Physical activity problem-solving inventory for adolescents: Development and initial validation

USDA-ARS?s Scientific Manuscript database

Youth encounter physical activity barriers, often called problems. The purpose of problem-solving is to generate solutions to overcome the barriers. Enhancing problem-solving ability may enable youth to be more physically active. Therefore, a method for reliably assessing physical activity problem-s...

Evaluation of Undergraduate Geologists' Problem Solving and Cognition during Field Exams Using a Mixed Methods Approach

ERIC Educational Resources Information Center

Balliet, Russell N.

2012-01-01

Understanding how geologists conduct fieldwork through analysis of problem solving has significant potential impact on field instruction methods. Recent progress has been made in this area but the problem solving behaviors displayed by geologists during fieldwork and the associated underlying cognition remains poorly understood. We present…

Mathematical Problem Solving Ability of Junior High School Students through Ang’s Framework for Mathematical Modelling Instruction

NASA Astrophysics Data System (ADS)

Fasni, N.; Turmudi, T.; Kusnandi, K.

2017-09-01

This research background of this research is the importance of student problem solving abilities. The purpose of this study is to find out whether there are differences in the ability to solve mathematical problems between students who have learned mathematics using Ang’s Framework for Mathematical Modelling Instruction (AFFMMI) and students who have learned using scientific approach (SA). The method used in this research is a quasi-experimental method with pretest-postest control group design. Data analysis of mathematical problem solving ability using Indepent Sample Test. The results showed that there was a difference in the ability to solve mathematical problems between students who received learning with Ang’s Framework for Mathematical Modelling Instruction and students who received learning with a scientific approach. AFFMMI focuses on mathematical modeling. This modeling allows students to solve problems. The use of AFFMMI is able to improve the solving ability.

The effects of cumulative practice on mathematics problem solving.

PubMed

Mayfield, Kristin H; Chase, Philip N

2002-01-01

This study compared three different methods of teaching five basic algebra rules to college students. All methods used the same procedures to teach the rules and included four 50-question review sessions interspersed among the training of the individual rules. The differences among methods involved the kinds of practice provided during the four review sessions. Participants who received cumulative practice answered 50 questions covering a mix of the rules learned prior to each review session. Participants who received a simple review answered 50 questions on one previously trained rule. Participants who received extra practice answered 50 extra questions on the rule they had just learned. Tests administered after each review included new questions for applying each rule (application items) and problems that required novel combinations of the rules (problem-solving items). On the final test, the cumulative group outscored the other groups on application and problem-solving items. In addition, the cumulative group solved the problem-solving items significantly faster than the other groups. These results suggest that cumulative practice of component skills is an effective method of training problem solving.

The effects of cumulative practice on mathematics problem solving.

PubMed Central

Mayfield, Kristin H; Chase, Philip N

2002-01-01

This study compared three different methods of teaching five basic algebra rules to college students. All methods used the same procedures to teach the rules and included four 50-question review sessions interspersed among the training of the individual rules. The differences among methods involved the kinds of practice provided during the four review sessions. Participants who received cumulative practice answered 50 questions covering a mix of the rules learned prior to each review session. Participants who received a simple review answered 50 questions on one previously trained rule. Participants who received extra practice answered 50 extra questions on the rule they had just learned. Tests administered after each review included new questions for applying each rule (application items) and problems that required novel combinations of the rules (problem-solving items). On the final test, the cumulative group outscored the other groups on application and problem-solving items. In addition, the cumulative group solved the problem-solving items significantly faster than the other groups. These results suggest that cumulative practice of component skills is an effective method of training problem solving. PMID:12102132

Numerical methods for the inverse problem of density functional theory

DOE PAGES

Jensen, Daniel S.; Wasserman, Adam

2017-07-17

Here, the inverse problem of Kohn–Sham density functional theory (DFT) is often solved in an effort to benchmark and design approximate exchange-correlation potentials. The forward and inverse problems of DFT rely on the same equations but the numerical methods for solving each problem are substantially different. We examine both problems in this tutorial with a special emphasis on the algorithms and error analysis needed for solving the inverse problem. Two inversion methods based on partial differential equation constrained optimization and constrained variational ideas are introduced. We compare and contrast several different inversion methods applied to one-dimensional finite and periodic modelmore » systems.« less

Numerical methods for the inverse problem of density functional theory

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

Jensen, Daniel S.; Wasserman, Adam

Here, the inverse problem of Kohn–Sham density functional theory (DFT) is often solved in an effort to benchmark and design approximate exchange-correlation potentials. The forward and inverse problems of DFT rely on the same equations but the numerical methods for solving each problem are substantially different. We examine both problems in this tutorial with a special emphasis on the algorithms and error analysis needed for solving the inverse problem. Two inversion methods based on partial differential equation constrained optimization and constrained variational ideas are introduced. We compare and contrast several different inversion methods applied to one-dimensional finite and periodic modelmore » systems.« less

Teaching Problem Solving; the Effect of Algorithmic and Heuristic Problem Solving Training in Relation to Task Complexity and Relevant Aptitudes.

ERIC Educational Resources Information Center

de Leeuw, L.

Sixty-four fifth and sixth-grade pupils were taught number series extrapolation by either an algorithm, fully prescribed problem-solving method or a heuristic, less prescribed method. The trained problems were within categories of two degrees of complexity. There were 16 subjects in each cell of the 2 by 2 design used. Aptitude Treatment…

A simple level set method for solving Stefan problems

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

Chen, S.; Merriman, B.; Osher, S.

1997-07-15

Discussed in this paper is an implicit finite difference scheme for solving a heat equation and a simple level set method for capturing the interface between solid and liquid phases which are used to solve Stefan problems.

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.

A method for the automated construction of the joint system of equations to solve the problem of the flow distribution in hydraulic networks

NASA Astrophysics Data System (ADS)

Novikov, A. E.

1993-10-01

There are several methods of solving the problem of the flow distribution in hydraulic networks. But all these methods have no mathematical tools for forming joint systems of equations to solve this problem. This paper suggests a method of constructing joint systems of equations to calculate hydraulic circuits of the arbitrary form. The graph concept, according to Kirchhoff, has been introduced.

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.

Developing a Theory of Digitally-Enabled Trial-Based Problem Solving through Simulation Methods: The Case of Direct-Response Marketing

ERIC Educational Resources Information Center

Clark, Joseph Warren

2012-01-01

In turbulent business environments, change is rapid, continuous, and unpredictable. Turbulence undermines those adaptive problem solving methods that generate solutions by extrapolating from what worked (or did not work) in the past. To cope with this challenge, organizations utilize trial-based problem solving (TBPS) approaches in which they…

Perspectives on Problem Solving and Instruction

ERIC Educational Resources Information Center

van Merrienboer, Jeroen J. G.

2013-01-01

Most educators claim that problem solving is important, but they take very different perspective on it and there is little agreement on how it should be taught. This article aims to sort out the different perspectives and discusses problem solving as a goal, a method, and a skill. As a goal, problem solving should not be limited to well-structured…

Impacts of Learning Inventive Problem-Solving Principles: Students' Transition from Systematic Searching to Heuristic Problem Solving

ERIC Educational Resources Information Center

Barak, Moshe

2013-01-01

This paper presents the outcomes of teaching an inventive problem-solving course in junior high schools in an attempt to deal with the current relative neglect of fostering students' creativity and problem-solving capabilities in traditional schooling. The method involves carrying out systematic manipulation with attributes, functions and…

An iterative kernel based method for fourth order nonlinear equation with nonlinear boundary condition

NASA Astrophysics Data System (ADS)

Azarnavid, Babak; Parand, Kourosh; Abbasbandy, Saeid

2018-06-01

This article discusses an iterative reproducing kernel method with respect to its effectiveness and capability of solving a fourth-order boundary value problem with nonlinear boundary conditions modeling beams on elastic foundations. Since there is no method of obtaining reproducing kernel which satisfies nonlinear boundary conditions, the standard reproducing kernel methods cannot be used directly to solve boundary value problems with nonlinear boundary conditions as there is no knowledge about the existence and uniqueness of the solution. The aim of this paper is, therefore, to construct an iterative method by the use of a combination of reproducing kernel Hilbert space method and a shooting-like technique to solve the mentioned problems. Error estimation for reproducing kernel Hilbert space methods for nonlinear boundary value problems have yet to be discussed in the literature. In this paper, we present error estimation for the reproducing kernel method to solve nonlinear boundary value problems probably for the first time. Some numerical results are given out to demonstrate the applicability of the method.

Tour of a Simple Trigonometry Problem

ERIC Educational Resources Information Center

Poon, Kin-Keung

2012-01-01

This article focuses on a simple trigonometric problem that generates a strange phenomenon when different methods are applied to tackling it. A series of problem-solving activities are discussed, so that students can be alerted that the precision of diagrams is important when solving geometric problems. In addition, the problem-solving plan was…

Crime Solving Techniques: Training Bulletin.

ERIC Educational Resources Information Center

Sands, Jack M.

The document is a training bulletin for criminal investigators, explaining the use of probability, logic, lateral thinking, group problem solving, and psychological profiles as methods of solving crimes. One chpater of several pages is devoted to each of the five methods. The use of each method is explained; problems are presented for the user to…

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.

WHAT DOESNT GET MEASURED - DOESNT GET DONE: IMPLEMENTING CONTINUOUS PROCESS IMPROVEMENT IN THE AIR FORCE RESERVE

DTIC Science & Technology

2016-04-01

Practical Problem Solving Method RMD Resource Management Decision ROI Return on Investment SECAF Secretary of the Air Force SECNAV Secretary of...AFSO21 and now AF CPI, this program seeks to train and certify an organic cadre of CPI practitioners to support the use of its standard problem solving ...process known as the AF Practical Problem Solving Method (PPSM) to solve mission critical process deficiencies. The PPSM leverages several industry

Enhancement of problem solving ability of high school students through learning with real engagement in active problem solving (REAPS) model on the concept of heat transfer

NASA Astrophysics Data System (ADS)

Yulindar, A.; Setiawan, A.; Liliawati, W.

2018-05-01

This study aims to influence the enhancement of problem solving ability before and after learning using Real Engagement in Active Problem Solving (REAPS) model on the concept of heat transfer. The research method used is quantitative method with 35 high school students in Pontianak as sample. The result of problem solving ability of students is obtained through the test in the form of 3 description questions. The instrument has tested the validity by the expert judgment and field testing that obtained the validity value of 0.84. Based on data analysis, the value of N-Gain is 0.43 and the enhancement of students’ problem solving ability is in medium category. This was caused of students who are less accurate in calculating the results of answers and they also have limited time in doing the questions given.

Methods Used by Pre-Service Nigeria Certificate in Education Teachers in Solving Quantitative Problems in Chemistry

ERIC Educational Resources Information Center

Danjuma, Ibrahim Mohammed

2011-01-01

This paper reports part of the results of research on chemical problem solving behavior of pre-service teachers in Plateau and Northeastern states of Nigeria. Specifically, it examines and describes the methods used by 204 pre-service teachers in solving quantitative problems from four topics in chemistry. Namely, gas laws; electrolysis;…

Developing a Blended Learning-Based Method for Problem-Solving in Capability Learning

ERIC Educational Resources Information Center

Dwiyogo, Wasis D.

2018-01-01

The main objectives of the study were to develop and investigate the implementation of blended learning based method for problem-solving. Three experts were involved in the study and all three had stated that the model was ready to be applied in the classroom. The implementation of the blended learning-based design for problem-solving was…

Using CAS to Solve Classical Mathematics Problems

ERIC Educational Resources Information Center

Burke, Maurice J.; Burroughs, Elizabeth A.

2009-01-01

Historically, calculus has displaced many algebraic methods for solving classical problems. This article illustrates an algebraic method for finding the zeros of polynomial functions that is closely related to Newton's method (devised in 1669, published in 1711), which is encountered in calculus. By exploring this problem, precalculus students…

A duality approach for solving bounded linear programming problems with fuzzy variables based on ranking functions and its application in bounded transportation problems

NASA Astrophysics Data System (ADS)

Ebrahimnejad, Ali

2015-08-01

There are several methods, in the literature, for solving fuzzy variable linear programming problems (fuzzy linear programming in which the right-hand-side vectors and decision variables are represented by trapezoidal fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings a new method based on the bounded dual simplex method is proposed to determine the fuzzy optimal solution of that kind of fuzzy variable linear programming problems in which some or all variables are restricted to lie within lower and upper bounds. To illustrate the proposed method, an application example is solved and the obtained results are given. The advantages of the proposed method over existing methods are discussed. Also, one application of this algorithm in solving bounded transportation problems with fuzzy supplies and demands is dealt with. The proposed method is easy to understand and to apply for determining the fuzzy optimal solution of bounded fuzzy variable linear programming problems occurring in real-life situations.

The Social Problem-Solving Questionnaire: Evaluation of Psychometric Properties among Turkish Primary School Students

ERIC Educational Resources Information Center

Dereli Iman, Esra

2013-01-01

Problem Statement: Children, like adults, face numerous problems and conflicts in their everyday lives, including issues with peers, siblings, older children, parents, teachers, and other adults. The methods children use to solve such problems are more important than actually facing the problems. The lack of effective social problem-solving skills…

The Effectiveness of Using the Model Method to Solve Word Problems

ERIC Educational Resources Information Center

Bao, Lei

2016-01-01

The aim of this study is to investigate whether the model method is effective to assist primary students to solve word problems. The model method not only provides students with an opportunity to interpret the problem by drawing the rectangular bar but also helps students to visually represent problem situations and relevant relationships on the…

Review on solving the forward problem in EEG source analysis

PubMed Central

Hallez, Hans; Vanrumste, Bart; Grech, Roberta; Muscat, Joseph; De Clercq, Wim; Vergult, Anneleen; D'Asseler, Yves; Camilleri, Kenneth P; Fabri, Simon G; Van Huffel, Sabine; Lemahieu, Ignace

2007-01-01

Background The aim of electroencephalogram (EEG) source localization is to find the brain areas responsible for EEG waves of interest. It consists of solving forward and inverse problems. The forward problem is solved by starting from a given electrical source and calculating the potentials at the electrodes. These evaluations are necessary to solve the inverse problem which is defined as finding brain sources which are responsible for the measured potentials at the EEG electrodes. Methods While other reviews give an extensive summary of the both forward and inverse problem, this review article focuses on different aspects of solving the forward problem and it is intended for newcomers in this research field. Results It starts with focusing on the generators of the EEG: the post-synaptic potentials in the apical dendrites of pyramidal neurons. These cells generate an extracellular current which can be modeled by Poisson's differential equation, and Neumann and Dirichlet boundary conditions. The compartments in which these currents flow can be anisotropic (e.g. skull and white matter). In a three-shell spherical head model an analytical expression exists to solve the forward problem. During the last two decades researchers have tried to solve Poisson's equation in a realistically shaped head model obtained from 3D medical images, which requires numerical methods. The following methods are compared with each other: the boundary element method (BEM), the finite element method (FEM) and the finite difference method (FDM). In the last two methods anisotropic conducting compartments can conveniently be introduced. Then the focus will be set on the use of reciprocity in EEG source localization. It is introduced to speed up the forward calculations which are here performed for each electrode position rather than for each dipole position. Solving Poisson's equation utilizing FEM and FDM corresponds to solving a large sparse linear system. Iterative methods are required to solve these sparse linear systems. The following iterative methods are discussed: successive over-relaxation, conjugate gradients method and algebraic multigrid method. Conclusion Solving the forward problem has been well documented in the past decades. In the past simplified spherical head models are used, whereas nowadays a combination of imaging modalities are used to accurately describe the geometry of the head model. Efforts have been done on realistically describing the shape of the head model, as well as the heterogenity of the tissue types and realistically determining the conductivity. However, the determination and validation of the in vivo conductivity values is still an important topic in this field. In addition, more studies have to be done on the influence of all the parameters of the head model and of the numerical techniques on the solution of the forward problem. PMID:18053144

Augmented Lagrange Hopfield network for solving economic dispatch problem in competitive environment

NASA Astrophysics Data System (ADS)

Vo, Dieu Ngoc; Ongsakul, Weerakorn; Nguyen, Khai Phuc

2012-11-01

This paper proposes an augmented Lagrange Hopfield network (ALHN) for solving economic dispatch (ED) problem in the competitive environment. The proposed ALHN is a continuous Hopfield network with its energy function based on augmented Lagrange function for efficiently dealing with constrained optimization problems. The ALHN method can overcome the drawbacks of the conventional Hopfield network such as local optimum, long computational time, and linear constraints. The proposed method is used for solving the ED problem with two revenue models of revenue based on payment for power delivered and payment for reserve allocated. The proposed ALHN has been tested on two systems of 3 units and 10 units for the two considered revenue models. The obtained results from the proposed methods are compared to those from differential evolution (DE) and particle swarm optimization (PSO) methods. The result comparison has indicated that the proposed method is very efficient for solving the problem. Therefore, the proposed ALHN could be a favorable tool for ED problem in the competitive environment.

Project-Based Learning Using Discussion and Lesson-Learned Methods via Social Media Model for Enhancing Problem Solving Skills

ERIC Educational Resources Information Center

Jewpanich, Chaiwat; Piriyasurawong, Pallop

2015-01-01

This research aims to 1) develop the project-based learning using discussion and lesson-learned methods via social media model (PBL-DLL SoMe Model) used for enhancing problem solving skills of undergraduate in education student, and 2) evaluate the PBL-DLL SoMe Model used for enhancing problem solving skills of undergraduate in education student.…

Examination of the Mathematical Problem-Solving Beliefs and Success Levels of Primary School Teacher Candidates through the Variables of Mathematical Success and Gender

ERIC Educational Resources Information Center

Bal, Ayten Pinar

2015-01-01

The aim of this study is to examine the mathematical problem-solving beliefs and problem-solving success levels of primary school teacher candidates through the variables of academic success and gender. The research was designed according to the mixed methods technique in which qualitative and quantitative methods are used together. The working…

Case-based reasoning in design: An apologia

NASA Technical Reports Server (NTRS)

Pulaski, Kirt

1990-01-01

Three positions are presented and defended: the process of generating solutions in problem solving is viewable as a design task; case-based reasoning is a strong method of problem solving; and a synergism exists between case-based reasoning and design problem solving.

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.

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.

Direct SQP-methods for solving optimal control problems with delays

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

Goellmann, L.; Bueskens, C.; Maurer, H.

The maximum principle for optimal control problems with delays leads to a boundary value problem (BVP) which is retarded in the state and advanced in the costate function. Based on shooting techniques, solution methods for this type of BVP have been proposed. In recent years, direct optimization methods have been favored for solving control problems without delays. Direct methods approximate the control and the state over a fixed mesh and solve the resulting NLP-problem with SQP-methods. These methods dispense with the costate function and have shown to be robust and efficient. In this paper, we propose a direct SQP-method formore » retarded control problems. In contrast to conventional direct methods, only the control variable is approximated by e.g. spline-functions. The state is computed via a high order Runge-Kutta type algorithm and does not enter explicitly the NLP-problem through an equation. This approach reduces the number of optimization variables considerably and is implementable even on a PC. Our method is illustrated by the numerical solution of retarded control problems with constraints. In particular, we consider the control of a continuous stirred tank reactor which has been solved by dynamic programming. This example illustrates the robustness and efficiency of the proposed method. Open questions concerning sufficient conditions and convergence of discretized NLP-problems are discussed.« less

Examining Information Problem-Solving, Knowledge, and Application Gains within Two Instructional Methods: Problem-Based and Computer-Mediated Participatory Simulation

ERIC Educational Resources Information Center

Newell, Terrance S.

2008-01-01

This study compared the effectiveness of two instructional methods--problem-based instruction within a face-to-face context and computer-mediated participatory simulation--in increasing students' content knowledge and application gains in the area of information problem-solving. The instructional methods were implemented over a four-week period. A…

Optimal Price Decision Problem for Simultaneous Multi-article Auction and Its Optimal Price Searching Method by Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Masuda, Kazuaki; Aiyoshi, Eitaro

We propose a method for solving optimal price decision problems for simultaneous multi-article auctions. An auction problem, originally formulated as a combinatorial problem, determines both every seller's whether or not to sell his/her article and every buyer's which article(s) to buy, so that the total utility of buyers and sellers will be maximized. Due to the duality theory, we transform it equivalently into a dual problem in which Lagrange multipliers are interpreted as articles' transaction price. As the dual problem is a continuous optimization problem with respect to the multipliers (i.e., the transaction prices), we propose a numerical method to solve it by applying heuristic global search methods. In this paper, Particle Swarm Optimization (PSO) is used to solve the dual problem, and experimental results are presented to show the validity of the proposed method.

Tour of a simple trigonometry problem

NASA Astrophysics Data System (ADS)

Poon, Kin-Keung

2012-06-01

This article focuses on a simple trigonometric problem that generates a strange phenomenon when different methods are applied to tackling it. A series of problem-solving activities are discussed, so that students can be alerted that the precision of diagrams is important when solving geometric problems. In addition, the problem-solving plan was implemented in a high school and the results indicated that students are relatively weak in problem-solving abilities but they understand and appreciate the thinking process in different stages and steps of the activities.

A Decision Support System for Evaluating and Selecting Information Systems Projects

NASA Astrophysics Data System (ADS)

Deng, Hepu; Wibowo, Santoso

2009-01-01

This chapter presents a decision support system (DSS) for effectively solving the information systems (IS) project selection problem. The proposed DSS recognizes the multidimensional nature of the IS project selection problem, the availability of multicriteria analysis (MA) methods, and the preferences of the decision-maker (DM) on the use of specific MA methods in a given situation. A knowledge base consisting of IF-THEN production rules is developed for assisting the DM with a systematic adoption of the most appropriate method with the efficient use of the powerful reasoning and explanation capabilities of intelligent DSS. The idea of letting the problem to be solved determines the method to be used is incorporated into the proposed DSS. As a result, effective decisions can be made for solving the IS project selection problem. An example is presented to demonstrate the applicability of the proposed DSS for solving the problem of selecting IS projects in real world situations.

Solving large-scale fixed cost integer linear programming models for grid-based location problems with heuristic techniques

NASA Astrophysics Data System (ADS)

Noor-E-Alam, Md.; Doucette, John

2015-08-01

Grid-based location problems (GBLPs) can be used to solve location problems in business, engineering, resource exploitation, and even in the field of medical sciences. To solve these decision problems, an integer linear programming (ILP) model is designed and developed to provide the optimal solution for GBLPs considering fixed cost criteria. Preliminary results show that the ILP model is efficient in solving small to moderate-sized problems. However, this ILP model becomes intractable in solving large-scale instances. Therefore, a decomposition heuristic is proposed to solve these large-scale GBLPs, which demonstrates significant reduction of solution runtimes. To benchmark the proposed heuristic, results are compared with the exact solution via ILP. The experimental results show that the proposed method significantly outperforms the exact method in runtime with minimal (and in most cases, no) loss of optimality.

Assertiveness and problem solving in midwives

PubMed Central

Yurtsal, Zeliha Burcu; Özdemir, Levent

2015-01-01

Background: Midwifery profession is required to bring solutions to problems and a midwife is expected to be an assertive person and to develop midwifery care. This study was planned to examine the relationship between assertiveness and problem-solving skills of midwives. Materials and Methods: This cross-sectional study was conducted with 201 midwives between July 2008 and February 2009 in the city center of Sivas. The Rathus Assertiveness Schedule (RAS) and Problem Solving Inventory (PSI) were used to determine the level of assertiveness and problem-solving skills of midwives. Statistical methods were used as mean, standard deviation, percentage, Student's T, ANOVA and Tukey HSD, Kruskal Wallis, Fisher Exact, Pearson Correlation and Chi-square tests and P < 0.05. Results: The RAS mean scores and the PSI mean scores showed statistically significant differences in terms of a midwife's considering herself as a member of the health team, expressing herself within the health care team, being able to say “no” when necessary, cooperating with her colleagues, taking part in problem-solving skills training. A statistically significant negative correlation was found between the RAS and PSI scores. The RAS scores decreased while the problem-solving scores increased (r: -0451, P < 0.01). Conclusions: There were significant statistical differences between assertiveness levels and problem solving skills of midwives, and midwives who were assertive solved their problems better than did others. Assertiveness and problem-solving skills training will contribute to the success of the midwifery profession. Midwives able to solve problems, and display assertive behaviors will contribute to the development of midwifery profession. PMID:26793247

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.

An adaptive grid algorithm for one-dimensional nonlinear equations

NASA Technical Reports Server (NTRS)

Gutierrez, William E.; Hills, Richard G.

1990-01-01

Richards' equation, which models the flow of liquid through unsaturated porous media, is highly nonlinear and difficult to solve. Step gradients in the field variables require the use of fine grids and small time step sizes. The numerical instabilities caused by the nonlinearities often require the use of iterative methods such as Picard or Newton interation. These difficulties result in large CPU requirements in solving Richards equation. With this in mind, adaptive and multigrid methods are investigated for use with nonlinear equations such as Richards' equation. Attention is focused on one-dimensional transient problems. To investigate the use of multigrid and adaptive grid methods, a series of problems are studied. First, a multigrid program is developed and used to solve an ordinary differential equation, demonstrating the efficiency with which low and high frequency errors are smoothed out. The multigrid algorithm and an adaptive grid algorithm is used to solve one-dimensional transient partial differential equations, such as the diffusive and convective-diffusion equations. The performance of these programs are compared to that of the Gauss-Seidel and tridiagonal methods. The adaptive and multigrid schemes outperformed the Gauss-Seidel algorithm, but were not as fast as the tridiagonal method. The adaptive grid scheme solved the problems slightly faster than the multigrid method. To solve nonlinear problems, Picard iterations are introduced into the adaptive grid and tridiagonal methods. Burgers' equation is used as a test problem for the two algorithms. Both methods obtain solutions of comparable accuracy for similar time increments. For the Burgers' equation, the adaptive grid method finds the solution approximately three times faster than the tridiagonal method. Finally, both schemes are used to solve the water content formulation of the Richards' equation. For this problem, the adaptive grid method obtains a more accurate solution in fewer work units and less computation time than required by the tridiagonal method. The performance of the adaptive grid method tends to degrade as the solution process proceeds in time, but still remains faster than the tridiagonal scheme.

Cognitive functioning and social problem-solving skills in schizophrenia.

PubMed

Hatashita-Wong, Michi; Smith, Thomas E; Silverstein, Steven M; Hull, James W; Willson, Deborah F

2002-05-01

This study examined the relationships between symptoms, cognitive functioning, and social skill deficits in schizophrenia. Few studies have incorporated measures of cognitive functioning and symptoms in predictive models for social problem solving. For our study, 44 participants were recruited from consecutive outpatient admissions. Neuropsychological tests were given to assess cognitive function, and social problem solving was assessed using structured vignettes designed to evoke the participant's ability to generate, evaluate, and apply solutions to social problems. A sequential model-fitting method of analysis was used to incorporate social problem solving, symptom presentation, and cognitive impairment into linear regression models. Predictor variables were drawn from demographic, cognitive, and symptom domains. Because this method of analysis was exploratory and not intended as hierarchical modelling, no a priori hypotheses were proposed. Participants with higher scores on tests of cognitive flexibility were better able to generate accurate, appropriate, and relevant responses to the social problem-solving vignettes. The results suggest that cognitive flexibility is a potentially important mediating factor in social problem-solving competence. While other factors are related to social problem-solving skill, this study supports the importance of cognition and understanding how it relates to the complex and multifaceted nature of social functioning.

A multilevel correction adaptive finite element method for Kohn-Sham equation

NASA Astrophysics Data System (ADS)

Hu, Guanghui; Xie, Hehu; Xu, Fei

2018-02-01

In this paper, an adaptive finite element method is proposed for solving Kohn-Sham equation with the multilevel correction technique. In the method, the Kohn-Sham equation is solved on a fixed and appropriately coarse mesh with the finite element method in which the finite element space is kept improving by solving the derived boundary value problems on a series of adaptively and successively refined meshes. A main feature of the method is that solving large scale Kohn-Sham system is avoided effectively, and solving the derived boundary value problems can be handled efficiently by classical methods such as the multigrid method. Hence, the significant acceleration can be obtained on solving Kohn-Sham equation with the proposed multilevel correction technique. The performance of the method is examined by a variety of numerical experiments.

Enhanced Critical Thinking Skills through Problem-Solving Games in Secondary Schools

ERIC Educational Resources Information Center

McDonald, Scott Douglas

2017-01-01

Aim/Purpose: Students face many challenges improving their soft skills such as critical thinking. This paper offers one possible solution to this problem. Background: This paper considers one method of enhancing critical thinking through a problem-solving game called the Coffee Shop. Problem-solving is a key component to critical thinking, and…

Problem solving using soft systems methodology.

PubMed

Land, L

This article outlines a method of problem solving which considers holistic solutions to complex problems. Soft systems methodology allows people involved in the problem situation to have control over the decision-making process.

a Novel Discrete Optimal Transport Method for Bayesian Inverse Problems

NASA Astrophysics Data System (ADS)

Bui-Thanh, T.; Myers, A.; Wang, K.; Thiery, A.

2017-12-01

We present the Augmented Ensemble Transform (AET) method for generating approximate samples from a high-dimensional posterior distribution as a solution to Bayesian inverse problems. Solving large-scale inverse problems is critical for some of the most relevant and impactful scientific endeavors of our time. Therefore, constructing novel methods for solving the Bayesian inverse problem in more computationally efficient ways can have a profound impact on the science community. This research derives the novel AET method for exploring a posterior by solving a sequence of linear programming problems, resulting in a series of transport maps which map prior samples to posterior samples, allowing for the computation of moments of the posterior. We show both theoretical and numerical results, indicating this method can offer superior computational efficiency when compared to other SMC methods. Most of this efficiency is derived from matrix scaling methods to solve the linear programming problem and derivative-free optimization for particle movement. We use this method to determine inter-well connectivity in a reservoir and the associated uncertainty related to certain parameters. The attached file shows the difference between the true parameter and the AET parameter in an example 3D reservoir problem. The error is within the Morozov discrepancy allowance with lower computational cost than other particle methods.

Assessing Creative Problem-Solving with Automated Text Grading

ERIC Educational Resources Information Center

Wang, Hao-Chuan; Chang, Chun-Yen; Li, Tsai-Yen

2008-01-01

The work aims to improve the assessment of creative problem-solving in science education by employing language technologies and computational-statistical machine learning methods to grade students' natural language responses automatically. To evaluate constructs like creative problem-solving with validity, open-ended questions that elicit…

Solving Word Problems using Schemas: A Review of the Literature

PubMed Central

Powell, Sarah R.

2011-01-01

Solving word problems is a difficult task for students at-risk for or with learning disabilities (LD). One instructional approach that has emerged as a valid method for helping students at-risk for or with LD to become more proficient at word-problem solving is using schemas. A schema is a framework for solving a problem. With a schema, students are taught to recognize problems as falling within word-problem types and to apply a problem solution method that matches that problem type. This review highlights two schema approaches for 2nd- and 3rd-grade students at-risk for or with LD: schema-based instruction and schema-broadening instruction. A total of 12 schema studies were reviewed and synthesized. Both types of schema approaches enhanced the word-problem skill of students at-risk for or with LD. Based on the review, suggestions are provided for incorporating word-problem instruction using schemas. PMID:21643477

Knowledge acquisition from natural language for expert systems based on classification problem-solving methods

NASA Technical Reports Server (NTRS)

Gomez, Fernando

1989-01-01

It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM.

