the DG theory, these solutions describe nonlinear waves coupled to gravity and also static states and cosmologies. For static states and cosmologies, we propose and study a more general one-dimensional TL model typically emerging in one-dimensional reductions of higher-dimensional gravity and supergravity theories. We especially attend to making the analytic structure of the solutions of the Toda equations as simple and transparent as possible.

Goals and everyday problem solving: examining the link between age-related goals and problem-solving strategy use.

PubMed

Hoppmann, Christiane A; Coats, Abby Heckman; Blanchard-Fields, Fredda

2008-07-01

Qualitative interviews on family and financial problems from 332 adolescents, young, middle-aged, and older adults, demonstrated that developmentally relevant goals predicted problem-solving strategy use over and above problem domain. Four focal goals concerned autonomy, generativity, maintaining good relationships with others, and changing another person. We examined both self- and other-focused problem-solving strategies. Autonomy goals were associated with self-focused instrumental problem solving and generative goals were related to other-focused instrumental problem solving in family and financial problems. Goals of changing another person were related to other-focused instrumental problem solving in the family domain only. The match between goals and strategies, an indicator of problem-solving adaptiveness, showed that young individuals displayed the greatest match between autonomy goals and self-focused problem solving, whereas older adults showed a greater match between generative goals and other-focused problem solving. Findings speak to the importance of considering goals in investigations of age-related differences in everyday problem solving.

Minimization of the root of a quadratic functional under a system of affine equality constraints with application to portfolio management

NASA Astrophysics Data System (ADS)

Landsman, Zinoviy

2008-10-01

We present an explicit closed form solution of the problem of minimizing the root of a quadratic functional subject to a system of affine constraints. The result generalizes Z. Landsman, Minimization of the root of a quadratic functional under an affine equality constraint, J. Comput. Appl. Math. 2007, to appear, see , articles in press, where the optimization problem was solved under only one linear constraint. This is of interest for solving significant problems pertaining to financial economics as well as some classes of feasibility and optimization problems which frequently occur in tomography and other fields. The results are illustrated in the problem of optimal portfolio selection and the particular case when the expected return of finance portfolio is certain is discussed.

Gravity with free initial conditions: A solution to the cosmological constant problem testable by CMB B -mode polarization

NASA Astrophysics Data System (ADS)

Totani, Tomonori

2017-10-01

In standard general relativity the universe cannot be started with arbitrary initial conditions, because four of the ten components of the Einstein's field equations (EFE) are constraints on initial conditions. In the previous work it was proposed to extend the gravity theory to allow free initial conditions, with a motivation to solve the cosmological constant problem. This was done by setting four constraints on metric variations in the action principle, which is reasonable because the gravity's physical degrees of freedom are at most six. However, there are two problems about this theory; the three constraints in addition to the unimodular condition were introduced without clear physical meanings, and the flat Minkowski spacetime is unstable against perturbations. Here a new set of gravitational field equations is derived by replacing the three constraints with new ones requiring that geodesic paths remain geodesic against metric variations. The instability problem is then naturally solved. Implications for the cosmological constant Λ are unchanged; the theory converges into EFE with nonzero Λ by inflation, but Λ varies on scales much larger than the present Hubble horizon. Then galaxies are formed only in small Λ regions, and the cosmological constant problem is solved by the anthropic argument. Because of the increased degrees of freedom in metric dynamics, the theory predicts new non-oscillatory modes of metric anisotropy generated by quantum fluctuation during inflation, and CMB B -mode polarization would be observed differently from the standard predictions by general relativity.

A Semi-Infinite Programming based algorithm for determining T-optimum designs for model discrimination

PubMed Central

Duarte, Belmiro P.M.; Wong, Weng Kee; Atkinson, Anthony C.

2016-01-01

T-optimum designs for model discrimination are notoriously difficult to find because of the computational difficulty involved in solving an optimization problem that involves two layers of optimization. Only a handful of analytical T-optimal designs are available for the simplest problems; the rest in the literature are found using specialized numerical procedures for a specific problem. We propose a potentially more systematic and general way for finding T-optimal designs using a Semi-Infinite Programming (SIP) approach. The strategy requires that we first reformulate the original minimax or maximin optimization problem into an equivalent semi-infinite program and solve it using an exchange-based method where lower and upper bounds produced by solving the outer and the inner programs, are iterated to convergence. A global Nonlinear Programming (NLP) solver is used to handle the subproblems, thus finding the optimal design and the least favorable parametric configuration that minimizes the residual sum of squares from the alternative or test models. We also use a nonlinear program to check the global optimality of the SIP-generated design and automate the construction of globally optimal designs. The algorithm is successfully used to produce results that coincide with several T-optimal designs reported in the literature for various types of model discrimination problems with normally distributed errors. However, our method is more general, merely requiring that the parameters of the model be estimated by a numerical optimization. PMID:27330230

A Semi-Infinite Programming based algorithm for determining T-optimum designs for model discrimination.

PubMed

Duarte, Belmiro P M; Wong, Weng Kee; Atkinson, Anthony C

2015-03-01

T-optimum designs for model discrimination are notoriously difficult to find because of the computational difficulty involved in solving an optimization problem that involves two layers of optimization. Only a handful of analytical T-optimal designs are available for the simplest problems; the rest in the literature are found using specialized numerical procedures for a specific problem. We propose a potentially more systematic and general way for finding T-optimal designs using a Semi-Infinite Programming (SIP) approach. The strategy requires that we first reformulate the original minimax or maximin optimization problem into an equivalent semi-infinite program and solve it using an exchange-based method where lower and upper bounds produced by solving the outer and the inner programs, are iterated to convergence. A global Nonlinear Programming (NLP) solver is used to handle the subproblems, thus finding the optimal design and the least favorable parametric configuration that minimizes the residual sum of squares from the alternative or test models. We also use a nonlinear program to check the global optimality of the SIP-generated design and automate the construction of globally optimal designs. The algorithm is successfully used to produce results that coincide with several T-optimal designs reported in the literature for various types of model discrimination problems with normally distributed errors. However, our method is more general, merely requiring that the parameters of the model be estimated by a numerical optimization.

Parallelized traveling cluster approximation to study numerically spin-fermion models on large lattices

NASA Astrophysics Data System (ADS)

Mukherjee, Anamitra; Patel, Niravkumar D.; Bishop, Chris; Dagotto, Elbio

2015-06-01

Lattice spin-fermion models are important to study correlated systems where quantum dynamics allows for a separation between slow and fast degrees of freedom. The fast degrees of freedom are treated quantum mechanically while the slow variables, generically referred to as the "spins," are treated classically. At present, exact diagonalization coupled with classical Monte Carlo (ED + MC) is extensively used to solve numerically a general class of lattice spin-fermion problems. In this common setup, the classical variables (spins) are treated via the standard MC method while the fermion problem is solved by exact diagonalization. The "traveling cluster approximation" (TCA) is a real space variant of the ED + MC method that allows to solve spin-fermion problems on lattice sizes with up to 103 sites. In this publication, we present a novel reorganization of the TCA algorithm in a manner that can be efficiently parallelized. This allows us to solve generic spin-fermion models easily on 104 lattice sites and with some effort on 105 lattice sites, representing the record lattice sizes studied for this family of models.

Resources in Technology: Problem-Solving.

ERIC Educational Resources Information Center

Technology Teacher, 1986

1986-01-01

This instructional module examines a key function of science and technology: problem solving. It studies the meaning of problem solving, looks at techniques for problem solving, examines case studies that exemplify the problem-solving approach, presents problems for the reader to solve, and provides a student self-quiz. (Author/CT)

Fuzzy α-minimum spanning tree problem: definition and solutions

NASA Astrophysics Data System (ADS)

Zhou, Jian; Chen, Lu; Wang, Ke; Yang, Fan

2016-04-01

In this paper, the minimum spanning tree problem is investigated on the graph with fuzzy edge weights. The notion of fuzzy ? -minimum spanning tree is presented based on the credibility measure, and then the solutions of the fuzzy ? -minimum spanning tree problem are discussed under different assumptions. First, we respectively, assume that all the edge weights are triangular fuzzy numbers and trapezoidal fuzzy numbers and prove that the fuzzy ? -minimum spanning tree problem can be transformed to a classical problem on a crisp graph in these two cases, which can be solved by classical algorithms such as the Kruskal algorithm and the Prim algorithm in polynomial time. Subsequently, as for the case that the edge weights are general fuzzy numbers, a fuzzy simulation-based genetic algorithm using Prüfer number representation is designed for solving the fuzzy ? -minimum spanning tree problem. Some numerical examples are also provided for illustrating the effectiveness of the proposed solutions.

Introduction of Mass Spectrometry in an First-Semester General Chemistry Laboratory Course: Quantification of Mtbe or Dmso in Water

ERIC Educational Resources Information Center

Solow, Mike

2004-01-01

Quantification of a contaminant in water provides the first-year general chemistry students with a tangible application of mass spectrometry. The relevance of chemistry to assessing and solving environmental problems is highlighted for students when they perform mass spectroscopy experiments.

Minding Your Own Small Business. Teacher's Manual.

ERIC Educational Resources Information Center

Athena Corp., Bethesda, MD.

The one-semester high school course in small business ownership/management for which this manual is designed is intended to easily articulate with both general and vocational education curricula. Focus of the course is on general management skills with opportunity to develop and practice problem solving, decisionmaking, and resource management.…

Examining the Generality of Self-Explanation

ERIC Educational Resources Information Center

Wylie, Ruth

2011-01-01

Prompting students to self-explain during problem solving has proven to be an effective instructional strategy across many domains. However, despite being called "domain general", very little work has been done in areas outside of math and science. In this dissertation, I investigate whether the self-explanation effect holds when applied…

Examination of the Computational Thinking Skills of Students

ERIC Educational Resources Information Center

Korucu, Agah Tugrul; Gencturk, Abdullah Tarik; Gundogdu, Mustafa Mucahit

2017-01-01

Computational thinking is generally considered as a kind of analytical way of thinking. According to Wings (2008) it shares with mathematical thinking, engineering thinking and scientific thinking in the general ways in which we may use for solving a problem, designing and evaluating complex systems or understanding computability and intelligence…

Deductive Error Diagnosis and Inductive Error Generalization for Intelligent Tutoring Systems.

ERIC Educational Resources Information Center

Hoppe, H. Ulrich

1994-01-01

Examines the deductive approach to error diagnosis for intelligent tutoring systems. Topics covered include the principles of the deductive approach to diagnosis; domain-specific heuristics to solve the problem of generalizing error patterns; and deductive diagnosis and the hypertext-based learning environment. (Contains 26 references.) (JLB)

Design of Intelligent Power Supply System for Expressway Tunnel

NASA Astrophysics Data System (ADS)

Wang, Li; Li, Yutong; Lin, Zimian

2018-01-01

Tunnel lighting program is one of the key points of tunnel infrastructure construction. As tunnels tend to handle remote locations, power supply line construction generally has been having the distance, investment, high cost characteristics. To solve this problem, we propose a green, environmentally friendly, energy-efficient lighting system. This program uses the piston-wind which cars within tunnel produce as the power and combines with solar energy, physical lighting to achieve it, which solves the problem of difficult and high cost of highway tunnel section, and provides new ideas for the future construction of tunnel power supply.

Application of a Modal Approach in Solving the Static Stability Problem for Electric Power Systems

NASA Astrophysics Data System (ADS)

Sharov, J. V.

2017-12-01

Application of a modal approach in solving the static stability problem for power systems is examined. It is proposed to use the matrix exponent norm as a generalized transition function of the power system disturbed motion. Based on the concept of a stability radius and the pseudospectrum of Jacobian matrix, the necessary and sufficient conditions for existence of the static margins were determined. The capabilities and advantages of the modal approach in designing centralized or distributed control and the prospects for the analysis of nonlinear oscillations and rendering the dynamic stability are demonstrated.

Numerical simulation of transient, incongruent vaporization induced by high power laser

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsai, C.H.

1981-01-01

A mathematical model and numerical calculations were developed to solve the heat and mass transfer problems specifically for uranum oxide subject to laser irradiation. It can easily be modified for other heat sources or/and other materials. In the uranium-oxygen system, oxygen is the preferentially vaporizing component, and as a result of the finite mobility of oxygen in the solid, an oxygen deficiency is set up near the surface. Because of the bivariant behavior of uranium oxide, the heat transfer problem and the oxygen diffusion problem are coupled and a numerical method of simultaneously solving the two boundary value problems ismore » studied. The temperature dependence of the thermal properties and oxygen diffusivity, as well as the highly ablative effect on the surface, leads to considerable non-linearities in both the governing differential equations and the boundary conditions. Based on the earlier work done in this laboratory by Olstad and Olander on Iron and on Zirconium hydride, the generality of the problem is expanded and the efficiency of the numerical scheme is improved. The finite difference method, along with some advanced numerical techniques, is found to be an efficient way to solve this problem.« less

Using genetic algorithms to determine near-optimal pricing, investment and operating strategies in the electric power industry

NASA Astrophysics Data System (ADS)

Wu, Dongjun

Network industries have technologies characterized by a spatial hierarchy, the "network," with capital-intensive interconnections and time-dependent, capacity-limited flows of products and services through the network to customers. This dissertation studies service pricing, investment and business operating strategies for the electric power network. First-best solutions for a variety of pricing and investment problems have been studied. The evaluation of genetic algorithms (GA, which are methods based on the idea of natural evolution) as a primary means of solving complicated network problems, both w.r.t. pricing: as well as w.r.t. investment and other operating decisions, has been conducted. New constraint-handling techniques in GAs have been studied and tested. The actual application of such constraint-handling techniques in solving practical non-linear optimization problems has been tested on several complex network design problems with encouraging initial results. Genetic algorithms provide solutions that are feasible and close to optimal when the optimal solution is know; in some instances, the near-optimal solutions for small problems by the proposed GA approach can only be tested by pushing the limits of currently available non-linear optimization software. The performance is far better than several commercially available GA programs, which are generally inadequate in solving any of the problems studied in this dissertation, primarily because of their poor handling of constraints. Genetic algorithms, if carefully designed, seem very promising in solving difficult problems which are intractable by traditional analytic methods.

A Cognitive Analysis of Students’ Mathematical Problem Solving Ability on Geometry

NASA Astrophysics Data System (ADS)

Rusyda, N. A.; Kusnandi, K.; Suhendra, S.