Evaluation of POE and instructor-led problem-solving approaches integrated into force and motion lecture classes using a model analysis technique

NASA Astrophysics Data System (ADS)

Rakkapao, S.; Pengpan, T.; Srikeaw, S.; Prasitpong, S.

2014-01-01

This study aims to investigate the use of the predict-observe-explain (POE) approach integrated into large lecture classes on forces and motion. It is compared to the instructor-led problem-solving method using model analysis. The samples are science (SC, N = 420) and engineering (EN, N = 434) freshmen, from Prince of Songkla University, Thailand. Research findings from the force and motion conceptual evaluation indicate that the multimedia-supported POE method promotes students’ learning better than the problem-solving method, in particular for the velocity and acceleration concepts. There is a small shift of the students’ model states after the problem-solving instruction. Moreover, by using model analysis instructors are able to investigate students’ misconceptions and evaluate teaching methods. It benefits instructors in organizing subsequent instructional materials.

Implicit Runge-Kutta Methods with Explicit Internal Stages

NASA Astrophysics Data System (ADS)

Skvortsov, L. M.

2018-03-01

The main computational costs of implicit Runge-Kutta methods are caused by solving a system of algebraic equations at every step. By introducing explicit stages, it is possible to increase the stage (or pseudo-stage) order of the method, which makes it possible to increase the accuracy and avoid reducing the order in solving stiff problems, without additional costs of solving algebraic equations. The paper presents implicit methods with an explicit first stage and one or two explicit internal stages. The results of solving test problems are compared with similar methods having no explicit internal stages.

Spectral collocation for multiparameter eigenvalue problems arising from separable boundary value problems

NASA Astrophysics Data System (ADS)

Plestenjak, Bor; Gheorghiu, Călin I.; Hochstenbach, Michiel E.

2015-10-01

In numerous science and engineering applications a partial differential equation has to be solved on some fairly regular domain that allows the use of the method of separation of variables. In several orthogonal coordinate systems separation of variables applied to the Helmholtz, Laplace, or Schrödinger equation leads to a multiparameter eigenvalue problem (MEP); important cases include Mathieu's system, Lamé's system, and a system of spheroidal wave functions. Although multiparameter approaches are exploited occasionally to solve such equations numerically, MEPs remain less well known, and the variety of available numerical methods is not wide. The classical approach of discretizing the equations using standard finite differences leads to algebraic MEPs with large matrices, which are difficult to solve efficiently. The aim of this paper is to change this perspective. We show that by combining spectral collocation methods and new efficient numerical methods for algebraic MEPs it is possible to solve such problems both very efficiently and accurately. We improve on several previous results available in the literature, and also present a MATLAB toolbox for solving a wide range of problems.

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

Solving Integer Programs from Dependence and Synchronization Problems

DTIC Science & Technology

1993-03-01

DEFF.NSNE Solving Integer Programs from Dependence and Synchronization Problems Jaspal Subhlok March 1993 CMU-CS-93-130 School of Computer ScienceT IC...method Is an exact and efficient way of solving integer programming problems arising in dependence and synchronization analysis of parallel programs...7/;- p Keywords: Exact dependence tesing, integer programming. parallelilzng compilers, parallel program analysis, synchronization analysis Solving

Derivative free Davidon-Fletcher-Powell (DFP) for solving symmetric systems of nonlinear equations

NASA Astrophysics Data System (ADS)

Mamat, M.; Dauda, M. K.; Mohamed, M. A. bin; Waziri, M. Y.; Mohamad, F. S.; Abdullah, H.

2018-03-01

Research from the work of engineers, economist, modelling, industry, computing, and scientist are mostly nonlinear equations in nature. Numerical solution to such systems is widely applied in those areas of mathematics. Over the years, there has been significant theoretical study to develop methods for solving such systems, despite these efforts, unfortunately the methods developed do have deficiency. In a contribution to solve systems of the form F(x) = 0, x ∈ Rn , a derivative free method via the classical Davidon-Fletcher-Powell (DFP) update is presented. This is achieved by simply approximating the inverse Hessian matrix with {Q}k+1-1 to θkI. The modified method satisfied the descent condition and possess local superlinear convergence properties. Interestingly, without computing any derivative, the proposed method never fail to converge throughout the numerical experiments. The output is based on number of iterations and CPU time, different initial starting points were used on a solve 40 benchmark test problems. With the aid of the squared norm merit function and derivative-free line search technique, the approach yield a method of solving symmetric systems of nonlinear equations that is capable of significantly reducing the CPU time and number of iteration, as compared to its counterparts. A comparison between the proposed method and classical DFP update were made and found that the proposed methodis the top performer and outperformed the existing method in almost all the cases. In terms of number of iterations, out of the 40 problems solved, the proposed method solved 38 successfully, (95%) while classical DFP solved 2 problems (i.e. 05%). In terms of CPU time, the proposed method solved 29 out of the 40 problems given, (i.e.72.5%) successfully whereas classical DFP solves 11 (27.5%). The method is valid in terms of derivation, reliable in terms of number of iterations and accurate in terms of CPU time. Thus, suitable and achived the objective.

The Model Method: Singapore Children's Tool for Representing and Solving Algebraic Word Problems

ERIC Educational Resources Information Center

Ng, Swee Fong; Lee, Kerry

2009-01-01

Solving arithmetic and algebraic word problems is a key component of the Singapore elementary mathematics curriculum. One heuristic taught, the model method, involves drawing a diagram to represent key information in the problem. We describe the model method and a three-phase theoretical framework supporting its use. We conducted 2 studies to…

Inquiry-based problem solving in introductory physics

NASA Astrophysics Data System (ADS)

Koleci, Carolann

What makes problem solving in physics difficult? How do students solve physics problems, and how does this compare to an expert physicist's strategy? Over the past twenty years, physics education research has revealed several differences between novice and expert problem solving. The work of Chi, Feltovich, and Glaser demonstrates that novices tend to categorize problems based on surface features, while experts categorize according to theory, principles, or concepts1. If there are differences between how problems are categorized, then are there differences between how physics problems are solved? Learning more about the problem solving process, including how students like to learn and what is most effective, requires both qualitative and quantitative analysis. In an effort to learn how novices and experts solve introductory electricity problems, a series of in-depth interviews were conducted, transcribed, and analyzed, using both qualitative and quantitative methods. One-way ANOVA tests were performed in order to learn if there are any significant problem solving differences between: (a) novices and experts, (b) genders, (c) students who like to answer questions in class and those who don't, (d) students who like to ask questions in class and those who don't, (e) students employing an interrogative approach to problem solving and those who don't, and (f) those who like physics and those who dislike it. The results of both the qualitative and quantitative methods reveal that inquiry-based problem solving is prevalent among novices and experts, and frequently leads to the correct physics. These findings serve as impetus for the third dimension of this work: the development of Choose Your Own Adventure Physics(c) (CYOAP), an innovative teaching tool in physics which encourages inquiry-based problem solving. 1Chi, M., P. Feltovich, R. Glaser, "Categorization and Representation of Physics Problems by Experts and Novices", Cognitive Science, 5, 121--152 (1981).

The Effect of Dynamic Web Technologies on Student Academic Achievement in Problem-Based Collaborative Learning Environment

ERIC Educational Resources Information Center

Korucu, Agâh Tugrul; Cakir, Hasan

2018-01-01

Some of the 21st century proficiencies expected from people are determined as collaborative working and problem solving. One way to gain these proficiencies is by using collaborative problem solving based on social constructivism theory. Collaborative problem solving is one of the methods allowing for social constructivism in the class. In…

Problem-Solving Training: Effects on the Problem-Solving Skills and Self-Efficacy of Nursing Students

ERIC Educational Resources Information Center

Ancel, Gulsum

2016-01-01

Problem Statement: Problem-Solving (PS) skills have been determined to be an internationally useful strategy for better nursing. That is why PS skills underlie all nursing practice, teamwork, and health care management, and are a main topic in undergraduate nursing education. Thus, there is a need to develop effective methods to teach…

Facilitating problem solving in high school chemistry

NASA Astrophysics Data System (ADS)

Gabel, Dorothy L.; Sherwood, Robert D.

The major purpose for conducting this study was to determine whether certain instructional strategies were superior to others in teaching high school chemistry students problem solving. The effectiveness of four instructional strategies for teaching problem solving to students of various proportional reasoning ability, verbal and visual preference, and mathematics anxiety were compared in this aptitude by treatment interaction study. The strategies used were the factor-label method, analogies, diagrams, and proportionality. Six hundred and nine high school students in eight schools were randomly assigned to one of four teaching strategies within each classroom. Students used programmed booklets to study the mole concept, the gas laws, stoichiometry, and molarity. Problem-solving ability was measured by a series of immediate posttests, delayed posttests and the ACS-NSTA Examination in High School Chemistry. Results showed that mathematics anxiety is negatively correlated with science achievement and that problem solving is dependent on students' proportional reasoning ability. The factor-label method was found to be the most desirable method and proportionality the least desirable method for teaching the mole concept. However, the proportionality method was best for teaching the gas laws. Several second-order interactions were found to be significant when mathematics anxiety was one of the aptitudes involved.

Solving mixed integer nonlinear programming problems using spiral dynamics optimization algorithm

NASA Astrophysics Data System (ADS)

Kania, Adhe; Sidarto, Kuntjoro Adji

2016-02-01

Many engineering and practical problem can be modeled by mixed integer nonlinear programming. This paper proposes to solve the problem with modified spiral dynamics inspired optimization method of Tamura and Yasuda. Four test cases have been examined, including problem in engineering and sport. This method succeeds in obtaining the optimal result in all test cases.

An accurate method for solving a class of fractional Sturm-Liouville eigenvalue problems

NASA Astrophysics Data System (ADS)

Kashkari, Bothayna S. H.; Syam, Muhammed I.

2018-06-01

This article is devoted to both theoretical and numerical study of the eigenvalues of nonsingular fractional second-order Sturm-Liouville problem. In this paper, we implement a fractional-order Legendre Tau method to approximate the eigenvalues. This method transforms the Sturm-Liouville problem to a sparse nonsingular linear system which is solved using the continuation method. Theoretical results for the considered problem are provided and proved. Numerical results are presented to show the efficiency of the proposed method.

Solving traveling salesman problems with DNA molecules encoding numerical values.

PubMed

Lee, Ji Youn; Shin, Soo-Yong; Park, Tai Hyun; Zhang, Byoung-Tak

2004-12-01

We introduce a DNA encoding method to represent numerical values and a biased molecular algorithm based on the thermodynamic properties of DNA. DNA strands are designed to encode real values by variation of their melting temperatures. The thermodynamic properties of DNA are used for effective local search of optimal solutions using biochemical techniques, such as denaturation temperature gradient polymerase chain reaction and temperature gradient gel electrophoresis. The proposed method was successfully applied to the traveling salesman problem, an instance of optimization problems on weighted graphs. This work extends the capability of DNA computing to solving numerical optimization problems, which is contrasted with other DNA computing methods focusing on logical problem solving.

Assessment of Expert-Novice Chemistry Problem Solving Using HyperCard: Early Findings.

ERIC Educational Resources Information Center

Kumar, David D.

1993-01-01

Results of a HyperCard method for assessing the performance of expert and novice high school chemistry students solving stoichiometric chemistry problems (balancing chemical equations) is reported. MANOVA results indicate significant difference between expert and novice students solving the five stoichiometric chemistry problems using…

Determining Students' Attitude towards Physics through Problem-Solving Strategy

ERIC Educational Resources Information Center

Erdemir, Naki

2009-01-01

In this study, the effects of teacher-directed and self-directed problem-solving strategies on students' attitudes toward physics were explored. Problem-solving strategies were used with the experimental group, while the control group was instructed using traditional teaching methods. The study was conducted with 270 students at various high…

Parallel Algorithm Solves Coupled Differential Equations

NASA Technical Reports Server (NTRS)

Hayashi, A.

1987-01-01

Numerical methods adapted to concurrent processing. Algorithm solves set of coupled partial differential equations by numerical integration. Adapted to run on hypercube computer, algorithm separates problem into smaller problems solved concurrently. Increase in computing speed with concurrent processing over that achievable with conventional sequential processing appreciable, especially for large problems.

Developing Legal Problem-Solving Skills.

ERIC Educational Resources Information Center

Nathanson, Stephen

1994-01-01

A law professor explains how he came to view legal problem solving as the driving concept in law school curriculum design and draws on personal experience and a survey of students concerning teaching methods in a commercial law course. He outlines six curriculum design principles for teaching legal problem solving. (MSE)

Teaching Evidence-based Medicine Using Literature for Problem Solving.

ERIC Educational Resources Information Center

Mottonen, Merja; Tapanainen, Paivi; Nuutinen, Matti; Rantala, Heikki; Vainionpaa, Leena; Uhari, Matti

2001-01-01

Evidence-based medicine--the process of using research findings systematically as the basis for clinical decisions--can be taught using problem-solving teaching methods. Evaluates whether it was possible to motivate students to use the original literature by giving them selected patient problems to solve. (Author/ASK)

New Testing Methods to Assess Technical Problem-Solving Ability.

ERIC Educational Resources Information Center

Hambleton, Ronald K.; And Others

Tests to assess problem-solving ability being provided for the Air Force are described, and some details on the development and validation of these computer-administered diagnostic achievement tests are discussed. Three measurement approaches were employed: (1) sequential problem solving; (2) context-free assessment of fundamental skills and…

Students' Problem Solving Approaches for Developing Geologic Models in the Field

ERIC Educational Resources Information Center

Balliet, Russell N.; Riggs, Eric M.; Maltese, Adam V.

2015-01-01

Understanding how geologists conduct fieldwork through analysis of problem solving has significant potential impact on field instruction methods within geology and other science fields. Recent work has highlighted many aspects of fieldwork, but the problem solving behaviors displayed by geologists during fieldwork and the associated cognitive…

Cross-Proportions: A Conceptual Method for Developing Quantitative Problem-Solving Skills

ERIC Educational Resources Information Center

Cook, Elzbieta; Cook, Stephen L.

2005-01-01

The cross-proportion method allows both the instructor and the student to easily determine where an error is made during problem solving. The C-P method supports a strong cognitive foundation upon which students can develop other diagnostic methods as they advance in chemistry and scientific careers.

A Monte-Carlo game theoretic approach for Multi-Criteria Decision Making under uncertainty

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Lund, Jay R.

2011-05-01

Game theory provides a useful framework for studying Multi-Criteria Decision Making problems. This paper suggests modeling Multi-Criteria Decision Making problems as strategic games and solving them using non-cooperative game theory concepts. The suggested method can be used to prescribe non-dominated solutions and also can be used as a method to predict the outcome of a decision making problem. Non-cooperative stability definitions for solving the games allow consideration of non-cooperative behaviors, often neglected by other methods which assume perfect cooperation among decision makers. To deal with the uncertainty in input variables a Monte-Carlo Game Theory (MCGT) approach is suggested which maps the stochastic problem into many deterministic strategic games. The games are solved using non-cooperative stability definitions and the results include possible effects of uncertainty in input variables on outcomes. The method can handle multi-criteria multi-decision-maker problems with uncertainty. The suggested method does not require criteria weighting, developing a compound decision objective, and accurate quantitative (cardinal) information as it simplifies the decision analysis by solving problems based on qualitative (ordinal) information, reducing the computational burden substantially. The MCGT method is applied to analyze California's Sacramento-San Joaquin Delta problem. The suggested method provides insights, identifies non-dominated alternatives, and predicts likely decision outcomes.

A complexity theory model in science education problem solving: random walks for working memory and mental capacity.

PubMed

Stamovlasis, Dimitrios; Tsaparlis, Georgios

2003-07-01

The present study examines the role of limited human channel capacity from a science education perspective. A model of science problem solving has been previously validated by applying concepts and tools of complexity theory (the working memory, random walk method). The method correlated the subjects' rank-order achievement scores in organic-synthesis chemistry problems with the subjects' working memory capacity. In this work, we apply the same nonlinear approach to a different data set, taken from chemical-equilibrium problem solving. In contrast to the organic-synthesis problems, these problems are algorithmic, require numerical calculations, and have a complex logical structure. As a result, these problems cause deviations from the model, and affect the pattern observed with the nonlinear method. In addition to Baddeley's working memory capacity, the Pascual-Leone's mental (M-) capacity is examined by the same random-walk method. As the complexity of the problem increases, the fractal dimension of the working memory random walk demonstrates a sudden drop, while the fractal dimension of the M-capacity random walk decreases in a linear fashion. A review of the basic features of the two capacities and their relation is included. The method and findings have consequences for problem solving not only in chemistry and science education, but also in other disciplines.

Social Problem Solving and Depressive Symptoms Over Time: A Randomized Clinical Trial of Cognitive Behavioral Analysis System of Psychotherapy, Brief Supportive Psychotherapy, and Pharmacotherapy

PubMed Central

Klein, Daniel N.; Leon, Andrew C.; Li, Chunshan; D’Zurilla, Thomas J.; Black, Sarah R.; Vivian, Dina; Dowling, Frank; Arnow, Bruce A.; Manber, Rachel; Markowitz, John C.; Kocsis, James H.

2011-01-01

Objective Depression is associated with poor social problem-solving, and psychotherapies that focus on problem-solving skills are efficacious in treating depression. We examined the associations between treatment, social problem solving, and depression in a randomized clinical trial testing the efficacy of psychotherapy augmentation for chronically depressed patients who failed to fully respond to an initial trial of pharmacotherapy (Kocsis et al., 2009). Method Participants with chronic depression (n = 491) received Cognitive Behavioral Analysis System of Psychotherapy (CBASP), which emphasizes interpersonal problem-solving, plus medication; Brief Supportive Psychotherapy (BSP) plus medication; or medication alone for 12 weeks. Results CBASP plus pharmacotherapy was associated with significantly greater improvement in social problem solving than BSP plus pharmacotherapy, and a trend for greater improvement in problem solving than pharmacotherapy alone. In addition, change in social problem solving predicted subsequent change in depressive symptoms over time. However, the magnitude of the associations between changes in social problem solving and subsequent depressive symptoms did not differ across treatment conditions. Conclusions It does not appear that improved social problem solving is a mechanism that uniquely distinguishes CBASP from other treatment approaches. PMID:21500885

Implementing thinking aloud pair and Pólya problem solving strategies in fractions

NASA Astrophysics Data System (ADS)

Simpol, N. S. H.; Shahrill, M.; Li, H.-C.; Prahmana, R. C. I.

2017-12-01

This study implemented two pedagogical strategies, the Thinking Aloud Pair Problem Solving and Pólya’s Problem Solving, to support students’ learning of fractions. The participants were 51 students (ages 11-13) from two Year 7 classes in a government secondary school in Brunei Darussalam. A mixed method design was employed in the present study, with data collected from the pre- and post-tests, problem solving behaviour questionnaire and interviews. The study aimed to explore if there were differences in the students’ problem solving behaviour before and after the implementation of the problem solving strategies. Results from the Wilcoxon Signed Rank Test revealed a significant difference in the test results regarding student problem solving behaviour, z = -3.68, p = .000, with a higher mean score for the post-test (M = 95.5, SD = 13.8) than for the pre-test (M = 88.9, SD = 15.2). This implied that there was improvement in the students’ problem solving performance from the pre-test to the post-test. Results from the questionnaire showed that more than half of the students increased scores in all four stages of the Pólya’s problem solving strategy, which provided further evidence of the students’ improvement in problem solving.

Problem-Solving Deficits in Iranian People with Borderline Personality Disorder

PubMed Central

Akbari Dehaghi, Ashraf; Kaviani, Hossein; Tamanaeefar, Shima

2014-01-01

Objective: Interventions for people suffering from borderline personality disorder (BPD), such as dialectical behavior therapy, often include a problem-solving component. However, there is an absence of published studies examining the problem-solving abilities of this client group in Iran. The study compared inpatients and outpatients with BPD and a control group on problem-solving capabilities in an Iranian sample. It was hypothesized that patients with BPD would have more deficiencies in this area. Methods: Fifteen patients with BPD were compared to 15 healthy participants. Means-ends problem-solving task (MEPS) was used to measure problem-solving skills in both groups. Results: BPD group reported less effective strategies in solving problems as opposed to the healthy group. Compared to the control group, participants with BPD provided empirical support for the use of problem-solving interventions with people suffering from BPD. Conclusions: The findings supported the idea that a problem-solving intervention can be efficiently applied either as a stand-alone therapy or in conjunction with other available psychotherapies to treat people with BPD. PMID:25798169

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 Effect of Metacognitive Instruction on Problem Solving Skills in Iranian Students of Health Sciences

PubMed Central

Safari, Yahya; Meskini, Habibeh

2016-01-01

Background: Learning requires application of such processes as planning, supervision, monitoring and reflection that are included in the metacognition. Studies have shown that metacognition is associated with problem solving skills. The current research was conducted to investigate the impact of metacognitive instruction on students’ problem solving skills. Methods: The study sample included 40 students studying in the second semester at Kermanshah University of Medical Sciences, 2013-2014. They were selected through convenience sampling technique and were randomly assigned into two equal groups of experimental and control. For the experimental group, problem solving skills were taught through metacognitive instruction during ten two-hour sessions and for the control group, problem solving skills were taught via conventional teaching method. The instrument for data collection included problem solving inventory (Heppner, 1988), which was administered before and after instruction. The validity and reliability of the questionnaire had been previously confirmed. The collected data were analyzed by descriptive statistics, mean and standard deviation and the hypotheses were tested by t-test and ANCOVA. Results: The findings of the posttest showed that the total mean scores of problem solving skills in the experimental and control groups were 151.90 and 101.65, respectively, indicating a significant difference between them (p<0.001). This difference was also reported to be statistically significant between problem solving skills and its components, including problem solving confidence, orientation-avoidance coping style and personal control (p<0.001). No significant difference, however, was found between the students’ mean scores in terms of gender and major. Conclusion: Since metacognitive instruction has positive effects on students’ problem solving skills and is required to enhance academic achievement, metacognitive strategies are recommended to be taught to the students. PMID:26234970

Tracing for the problem-solving ability in advanced calculus class based on modification of SAVI model at Universitas Negeri Semarang

NASA Astrophysics Data System (ADS)

Pujiastuti, E.; Waluya, B.; Mulyono

2018-03-01

There were many ways of solving the problem offered by the experts. The author combines various ways of solving the problem as a form of novelty. Among the learning model that was expected to support the growth of problem-solving skills was SAVI. The purpose, to obtain trace results from the analysis of the problem-solving ability of students in the Dual Integral material. The research method was a qualitative approach. Its activities include tests was filled with mathematical connections, observation, interviews, FGD, and triangulation. The results were: (1) some students were still experiencing difficulties in solving the problems. (2) The application of modification of SAVI learning model effective in supporting the growth of problem-solving abilities. (3) The strength of the students related to solving the problem, there were two students in the excellent category, there were three students in right classes and one student in the medium group.

Recherche Empirique sur les Processes de reequilibrage de l'attention dans le traitement des problemes educatifs. (Empirical Study on the Process of Redirecting Attention in Educational Problem-Solving.)

ERIC Educational Resources Information Center

Wasserstein-Warnet, Marc M.

2000-01-01

Asserts that traditional strategies of problem-solving are inadequate and that a new method is needed. Suggests four ways to redirect attention in problem solving: overcoming an instant or linear perception of time, interacting between the problem's components and its whole, searching for the meaning or sense of a problem, and studying the…

Neighboring extremals of dynamic optimization problems with path equality constraints

NASA Technical Reports Server (NTRS)

Lee, A. Y.

1988-01-01

Neighboring extremals of dynamic optimization problems with path equality constraints and with an unknown parameter vector are considered in this paper. With some simplifications, the problem is reduced to solving a linear, time-varying two-point boundary-value problem with integral path equality constraints. A modified backward sweep method is used to solve this problem. Two example problems are solved to illustrate the validity and usefulness of the solution technique.

The Acquisition of Problem-Solving Skills in Mathematics: How Animations Can Aid Understanding of Structural Problem Features and Solution Procedures

ERIC Educational Resources Information Center

Scheiter, Katharina; Gerjets, Peter; Schuh, Julia

2010-01-01

In this paper the augmentation of worked examples with animations for teaching problem-solving skills in mathematics is advocated as an effective instructional method. First, in a cognitive task analysis different knowledge prerequisites are identified for solving mathematical word problems. Second, it is argued that so called hybrid animations…

The Universal Traveler, A Soft-Systems Guide to: Creativity, Problem Solving, and the Process of Reaching Goals. [Revised Edition.

ERIC Educational Resources Information Center

Koberg, Don; Bagnall, Jim

This publication provides an organizational scheme for a creative problem solving process. The authors indicate that all problems can benefit from the same logical and orderly process now employed to solve many complex problems. The principles remain constant; only specific methods change. Chapter 1 analyzes the development of creativity and fear…

Geo-Sandbox: An Interactive Geoscience Training Tool with Analytics to Better Understand Student Problem Solving Approaches

NASA Astrophysics Data System (ADS)

Butt, N.; Pidlisecky, A.; Ganshorn, H.; Cockett, R.

2015-12-01

The software company 3 Point Science has developed three interactive learning programs designed to teach, test and practice visualization skills and geoscience concepts. A study was conducted with 21 geoscience students at the University of Calgary who participated in 2 hour sessions of software interaction and written pre and post-tests. Computer and SMART touch table interfaces were used to analyze user interaction, problem solving methods and visualization skills. By understanding and pinpointing user problem solving methods it is possible to reconstruct viewpoints and thought processes. This could allow us to give personalized feedback in real time, informing the user of problem solving tips and possible misconceptions.

Solution mechanism guide: implementing innovation within a research & development organization.

PubMed

Keeton, Kathryn E; Richard, Elizabeth E; Davis, Jeffrey R

2014-10-01

In order to create a culture more open to novel problem-solving mechanisms, NASA's Human Health and Performance Directorate (HH&P) created a strategic knowledge management tool that educates employees about innovative problem-solving techniques, the Solution Mechanism Guide (SMG). The SMG is a web-based, interactive guide that leverages existing and innovative problem-solving methods and presents this information as a unique user experience so that the employee is empowered to make the best decision about which problem-solving tool best meets their needs. By integrating new and innovative methods with existing problem solving tools, the SMG seamlessly introduces open innovation and collaboration concepts within HH&P to more effectively address human health and performance risks. This commentary reviews the path of creating a more open and innovative culture within HH&P and the process and development steps that were taken to develop the SMG.

The Relationship between Functional Status and Judgment/Problem Solving Among Individuals with Dementia

PubMed Central

Mayo, Ann M.; Wallhagen, Margaret; Cooper, Bruce A.; Mehta, Kala; Ross, Leslie; Miller, Bruce

2012-01-01

Objective To determine the relationship between functional status (independent activities of daily living) and judgment/problem solving and the extent to which select demographic characteristics such as dementia subtype and cognitive measures may moderate that relationship in older adult individuals with dementia. Methods The National Alzheimer’s Coordinating Center Universal Data Set was accessed for a study sample of 3,855 individuals diagnosed with dementia. Primary variables included functional status, judgment/problem solving, and cognition. Results Functional status was related to judgment/problem solving (r= 0.66; p< .0005). Functional status and cognition jointly predicted 56% of the variance in judgment/problem solving (R-squared = .56, p <.0005). As cognition decreases, the prediction of poorer judgment/problem solving by functional status became stronger. Conclusions Among individuals with a diagnosis of dementia, declining functional status as well as declining cognition should raise concerns about judgment/problem solving. PMID:22786576

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.

An Investigation of Maternal Emotion Socialization Behaviors, Children's Self-Perceptions, and Social Problem-Solving Skills

ERIC Educational Resources Information Center

Ozkan, Hurside Kubra; Aksoy, Ayse Belgin

2017-01-01

Purpose: The present study aims to investigate maternal emotion socialization, children's self-perception, and social problem-solving skills. In addition, this study describes the association between the levels of children's self-perception and social problem-solving skills. Research Methods: This is a quantitative study adopting a relational…

Three Measures of Family Problem Solving Behavior: A Procedural Manual.

ERIC Educational Resources Information Center

Nickerson, Mark; And Others

The procedural details of three measures of family problem-solving behavior are presented. These measures are used to code videotapes that are recorded when family members discuss and try to solve a family problem that they consider important. The measures were developed to accompany methods for training parents and their preadolescent and…

Problem-Solving Skills among Precollege Students in Clinical Immunology and Microbiology: Classifying Strategies with a Rubric and Artificial Neural Network Technology.

ERIC Educational Resources Information Center

Kanowith-Klein, Susan; Stave, Mel; Stevens, Ron; Casillas, Adrian M.

2001-01-01

Investigates methods for classifying problem solving strategies of high school students who studied infectious and non-infectious diseases by using a software system that can generate a picture of students' strategies in solving problems. (Contains 24 references.) (Author/YDS)

Pre-Service and In-Service Teachers' Metacognitive Knowledge about Problem-Solving Strategies

ERIC Educational Resources Information Center

Metallidou, Panayiota

2009-01-01

The present study based on Antonietti, A., Ignazi, S., & Perego, P. (2000). Metacognitive knowledge about problem-solving methods. "British Journal of Educational Psychology, 70", 1-16 methodology with the aim to examine primary school teachers' metacognitive knowledge about problem-solving strategies. A sample of 338 in-service (172) and…

Teaching Teamwork and Problem Solving Concurrently

ERIC Educational Resources Information Center

Goltz, Sonia M.; Hietapelto, Amy B.; Reinsch, Roger W.; Tyrell, Sharon K.

2008-01-01

Teamwork and problem-solving skills have frequently been identified by business leaders as being key competencies; thus, teaching methods such as problem-based learning and team-based learning have been developed. However, the focus of these methods has been on teaching one skill or the other. A key argument for teaching the skills concurrently is…

Association Between Anticipatory Grief and Problem Solving Among Family Caregivers of Persons with Cognitive Impairment

PubMed Central

Fowler, Nicole R.; Hansen, Alexandra S.; Barnato, Amber E.; Garand, Linda

2013-01-01

Objective Measure perceived involvement in medical decision making and determine if anticipatory grief is associated with problem solving among family caregivers of older adults with cognitive impairment. Method Retrospective analysis of baseline data from a caregiver intervention (n=73). Multivariable regression models testing the association between caregivers’ anticipatory grief, measured by the Anticipatory Grief Scale (AGS), with problem solving abilities, measured by the Social Problem Solving Inventory – Revised: Short Form (SPSI-R: S). Results 47/73 (64%) of caregivers reported involvement in medical decision making. Mean AGS was 70.1 (± 14.8) and mean SPSI-R:S was 107.2 (± 11.6). Higher AGS scores were associated with lower positive problem orientation (P=0.041) and higher negative problem orientation scores (P=0.001) but not other components of problem solving- rational problem solving, avoidance style, and impulsivity/carelessness style. Discussion Higher anticipatory grief among family caregivers impaired problem solving, which could have negative consequences for their medical decision making responsibilities. PMID:23428394

Analysis of students’ creative thinking level in problem solving based on national council of teachers of mathematics

NASA Astrophysics Data System (ADS)

Hobri; Suharto; Rifqi Naja, Ahmad

2018-04-01

This research aims to determine students’ creative thinking level in problem solving based on NCTM in function subject. The research type is descriptive with qualitative approach. Data collection methods which were used are test and interview. Creative thinking level in problem solving based on NCTM indicators consists of (1) Make mathematical model from a contextual problem and solve the problem, (2) Solve problem using various possible alternatives, (3) Find new alternative(s) to solve the problem, (4) Determine the most efficient and effective alternative for that problem, (5) Review and correct mistake(s) on the process of problem solving. Result of the research showed that 10 students categorized in very satisfying level, 23 students categorized in satisfying level and 1 students categorized in less satisfying level. Students in very satisfying level meet all indicators, students in satisfying level meet first, second, fourth, and fifth indicator, while students in less satisfying level only meet first and fifth indicator.

Application of the boundary integral method to immiscible displacement problems

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

Masukawa, J.; Horne, R.N.

1988-08-01

This paper presents an application of the boundary integral method (BIM) to fluid displacement problems to demonstrate its usefulness in reservoir simulation. A method for solving two-dimensional (2D), piston-like displacement for incompressible fluids with good accuracy has been developed. Several typical example problems with repeated five-spot patterns were solved for various mobility ratios. The solutions were compared with the analytical solutions to demonstrate accuracy. Singularity programming was found to be a major advantage in handling flow in the vicinity of wells. The BIM was found to be an excellent way to solve immiscible displacement problems. Unlike analytic methods, it canmore » accommodate complex boundary shapes and does not suffer from numerical dispersion at the front.« less

Assessing metacognition of grade 2 and grade 4 students using an adaptation of multi-method interview approach during mathematics problem-solving

NASA Astrophysics Data System (ADS)

Kuzle, A.

2018-06-01

The important role that metacognition plays as a predictor for student mathematical learning and for mathematical problem-solving, has been extensively documented. But only recently has attention turned to primary grades, and more research is needed at this level. The goals of this paper are threefold: (1) to present metacognitive framework during mathematics problem-solving, (2) to describe their multi-method interview approach developed to study student mathematical metacognition, and (3) to empirically evaluate the utility of their model and the adaptation of their approach in the context of grade 2 and grade 4 mathematics problem-solving. The results are discussed not only with regard to further development of the adapted multi-method interview approach, but also with regard to their theoretical and practical implications.

Gender differences in algebraic thinking ability to solve mathematics problems

NASA Astrophysics Data System (ADS)

Kusumaningsih, W.; Darhim; Herman, T.; Turmudi

2018-05-01

This study aimed to conduct a gender study on students' algebraic thinking ability in solving a mathematics problem, polyhedron concept, for grade VIII. This research used a qualitative method. The data was collected using: test and interview methods. The subjects in this study were eight male and female students with different level of abilities. It was found that the algebraic thinking skills of male students reached high group of five categories. They were superior in terms of reasoning and quick understanding in solving problems. Algebraic thinking ability of high-achieving group of female students also met five categories of algebraic thinking indicators. They were more diligent, tenacious and thorough in solving problems. Algebraic thinking ability of male students in medium category only satisfied three categories of algebraic thinking indicators. They were sufficient in terms of reasoning and understanding in solving problems. Algebraic thinking ability group of female students in medium group also satisfied three categories of algebraic thinking indicators. They were fairly diligent, tenacious and meticulous on working on the problems.

Alternative Representations for Algebraic Problem Solving: When Are Graphs Better than Equations?

ERIC Educational Resources Information Center

Mielicki, Marta K.; Wiley, Jennifer

2016-01-01

Successful algebraic problem solving entails adaptability of solution methods using different representations. Prior research has suggested that students are more likely to prefer symbolic solution methods (equations) over graphical ones, even when graphical methods should be more efficient. However, this research has not tested how representation…

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.

The Effects of Problem-Solving Teaching on Creative Thinking among District 2 High School Students in Sari City.

PubMed

Nozari, Ali Yazdanpanah; Siamian, Hasan

2014-12-01

Nowadays, regarding the learners' needs and social conditions, it is obviously needed to revise and reconsider the traditional methods and approaches in teaching. The problem solving approach is one of the new ways in Teaching and learning process. This study aimed at studying and examining the effect of "problem-solving" approach on creative thinking of high school female students. An experimental method is used for this research. In this research, 342 out of 3047 female-students from Sari high schools were randomly selected. These 342 students were divided into two groups (experimental and control) in which there were seven classrooms. The total number of students in every group was about 171. After testing them with Jamal Abedi creativity test, it was revealed that two groups were equal in creativity score. The tests were done through Requirements. The experimental group was taught by problem solving method for three months while the control group was taught by traditional method. The research results showed that using descriptive indices and t-test for the two independent sample groups in which problem solving teaching method was used in teaching processes had an effect on creativity level in comparison with traditional method used in the control group. Considering the results of this study, the application of problem-solving teaching methods increased the creativity and its components (fluidity, expansion, originality and flexibility) in learners, therefore, it is recommended that students be encouraged to take classes on frequent responses on various topics (variability) and draw attention on different issues, and expand their analysis on elements in particular courses like art (expansion). To enhance the learner's mental flexibility and attention to various aspects, they are encouraged to provide a variety of responses.

Gauging the Gaps in Student Problem-Solving Skills: Assessment of Individual and Group Use of Problem-Solving Strategies Using Online Discussions

ERIC Educational Resources Information Center

Anderson, William L.; Mitchell, Steven M.; Osgood, Marcy P.

2008-01-01

For the past 3 yr, faculty at the University of New Mexico, Department of Biochemistry and Molecular Biology have been using interactive online Problem-Based Learning (PBL) case discussions in our large-enrollment classes. We have developed an illustrative tracking method to monitor student use of problem-solving strategies to provide targeted…

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

Performance comparison of some evolutionary algorithms on job shop scheduling problems

NASA Astrophysics Data System (ADS)

Mishra, S. K.; Rao, C. S. P.

2016-09-01

Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.

Approximate static condensation algorithm for solving multi-material diffusion problems on meshes non-aligned with material interfaces

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

Kikinzon, Evgeny; Kuznetsov, Yuri; Lipnikov, Konstatin

In this study, we describe a new algorithm for solving multi-material diffusion problem when material interfaces are not aligned with the mesh. In this case interface reconstruction methods are used to construct approximate representation of interfaces between materials. They produce so-called multi-material cells, in which materials are represented by material polygons that contain only one material. The reconstructed interface is not continuous between cells. Finally, we suggest the new method for solving multi-material diffusion problems on such meshes and compare its performance with known homogenization methods.

Approximate static condensation algorithm for solving multi-material diffusion problems on meshes non-aligned with material interfaces

DOE PAGES

Kikinzon, Evgeny; Kuznetsov, Yuri; Lipnikov, Konstatin; ...

2017-07-08

In this study, we describe a new algorithm for solving multi-material diffusion problem when material interfaces are not aligned with the mesh. In this case interface reconstruction methods are used to construct approximate representation of interfaces between materials. They produce so-called multi-material cells, in which materials are represented by material polygons that contain only one material. The reconstructed interface is not continuous between cells. Finally, we suggest the new method for solving multi-material diffusion problems on such meshes and compare its performance with known homogenization methods.

An approach to solve replacement problems under intuitionistic fuzzy nature

NASA Astrophysics Data System (ADS)

Balaganesan, M.; Ganesan, K.

2018-04-01

Due to impreciseness to solve the day to day problems the researchers use fuzzy sets in their discussions of the replacement problems. The aim of this paper is to solve the replacement theory problems with triangular intuitionistic fuzzy numbers. An effective methodology based on fuzziness index and location index is proposed to determine the optimal solution of the replacement problem. A numerical example is illustrated to validate the proposed method.

New displacement-based methods for optimal truss topology design

NASA Technical Reports Server (NTRS)

Bendsoe, Martin P.; Ben-Tal, Aharon; Haftka, Raphael T.

1991-01-01

Two alternate methods for maximum stiffness truss topology design are presented. The ground structure approach is used, and the problem is formulated in terms of displacements and bar areas. This large, nonconvex optimization problem can be solved by a simultaneous analysis and design approach. Alternatively, an equivalent, unconstrained, and convex problem in the displacements only can be formulated, and this problem can be solved by a nonsmooth, steepest descent algorithm. In both methods, the explicit solving of the equilibrium equations and the assembly of the global stiffness matrix are circumvented. A large number of examples have been studied, showing the attractive features of topology design as well as exposing interesting features of optimal topologies.

Invisibility problem in acoustics, electromagnetism and heat transfer. Inverse design method

NASA Astrophysics Data System (ADS)

Alekseev, G.; Tokhtina, A.; Soboleva, O.

2017-10-01

Two approaches (direct design and inverse design methods) for solving problems of designing devices providing invisibility of material bodies of detection using different physical fields - electromagnetic, acoustic and static are discussed. The second method is applied for solving problems of designing cloaking devices for the 3D stationary thermal scattering model. Based on this method the design problems under study are reduced to respective control problems. The material parameters (radial and tangential heat conductivities) of the inhomogeneous anisotropic medium filling the thermal cloak and the density of auxiliary heat sources play the role of controls. A unique solvability of direct thermal scattering problem in the Sobolev space is proved and the new estimates of solutions are established. Using these results, the solvability of control problem is proved and the optimality system is derived. Based on analysis of optimality system, the stability estimates of optimal solutions are established and numerical algorithms for solving particular thermal cloaking problem are proposed.

A case study of analyzing 11th graders’ problem solving ability on heat and temperature topic

NASA Astrophysics Data System (ADS)

Yulianawati, D.; Muslim; Hasanah, L.; Samsudin, A.

2018-05-01

Problem solving ability must be owned by students after the process of physics learning so that the concept of physics becomes meaningful. Consequently, the research aims to describe their problem solving ability. Metacognition is contributed to physics learning to the success of students in solving problems. This research has already been implemented to 37 science students (30 women and 7 men) of eleventh grade from one of the secondary schools in Bandung. The research methods utilized the single case study with embedded research design. The instrument is Heat and Temperature Problem Solving Ability Test (HT-PSAT) which consists of twelve questions from three context problems. The result shows that the average value of the test is 8.27 out of the maximum total value of 36. In conclusion, eleventh graders’ problem-solving ability is still under expected. The implication of the findings is able to create learning situations which are probably developing students to embrace better problem solving ability.

Active and Passive Problem Solving: Moderating Role in the Relation between Depressive Symptoms and Future Suicidal Ideation Varies by Suicide Attempt History

PubMed Central

Quiñones, Victoria; Jurska, Justyna; Fener, Eileen; Miranda, Regina

2016-01-01

Objective Research suggests that being unable to generate solutions to problems in times of distress may contribute to suicidal thoughts and behavior, and that depression is associated with problem solving deficits. This study examined active and passive problem solving as moderators of the association between depressive symptoms and future suicidal ideation (SI) among suicide attempters and non-attempters. Method Young adults (n = 324, 73% female, Mage = 19, SD = 2.22) with (n = 78) and without (n = 246) a suicide attempt history completed a problem-solving task, self-report measures of hopelessness, depression, and SI at baseline, and also completed a self-report measure of SI at 6-month follow-up. Results Passive problem solving was higher among suicide attempters but did not moderate the association between depressive symptoms and future SI. Among attempters, active problem solving buffered against depressive symptoms in predicting future SI. Conclusions Suicide prevention should foster active problem solving, especially among suicide attempters. PMID:25760651

Conceptual problem solving in high school physics

NASA Astrophysics Data System (ADS)

Docktor, Jennifer L.; Strand, Natalie E.; Mestre, José P.; Ross, Brian H.

2015-12-01

Problem solving is a critical element of learning physics. However, traditional instruction often emphasizes the quantitative aspects of problem solving such as equations and mathematical procedures rather than qualitative analysis for selecting appropriate concepts and principles. This study describes the development and evaluation of an instructional approach called Conceptual Problem Solving (CPS) which guides students to identify principles, justify their use, and plan their solution in writing before solving a problem. The CPS approach was implemented by high school physics teachers at three schools for major theorems and conservation laws in mechanics and CPS-taught classes were compared to control classes taught using traditional problem solving methods. Information about the teachers' implementation of the approach was gathered from classroom observations and interviews, and the effectiveness of the approach was evaluated from a series of written assessments. Results indicated that teachers found CPS easy to integrate into their curricula, students engaged in classroom discussions and produced problem solutions of a higher quality than before, and students scored higher on conceptual and problem solving measures.

Effects of problem-based learning vs. traditional lecture on Korean nursing students' critical thinking, problem-solving, and self-directed learning.

PubMed

Choi, Eunyoung; Lindquist, Ruth; Song, Yeoungsuk

2014-01-01

Problem-based learning (PBL) is a method widely used in nursing education to develop students' critical thinking skills to solve practice problems independently. Although PBL has been used in nursing education in Korea for nearly a decade, few studies have examined its effects on Korean nursing students' learning outcomes, and few Korean studies have examined relationships among these outcomes. The objectives of this study are to examine outcome abilities including critical thinking, problem-solving, and self-directed learning of nursing students receiving PBL vs. traditional lecture, and to examine correlations among these outcome abilities. A quasi-experimental non-equivalent group pretest-posttest design was used. First-year nursing students (N=90) were recruited from two different junior colleges in two cities (GY and GJ) in South Korea. In two selected educational programs, one used traditional lecture methods, while the other used PBL methods. Standardized self-administered questionnaires of critical thinking, problem-solving, and self-directed learning abilities were administered before and at 16weeks (after instruction). Learning outcomes were significantly positively correlated, however outcomes were not statistically different between groups. Students in the PBL group improved across all abilities measured, while student scores in the traditional lecture group decreased in problem-solving and self-directed learning. Critical thinking was positively associated with problem-solving and self-directed learning (r=.71, and r=.50, respectively, p<.001); problem-solving was positively associated with self-directed learning (r=.75, p<.001). Learning outcomes of PBL were not significantly different from traditional lecture in this small underpowered study, despite positive trends. Larger studies are recommended to study effects of PBL on critical student abilities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Problem Solving Method Based on E-Learning System for Engineering Education

ERIC Educational Resources Information Center

Khazaal, Hasan F.

2015-01-01

Encouraging engineering students to handle advanced technology with multimedia, as well as motivate them to have the skills of solving the problem, are the missions of the teacher in preparing students for a modern professional career. This research proposes a scenario of problem solving in basic electrical circuits based on an e-learning system…

Mathematical Problem Solving among Latina/o Kindergartners: An Analysis of Opportunities to Learn

ERIC Educational Resources Information Center

Turner, Erin E.; Celedon-Pattichis, Sylvia

2011-01-01

This study explores opportunities to learn mathematics problem solving for Latina/o students in 3 kindergarten classrooms in the southwest. Mixed methods were used to examine teaching practices that engaged Latina/o students in problem solving and supported their learning. Findings indicate that although students in all 3 classrooms showed growth…

Toward Teaching Methods that Develop Learning and Enhance Problem Solving Skills in Engineering Students

ERIC Educational Resources Information Center

Loji, K.

2012-01-01

Problem solving skills and abilities are critical in life and more specifically in the engineering field. Unfortunately, significant numbers of South African students who are accessing higher education lack problem solving skills and this results in poor academic performance jeopardizing their progress especially from first to second year. On the…

Use of Social Media in Different Contexts of Information Seeking: Effects of Sex and Problemsolving Style

ERIC Educational Resources Information Center

Kim, Kyung­-Sun; Sin, Sei­-Ching Joanna

2015-01-01

Introduction: Social media are increasingly popular and emerging as important information sources. The study investigates how users' sex and problem-solving style affect their use and evaluation of social media in two contexts. Method: A Web survey including the problem solving inventory (problem solving inventory) was used to collect data. Over…

Learning Problem-Solving through Making Games at the Game Design and Learning Summer Program

ERIC Educational Resources Information Center

Akcaoglu, Mete

2014-01-01

Today's complex and fast-evolving world necessitates young students to possess design and problem-solving skills more than ever. One alternative method of teaching children problem-solving or thinking skills has been using computer programming, and more recently, game-design tasks. In this pre-experimental study, a group of middle school…

Design, Development and Validation of a Model of Problem Solving for Egyptian Science Classes

ERIC Educational Resources Information Center

Shahat, Mohamed A.; Ohle, Annika; Treagust, David F.; Fischer, Hans E.

2013-01-01

Educators and policymakers envision the future of education in Egypt as enabling learners to acquire scientific inquiry and problem-solving skills. In this article, we describe the validation of a model for problem solving and the design of instruments for evaluating new teaching methods in Egyptian science classes. The instruments were based on…

The New Method of Problem Solving in Physics Education by Using SCORM-Compliant Content Package

ERIC Educational Resources Information Center

Gonen, Selahattin; Basaran, Bulent

2008-01-01

In this article, two basic purposes are presented. First, taking effective feedbacks in the electronic learning environment about the learning level of students at the problem solving which are told in physics lessons and laboratories. Second, providing a possibility for students to repeat the subjects and solved problems by watching and…

The Motivation of Secondary School Students in Mathematical Word Problem Solving

ERIC Educational Resources Information Center

Gasco, Javier; Villarroel, Jose-Domingo

2014-01-01

Introduction: Motivation is an important factor in the learning of mathematics. Within this area of education, word problem solving is central in most mathematics curricula of Secondary School. The objective of this research is to detect the differences in motivation in terms of the strategies used to solve word problems. Method: It analyzed the…

Differential Effects of Methylphenidate on Problem Solving in Adults with ADHD

ERIC Educational Resources Information Center

Tucha, Lara; Tucha, Oliver; Sontag, Thomas A.; Stasik, Dorota; Laufkotter, Rainer; Lange, Klaus W.

2011-01-01

Objective: Two studies were performed to assess both divergent and convergent thinking in adults with ADHD. Method: The first study compared the problem-solving abilities of healthy participants (N = 144) and unmedicated adults with ADHD (N = 144). In the second study, problem-solving abilities of adults with diagnosed ADHD (N = 22) were examined…

Instructional Design-Based Research on Problem Solving Strategies

ERIC Educational Resources Information Center

Emre-Akdogan, Elçin; Argün, Ziya

2016-01-01

The main goal of this study is to find out the effect of the instructional design method on the enhancement of problem solving abilities of students. Teaching sessions were applied to ten students who are in 11th grade, to teach them problem solving strategies which are working backwards, finding pattern, adopting a different point of view,…

Self-Monitoring Checklists for Inquiry Problem-Solving: Functional Problem-Solving Methods for Students with Intellectual Disability

ERIC Educational Resources Information Center

Miller, Bridget; Taber-Doughty, Teresa

2014-01-01

Three students with mild to moderate intellectual and multiple disability, enrolled in a self-contained functional curriculum class were taught to use a self-monitoring checklist and science notebook to increase independence in inquiry problem-solving skills. Using a single-subject multiple-probe design, all students acquired inquiry…

Assessing Reflective Thinking in Solving Design Problems: The Development of a Questionnaire

ERIC Educational Resources Information Center

Hong, Yi-Chun; Choi, Ikseon

2015-01-01

Reflection is a critical factor in solving design problems. Using good methods to observe designers' reflection is essential to inform the design of the learning environments that support the development of design problem-solving skills. In this study, we have developed and validated a novel self-reporting questionnaire as an efficient instrument…

Pedagogy and/or technology: Making difference in improving students' problem solving skills

NASA Astrophysics Data System (ADS)

Hrepic, Zdeslav; Lodder, Katherine; Shaw, Kimberly A.

2013-01-01

Pen input computers combined with interactive software may have substantial potential for promoting active instructional methodologies and for facilitating students' problem solving ability. An excellent example is a study in which introductory physics students improved retention, conceptual understanding and problem solving abilities when one of three weekly lectures was replaced with group problem solving sessions facilitated with Tablet PCs and DyKnow software [1,2]. The research goal of the present study was to isolate the effect of the methodology itself (using additional time to teach problem solving) from that of the involved technology. In Fall 2011 we compared the performance of students taking the same introductory physics lecture course while enrolled in two separate problem-solving sections. One section used pen-based computing to facilitate group problem solving while the other section used low-tech methods for one third of the semester (covering Kinematics), and then traded technologies for the middle third of the term (covering Dynamics). Analysis of quiz, exam and standardized pre-post test results indicated no significant difference in scores of the two groups. Combining this result with those of previous studies implies primacy of pedagogy (collaborative problem solving itself) over technology for student learning in problem solving recitations.

The Monte Carlo Method. Popular Lectures in Mathematics.

ERIC Educational Resources Information Center

Sobol', I. M.

The Monte Carlo Method is a method of approximately solving mathematical and physical problems by the simulation of random quantities. The principal goal of this booklet is to suggest to specialists in all areas that they will encounter problems which can be solved by the Monte Carlo Method. Part I of the booklet discusses the simulation of random…

Finite difference and Runge-Kutta methods for solving vibration problems

NASA Astrophysics Data System (ADS)

Lintang Renganis Radityani, Scolastika; Mungkasi, Sudi

2017-11-01

The vibration of a storey building can be modelled into a system of second order ordinary differential equations. If the number of floors of a building is large, then the result is a large scale system of second order ordinary differential equations. The large scale system is difficult to solve, and if it can be solved, the solution may not be accurate. Therefore, in this paper, we seek for accurate methods for solving vibration problems. We compare the performance of numerical finite difference and Runge-Kutta methods for solving large scale systems of second order ordinary differential equations. The finite difference methods include the forward and central differences. The Runge-Kutta methods include the Euler and Heun methods. Our research results show that the central finite difference and the Heun methods produce more accurate solutions than the forward finite difference and the Euler methods do.

The Application of Problem Solving Method on Science Teacher Trainees on the Solution of the Environmental Problems

ERIC Educational Resources Information Center

Dogru, Mustafa

2008-01-01

Helping students to improve their problems solving skills is the primary target of science teacher trainees. In modern science, for training the students, methods should be used for improving their thinking skills, making connections with events and concepts and scientific operations skills rather than information and definition giving. One of…

Class and Home Problems: Optimization Problems

ERIC Educational Resources Information Center

Anderson, Brian J.; Hissam, Robin S.; Shaeiwitz, Joseph A.; Turton, Richard

2011-01-01

Optimization problems suitable for all levels of chemical engineering students are available. These problems do not require advanced mathematical techniques, since they can be solved using typical software used by students and practitioners. The method used to solve these problems forces students to understand the trends for the different terms…

[Computer-assisted education in problem-solving in neurology; a randomized educational study].

PubMed

Weverling, G J; Stam, J; ten Cate, T J; van Crevel, H

1996-02-24

To determine the effect of computer-based medical teaching (CBMT) as a supplementary method to teach clinical problem-solving during the clerkship in neurology. Randomized controlled blinded study. Academic Medical Centre, Amsterdam, the Netherlands. 103 Students were assigned at random to a group with access to CBMT and a control group. CBMT consisted of 20 computer-simulated patients with neurological diseases, and was permanently available during five weeks to students in the CBMT group. The ability to recognize and solve neurological problems was assessed with two free-response tests, scored by two blinded observers. The CBMT students scored significantly better on the test related to the CBMT cases (mean score 7.5 on a zero to 10 point scale; control group 6.2; p < 0.001). There was no significant difference on the control test not related to the problems practised with CBMT. CBMT can be an effective method for teaching clinical problem-solving, when used as a supplementary teaching facility during a clinical clerkship. The increased ability to solve problems learned by CBMT had no demonstrable effect on the performance with other neurological problems.

Significance testing of rules in rule-based models of human problem solving

NASA Technical Reports Server (NTRS)

Lewis, C. M.; Hammer, J. M.

1986-01-01

Rule-based models of human problem solving have typically not been tested for statistical significance. Three methods of testing rules - analysis of variance, randomization, and contingency tables - are presented. Advantages and disadvantages of the methods are also described.

Exploring the Use of Electroencephalography to Gather Objective Evidence of Cognitive Processing During Problem Solving

NASA Astrophysics Data System (ADS)

Delahunty, Thomas; Seery, Niall; Lynch, Raymond

2018-04-01

Currently, there is significant interest being directed towards the development of STEM education to meet economic and societal demands. While economic concerns can be a powerful driving force in advancing the STEM agenda, care must be taken that such economic imperative does not promote research approaches that overemphasize pragmatic application at the expense of augmenting the fundamental knowledge base of the discipline. This can be seen in the predominance of studies investigating problem solving approaches and procedures, while neglecting representational and conceptual processes, within the literature. Complementing concerns about STEM graduates' problem solving capabilities, raised within the pertinent literature, this paper discusses a novel methodological approach aimed at investigating the cognitive elements of problem conceptualization. The intention is to demonstrate a novel method of data collection that overcomes some of the limitations cited in classic problem solving research while balancing a search for fundamental understanding with the possibility of application. The methodology described in this study employs an electroencephalographic (EEG) headset, as part of a mixed methods approach, to gather objective evidence of students' cognitive processing during problem solving epochs. The method described provides rich evidence of students' cognitive representations of problems during episodes of applied reasoning. The reliability and validity of the EEG method is supported by the stability of the findings across the triangulated data sources. The paper presents a novel method in the context of research within STEM education and demonstrates an effective procedure for gathering rich evidence of cognitive processing during the early stages of problem conceptualization.

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.

The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm

ERIC Educational Resources Information Center

Ohlsson, Stellan

2012-01-01

The research paradigm invented by Allen Newell and Herbert A. Simon in the late 1950s dominated the study of problem solving for more than three decades. But in the early 1990s, problem solving ceased to drive research on complex cognition. As part of this decline, Newell and Simon's most innovative research practices--especially their method for…

Efficient ICCG on a shared memory multiprocessor

NASA Technical Reports Server (NTRS)

Hammond, Steven W.; Schreiber, Robert

1989-01-01

Different approaches are discussed for exploiting parallelism in the ICCG (Incomplete Cholesky Conjugate Gradient) method for solving large sparse symmetric positive definite systems of equations on a shared memory parallel computer. Techniques for efficiently solving triangular systems and computing sparse matrix-vector products are explored. Three methods for scheduling the tasks in solving triangular systems are implemented on the Sequent Balance 21000. Sample problems that are representative of a large class of problems solved using iterative methods are used. We show that a static analysis to determine data dependences in the triangular solve can greatly improve its parallel efficiency. We also show that ignoring symmetry and storing the whole matrix can reduce solution time substantially.

Students' Use of "Look Back" Strategies in Multiple Solution Methods

ERIC Educational Resources Information Center

Lee, Shin-Yi

2016-01-01

The purpose of this study was to investigate the relationship between both 9th-grade and 1st-year undergraduate students' use of "look back" strategies and problem solving performance in multiple solution methods, the difference in their use of look back strategies and problem solving performance in multiple solution methods, and the…

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 the Container Stowage Problem (CSP) using Particle Swarm Optimization (PSO)

NASA Astrophysics Data System (ADS)

Matsaini; Santosa, Budi

2018-04-01

Container Stowage Problem (CSP) is a problem of containers arrangement into ships by considering rules such as: total weight, weight of one stack, destination, equilibrium, and placement of containers on vessel. Container stowage problem is combinatorial problem and hard to solve with enumeration technique. It is an NP-Hard Problem. Therefore, to find a solution, metaheuristics is preferred. The objective of solving the problem is to minimize the amount of shifting such that the unloading time is minimized. Particle Swarm Optimization (PSO) is proposed to solve the problem. The implementation of PSO is combined with some steps which are stack position change rules, stack changes based on destination, and stack changes based on the weight type of the stacks (light, medium, and heavy). The proposed method was applied on five different cases. The results were compared to Bee Swarm Optimization (BSO) and heuristics method. PSO provided mean of 0.87% gap and time gap of 60 second. While BSO provided mean of 2,98% gap and 459,6 second to the heuristcs.

Characterization and Developmental History of Problem Solving Methods in Medicine

PubMed Central

Harbort, Robert A.

1980-01-01

The central thesis of this paper is the importance of the framework in which information is structured. It is technically important in the design of systems; it is also important in guaranteeing that systems are usable by clinicians. Progress in medical computing depends on our ability to develop a more quantitative understanding of the role of context in our choice of problem solving techniques. This in turn will help us to design more flexible and responsive computer systems. The paper contains an overview of some models of knowledge and problem solving methods, a characterization of modern diagnostic techniques, and a discussion of skill development in medical practice. Diagnostic techniques are examined in terms of how they are taught, what problem solving methods they use, and how they fit together into an overall theory of interpretation of the medical status of a patient.

Analysis of problem solving in terms of cognitive style

NASA Astrophysics Data System (ADS)

Anthycamurty, Rr C. C.; Mardiyana; Saputro, D. R. S.

2018-03-01

The purpose of this study was to analyze the problem solving based on the type of cognitive style. Subjects used in this study are students of class X SMK located in Purworejo. The method used in this research is qualitative descriptive. Data collection techniques used in this research is a problem-solving test to determine student problem solving and GEFT to determine the type of cognitive style possessed by students. The result of this research is to determine the mastery of each type in cognitive style, that is Field Independent type and Field Dependent type on problem solving indicator. The impact of this research is the teacher can know the mastery of student problem solving on each type of cognitive style so that teacher can determine the proper way of delivering to student at next meeting.

The mathematical statement for the solving of the problem of N-version software system design

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Kovalev, D. I.; Zelenkov, P. V.; Voroshilova, A. A.

2015-10-01

The N-version programming, as a methodology of the fault-tolerant software systems design, allows successful solving of the mentioned tasks. The use of N-version programming approach turns out to be effective, since the system is constructed out of several parallel executed versions of some software module. Those versions are written to meet the same specification but by different programmers. The problem of developing an optimal structure of N-version software system presents a kind of very complex optimization problem. This causes the use of deterministic optimization methods inappropriate for solving the stated problem. In this view, exploiting heuristic strategies looks more rational. In the field of pseudo-Boolean optimization theory, the so called method of varied probabilities (MVP) has been developed to solve problems with a large dimensionality.

Iterative Adaptive Dynamic Programming for Solving Unknown Nonlinear Zero-Sum Game Based on Online Data.

PubMed

Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun

2017-03-01

H ∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.

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.

Mathematical programming formulations for satellite synthesis

NASA Technical Reports Server (NTRS)

Bhasin, Puneet; Reilly, Charles H.

1987-01-01

The problem of satellite synthesis can be described as optimally allotting locations and sometimes frequencies and polarizations, to communication satellites so that interference from unwanted satellite signals does not exceed a specified threshold. In this report, mathematical programming models and optimization methods are used to solve satellite synthesis problems. A nonlinear programming formulation which is solved using Zoutendijk's method and a gradient search method is described. Nine mixed integer programming models are considered. Results of computer runs with these nine models and five geographically compatible scenarios are presented and evaluated. A heuristic solution procedure is also used to solve two of the models studied. Heuristic solutions to three large synthesis problems are presented. The results of our analysis show that the heuristic performs very well, both in terms of solution quality and solution time, on the two models to which it was applied. It is concluded that the heuristic procedure is the best of the methods considered for solving satellite synthesis problems.

The application of hybrid artificial intelligence systems for forecasting

NASA Astrophysics Data System (ADS)

Lees, Brian; Corchado, Juan

1999-03-01

The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

Tin Cans Revisited.

ERIC Educational Resources Information Center

Verderber, Nadine L.

1992-01-01

Presents the use of spreadsheets as an alternative method for precalculus students to solve maximum or minimum problems involving surface area and volume. Concludes that students with less technical backgrounds can solve problems normally requiring calculus and suggests sources for additional problems. (MDH)

Implementation Authentic Task to Enhance Problem Solving and Self-Management for Physics College Students

NASA Astrophysics Data System (ADS)

Festiyed; Djamas, D.; Pilendia, D.