2017-09-01

The purpose of this research is to analyze of mathematical problem solving ability of students in one of secondary school on geometry. This research was conducted by using quantitative approach with descriptive method. Population in this research was all students of that school and the sample was twenty five students that was chosen by purposive sampling technique. Data of mathematical problem solving were collected through essay test. The results showed the percentage of achievement of mathematical problem solving indicators of students were: 1) solve closed mathematical problems with context in math was 50%; 2) solve the closed mathematical problems with the context beyond mathematics was 24%; 3) solving open mathematical problems with contexts in mathematics was 35%; And 4) solving open mathematical problems with contexts outside mathematics was 44%. Based on the percentage, it can be concluded that the level of achievement of mathematical problem solving ability in geometry still low. This is because students are not used to solving problems that measure mathematical problem solving ability, weaknesses remember previous knowledge, and lack of problem solving framework. So the students’ ability of mathematical problems solving need to be improved with implement appropriate learning strategy.

Modification of the nuclear landscape in the inverse problem framework using the generalized Bethe-Weizsäcker mass formula

NASA Astrophysics Data System (ADS)

Mavrodiev, S. Cht.; Deliyergiyev, M. A.

We formalized the nuclear mass problem in the inverse problem framework. This approach allows us to infer the underlying model parameters from experimental observation, rather than to predict the observations from the model parameters. The inverse problem was formulated for the numerically generalized semi-empirical mass formula of Bethe and von Weizsäcker. It was solved in a step-by-step way based on the AME2012 nuclear database. The established parametrization describes the measured nuclear masses of 2564 isotopes with a maximum deviation less than 2.6MeV, starting from the number of protons and number of neutrons equal to 1. The explicit form of unknown functions in the generalized mass formula was discovered in a step-by-step way using the modified least χ2 procedure, that realized in the algorithms which were developed by Lubomir Aleksandrov to solve the nonlinear systems of equations via the Gauss-Newton method, lets us to choose the better one between two functions with same χ2. In the obtained generalized model, the corrections to the binding energy depend on nine proton (2, 8, 14, 20, 28, 50, 82, 108, 124) and ten neutron (2, 8, 14, 20, 28, 50, 82, 124, 152, 202) magic numbers as well on the asymptotic boundaries of their influence. The obtained results were compared with the predictions of other models.

Learning through Business Games: Acquiring Competences within Virtual Realities

ERIC Educational Resources Information Center

Fortmuller, Richard

2009-01-01

The didactic function of business games is often seen only in the development of sociocommunicative competences and general problem-solving strategies. An equally important aspect of business games lies in the acquirement of technical and problem-oriented knowledge, which is the focus of this article. Moreover, this knowledge dimension is further…

Introductory Economic Geography: Problem-Solving or a Teaching Problem?

ERIC Educational Resources Information Center

Wheeler, James O.

Because economic geography is viewed as a field with too many different aspects for one person to master, teaching an introductory course in the subject poses the challenge of selecting an organizing theme. One specific approach, organized around higher level generalizations and theories, is the use of location theory. Coupling location theory…

Development and Technical Characteristics of a Team Decision-Making Assessment Tool: Decision Observation, Recording, and Analysis (DORA)

ERIC Educational Resources Information Center

Algozzine, Bob; Newton, J. Stephen; Horner, Robert H.; Todd, Anne W.; Algozzine, Kate

2012-01-01

Problem solving is fundamental to psychoeducational assessment practices and generally grounded in activities related to identifying problems, developing and refining hypotheses, generating solutions, developing and implementing actions, and evaluating outcomes. While the process is central to response-to-intervention practices as well, little…

Undergraduate Chemistry Students' Perceptions of and Misconceptions about Buffers and Buffer Problems

ERIC Educational Resources Information Center

Orgill, MaryKay; Sutherland, Aynsley

2008-01-01

Both upper- and lower-level chemistry students struggle with understanding the concept of buffers and with solving corresponding buffer problems. While it might be reasonable to expect general chemistry students to struggle with this abstract concept, it is surprising that upper-level students in analytical chemistry and biochemistry continue to…

Learning Ethics through Everyday Problems: Informed Consent

ERIC Educational Resources Information Center

Verdu, Fernando; Frances, Francesc; Castello, Ana

2012-01-01

The teaching of bioethics and its importance in clinical relationships is to a certain extent complicated when we address students of medicine, young people who are more used to dealing with and solving strictly clinical problems. Informed Consent is one of the aspects of professional practice that is generally and widely accepted in Western…

Traffic Flow - USMES Teacher Resource Book. Fourth Edition. Trial Edition.

ERIC Educational Resources Information Center

Keskulla, Jean

This Unified Sciences and Mathematics for Elementary Schools (USMES) unit challenges students to improve traffic flow at a problem location. The challenge is general enough to apply to many problem-solving situations in mathematics, science, social science, and language arts at any elementary school level (grades 1-8). The Teacher Resource Book…

Weighing the Benefits of Anchored Math Instruction for Students with Disabilities in General Education Classes.

ERIC Educational Resources Information Center

Bottge, Brian A.; Heinrichs, Mary; Mehta, Zara Dee; Hung, Ya-Hui

2002-01-01

A study examined the effectiveness of enhanced anchor instruction and traditional problem instruction in improving the problem-solving performance of 42 seventh-graders with and without disabilities in inclusive classrooms. Students without disabilities profited from contextualized instruction, but benefits for the students with disabilities were…

Bagnulo Heavy Fuel Internal Combustion Engine and Its Employment in Aviation

NASA Technical Reports Server (NTRS)

Fiore, Amedeo

1922-01-01

We see with great satisfaction that Bagnulo's studies and experiments on his high-speed, heavy-fuel engines, promise to solve not only the general problem of economical power and hence of thermal efficiency, but also all other special problems, of weight and space, and, what is still more important, range of error.

Solving Discipline Problems: Strategies for Classroom Teachers.

ERIC Educational Resources Information Center

Wolfgang, Charles H.; Glickman, Carl D.

This book provides classroom teachers with a variety of discipline models, techniques, methods, and constructs designed to enable them to move beyond a singular approach in handling classroom behavior problems. The book first discusses the Teacher Behavior Continuum (TBC) which shows the teacher the context of his or her own general behavior with…

The Role of Multiple Representations in the Understanding of Ideal Gas Problems

ERIC Educational Resources Information Center

Madden, Sean P.; Jones, Loretta L.; Rahm, Jrene

2011-01-01

This study examined the representational competence of students as they solved problems dealing with the temperature-pressure relationship for ideal gases. Seven students enrolled in a first-semester general chemistry course and two advanced undergraduate science majors participated in the study. The written work and transcripts from videotaped…

Conformal mapping for multiple terminals

PubMed Central

Wang, Weimin; Ma, Wenying; Wang, Qiang; Ren, Hao

2016-01-01

Conformal mapping is an important mathematical tool that can be used to solve various physical and engineering problems in many fields, including electrostatics, fluid mechanics, classical mechanics, and transformation optics. It is an accurate and convenient way to solve problems involving two terminals. However, when faced with problems involving three or more terminals, which are more common in practical applications, existing conformal mapping methods apply assumptions or approximations. A general exact method does not exist for a structure with an arbitrary number of terminals. This study presents a conformal mapping method for multiple terminals. Through an accurate analysis of boundary conditions, additional terminals or boundaries are folded into the inner part of a mapped region. The method is applied to several typical situations, and the calculation process is described for two examples of an electrostatic actuator with three electrodes and of a light beam splitter with three ports. Compared with previously reported results, the solutions for the two examples based on our method are more precise and general. The proposed method is helpful in promoting the application of conformal mapping in analysis of practical problems. PMID:27830746

LSENS: A General Chemical Kinetics and Sensitivity Analysis Code for homogeneous gas-phase reactions. Part 1: Theory and numerical solution procedures

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan

1994-01-01

LSENS, the Lewis General Chemical Kinetics and Sensitivity Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part 1 of a series of three reference publications that describe LENS, provide a detailed guide to its usage, and present many example problems. Part 1 derives the governing equations and describes the numerical solution procedures for the types of problems that can be solved. The accuracy and efficiency of LSENS are examined by means of various test problems, and comparisons with other methods and codes are presented. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions.

ASKI: A modular toolbox for scattering-integral-based seismic full waveform inversion and sensitivity analysis utilizing external forward codes

NASA Astrophysics Data System (ADS)

Schumacher, Florian; Friederich, Wolfgang

Due to increasing computational resources, the development of new numerically demanding methods and software for imaging Earth's interior remains of high interest in Earth sciences. Here, we give a description from a user's and programmer's perspective of the highly modular, flexible and extendable software package ASKI-Analysis of Sensitivity and Kernel Inversion-recently developed for iterative scattering-integral-based seismic full waveform inversion. In ASKI, the three fundamental steps of solving the seismic forward problem, computing waveform sensitivity kernels and deriving a model update are solved by independent software programs that interact via file output/input only. Furthermore, the spatial discretizations of the model space used for solving the seismic forward problem and for deriving model updates, respectively, are kept completely independent. For this reason, ASKI does not contain a specific forward solver but instead provides a general interface to established community wave propagation codes. Moreover, the third fundamental step of deriving a model update can be repeated at relatively low costs applying different kinds of model regularization or re-selecting/weighting the inverted dataset without need to re-solve the forward problem or re-compute the kernels. Additionally, ASKI offers the user sensitivity and resolution analysis tools based on the full sensitivity matrix and allows to compose customized workflows in a consistent computational environment. ASKI is written in modern Fortran and Python, it is well documented and freely available under terms of the GNU General Public License (http://www.rub.de/aski).

Solving multiconstraint assignment problems using learning automata.

PubMed

Horn, Geir; Oommen, B John

2010-02-01

This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the pioneering LA solutions to this problem, unequivocally demonstrates that LA can play an important role in solving complex combinatorial and integer optimization problems.

User's Manual: Thermal Radiation Analysis System TRASYS 2

NASA Technical Reports Server (NTRS)

Jensen, C. L.

1981-01-01

A digital computer software system with generalized capability to solve the radiation related aspects of thermal analysis problems is presented. When used in conjunction with a generalized thermal analysis program such as the systems improved numerical differencing analyzer program, any thermal problem that can be expressed in terms of a lumped parameter R-C thermal network can be solved. The function of TRASYS is twofold. It provides: (a) Internode radiation interchange data; and (b) Incident and absorbed heat rate data from environmental radiant heat sources. Data of both types is provided in a format directly usable by the thermal analyzer programs. The system allows the user to write his own executive or driver program which organizes and directs the program library routines toward solution of each specific problem in the most expeditious manner. The user also may write his own output routines, thus the system data output can directly interface with any thermal analyzer using the R-C network concept.

Topological defects in alternative theories to cosmic inflation and string cosmology

NASA Astrophysics Data System (ADS)

Alexander, Stephon H. S.

The physics of the Early Universe is described in terms of the inflationary paradigm, which is based on a marriage between Einstein's general theory of relativity minimally coupled to quantum field theory. Inflation was posed to solve some of the outstanding problems of the Standard Big Bang Cosmology (SBB) such as the horizon, formation of structure and monopole problems. Despite its observational and theoretical successes, inflation is plagued with fine tuning and initial singularity problems. On the other hand, superstring/M theory, a theory of quantum gravity, possesses symmetries which naturally avoid space-time singularities. This thesis investigates alternative theories to cosmic inflation for solving the initial singularity, horizon and monopole problems, making use of topological defects. It was proposed by Dvali, Liu and Vaschaspati that the monopole problem can be solved without inflation if domain walls "sweep" up the monopoles in the early universe, thus reducing their number density significantly. Necessary for this mechanism to work is the presence of an attractive force between the monopole and the domain wall as well as a channel for the monopole's unwinding. We show numerically and analytically in two field theory models that for global defects the attraction is a universal result but the unwinding is model specific. The second part of this thesis investigates a string/M theory inspired model for solving the horizon problem. It was proposed by Moffat, Albrecht and Magueijo that the horizon problem is solved with a "phase transition" associated with a varying speed of light before the surface of last scattering. We provide a string/M theory mechanism based on assuming that our space-time is a D-3 brane probing a bulk supergravity black hole bulk background. This mechanism provides the necessary time variation of the velocity of light to solve the horizon problem. We suggest a mechanism which stablilizes the speed of light on the D-3 brane. We finally address the cosmological initial singularity problem using the target space duality inherent in string/M theory. It was suggested by Brandenberger and Vafa that superstring theory can solve the singularity problem and in addition explain why only three spatial dimensions can become large. We show that under specific conditions this mechanism still persists when including the effects of D-branes.

Generalized Pattern Search methods for a class of nonsmooth optimization problems with structure

NASA Astrophysics Data System (ADS)

Bogani, C.; Gasparo, M. G.; Papini, A.

2009-07-01

We propose a Generalized Pattern Search (GPS) method to solve a class of nonsmooth minimization problems, where the set of nondifferentiability is included in the union of known hyperplanes and, therefore, is highly structured. Both unconstrained and linearly constrained problems are considered. At each iteration the set of poll directions is enforced to conform to the geometry of both the nondifferentiability set and the boundary of the feasible region, near the current iterate. This is the key issue to guarantee the convergence of certain subsequences of iterates to points which satisfy first-order optimality conditions. Numerical experiments on some classical problems validate the method.

An iterative method for tri-level quadratic fractional programming problems using fuzzy goal programming approach

NASA Astrophysics Data System (ADS)

Kassa, Semu Mitiku; Tsegay, Teklay Hailay

2017-08-01

Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of problems. In this paper, we investigate a tri-level programming problem with quadratic fractional objective functions at each of the three levels. A solution algorithm has been proposed by applying fuzzy goal programming approach and by reformulating the fractional constraints to equivalent but non-fractional non-linear constraints. Based on the transformed formulation, an iterative procedure is developed that can yield a satisfactory solution to the tri-level problem. The numerical results on various illustrative examples demonstrated that the proposed algorithm is very much promising and it can also be used to solve larger-sized as well as n-level problems of similar structure.

Lichenometry: Field Work for Schools and Colleges.

ERIC Educational Resources Information Center

Newton, Douglas P.; Newton, Lynn D.

1989-01-01

Lichenometry is described for use in the study of biology and physical weathering. Discussed are lichens in general and an outline for studying growth and ecology. A problem solving format is used. (CW)

Algebraic reasoning and bat-and-ball problem variants: Solving isomorphic algebra first facilitates problem solving later.

PubMed

Hoover, Jerome D; Healy, Alice F

2017-12-01

The classic bat-and-ball problem is used widely to measure biased and correct reasoning in decision-making. University students overwhelmingly tend to provide the biased answer to this problem. To what extent might reasoners be led to modify their judgement, and, more specifically, is it possible to facilitate problem solution by prompting participants to consider the problem from an algebraic perspective? One hundred ninety-seven participants were recruited to investigate the effect of algebraic cueing as a debiasing strategy on variants of the bat-and-ball problem. Participants who were cued to consider the problem algebraically were significantly more likely to answer correctly relative to control participants. Most of this cueing effect was confined to a condition that required participants to solve isomorphic algebra equations corresponding to the structure of bat-and-ball question types. On a subsequent critical question with differing item and dollar amounts presented without a cue, participants were able to generalize the learned information to significantly reduce overall bias. Math anxiety was also found to be significantly related to bat-and-ball problem accuracy. These results suggest that, under specific conditions, algebraic reasoning is an effective debiasing strategy on bat-and-ball problem variants, and provide the first documented evidence for the influence of math anxiety on Cognitive Reflection Test performance.

Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

PubMed

Li, Shuai; Li, Yangming

2013-10-28

The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

LSENS: A General Chemical Kinetics and Sensitivity Analysis Code for homogeneous gas-phase reactions. Part 3: Illustrative test problems

NASA Technical Reports Server (NTRS)

Bittker, David A.; Radhakrishnan, Krishnan

1994-01-01

LSENS, the Lewis General Chemical Kinetics and Sensitivity Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part 3 of a series of three reference publications that describe LSENS, provide a detailed guide to its usage, and present many example problems. Part 3 explains the kinetics and kinetics-plus-sensitivity analysis problems supplied with LSENS and presents sample results. These problems illustrate the various capabilities of, and reaction models that can be solved by, the code and may provide a convenient starting point for the user to construct the problem data file required to execute LSENS. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions.

When dogs look back: inhibition of independent problem-solving behaviour in domestic dogs (Canis lupus familiaris) compared with wolves (Canis lupus).

PubMed

Udell, Monique A R

2015-09-01

Domestic dogs have been recognized for their social sensitivity and aptitude in human-guided tasks. For example, prior studies have demonstrated that dogs look to humans when confronted with an unsolvable task; an action often interpreted as soliciting necessary help. Conversely, wolves persist on such tasks. While dogs' 'looking back' behaviour has been used as an example of socio-cognitive advancement, an alternative explanation is that pet dogs show less persistence on independent tasks more generally. In this study, pet dogs, shelter dogs and wolves were given up to three opportunities to open a solvable puzzle box: when subjects were with a neutral human caretaker, alone and when encouraged by the human. Wolves were more persistent and more successful on this task than dogs, with 80% average success rate for wolves versus a 5% average success rate for dogs in both the human-in and alone conditions. Dogs showed increased contact with the puzzle box during the encouragement condition, but only a moderate increase in problem-solving success. Social sensitivity appears to play an important role in pet and shelter dogs' willingness to engage in problem-solving behaviour, which could suggest generalized dependence on, or deference to, human action. © 2015 The Author(s).

Problem-solving variability in older spouses: how is it linked to problem-, person-, and couple-characteristics?

PubMed

Hoppmann, Christiane A; Blanchard-Fields, Fredda

2011-09-01

Problem-solving does not take place in isolation and often involves social others such as spouses. Using repeated daily life assessments from 98 older spouses (M age = 72 years; M marriage length = 42 years), the present study examined theoretical notions from social-contextual models of coping regarding (a) the origins of problem-solving variability and (b) associations between problem-solving and specific problem-, person-, and couple- characteristics. Multilevel models indicate that the lion's share of variability in everyday problem-solving is located at the level of the problem situation. Importantly, participants reported more proactive emotion regulation and collaborative problem-solving for social than nonsocial problems. We also found person-specific consistencies in problem-solving. That is, older spouses high in Neuroticism reported more problems across the study period as well as less instrumental problem-solving and more passive emotion regulation than older spouses low in Neuroticism. Contrary to expectations, relationship satisfaction was unrelated to problem-solving in the present sample. Results are in line with the stress and coping literature in demonstrating that everyday problem-solving is a dynamic process that has to be viewed in the broader context in which it occurs. Our findings also complement previous laboratory-based work on everyday problem-solving by underscoring the benefits of examining everyday problem-solving as it unfolds in spouses' own environment.

A Sequential Linear Quadratic Approach for Constrained Nonlinear Optimal Control with Adaptive Time Discretization and Application to Higher Elevation Mars Landing Problem

NASA Astrophysics Data System (ADS)

Sandhu, Amit

A sequential quadratic programming method is proposed for solving nonlinear optimal control problems subject to general path constraints including mixed state-control and state only constraints. The proposed algorithm further develops on the approach proposed in [1] with objective to eliminate the use of a high number of time intervals for arriving at an optimal solution. This is done by introducing an adaptive time discretization to allow formation of a desirable control profile without utilizing a lot of intervals. The use of fewer time intervals reduces the computation time considerably. This algorithm is further used in this thesis to solve a trajectory planning problem for higher elevation Mars landing.

Routine human-competitive machine intelligence by means of genetic programming

NASA Astrophysics Data System (ADS)

Koza, John R.; Streeter, Matthew J.; Keane, Martin

2004-01-01

Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

Scattering and bound states of spinless particles in a mixed vector-scalar smooth step potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garcia, M.G.; Castro, A.S. de

2009-11-15

Scattering and bound states for a spinless particle in the background of a kink-like smooth step potential, added with a scalar uniform background, are considered with a general mixing of vector and scalar Lorentz structures. The problem is mapped into the Schroedinger-like equation with an effective Rosen-Morse potential. It is shown that the scalar uniform background present subtle and trick effects for the scattering states and reveals itself a high-handed element for formation of bound states. In that process, it is shown that the problem of solving a differential equation for the eigenenergies is transmuted into the simpler and moremore » efficient problem of solving an irrational algebraic equation.« less

Quantifying risk and accuracy in cancer risk assessment: the process and its role in risk management problem-solving.

PubMed

Turturro, A; Hart, R W

1987-01-01

A better understanding of chemical-induced cancer has led to appreciation of similarities to problems addressed by risk management of radiation-induced toxicity. Techniques developed for cancer risk assessment of toxic substances can be generalized to toxic agents. A recent problem-solving approach for risk management of toxic substances developed for the U.S. Department of Health and Human Services, and the role of risk assessment and how uncertainty should be treated within the context of this approach, is discussed. Finally, two different methods, research into the assumptions underlying risk assessment and the modification of risk assessment/risk management documents, are used to illustrate how the technique can be applied.

Reference manual for the POISSON/SUPERFISH Group of Codes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1987-01-01

The POISSON/SUPERFISH Group codes were set up to solve two separate problems: the design of magnets and the design of rf cavities in a two-dimensional geometry. The first stage of either problem is to describe the layout of the magnet or cavity in a way that can be used as input to solve the generalized Poisson equation for magnets or the Helmholtz equations for cavities. The computer codes require that the problems be discretized by replacing the differentials (dx,dy) by finite differences ({delta}X,{delta}Y). Instead of defining the function everywhere in a plane, the function is defined only at a finitemore » number of points on a mesh in the plane.« less

Some new results on the central overlap problem in astrometry

NASA Astrophysics Data System (ADS)

Rapaport, M.

1998-07-01

The central overlap problem in astrometry has been revisited in the recent last years by Eichhorn (1988) who explicitly inverted the matrix of a constrained least squares problem. In this paper, the general explicit solution of the unconstrained central overlap problem is given. We also give the explicit solution for an other set of constraints; this result is a confirmation of a conjecture expressed by Eichhorn (1988). We also consider the use of iterative methods to solve the central overlap problem. A surprising result is obtained when the classical Gauss Seidel method is used; the iterations converge immediately to the general solution of the equations; we explain this property writing the central overlap problem in a new set of variables.

Graphical models for optimal power flow

DOE PAGES

Dvijotham, Krishnamurthy; Chertkov, Michael; Van Hentenryck, Pascal; ...

2016-09-13

Optimal power flow (OPF) is the central optimization problem in electric power grids. Although solved routinely in the course of power grid operations, it is known to be strongly NP-hard in general, and weakly NP-hard over tree networks. In this paper, we formulate the optimal power flow problem over tree networks as an inference problem over a tree-structured graphical model where the nodal variables are low-dimensional vectors. We adapt the standard dynamic programming algorithm for inference over a tree-structured graphical model to the OPF problem. Combining this with an interval discretization of the nodal variables, we develop an approximation algorithmmore » for the OPF problem. Further, we use techniques from constraint programming (CP) to perform interval computations and adaptive bound propagation to obtain practically efficient algorithms. Compared to previous algorithms that solve OPF with optimality guarantees using convex relaxations, our approach is able to work for arbitrary tree-structured distribution networks and handle mixed-integer optimization problems. Further, it can be implemented in a distributed message-passing fashion that is scalable and is suitable for “smart grid” applications like control of distributed energy resources. In conclusion, numerical evaluations on several benchmark networks show that practical OPF problems can be solved effectively using this approach.« less

Assessment of collaborative problem solving skills in Undergraduate Medical Students at Ziauddin College of Medicine, Karachi

PubMed Central

Mughal, Arsalan Manzoor; Shaikh, Sirajul Haque

2018-01-01

Objective: Collaborative Problem Solving Empirical Progressions from the Assessment and Teaching of 21st Century Skills (ATC21S) framework were used to determine the level of collaborative problem solving skills (CPS) in first, second and third year MBBS students at Ziauddin College of Medicine during Problem-Based Learning (PBL) sessions. Variations based on gender and roles were studied. Methods: It is an analytical comparative cross-sectional study in which seven PBL groups were selected per year by non-probability convenient sampling. Data was collected using the Collaborative Problem Solving Five Strands Empirical Progressions by the primary investigator through observation of the students during PBL sessions. Duration of study was six months. Results: We found that in our students, development of social dimension skills is facilitated to a greater extent than the development of cognitive dimension skills through the process of PBL. These skills are generally better developed in the leader compared to the scribe and members in a group. They are also more developed in females compared to males. Modification in them is also observed as the year's progress. Conclusion: Although PBLs facilitate development of CPS skills' progression however in our curriculum, PBLs mainly focus on social skills development and have less emphasis on cognitive skill development. Thus, hybrid instructional strategies with components from TBL and mentorship are recommended for better development of CPS skills. PMID:29643904

Assessment of collaborative problem solving skills in Undergraduate Medical Students at Ziauddin College of Medicine, Karachi.

PubMed

Mughal, Arsalan Manzoor; Shaikh, Sirajul Haque

2018-01-01

Collaborative Problem Solving Empirical Progressions from the Assessment and Teaching of 21st Century Skills (ATC21S) framework were used to determine the level of collaborative problem solving skills (CPS) in first, second and third year MBBS students at Ziauddin College of Medicine during Problem-Based Learning (PBL) sessions. Variations based on gender and roles were studied. It is an analytical comparative cross-sectional study in which seven PBL groups were selected per year by non-probability convenient sampling. Data was collected using the Collaborative Problem Solving Five Strands Empirical Progressions by the primary investigator through observation of the students during PBL sessions. Duration of study was six months. We found that in our students, development of social dimension skills is facilitated to a greater extent than the development of cognitive dimension skills through the process of PBL. These skills are generally better developed in the leader compared to the scribe and members in a group. They are also more developed in females compared to males. Modification in them is also observed as the year's progress. Although PBLs facilitate development of CPS skills' progression however in our curriculum, PBLs mainly focus on social skills development and have less emphasis on cognitive skill development. Thus, hybrid instructional strategies with components from TBL and mentorship are recommended for better development of CPS skills.

20 CFR 664.205 - How is the “deficient in basic literacy skills” criterion in § 664.200(c)(1) defined and documented?

Code of Federal Regulations, 2010 CFR

2010-04-01

... State or local concerns, and must include a determination that an individual: (1) Computes or solves problems, reads, writes, or speaks English at or below the 8th grade level on a generally accepted standardized test or a comparable score on a criterion-referenced test; or (2) Is unable to compute or solve...

LORENE: Spectral methods differential equations solver

NASA Astrophysics Data System (ADS)

Gourgoulhon, Eric; Grandclément, Philippe; Marck, Jean-Alain; Novak, Jérôme; Taniguchi, Keisuke

2016-08-01

LORENE (Langage Objet pour la RElativité NumériquE) solves various problems arising in numerical relativity, and more generally in computational astrophysics. It is a set of C++ classes and provides tools to solve partial differential equations by means of multi-domain spectral methods. LORENE classes implement basic structures such as arrays and matrices, but also abstract mathematical objects, such as tensors, and astrophysical objects, such as stars and black holes.

Exploiting Quantum Resonance to Solve Combinatorial Problems

NASA Technical Reports Server (NTRS)

Zak, Michail; Fijany, Amir

2006-01-01

Quantum resonance would be exploited in a proposed quantum-computing approach to the solution of combinatorial optimization problems. In quantum computing in general, one takes advantage of the fact that an algorithm cannot be decoupled from the physical effects available to implement it. Prior approaches to quantum computing have involved exploitation of only a subset of known quantum physical effects, notably including parallelism and entanglement, but not including resonance. In the proposed approach, one would utilize the combinatorial properties of tensor-product decomposability of unitary evolution of many-particle quantum systems for physically simulating solutions to NP-complete problems (a class of problems that are intractable with respect to classical methods of computation). In this approach, reinforcement and selection of a desired solution would be executed by means of quantum resonance. Classes of NP-complete problems that are important in practice and could be solved by the proposed approach include planning, scheduling, search, and optimal design.

The Circle of Apollonius and Its Applications in Introductory Physics

NASA Astrophysics Data System (ADS)

Partensky, Michael B.

2008-02-01

The circle of Apollonius is named after the ancient geometrician Apollonius of Perga. This beautiful geometric construct can be helpful when solving some general problems of geometry and mathematical physics, optics, and electricity. Here we discuss two of its applications: localizing an object in space and calculating electric fields. First, we pose an entertaining localization problem to trigger students' interest in the subject. Analyzing this problem, we introduce the circle of Apollonius and show that this geometric technique helps solve the problem in an elegant and intuitive manner. Then we switch to seemingly unrelated problems of calculating the electric fields. We show that the zero equipotential line for two unlike charges is the Apollonius circle for these two charges and use this discovery to find the electric field of a charge positioned near a grounded conductive sphere. Finally, we pose some questions for further examination.

Virtual and Concrete Manipulatives: A Comparison of Approaches for Solving Mathematics Problems for Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Bouck, Emily C.; Satsangi, Rajiv; Doughty, Teresa Taber; Courtney, William T.

2014-01-01

Students with autism spectrum disorder (ASD) are included in general education classes and expected to participate in general education content, such as mathematics. Yet, little research explores academically-based mathematics instruction for this population. This single subject alternating treatment design study explored the effectiveness of…

Strategy Generalization across Orientation Tasks: Testing a Computational Cognitive Model

ERIC Educational Resources Information Center

Gunzelmann, Glenn

2008-01-01

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human…

Modeling the missile-launch tube problem in DYSCO

NASA Technical Reports Server (NTRS)

Berman, Alex; Gustavson, Bruce A.