2018-04-01

The purpose of this study is to enhance the problem solving and self-management abilities of student teachers through individual and group authentic task. Preliminary results showed that the learning outcomes in high category, nevertheless problem solving and self-management abilities are still low and average categories (scattered at interval 40 ≤ N ≤ 65). Initiative to improve this condition is needed. Action research is the alternative solution for that condition through planning, acting, evaluating, and reflecting. This study is allowed in 4 cycles. The acting step result with integrated discuss method, case study, and presentation including self-assessment for individual and group. This method was effective to enhance problem solving and self-management abilities. The final learning outcomes seen from the correlation between student self-assessment and lecture-assessment (r=0.19). Its means there are unidirectional relationship between the result of self-assessment and lecture-assessment. The Conclusion of the research was effective to enhance problem solving and self-management ability.

Randomized Controlled Trial of Problem-Solving Therapy for Minor Depression in Home Care

ERIC Educational Resources Information Center

Gellis, Zvi D.; McGinty, Jean; Tierney, Lynda; Jordan, Cindy; Burton, Jean; Misener, Elizabeth

2008-01-01

Objective: Data are presented from a pilot research program initiated to develop, refine, and test the outcomes of problem-solving therapy that targets the needs of older adults with minor depression in home care settings. Method: A pilot randomized clinical trial compares the impact of problem-solving therapy for home care to treatment as usual…

Using Educational Data Mining Methods to Assess Field-Dependent and Field-Independent Learners' Complex Problem Solving

ERIC Educational Resources Information Center

Angeli, Charoula; Valanides, Nicos

2013-01-01

The present study investigated the problem-solving performance of 101 university students and their interactions with a computer modeling tool in order to solve a complex problem. Based on their performance on the hidden figures test, students were assigned to three groups of field-dependent (FD), field-mixed (FM), and field-independent (FI)…

Assessment of Students’ Critical-Thinking and Problem-Solving Abilities Across a 6-Year Doctor of Pharmacy Program

PubMed Central

Gaebelein, Claude J.; Grice, Gloria R.; Crannage, Andrew J.; Weck, Margaret A.; Hurd, Peter; Walter, Brenda; Duncan, Wendy

2013-01-01

Objective. To determine the feasibility of using a validated set of assessment rubrics to assess students’ critical-thinking and problem-solving abilities across a doctor of pharmacy (PharmD) curriculum. Methods. Trained faculty assessors used validated rubrics to assess student work samples for critical-thinking and problem-solving abilities. Assessment scores were collected and analyzed to determine student achievement of these 2 ability outcomes across the curriculum. Feasibility of the process was evaluated in terms of time and resources used. Results. One hundred sixty-one samples were assessed for critical thinking, and 159 samples were assessed for problem-solving. Rubric scoring allowed assessors to evaluate four 5- to 7-page work samples per hour. The analysis indicated that overall critical-thinking scores improved over the curriculum. Although low yield for problem-solving samples precluded meaningful data analysis, it was informative for identifying potentially needed curricular improvements. Conclusions. Use of assessment rubrics for program ability outcomes was deemed authentic and feasible. Problem-solving was identified as a curricular area that may need improving. This assessment method has great potential to inform continuous quality improvement of a PharmD program. PMID:24159207

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.

Analysing student written solutions to investigate if problem-solving processes are evident throughout

NASA Astrophysics Data System (ADS)

Kelly, Regina; McLoughlin, Eilish; Finlayson, Odilla E.

2016-07-01

An interdisciplinary science course has been implemented at a university with the intention of providing students the opportunity to develop a range of key skills in relation to: real-world connections of science, problem-solving, information and communications technology use and team while linking subject knowledge in each of the science disciplines. One of the problems used in this interdisciplinary course has been selected to evaluate if it affords students the opportunity to explicitly display problem-solving processes. While the benefits of implementing problem-based learning have been well reported, far less research has been devoted to methods of assessing student problem-solving solutions. A problem-solving theoretical framework was used as a tool to assess student written solutions to indicate if problem-solving processes were present. In two academic years, student problem-solving processes were satisfactory for exploring and understanding, representing and formulating, and planning and executing, indicating that student collaboration on problems is a good initiator of developing these processes. In both academic years, students displayed poor monitoring and reflecting (MR) processes at the intermediate level. A key impact of evaluating student work in this way is that it facilitated meaningful feedback about the students' problem-solving process rather than solely assessing the correctness of problem solutions.

Artificial intelligence in robot control systems

NASA Astrophysics Data System (ADS)

Korikov, A.

2018-05-01

This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

Prediction of Sound Waves Propagating Through a Nozzle Without/With a Shock Wave Using the Space-Time CE/SE Method

NASA Technical Reports Server (NTRS)

Wang, Xiao-Yen; Chang, Sin-Chung; Jorgenson, Philip C. E.

2000-01-01

The benchmark problems in Category 1 (Internal Propagation) of the third Computational Aeroacoustics (CAA) Work-shop sponsored by NASA Glenn Research Center are solved using the space-time conservation element and solution element (CE/SE) method. The first problem addresses the propagation of sound waves through a nearly choked transonic nozzle. The second one concerns shock-sound interaction in a supersonic nozzle. A quasi one-dimension CE/SE Euler solver for a nonuniform mesh is developed and employed to solve both problems. Numerical solutions are compared with the analytical solution for both problems. It is demonstrated that the CE/SE method is capable of solving aeroacoustic problems with/without shock waves in a simple way. Furthermore, the simple nonreflecting boundary condition used in the CE/SE method which is not based on the characteristic theory works very well.

Problem-Based Learning: Student Engagement, Learning and Contextualized Problem-Solving. Occasional Paper

ERIC Educational Resources Information Center

Mossuto, Mark

2009-01-01

The adoption of problem-based learning as a teaching method in the advertising and public relations programs offered by the Business TAFE (Technical and Further Education) School at RMIT University is explored in this paper. The effect of problem-based learning on student engagement, student learning and contextualised problem-solving was…

Effects of performance feedback and coaching on the problem-solving process: Improving the integrity of implementation and enhancing student outcomes

NASA Astrophysics Data System (ADS)

Lundahl, Allison A.

Schools implementing Response to Intervention (RtI) procedures frequently engage in team problem-solving processes to address the needs of students who require intensive and individualized services. Because the effectiveness of the problem-solving process will impact the overall success of RtI systems, the present study was designed to learn more about how to strengthen the integrity of the problem-solving process. Research suggests that school districts must ensure high quality training and ongoing support to enhance the effectiveness, acceptability, and sustainability of the problem-solving process within an RtI model; however, there is a dearth of research examining the effectiveness of methods to provide this training and support. Consequently, this study investigated the effects of performance feedback and coaching strategies on the integrity with which teams of educators conducted the problem-solving process in schools. In addition, the relationships between problem-solving integrity, teacher acceptability, and student outcomes were examined. Results suggested that the performance feedback increased problem-solving procedural integrity across two of the three participating schools. Conclusions about the effectiveness of the (a) coaching intervention and (b) interventions implemented in the third school were inconclusive. Regression analyses indicated that the integrity with which the teams conducted the problem-solving process was a significant predictor of student outcomes. However, the relationship between problem-solving procedural integrity and teacher acceptability was not statistically significant.

Solving phase appearance/disappearance two-phase flow problems with high resolution staggered grid and fully implicit schemes by the Jacobian-free Newton–Krylov Method

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

Zou, Ling; Zhao, Haihua; Zhang, Hongbin

2016-04-01

The phase appearance/disappearance issue presents serious numerical challenges in two-phase flow simulations. Many existing reactor safety analysis codes use different kinds of treatments for the phase appearance/disappearance problem. However, to our best knowledge, there are no fully satisfactory solutions. Additionally, the majority of the existing reactor system analysis codes were developed using low-order numerical schemes in both space and time. In many situations, it is desirable to use high-resolution spatial discretization and fully implicit time integration schemes to reduce numerical errors. In this work, we adapted a high-resolution spatial discretization scheme on staggered grid mesh and fully implicit time integrationmore » methods (such as BDF1 and BDF2) to solve the two-phase flow problems. The discretized nonlinear system was solved by the Jacobian-free Newton Krylov (JFNK) method, which does not require the derivation and implementation of analytical Jacobian matrix. These methods were tested with a few two-phase flow problems with phase appearance/disappearance phenomena considered, such as a linear advection problem, an oscillating manometer problem, and a sedimentation problem. The JFNK method demonstrated extremely robust and stable behaviors in solving the two-phase flow problems with phase appearance/disappearance. No special treatments such as water level tracking or void fraction limiting were used. High-resolution spatial discretization and second- order fully implicit method also demonstrated their capabilities in significantly reducing numerical errors.« less

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.

Implementation of basic chemistry experiment based on metacognition to increase problem-solving and build concept understanding

NASA Astrophysics Data System (ADS)

Zuhaida, A.

2018-04-01

Implementation of the experiment have the three aspects of the goal: 1) develop basic skills of experimenting; 2) develop problem-solving skills with a scientific approach; 3) improve understanding of the subject matter. On the implementation of the experiment, students have some weaknesses include: observing, identifying problems, managing information, analyzing, and evaluating. This weakness is included in the metacognition indicator.The objective of the research is to implementation of Basic Chemistry Experiment based on metacognition to increase problem-solving skills and build concept understanding for students of Science Education Department. The method of this research is a quasi- experimental method with pretest-posttest control group design. Problem-solving skills are measured through performance assessments using rubrics from problem solving reports, and results presentation. The conceptual mastery is measured through a description test. The result of the research: (1) improve the problem solving skills of the students with very high category; (2) increase the students’ concept understanding better than the conventional experiment with the result of N-gain in medium category, and (3) increase student's response positively for learning implementation. The contribution of this research is to extend the implementation of practical learning for some subjects, and to improve the students' competence in science.

The Relationship of Social Problem-Solving Skills and Dysfunctional Attitudes with Risk of Drug Abuse among Dormitory Students at Isfahan University of Medical Sciences

PubMed Central

Nasrazadani, Ehteram; Maghsoudi, Jahangir; Mahrabi, Tayebeh

2017-01-01

Background: Dormitory students encounter multiple social factors which cause pressure, such as new social relationships, fear of the future, and separation from family, which could cause serious problems such as tendency toward drug abuse. This research was conducted with the goal to determine social problem-solving skills, dysfunctional attitudes, and risk of drug abuse among dormitory students of Isfahan University of Medical Sciences, Iran. Materials and Methods: This was a descriptive-analytical, correlational, and cross-sectional research. The research sample consisted of 211 students living in dormitories. The participants were selected using randomized quota sampling method. The data collection tools included the Social Problem-Solving Inventory (SPSI), Dysfunctional Attitude Scale (DAS), and Identifying People at Risk of Addiction Questionnaire. Results: The results indicated an inverse relationship between social problem-solving skills and risk of drug abuse (P = 0.0002), a direct relationship between dysfunctional attitude and risk of drug abuse (P = 0.030), and an inverse relationship between social problem-solving skills and dysfunctional attitude among students (P = 0.0004). Conclusions: Social problem-solving skills have a correlation with dysfunctional attitudes. As a result, teaching these skills and the way to create efficient attitudes should be considered in dormitory students. PMID:28904539

Collaborative Problem Solving Methods towards Critical Thinking

ERIC Educational Resources Information Center

Yin, Khoo Yin; Abdullah, Abdul Ghani Kanesan; Alazidiyeen, Naser Jamil

2011-01-01

This research attempts to examine the collaborative problem solving methods towards critical thinking based on economy (AE) and non economy (TE) in the SPM level among students in the lower sixth form. The quasi experiment method that uses the modal of 3X2 factorial is applied. 294 lower sixth form students from ten schools are distributed…

Problem Solving by Design

ERIC Educational Resources Information Center

Capobianco, Brenda M.; Tyrie, Nancy

2009-01-01

In a unique school-university partnership, methods students collaborated with fifth graders to use the engineering design process to build their problem-solving skills. By placing the problem in the context of a client having particular needs, the problem took on a real-world appeal that students found intriguing and inviting. In this article, the…

The Creativity of Reflective and Impulsive Selected Students in Solving Geometric Problems

NASA Astrophysics Data System (ADS)

Shoimah, R. N.; Lukito, A.; Siswono, T. Y. E.

2018-01-01

This research purposed to describe the elementary students’ creativity with reflective and impulsive cognitive style in solving geometric problems. This research used qualitative research methods. The data was collected by written tests and task-based interviews. The subjects consisted of two 5th grade students that were measured by MFFT (Matching Familiar Figures Test). The data were analyzed based on the three main components of creativity; that is fluency, flexibility, and novelty. This results showed that subject with reflective cognitive style in solving geometric problems met all components of creativity (fluency; subject generated more than three different right-ideas in solving problems, flexibility; subject generated more than two different ways to get problem solved, and novelty; subject generated new ideas and new ways that original and has never been used before). While subject with impulsive cognitive style in solving geometric problems met two components of creativity (fluency; subject generated more than three different right-ideas in solving problems, flexibility; subject generated two different ways to get problem solved). Thus, it could be concluded that reflective students are more creative in solving geometric problems. The results of this research can also be used as a guideline in the future assessment of creativity based on cognitive style.

Use of various versions of Schwarz method for solving the problem of contact interaction of elastic bodies

NASA Astrophysics Data System (ADS)

Galanin, M. P.; Lukin, V. V.; Rodin, A. S.

2018-04-01

A definition of a sufficiently common problem of mechanical contact interaction in a system of elastic bodies is given. Various versions of realization of the Schwarz method for solving the contact problem numerically are described and the results of solution of a number of problems are presented. Special attention is paid to calculations where the grids in the bodies significantly differ in steps.

Problem Solving with General Semantics.

ERIC Educational Resources Information Center

Hewson, David

1996-01-01

Discusses how to use general semantics formulations to improve problem solving at home or at work--methods come from the areas of artificial intelligence/computer science, engineering, operations research, and psychology. (PA)

A class of finite-time dual neural networks for solving quadratic programming problems and its k-winners-take-all application.

PubMed

Li, Shuai; Li, Yangming; Wang, Zheng

2013-03-01

This paper presents a class of recurrent neural networks to solve quadratic programming problems. Different from most existing recurrent neural networks for solving quadratic programming problems, the proposed neural network model converges in finite time and the activation function is not required to be a hard-limiting function for finite convergence time. The stability, finite-time convergence property and the optimality of the proposed neural network for solving the original quadratic programming problem are proven in theory. Extensive simulations are performed to evaluate the performance of the neural network with different parameters. In addition, the proposed neural network is applied to solving the k-winner-take-all (k-WTA) problem. Both theoretical analysis and numerical simulations validate the effectiveness of our method for solving the k-WTA problem. Copyright © 2012 Elsevier Ltd. All rights reserved.

Effect of case-based learning on the development of graduate nurses' problem-solving ability.

PubMed

Yoo, Moon-Sook; Park, Jin-Hee

2014-01-01

Case-based learning (CBL) is a teaching strategy which promotes clinical problem-solving ability. This research was performed to investigate the effects of CBL on problem-solving ability of graduate nurses. This research was a quasi-experimental design using pre-test, intervention, and post-test with a non-synchronized, non-equivalent control group. The study population was composed of 190 new graduate nurses from university hospital A in Korea. Results of the research indicate that there was a statistically significant difference in objective problem-solving ability scores of CBL group demonstrating higher scores. Subjective problem-solving ability was also significantly higher in CBL group than in the lecture-based group. These results may suggest that CBL is a beneficial and effective instructional method of training graduate nurses to improve their clinical problem-solving ability. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effectiveness of discovery learning model on mathematical problem solving

NASA Astrophysics Data System (ADS)

Herdiana, Yunita; Wahyudin, Sispiyati, Ririn

2017-08-01

This research is aimed to describe the effectiveness of discovery learning model on mathematical problem solving. This research investigate the students' problem solving competency before and after learned by using discovery learning model. The population used in this research was student in grade VII in one of junior high school in West Bandung Regency. From nine classes, class VII B were randomly selected as the sample of experiment class, and class VII C as control class, which consist of 35 students every class. The method in this research was quasi experiment. The instrument in this research is pre-test, worksheet and post-test about problem solving of mathematics. Based on the research, it can be conclude that the qualification of problem solving competency of students who gets discovery learning model on level 80%, including in medium category and it show that discovery learning model effective to improve mathematical problem solving.

The Influence of Self-Efficacy Beliefs and Metacognitive Prompting on Genetics Problem Solving Ability among High School Students in Kenya

NASA Astrophysics Data System (ADS)

Aurah, Catherine Muhonja

Within the framework of social cognitive theory, the influence of self-efficacy beliefs and metacognitive prompting on genetics problem solving ability among high school students in Kenya was examined through a mixed methods research design. A quasi-experimental study, supplemented by focus group interviews, was conducted to investigate both the outcomes and the processes of students' genetics problem-solving ability. Focus group interviews substantiated and supported findings from the quantitative instruments. The study was conducted in 17 high schools in Western Province, Kenya. A total of 2,138 high school students were purposively sampled. A sub-sample of 48 students participated in focus group interviews to understand their perspectives and experiences during the study so as to corroborate the quantitative data. Quantitative data were analyzed through descriptive statistics, zero-order correlations, 2 x 2 factorial ANOVA,, and sequential hierarchical multiple regressions. Qualitative data were transcribed, coded, and reported thematically. Results revealed metacognitive prompts had significant positive effects on student problem-solving ability independent of gender. Self-efficacy and metacognitive prompting significantly predicted genetics problem-solving ability. Gender differences were revealed, with girls outperforming boys on the genetics problem-solving test. Furthermore, self-efficacy moderated the relationship between metacognitive prompting and genetics problem-solving ability. This study established a foundation for instructional methods for biology teachers and recommendations are made for implementing metacognitive prompting in a problem-based learning environment in high schools and science teacher education programs in Kenya.

Gauging the gaps in student problem-solving skills: assessment of individual and group use of problem-solving strategies using online discussions.

PubMed

Anderson, William L; Mitchell, Steven M; Osgood, Marcy P

2008-01-01

For the past 3 yr, faculty at the University of New Mexico, Department of Biochemistry and Molecular Biology have been using interactive online Problem-Based Learning (PBL) case discussions in our large-enrollment classes. We have developed an illustrative tracking method to monitor student use of problem-solving strategies to provide targeted help to groups and to individual students. This method of assessing performance has a high interrater reliability, and senior students, with training, can serve as reliable graders. We have been able to measure improvements in many students' problem-solving strategies, but, not unexpectedly, there is a population of students who consistently apply the same failing strategy when there is no faculty intervention. This new methodology provides an effective tool to direct faculty to constructively intercede in this area of student development.

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

Problem Solving Techniques for the Design of Algorithms.

ERIC Educational Resources Information Center

Kant, Elaine; Newell, Allen

1984-01-01

Presents model of algorithm design (activity in software development) based on analysis of protocols of two subjects designing three convex hull algorithms. Automation methods, methods for studying algorithm design, role of discovery in problem solving, and comparison of different designs of case study according to model are highlighted.…

Should Children Learn to Solve Problems?

ERIC Educational Resources Information Center

Watras, Joseph

2011-01-01

In this comparative essay, the author discusses the opposing educational theories of John Dewey and Gregory Bateson. While Dewey believed that the scientific method was the dominant method of solving problems and thereby acquiring knowledge that mattered, Bateson warned that this one-sided approach would lead to actions that could destroy the…

Using Depth Intuition in Creative Problem Solving and Strategic Innovation.

ERIC Educational Resources Information Center

Markley, O. W.

1988-01-01

The article describes four step-by-step methods to sharpen intuitive capacities for problem-solving and innovation. Visionary and transpersonal knowledge processes are tapped to gain access to relatively deep levels of intuition. The methods are considered useful for overcoming internal blockages or resistance, developing organizational mission…

How to Teach Procedures, Problem Solving, and Concepts in Microbial Genetics

ERIC Educational Resources Information Center

Bainbridge, Brian W.

1977-01-01

Flow-diagrams, algorithms, decision logic tables, and concept maps are presented in detail as methods for teaching practical procedures, problem solving, and basic concepts in microbial genetics. It is suggested that the flexible use of these methods should lead to an improved understanding of microbial genetics. (Author/MA)

A subgradient approach for constrained binary optimization via quantum adiabatic evolution

NASA Astrophysics Data System (ADS)

Karimi, Sahar; Ronagh, Pooya

2017-08-01

Outer approximation method has been proposed for solving the Lagrangian dual of a constrained binary quadratic programming problem via quantum adiabatic evolution in the literature. This should be an efficient prescription for solving the Lagrangian dual problem in the presence of an ideally noise-free quantum adiabatic system. However, current implementations of quantum annealing systems demand methods that are efficient at handling possible sources of noise. In this paper, we consider a subgradient method for finding an optimal primal-dual pair for the Lagrangian dual of a constrained binary polynomial programming problem. We then study the quadratic stable set (QSS) problem as a case study. We see that this method applied to the QSS problem can be viewed as an instance-dependent penalty-term approach that avoids large penalty coefficients. Finally, we report our experimental results of using the D-Wave 2X quantum annealer and conclude that our approach helps this quantum processor to succeed more often in solving these problems compared to the usual penalty-term approaches.

Assertiveness and problem solving in midwives.

PubMed

Yurtsal, Zeliha Burcu; Özdemir, Levent

2015-01-01

Midwifery profession is required to bring solutions to problems and a midwife is expected to be an assertive person and to develop midwifery care. This study was planned to examine the relationship between assertiveness and problem-solving skills of midwives. This cross-sectional study was conducted with 201 midwives between July 2008 and February 2009 in the city center of Sivas. The Rathus Assertiveness Schedule (RAS) and Problem Solving Inventory (PSI) were used to determine the level of assertiveness and problem-solving skills of midwives. Statistical methods were used as mean, standard deviation, percentage, Student's T, ANOVA and Tukey HSD, Kruskal Wallis, Fisher Exact, Pearson Correlation and Chi-square tests and P < 0.05. The RAS mean scores and the PSI mean scores showed statistically significant differences in terms of a midwife's considering herself as a member of the health team, expressing herself within the health care team, being able to say "no" when necessary, cooperating with her colleagues, taking part in problem-solving skills training. A statistically significant negative correlation was found between the RAS and PSI scores. The RAS scores decreased while the problem-solving scores increased (r: -0451, P < 0.01). There were significant statistical differences between assertiveness levels and problem solving skills of midwives, and midwives who were assertive solved their problems better than did others. Assertiveness and problem-solving skills training will contribute to the success of the midwifery profession. Midwives able to solve problems, and display assertive behaviors will contribute to the development of midwifery profession.

Problem Solving as Probabilistic Inference with Subgoaling: Explaining Human Successes and Pitfalls in the Tower of Hanoi

PubMed Central

Donnarumma, Francesco; Maisto, Domenico; Pezzulo, Giovanni

2016-01-01

How do humans and other animals face novel problems for which predefined solutions are not available? Human problem solving links to flexible reasoning and inference rather than to slow trial-and-error learning. It has received considerable attention since the early days of cognitive science, giving rise to well known cognitive architectures such as SOAR and ACT-R, but its computational and brain mechanisms remain incompletely known. Furthermore, it is still unclear whether problem solving is a “specialized” domain or module of cognition, in the sense that it requires computations that are fundamentally different from those supporting perception and action systems. Here we advance a novel view of human problem solving as probabilistic inference with subgoaling. In this perspective, key insights from cognitive architectures are retained such as the importance of using subgoals to split problems into subproblems. However, here the underlying computations use probabilistic inference methods analogous to those that are increasingly popular in the study of perception and action systems. To test our model we focus on the widely used Tower of Hanoi (ToH) task, and show that our proposed method can reproduce characteristic idiosyncrasies of human problem solvers: their sensitivity to the “community structure” of the ToH and their difficulties in executing so-called “counterintuitive” movements. Our analysis reveals that subgoals have two key roles in probabilistic inference and problem solving. First, prior beliefs on (likely) useful subgoals carve the problem space and define an implicit metric for the problem at hand—a metric to which humans are sensitive. Second, subgoals are used as waypoints in the probabilistic problem solving inference and permit to find effective solutions that, when unavailable, lead to problem solving deficits. Our study thus suggests that a probabilistic inference scheme enhanced with subgoals provides a comprehensive framework to study problem solving and its deficits. PMID:27074140

Problem Solving as Probabilistic Inference with Subgoaling: Explaining Human Successes and Pitfalls in the Tower of Hanoi.

PubMed

Donnarumma, Francesco; Maisto, Domenico; Pezzulo, Giovanni

2016-04-01

How do humans and other animals face novel problems for which predefined solutions are not available? Human problem solving links to flexible reasoning and inference rather than to slow trial-and-error learning. It has received considerable attention since the early days of cognitive science, giving rise to well known cognitive architectures such as SOAR and ACT-R, but its computational and brain mechanisms remain incompletely known. Furthermore, it is still unclear whether problem solving is a "specialized" domain or module of cognition, in the sense that it requires computations that are fundamentally different from those supporting perception and action systems. Here we advance a novel view of human problem solving as probabilistic inference with subgoaling. In this perspective, key insights from cognitive architectures are retained such as the importance of using subgoals to split problems into subproblems. However, here the underlying computations use probabilistic inference methods analogous to those that are increasingly popular in the study of perception and action systems. To test our model we focus on the widely used Tower of Hanoi (ToH) task, and show that our proposed method can reproduce characteristic idiosyncrasies of human problem solvers: their sensitivity to the "community structure" of the ToH and their difficulties in executing so-called "counterintuitive" movements. Our analysis reveals that subgoals have two key roles in probabilistic inference and problem solving. First, prior beliefs on (likely) useful subgoals carve the problem space and define an implicit metric for the problem at hand-a metric to which humans are sensitive. Second, subgoals are used as waypoints in the probabilistic problem solving inference and permit to find effective solutions that, when unavailable, lead to problem solving deficits. Our study thus suggests that a probabilistic inference scheme enhanced with subgoals provides a comprehensive framework to study problem solving and its deficits.

Enhancing chemistry problem-solving achievement using problem categorization

NASA Astrophysics Data System (ADS)

Bunce, Diane M.; Gabel, Dorothy L.; Samuel, John V.

The enhancement of chemistry students' skill in problem solving through problem categorization is the focus of this study. Twenty-four students in a freshman chemistry course for health professionals are taught how to solve problems using the explicit method of problem solving (EMPS) (Bunce & Heikkinen, 1986). The EMPS is an organized approach to problem analysis which includes encoding the information given in a problem (Given, Asked For), relating this to what is already in long-term memory (Recall), and planning a solution (Overall Plan) before a mathematical solution is attempted. In addition to the EMPS training, treatment students receive three 40-minute sessions following achievement tests in which they are taught how to categorize problems. Control students use this time to review the EMPS solutions of test questions. Although problem categorization is involved in one section of the EMPS (Recall), treatment students who received specific training in problem categorization demonstrate significantly higher achievement on combination problems (those problems requiring the use of more than one chemical topic for their solution) at (p = 0.01) than their counterparts. Significantly higher achievement for treatment students is also measured on an unannounced test (p = 0.02). Analysis of interview transcripts of both treatment and control students illustrates a Rolodex approach to problem solving employed by all students in this study. The Rolodex approach involves organizing equations used to solve problems on mental index cards and flipping through them, matching units given when a new problem is to be solved. A second phenomenon observed during student interviews is the absence of a link in the conceptual understanding of the chemical concepts involved in a problem and the problem-solving skills employed to correctly solve problems. This study shows that explicit training in categorization skills and the EMPS can lead to higher achievement in complex problem-solving situations (combination problems and unannounced test). However, such achievement may be limited by the lack of linkages between students' conceptual understanding and improved problem-solving skill.

Application of shifted Jacobi pseudospectral method for solving (in)finite-horizon min-max optimal control problems with uncertainty

NASA Astrophysics Data System (ADS)

Nikooeinejad, Z.; Delavarkhalafi, A.; Heydari, M.

2018-03-01

The difficulty of solving the min-max optimal control problems (M-MOCPs) with uncertainty using generalised Euler-Lagrange equations is caused by the combination of split boundary conditions, nonlinear differential equations and the manner in which the final time is treated. In this investigation, the shifted Jacobi pseudospectral method (SJPM) as a numerical technique for solving two-point boundary value problems (TPBVPs) in M-MOCPs for several boundary states is proposed. At first, a novel framework of approximate solutions which satisfied the split boundary conditions automatically for various boundary states is presented. Then, by applying the generalised Euler-Lagrange equations and expanding the required approximate solutions as elements of shifted Jacobi polynomials, finding a solution of TPBVPs in nonlinear M-MOCPs with uncertainty is reduced to the solution of a system of algebraic equations. Moreover, the Jacobi polynomials are particularly useful for boundary value problems in unbounded domain, which allow us to solve infinite- as well as finite and free final time problems by domain truncation method. Some numerical examples are given to demonstrate the accuracy and efficiency of the proposed method. A comparative study between the proposed method and other existing methods shows that the SJPM is simple and accurate.

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.

A feasible DY conjugate gradient method for linear equality constraints

NASA Astrophysics Data System (ADS)

LI, Can

2017-09-01

In this paper, we propose a feasible conjugate gradient method for solving linear equality constrained optimization problem. The method is an extension of the Dai-Yuan conjugate gradient method proposed by Dai and Yuan to linear equality constrained optimization problem. It can be applied to solve large linear equality constrained problem due to lower storage requirement. An attractive property of the method is that the generated direction is always feasible and descent direction. Under mild conditions, the global convergence of the proposed method with exact line search is established. Numerical experiments are also given which show the efficiency of the method.

Factors affecting the social problem-solving ability of baccalaureate nursing students.

PubMed

Lau, Ying

2014-01-01

The hospital environment is characterized by time pressure, uncertain information, conflicting goals, high stakes, stress, and dynamic conditions. These demands mean there is a need for nurses with social problem-solving skills. This study set out to (1) investigate the social problem-solving ability of Chinese baccalaureate nursing students in Macao and (2) identify the association between communication skill, clinical interaction, interpersonal dysfunction, and social problem-solving ability. All nursing students were recruited in one public institute through the census method. The research design was exploratory, cross-sectional, and quantitative. The study used the Chinese version of the Social Problem Solving Inventory short form (C-SPSI-R), Communication Ability Scale (CAS), Clinical Interactive Scale (CIS), and Interpersonal Dysfunction Checklist (IDC). Macao nursing students were more likely to use the two constructive or adaptive dimensions rather than the three dysfunctional dimensions of the C-SPSI-R to solve their problems. Multiple linear regression analysis revealed that communication ability (ß=.305, p<.0001), clinical interaction (ß=.129, p=.047), and interpersonal dysfunction (ß=-.402, p<.0001) were associated with social problem-solving after controlling for covariates. Macao has had no problem-solving training in its educational curriculum; an effective problem-solving training should be implemented as part of the curriculum. With so many changes in healthcare today, nurses must be good social problem-solvers in order to deliver holistic care. Copyright © 2012 Elsevier Ltd. All rights reserved.

The pseudo-Boolean optimization approach to form the N-version software structure

NASA Astrophysics Data System (ADS)

Kovalev, I. V.; Kovalev, D. I.; Zelenkov, P. V.; Voroshilova, A. A.

2015-10-01

The problem of developing an optimal structure of N-version software system presents a kind of very complex optimization problem. This causes the use of deterministic optimization methods inappropriate for solving the stated problem. In this view, exploiting heuristic strategies looks more rational. In the field of pseudo-Boolean optimization theory, the so called method of varied probabilities (MVP) has been developed to solve problems with a large dimensionality. Some additional modifications of MVP have been made to solve the problem of N-version systems design. Those algorithms take into account the discovered specific features of the objective function. The practical experiments have shown the advantage of using these algorithm modifications because of reducing a search space.

A numerical method for solving a nonlinear 2-D optimal control problem with the classical diffusion equation

NASA Astrophysics Data System (ADS)

Mamehrashi, K.; Yousefi, S. A.

2017-02-01

This paper presents a numerical solution for solving a nonlinear 2-D optimal control problem (2DOP). The performance index of a nonlinear 2DOP is described with a state and a control function. Furthermore, dynamic constraint of the system is given by a classical diffusion equation. It is preferred to use the Ritz method for finding the numerical solution of the problem. The method is based upon the Legendre polynomial basis. By using this method, the given optimisation nonlinear 2DOP reduces to the problem of solving a system of algebraic equations. The benefit of the method is that it provides greater flexibility in which the given initial and boundary conditions of the problem are imposed. Moreover, compared with the eigenfunction method, the satisfactory results are obtained only in a small number of polynomials order. This numerical approach is applicable and effective for such a kind of nonlinear 2DOP. The convergence of the method is extensively discussed and finally two illustrative examples are included to observe the validity and applicability of the new technique developed in the current work.

A method to stabilize linear systems using eigenvalue gradient information

NASA Technical Reports Server (NTRS)

Wieseman, C. D.

1985-01-01

Formal optimization methods and eigenvalue gradient information are used to develop a stabilizing control law for a closed loop linear system that is initially unstable. The method was originally formulated by using direct, constrained optimization methods with the constraints being the real parts of the eigenvalues. However, because of problems in trying to achieve stabilizing control laws, the problem was reformulated to be solved differently. The method described uses the Davidon-Fletcher-Powell minimization technique to solve an indirect, constrained minimization problem in which the performance index is the Kreisselmeier-Steinhauser function of the real parts of all the eigenvalues. The method is applied successfully to solve two different problems: the determination of a fourth-order control law stabilizes a single-input single-output active flutter suppression system and the determination of a second-order control law for a multi-input multi-output lateral-directional flight control system. Various sets of design variables and initial starting points were chosen to show the robustness of the method.

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.

Using Science Inquiry Methods to Promote Self-Determination and Problem-Solving Skills for Students with Moderate Intellectual Disability

ERIC Educational Resources Information Center

Miller, Bridget T.

2013-01-01

The purpose of this study was to investigate the use of guided science inquiry methods with self-monitoring checklists to support problem-solving for students with moderate cognitive disabilities in both science and functional daily activities. The present study contributes to the literature examining guided inquiry methods as a means for student…

From Addition to Multiplication ... and Back: The Development of Students' Additive and Multiplicative Reasoning Skills

ERIC Educational Resources Information Center

Van Dooren, Wim; De Bock, Dirk; Verschaffel, Lieven

2010-01-01

This study builds on two lines of research that have so far developed largely separately: the use of additive methods to solve proportional word problems and the use of proportional methods to solve additive word problems. We investigated the development with age of both kinds of erroneous solution methods. We gave a test containing missing-value…

An accurate, fast, and scalable solver for high-frequency wave propagation

NASA Astrophysics Data System (ADS)

Zepeda-Núñez, L.; Taus, M.; Hewett, R.; Demanet, L.

2017-12-01

In many science and engineering applications, solving time-harmonic high-frequency wave propagation problems quickly and accurately is of paramount importance. For example, in geophysics, particularly in oil exploration, such problems can be the forward problem in an iterative process for solving the inverse problem of subsurface inversion. It is important to solve these wave propagation problems accurately in order to efficiently obtain meaningful solutions of the inverse problems: low order forward modeling can hinder convergence. Additionally, due to the volume of data and the iterative nature of most optimization algorithms, the forward problem must be solved many times. Therefore, a fast solver is necessary to make solving the inverse problem feasible. For time-harmonic high-frequency wave propagation, obtaining both speed and accuracy is historically challenging. Recently, there have been many advances in the development of fast solvers for such problems, including methods which have linear complexity with respect to the number of degrees of freedom. While most methods scale optimally only in the context of low-order discretizations and smooth wave speed distributions, the method of polarized traces has been shown to retain optimal scaling for high-order discretizations, such as hybridizable discontinuous Galerkin methods and for highly heterogeneous (and even discontinuous) wave speeds. The resulting fast and accurate solver is consequently highly attractive for geophysical applications. To date, this method relies on a layered domain decomposition together with a preconditioner applied in a sweeping fashion, which has limited straight-forward parallelization. In this work, we introduce a new version of the method of polarized traces which reveals more parallel structure than previous versions while preserving all of its other advantages. We achieve this by further decomposing each layer and applying the preconditioner to these new components separately and in parallel. We demonstrate that this produces an even more effective and parallelizable preconditioner for a single right-hand side. As before, additional speed can be gained by pipelining several right-hand-sides.

Skill Acquisition: Compilation of Weak-Method Problem Solutions.

ERIC Educational Resources Information Center

Anderson, John R.

According to the ACT theory of skill acquisition, cognitive skills are encoded by a set of productions, which are organized according to a hierarchical goal structure. People solve problems in new domains by applying weak problem-solving procedures to declarative knowledge they have about this domain. From these initial problem solutions,…

Clinical Problem Analysis (CPA): A Systematic Approach To Teaching Complex Medical Problem Solving.

ERIC Educational Resources Information Center

Custers, Eugene J. F. M.; Robbe, Peter F. De Vries; Stuyt, Paul M. J.

2000-01-01

Discusses clinical problem analysis (CPA) in medical education, an approach to solving complex clinical problems. Outlines the five step CPA model and examines the value of CPA's content-independent (methodical) approach. Argues that teaching students to use CPA will enable them to avoid common diagnostic reasoning errors and pitfalls. Compares…

Problem—solving counseling as a therapeutic tool on youth suicidal behavior in the suburban population in Sri Lanka

PubMed Central

Perera, E. A. Ramani; Kathriarachchi, Samudra T.

2011-01-01

Background: Suicidal behaviour among youth is a major public health concern in Sri Lanka. Prevention of youth suicides using effective, feasible and culturally acceptable methods is invaluable in this regard, however research in this area is grossly lacking. Objective: This study aimed at determining the effectiveness of problem solving counselling as a therapeutic intervention in prevention of youth suicidal behaviour in Sri Lanka. Setting and design: This control trial study was based on hospital admissions with suicidal attempts in a sub-urban hospital in Sri Lanka. The study was carried out at Base Hospital Homagama. Materials and Methods: A sample of 124 was recruited using convenience sampling method and divided into two groups, experimental and control. Control group was offered routine care and experimental group received four sessions of problem solving counselling over one month. Outcome of both groups was measured, six months after the initial screening, using the visual analogue scale. Results: Individualized outcome measures on problem solving counselling showed that problem solving ability among the subjects in the experimental group had improved after four counselling sessions and suicidal behaviour has been reduced. The results are statistically significant. Conclusion: This Study confirms that problem solving counselling is an effective therapeutic tool in management of youth suicidal behaviour in hospital setting in a developing country. PMID:21431005

Problem-Solving Skills Appraisal Mediates Hardiness and Suicidal Ideation among Malaysian Undergraduate Students

PubMed Central

Abdollahi, Abbas; Talib, Mansor Abu; Yaacob, Siti Nor; Ismail, Zanariah

2015-01-01

Objectives Recent evidence suggests that suicidal ideation is increased among university students, it is essential to increase our knowledge concerning the etiology of suicidal ideation among university students. This study was conducted to examine the relationships between problem-solving skills appraisal, hardiness, and suicidal ideation among university students. In addition, this study was conducted to examine problem-solving skills appraisal (including the three components of problem-solving confidence, approach-avoidance style, and personal control of emotion) as a potential mediator between hardiness and suicidal ideation. Methods The participants consisted of 500 undergraduate students from Malaysian public universities. Results Structural Equation Modelling (SEM) estimated that undergraduate students with lower hardiness, poor problem-solving confidence, external personal control of emotion, and avoiding style was associated with higher suicidal ideation. Problem-solving skills appraisal (including the three components of problem-solving confidence, approach-avoidance style, and personal control of emotion) partially mediated the relationship between hardiness and suicidal ideation. Conclusion These findings underline the importance of studying mediating processes that explain how hardiness affects suicidal ideation. PMID:25830229

An evaluation of the problem-solving ability of diplomates from a comprehensive nursing programme.

PubMed

Makhathini, J T; Uys, L R

1996-10-01

The aim of this South African study was to obtain a measurement of the problem-solving ability of diplomates from a basic nursing programme with this skill included in its programme objectives. The problem-solving skills of diplomates from this programme were compared with those of first years to determine if there is an improvement in the problem-solving skills. A comparison was also made with a different basic programmes not claiming to teach problem-solving. The research design selected for this study was the ex post facto design. Data were collected using the Triple Jump Method which is an interview technique. The findings suggested that the level of the problem-solving skills of the comprehensive nursing programme diplomate is not satisfactory. There was, however, some improvement in the problem-solving ability from the first to the fourth year. The level of performance of the fourth years was slightly higher than that of the third years of the three-year nursing programme, who were used as the control group. Recommendations on selection teaching and evaluation of students, as well as further research, were made.

The Effects of Problem Solving Applications on the Development of Science Process Skills, Logical Thinking Skills and Perception on Problem Solving Ability in the Science Laboratory

ERIC Educational Resources Information Center

Seyhan, Hatice Güngör

2015-01-01

This study was conducted with 98 prospective science teachers, who were composed of 50 prospective teachers that had participated in problem-solving applications and 48 prospective teachers who were taught within a more researcher-oriented teaching method in science laboratories. The first aim of this study was to determine the levels of…

Problem-solving counseling as a therapeutic tool on youth suicidal behavior in the suburban population in Sri Lanka.

PubMed

Perera, E A Ramani; Kathriarachchi, Samudra T

2011-01-01

Suicidal behaviour among youth is a major public health concern in Sri Lanka. Prevention of youth suicides using effective, feasible and culturally acceptable methods is invaluable in this regard, however research in this area is grossly lacking. This study aimed at determining the effectiveness of problem solving counselling as a therapeutic intervention in prevention of youth suicidal behaviour in Sri Lanka. This control trial study was based on hospital admissions with suicidal attempts in a sub-urban hospital in Sri Lanka. The study was carried out at Base Hospital Homagama. A sample of 124 was recruited using convenience sampling method and divided into two groups, experimental and control. Control group was offered routine care and experimental group received four sessions of problem solving counselling over one month. Outcome of both groups was measured, six months after the initial screening, using the visual analogue scale. Individualized outcome measures on problem solving counselling showed that problem solving ability among the subjects in the experimental group had improved after four counselling sessions and suicidal behaviour has been reduced. The results are statistically significant. This Study confirms that problem solving counselling is an effective therapeutic tool in management of youth suicidal behaviour in hospital setting in a developing country.

Using Problem-solving Therapy to Improve Problem-solving Orientation, Problem-solving Skills and Quality of Life in Older Hemodialysis Patients.

PubMed

Erdley-Kass, Shiloh D; Kass, Darrin S; Gellis, Zvi D; Bogner, Hillary A; Berger, Andrea; Perkins, Robert M

2017-08-24

To determine the effectiveness of Problem-Solving Therapy (PST) in older hemodialysis (HD) patients by assessing changes in health-related quality of life and problem-solving skills. 33 HD patients in an outpatient hemodialysis center without active medical and psychiatric illness were enrolled. The intervention group (n = 15) received PST from a licensed social worker for 6 weeks, whereas the control group (n = 18) received usual care treatment. In comparison to the control group, patients receiving PST intervention reported improved perceptions of mental health, were more likely to view their problems with a positive orientation and were more likely to use functional problem-solving methods. Furthermore, this group was also more likely to view their overall health, activity limits, social activities and ability to accomplish desired tasks with a more positive mindset. The results demonstrate that PST may positively impact mental health components of quality of life and problem-solving coping among older HD patients. PST is an effective, efficient, and easy to implement intervention that can benefit problem-solving abilities and mental health-related quality of life in older HD patients. In turn, this will help patients manage their daily living activities related to their medical condition and reduce daily stressors.

Novel methods for Solving Economic Dispatch of Security-Constrained Unit Commitment Based on Linear Programming

NASA Astrophysics Data System (ADS)

Guo, Sangang

2017-09-01

There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.

Planning and Scheduling for Fleets of Earth Observing Satellites

NASA Technical Reports Server (NTRS)

Frank, Jeremy; Jonsson, Ari; Morris, Robert; Smith, David E.; Norvig, Peter (Technical Monitor)

2001-01-01

We address the problem of scheduling observations for a collection of earth observing satellites. This scheduling task is a difficult optimization problem, potentially involving many satellites, hundreds of requests, constraints on when and how to service each request, and resources such as instruments, recording devices, transmitters, and ground stations. High-fidelity models are required to ensure the validity of schedules; at the same time, the size and complexity of the problem makes it unlikely that systematic optimization search methods will be able to solve them in a reasonable time. This paper presents a constraint-based approach to solving the Earth Observing Satellites (EOS) scheduling problem, and proposes a stochastic heuristic search method for solving it.

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.

An efficient method for generalized linear multiplicative programming problem with multiplicative constraints.

PubMed

Zhao, Yingfeng; Liu, Sanyang

2016-01-01

We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of some sample examples and a small random experiment show that the proposed algorithm is feasible and efficient.

Efficient algorithms for analyzing the singularly perturbed boundary value problems of fractional order

NASA Astrophysics Data System (ADS)

Sayevand, K.; Pichaghchi, K.

2018-04-01

In this paper, we were concerned with the description of the singularly perturbed boundary value problems in the scope of fractional calculus. We should mention that, one of the main methods used to solve these problems in classical calculus is the so-called matched asymptotic expansion method. However we shall note that, this was not achievable via the existing classical definitions of fractional derivative, because they do not obey the chain rule which one of the key elements of the matched asymptotic expansion method. In order to accommodate this method to fractional derivative, we employ a relatively new derivative so-called the local fractional derivative. Using the properties of local fractional derivative, we extend the matched asymptotic expansion method to the scope of fractional calculus and introduce a reliable new algorithm to develop approximate solutions of the singularly perturbed boundary value problems of fractional order. In the new method, the original problem is partitioned into inner and outer solution equations. The reduced equation is solved with suitable boundary conditions which provide the terminal boundary conditions for the boundary layer correction. The inner solution problem is next solved as a solvable boundary value problem. The width of the boundary layer is approximated using appropriate resemblance function. Some theoretical results are established and proved. Some illustrating examples are solved and the results are compared with those of matched asymptotic expansion method and homotopy analysis method to demonstrate the accuracy and efficiency of the method. It can be observed that, the proposed method approximates the exact solution very well not only in the boundary layer, but also away from the layer.

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.

A Teaching-Learning Method Enhancing Problem Solving and Motivation in Secondary Schools.

ERIC Educational Resources Information Center

Markoczi-Revak, Ibolya

2003-01-01

Presents a teaching-learning method for enhancing problem solving and motivation for studying science in secondary schools. Emerges from a former survey which, found that the motivation of 14-18-year-olds as measured by the Kozekik-Entwistle test was at a rather low level. (Contains 16 references.) (Author/YDS)

An Appropriate Prompts System Based on the Polya Method for Mathematical Problem-Solving

ERIC Educational Resources Information Center

Lee, Chien I.

2017-01-01

Current mathematics education emphasizes techniques, formulas, and procedures, neglecting the importance of understanding, presentation, and reasoning. This turns students into passive listeners that are well-practiced only in using formulas that they do not understand. We therefore adopted the Polya problem-solving method to provide students with…

Students’ thinking preferences in solving mathematics problems based on learning styles: a comparison of paper-pencil and geogebra

NASA Astrophysics Data System (ADS)

Farihah, Umi

2018-04-01

The purpose of this study was to analyze students’ thinking preferences in solving mathematics problems using paper pencil comparing to geogebra based on their learning styles. This research employed a qualitative descriptive study. The subjects of this research was six of eighth grade students of Madrasah Tsanawiyah Negeri 2 Trenggalek, East Java Indonesia academic year 2015-2016 with their difference learning styles; two visual students, two auditory students, and two kinesthetic students.. During the interview, the students presented the Paper and Pencil-based Task (PBTs) and the Geogebra-based Task (GBTs). By investigating students’ solution methods and the representation in solving the problems, the researcher compared their visual and non-visual thinking preferences in solving mathematics problems while they were using Geogebra and without Geogebra. Based on the result of research analysis, it was shown that the comparison between students’ PBTs and GBTs solution either visual, auditory, or kinesthetic represented how Geogebra can influence their solution method. By using Geogebra, they prefer using visual method while presenting GBTs to using non-visual method.

Adaptive sparsest narrow-band decomposition method and its applications to rolling element bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Junsheng; Peng, Yanfeng; Yang, Yu; Wu, Zhantao

2017-02-01

Enlightened by ASTFA method, adaptive sparsest narrow-band decomposition (ASNBD) method is proposed in this paper. In ASNBD method, an optimized filter must be established at first. The parameters of the filter are determined by solving a nonlinear optimization problem. A regulated differential operator is used as the objective function so that each component is constrained to be a local narrow-band signal. Afterwards, the signal is filtered by the optimized filter to generate an intrinsic narrow-band component (INBC). ASNBD is proposed aiming at solving the problems existed in ASTFA. Gauss-Newton type method, which is applied to solve the optimization problem in ASTFA, is irreplaceable and very sensitive to initial values. However, more appropriate optimization method such as genetic algorithm (GA) can be utilized to solve the optimization problem in ASNBD. Meanwhile, compared with ASTFA, the decomposition results generated by ASNBD have better physical meaning by constraining the components to be local narrow-band signals. Comparisons are made between ASNBD, ASTFA and EMD by analyzing simulation and experimental signals. The results indicate that ASNBD method is superior to the other two methods in generating more accurate components from noise signal, restraining the boundary effect, possessing better orthogonality and diagnosing rolling element bearing fault.

The effect of Think Pair Share (TPS) using scientific approach on students’ self-confidence and mathematical problem-solving

NASA Astrophysics Data System (ADS)

Rifa’i, A.; Lestari, H. P.

2018-03-01

This study was designed to know the effects of Think Pair Share using Scientific Approach on students' self-confidence and mathematical problem-solving. Quasi-experimental with pre-test post-test non-equivalent group method was used as a basis for design this study. Self-confidence questionnaire and problem-solving test have been used for measurement of the two variables. Two classes of the first grade in religious senior high school (MAN) in Indonesia were randomly selected for this study. Teaching sequence and series from mathematics book at control group in the traditional way and at experiment group has been in TPS using scientific approach learning method. For data analysis regarding students’ problem-solving skill and self-confidence, One-Sample t-Test, Independent Sample t-Test, and Multivariate of Variance (MANOVA) were used. The results showed that (1) TPS using a scientific approach and traditional learning had positive effects (2) TPS using scientific approach learning in comparative with traditional learning had a more significant effect on students’ self-confidence and problem-solving skill.

About the mechanism of ERP-system pilot test

NASA Astrophysics Data System (ADS)

Mitkov, V. V.; Zimin, V. V.

2018-05-01

In the paper the mathematical problem of defining the scope of pilot test is stated, which is a task of quadratic programming. The procedure of the problem solving includes the method of network programming based on the structurally similar network representation of the criterion and constraints and which reduces the original problem to a sequence of simpler evaluation tasks. The evaluation tasks are solved by the method of dichotomous programming.

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.

New computer program solves wide variety of heat flow problems

NASA Technical Reports Server (NTRS)

Almond, J. C.

1966-01-01

Boeing Engineering Thermal Analyzer /BETA/ computer program uses numerical methods to provide accurate heat transfer solutions to a wide variety of heat flow problems. The program solves steady-state and transient problems in almost any situation that can be represented by a resistance-capacitance network.

Design and Application of Interactive Simulations in Problem-Solving in University-Level Physics Education

NASA Astrophysics Data System (ADS)

Ceberio, Mikel; Almudí, José Manuel; Franco, Ángel

2016-08-01

In recent years, interactive computer simulations have been progressively integrated in the teaching of the sciences and have contributed significant improvements in the teaching-learning process. Practicing problem-solving is a key factor in science and engineering education. The aim of this study was to design simulation-based problem-solving teaching materials and assess their effectiveness in improving students' ability to solve problems in university-level physics. Firstly, we analyze the effect of using simulation-based materials in the development of students' skills in employing procedures that are typically used in the scientific method of problem-solving. We found that a significant percentage of the experimental students used expert-type scientific procedures such as qualitative analysis of the problem, making hypotheses, and analysis of results. At the end of the course, only a minority of the students persisted with habits based solely on mathematical equations. Secondly, we compare the effectiveness in terms of problem-solving of the experimental group students with the students who are taught conventionally. We found that the implementation of the problem-solving strategy improved experimental students' results regarding obtaining a correct solution from the academic point of view, in standard textbook problems. Thirdly, we explore students' satisfaction with simulation-based problem-solving teaching materials and we found that the majority appear to be satisfied with the methodology proposed and took on a favorable attitude to learning problem-solving. The research was carried out among first-year Engineering Degree students.

Conic Sampling: An Efficient Method for Solving Linear and Quadratic Programming by Randomly Linking Constraints within the Interior

PubMed Central

Serang, Oliver

2012-01-01

Linear programming (LP) problems are commonly used in analysis and resource allocation, frequently surfacing as approximations to more difficult problems. Existing approaches to LP have been dominated by a small group of methods, and randomized algorithms have not enjoyed popularity in practice. This paper introduces a novel randomized method of solving LP problems by moving along the facets and within the interior of the polytope along rays randomly sampled from the polyhedral cones defined by the bounding constraints. This conic sampling method is then applied to randomly sampled LPs, and its runtime performance is shown to compare favorably to the simplex and primal affine-scaling algorithms, especially on polytopes with certain characteristics. The conic sampling method is then adapted and applied to solve a certain quadratic program, which compute a projection onto a polytope; the proposed method is shown to outperform the proprietary software Mathematica on large, sparse QP problems constructed from mass spectometry-based proteomics. PMID:22952741

Multigrid methods for bifurcation problems: The self adjoint case

NASA Technical Reports Server (NTRS)

Taasan, Shlomo

1987-01-01

This paper deals with multigrid methods for computational problems that arise in the theory of bifurcation and is restricted to the self adjoint case. The basic problem is to solve for arcs of solutions, a task that is done successfully with an arc length continuation method. Other important issues are, for example, detecting and locating singular points as part of the continuation process, switching branches at bifurcation points, etc. Multigrid methods have been applied to continuation problems. These methods work well at regular points and at limit points, while they may encounter difficulties in the vicinity of bifurcation points. A new continuation method that is very efficient also near bifurcation points is presented here. The other issues mentioned above are also treated very efficiently with appropriate multigrid algorithms. For example, it is shown that limit points and bifurcation points can be solved for directly by a multigrid algorithm. Moreover, the algorithms presented here solve the corresponding problems in just a few work units (about 10 or less), where a work unit is the work involved in one local relaxation on the finest grid.

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.

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.

An investigative framework to facilitate epidemiological thinking during herd problem-solving.

PubMed

More, Simon J; Doherty, Michael L; O'Grady, Luke

2017-01-01

Veterinary clinicians and students commonly use diagnostic approaches appropriate for individual cases when conducting herd problem-solving. However, these approaches can be problematic, in part because they make limited use of epidemiological principles and methods, which has clear application during the investigation of herd problems. In this paper, we provide an overview of diagnostic approaches that are used when investigating individual animal cases, and the challenges faced when these approaches are directly translated from the individual to the herd. Further, we propose an investigative framework to facilitate epidemiological thinking during herd problem-solving. A number of different approaches are used when making a diagnosis on an individual animal, including pattern recognition, hypothetico-deductive reasoning, and the key abnormality method. Methods commonly applied to individuals are often adapted for herd problem-solving: 'comparison with best practice' being a herd-level adaptation of pattern recognition, and 'differential diagnoses' a herd-level adaptation of hypothetico-deductive reasoning. These approaches can be effective, however, challenges can arise. Herds are complex; a collection of individual cows, but also additional layers relating to environment, management, feeding etc. It is unrealistic to expect seamless translation of diagnostic approaches from the individual to the herd. Comparison with best practice is time-consuming and prioritisation of actions can be problematic, whereas differential diagnoses can lead to 'pathogen hunting', particularly in complex cases. Epidemiology is the science of understanding disease in populations. The focus is on the population, underpinned by principles and utilising methods that seek to allow us to generate solid conclusions from apparently uncontrolled situations. In this paper, we argue for the inclusion of epidemiological principles and methods as an additional tool for herd problem-solving, and outline an investigative framework, with examples, to effectively incorporate these principles and methods with other diagnostic approaches during herd problem-solving. Relevant measures of performance are identified, and measures of case frequencies are calculated and compared across time, in space and among animal groupings, to identify patterns, clues and plausible hypotheses, consistent with potential biological processes. With this knowledge, the subsequent investigation (relevant on-farm activities, diagnostic testing and other examinations) can be focused, and actions prioritised (specifically, those actions that are likely to make the greatest difference in addressing the problem if enacted). In our experience, this investigative framework is an effective teaching tool, facilitating epidemiological thinking among students during herd problem-solving. It is a generic and robust process, suited to many herd-based problems.

The effects of using diagramming as a representational technique on high school students' achievement in solving math word problems

NASA Astrophysics Data System (ADS)

Banerjee, Banmali

Methods and procedures for successfully solving math word problems have been, and continue to be a mystery to many U.S. high school students. Previous studies suggest that the contextual and mathematical understanding of a word problem, along with the development of schemas and their related external representations, positively contribute to students' accomplishments when solving word problems. Some studies have examined the effects of diagramming on students' abilities to solve word problems that only involved basic arithmetic operations. Other studies have investigated how instructional models that used technology influenced students' problem solving achievements. Still other studies have used schema-based instruction involving students with learning disabilities. No study has evaluated regular high school students' achievements in solving standard math word problems using a diagramming technique without technological aid. This study evaluated students' achievement in solving math word problems using a diagramming technique. Using a quasi-experimental experimental pretest-posttest research design, quantitative data were collected from 172 grade 11 Hispanic English language learners (ELLS) and African American learners whose first language is English (EFLLs) in 18 classes at an inner city high school in Northern New Jersey. There were 88 control and 84 experimental students. The pretest and posttest of each participating student and samples of the experimental students' class assignments provided the qualitative data for the study. The data from this study exhibited that the diagramming method of solving math word problems significantly improved student achievement in the experimental group (p<.01) compared to the control group. The study demonstrated that urban, high school, ELLs benefited from instruction that placed emphasis on the mathematical vocabulary and symbols used in word problems and that both ELLs and EFLLs improved their problem solving success through careful attention to the creation and labeling of diagrams to represent the mathematics involved in standard word problems. Although Learnertype (ELL, EFLL), Classtype (Bilingual and Mixed), and Gender (Female, Male) were not significant indicators of student achievement, there was significant interaction between Treatment and Classtype at the level of the Bilingual students ( p<.01) and between Treatment and Learnertype at the level of the ELLs (p<.01).

Investigating the effect of mental set on insight problem solving.

PubMed

Ollinger, Michael; Jones, Gary; Knoblich, Günther

2008-01-01

Mental set is the tendency to solve certain problems in a fixed way based on previous solutions to similar problems. The moment of insight occurs when a problem cannot be solved using solution methods suggested by prior experience and the problem solver suddenly realizes that the solution requires different solution methods. Mental set and insight have often been linked together and yet no attempt thus far has systematically examined the interplay between the two. Three experiments are presented that examine the extent to which sets of noninsight and insight problems affect the subsequent solutions of insight test problems. The results indicate a subtle interplay between mental set and insight: when the set involves noninsight problems, no mental set effects are shown for the insight test problems, yet when the set involves insight problems, both facilitation and inhibition can be seen depending on the type of insight problem presented in the set. A two process model is detailed to explain these findings that combines the representational change mechanism with that of proceduralization.

Physical activity problem-solving inventory for adolescents: development and initial validation.

PubMed

Thompson, Debbe; Bhatt, Riddhi; Watson, Kathy

2013-08-01

Youth encounter physical activity barriers, often called problems. The purpose of problem solving is to generate solutions to overcome the barriers. Enhancing problem-solving ability may enable youth to be more physically active. Therefore, a method for reliably assessing physical activity problem-solving ability is needed. The purpose of this research was to report the development and initial validation of the physical activity problem-solving inventory for adolescents (PAPSIA). Qualitative and quantitative procedures were used. The social problem-solving inventory for adolescents guided the development of the PAPSIA scale. Youth (14- to 17-year-olds) were recruited using standard procedures, such as distributing flyers in the community and to organizations likely to be attended by adolescents. Cognitive interviews were conducted in person. Adolescents completed pen and paper versions of the questionnaire and/or scales assessing social desirability, self-reported physical activity, and physical activity self-efficacy. An expert panel review, cognitive interviews, and a pilot study (n = 129) established content validity. Construct, concurrent, and predictive validity were also established (n = 520 youth). PAPSIA is a promising measure for assessing youth physical activity problem-solving ability. Future research will assess its validity with objectively measured physical activity.

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.

A multilevel finite element method for Fredholm integral eigenvalue problems

NASA Astrophysics Data System (ADS)

Xie, Hehu; Zhou, Tao

2015-12-01

In this work, we proposed a multigrid finite element (MFE) method for solving the Fredholm integral eigenvalue problems. The main motivation for such studies is to compute the Karhunen-Loève expansions of random fields, which play an important role in the applications of uncertainty quantification. In our MFE framework, solving the eigenvalue problem is converted to doing a series of integral iterations and eigenvalue solving in the coarsest mesh. Then, any existing efficient integration scheme can be used for the associated integration process. The error estimates are provided, and the computational complexity is analyzed. It is noticed that the total computational work of our method is comparable with a single integration step in the finest mesh. Several numerical experiments are presented to validate the efficiency of the proposed numerical method.

Analysis of mathematical problem-solving ability based on metacognition on problem-based learning

NASA Astrophysics Data System (ADS)

Mulyono; Hadiyanti, R.

2018-03-01

Problem-solving is the primary purpose of the mathematics curriculum. Problem-solving abilities influenced beliefs and metacognition. Metacognition as superordinate capabilities can direct, regulate cognition and motivation and then problem-solving processes. This study aims to (1) test and analyzes the quality of problem-based learning and (2) investigate the problem-solving capabilities based on metacognition. This research uses mixed method study with The subject research are class XI students of Mathematics and Science at High School Kesatrian 2 Semarang which divided into tacit use, aware use, strategic use and reflective use level. The collecting data using scale, interviews, and tests. The data processed with the proportion of test, t-test, and paired samples t-test. The result shows that the students with levels tacit use were able to complete the whole matter given, but do not understand what and why a strategy is used. Students with aware use level were able to solve the problem, be able to build new knowledge through problem-solving to the indicators, understand the problem, determine the strategies used, although not right. Students on the Strategic ladder Use can be applied and adopt a wide variety of appropriate strategies to solve the issues and achieved re-examine indicators of process and outcome. The student with reflective use level is not found in this study. Based on the results suggested that study about the identification of metacognition in problem-solving so that the characteristics of each level of metacognition more clearly in a more significant sampling. Teachers need to know in depth about the student metacognitive activity and its relationship with mathematical problem solving and another problem resolution.

Solving Capacitated Closed Vehicle Routing Problem with Time Windows (CCVRPTW) using BRKGA with local search

NASA Astrophysics Data System (ADS)

Prasetyo, H.; Alfatsani, M. A.; Fauza, G.