1989-01-01

DYSCO is a versatile, general purpose dynamic analysis program which assembles equations and solves dynamics problems. The executive manages a library of technology modules which contain routines that compute the matrix coefficients of the second order ordinary differential equations of the components. The executive performs the coupling of the equations of the components and manages the solution of the coupled equations. Any new component representation may be added to the library if, given the state vector, a FORTRAN program can be written to compute M, C, K, and F. The problem described demonstrates the generality of this statement.

Local polynomial chaos expansion for linear differential equations with high dimensional random inputs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yi; Jakeman, John; Gittelson, Claude

2015-01-08

In this paper we present a localized polynomial chaos expansion for partial differential equations (PDE) with random inputs. In particular, we focus on time independent linear stochastic problems with high dimensional random inputs, where the traditional polynomial chaos methods, and most of the existing methods, incur prohibitively high simulation cost. Furthermore, the local polynomial chaos method employs a domain decomposition technique to approximate the stochastic solution locally. In each subdomain, a subdomain problem is solved independently and, more importantly, in a much lower dimensional random space. In a postprocesing stage, accurate samples of the original stochastic problems are obtained frommore » the samples of the local solutions by enforcing the correct stochastic structure of the random inputs and the coupling conditions at the interfaces of the subdomains. Overall, the method is able to solve stochastic PDEs in very large dimensions by solving a collection of low dimensional local problems and can be highly efficient. In our paper we present the general mathematical framework of the methodology and use numerical examples to demonstrate the properties of the method.« less

Problem solving during artificial selection of self-replicating loops

NASA Astrophysics Data System (ADS)

Chou, Hui-Hsien; Reggia, James A.

1998-05-01

Past cellular automata models of self-replication have generally done only one thing: replicate themselves. However, it has recently been demonstrated that such self-replicating structures can be programmed to also carry out a task during the replication process. Past models of this sort have been limited in that the “program” involved is copied unchanged from parent to child, so that each generation of replicants is executing exactly the same program on exactly the same data. Here we take a different approach in which each replicant receives a distinct partial solution that is modified during replication. Under artificial selection, replicants with promising solutions proliferate while those with failed solutions are lost. We show that this approach can be applied successfully to solve an NP-complete problem, the satisfiability problem. Bounds are given on the cellular space size and time needed to solve a given problem, and simulations demonstrate that this approach works effectively. These and other recent results raise the possibility of evolving self-replicating structures that have a simulated metabolism or that carry out useful tasks.

Building up explanations in physics teaching

NASA Astrophysics Data System (ADS)

Pessoa de Carvalho, Anna Maria; Paulo, Sao

2004-02-01

The purpose of this research project was to study how students in the first years of elementary school (children from 7 to 10 years of age) are initiated into the construction of explanations of physical phenomena in the teaching of science. With this purpose in mind, we organized classes based on the proposition of investigative problems, where children, working in groups, could solve problems by raising and testing their own hypotheses. They would then attempt, by means of general discussion organized by the teacher, to discuss how each problem was solved and why it worked. We videotaped a series of classes in which the students solved 15 different investigative problems. We also analysed the teacher/student interactions that took place (in this paper, we present data on two of these classes). Based on our data we found that students construct their own causal explanations by following a sequence of stages that includes the appearance of novelties. We also discuss how our data relate to the teacher's role in the classroom and to the organization of science teaching at this level.

Search and Coherence-Building in Intuition and Insight Problem Solving.

PubMed

Öllinger, Michael; von Müller, Albrecht

2017-01-01

Coherence-building is a key concept for a better understanding of the underlying mechanisms of intuition and insight problem solving. There are several accounts that address certain aspects of coherence-building. However, there is still no proper framework defining the general principles of coherence-building. We propose a four-stage model of coherence-building. The first stage starts with spreading activation restricted by constraints. This dynamic is a well-defined rule based process. The second stage is characterized by detecting a coherent state. We adopted a fluency account assuming that the ease of information processing indicates the realization of a coherent state. The third stage is designated to evaluate the result of the coherence-building process and assess whether the given problem is solved or not. If the coherent state does not fit the requirements of the task, the process re-enters at stage 1. These three stages characterize intuition. For insight problem solving a fourth stage is necessary, which restructures the given representation after repeated failure, so that a new search space results. The new search space enables new coherent states. We provide a review of the most important findings, outline our model, present a large number of examples, deduce potential new paradigms and measures that might help to decipher the underlying cognitive processes.

Search and Coherence-Building in Intuition and Insight Problem Solving

PubMed Central

Öllinger, Michael; von Müller, Albrecht

2017-01-01

Coherence-building is a key concept for a better understanding of the underlying mechanisms of intuition and insight problem solving. There are several accounts that address certain aspects of coherence-building. However, there is still no proper framework defining the general principles of coherence-building. We propose a four-stage model of coherence-building. The first stage starts with spreading activation restricted by constraints. This dynamic is a well-defined rule based process. The second stage is characterized by detecting a coherent state. We adopted a fluency account assuming that the ease of information processing indicates the realization of a coherent state. The third stage is designated to evaluate the result of the coherence-building process and assess whether the given problem is solved or not. If the coherent state does not fit the requirements of the task, the process re-enters at stage 1. These three stages characterize intuition. For insight problem solving a fourth stage is necessary, which restructures the given representation after repeated failure, so that a new search space results. The new search space enables new coherent states. We provide a review of the most important findings, outline our model, present a large number of examples, deduce potential new paradigms and measures that might help to decipher the underlying cognitive processes. PMID:28611702

New Existence Conditions for Order Complementarity Problems

NASA Astrophysics Data System (ADS)

Németh, S. Z.

2009-09-01

Complementarity problems are mathematical models of problems in economics, engineering and physics. A special class of complementarity problems are the order complementarity problems [2]. Order complementarity problems can be applied in lubrication theory [6] and economics [1]. The notion of exceptional family of elements for general order complementarity problems in Banach spaces will be introduced. It will be shown that for general order complementarity problems defined by completely continuous fields the problem has either a solution or an exceptional family of elements (for other notions of exceptional family of elements see [1, 2, 3, 4] and the related references therein). This solves a conjecture of [2] about the existence of exceptional family of elements for order complementarity problems. The proof can be done by using the Leray-Schauder alternative [5]. An application to integral operators will be given.

Shear free, twisting Einstein-Maxwell metrics in the Newman-Penrose formalism

NASA Technical Reports Server (NTRS)

Lind, R. W.

1972-01-01

The problem of finding algebraically special solutions to the vacuum Einstein-Maxwell equations was investigated using a spin coefficient formalism. The general case in which the degenerate null vectors are not hypersurface orthogonal is reduced to a problem of solving five coupled differential equations that are no longer dependent on the affine parameter along the degenerate null directions. It is shown that the most general regular, shear-free, nonradiating solution to these equations is the Kerr-Newman metric.

Students’ difficulties in probabilistic problem-solving

NASA Astrophysics Data System (ADS)

Arum, D. P.; Kusmayadi, T. A.; Pramudya, I.

2018-03-01

There are many errors can be identified when students solving mathematics problems, particularly in solving the probabilistic problem. This present study aims to investigate students’ difficulties in solving the probabilistic problem. It focuses on analyzing and describing students errors during solving the problem. This research used the qualitative method with case study strategy. The subjects in this research involve ten students of 9th grade that were selected by purposive sampling. Data in this research involve students’ probabilistic problem-solving result and recorded interview regarding students’ difficulties in solving the problem. Those data were analyzed descriptively using Miles and Huberman steps. The results show that students have difficulties in solving the probabilistic problem and can be divided into three categories. First difficulties relate to students’ difficulties in understanding the probabilistic problem. Second, students’ difficulties in choosing and using appropriate strategies for solving the problem. Third, students’ difficulties with the computational process in solving the problem. Based on the result seems that students still have difficulties in solving the probabilistic problem. It means that students have not able to use their knowledge and ability for responding probabilistic problem yet. Therefore, it is important for mathematics teachers to plan probabilistic learning which could optimize students probabilistic thinking ability.

Eigenmode computation of cavities with perturbed geometry using matrix perturbation methods applied on generalized eigenvalue problems

NASA Astrophysics Data System (ADS)

Gorgizadeh, Shahnam; Flisgen, Thomas; van Rienen, Ursula

2018-07-01

Generalized eigenvalue problems are standard problems in computational sciences. They may arise in electromagnetic fields from the discretization of the Helmholtz equation by for example the finite element method (FEM). Geometrical perturbations of the structure under concern lead to a new generalized eigenvalue problems with different system matrices. Geometrical perturbations may arise by manufacturing tolerances, harsh operating conditions or during shape optimization. Directly solving the eigenvalue problem for each perturbation is computationally costly. The perturbed eigenpairs can be approximated using eigenpair derivatives. Two common approaches for the calculation of eigenpair derivatives, namely modal superposition method and direct algebraic methods, are discussed in this paper. Based on the direct algebraic methods an iterative algorithm is developed for efficiently calculating the eigenvalues and eigenvectors of the perturbed geometry from the eigenvalues and eigenvectors of the unperturbed geometry.

Engineering design: A cognitive process approach

NASA Astrophysics Data System (ADS)

Strimel, Greg Joseph

The intent of this dissertation was to identify the cognitive processes used by advanced pre-engineering students to solve complex engineering design problems. Students in technology and engineering education classrooms are often taught to use an ideal engineering design process that has been generated mostly by educators and curriculum developers. However, the review of literature showed that it is unclear as to how advanced pre-engineering students cognitively navigate solving a complex and multifaceted problem from beginning to end. Additionally, it was unclear how a student thinks and acts throughout their design process and how this affects the viability of their solution. Therefore, Research Objective 1 was to identify the fundamental cognitive processes students use to design, construct, and evaluate operational solutions to engineering design problems. Research Objective 2 was to determine identifiers within student cognitive processes for monitoring aptitude to successfully design, construct, and evaluate technological solutions. Lastly, Research Objective 3 was to create a conceptual technological and engineering problem-solving model integrating student cognitive processes for the improved development of problem-solving abilities. The methodology of this study included multiple forms of data collection. The participants were first given a survey to determine their prior experience with engineering and to provide a description of the subjects being studied. The participants were then presented an engineering design challenge to solve individually. While they completed the challenge, the participants verbalized their thoughts using an established "think aloud" method. These verbalizations were captured along with participant observational recordings using point-of-view camera technology. Additionally, the participant design journals, design artifacts, solution effectiveness data, and teacher evaluations were collected for analysis to help achieve the research objectives of this study. Two independent coders then coded the video/audio recordings and the additional design data using Halfin's (1973) 17 mental processes for technological problem-solving. The results of this study indicated that the participants employed a wide array of mental processes when solving engineering design challenges. However, the findings provide a general analysis of the number of times participants employed each mental process, as well as the amount of time consumed employing the various mental processes through the different stages of the engineering design process. The results indicated many similarities between the students solving the problem, which may highlight voids in current technology and engineering education curricula. Additionally, the findings showed differences between the processes employed by participants that created the most successful solutions and the participants who developed the least effective solutions. Upon comparing and contrasting these processes, recommendations for instructional strategies to enhance a student's capability for solving engineering design problems were developed. The results also indicated that students, when left without teacher intervention, use a simplified and more natural process to solve design challenges than the 12-step engineering design process reported in much of the literature. Lastly, these data indicated that students followed two different approaches to solving the design problem. Some students employed a sequential and logical approach, while others employed a nebulous, solution centered trial-and-error approach to solving the problem. In this study the participants who were more sequential had better performing solutions. Examining these two approaches and the student cognition data enabled the researcher to generate a conceptual engineering design model for the improved teaching and development of engineering design problem solving.

Producing or reproducing reasoning? Socratic dialog is very effective, but only for a few.

PubMed

Goldin, Andrea Paula; Pedroncini, Olivia; Sigman, Mariano

2017-01-01

Successful communication between a teacher and a student is at the core of pedagogy. A well known example of a pedagogical dialog is 'Meno', a socratic lesson of geometry in which a student learns (or 'discovers') how to double the area of a given square 'in essence, a demonstration of Pythagoras' theorem. In previous studies we found that after engaging in the dialog participants can be divided in two kinds: those who can only apply a rule to solve the problem presented in the dialog and those who can go beyond and generalize that knowledge to solve any square problems. Here we study the effectiveness of this socratic dialog in an experimental and a control high-school classrooms, and we explore the boundaries of what is learnt by testing subjects with a set of 9 problems of varying degrees of difficulty. We found that half of the adolescents did not learn anything from the dialog. The other half not only learned to solve the problem, but could abstract something more: the geometric notion that the diagonal can be used to solve diverse area problems. Conceptual knowledge is critical for achievement in geometry, and it is not clear whether geometric concepts emerge spontaneously on the basis of universal experience with space, or reflect intrinsic properties of the human mind. We show that, for half of the learners, an exampled-based Socratic dialog in lecture form can give rise to formal geometric knowledge that can be applied to new, different problems.

The dynamics of search, impasse, and representational change provide a coherent explanation of difficulty in the nine-dot problem.

PubMed

Öllinger, Michael; Jones, Gary; Knoblich, Günther

2014-03-01

The nine-dot problem is often used to demonstrate and explain mental impasse, creativity, and out of the box thinking. The present study investigated the interplay of a restricted initial search space, the likelihood of invoking a representational change, and the subsequent constraining of an unrestricted search space. In three experimental conditions, participants worked on different versions of the nine-dot problem that hinted at removing particular sources of difficulty from the standard problem. The hints were incremental such that the first suggested a possible route for a solution attempt; the second additionally indicated the dot at which lines meet on the solution path; and the final condition also provided non-dot locations that appear in the solution path. The results showed that in the experimental conditions, representational change is encountered more quickly and problems are solved more often than for the control group. We propose a cognitive model that focuses on general problem-solving heuristics and representational change to explain problem difficulty.

EPA Unmix 6.0 Fundamentals & User Guide

EPA Pesticide Factsheets

Unmix seeks to solve the general mixture problem where the data are assumed to be a linear combination of an unknown number of sources of unknown composition, which contribute an unknown amount to each sample.

Infinite Possibilities for the Finite Element.

ERIC Educational Resources Information Center

Finlayson, Bruce A.

1981-01-01

Describes the uses of finite element methods in solving problems of heat transfer, fluid flow, etc. Suggests that engineers should know the general concepts and be able to apply the principles of finite element methods. (Author/WB)

Federal Aviation Administration's Runway Incursion Program

DOT National Transportation Integrated Search

1997-12-08

To reverse the upward trend in runway incursions, FAA must have a strong : Runway Incursion Program to solve systemwide problems and expedite : solutions. The Office of Inspector General report recommends that FAA (1) assign specific responsibility f...

A comparison of spontaneous problem-solving abilities in three estrildid finch (Taeniopygia guttata, Lonchura striata var. domestica, Stagonopleura guttata) species.