2018-05-01

The main issue in vehicle routing problem (VRP) is finding the shortest route of product distribution from the depot to outlets to minimize total cost of distribution. Capacitated Closed Vehicle Routing Problem with Time Windows (CCVRPTW) is one of the variants of VRP that accommodates vehicle capacity and distribution period. Since the main problem of CCVRPTW is considered a non-polynomial hard (NP-hard) problem, it requires an efficient and effective algorithm to solve the problem. This study was aimed to develop Biased Random Key Genetic Algorithm (BRKGA) that is combined with local search to solve the problem of CCVRPTW. The algorithm design was then coded by MATLAB. Using numerical test, optimum algorithm parameters were set and compared with the heuristic method and Standard BRKGA to solve a case study on soft drink distribution. Results showed that BRKGA combined with local search resulted in lower total distribution cost compared with the heuristic method. Moreover, the developed algorithm was found to be successful in increasing the performance of Standard BRKGA.

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.

An improved genetic algorithm and its application in the TSP problem

NASA Astrophysics Data System (ADS)

Li, Zheng; Qin, Jinlei

2011-12-01

Concept and research actuality of genetic algorithm are introduced in detail in the paper. Under this condition, the simple genetic algorithm and an improved algorithm are described and applied in an example of TSP problem, where the advantage of genetic algorithm is adequately shown in solving the NP-hard problem. In addition, based on partial matching crossover operator, the crossover operator method is improved into extended crossover operator in order to advance the efficiency when solving the TSP. In the extended crossover method, crossover operator can be performed between random positions of two random individuals, which will not be restricted by the position of chromosome. Finally, the nine-city TSP is solved using the improved genetic algorithm with extended crossover method, the efficiency of whose solution process is much higher, besides, the solving speed of the optimal solution is much faster.

Making Changes: A Futures-Oriented Course in Inventive Problem Solving. Lesson Book.

ERIC Educational Resources Information Center

Thomas, John W.

This textbook/workbook for secondary school students is designed to stimulate inventive problem solving of future world problems. It is organized into four units and contains 23 lessons. Unit I defines the nature of the course and provides methods for stating and defining problems, brainstorming, working in groups, and judging ideas. Unit II…

Building and Solving Odd-One-Out Classification Problems: A Systematic Approach

ERIC Educational Resources Information Center

Ruiz, Philippe E.

2011-01-01

Classification problems ("find the odd-one-out") are frequently used as tests of inductive reasoning to evaluate human or animal intelligence. This paper introduces a systematic method for building the set of all possible classification problems, followed by a simple algorithm for solving the problems of the R-ASCM, a psychometric test derived…

Computational inverse methods of heat source in fatigue damage problems

NASA Astrophysics Data System (ADS)

Chen, Aizhou; Li, Yuan; Yan, Bo

2018-04-01

Fatigue dissipation energy is the research focus in field of fatigue damage at present. It is a new idea to solve the problem of calculating fatigue dissipation energy by introducing inverse method of heat source into parameter identification of fatigue dissipation energy model. This paper introduces the research advances on computational inverse method of heat source and regularization technique to solve inverse problem, as well as the existing heat source solution method in fatigue process, prospects inverse method of heat source applying in fatigue damage field, lays the foundation for further improving the effectiveness of fatigue dissipation energy rapid prediction.

Factor Structure and Item Level Psychometrics of the Social Problem Solving Inventory Revised-Short Form in Traumatic Brain Injury

PubMed Central

Li, Chih-Ying; Waid-Ebbs, Julia; Velozo, Craig A.; Heaton, Shelley C.

2016-01-01

Primary Objective Social problem solving deficits characterize individuals with traumatic brain injury (TBI). Poor social problem solving interferes with daily functioning and productive lifestyles. Therefore, it is of vital importance to use the appropriate instrument to identify deficits in social problem solving for individuals with TBI. This study investigates factor structure and item-level psychometrics of the Social Problem Solving Inventory-Revised Short Form (SPSI-R:S), for adults with moderate and severe TBI. Research Design Secondary analysis of 90 adults with moderate and severe TBI who completed the SPSI-R:S. Methods and Procedures An exploratory factor analysis (EFA), principal components analysis (PCA) and Rasch analysis examined the factor structure and item-level psychometrics of the SPSI-R:S. Main Outcomes and Results The EFA showed three dominant factors, with positively worded items represented as the most definite factor. The other two factors are negative problem solving orientation and skills; and negative problem solving emotion. Rasch analyses confirmed the three factors are each unidimensional constructs. Conclusions The total score interpretability of the SPSI-R:S may be challenging due to the multidimensional structure of the total measure. Instead, we propose using three separate SPSI-R:S subscores to measure social problem solving for the TBI population. PMID:26052731

The Quantum Binding Problem in the Context of Associative Memory

PubMed Central

Wichert, Andreas

2016-01-01

We present a method to solve the binding problem by using a quantum algorithm for the retrieval of associations from associative memory during visual scene analysis. The problem is solved by mapping the information representing different objects into superposition by using entanglement and Grover’s amplification algorithm. PMID:27603782

Middle School Engineering Problem Solving Using Traditional vs. E-PBL Module Instruction

ERIC Educational Resources Information Center

Baele, Loren C.

2017-01-01

This multiple methods (Denzin, 1978) study investigated two instructional approaches, traditional module and electronic Problem-Based Learning instruction (e-PBL), used within a middle school engineering classroom focused on the variables of engagement, content knowledge, student self-assessment and teacher assessment of problem solving solutions.…

Problem solving performance and learning strategies of undergraduate students who solved microbiology problems using IMMEX educational software

NASA Astrophysics Data System (ADS)

Ebomoyi, Josephine Itota

The objectives of this study were as follows: (1) Determine the relationship between learning strategies and performance in problem solving, (2) Explore the role of a student's declared major on performance in problem solving, (3) Understand the decision making process of high and low achievers during problem solving. Participants (N = 65) solved problems using the Interactive multimedia exercise (IMMEX) software. All participants not only solved "Microquest," which focuses on cellular processes and mode of action of antibiotics, but also "Creeping Crud," which focuses on the cause, origin and transmission of diseases. Participants also responded to the "Motivated Strategy Learning Questionnaire" (MSLQ). Hierarchical multiple regression was used for analysis with GPA (Gracie point average) as a control. There were 49 (78.6%) that successfully solved "Microquest" while 52 (82.5%) successfully solved "Creeping Crud". Metacognitive self regulation strategy was significantly (p < .10) related to ability to solve "Creeping Crud". Peer learning strategy showed a positive significant (p < .10) relationship with scores obtained from solving "Creeping Crud". Students' declared major made a significant (p < .05) difference on the ability to solve "Microquest". A subset (18) volunteered for a think aloud method to determine decision-making process. High achievers used fewer steps, and had more focused approach than low achievers. Common strategies and attributes included metacognitive skills, writing to keep track, using prior knowledge. Others included elements of frustration/confusion and self-esteem problems. The implications for educational and relevance to real life situations are discussed.

Asymptotically suboptimal control of weakly interconnected dynamical systems

NASA Astrophysics Data System (ADS)

Dmitruk, N. M.; Kalinin, A. I.

2016-10-01

Optimal control problems for a group of systems with weak dynamical interconnections between its constituent subsystems are considered. A method for decentralized control is proposed which distributes the control actions between several controllers calculating in real time control inputs only for theirs subsystems based on the solution of the local optimal control problem. The local problem is solved by asymptotic methods that employ the representation of the weak interconnection by a small parameter. Combination of decentralized control and asymptotic methods allows to significantly reduce the dimension of the problems that have to be solved in the course of the control process.

Pseudo-time methods for constrained optimization problems governed by PDE

NASA Technical Reports Server (NTRS)

Taasan, Shlomo

1995-01-01

In this paper we present a novel method for solving optimization problems governed by partial differential equations. Existing methods are gradient information in marching toward the minimum, where the constrained PDE is solved once (sometimes only approximately) per each optimization step. Such methods can be viewed as a marching techniques on the intersection of the state and costate hypersurfaces while improving the residuals of the design equations per each iteration. In contrast, the method presented here march on the design hypersurface and at each iteration improve the residuals of the state and costate equations. The new method is usually much less expensive per iteration step since, in most problems of practical interest, the design equation involves much less unknowns that that of either the state or costate equations. Convergence is shown using energy estimates for the evolution equations governing the iterative process. Numerical tests show that the new method allows the solution of the optimization problem in a cost of solving the analysis problems just a few times, independent of the number of design parameters. The method can be applied using single grid iterations as well as with multigrid solvers.

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…

Iterative Methods for Solving Nonlinear Parabolic Problem in Pension Saving Management

NASA Astrophysics Data System (ADS)

Koleva, M. N.

2011-11-01

In this work we consider a nonlinear parabolic equation, obtained from Riccati like transformation of the Hamilton-Jacobi-Bellman equation, arising in pension saving management. We discuss two numerical iterative methods for solving the model problem—fully implicit Picard method and mixed Picard-Newton method, which preserves the parabolic characteristics of the differential problem. Numerical experiments for comparison the accuracy and effectiveness of the algorithms are discussed. Finally, observations are given.

A Legendre tau-spectral method for solving time-fractional heat equation with nonlocal conditions.

PubMed

Bhrawy, A H; Alghamdi, M A

2014-01-01

We develop the tau-spectral method to solve the time-fractional heat equation (T-FHE) with nonlocal condition. In order to achieve highly accurate solution of this problem, the operational matrix of fractional integration (described in the Riemann-Liouville sense) for shifted Legendre polynomials is investigated in conjunction with tau-spectral scheme and the Legendre operational polynomials are used as the base function. The main advantage in using the presented scheme is that it converts the T-FHE with nonlocal condition to a system of algebraic equations that simplifies the problem. For demonstrating the validity and applicability of the developed spectral scheme, two numerical examples are presented. The logarithmic graphs of the maximum absolute errors is presented to achieve the exponential convergence of the proposed method. Comparing between our spectral method and other methods ensures that our method is more accurate than those solved similar problem.

A Legendre tau-Spectral Method for Solving Time-Fractional Heat Equation with Nonlocal Conditions

PubMed Central

Bhrawy, A. H.; Alghamdi, M. A.

2014-01-01

We develop the tau-spectral method to solve the time-fractional heat equation (T-FHE) with nonlocal condition. In order to achieve highly accurate solution of this problem, the operational matrix of fractional integration (described in the Riemann-Liouville sense) for shifted Legendre polynomials is investigated in conjunction with tau-spectral scheme and the Legendre operational polynomials are used as the base function. The main advantage in using the presented scheme is that it converts the T-FHE with nonlocal condition to a system of algebraic equations that simplifies the problem. For demonstrating the validity and applicability of the developed spectral scheme, two numerical examples are presented. The logarithmic graphs of the maximum absolute errors is presented to achieve the exponential convergence of the proposed method. Comparing between our spectral method and other methods ensures that our method is more accurate than those solved similar problem. PMID:25057507

Space-dependent perfusion coefficient estimation in a 2D bioheat transfer problem

NASA Astrophysics Data System (ADS)

Bazán, Fermín S. V.; Bedin, Luciano; Borges, Leonardo S.

2017-05-01

In this work, a method for estimating the space-dependent perfusion coefficient parameter in a 2D bioheat transfer model is presented. In the method, the bioheat transfer model is transformed into a time-dependent semidiscrete system of ordinary differential equations involving perfusion coefficient values as parameters, and the estimation problem is solved through a nonlinear least squares technique. In particular, the bioheat problem is solved by the method of lines based on a highly accurate pseudospectral approach, and perfusion coefficient values are estimated by the regularized Gauss-Newton method coupled with a proper regularization parameter. The performance of the method on several test problems is illustrated numerically.

A mediational model of self-esteem and social problem-solving in anorexia nervosa.

PubMed

Paterson, Gillian; Power, Kevin; Collin, Paula; Greirson, David; Yellowlees, Alex; Park, Katy

2011-01-01

Poor problem-solving and low self-esteem are frequently cited as significant factors in the development and maintenance of anorexia nervosa. The current study examines the multi-dimensional elements of these measures and postulates a model whereby self-esteem mediates the relationship between social problems-solving and anorexic pathology and considers the implications of this pathway. Fifty-five inpatients with a diagnosis of anorexia nervosa and 50 non-clinical controls completed three standardised multi-dimensional questionnaires pertaining to social problem-solving, self-esteem and eating pathology. Significant differences were yielded between clinical and non-clinical samples on all measures. Within the clinical group, elements of social problem-solving most significant to anorexic pathology were positive problem orientation, negative problem orientation and avoidance. Components of self-esteem most significant to anorexic pathology were eating, weight and shape concern but not eating restraint. The mediational model was upheld with social problem-solving impacting on anorexic pathology through the existence of low self-esteem. Problem orientation, that is, the cognitive processes of social problem-solving appear to be more significant than problem-solving methods in individuals with anorexia nervosa. Negative perceptions of eating, weight and shape appear to impact on low self-esteem but level of restriction does not. Finally, results indicate that self-esteem is a significant factor in the development and execution of positive or negative social problem-solving in individuals with anorexia nervosa by mediating the relationship between those two variables. Copyright © 2010 John Wiley & Sons, Ltd and Eating Disorders Association.

Total-variation based velocity inversion with Bregmanized operator splitting algorithm

NASA Astrophysics Data System (ADS)

Zand, Toktam; Gholami, Ali

2018-04-01

Many problems in applied geophysics can be formulated as a linear inverse problem. The associated problems, however, are large-scale and ill-conditioned. Therefore, regularization techniques are needed to be employed for solving them and generating a stable and acceptable solution. We consider numerical methods for solving such problems in this paper. In order to tackle the ill-conditioning of the problem we use blockiness as a prior information of the subsurface parameters and formulate the problem as a constrained total variation (TV) regularization. The Bregmanized operator splitting (BOS) algorithm as a combination of the Bregman iteration and the proximal forward backward operator splitting method is developed to solve the arranged problem. Two main advantages of this new algorithm are that no matrix inversion is required and that a discrepancy stopping criterion is used to stop the iterations, which allow efficient solution of large-scale problems. The high performance of the proposed TV regularization method is demonstrated using two different experiments: 1) velocity inversion from (synthetic) seismic data which is based on Born approximation, 2) computing interval velocities from RMS velocities via Dix formula. Numerical examples are presented to verify the feasibility of the proposed method for high-resolution velocity inversion.

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.

Characteristics of students in comparative problem solving

NASA Astrophysics Data System (ADS)

Irfan, M.; Sudirman; Rahardi, R.

2018-01-01

Often teachers provided examples and exercised to students with regard to comparative problems consisting of one quantity. In this study, the researchers gave the problem of comparison with the two quantities mixed. It was necessary to have a good understanding to solve this problem. This study aimed to determine whether students understand the comparison in depth and be able to solve the problem of non-routine comparison. This study used qualitative explorative methods, with researchers conducting in-depth interviews on subjects to explore the thinking process when solving comparative problems. The subject of this study was three students selected by purposive sampling of 120 students. From this research, researchers found there were three subjects with different characteristics, namely: subject 1, he did the first and second questions with methods of elimination and substitution (non-comparison); subject 2, he did the first question with the concept of comparison although the answer was wrong, and did the second question with the method of elimination and substitution (non-comparison); and subject 3, he did both questions with the concept of comparison. In the first question, he did wrong because he was unable to understand the problem, while on the second he did correctly. From the characteristics of the answers, the researchers divided into 3 groups based on thinking process, namely: blind-proportion, partial-proportion, and proportion thinking.

The Influence of Science Knowledge Structures on Children's Success in Solving Academic Problems.

ERIC Educational Resources Information Center

Champagne, Audrey B.; And Others

Presented is a study of eighth-grade students' academic problem-solving ability based on their knowledge structures, or their information stored in semantic or long-term memory. The authors describe a technique that they developed to probe knowledge structures with an extension of the card-sort method. The method, known as the Concept Structure…

Effects of Singapore's Model Method on Elementary Student Problem Solving Performance: Single Subject Research

ERIC Educational Resources Information Center

Mahoney, Kevin

2012-01-01

This research investigation examined the effects of Singapore's Model Method, also known as "model drawing" or "bar modeling" on the word problem-solving performance of American third and fourth grade students. Employing a single-case design, a researcher-designed teaching intervention was delivered to a child in third…

Using Science Inquiry Methods to Promote Self-Determination and Problem-Solving Skills for Students with Moderate Intellectual Disability

ERIC Educational Resources Information Center

Miller, Bridget; Doughty, Teresa; Krockover, Gerald

2015-01-01

This study investigated the use of guided science inquiry methods with self-monitoring checklists to support problem-solving for students and increased autonomy during science instruction for students with moderate intellectual disability. Three students with moderate intellectual disability were supported in not only accessing the general…

The Possible Impact of Problem-Solving Method of Instruction on Exceptional Students' Creativity

ERIC Educational Resources Information Center

Fard, Adnan Eshrati; Bahador, Ali; Moghadam, Mahsa Nazemi; Rajabi, Hooman; Moradi, Alinoor Noor

2014-01-01

The current study aimed at investigating the possible impact of the problem-solving method of instruction on the exceptional students' creativity. A sample of 50 male exceptional (Mild intellectual disability) students studying in the third grade of junior high school was chosen and divided into two equal groups. Both groups filled out the…

Self-Instructional Methods of Teaching Diagnostic Problem Solving to Automotive Students. Vocational-Industrial Education Research Report.

ERIC Educational Resources Information Center

Finch, Curtis R.

The objective of this study was to investigate the effects of three methods of teaching diagnostic problem-solving (troubleshooting) to automotive students. The sample consisted of 45 community college students enrolled in automotive courses. Initially, all students received a presentation on ignition principles, and the Otis Mental Ability Test…

Solving Differential Equations in R: Package deSolve

EPA Science Inventory

In this paper we present the R package deSolve to solve initial value problems (IVP) written as ordinary differential equations (ODE), differential algebraic equations (DAE) of index 0 or 1 and partial differential equations (PDE), the latter solved using the method of lines appr...

Decision-making and problem-solving methods in automation technology

NASA Technical Reports Server (NTRS)

Hankins, W. W.; Pennington, J. E.; Barker, L. K.

1983-01-01

The state of the art in the automation of decision making and problem solving is reviewed. The information upon which the report is based was derived from literature searches, visits to university and government laboratories performing basic research in the area, and a 1980 Langley Research Center sponsored conferences on the subject. It is the contention of the authors that the technology in this area is being generated by research primarily in the three disciplines of Artificial Intelligence, Control Theory, and Operations Research. Under the assumption that the state of the art in decision making and problem solving is reflected in the problems being solved, specific problems and methods of their solution are often discussed to elucidate particular aspects of the subject. Synopses of the following major topic areas comprise most of the report: (1) detection and recognition; (2) planning; and scheduling; (3) learning; (4) theorem proving; (5) distributed systems; (6) knowledge bases; (7) search; (8) heuristics; and (9) evolutionary programming.

One shot methods for optimal control of distributed parameter systems 1: Finite dimensional control

NASA Technical Reports Server (NTRS)

Taasan, Shlomo

1991-01-01

The efficient numerical treatment of optimal control problems governed by elliptic partial differential equations (PDEs) and systems of elliptic PDEs, where the control is finite dimensional is discussed. Distributed control as well as boundary control cases are discussed. The main characteristic of the new methods is that they are designed to solve the full optimization problem directly, rather than accelerating a descent method by an efficient multigrid solver for the equations involved. The methods use the adjoint state in order to achieve efficient smoother and a robust coarsening strategy. The main idea is the treatment of the control variables on appropriate scales, i.e., control variables that correspond to smooth functions are solved for on coarse grids depending on the smoothness of these functions. Solution of the control problems is achieved with the cost of solving the constraint equations about two to three times (by a multigrid solver). Numerical examples demonstrate the effectiveness of the method proposed in distributed control case, pointwise control and boundary control problems.

Extrusion Process by Finite Volume Method Using OpenFoam Software

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

Matos Martins, Marcelo; Tonini Button, Sergio; Divo Bressan, Jose

The computational codes are very important tools to solve engineering problems. In the analysis of metal forming process, such as extrusion, this is not different because the computational codes allow analyzing the process with reduced cost. Traditionally, the Finite Element Method is used to solve solid mechanic problems, however, the Finite Volume Method (FVM) have been gaining force in this field of applications. This paper presents the velocity field and friction coefficient variation results, obtained by numerical simulation using the OpenFoam Software and the FVM to solve an aluminum direct cold extrusion process.

How Instructional Designers Solve Workplace Problems

ERIC Educational Resources Information Center

Fortney, Kathleen S.; Yamagata-Lynch, Lisa C.

2013-01-01

This naturalistic inquiry investigated how instructional designers engage in complex and ambiguous problem solving across organizational boundaries in two corporations. Participants represented a range of instructional design experience, from novices to experts. Research methods included a participant background survey, observations of…

Fictitious domain method for fully resolved reacting gas-solid flow simulation

NASA Astrophysics Data System (ADS)

Zhang, Longhui; Liu, Kai; You, Changfu

2015-10-01

Fully resolved simulation (FRS) for gas-solid multiphase flow considers solid objects as finite sized regions in flow fields and their behaviours are predicted by solving equations in both fluid and solid regions directly. Fixed mesh numerical methods, such as fictitious domain method, are preferred in solving FRS problems and have been widely researched. However, for reacting gas-solid flows no suitable fictitious domain numerical method has been developed. This work presents a new fictitious domain finite element method for FRS of reacting particulate flows. Low Mach number reacting flow governing equations are solved sequentially on a regular background mesh. Particles are immersed in the mesh and driven by their surface forces and torques integrated on immersed interfaces. Additional treatments on energy and surface reactions are developed. Several numerical test cases validated the method and a burning carbon particles array falling simulation proved the capability for solving moving reacting particle cluster problems.

Patterns of problem-solving in children's literacy and arithmetic.

PubMed

Farrington-Flint, Lee; Vanuxem-Cotterill, Sophie; Stiller, James

2009-11-01

Patterns of problem-solving among 5-to-7 year-olds' were examined on a range of literacy (reading and spelling) and arithmetic-based (addition and subtraction) problem-solving tasks using verbal self-reports to monitor strategy choice. The results showed higher levels of variability in the children's strategy choice across Years I and 2 on the arithmetic (addition and subtraction) than literacy-based tasks (reading and spelling). However, across all four tasks, the children showed a tendency to move from less sophisticated procedural-based strategies, which included phonological strategies for reading and spelling and counting-all and finger modellingfor addition and subtraction, to more efficient retrieval methods from Years I to 2. Distinct patterns in children's problem-solving skill were identified on the literacy and arithmetic tasks using two separate cluster analyses. There was a strong association between these two profiles showing that those children with more advanced problem-solving skills on the arithmetic tasks also showed more advanced profiles on the literacy tasks. The results highlight how different-aged children show flexibility in their use of problem-solving strategies across literacy and arithmetical contexts and reinforce the importance of studying variations in children's problem-solving skill across different educational contexts.

Cognitive Predictors of Everyday Problem Solving across the Lifespan

PubMed Central

Chen, Xi; Hertzog, Christopher; Park, Denise C.

2017-01-01

Background An important aspect of successful aging is maintaining the ability to solve everyday problems encountered in daily life. The limited evidence today suggests that everyday problem solving ability increases from young adulthood to middle age, but decreases in older age. Objectives The present study examined age differences in the relative contributions of fluid and crystallized abilities to solving problems on the Everyday Problems Test (EPT; [1]). We hypothesized that due to diminishing fluid resources available with advanced age, crystallized knowledge would become increasingly important in predicting everyday problem solving with greater age. Method Two hundred and twenty-one healthy adults from the Dallas Lifespan Brain Study, aged 24–93 years, completed a cognitive battery that included measures of fluid ability (i.e., processing speed, working memory, inductive reasoning) and crystallized ability (i.e., multiple measures of vocabulary). These measures were used to predict performance on the Everyday Problems Test. Results Everyday problem solving showed an increase in performance from young to early middle age, with performance beginning to decrease at about age of fifty. As hypothesized, fluid ability was the primary predictor of performance on everyday problem solving for young adults, but with increasing age, crystallized ability became the dominant predictor. Conclusion This study provides evidence that everyday problem solving ability differs with age, and, more importantly, that the processes underlying it differ with age as well. The findings indicate that older adults increasingly rely on knowledge to support everyday problem solving, whereas young adults rely almost exclusively on fluid intelligence. PMID:28273664

Social problem solving among depressed adolescents is enhanced by structured psychotherapies

PubMed Central

Dietz, Laura J.; Marshal, Michael P.; Burton, Chad M.; Bridge, Jeffrey A.; Birmaher, Boris; Kolko, David; Duffy, Jamira N.; Brent, David A.

2014-01-01

Objective Changes in adolescent interpersonal behavior before and after an acute course of psychotherapy were investigated as outcomes and mediators of remission status in a previously described treatment study of depressed adolescents. Maternal depressive symptoms were examined as moderators of the association between psychotherapy condition and changes in adolescents’ interpersonal behavior. Method Adolescents (n = 63, mean age = 15.6 years, 77.8% female, 84.1% Caucasian) engaged in videotaped interactions with their mothers before randomization to cognitive behavior therapy (CBT), systemic behavior family therapy (SBFT), or nondirective supportive therapy (NST), and after 12–16 weeks of treatment. Adolescent involvement, problem solving and dyadic conflict were examined. Results Improvements in adolescent problem solving were significantly associated with CBT and SBFT. Maternal depressive symptoms moderated the effect of CBT, but not SBFT, on adolescents’ problem solving; adolescents experienced increases in problem solving only when their mothers had low or moderate levels of depressive symptoms. Improvements in adolescents’ problem solving were associated with higher rates of remission across treatment conditions, but there were no significant indirect effects of SBFT on remission status through problem solving. Exploratory analyses revealed a significant indirect effect of CBT on remission status through changes in adolescent problem solving, but only when maternal depressive symptoms at study entry were low. Conclusions Findings provide preliminary support for problem solving as an active treatment component of structured psychotherapies for depressed adolescents and suggest one Pathway by which maternal depression may disrupt treatment efficacy for depressed adolescents treated with CBT. PMID:24491077

Regularization and computational methods for precise solution of perturbed orbit transfer problems

NASA Astrophysics Data System (ADS)

Woollands, Robyn Michele

The author has developed a suite of algorithms for solving the perturbed Lambert's problem in celestial mechanics. These algorithms have been implemented as a parallel computation tool that has broad applicability. This tool is composed of four component algorithms and each provides unique benefits for solving a particular type of orbit transfer problem. The first one utilizes a Keplerian solver (a-iteration) for solving the unperturbed Lambert's problem. This algorithm not only provides a "warm start" for solving the perturbed problem but is also used to identify which of several perturbed solvers is best suited for the job. The second algorithm solves the perturbed Lambert's problem using a variant of the modified Chebyshev-Picard iteration initial value solver that solves two-point boundary value problems. This method converges over about one third of an orbit and does not require a Newton-type shooting method and thus no state transition matrix needs to be computed. The third algorithm makes use of regularization of the differential equations through the Kustaanheimo-Stiefel transformation and extends the domain of convergence over which the modified Chebyshev-Picard iteration two-point boundary value solver will converge, from about one third of an orbit to almost a full orbit. This algorithm also does not require a Newton-type shooting method. The fourth algorithm uses the method of particular solutions and the modified Chebyshev-Picard iteration initial value solver to solve the perturbed two-impulse Lambert problem over multiple revolutions. The method of particular solutions is a shooting method but differs from the Newton-type shooting methods in that it does not require integration of the state transition matrix. The mathematical developments that underlie these four algorithms are derived in the chapters of this dissertation. For each of the algorithms, some orbit transfer test cases are included to provide insight on accuracy and efficiency of these individual algorithms. Following this discussion, the combined parallel algorithm, known as the unified Lambert tool, is presented and an explanation is given as to how it automatically selects which of the three perturbed solvers to compute the perturbed solution for a particular orbit transfer. The unified Lambert tool may be used to determine a single orbit transfer or for generating of an extremal field map. A case study is presented for a mission that is required to rendezvous with two pieces of orbit debris (spent rocket boosters). The unified Lambert tool software developed in this dissertation is already being utilized by several industrial partners and we are confident that it will play a significant role in practical applications, including solution of Lambert problems that arise in the current applications focused on enhanced space situational awareness.

Workflow Agents vs. Expert Systems: Problem Solving Methods in Work Systems Design

NASA Technical Reports Server (NTRS)

Clancey, William J.; Sierhuis, Maarten; Seah, Chin

2009-01-01

During the 1980s, a community of artificial intelligence researchers became interested in formalizing problem solving methods as part of an effort called "second generation expert systems" (2nd GES). How do the motivations and results of this research relate to building tools for the workplace today? We provide an historical review of how the theory of expertise has developed, a progress report on a tool for designing and implementing model-based automation (Brahms), and a concrete example how we apply 2nd GES concepts today in an agent-based system for space flight operations (OCAMS). Brahms incorporates an ontology for modeling work practices, what people are doing in the course of a day, characterized as "activities." OCAMS was developed using a simulation-to-implementation methodology, in which a prototype tool was embedded in a simulation of future work practices. OCAMS uses model-based methods to interactively plan its actions and keep track of the work to be done. The problem solving methods of practice are interactive, employing reasoning for and through action in the real world. Analogously, it is as if a medical expert system were charged not just with interpreting culture results, but actually interacting with a patient. Our perspective shifts from building a "problem solving" (expert) system to building an actor in the world. The reusable components in work system designs include entire "problem solvers" (e.g., a planning subsystem), interoperability frameworks, and workflow agents that use and revise models dynamically in a network of people and tools. Consequently, the research focus shifts so "problem solving methods" include ways of knowing that models do not fit the world, and ways of interacting with other agents and people to gain or verify information and (ultimately) adapt rules and procedures to resolve problematic situations.

Teaching Creative Problem Solving Methods to Undergraduate Economics and Business Students

ERIC Educational Resources Information Center

Cancer, Vesna

2014-01-01

This paper seeks to explore the need for and possibility of teaching current and potential problem solvers--undergraduate students in the economic and business field to define problems, to generate and choose creative and useful ideas and to verify them. It aims to select an array of quick and easy-to-use creative problem solving (CPS) techniques.…

Problem-based learning on quantitative analytical chemistry course

NASA Astrophysics Data System (ADS)

Fitri, Noor

2017-12-01

This research applies problem-based learning method on chemical quantitative analytical chemistry, so called as "Analytical Chemistry II" course, especially related to essential oil analysis. The learning outcomes of this course include aspects of understanding of lectures, the skills of applying course materials, and the ability to identify, formulate and solve chemical analysis problems. The role of study groups is quite important in improving students' learning ability and in completing independent tasks and group tasks. Thus, students are not only aware of the basic concepts of Analytical Chemistry II, but also able to understand and apply analytical concepts that have been studied to solve given analytical chemistry problems, and have the attitude and ability to work together to solve the problems. Based on the learning outcome, it can be concluded that the problem-based learning method in Analytical Chemistry II course has been proven to improve students' knowledge, skill, ability and attitude. Students are not only skilled at solving problems in analytical chemistry especially in essential oil analysis in accordance with local genius of Chemistry Department, Universitas Islam Indonesia, but also have skilled work with computer program and able to understand material and problem in English.

Multigrid method for stability problems

NASA Technical Reports Server (NTRS)

Ta'asan, Shlomo

1988-01-01

The problem of calculating the stability of steady state solutions of differential equations is addressed. Leading eigenvalues of large matrices that arise from discretization are calculated, and an efficient multigrid method for solving these problems is presented. The resulting grid functions are used as initial approximations for appropriate eigenvalue problems. The method employs local relaxation on all levels together with a global change on the coarsest level only, which is designed to separate the different eigenfunctions as well as to update their corresponding eigenvalues. Coarsening is done using the FAS formulation in a nonstandard way in which the right-hand side of the coarse grid equations involves unknown parameters to be solved on the coarse grid. This leads to a new multigrid method for calculating the eigenvalues of symmetric problems. Numerical experiments with a model problem are presented which demonstrate the effectiveness of the method.

Students' Problem Solving and Justification

ERIC Educational Resources Information Center

Glass, Barbara; Maher, Carolyn A.

2004-01-01

This paper reports on methods of students' justifications of their solution to a problem in the area of combinatorics. From the analysis of the problem solving of 150 students in a variety of settings from high-school to graduate study, four major forms of reasoning evolved: (1) Justification by Cases, (2) Inductive Argument, (3) Elimination…

Chebyshev polynomials in the spectral Tau method and applications to Eigenvalue problems

NASA Technical Reports Server (NTRS)

Johnson, Duane

1996-01-01

Chebyshev Spectral methods have received much attention recently as a technique for the rapid solution of ordinary differential equations. This technique also works well for solving linear eigenvalue problems. Specific detail is given to the properties and algebra of chebyshev polynomials; the use of chebyshev polynomials in spectral methods; and the recurrence relationships that are developed. These formula and equations are then applied to several examples which are worked out in detail. The appendix contains an example FORTRAN program used in solving an eigenvalue problem.

Modern architectures for intelligent systems: reusable ontologies and problem-solving methods.

PubMed Central

Musen, M. A.

1998-01-01

When interest in intelligent systems for clinical medicine soared in the 1970s, workers in medical informatics became particularly attracted to rule-based systems. Although many successful rule-based applications were constructed, development and maintenance of large rule bases remained quite problematic. In the 1980s, an entire industry dedicated to the marketing of tools for creating rule-based systems rose and fell, as workers in medical informatics began to appreciate deeply why knowledge acquisition and maintenance for such systems are difficult problems. During this time period, investigators began to explore alternative programming abstractions that could be used to develop intelligent systems. The notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) domain-independent problem-solving methods-standard algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper will highlight how intelligent systems for diverse tasks can be efficiently automated using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community. PMID:9929181

Modern architectures for intelligent systems: reusable ontologies and problem-solving methods.

PubMed

Musen, M A

1998-01-01

When interest in intelligent systems for clinical medicine soared in the 1970s, workers in medical informatics became particularly attracted to rule-based systems. Although many successful rule-based applications were constructed, development and maintenance of large rule bases remained quite problematic. In the 1980s, an entire industry dedicated to the marketing of tools for creating rule-based systems rose and fell, as workers in medical informatics began to appreciate deeply why knowledge acquisition and maintenance for such systems are difficult problems. During this time period, investigators began to explore alternative programming abstractions that could be used to develop intelligent systems. The notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) domain-independent problem-solving methods-standard algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper will highlight how intelligent systems for diverse tasks can be efficiently automated using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

NASA Astrophysics Data System (ADS)

Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

2015-12-01

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

Vectorial finite elements for solving the radiative transfer equation

NASA Astrophysics Data System (ADS)

Badri, M. A.; Jolivet, P.; Rousseau, B.; Le Corre, S.; Digonnet, H.; Favennec, Y.

2018-06-01

The discrete ordinate method coupled with the finite element method is often used for the spatio-angular discretization of the radiative transfer equation. In this paper we attempt to improve upon such a discretization technique. Instead of using standard finite elements, we reformulate the radiative transfer equation using vectorial finite elements. In comparison to standard finite elements, this reformulation yields faster timings for the linear system assemblies, as well as for the solution phase when using scattering media. The proposed vectorial finite element discretization for solving the radiative transfer equation is cross-validated against a benchmark problem available in literature. In addition, we have used the method of manufactured solutions to verify the order of accuracy for our discretization technique within different absorbing, scattering, and emitting media. For solving large problems of radiation on parallel computers, the vectorial finite element method is parallelized using domain decomposition. The proposed domain decomposition method scales on large number of processes, and its performance is unaffected by the changes in optical thickness of the medium. Our parallel solver is used to solve a large scale radiative transfer problem of the Kelvin-cell radiation.

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.

Reliable use of determinants to solve nonlinear structural eigenvalue problems efficiently

NASA Technical Reports Server (NTRS)

Williams, F. W.; Kennedy, D.

1988-01-01

The analytical derivation, numerical implementation, and performance of a multiple-determinant parabolic interpolation method (MDPIM) for use in solving transcendental eigenvalue (critical buckling or undamped free vibration) problems in structural mechanics are presented. The overall bounding, eigenvalue-separation, qualified parabolic interpolation, accuracy-confirmation, and convergence-recovery stages of the MDPIM are described in detail, and the numbers of iterations required to solve sample plane-frame problems using the MDPIM are compared with those for a conventional bisection method and for the Newtonian method of Simpson (1984) in extensive tables. The MDPIM is shown to use 31 percent less computation time than bisection when accuracy of 0.0001 is required, but 62 percent less when accuracy of 10 to the -8th is required; the time savings over the Newtonian method are about 10 percent.

The Research of Improving the Particleboard Glue Dosing Process Based on TRIZ Analysis

NASA Astrophysics Data System (ADS)

Yu, Huiling; Fan, Delin; Zhang, Yizhuo

This research creates a design methodology by synthesizing the Theory of Inventive Problem Solving (TRIZ) and cascade control based on Smith predictor. The particleboard glue supplying and dosing system case study defines the problem and the solution using the methodology proposed in the paper. Status difference existing in the gluing dosing process of particleboard production usually causes gluing volume inaccurately. In order to solve the problem above, we applied the TRIZ technical contradiction and inventive principle to improve the key process of particleboard production. The improving method mapped inaccurate problem to TRIZ technical contradiction, the prior action proposed Smith predictor as the control algorithm in the glue dosing system. This research examines the usefulness of a TRIZ based problem-solving process designed to improve the problem-solving ability of users in addressing difficult or reoccurring problems and also testify TRIZ is practicality and validity. Several suggestions are presented on how to approach this problem.

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.

Reconstruction of local perturbations in periodic surfaces

NASA Astrophysics Data System (ADS)

Lechleiter, Armin; Zhang, Ruming

2018-03-01

This paper concerns the inverse scattering problem to reconstruct a local perturbation in a periodic structure. Unlike the periodic problems, the periodicity for the scattered field no longer holds, thus classical methods, which reduce quasi-periodic fields in one periodic cell, are no longer available. Based on the Floquet-Bloch transform, a numerical method has been developed to solve the direct problem, that leads to a possibility to design an algorithm for the inverse problem. The numerical method introduced in this paper contains two steps. The first step is initialization, that is to locate the support of the perturbation by a simple method. This step reduces the inverse problem in an infinite domain into one periodic cell. The second step is to apply the Newton-CG method to solve the associated optimization problem. The perturbation is then approximated by a finite spline basis. Numerical examples are given at the end of this paper, showing the efficiency of the numerical method.

New modified multi-level residue harmonic balance method for solving nonlinearly vibrating double-beam problem

NASA Astrophysics Data System (ADS)

Rahman, Md. Saifur; Lee, Yiu-Yin

2017-10-01

In this study, a new modified multi-level residue harmonic balance method is presented and adopted to investigate the forced nonlinear vibrations of axially loaded double beams. Although numerous nonlinear beam or linear double-beam problems have been tackled and solved, there have been few studies of this nonlinear double-beam problem. The geometric nonlinear formulations for a double-beam model are developed. The main advantage of the proposed method is that a set of decoupled nonlinear algebraic equations is generated at each solution level. This heavily reduces the computational effort compared with solving the coupled nonlinear algebraic equations generated in the classical harmonic balance method. The proposed method can generate the higher-level nonlinear solutions that are neglected by the previous modified harmonic balance method. The results from the proposed method agree reasonably well with those from the classical harmonic balance method. The effects of damping, axial force, and excitation magnitude on the nonlinear vibrational behaviour are examined.

Propagation of Axisymmetric Electroelastic Waves in a Hollow Layered Cylinder Under Mechanical Excitation

NASA Astrophysics Data System (ADS)

Grigorenko, A. Ya.; Loza, I. A.

2017-09-01

The problem on propagation of axisymmetric electroelastic waves in a hollow layered cylinder made of metallic and radially polarized piezoceramic layers is solved. The lateral surfaces of the cylinder are free of electrodes. The outside surface is free of mechanical loads, while the inside one undergoes harmonically varying pressure Pe. The problem was solved with a numerical-analytical method. By representing the components of the stress tensor, displacement vectors, electric-flux density, and electrostatic potential by traveling waves, the original electroelastic problem in partial derivatives is reduced to an inhomogeneous boundary-value problem for ordinary differential equations. To solve the problem, the stable numerical discrete-orthogonalization method is used. The results of the kinematic analysis of the layered cylinder both with metallic and piezoceramic (PZT 4) layers are presented. The numerical results are analyzed.

A Novel Harmony Search Algorithm Based on Teaching-Learning Strategies for 0-1 Knapsack Problems

PubMed Central

Tuo, Shouheng; Yong, Longquan; Deng, Fang'an

2014-01-01

To enhance the performance of harmony search (HS) algorithm on solving the discrete optimization problems, this paper proposes a novel harmony search algorithm based on teaching-learning (HSTL) strategies to solve 0-1 knapsack problems. In the HSTL algorithm, firstly, a method is presented to adjust dimension dynamically for selected harmony vector in optimization procedure. In addition, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation) are employed to improve the performance of HS algorithm. Another improvement in HSTL method is that the dynamic strategies are adopted to change the parameters, which maintains the proper balance effectively between global exploration power and local exploitation power. Finally, simulation experiments with 13 knapsack problems show that the HSTL algorithm can be an efficient alternative for solving 0-1 knapsack problems. PMID:24574905

A novel harmony search algorithm based on teaching-learning strategies for 0-1 knapsack problems.

PubMed

Tuo, Shouheng; Yong, Longquan; Deng, Fang'an

2014-01-01

To enhance the performance of harmony search (HS) algorithm on solving the discrete optimization problems, this paper proposes a novel harmony search algorithm based on teaching-learning (HSTL) strategies to solve 0-1 knapsack problems. In the HSTL algorithm, firstly, a method is presented to adjust dimension dynamically for selected harmony vector in optimization procedure. In addition, four strategies (harmony memory consideration, teaching-learning strategy, local pitch adjusting, and random mutation) are employed to improve the performance of HS algorithm. Another improvement in HSTL method is that the dynamic strategies are adopted to change the parameters, which maintains the proper balance effectively between global exploration power and local exploitation power. Finally, simulation experiments with 13 knapsack problems show that the HSTL algorithm can be an efficient alternative for solving 0-1 knapsack problems.

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.

About decomposition approach for solving the classification problem

NASA Astrophysics Data System (ADS)

Andrianova, A. A.

2016-11-01

This article describes the features of the application of an algorithm with using of decomposition methods for solving the binary classification problem of constructing a linear classifier based on Support Vector Machine method. Application of decomposition reduces the volume of calculations, in particular, due to the emerging possibilities to build parallel versions of the algorithm, which is a very important advantage for the solution of problems with big data. The analysis of the results of computational experiments conducted using the decomposition approach. The experiment use known data set for binary classification problem.

Solving Large-Scale Inverse Magnetostatic Problems using the Adjoint Method

PubMed Central

Bruckner, Florian; Abert, Claas; Wautischer, Gregor; Huber, Christian; Vogler, Christoph; Hinze, Michael; Suess, Dieter

2017-01-01

An efficient algorithm for the reconstruction of the magnetization state within magnetic components is presented. The occurring inverse magnetostatic problem is solved by means of an adjoint approach, based on the Fredkin-Koehler method for the solution of the forward problem. Due to the use of hybrid FEM-BEM coupling combined with matrix compression techniques the resulting algorithm is well suited for large-scale problems. Furthermore the reconstruction of the magnetization state within a permanent magnet as well as an optimal design application are demonstrated. PMID:28098851

The Effect of Montessori Method Supported by Social Skills Training Program on Turkish Kindergarten Children's Skills of Understanding Feelings and Social Problem Solving

ERIC Educational Resources Information Center

Kayili, Gökhan; Ari, Ramazan

2016-01-01

The current research was conducted with the purpose of analyzing the effect of Montessori method supported by Social Skills Training Program on kindergarten children's skills of understanding feelings and social problem solving. 53 children attending Ihsan Dogramaci Applied Nursery School affiliated to Selcuk University, Faculty of Health Sciences…

The Development of a Small-World Network of Higher Education Students, Using a Large-Group Problem-Solving Method

ERIC Educational Resources Information Center

Sousa, Fernando Cardoso; Monteiro, Ileana Pardal; Pellissier, René

2014-01-01

This article presents the development of a small-world network using an adapted version of the large-group problem-solving method "Future Search." Two management classes in a higher education setting were selected and required to plan a project. The students completed a survey focused on the frequency of communications before and after…

Effects of Problem-Solving Method on Secondary School Students' Achievement and Retention in Social Studies, in Ekiti State, Nigeria

ERIC Educational Resources Information Center

Abdu-Raheem, B. O.

2012-01-01

This study investigated the effects of problem-solving method of teaching on secondary school students' achievement and retention in Social Studies. The study adopted the quasi-experimental, pre-test, post-test, control group design. The sample for the study consisted of 240 Junior Secondary School Class II students randomly selected from six…

The Usefulness of Qualitative and Quantitative Approaches and Methods in Researching Problem-Solving Ability in Science Education Curriculum

ERIC Educational Resources Information Center

Eyisi, Daniel

2016-01-01

Research in science education is to discover the truth which involves the combination of reasoning and experiences. In order to find out appropriate teaching methods that are necessary for teaching science students problem-solving skills, different research approaches are used by educational researchers based on the data collection and analysis…

Problem solving as a core strategy in the prevention of schizophrenia and other mental disorders.

PubMed

Falloon, I R

2000-11-01

To outline the rationale for implementing training in structured problem solving as a primary prevention strategy for major mental disorders. The evidence that training people in a structured method of solving their personal problems is an effective strategy in the treatment of established cases of schizophrenic and major mood disorders, is selectively reviewed. Most of the relevant research focused on the prevention of major recurrent episodes of psychosis. There is some evidence to support the hypothesis that this strategy may assist many people to achieve a full and sustained recovery from the clinical and social impairments of these disorders, especially when patients are taught to use structured problem solving with members of their personal resource groups, and they continue to take optimal doses of psychoactive medication. There is support for the hypothesis that the key therapeutic factor associated with these benefits is the improved efficiency of the management of life stress. The simplicity of problem solving, the educational methods used, and the widespread application to a person's lifestyle would appear to make this a possible candidate for a primary prevention program for major mental disorders. Guidebooks and teaching aids have been developed and show excellent consumer acceptance.

An optical solution for the traveling salesman problem.

PubMed

Haist, Tobias; Osten, Wolfgang

2007-08-06

We introduce an optical method based on white light interferometry in order to solve the well-known NP-complete traveling salesman problem. To our knowledge it is the first time that a method for the reduction of non-polynomial time to quadratic time has been proposed. We will show that this achievement is limited by the number of available photons for solving the problem. It will turn out that this number of photons is proportional to N(N) for a traveling salesman problem with N cities and that for large numbers of cities the method in practice therefore is limited by the signal-to-noise ratio. The proposed method is meant purely as a gedankenexperiment.

Efficient Parallel Formulations of Hierarchical Methods and Their Applications

NASA Astrophysics Data System (ADS)

Grama, Ananth Y.

1996-01-01

Hierarchical methods such as the Fast Multipole Method (FMM) and Barnes-Hut (BH) are used for rapid evaluation of potential (gravitational, electrostatic) fields in particle systems. They are also used for solving integral equations using boundary element methods. The linear systems arising from these methods are dense and are solved iteratively. Hierarchical methods reduce the complexity of the core matrix-vector product from O(n^2) to O(n log n) and the memory requirement from O(n^2) to O(n). We have developed highly scalable parallel formulations of a hybrid FMM/BH method that are capable of handling arbitrarily irregular distributions. We apply these formulations to astrophysical simulations of Plummer and Gaussian galaxies. We have used our parallel formulations to solve the integral form of the Laplace equation. We show that our parallel hierarchical mat-vecs yield high efficiency and overall performance even on relatively small problems. A problem containing approximately 200K nodes takes under a second to compute on 256 processors and yet yields over 85% efficiency. The efficiency and raw performance is expected to increase for bigger problems. For the 200K node problem, our code delivers about 5 GFLOPS of performance on a 256 processor T3D. This is impressive considering the fact that the problem has floating point divides and roots, and very little locality resulting in poor cache performance. A dense matrix-vector product of the same dimensions would require about 0.5 TeraBytes of memory and about 770 TeraFLOPS of computing speed. Clearly, if the loss in accuracy resulting from the use of hierarchical methods is acceptable, our code yields significant savings in time and memory. We also study the convergence of a GMRES solver built around this mat-vec. We accelerate the convergence of the solver using three preconditioning techniques: diagonal scaling, block-diagonal preconditioning, and inner-outer preconditioning. We study the performance and parallel efficiency of these preconditioned solvers. Using this solver, we solve dense linear systems with hundreds of thousands of unknowns. Solving a 105K unknown problem takes about 10 minutes on a 64 processor T3D. Until very recently, boundary element problems of this magnitude could not even be generated, let alone solved.

Are middle school mathematics teachers able to solve word problems without using variable?

NASA Astrophysics Data System (ADS)

Gökkurt Özdemir, Burçin; Erdem, Emrullah; Örnek, Tuğba; Soylu, Yasin

2018-01-01

Many people consider problem solving as a complex process in which variables such as x, y are used. Problems may not be solved by only using 'variable.' Problem solving can be rationalized and made easier using practical strategies. When especially the development of children at younger ages is considered, it is obvious that mathematics teachers should solve problems through concrete processes. In this context, middle school mathematics teachers' skills to solve word problems without using variables were examined in the current study. Through the case study method, this study was conducted with 60 middle school mathematics teachers who have different professional experiences in five provinces in Turkey. A test consisting of five open-ended word problems was used as the data collection tool. The content analysis technique was used to analyze the data. As a result of the analysis, it was seen that the most of the teachers used trial-and-error strategy or area model as the solution strategy. On the other hand, the teachers who solved the problems using variables such as x, a, n or symbols such as Δ, □, ○, * and who also felt into error by considering these solutions as without variable were also seen in the study.

The Effect of Metacognitive Instruction on Problem Solving Skills in Iranian Students of Health Sciences.

PubMed

Safari, Yahya; Meskini, Habibeh

2015-05-17

Learning requires application of such processes as planning, supervision, monitoring and reflection that are included in the metacognition. Studies have shown that metacognition is associated with problem solving skills. The current research was conducted to investigate the impact of metacognitive instruction on students' problem solving skills. The study sample included 40 students studying in the second semester at Kermanshah University of Medical Sciences, 2013-2014. They were selected through convenience sampling technique and were randomly assigned into two equal groups of experimental and control. For the experimental group, problem solving skills were taught through metacognitive instruction during ten two-hour sessions and for the control group, problem solving skills were taught via conventional teaching method. The instrument for data collection included problem solving inventory (Heppner, 1988), which was administered before and after instruction. The validity and reliability of the questionnaire had been previously confirmed. The collected data were analyzed by descriptive statistics, mean and standard deviation and the hypotheses were tested by t-test and ANCOVA. The findings of the posttest showed that the total mean scores of problem solving skills in the experimental and control groups were 151.90 and 101.65, respectively, indicating a significant difference between them (p<0.001). This difference was also reported to be statistically significant between problem solving skills and its components, including problem solving confidence, orientation-avoidance coping style and personal control (p<0.001). No significant difference, however, was found between the students' mean scores in terms of gender and major. Since metacognitive instruction has positive effects on students' problem solving skills and is required to enhance academic achievement, metacognitive strategies are recommended to be taught to the students.

An optimization-based approach for solving a time-harmonic multiphysical wave problem with higher-order schemes

NASA Astrophysics Data System (ADS)

Mönkölä, Sanna

2013-06-01

This study considers developing numerical solution techniques for the computer simulations of time-harmonic fluid-structure interaction between acoustic and elastic waves. The focus is on the efficiency of an iterative solution method based on a controllability approach and spectral elements. We concentrate on the model, in which the acoustic waves in the fluid domain are modeled by using the velocity potential and the elastic waves in the structure domain are modeled by using displacement. Traditionally, the complex-valued time-harmonic equations are used for solving the time-harmonic problems. Instead of that, we focus on finding periodic solutions without solving the time-harmonic problems directly. The time-dependent equations can be simulated with respect to time until a time-harmonic solution is reached, but the approach suffers from poor convergence. To overcome this challenge, we follow the approach first suggested and developed for the acoustic wave equations by Bristeau, Glowinski, and Périaux. Thus, we accelerate the convergence rate by employing a controllability method. The problem is formulated as a least-squares optimization problem, which is solved with the conjugate gradient (CG) algorithm. Computation of the gradient of the functional is done directly for the discretized problem. A graph-based multigrid method is used for preconditioning the CG algorithm.

A Coupling Strategy of FEM and BEM for the Solution of a 3D Industrial Crack Problem

NASA Astrophysics Data System (ADS)

Kouitat Njiwa, Richard; Taha Niane, Ngadia; Frey, Jeremy; Schwartz, Martin; Bristiel, Philippe

2015-03-01

Analyzing crack stability in an industrial context is challenging due to the geometry of the structure. The finite element method is effective for defect-free problems. The boundary element method is effective for problems in simple geometries with singularities. We present a strategy that takes advantage of both approaches. Within the iterative solution procedure, the FEM solves a defect-free problem over the structure while the BEM solves the crack problem over a fictitious domain with simple geometry. The effectiveness of the approach is demonstrated on some simple examples which allow comparison with literature results and on an industrial problem.

Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.

PubMed

Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou

2015-01-01

Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1) βk ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.

Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models

PubMed Central

Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou

2015-01-01

Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1)β k ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations. PMID:26502409

Numerical solution of the nonlinear Schrodinger equation by feedforward neural networks

NASA Astrophysics Data System (ADS)

Shirvany, Yazdan; Hayati, Mohsen; Moradian, Rostam

2008-12-01

We present a method to solve boundary value problems using artificial neural networks (ANN). A trial solution of the differential equation is written as a feed-forward neural network containing adjustable parameters (the weights and biases). From the differential equation and its boundary conditions we prepare the energy function which is used in the back-propagation method with momentum term to update the network parameters. We improved energy function of ANN which is derived from Schrodinger equation and the boundary conditions. With this improvement of energy function we can use unsupervised training method in the ANN for solving the equation. Unsupervised training aims to minimize a non-negative energy function. We used the ANN method to solve Schrodinger equation for few quantum systems. Eigenfunctions and energy eigenvalues are calculated. Our numerical results are in agreement with their corresponding analytical solution and show the efficiency of ANN method for solving eigenvalue problems.

Topology optimization of unsteady flow problems using the lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Nørgaard, Sebastian; Sigmund, Ole; Lazarov, Boyan

2016-02-01

This article demonstrates and discusses topology optimization for unsteady incompressible fluid flows. The fluid flows are simulated using the lattice Boltzmann method, and a partial bounceback model is implemented to model the transition between fluid and solid phases in the optimization problems. The optimization problem is solved with a gradient based method, and the design sensitivities are computed by solving the discrete adjoint problem. For moderate Reynolds number flows, it is demonstrated that topology optimization can successfully account for unsteady effects such as vortex shedding and time-varying boundary conditions. Such effects are relevant in several engineering applications, i.e. fluid pumps and control valves.

Numerical method for solving the nonlinear four-point boundary value problems

NASA Astrophysics Data System (ADS)

Lin, Yingzhen; Lin, Jinnan

2010-12-01

In this paper, a new reproducing kernel space is constructed skillfully in order to solve a class of nonlinear four-point boundary value problems. The exact solution of the linear problem can be expressed in the form of series and the approximate solution of the nonlinear problem is given by the iterative formula. Compared with known investigations, the advantages of our method are that the representation of exact solution is obtained in a new reproducing kernel Hilbert space and accuracy of numerical computation is higher. Meanwhile we present the convergent theorem, complexity analysis and error estimation. The performance of the new method is illustrated with several numerical examples.

Junior high school students' cognitive process in solving the developed algebraic problems based on information processing taxonomy model

NASA Astrophysics Data System (ADS)

Purwoko, Saad, Noor Shah; Tajudin, Nor'ain Mohd

2017-05-01

This study aims to: i) develop problem solving questions of Linear Equations System of Two Variables (LESTV) based on levels of IPT Model, ii) explain the level of students' skill of information processing in solving LESTV problems; iii) explain students' skill in information processing in solving LESTV problems; and iv) explain students' cognitive process in solving LESTV problems. This study involves three phases: i) development of LESTV problem questions based on Tessmer Model; ii) quantitative survey method on analyzing students' skill level of information processing; and iii) qualitative case study method on analyzing students' cognitive process. The population of the study was 545 eighth grade students represented by a sample of 170 students of five Junior High Schools in Hilir Barat Zone, Palembang (Indonesia) that were chosen using cluster sampling. Fifteen students among them were drawn as a sample for the interview session with saturated information obtained. The data were collected using the LESTV problem solving test and the interview protocol. The quantitative data were analyzed using descriptive statistics, while the qualitative data were analyzed using the content analysis. The finding of this study indicated that students' cognitive process was just at the step of indentifying external source and doing algorithm in short-term memory fluently. Only 15.29% students could retrieve type A information and 5.88% students could retrieve type B information from long-term memory. The implication was the development problems of LESTV had validated IPT Model in modelling students' assessment by different level of hierarchy.

Linear homotopy solution of nonlinear systems of equations in geodesy

NASA Astrophysics Data System (ADS)

Paláncz, Béla; Awange, Joseph L.; Zaletnyik, Piroska; Lewis, Robert H.

2010-01-01

A fundamental task in geodesy is solving systems of equations. Many geodetic problems are represented as systems of multivariate polynomials. A common problem in solving such systems is improper initial starting values for iterative methods, leading to convergence to solutions with no physical meaning, or to convergence that requires global methods. Though symbolic methods such as Groebner bases or resultants have been shown to be very efficient, i.e., providing solutions for determined systems such as 3-point problem of 3D affine transformation, the symbolic algebra can be very time consuming, even with special Computer Algebra Systems (CAS). This study proposes the Linear Homotopy method that can be implemented easily in high-level computer languages like C++ and Fortran that are faster than CAS by at least two orders of magnitude. Using Mathematica, the power of Homotopy is demonstrated in solving three nonlinear geodetic problems: resection, GPS positioning, and affine transformation. The method enlarging the domain of convergence is found to be efficient, less sensitive to rounding of numbers, and has lower complexity compared to other local methods like Newton-Raphson.

Space structures insulating material's thermophysical and radiation properties estimation

NASA Astrophysics Data System (ADS)

Nenarokomov, A. V.; Alifanov, O. M.; Titov, D. M.

2007-11-01

In many practical situations in aerospace technology it is impossible to measure directly such properties of analyzed materials (for example, composites) as thermal and radiation characteristics. The only way that can often be used to overcome these difficulties is indirect measurements. This type of measurement is usually formulated as the solution of inverse heat transfer problems. Such problems are ill-posed in mathematical sense and their main feature shows itself in the solution instabilities. That is why special regularizing methods are needed to solve them. The experimental methods of identification of the mathematical models of heat transfer based on solving the inverse problems are one of the modern effective solving manners. The objective of this paper is to estimate thermal and radiation properties of advanced materials using the approach based on inverse methods.

An Efficient Augmented Lagrangian Method with Applications to Total Variation Minimization

DTIC Science & Technology

2012-08-17

the classic augmented Lagrangian multiplier method, we propose, analyze and test an algorithm for solving a class of equality-constrained non-smooth...method, we propose, analyze and test an algorithm for solving a class of equality-constrained non-smooth optimization problems (chie y but not...significantly outperforming several state-of-the-art solvers on most tested problems. The resulting MATLAB solver, called TVAL3, has been posted online [23]. 2

The Effects of Problem-Based Learning on Pre-Service Teachers' Critical Thinking Dispositions and Perceptions of Problem-Solving Ability

ERIC Educational Resources Information Center

Temel, Senar

2014-01-01

The aim of this study was two-fold. The first aim was to determine the levels of critical thinking disposition and perception of problem-solving ability of pre-service teachers. The second aim was to compare the effects of problem-based learning and traditional teaching methods on the critical thinking dispositions and perceptions of…

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.

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

Facilitating Problem Solving in High School Chemistry.

ERIC Educational Resources Information Center

Gabel, Dorothy L.; Sherwood, Robert D.

1983-01-01

Investigated superiority of instructional strategies (factor-label method, proportionality, use of analogies, use of diagrams) in teaching problem-solving related to mole concept, gas laws, stoichiometry, and molarity. Also investigated effectiveness of strategies for students (N=609) with different verbal-visual preferences, proportional…

The Problem-Solving Nemesis: Mindless Manipulation.

ERIC Educational Resources Information Center

Hawkins, Vincent J.

1987-01-01

Indicates that only 21% of respondents (secondary school math teachers) used computer-assisted instruction for tutorial work, physical models to interpret abstract concepts, or real-life application of the arithmetic or algebraic manipulation. Recommends that creative teaching methods be applied to problem solving. (NKA)

Beyond Assertiveness Training: A Problem-Solving Approach.

ERIC Educational Resources Information Center

Scott, Nancy A.

1979-01-01

Assertiveness training models show shortcomings in those situations where assertiveness results in stalemates or conflicts, or both. Deadlocks may occur when antagonists demonstrate appropriate assertive behavior. Conflict management using problem-solving skills allows individuals to learn appropriate methods of dealing with conflictual or…

Problem Solving with Spreadsheets.

ERIC Educational Resources Information Center

Catterall, P.; Lewis, R.

1985-01-01

Documents the educational use of spreadsheets through a description of exploratory work which utilizes spreadsheets to achieve the objectives of Conway's Game of Life, a scientific method game for the development of problem-solving techniques. The implementation and classroom use of the spreadsheet programs are discussed. (MBR)

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.

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

Numerical algebraic geometry: a new perspective on gauge and string theories

NASA Astrophysics Data System (ADS)

Mehta, Dhagash; He, Yang-Hui; Hauensteine, Jonathan D.

2012-07-01

There is a rich interplay between algebraic geometry and string and gauge theories which has been recently aided immensely by advances in computational algebra. However, symbolic (Gröbner) methods are severely limited by algorithmic issues such as exponential space complexity and being highly sequential. In this paper, we introduce a novel paradigm of numerical algebraic geometry which in a plethora of situations overcomes these shortcomings. The so-called `embarrassing parallelizability' allows us to solve many problems and extract physical information which elude symbolic methods. We describe the method and then use it to solve various problems arising from physics which could not be otherwise solved.

An Exploratory Study Contrasting High- and Low-Achieving Students' Percent Word Problem Solving

ERIC Educational Resources Information Center

Jitendra, Asha K.; Star, Jon R.

2012-01-01

This study evaluated whether schema-based instruction (SBI), a promising method for teaching students to represent and solve mathematical word problems, impacted the learning of percent word problems. Of particular interest was the extent that SBI improved high- and low-achieving students' learning and to a lesser degree on the indirect effect of…

Singapore Math: Problem-Solving Secrets from the World's Math Leader

ERIC Educational Resources Information Center

Hogan, Bob

2005-01-01

Using this four CD-ROM disc set, teachers can have their very own math problem solving mentor as a leading expert in Singapore Math guides them through a lively presentation, working through math problems and explaining how Singapore has become the world's leading method in math. The expert's explanation of how to use Singapore's model-drawing…

Dynamic Restructuring Of Problems In Artificial Intelligence

NASA Technical Reports Server (NTRS)

Schwuttke, Ursula M.