PubMed

Schmelz, Martin; Krüger, Oliver; Call, Josep; Krause, E Tobias

2015-11-01

Cognition has been extensively studied in primates while other, more distantly related taxa have been neglected for a long time. More recently, there has been an increased interest in avian cognition, with the focus mostly on big-brained species like parrots and corvids. However, the majority of bird species has never systematically been studied in diverse cognitive tasks other than memory and learning tasks, so not much can yet be concluded about the relevant factors for the evolution of cognition. Here we examined 3 species of the estrildid finch family in problem-solving tasks. These granivorous, non-tool-using birds are distributed across 3 continents and are not known for high levels of innovation or spontaneous problem solving in the wild. In this study, our aim was to find such abilities in these species, assess what role domestication might play with a comparison of 4 genetically separated zebra finch strains, and to look for between-species differences between zebra finches, Bengalese finches, and diamond firetails. Furthermore, we established a 3-step spontaneous problem-solving procedure with increasing levels of complexity. Results showed that some estrildid finches were generally capable of spontaneously solving problems of variable complexity to obtain food. We found striking differences in these abilities between species, but not between strains within species, and offer a discussion of potential reasons. Our established methodology can now be applied to a larger number of bird species for phylogenetic comparisons on the behavioral level to get a deeper understanding of the evolution of cognitive abilities. (c) 2015 APA, all rights reserved).

A numerical projection technique for large-scale eigenvalue problems

NASA Astrophysics Data System (ADS)

Gamillscheg, Ralf; Haase, Gundolf; von der Linden, Wolfgang

2011-10-01

We present a new numerical technique to solve large-scale eigenvalue problems. It is based on the projection technique, used in strongly correlated quantum many-body systems, where first an effective approximate model of smaller complexity is constructed by projecting out high energy degrees of freedom and in turn solving the resulting model by some standard eigenvalue solver. Here we introduce a generalization of this idea, where both steps are performed numerically and which in contrast to the standard projection technique converges in principle to the exact eigenvalues. This approach is not just applicable to eigenvalue problems encountered in many-body systems but also in other areas of research that result in large-scale eigenvalue problems for matrices which have, roughly speaking, mostly a pronounced dominant diagonal part. We will present detailed studies of the approach guided by two many-body models.

A generalized Condat's algorithm of 1D total variation regularization

NASA Astrophysics Data System (ADS)

Makovetskii, Artyom; Voronin, Sergei; Kober, Vitaly

2017-09-01

A common way for solving the denosing problem is to utilize the total variation (TV) regularization. Many efficient numerical algorithms have been developed for solving the TV regularization problem. Condat described a fast direct algorithm to compute the processed 1D signal. Also there exists a direct algorithm with a linear time for 1D TV denoising referred to as the taut string algorithm. The Condat's algorithm is based on a dual problem to the 1D TV regularization. In this paper, we propose a variant of the Condat's algorithm based on the direct 1D TV regularization problem. The usage of the Condat's algorithm with the taut string approach leads to a clear geometric description of the extremal function. Computer simulation results are provided to illustrate the performance of the proposed algorithm for restoration of degraded signals.

Algorithm 937: MINRES-QLP for Symmetric and Hermitian Linear Equations and Least-Squares Problems.

PubMed

Choi, Sou-Cheng T; Saunders, Michael A

2014-02-01

We describe algorithm MINRES-QLP and its FORTRAN 90 implementation for solving symmetric or Hermitian linear systems or least-squares problems. If the system is singular, MINRES-QLP computes the unique minimum-length solution (also known as the pseudoinverse solution), which generally eludes MINRES. In all cases, it overcomes a potential instability in the original MINRES algorithm. A positive-definite pre-conditioner may be supplied. Our FORTRAN 90 implementation illustrates a design pattern that allows users to make problem data known to the solver but hidden and secure from other program units. In particular, we circumvent the need for reverse communication. Example test programs input and solve real or complex problems specified in Matrix Market format. While we focus here on a FORTRAN 90 implementation, we also provide and maintain MATLAB versions of MINRES and MINRES-QLP.

A Scenario-Based Parametric Analysis of Stable Marriage Approaches to the Army Officer Assignment Problem

DTIC Science & Technology

2017-03-23

solutions obtained through their proposed method to comparative instances of a generalized assignment problem with either ordinal cost components or... method flag: Designates the method by which the changed/ new assignment problem instance is solved. methodFlag = 0:SMAWarmstart Returns a matching...of randomized perturbations. We examine the contrasts between these methods in the context of assigning Army Officers among a set of identified

Conceptualizing Teaching as Science: John Dewey in Dialogue with the National Research Council

ERIC Educational Resources Information Center

Seals, Greg

2004-01-01

John Dewey and the National Research Council NRC both discuss the problem of translating scientific research into contexts of schooling, but differ about the proper solution to the problem. The NRC would solve it by empirical investigation. Dewey finds value in that approach, but also wants educational theorists to construct general heuristics to…

Anodal Transcranial Direct Current Stimulation of the Prefrontal Cortex Enhances Complex Verbal Associative Thought

ERIC Educational Resources Information Center

Cerruti, Carlo; Schlaug, Gottfried

2009-01-01

The remote associates test (RAT) is a complex verbal task with associations to both creative thought and general intelligence. RAT problems require not only lateral associations and the internal production of many words but a convergent focus on a single answer. Complex problem-solving of this sort may thus require both substantial verbal…

Developmental Changes in Problem Solving as a Function of Level of Socialization.

ERIC Educational Resources Information Center

Oerter, Rolf; And Others

In this study, which examines the relationship between level of information processing and level of general socialization, a total of 90 children aged 11 and 14 years and a group of 17 adults were presented with an organizational problem: how to order simultaneously presented tasks. Subjects were individually shown a map with locations and…

Development of a problem solving evaluation instrument; untangling of specific problem solving assets

NASA Astrophysics Data System (ADS)

Adams, Wendy Kristine

The purpose of my research was to produce a problem solving evaluation tool for physics. To do this it was necessary to gain a thorough understanding of how students solve problems. Although physics educators highly value problem solving and have put extensive effort into understanding successful problem solving, there is currently no efficient way to evaluate problem solving skill. Attempts have been made in the past; however, knowledge of the principles required to solve the subject problem are so absolutely critical that they completely overshadow any other skills students may use when solving a problem. The work presented here is unique because the evaluation tool removes the requirement that the student already have a grasp of physics concepts. It is also unique because I picked a wide range of people and picked a wide range of tasks for evaluation. This is an important design feature that helps make things emerge more clearly. This dissertation includes an extensive literature review of problem solving in physics, math, education and cognitive science as well as descriptions of studies involving student use of interactive computer simulations, the design and validation of a beliefs about physics survey and finally the design of the problem solving evaluation tool. I have successfully developed and validated a problem solving evaluation tool that identifies 44 separate assets (skills) necessary for solving problems. Rigorous validation studies, including work with an independent interviewer, show these assets identified by this content-free evaluation tool are the same assets that students use to solve problems in mechanics and quantum mechanics. Understanding this set of component assets will help teachers and researchers address problem solving within the classroom.

Willing Retention of Misbelief

NASA Astrophysics Data System (ADS)

Moore, John W.

2003-12-01

Students also ought to get a better picture of how useful chemistry is and what insights it can provide regarding crucial problems that face society. A student who has completed a general chemistry course ought to have some understanding of how chemists are addressing major problems involving energy resources, adequate supplies of pure food and water, degradation of the environment, poverty, disease, and terrorism. Even better, the student should be aware that these problems are intertwined and solving one of them at the expense of any or all of the others is not a true solution. Better yet, the student should realize that with appropriate education and experience, the student could contribute significantly to society’s efforts to solve these problems. Former ACS President Ronald Breslow has suggested on numerous occasions that students are more likely to be attracted to a field in which the student can participate in solving important problems, but we persist in teaching chemistry as if it is a dead science, where everything is already known. Both learning and the unknown are powerful challenges that can motivate students to put forth their best efforts. We ought to make better use of them.

Role of autobiographical memory in social problem solving and depression.

PubMed

Goddard, L; Dritschel, B; Burton, A

1996-11-01

Depressed patients frequently exhibit deficiencies in social problem solving (SPS). A possible cause of this deficit is an impairment in patients' ability to retrieve specific autobiographical memories. A clinically depressed group and a hospital control group performed the Means-End Problem-Solving (MEPS; J. J. Platt & G. Spivack, 1975a) task, during which they were required to attend to the memories retrieved during solution generation. Memories were categorized according to whether they were specific, categoric, or extended and whether the valence of the memories was positive or negative. Results support the general hypothesis that SPS skill is a function of autobiographical memory retrieval as measured by a cuing task and by the types of memories retrieved during the MEPS. However, the dysfunctional nature of categoric memories in SPS, rather than the importance of specific memories, was highlighted in the depressed group. Valence proved to be an unimportant variable in SPS ability. The cyclical links among autobiographical memory retrieval, SPS skills, and depression are discussed.

Multilevel acceleration of scattering-source iterations with application to electron transport

DOE PAGES

Drumm, Clif; Fan, Wesley

2017-08-18

Acceleration/preconditioning strategies available in the SCEPTRE radiation transport code are described. A flexible transport synthetic acceleration (TSA) algorithm that uses a low-order discrete-ordinates (S N) or spherical-harmonics (P N) solve to accelerate convergence of a high-order S N source-iteration (SI) solve is described. Convergence of the low-order solves can be further accelerated by applying off-the-shelf incomplete-factorization or algebraic-multigrid methods. Also available is an algorithm that uses a generalized minimum residual (GMRES) iterative method rather than SI for convergence, using a parallel sweep-based solver to build up a Krylov subspace. TSA has been applied as a preconditioner to accelerate the convergencemore » of the GMRES iterations. The methods are applied to several problems involving electron transport and problems with artificial cross sections with large scattering ratios. These methods were compared and evaluated by considering material discontinuities and scattering anisotropy. Observed accelerations obtained are highly problem dependent, but speedup factors around 10 have been observed in typical applications.« less

Problem solving, contention, and struggle: how siblings resolve a conflict of interests.

PubMed

Ram, A; Ross, H S

2001-01-01

In a laboratory setting, 48 sibling dyads age 4 and 6 or 6 and 8 years negotiated the division of six toys. Findings revealed that, in general, children reached divisions while using a preponderance of constructive problem-solving strategies, rather than contentious tactics. The degree of conflict of interests and the quality of sibling relationships predicted the children's use of problem-solving and contentious negotiation strategies, and was related to the types of resolutions achieved. Dyads experiencing low conflict of interests resolved their differences quickly. High conflict of interests coupled with positive relationships and constructive negotiation resulted in longer negotiations and creative, agreeable resolutions. High conflict of interests coupled with more negative relationships and destructive negotiations resulted in children's failures to reach agreement. Developmental differences indicated that older siblings within the pairs took the lead in negotiation, and benefited slightly more from the divisions. Furthermore, children in older dyads were more sophisticated and other oriented in their negotiations.

Matter wave coupling of spatially separated and unequally pumped polariton condensates

NASA Astrophysics Data System (ADS)

Kalinin, Kirill P.; Lagoudakis, Pavlos G.; Berloff, Natalia G.

2018-03-01

Spatial quantum coherence between two separated driven-dissipative polariton condensates created nonresonantly and with a different occupation is studied. We identify the regions where the condensates remain coherent with the phase difference continuously changing with the pumping imbalance and the regions where each condensate acquires its own chemical potential with phase differences exhibiting time-dependent oscillations. We show that in the mutual coherence limit the coupling consists of two competing contributions: a symmetric Heisenberg exchange and the Dzyloshinskii-Moriya asymmetric interactions that enable a continuous tuning of the phase relation across the dyad and derive analytic expressions for these types of interactions. The introduction of nonequal pumping increases the complexity of the type of problems that can be solved by polariton condensates arranged in a graph configuration. If equally pumped polaritons condensates arrange their phases to solve the constrained quadratic minimisation problem with a real symmetric matrix, the nonequally pumped condensates solve that problem for a general Hermitian matrix.

Dehumanization in organizational settings: some scientific and ethical considerations

PubMed Central

Christoff, Kalina

2014-01-01

Dehumanizing attitudes and behaviors frequently occur in organizational settings and are often viewed as an acceptable, and even necessary, strategy for pursuing personal and organizational goals. Here I examine a number of commonly held beliefs about dehumanization and argue that there is relatively little support for them in light of the evidence emerging from social psychological and neuroscientific research. Contrary to the commonly held belief that everyday forms of dehumanization are innocent and inconsequential, the evidence shows profoundly negative consequences for both victims and perpetrators. As well, the belief that suppressing empathy automatically leads to improved problem solving is not supported by the evidence. The more general belief that empathy interferes with problem solving receives partial support, but only in the case of mechanistic problem solving. Overall, I question the usefulness of dehumanization in organizational settings and argue that it can be replaced by superior strategies that are ethically more acceptable and do not entail the severely negative consequences associated with dehumanization. PMID:25309401

Description of Student’s Metacognitive Ability in Understanding and Solving Mathematics Problem

NASA Astrophysics Data System (ADS)

Ahmad, Herlina; Febryanti, Fatimah; Febryanti, Fatimah; Muthmainnah

2018-01-01

This research was conducted qualitative which was aim to describe metacognitive ability to understand and solve the problems of mathematics. The subject of the research was the first year students at computer and networking department of SMK Mega Link Majene. The sample was taken by purposive sampling technique. The data obtained used the research instrument based on the form of students achievements were collected by using test of student’s achievement and interview guidance. The technique of collecting data researcher had observation to ascertain the model that used by teacher was teaching model of developing metacognitive. The technique of data analysis in this research was reduction data, presentation and conclusion. Based on the whole findings in this study it was shown that student’s metacognitive ability generally not develops optimally. It was because of limited scope of the materials, and cognitive teaching strategy handled by verbal presentation and trained continuously in facing cognitive tasks, such as understanding and solving problem.

Age differences in everyday problem-solving effectiveness: older adults select more effective strategies for interpersonal problems.

PubMed

Blanchard-Fields, Fredda; Mienaltowski, Andrew; Seay, Renee Baldi

2007-01-01

Using the Everyday Problem Solving Inventory of Cornelius and Caspi, we examined differences in problem-solving strategy endorsement and effectiveness in two domains of everyday functioning (instrumental or interpersonal, and a mixture of the two domains) and for four strategies (avoidance-denial, passive dependence, planful problem solving, and cognitive analysis). Consistent with past research, our research showed that older adults were more problem focused than young adults in their approach to solving instrumental problems, whereas older adults selected more avoidant-denial strategies than young adults when solving interpersonal problems. Overall, older adults were also more effective than young adults when solving everyday problems, in particular for interpersonal problems.

Does the non-identity problem block a class of arguments against cloning?

PubMed

Green, Richard

2004-01-01

One class of argument against cloning human beings in the contemporary literature focuses on the bad consequences that will befall the clone or "later-twin." In this paper I consider whether this line of argumentation can be blocked by invoking Parfit's non-identity problem. I canvass two general strategies for solving the non-identity problem: a consequentialist strategy and non-consequentialist, rights based strategy. I argue that while each general strategy offers a plausible solution to the non-identity problem as applied to the cases most frequently discussed in the non-identity problem literature, neither provides a reason for putting aside the non-identity problem when applied to cloning. I conclude (roughly) that the non-identity problem does serve to block this class of argument against cloning.

Spontaneous gestures influence strategy choices in problem solving.

PubMed

Alibali, Martha W; Spencer, Robert C; Knox, Lucy; Kita, Sotaro

2011-09-01

Do gestures merely reflect problem-solving processes, or do they play a functional role in problem solving? We hypothesized that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving. Participants in two experiments solved problems requiring the prediction of gear movement, either with gesture allowed or with gesture prohibited. Such problems can be correctly solved using either a perceptual-motor strategy (simulation of gear movements) or an abstract strategy (the parity strategy). Participants in the gesture-allowed condition were more likely to use perceptual-motor strategies than were participants in the gesture-prohibited condition. Gesture promoted use of perceptual-motor strategies both for participants who talked aloud while solving the problems (Experiment 1) and for participants who solved the problems silently (Experiment 2). Thus, spontaneous gestures influence strategy choices in problem solving.

Too upset to think: the interplay of borderline personality features, negative emotions, and social problem solving in the laboratory.

PubMed

Dixon-Gordon, Katherine L; Chapman, Alexander L; Lovasz, Nathalie; Walters, Kris

2011-10-01

Borderline personality disorder (BPD) is associated with poor social problem solving and problems with emotion regulation. In this study, the social problem-solving performance of undergraduates with high (n = 26), mid (n = 32), or low (n = 29) levels of BPD features was assessed with the Social Problem-Solving Inventory-Revised and using the means-ends problem-solving procedure before and after a social rejection stressor. The high-BP group, but not the low-BP group, showed a significant reduction in relevant solutions to social problems and more inappropriate solutions following the negative emotion induction. Increases in self-reported negative emotions during the emotion induction mediated the relationship between BP features and reductions in social problem-solving performance. In addition, the high-BP group demonstrated trait deficits in social problem solving on the Social Problem-Solving Inventory-Revised. These findings suggest that future research must examine social problem solving under differing emotional conditions, and that clinical interventions to improve social problem solving among persons with BP features should focus on responses to emotional contexts.

An Investigation of Secondary Teachers’ Understanding and Belief on Mathematical Problem Solving

NASA Astrophysics Data System (ADS)

Yuli Eko Siswono, Tatag; Wachidul Kohar, Ahmad; Kurniasari, Ika; Puji Astuti, Yuliani

2016-02-01

Weaknesses on problem solving of Indonesian students as reported by recent international surveys give rise to questions on how Indonesian teachers bring out idea of problem solving in mathematics lesson. An explorative study was undertaken to investigate how secondary teachers who teach mathematics at junior high school level understand and show belief toward mathematical problem solving. Participants were teachers from four cities in East Java province comprising 45 state teachers and 25 private teachers. Data was obtained through questionnaires and written test. The results of this study point out that the teachers understand pedagogical problem solving knowledge well as indicated by high score of observed teachers‘ responses showing understanding on problem solving as instruction as well as implementation of problem solving in teaching practice. However, they less understand on problem solving content knowledge such as problem solving strategies and meaning of problem itself. Regarding teacher's difficulties, teachers admitted to most frequently fail in (1) determining a precise mathematical model or strategies when carrying out problem solving steps which is supported by data of test result that revealed transformation error as the most frequently observed errors in teachers’ work and (2) choosing suitable real situation when designing context-based problem solving task. Meanwhile, analysis of teacher's beliefs on problem solving shows that teachers tend to view both mathematics and how students should learn mathematics as body static perspective, while they tend to believe to apply idea of problem solving as dynamic approach when teaching mathematics.

The Impact of Teacher Training on Creative Writing and Problem-Solving Using Futuristic Scenarios for Creative Problem Solving and Creative Problem Solving Programs

ERIC Educational Resources Information Center

Hayel Al-Srour, Nadia; Al-Ali, Safa M.; Al-Oweidi, Alia

2016-01-01

The present study aims to detect the impact of teacher training on creative writing and problem-solving using both Futuristic scenarios program to solve problems creatively, and creative problem solving. To achieve the objectives of the study, the sample was divided into two groups, the first consist of 20 teachers, and 23 teachers to second…

Problem-solving skills in high school biology: The effectiveness of the IMMEX problem-solving assessment software

NASA Astrophysics Data System (ADS)

Palacio-Cayetano, Joycelin

"Problem-solving through reflective thinking should be both the method and valuable outcome of science instruction in America's schools" proclaimed John Dewey (Gabel, 1995). If the development of problem-solving is a primary goal of science education, more problem-solving opportunities must be an integral part of K-16 education. To examine the effective use of technology in developing and assessing problem-solving skills, a problem-solving authoring, learning, and assessment software, the UCLA IMMEX Program-Interactive Multimedia Exercises-was investigated. This study was a twenty-week quasi-experimental study that was implemented as a control-group time series design among 120 tenth grade students. Both the experimental group (n = 60) and the control group (n = 60) participated in a problem-based learning curriculum; however, the experimental group received regular intensive experiences with IMMEX problem-solving and the control group did not. Problem-solving pretest and posttest were administered to all students. The instruments used were a 35-item Processes of Biological Inquiry Test and an IMMEX problem-solving assessment test, True Roots. Students who participated in the IMMEX Program achieved significant (p <.05) gains in problem-solving skills on both problem-solving assessment instruments. This study provided evidence that IMMEX software is highly efficient in evaluating salient elements of problem-solving. Outputs of students' problem-solving strategies revealed that unsuccessful problem solvers primarily used the following four strategies: (1) no data search strategy, students simply guessed; (2) limited data search strategy leading to insufficient data and premature closing; (3) irrelevant data search strategy, students focus in areas bearing no substantive data; and (4) extensive data search strategy with inadequate integration and analysis. On the contrary, successful problem solvers used the following strategies; (1) focused search strategy coupled with the ability to fill in knowledge gaps by accessing the appropriate resources; (2) targeted search strategy coupled with high level of analytical and integration skills; and (3) focused search strategy coupled with superior discrimination, analytical, and integration skills. The strategies of students who were successful and unsuccessful solving IMMEX problems were consistent with those of expert and novice problem solvers identified in the literature on problem-solving.

Disfluent fonts don't help people solve math problems.

PubMed

Meyer, Andrew; Frederick, Shane; Burnham, Terence C; Guevara Pinto, Juan D; Boyer, Ty W; Ball, Linden J; Pennycook, Gordon; Ackerman, Rakefet; Thompson, Valerie A; Schuldt, Jonathon P

2015-04-01

Prior research suggests that reducing font clarity can cause people to consider printed information more carefully. The most famous demonstration showed that participants were more likely to solve counterintuitive math problems when they were printed in hard-to-read font. However, after pooling data from that experiment with 16 attempts to replicate it, we find no effect on solution rates. We examine potential moderating variables, including cognitive ability, presentation format, and experimental setting, but we find no evidence of a disfluent font benefit under any conditions. More generally, though disfluent fonts slightly increase response times, we find little evidence that they activate analytic reasoning. (c) 2015 APA, all rights reserved).

Stochastic Galerkin methods for the steady-state Navier–Stokes equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sousedík, Bedřich, E-mail: sousedik@umbc.edu; Elman, Howard C., E-mail: elman@cs.umd.edu

2016-07-01

We study the steady-state Navier–Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion. For the resulting stochastic problem, we formulate the model and linearization schemes using Picard and Newton iterations in the framework of the stochastic Galerkin method, and we explore properties of the resulting stochastic solutions. We also propose a preconditioner for solving the linear systems of equations arising at each step of the stochastic (Galerkin) nonlinear iteration and demonstrate its effectiveness for solving a set of benchmarkmore » problems.« less

Group decision-making techniques for natural resource management applications

USGS Publications Warehouse

Coughlan, Beth A.K.; Armour, Carl L.

1992-01-01

This report is an introduction to decision analysis and problem-solving techniques for professionals in natural resource management. Although these managers are often called upon to make complex decisions, their training in the natural sciences seldom provides exposure to the decision-making tools developed in management science. Our purpose is to being to fill this gap. We present a general analysis of the pitfalls of group problem solving, and suggestions for improved interactions followed by the specific techniques. Selected techniques are illustrated. The material is easy to understand and apply without previous training or excessive study and is applicable to natural resource management issues.

Stochastic Galerkin methods for the steady-state Navier–Stokes equations

DOE PAGES

Sousedík, Bedřich; Elman, Howard C.

2016-04-12

We study the steady-state Navier–Stokes equations in the context of stochastic finite element discretizations. Specifically, we assume that the viscosity is a random field given in the form of a generalized polynomial chaos expansion. For the resulting stochastic problem, we formulate the model and linearization schemes using Picard and Newton iterations in the framework of the stochastic Galerkin method, and we explore properties of the resulting stochastic solutions. We also propose a preconditioner for solving the linear systems of equations arising at each step of the stochastic (Galerkin) nonlinear iteration and demonstrate its effectiveness for solving a set of benchmarkmore » problems.« less

Intuitive reasoning about abstract and familiar physics problems

NASA Technical Reports Server (NTRS)

Kaiser, Mary Kister; Jonides, John; Alexander, Joanne

1986-01-01

Previous research has demonstrated that many people have misconceptions about basic properties of motion. Two experiments examined whether people are more likely to produce dynamically correct predictions about basic motion problems involving situations with which they are familiar, and whether solving such problems enhances performance on a subsequent abstract problem. In experiment 1, college students were asked to predict the trajectories of objects exiting a curved tube. Subjects were more accurate on the familiar version of the problem, and there was no evidence of transfer to the abstract problem. In experiment 2, two familiar problems were provided in an attempt to enhance subjects' tendency to extract the general structure of the problems. Once again, they gave more correct responses to the familiar problems but failed to generalize to the abstract problem. Formal physics training was associated with correct predictions for the abstract problem but was unrelated to performance on the familiar problems.

A Radiation Transfer Solver for Athena Using Short Characteristics

NASA Astrophysics Data System (ADS)

Davis, Shane W.; Stone, James M.; Jiang, Yan-Fei

2012-03-01

We describe the implementation of a module for the Athena magnetohydrodynamics (MHD) code that solves the time-independent, multi-frequency radiative transfer (RT) equation on multidimensional Cartesian simulation domains, including scattering and non-local thermodynamic equilibrium (LTE) effects. The module is based on well known and well tested algorithms developed for modeling stellar atmospheres, including the method of short characteristics to solve the RT equation, accelerated Lambda iteration to handle scattering and non-LTE effects, and parallelization via domain decomposition. The module serves several purposes: it can be used to generate spectra and images, to compute a variable Eddington tensor (VET) for full radiation MHD simulations, and to calculate the heating and cooling source terms in the MHD equations in flows where radiation pressure is small compared with gas pressure. For the latter case, the module is combined with the standard MHD integrators using operator splitting: we describe this approach in detail, including a new constraint on the time step for stability due to radiation diffusion modes. Implementation of the VET method for radiation pressure dominated flows is described in a companion paper. We present results from a suite of test problems for both the RT solver itself and for dynamical problems that include radiative heating and cooling. These tests demonstrate that the radiative transfer solution is accurate and confirm that the operator split method is stable, convergent, and efficient for problems of interest. We demonstrate there is no need to adopt ad hoc assumptions of questionable accuracy to solve RT problems in concert with MHD: the computational cost for our general-purpose module for simple (e.g., LTE gray) problems can be comparable to or less than a single time step of Athena's MHD integrators, and only few times more expensive than that for more general (non-LTE) problems.

MIDSHIPS: multicentre intervention designed for self-harm using interpersonal problem-solving: protocol for a randomised controlled feasibility study.

PubMed

Collinson, Michelle; Owens, David; Blenkiron, Paul; Burton, Kayleigh; Graham, Liz; Hatcher, Simon; House, Allan; Martin, Katie; Pembroke, Louise; Protheroe, David; Tubeuf, Sandy; Farrin, Amanda

2014-05-10

Around 150,000 people each year attend hospitals in England due to self-harm, many of them more than once. Over 5,000 people die by suicide each year in the UK, a quarter of them having attended hospital in the previous year because of self-harm. Self-harm is a major identifiable risk factor for suicide. People receive variable care at hospital; many are not assessed for their psychological needs and little psychological therapy is offered. Despite its frequent occurrence, we have no clear research evidence about how to reduce the repetition of self-harm. Some people who have self-harmed show less active ways of solving problems, and brief problem-solving therapies are considered the most promising psychological treatments. This is a pragmatic, individually randomised, controlled, feasibility study comparing interpersonal problem-solving therapy plus treatment-as-usual with treatment-as-usual alone, for adults attending a general hospital following self-harm. A total of 60 participants will be randomised equally between the treatment arms, which will be balanced with respect to the type of most recent self-harm event, number of previous self-harm events, gender and age. Feasibility objectives are as follows: a) To establish and field test procedures for implementing the problem-solving intervention; b) To determine the feasibility and best method of participant recruitment and follow up; c) To assess therapeutic delivery; d) To assess the feasibility of obtaining the definitive trial's primary and secondary outcomes; e) To assess the perceived burden and acceptability of obtaining the trial's self-reported outcome data; f) To inform the sample size calculation for the definitive trial. The results of this feasibility study will be used to determine the appropriateness of proceeding to a definitive trial and will allow us to design an achievable trial of interpersonal problem-solving therapy for adults who self-harm. Current Controlled Trials (ISRCTN54036115).

MIDSHIPS: Multicentre Intervention Designed for Self-Harm using Interpersonal Problem-Solving: protocol for a randomised controlled feasibility study

PubMed Central

2014-01-01

Background Around 150,000 people each year attend hospitals in England due to self-harm, many of them more than once. Over 5,000 people die by suicide each year in the UK, a quarter of them having attended hospital in the previous year because of self-harm. Self-harm is a major identifiable risk factor for suicide. People receive variable care at hospital; many are not assessed for their psychological needs and little psychological therapy is offered. Despite its frequent occurrence, we have no clear research evidence about how to reduce the repetition of self-harm. Some people who have self-harmed show less active ways of solving problems, and brief problem-solving therapies are considered the most promising psychological treatments. Methods/Design This is a pragmatic, individually randomised, controlled, feasibility study comparing interpersonal problem-solving therapy plus treatment-as-usual with treatment-as-usual alone, for adults attending a general hospital following self-harm. A total of 60 participants will be randomised equally between the treatment arms, which will be balanced with respect to the type of most recent self-harm event, number of previous self-harm events, gender and age. Feasibility objectives are as follows: a) To establish and field test procedures for implementing the problem-solving intervention; b) To determine the feasibility and best method of participant recruitment and follow up; c) To assess therapeutic delivery; d) To assess the feasibility of obtaining the definitive trial’s primary and secondary outcomes; e) To assess the perceived burden and acceptability of obtaining the trial’s self-reported outcome data; f) To inform the sample size calculation for the definitive trial. Discussion The results of this feasibility study will be used to determine the appropriateness of proceeding to a definitive trial and will allow us to design an achievable trial of interpersonal problem-solving therapy for adults who self-harm. Trial registration Current Controlled Trials (ISRCTN54036115) PMID:24886683

Autistic children and the object permanence task.

PubMed

Adrien, J L; Tanguay, P; Barthélémy, C; Martineaú, J; Perrot, A; Hameury, L; Sauvage, D

1993-01-01

Many mentally retarded autistic children can understand the concept of object permanence, but, in comparison to developmental-age matched normal children, the behavioral strategies they employ in carrying out the Casati-Lezine Object Permanence Test are deficient and lead to failure. These deficiencies appear unrelated to interference of stereotypic or other bizarre behavior in task performance. Similar problem-solving deficiencies can be found in mentally retarded children who are not autistic, suggesting that the deficiencies themselves are less related to the social-communication deficits of autistic children, but more to the general problem-solving difficulties found in children with a lower developmental quotient. Nevertheless, the qualitative analysis of results shows a tendency in autistic children, despite their better developmental level, to use less coordinated and regular sequences to solve the task than normal or mentally retarded children.

Pre-Service Class Teacher' Ability in Solving Mathematical Problems and Skills in Solving Daily Problems

ERIC Educational Resources Information Center

Aljaberi, Nahil M.; Gheith, Eman

2016-01-01

This study aims to investigate the ability of pre-service class teacher at University of Petrain solving mathematical problems using Polya's Techniques, their level of problem solving skills in daily-life issues. The study also investigates the correlation between their ability to solve mathematical problems and their level of problem solving…

The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems.

PubMed

Baars, Martine; Wijnia, Lisette; Paas, Fred

2017-01-01

Self-regulated learning (SRL) skills are essential for learning during school years, particularly in complex problem-solving domains, such as biology and math. Although a lot of studies have focused on the cognitive resources that are needed for learning to solve problems in a self-regulated way, affective and motivational resources have received much less research attention. The current study investigated the relation between affect (i.e., Positive Affect and Negative Affect Scale), motivation (i.e., autonomous and controlled motivation), mental effort, SRL skills, and problem-solving performance when learning to solve biology problems in a self-regulated online learning environment. In the learning phase, secondary education students studied video-modeling examples of how to solve hereditary problems, solved hereditary problems which they chose themselves from a set of problems with different complexity levels (i.e., five levels). In the posttest, students solved hereditary problems, self-assessed their performance, and chose a next problem from the set of problems but did not solve these problems. The results from this study showed that negative affect, inaccurate self-assessments during the posttest, and higher perceptions of mental effort during the posttest were negatively associated with problem-solving performance after learning in a self-regulated way.

A general heuristic for genome rearrangement problems.

PubMed

Dias, Ulisses; Galvão, Gustavo Rodrigues; Lintzmayer, Carla Négri; Dias, Zanoni

2014-06-01

In this paper, we present a general heuristic for several problems in the genome rearrangement field. Our heuristic does not solve any problem directly, it is rather used to improve the solutions provided by any non-optimal algorithm that solve them. Therefore, we have implemented several algorithms described in the literature and several algorithms developed by ourselves. As a whole, we implemented 23 algorithms for 9 well known problems in the genome rearrangement field. A total of 13 algorithms were implemented for problems that use the notions of prefix and suffix operations. In addition, we worked on 5 algorithms for the classic problem of sorting by transposition and we conclude the experiments by presenting results for 3 approximation algorithms for the sorting by reversals and transpositions problem and 2 approximation algorithms for the sorting by reversals problem. Another algorithm with better approximation ratio can be found for the last genome rearrangement problem, but it is purely theoretical with no practical implementation. The algorithms we implemented in addition to our heuristic lead to the best practical results in each case. In particular, we were able to improve results on the sorting by transpositions problem, which is a very special case because many efforts have been made to generate algorithms with good results in practice and some of these algorithms provide results that equal the optimum solutions in many cases. Our source codes and benchmarks are freely available upon request from the authors so that it will be easier to compare new approaches against our results.

Semilinear programming: applications and implementation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mohan, S.

Semilinear programming is a method of solving optimization problems with linear constraints where the non-negativity restrictions on the variables are dropped and the objective function coefficients can take on different values depending on whether the variable is positive or negative. The simplex method for linear programming is modified in this thesis to solve general semilinear and piecewise linear programs efficiently without having to transform them into equivalent standard linear programs. Several models in widely different areas of optimization such as production smoothing, facility locations, goal programming and L/sub 1/ estimation are presented first to demonstrate the compact formulation that arisesmore » when such problems are formulated as semilinear programs. A code SLP is constructed using the semilinear programming techniques. Problems in aggregate planning and L/sub 1/ estimation are solved using SLP and equivalent linear programs using a linear programming simplex code. Comparisons of CPU times and number iterations indicate SLP to be far superior. The semilinear programming techniques are extended to piecewise linear programming in the implementation of the code PLP. Piecewise linear models in aggregate planning are solved using PLP and equivalent standard linear programs using a simple upper bounded linear programming code SUBLP.« less

SIERRA Multimechanics Module: Aria User Manual Version 4.44

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sierra Thermal /Fluid Team

2017-04-01

Aria is a Galerkin fnite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process fows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( %3C 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of eithermore » arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h -adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sierra Thermal/Fluid Team

Aria is a Galerkin fnite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process fows via the incompressible Navier-Stokes equations specialized to a low Reynolds number ( %3C 1 ) regime. Enhanced modeling support of manufacturing processing is made possible through use of eithermore » arbitrary Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h -adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sierra Thermal /Fluid Team

Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes thermal energy transport, species transport, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for manufacturing process flows via the incompressible Navier-Stokes equations specialized to a low Reynolds number (Re %3C 1) regime. Enhanced modeling support of manufacturing processing is made possible through use of either arbitrarymore » Lagrangian- Eulerian (ALE) and level set based free and moving boundary tracking in conjunction with quasi-static nonlinear elastic solid mechanics for mesh control. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton- Krylov methods and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h-adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based upon the Sierra Framework.« less

Parallelized traveling cluster approximation to study numerically spin-fermion models on large lattices

DOE PAGES

Mukherjee, Anamitra; Patel, Niravkumar D.; Bishop, Chris; ...

2015-06-08

Lattice spin-fermion models are quite important to study correlated systems where quantum dynamics allows for a separation between slow and fast degrees of freedom. The fast degrees of freedom are treated quantum mechanically while the slow variables, generically referred to as the “spins,” are treated classically. At present, exact diagonalization coupled with classical Monte Carlo (ED + MC) is extensively used to solve numerically a general class of lattice spin-fermion problems. In this common setup, the classical variables (spins) are treated via the standard MC method while the fermion problem is solved by exact diagonalization. The “traveling cluster approximation” (TCA)more » is a real space variant of the ED + MC method that allows to solve spin-fermion problems on lattice sizes with up to 10 3 sites. In this paper, we present a novel reorganization of the TCA algorithm in a manner that can be efficiently parallelized. Finally, this allows us to solve generic spin-fermion models easily on 10 4 lattice sites and with some effort on 10 5 lattice sites, representing the record lattice sizes studied for this family of models.« less

Parallelized traveling cluster approximation to study numerically spin-fermion models on large lattices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukherjee, Anamitra; Patel, Niravkumar D.; Bishop, Chris

Lattice spin-fermion models are quite important to study correlated systems where quantum dynamics allows for a separation between slow and fast degrees of freedom. The fast degrees of freedom are treated quantum mechanically while the slow variables, generically referred to as the “spins,” are treated classically. At present, exact diagonalization coupled with classical Monte Carlo (ED + MC) is extensively used to solve numerically a general class of lattice spin-fermion problems. In this common setup, the classical variables (spins) are treated via the standard MC method while the fermion problem is solved by exact diagonalization. The “traveling cluster approximation” (TCA)more » is a real space variant of the ED + MC method that allows to solve spin-fermion problems on lattice sizes with up to 10 3 sites. In this paper, we present a novel reorganization of the TCA algorithm in a manner that can be efficiently parallelized. Finally, this allows us to solve generic spin-fermion models easily on 10 4 lattice sites and with some effort on 10 5 lattice sites, representing the record lattice sizes studied for this family of models.« less

Cognitive patterns of neuroanatomy concepts: Knowledge organizations that emerge from problem solving versus information gathering

NASA Astrophysics Data System (ADS)

Weidner, Jeanne Margaret O'malley

2000-10-01

This study was motivated by some of the claims that are found in the literature on Problem-Based Learning (PBL). This instructional technique, which uses case studies as its primary instructional tool, has been advanced as an alternative to traditional instruction in order to foster more meaningful, integrative learning of scientific concepts. Several of the advantages attributed to Problem-Based Learning are that it (1) is generally preferred by students because it appears to foster a more nurturing and enjoyable learning experience, (2) fosters greater retention of knowledge and concepts acquired, and (3) results in increased ability to apply this knowledge toward solving new problems. This study examines the differences that result when students learn neuroanatomy concepts under two instructional contexts: problem solving vs. information gathering. The technological resource provided to students to support learning under each of these contexts was the multimedia program BrainStorm: An Interactive Neuroanatomy Atlas (Coppa & Tancred, 1995). The study explores the influence of context with regard to subjects' performance on objective post-tests, organization of knowledge as measured by Pathfinder Networks, differential use of the multimedia software and discourse differences emerging from the transcripts. The findings support previous research in the literature that problem-solving results in less knowledge acquisition in the short term, greater retention of material over time, and a subjects' preference for the method. However, both the degree of retention and preference were influenced by subjects' prior knowledge of the material in the exercises, as there was a significant difference in performance between the two exercises: for the exercise about which subjects appeared to have greater background information, memory decay was less, and subject attitude toward the problem solving instructional format was more favorable, than for the exercise for which subjects had less prior knowledge. Subjects also used the software differently under each format with regard to modules accessed, time spent in modules, and types of information sought. In addition, analyses of the transcripts showed more numerous occurrences of explanations and summarizations in the problem-solving context, compared to the information gathering context. The attempts to show significant differences between the contexts by means of Pathfinder analyses were less than successful.

Image size invariant visual cryptography for general access structures subject to display quality constraints.

PubMed

Lee, Kai-Hui; Chiu, Pei-Ling

2013-10-01

Conventional visual cryptography (VC) suffers from a pixel-expansion problem, or an uncontrollable display quality problem for recovered images, and lacks a general approach to construct visual secret sharing schemes for general access structures. We propose a general and systematic approach to address these issues without sophisticated codebook design. This approach can be used for binary secret images in non-computer-aided decryption environments. To avoid pixel expansion, we design a set of column vectors to encrypt secret pixels rather than using the conventional VC-based approach. We begin by formulating a mathematic model for the VC construction problem to find the column vectors for the optimal VC construction, after which we develop a simulated-annealing-based algorithm to solve the problem. The experimental results show that the display quality of the recovered image is superior to that of previous papers.

Comprehension and computation in Bayesian problem solving

PubMed Central

Johnson, Eric D.; Tubau, Elisabet

2015-01-01

Humans have long been characterized as poor probabilistic reasoners when presented with explicit numerical information. Bayesian word problems provide a well-known example of this, where even highly educated and cognitively skilled individuals fail to adhere to mathematical norms. It is widely agreed that natural frequencies can facilitate Bayesian inferences relative to normalized formats (e.g., probabilities, percentages), both by clarifying logical set-subset relations and by simplifying numerical calculations. Nevertheless, between-study performance on “transparent” Bayesian problems varies widely, and generally remains rather unimpressive. We suggest there has been an over-focus on this representational facilitator (i.e., transparent problem structures) at the expense of the specific logical and numerical processing requirements and the corresponding individual abilities and skills necessary for providing Bayesian-like output given specific verbal and numerical input. We further suggest that understanding this task-individual pair could benefit from considerations from the literature on mathematical cognition, which emphasizes text comprehension and problem solving, along with contributions of online executive working memory, metacognitive regulation, and relevant stored knowledge and skills. We conclude by offering avenues for future research aimed at identifying the stages in problem solving at which correct vs. incorrect reasoners depart, and how individual differences might influence this time point. PMID:26283976

Solving geosteering inverse problems by stochastic Hybrid Monte Carlo method

DOE PAGES

Shen, Qiuyang; Wu, Xuqing; Chen, Jiefu; ...

2017-11-20

The inverse problems arise in almost all fields of science where the real-world parameters are extracted from a set of measured data. The geosteering inversion plays an essential role in the accurate prediction of oncoming strata as well as a reliable guidance to adjust the borehole position on the fly to reach one or more geological targets. This mathematical treatment is not easy to solve, which requires finding an optimum solution among a large solution space, especially when the problem is non-linear and non-convex. Nowadays, a new generation of logging-while-drilling (LWD) tools has emerged on the market. The so-called azimuthalmore » resistivity LWD tools have azimuthal sensitivity and a large depth of investigation. Hence, the associated inverse problems become much more difficult since the earth model to be inverted will have more detailed structures. The conventional deterministic methods are incapable to solve such a complicated inverse problem, where they suffer from the local minimum trap. Alternatively, stochastic optimizations are in general better at finding global optimal solutions and handling uncertainty quantification. In this article, we investigate the Hybrid Monte Carlo (HMC) based statistical inversion approach and suggest that HMC based inference is more efficient in dealing with the increased complexity and uncertainty faced by the geosteering problems.« less

A comparison of acceleration methods for solving the neutron transport k-eigenvalue problem

NASA Astrophysics Data System (ADS)

Willert, Jeffrey; Park, H.; Knoll, D. A.

2014-10-01

Over the past several years a number of papers have been written describing modern techniques for numerically computing the dominant eigenvalue of the neutron transport criticality problem. These methods fall into two distinct categories. The first category of methods rewrite the multi-group k-eigenvalue problem as a nonlinear system of equations and solve the resulting system using either a Jacobian-Free Newton-Krylov (JFNK) method or Nonlinear Krylov Acceleration (NKA), a variant of Anderson Acceleration. These methods are generally successful in significantly reducing the number of transport sweeps required to compute the dominant eigenvalue. The second category of methods utilize Moment-Based Acceleration (or High-Order/Low-Order (HOLO) Acceleration). These methods solve a sequence of modified diffusion eigenvalue problems whose solutions converge to the solution of the original transport eigenvalue problem. This second class of methods is, in our experience, always superior to the first, as most of the computational work is eliminated by the acceleration from the LO diffusion system. In this paper, we review each of these methods. Our computational results support our claim that the choice of which nonlinear solver to use, JFNK or NKA, should be secondary. The primary computational savings result from the implementation of a HOLO algorithm. We display computational results for a series of challenging multi-dimensional test problems.

A Generalization of the Karush-Kuhn-Tucker Theorem for Approximate Solutions of Mathematical Programming Problems Based on Quadratic Approximation

NASA Astrophysics Data System (ADS)

Voloshinov, V. V.

2018-03-01

In computations related to mathematical programming problems, one often has to consider approximate, rather than exact, solutions satisfying the constraints of the problem and the optimality criterion with a certain error. For determining stopping rules for iterative procedures, in the stability analysis of solutions with respect to errors in the initial data, etc., a justified characteristic of such solutions that is independent of the numerical method used to obtain them is needed. A necessary δ-optimality condition in the smooth mathematical programming problem that generalizes the Karush-Kuhn-Tucker theorem for the case of approximate solutions is obtained. The Lagrange multipliers corresponding to the approximate solution are determined by solving an approximating quadratic programming problem.

Bringing NASA Technology Down to Earth

NASA Technical Reports Server (NTRS)

Lockney, Daniel P.; Taylor, Terry L.

2018-01-01

Whether putting rovers on Mars or sustaining life in extreme conditions, NASA develops technologies to solve some of the most difficult challenges ever faced. Through its Technology Transfer Program, the agency makes the innovations behind space exploration available to industry, academia, and the general public. This paper describes the primary mechanisms through which NASA disseminates technology to solve real-life problems; illustrates recent program accomplishments; and provides examples of spinoff success stories currently impacting everyday life.

Uncertain programming models for portfolio selection with uncertain returns

NASA Astrophysics Data System (ADS)

Zhang, Bo; Peng, Jin; Li, Shengguo

2015-10-01

In an indeterminacy economic environment, experts' knowledge about the returns of securities consists of much uncertainty instead of randomness. This paper discusses portfolio selection problem in uncertain environment in which security returns cannot be well reflected by historical data, but can be evaluated by the experts. In the paper, returns of securities are assumed to be given by uncertain variables. According to various decision criteria, the portfolio selection problem in uncertain environment is formulated as expected-variance-chance model and chance-expected-variance model by using the uncertainty programming. Within the framework of uncertainty theory, for the convenience of solving the models, some crisp equivalents are discussed under different conditions. In addition, a hybrid intelligent algorithm is designed in the paper to provide a general method for solving the new models in general cases. At last, two numerical examples are provided to show the performance and applications of the models and algorithm.

Guided particle swarm optimization method to solve general nonlinear optimization problems

NASA Astrophysics Data System (ADS)

Abdelhalim, Alyaa; Nakata, Kazuhide; El-Alem, Mahmoud; Eltawil, Amr

2018-04-01

The development of hybrid algorithms is becoming an important topic in the global optimization research area. This article proposes a new technique in hybridizing the particle swarm optimization (PSO) algorithm and the Nelder-Mead (NM) simplex search algorithm to solve general nonlinear unconstrained optimization problems. Unlike traditional hybrid methods, the proposed method hybridizes the NM algorithm inside the PSO to improve the velocities and positions of the particles iteratively. The new hybridization considers the PSO algorithm and NM algorithm as one heuristic, not in a sequential or hierarchical manner. The NM algorithm is applied to improve the initial random solution of the PSO algorithm and iteratively in every step to improve the overall performance of the method. The performance of the proposed method was tested over 20 optimization test functions with varying dimensions. Comprehensive comparisons with other methods in the literature indicate that the proposed solution method is promising and competitive.

State-constrained booster trajectory solutions via finite elements and shooting

NASA Technical Reports Server (NTRS)

Bless, Robert R.; Hodges, Dewey H.; Seywald, Hans

1993-01-01

This paper presents an extension of a FEM formulation based on variational principles. A general formulation for handling internal boundary conditions and discontinuities in the state equations is presented, and the general formulation is modified for optimal control problems subject to state-variable inequality constraints. Solutions which only touch the state constraint and solutions which have a boundary arc of finite length are considered. Suitable shape and test functions are chosen for a FEM discretization. All element quadrature (equivalent to one-point Gaussian quadrature over each element) may be done in closed form. The final form of the algebraic equations is then derived. A simple state-constrained problem is solved. Then, for a practical application of the use of the FEM formulation, a launch vehicle subject to a dynamic pressure constraint (a first-order state inequality constraint) is solved. The results presented for the launch-vehicle trajectory have some interesting features, including a touch-point solution.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Unseren, M.A.

A general framework for solving the dynamic load distribution when two manipulators hold a rigid object is proposed. The underspecified problem of solving for the contact forces and torques based on the object`s equations of motion is transformed into a well specified problem. This is accomplished by augmenting the object`s equations of motion with additional equations which relate a new vector variable quantifying the internal contact force and torque degrees of freedom (DOF) as a linear function of the contact forces and torques. The resulting augmented system yields a well specified solution for the contact forces and torques in whichmore » they are separated into their motion inducing and internal components. A particular solution is suggested which enables the designer to conveniently specify what portion of the payload`s mass each manipulator is to bear. It is also shown that the results of the previous work are just a special case of the general load distribution framework described here.« less

Stringy Gravity: Solving the Dark Problems at `short' distance

NASA Astrophysics Data System (ADS)

Park, Jeong-Hyuck

2018-01-01

Dictated by Symmetry Principle, string theory predicts not General Relativity but its own gravity which assumes the entire closed string massless sector to be geometric and thus gravitational. In terms of R/(MG), i.e. the dimensionless radial variable normalized by mass, Stringy Gravity agrees with General Relativity toward infinity, but modifies it at short distance. At far short distance, gravitational force can be even repulsive. These may solve the dark matter and energy problems, as they arise essentially from small R/(MG) observations: long distance divided by much heavier mass. We address the pertinent differential geometry for Stringy Gravity, stringy Equivalence Principle, stringy geodesics and the minimal coupling to the Standard Model. We highlight the notion of `doubled-yet-gauged' coordinate system, in which a gauge orbit corresponds to a single physical point and proper distance is defined between two gauge orbits by a path integral.

Numerical approximations for fractional diffusion equations via a Chebyshev spectral-tau method

NASA Astrophysics Data System (ADS)

Doha, Eid H.; Bhrawy, Ali H.; Ezz-Eldien, Samer S.

2013-10-01

In this paper, a class of fractional diffusion equations with variable coefficients is considered. An accurate and efficient spectral tau technique for solving the fractional diffusion equations numerically is proposed. This method is based upon Chebyshev tau approximation together with Chebyshev operational matrix of Caputo fractional differentiation. Such approach has the advantage of reducing the problem to the solution of a system of algebraic equations, which may then be solved by any standard numerical technique. We apply this general method to solve four specific examples. In each of the examples considered, the numerical results show that the proposed method is of high accuracy and is efficient for solving the time-dependent fractional diffusion equations.

Extraction of a group-pair relation: problem-solving relation from web-board documents.

PubMed

Pechsiri, Chaveevan; Piriyakul, Rapepun

2016-01-01

This paper aims to extract a group-pair relation as a Problem-Solving relation, for example a DiseaseSymptom-Treatment relation and a CarProblem-Repair relation, between two event-explanation groups, a problem-concept group as a symptom/CarProblem-concept group and a solving-concept group as a treatment-concept/repair concept group from hospital-web-board and car-repair-guru-web-board documents. The Problem-Solving relation (particularly Symptom-Treatment relation) including the graphical representation benefits non-professional persons by supporting knowledge of primarily solving problems. The research contains three problems: how to identify an EDU (an Elementary Discourse Unit, which is a simple sentence) with the event concept of either a problem or a solution; how to determine a problem-concept EDU boundary and a solving-concept EDU boundary as two event-explanation groups, and how to determine the Problem-Solving relation between these two event-explanation groups. Therefore, we apply word co-occurrence to identify a problem-concept EDU and a solving-concept EDU, and machine-learning techniques to solve a problem-concept EDU boundary and a solving-concept EDU boundary. We propose using k-mean and Naïve Bayes to determine the Problem-Solving relation between the two event-explanation groups involved with clustering features. In contrast to previous works, the proposed approach enables group-pair relation extraction with high accuracy.

Students’ Mathematical Problem-Solving Abilities Through The Application of Learning Models Problem Based Learning

NASA Astrophysics Data System (ADS)

Nasution, M. L.; Yerizon, Y.; Gusmiyanti, R.

2018-04-01

One of the purpose mathematic learning is to develop problem solving abilities. Problem solving is obtained through experience in questioning non-routine. Improving students’ mathematical problem-solving abilities required an appropriate strategy in learning activities one of them is models problem based learning (PBL). Thus, the purpose of this research is to determine whether the problem solving abilities of mathematical students’ who learn to use PBL better than on the ability of students’ mathematical problem solving by applying conventional learning. This research included quasi experiment with static group design and population is students class XI MIA SMAN 1 Lubuk Alung. Class experiment in the class XI MIA 5 and class control in the class XI MIA 6. The instrument of final test students’ mathematical problem solving used essay form. The result of data final test in analyzed with t-test. The result is students’ mathematical problem solving abilities with PBL better then on the ability of students’ mathematical problem solving by applying conventional learning. It’s seen from the high percentage achieved by the group of students who learn to use PBL for each indicator of students’ mathematical problem solving.

Revising explanatory models to accommodate anomalous genetic phenomena: Problem solving in the context of discovery

NASA Astrophysics Data System (ADS)

Hafner, Robert; Stewart, Jim

Past problem-solving research has provided a basis for helping students structure their knowledge and apply appropriate problem-solving strategies to solve problems for which their knowledge (or mental models) of scientific phenomena is adequate (model-using problem solving). This research examines how problem solving in the domain of Mendelian genetics proceeds in situations where solvers' mental models are insufficient to solve problems at hand (model-revising problem solving). Such situations require solvers to use existing models to recognize anomalous data and to revise those models to accommodate the data. The study was conducted in the context of 9-week high school genetics course and addressed: the heuristics charactenstic of successful model-revising problem solving: the nature of the model revisions, made by students as well as the nature of model development across problem types; and the basis upon which solvers decide that a revised model is sufficient (that t has both predictive and explanatory power).

Parent-Teacher Communication about Children with Autism Spectrum Disorder: An Examination of Collaborative Problem-Solving

PubMed Central

Azad, Gazi F.; Kim, Mina; Marcus, Steven C.; Mandell, David S.; Sheridan, Susan M.

2016-01-01

Effective parent-teacher communication involves problem-solving concerns about students. Few studies have examined problem solving interactions between parents and teachers of children with autism spectrum disorder (ASD), with a particular focus on identifying communication barriers and strategies for improving them. This study examined the problem-solving behaviors of parents and teachers of children with ASD. Participants included 18 teachers and 39 parents of children with ASD. Parent-teacher dyads were prompted to discuss and provide a solution for a problem that a student experienced at home and at school. Parents and teachers also reported on their problem-solving behaviors. Results showed that parents and teachers displayed limited use of the core elements of problem-solving. Teachers displayed more problem-solving behaviors than parents. Both groups reported engaging in more problem-solving behaviors than they were observed to display during their discussions. Our findings suggest that teacher and parent training programs should include collaborative approaches to problem-solving. PMID:28392604

Parent-Teacher Communication about Children with Autism Spectrum Disorder: An Examination of Collaborative Problem-Solving.

PubMed

Azad, Gazi F; Kim, Mina; Marcus, Steven C; Mandell, David S; Sheridan, Susan M

2016-12-01

Effective parent-teacher communication involves problem-solving concerns about students. Few studies have examined problem solving interactions between parents and teachers of children with autism spectrum disorder (ASD), with a particular focus on identifying communication barriers and strategies for improving them. This study examined the problem-solving behaviors of parents and teachers of children with ASD. Participants included 18 teachers and 39 parents of children with ASD. Parent-teacher dyads were prompted to discuss and provide a solution for a problem that a student experienced at home and at school. Parents and teachers also reported on their problem-solving behaviors. Results showed that parents and teachers displayed limited use of the core elements of problem-solving. Teachers displayed more problem-solving behaviors than parents. Both groups reported engaging in more problem-solving behaviors than they were observed to display during their discussions. Our findings suggest that teacher and parent training programs should include collaborative approaches to problem-solving.

Errors analysis of problem solving using the Newman stage after applying cooperative learning of TTW type

NASA Astrophysics Data System (ADS)

Rr Chusnul, C.; Mardiyana, S., Dewi Retno

2017-12-01

Problem solving is the basis of mathematics learning. Problem solving teaches us to clarify an issue coherently in order to avoid misunderstanding information. Sometimes there may be mistakes in problem solving due to misunderstanding the issue, choosing a wrong concept or misapplied concept. The problem-solving test was carried out after students were given treatment on learning by using cooperative learning of TTW type. The purpose of this study was to elucidate student problem regarding to problem solving errors after learning by using cooperative learning of TTW type. Newman stages were used to identify problem solving errors in this study. The new research used a descriptive method to find out problem solving errors in students. The subject in this study were students of Vocational Senior High School (SMK) in 10th grade. Test and interview was conducted for data collection. Thus, the results of this study suggested problem solving errors in students after learning by using cooperative learning of TTW type for Newman stages.

Rejection Sensitivity and Depression: Indirect Effects Through Problem Solving.

PubMed

Kraines, Morganne A; Wells, Tony T

2017-01-01

Rejection sensitivity (RS) and deficits in social problem solving are risk factors for depression. Despite their relationship to depression and the potential connection between them, no studies have examined RS and social problem solving together in the context of depression. As such, we examined RS, five facets of social problem solving, and symptoms of depression in a young adult sample. A total of 180 participants completed measures of RS, social problem solving, and depressive symptoms. We used bootstrapping to examine the indirect effect of RS on depressive symptoms through problem solving. RS was positively associated with depressive symptoms. A negative problem orientation, impulsive/careless style, and avoidance style of social problem solving were positively associated with depressive symptoms, and a positive problem orientation was negatively associated with depressive symptoms. RS demonstrated an indirect effect on depressive symptoms through two social problem-solving facets: the tendency to view problems as threats to one's well-being and an avoidance problem-solving style characterized by procrastination, passivity, or overdependence on others. These results are consistent with prior research that found a positive association between RS and depression symptoms, but this is the first study to implicate specific problem-solving deficits in the relationship between RS and depression. Our results suggest that depressive symptoms in high RS individuals may result from viewing problems as threats and taking an avoidant, rather than proactive, approach to dealing with problems. These findings may have implications for problem-solving interventions for rejection sensitive individuals.