1992-01-01

"Dynamic tradeoff evaluation" (DTE) denotes proposed method and procedure for restructuring problem-solving strategies in artificial intelligence to satisfy need for timely responses to changing conditions. Detects situations in which optimal problem-solving strategies cannot be pursued because of real-time constraints, and effects tradeoffs among nonoptimal strategies in such way to minimize adverse effects upon performance of system.

Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

NASA Astrophysics Data System (ADS)

Omagari, Hiroki; Higashino, Shin-Ichiro

2018-04-01

In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

On a numerical solving of random generated hexamatrix games

NASA Astrophysics Data System (ADS)

Orlov, Andrei; Strekalovskiy, Alexander

2016-10-01

In this paper, we develop a global search method for finding a Nash equilibrium in a hexamatrix game (polymatrix game of three players). The method, on the one hand, is based on the equivalence theorem of the problem of finding a Nash equilibrium in the game and a special mathematical optimization problem, and, on the other hand, on the usage of Global Search Theory for solving the latter problem. The efficiency of this approach is demonstrated by the results of computational testing.

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.

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 framework for solving ill-structured community problems

NASA Astrophysics Data System (ADS)

Keller, William Cotesworth

A multifaceted protocol for solving ill-structured community problems has been developed. It embodies the lessons learned from the past by refining and extending features of previous models from the systems thinkers, and the fields of behavioral decision making and creative problem solving. The protocol also embraces additional features needed to address the unique aspects of community decision situations. The essential elements of the protocol are participants from the community, a problem-solving process, a systems picture, a facilitator, a modified Delphi method of communications, and technical expertise. This interdisciplinary framework has been tested by a quasi experiment with a real world community problem (the high cost of electrical power on Long Island, NY). Results indicate the protocol can enable members of the community to understand a complicated, ill-structured problem and guide them to action to solve the issue. However, the framework takes time (over one year in the test case) and will be inappropriate for crises where quick action is needed.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem.

PubMed

Rajeswari, M; Amudhavel, J; Pothula, Sujatha; Dhavachelvan, P

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria.

Directed Bee Colony Optimization Algorithm to Solve the Nurse Rostering Problem

PubMed Central

Amudhavel, J.; Pothula, Sujatha; Dhavachelvan, P.

2017-01-01

The Nurse Rostering Problem is an NP-hard combinatorial optimization, scheduling problem for assigning a set of nurses to shifts per day by considering both hard and soft constraints. A novel metaheuristic technique is required for solving Nurse Rostering Problem (NRP). This work proposes a metaheuristic technique called Directed Bee Colony Optimization Algorithm using the Modified Nelder-Mead Method for solving the NRP. To solve the NRP, the authors used a multiobjective mathematical programming model and proposed a methodology for the adaptation of a Multiobjective Directed Bee Colony Optimization (MODBCO). MODBCO is used successfully for solving the multiobjective problem of optimizing the scheduling problems. This MODBCO is an integration of deterministic local search, multiagent particle system environment, and honey bee decision-making process. The performance of the algorithm is assessed using the standard dataset INRC2010, and it reflects many real-world cases which vary in size and complexity. The experimental analysis uses statistical tools to show the uniqueness of the algorithm on assessment criteria. PMID:28473849

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

The min-conflicts heuristic: Experimental and theoretical results

NASA Technical Reports Server (NTRS)

Minton, Steven; Philips, Andrew B.; Johnston, Mark D.; Laird, Philip

1991-01-01

This paper describes a simple heuristic method for solving large-scale constraint satisfaction and scheduling problems. Given an initial assignment for the variables in a problem, the method operates by searching through the space of possible repairs. The search is guided by an ordering heuristic, the min-conflicts heuristic, that attempts to minimize the number of constraint violations after each step. We demonstrate empirically that the method performs orders of magnitude better than traditional backtracking techniques on certain standard problems. For example, the one million queens problem can be solved rapidly using our approach. We also describe practical scheduling applications where the method has been successfully applied. A theoretical analysis is presented to explain why the method works so well on certain types of problems and to predict when it is likely to be most effective.

Recursive heuristic classification

NASA Technical Reports Server (NTRS)

Wilkins, David C.

1994-01-01

The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

What relates newspaper, definite, and clothing? An article describing deficits in convergent problem solving and creativity following hippocampal damage

PubMed Central

Warren, David E.; Kurczek, Jake; Duff, Melissa C.

2016-01-01

Creativity relies on a diverse set of cognitive processes associated with distinct neural correlates, and one important aspect of creativity, divergent thinking, has been associated with the hippocampus. However, hippocampal contributions to another important aspect of creativity, convergent problem solving, have not been investigated. We tested the necessity of hippocampus for convergent problem solving using a neuropsychological method. Participants with amnesia due to hippocampal damage (N=5) and healthy normal comparison participants (N=5) were tested using a task that promoted solutions based on existing knowledge (Bowden and Jung-Beeman, 2003). During each trial, participants were given a list of three words (e.g., fly, man, place) and asked to respond with a word that could be combined with each of the three words (e.g., fire). The amnesic group produced significantly fewer correct responses than the healthy comparison group. These findings indicate that the hippocampus is necessary for normal convergent problem solving and that changes in the status of the hippocampus should affect convergent problem solving in the context of creative problem-solving across short intervals. This proposed contribution of the hippocampus to convergent problem solving is consistent with an expanded perspective on hippocampal function that acknowledges its role in cognitive processes beyond declarative memory. PMID:27010751

Modifications of the PCPT method for HJB equations

NASA Astrophysics Data System (ADS)

Kossaczký, I.; Ehrhardt, M.; Günther, M.

2016-10-01

In this paper we will revisit the modification of the piecewise constant policy timestepping (PCPT) method for solving Hamilton-Jacobi-Bellman (HJB) equations. This modification is called piecewise predicted policy timestepping (PPPT) method and if properly used, it may be significantly faster. We will quickly recapitulate the algorithms of PCPT, PPPT methods and of the classical implicit method and apply them on a passport option pricing problem with non-standard payoff. We will present modifications needed to solve this problem effectively with the PPPT method and compare the performance with the PCPT method and the classical implicit method.

Implement Method for Automated Testing of Markov Chain Convergence into INVERSE for ORNL12-RS-108J: Advanced Multi-Dimensional Forward and Inverse Modeling

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

Bledsoe, Keith C.

2015-04-01

The DiffeRential Evolution Adaptive Metropolis (DREAM) method is a powerful optimization/uncertainty quantification tool used to solve inverse transport problems in Los Alamos National Laboratory’s INVERSE code system. The DREAM method has been shown to be adept at accurate uncertainty quantification, but it can be very computationally demanding. Previously, the DREAM method in INVERSE performed a user-defined number of particle transport calculations. This placed a burden on the user to guess the number of calculations that would be required to accurately solve any given problem. This report discusses a new approach that has been implemented into INVERSE, the Gelman-Rubin convergence metric.more » This metric automatically detects when an appropriate number of transport calculations have been completed and the uncertainty in the inverse problem has been accurately calculated. In a test problem with a spherical geometry, this method was found to decrease the number of transport calculations (and thus time required) to solve a problem by an average of over 90%. In a cylindrical test geometry, a 75% decrease was obtained.« less

EIT image reconstruction based on a hybrid FE-EFG forward method and the complete-electrode model.

PubMed

Hadinia, M; Jafari, R; Soleimani, M

2016-06-01

This paper presents the application of the hybrid finite element-element free Galerkin (FE-EFG) method for the forward and inverse problems of electrical impedance tomography (EIT). The proposed method is based on the complete electrode model. Finite element (FE) and element-free Galerkin (EFG) methods are accurate numerical techniques. However, the FE technique has meshing task problems and the EFG method is computationally expensive. In this paper, the hybrid FE-EFG method is applied to take both advantages of FE and EFG methods, the complete electrode model of the forward problem is solved, and an iterative regularized Gauss-Newton method is adopted to solve the inverse problem. The proposed method is applied to compute Jacobian in the inverse problem. Utilizing 2D circular homogenous models, the numerical results are validated with analytical and experimental results and the performance of the hybrid FE-EFG method compared with the FE method is illustrated. Results of image reconstruction are presented for a human chest experimental phantom.

Simulation of 2D rarefied gas flows based on the numerical solution of the Boltzmann equation

NASA Astrophysics Data System (ADS)

Poleshkin, Sergey O.; Malkov, Ewgenij A.; Kudryavtsev, Alexey N.; Shershnev, Anton A.; Bondar, Yevgeniy A.; Kohanchik, A. A.

2017-10-01

There are various methods for calculating rarefied gas flows, in particular, statistical methods and deterministic methods based on the finite-difference solutions of the Boltzmann nonlinear kinetic equation and on the solutions of model kinetic equations. There is no universal method; each has its disadvantages in terms of efficiency or accuracy. The choice of the method depends on the problem to be solved and on parameters of calculated flows. Qualitative theoretical arguments help to determine the range of parameters of effectively solved problems for each method; however, it is advisable to perform comparative tests of calculations of the classical problems performed by different methods and with different parameters to have quantitative confirmation of this reasoning. The paper provides the results of the calculations performed by the authors with the help of the Direct Simulation Monte Carlo method and finite-difference methods of solving the Boltzmann equation and model kinetic equations. Based on this comparison, conclusions are made on selecting a particular method for flow simulations in various ranges of flow parameters.

Solving TSP problem with improved genetic algorithm

NASA Astrophysics Data System (ADS)

Fu, Chunhua; Zhang, Lijun; Wang, Xiaojing; Qiao, Liying

2018-05-01

The TSP is a typical NP problem. The optimization of vehicle routing problem (VRP) and city pipeline optimization can use TSP to solve; therefore it is very important to the optimization for solving TSP problem. The genetic algorithm (GA) is one of ideal methods in solving it. The standard genetic algorithm has some limitations. Improving the selection operator of genetic algorithm, and importing elite retention strategy can ensure the select operation of quality, In mutation operation, using the adaptive algorithm selection can improve the quality of search results and variation, after the chromosome evolved one-way evolution reverse operation is added which can make the offspring inherit gene of parental quality improvement opportunities, and improve the ability of searching the optimal solution algorithm.

A New Homotopy Perturbation Scheme for Solving Singular Boundary Value Problems Arising in Various Physical Models

NASA Astrophysics Data System (ADS)

Roul, Pradip; Warbhe, Ujwal

2017-08-01

The classical homotopy perturbation method proposed by J. H. He, Comput. Methods Appl. Mech. Eng. 178, 257 (1999) is useful for obtaining the approximate solutions for a wide class of nonlinear problems in terms of series with easily calculable components. However, in some cases, it has been found that this method results in slowly convergent series. To overcome the shortcoming, we present a new reliable algorithm called the domain decomposition homotopy perturbation method (DDHPM) to solve a class of singular two-point boundary value problems with Neumann and Robin-type boundary conditions arising in various physical models. Five numerical examples are presented to demonstrate the accuracy and applicability of our method, including thermal explosion, oxygen-diffusion in a spherical cell and heat conduction through a solid with heat generation. A comparison is made between the proposed technique and other existing seminumerical or numerical techniques. Numerical results reveal that only two or three iterations lead to high accuracy of the solution and this newly improved technique introduces a powerful improvement for solving nonlinear singular boundary value problems (SBVPs).

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

The neural network approximation method for solving multidimensional nonlinear inverse problems of geophysics

NASA Astrophysics Data System (ADS)

Shimelevich, M. I.; Obornev, E. A.; Obornev, I. E.; Rodionov, E. A.

2017-07-01

The iterative approximation neural network method for solving conditionally well-posed nonlinear inverse problems of geophysics is presented. The method is based on the neural network approximation of the inverse operator. The inverse problem is solved in the class of grid (block) models of the medium on a regularized parameterization grid. The construction principle of this grid relies on using the calculated values of the continuity modulus of the inverse operator and its modifications determining the degree of ambiguity of the solutions. The method provides approximate solutions of inverse problems with the maximal degree of detail given the specified degree of ambiguity with the total number of the sought parameters n × 103 of the medium. The a priori and a posteriori estimates of the degree of ambiguity of the approximated solutions are calculated. The work of the method is illustrated by the example of the three-dimensional (3D) inversion of the synthesized 2D areal geoelectrical (audio magnetotelluric sounding, AMTS) data corresponding to the schematic model of a kimberlite pipe.

Solving of the coefficient inverse problems for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time data

NASA Astrophysics Data System (ADS)

Lukyanenko, D. V.; Shishlenin, M. A.; Volkov, V. T.

2018-01-01

We propose the numerical method for solving coefficient inverse problem for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time observation data based on the asymptotic analysis and the gradient method. Asymptotic analysis allows us to extract a priory information about interior layer (moving front), which appears in the direct problem, and boundary layers, which appear in the conjugate problem. We describe and implement the method of constructing a dynamically adapted mesh based on this a priory information. The dynamically adapted mesh significantly reduces the complexity of the numerical calculations and improve the numerical stability in comparison with the usual approaches. Numerical example shows the effectiveness of the proposed method.

Robust Programming Problems Based on the Mean-Variance Model Including Uncertainty Factors

NASA Astrophysics Data System (ADS)

Hasuike, Takashi; Ishii, Hiroaki

2009-01-01

This paper considers robust programming problems based on the mean-variance model including uncertainty sets and fuzzy factors. Since these problems are not well-defined problems due to fuzzy factors, it is hard to solve them directly. Therefore, introducing chance constraints, fuzzy goals and possibility measures, the proposed models are transformed into the deterministic equivalent problems. Furthermore, in order to solve these equivalent problems efficiently, the solution method is constructed introducing the mean-absolute deviation and doing the equivalent transformations.

The use of Galerkin finite-element methods to solve mass-transport equations

USGS Publications Warehouse

Grove, David B.

1977-01-01

The partial differential equation that describes the transport and reaction of chemical solutes in porous media was solved using the Galerkin finite-element technique. These finite elements were superimposed over finite-difference cells used to solve the flow equation. Both convection and flow due to hydraulic dispersion were considered. Linear and Hermite cubic approximations (basis functions) provided satisfactory results: however, the linear functions were computationally more efficient for two-dimensional problems. Successive over relaxation (SOR) and iteration techniques using Tchebyschef polynomials were used to solve the sparce matrices generated using the linear and Hermite cubic functions, respectively. Comparisons of the finite-element methods to the finite-difference methods, and to analytical results, indicated that a high degree of accuracy may be obtained using the method outlined. The technique was applied to a field problem involving an aquifer contaminated with chloride, tritium, and strontium-90. (Woodard-USGS)

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

Overset meshing coupled with hybridizable discontinuous Galerkin finite elements

DOE PAGES

Kauffman, Justin A.; Sheldon, Jason P.; Miller, Scott T.

2017-03-01

We introduce the use of hybridizable discontinuous Galerkin (HDG) finite element methods on overlapping (overset) meshes. Overset mesh methods are advantageous for solving problems on complex geometrical domains. We also combine geometric flexibility of overset methods with the advantages of HDG methods: arbitrarily high-order accuracy, reduced size of the global discrete problem, and the ability to solve elliptic, parabolic, and/or hyperbolic problems with a unified form of discretization. This approach to developing the ‘overset HDG’ method is to couple the global solution from one mesh to the local solution on the overset mesh. We present numerical examples for steady convection–diffusionmore » and static elasticity problems. The examples demonstrate optimal order convergence in all primal fields for an arbitrary amount of overlap of the underlying meshes.« less

An historical survey of computational methods in optimal control.

NASA Technical Reports Server (NTRS)

Polak, E.

1973-01-01

Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.

A family of conjugate gradient methods for large-scale nonlinear equations.

PubMed

Feng, Dexiang; Sun, Min; Wang, Xueyong

2017-01-01

In this paper, we present a family of conjugate gradient projection methods for solving large-scale nonlinear equations. At each iteration, it needs low storage and the subproblem can be easily solved. Compared with the existing solution methods for solving the problem, its global convergence is established without the restriction of the Lipschitz continuity on the underlying mapping. Preliminary numerical results are reported to show the efficiency of the proposed method.

Connecting Mathematics in Primary Science Inquiry Projects

ERIC Educational Resources Information Center

So, Winnie Wing-mui

2013-01-01

Science as inquiry and mathematics as problem solving are conjoined fraternal twins attached by their similarities but with distinct differences. Inquiry and problem solving are promoted in contemporary science and mathematics education reforms as a critical attribute of the nature of disciplines, teaching methods, and learning outcomes involving…

Assessing Design Activity in Complex CMOS Circuit Design.

ERIC Educational Resources Information Center

Biswas, Gautam; And Others

This report characterizes human problem solving in digital circuit design. Protocols of 11 different designers with varying degrees of training were analyzed by identifying the designers' problem solving strategies and discussing activity patterns that differentiate the designers. These methods are proposed as a tentative basis for assessing…

Computer Software for Intelligent Systems.

ERIC Educational Resources Information Center

Lenat, Douglas B.

1984-01-01

Discusses the development and nature of computer software for intelligent systems, indicating that the key to intelligent problem-solving lies in reducing the random search for solutions. Formal reasoning methods, expert systems, and sources of power in problem-solving are among the areas considered. Specific examples of such software are…

Toward an Understanding of Development of Learning to Solve Ill-Defined Problems in an Online Context: A Multi-Year Qualitative Exploratory Study

ERIC Educational Resources Information Center

Peddibhotla, Naren

2016-01-01

The case study is a classic tool used in several educational programs that emphasizes solving of illdefined problems. Though it has been used in classroom-based teaching and educators have developed a rich repertoire of methods, its use in online courses presents different challenges. To explore factors that develop skills in solving ill-defined…

Use of Concept Profile Analysis to Identify Difficulties in Solving Science Problems.

ERIC Educational Resources Information Center

Gorodetsky, Malka; Hoz, Ron

1980-01-01

Proposed is a new method for analyzing how concepts are used in the process of problem solving in science. Through the use of a "thinking aloud" interview technique, 21 tenth-grade students worked with a problem concerning the boiling point of water at the Dead Sea. Interview protocols were analyzed to develop students' concept profiles.…

Synectics: An Explanation of the Process and Some Comments on its Application in the Secondary School.

ERIC Educational Resources Information Center

Marran, James F.; Rogan, Donald V.

Synectics is a method of creative problem solving through the use of metaphor and apparent irrelevancy developed by William J. J. Gordon. The process involves rational knowledge of the problem to be solved, irrational improvisations that lead to fertile associations creating new approaches to the problem, and euphoric state that is essential in…

W-algebra for solving problems with fuzzy parameters

NASA Astrophysics Data System (ADS)

Shevlyakov, A. O.; Matveev, M. G.

2018-03-01

A method of solving the problems with fuzzy parameters by means of a special algebraic structure is proposed. The structure defines its operations through operations on real numbers, which simplifies its use. It avoids deficiencies limiting applicability of the other known structures. Examples for solution of a quadratic equation, a system of linear equations and a network planning problem are given.

The Effects of Using Diagramming as a Representational Technique on High School Students' Achievement in Solving Math Word Problems

ERIC Educational Resources Information Center

Banerjee, Banmali

2010-01-01

Methods and procedures for successfully solving math word problems have been, and continue to be a mystery to many U.S. high school students. Previous studies suggest that the contextual and mathematical understanding of a word problem, along with the development of schemas and their related external representations, positively contribute to…

Quantum Heterogeneous Computing for Satellite Positioning Optimization

NASA Astrophysics Data System (ADS)

Bass, G.; Kumar, V.; Dulny, J., III

2016-12-01

Hard optimization problems occur in many fields of academic study and practical situations. We present results in which quantum heterogeneous computing is used to solve a real-world optimization problem: satellite positioning. Optimization problems like this can scale very rapidly with problem size, and become unsolvable with traditional brute-force methods. Typically, such problems have been approximately solved with heuristic approaches; however, these methods can take a long time to calculate and are not guaranteed to find optimal solutions. Quantum computing offers the possibility of producing significant speed-up and improved solution quality. There are now commercially available quantum annealing (QA) devices that are designed to solve difficult optimization problems. These devices have 1000+ quantum bits, but they have significant hardware size and connectivity limitations. We present a novel heterogeneous computing stack that combines QA and classical machine learning and allows the use of QA on problems larger than the quantum hardware could solve in isolation. We begin by analyzing the satellite positioning problem with a heuristic solver, the genetic algorithm. The classical computer's comparatively large available memory can explore the full problem space and converge to a solution relatively close to the true optimum. The QA device can then evolve directly to the optimal solution within this more limited space. Preliminary experiments, using the Quantum Monte Carlo (QMC) algorithm to simulate QA hardware, have produced promising results. Working with problem instances with known global minima, we find a solution within 8% in a matter of seconds, and within 5% in a few minutes. Future studies include replacing QMC with commercially available quantum hardware and exploring more problem sets and model parameters. Our results have important implications for how heterogeneous quantum computing can be used to solve difficult optimization problems in any field.

How to Solve Polyhedron Problem?

NASA Astrophysics Data System (ADS)

Wijayanti, A.; Kusumah, Y. S.; Suhendra

2017-09-01

The purpose of this research is to know the possible strategies to solve the problem in polyhedron topic with Knilsey’s Learning Model as scaffolding for the student. This research was conducted by using mixed method with sequential explanatory design. Researchers used purposive sampling technique to get two classes for Knisley class and conventional class and an extreme case sampling technique to get interview data. The instruments used are tests, observation sheets and interview guidelines. The result of the research shows that: (1) students’ strategies to solve polyhedron problem were grouped into two steps: by partitioning the problem to find out the solution and make a mathematical model of the mathematical sentence given and then connect it with the concept that the students already know; (2) students ‘mathematical problem solving ability in Knisley class is higher than those in conventional class.

Solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators.

PubMed

Zhao, Jing; Zong, Haili

2018-01-01

In this paper, we propose parallel and cyclic iterative algorithms for solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators. We also combine the process of cyclic and parallel iterative methods and propose two mixed iterative algorithms. Our several algorithms do not need any prior information about the operator norms. Under mild assumptions, we prove weak convergence of the proposed iterative sequences in Hilbert spaces. As applications, we obtain several iterative algorithms to solve the multiple-set split equality problem.

Solving a real-world problem using an evolving heuristically driven schedule builder.

PubMed

Hart, E; Ross, P; Nelson, J

1998-01-01

This work addresses the real-life scheduling problem of a Scottish company that must produce daily schedules for the catching and transportation of large numbers of live chickens. The problem is complex and highly constrained. We show that it can be successfully solved by division into two subproblems and solving each using a separate genetic algorithm (GA). We address the problem of whether this produces locally optimal solutions and how to overcome this. We extend the traditional approach of evolving a "permutation + schedule builder" by concentrating on evolving the schedule builder itself. This results in a unique schedule builder being built for each daily scheduling problem, each individually tailored to deal with the particular features of that problem. This results in a robust, fast, and flexible system that can cope with most of the circumstances imaginable at the factory. We also compare the performance of a GA approach to several other evolutionary methods and show that population-based methods are superior to both hill-climbing and simulated annealing in the quality of solutions produced. Population-based methods also have the distinct advantage of producing multiple, equally fit solutions, which is of particular importance when considering the practical aspects of the problem.

Counting to 20: Online Implementation of a Face-to-Face, Elementary Mathematics Methods Problem-Solving Activity

ERIC Educational Resources Information Center

Schwartz, Catherine Stein

2012-01-01

This study describes implementation of the same problem-solving activity in both online and face-to-face environments. The activity, done in the first class period or first module of a K-2 mathematics methods course, was initially used in a face-to-face class and then adapted later for use in an online class. While the task was originally designed…

Fortran programs for the time-dependent Gross-Pitaevskii equation in a fully anisotropic trap

NASA Astrophysics Data System (ADS)

Muruganandam, P.; Adhikari, S. K.

2009-10-01

Here we develop simple numerical algorithms for both stationary and non-stationary solutions of the time-dependent Gross-Pitaevskii (GP) equation describing the properties of Bose-Einstein condensates at ultra low temperatures. In particular, we consider algorithms involving real- and imaginary-time propagation based on a split-step Crank-Nicolson method. In a one-space-variable form of the GP equation we consider the one-dimensional, two-dimensional circularly-symmetric, and the three-dimensional spherically-symmetric harmonic-oscillator traps. In the two-space-variable form we consider the GP equation in two-dimensional anisotropic and three-dimensional axially-symmetric traps. The fully-anisotropic three-dimensional GP equation is also considered. Numerical results for the chemical potential and root-mean-square size of stationary states are reported using imaginary-time propagation programs for all the cases and compared with previously obtained results. Also presented are numerical results of non-stationary oscillation for different trap symmetries using real-time propagation programs. A set of convenient working codes developed in Fortran 77 are also provided for all these cases (twelve programs in all). In the case of two or three space variables, Fortran 90/95 versions provide some simplification over the Fortran 77 programs, and these programs are also included (six programs in all). Program summaryProgram title: (i) imagetime1d, (ii) imagetime2d, (iii) imagetime3d, (iv) imagetimecir, (v) imagetimesph, (vi) imagetimeaxial, (vii) realtime1d, (viii) realtime2d, (ix) realtime3d, (x) realtimecir, (xi) realtimesph, (xii) realtimeaxial Catalogue identifier: AEDU_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDU_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 122 907 No. of bytes in distributed program, including test data, etc.: 609 662 Distribution format: tar.gz Programming language: FORTRAN 77 and Fortran 90/95 Computer: PC Operating system: Linux, Unix RAM: 1 GByte (i, iv, v), 2 GByte (ii, vi, vii, x, xi), 4 GByte (iii, viii, xii), 8 GByte (ix) Classification: 2.9, 4.3, 4.12 Nature of problem: These programs are designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in one-, two- or three-space dimensions with a harmonic, circularly-symmetric, spherically-symmetric, axially-symmetric or anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Solution method: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation, in either imaginary or real time, over small time steps. The method yields the solution of stationary and/or non-stationary problems. Additional comments: This package consists of 12 programs, see "Program title", above. FORTRAN77 versions are provided for each of the 12 and, in addition, Fortran 90/95 versions are included for ii, iii, vi, viii, ix, xii. For the particular purpose of each program please see the below. Running time: Minutes on a medium PC (i, iv, v, vii, x, xi), a few hours on a medium PC (ii, vi, viii, xii), days on a medium PC (iii, ix). Program summary (1)Title of program: imagtime1d.F Title of electronic file: imagtime1d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 1 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in one-space dimension with a harmonic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (2)Title of program: imagtimecir.F Title of electronic file: imagtimecir.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 1 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in two-space dimensions with a circularly-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (3)Title of program: imagtimesph.F Title of electronic file: imagtimesph.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 1 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with a spherically-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (4)Title of program: realtime1d.F Title of electronic file: realtime1d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in one-space dimension with a harmonic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (5)Title of program: realtimecir.F Title of electronic file: realtimecir.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in two-space dimensions with a circularly-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (6)Title of program: realtimesph.F Title of electronic file: realtimesph.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 Typical running time: Minutes on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with a spherically-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (7)Title of programs: imagtimeaxial.F and imagtimeaxial.f90 Title of electronic file: imagtimeaxial.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Few hours on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with an axially-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (8)Title of program: imagtime2d.F and imagtime2d.f90 Title of electronic file: imagtime2d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 2 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Few hours on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in two-space dimensions with an anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (9)Title of program: realtimeaxial.F and realtimeaxial.f90 Title of electronic file: realtimeaxial.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 4 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time Hours on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with an axially-symmetric trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (10)Title of program: realtime2d.F and realtime2d.f90 Title of electronic file: realtime2d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 4 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Hours on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in two-space dimensions with an anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems. Program summary (11)Title of program: imagtime3d.F and imagtime3d.f90 Title of electronic file: imagtime3d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum RAM memory: 4 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Few days on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with an anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in imaginary time over small time steps. The method yields the solution of stationary problems. Program summary (12)Title of program: realtime3d.F and realtime3d.f90 Title of electronic file: realtime3d.tar.gz Catalogue identifier: Program summary URL: Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Distribution format: tar.gz Computers: PC/Linux, workstation/UNIX Maximum Ram Memory: 8 GByte Programming language used: Fortran 77 and Fortran 90 Typical running time: Days on a medium PC Unusual features: None Nature of physical problem: This program is designed to solve the time-dependent Gross-Pitaevskii nonlinear partial differential equation in three-space dimensions with an anisotropic trap. The Gross-Pitaevskii equation describes the properties of a dilute trapped Bose-Einstein condensate. Method of solution: The time-dependent Gross-Pitaevskii equation is solved by the split-step Crank-Nicolson method by discretizing in space and time. The discretized equation is then solved by propagation in real time over small time steps. The method yields the solution of stationary and non-stationary problems.

Artificial immune algorithm for multi-depot vehicle scheduling problems

NASA Astrophysics Data System (ADS)

Wu, Zhongyi; Wang, Donggen; Xia, Linyuan; Chen, Xiaoling

2008-10-01

In the fast-developing logistics and supply chain management fields, one of the key problems in the decision support system is that how to arrange, for a lot of customers and suppliers, the supplier-to-customer assignment and produce a detailed supply schedule under a set of constraints. Solutions to the multi-depot vehicle scheduling problems (MDVRP) help in solving this problem in case of transportation applications. The objective of the MDVSP is to minimize the total distance covered by all vehicles, which can be considered as delivery costs or time consumption. The MDVSP is one of nondeterministic polynomial-time hard (NP-hard) problem which cannot be solved to optimality within polynomial bounded computational time. Many different approaches have been developed to tackle MDVSP, such as exact algorithm (EA), one-stage approach (OSA), two-phase heuristic method (TPHM), tabu search algorithm (TSA), genetic algorithm (GA) and hierarchical multiplex structure (HIMS). Most of the methods mentioned above are time consuming and have high risk to result in local optimum. In this paper, a new search algorithm is proposed to solve MDVSP based on Artificial Immune Systems (AIS), which are inspirited by vertebrate immune systems. The proposed AIS algorithm is tested with 30 customers and 6 vehicles located in 3 depots. Experimental results show that the artificial immune system algorithm is an effective and efficient method for solving MDVSP problems.

Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem

NASA Astrophysics Data System (ADS)

Korayem, L.; Khorsid, M.; Kassem, S. S.

2015-05-01

The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.

[The application of new technologies to solving maths problems for students with learning disabilities: the 'underwater school'].

PubMed

Miranda-Casas, A; Marco-Taverner, R; Soriano-Ferrer, M; Melià de Alba, A; Simó-Casañ, P

2008-01-01

Different procedures have demonstrated efficacy to teach cognitive and metacognitive strategies to problem solving in mathematics. Some studies have used computer-based problem solving instructional programs. To analyze in students with learning disabilities the efficacy of a cognitive strategies training for problem solving, with three instructional delivery formats: a teacher-directed program (T-D), a computer-assisted instructional (CAI) program, and a combined program (T-D + CAI). Forty-four children with mathematics learning disabilities, between 8 and 10 years old participated in this study. The children were randomly assigned to one of the three instructional formats and a control group without cognitive strategies training. In the three instructional conditions which were compared all the students learnt problems solving linguistic and visual cognitive strategies trough the self-instructional procedure. Several types of measurements were used for analysing the possible differential efficacy of the three instructional methods implemented: solving problems tests, marks in mathematics, internal achievement responsibility scale, and school behaviours teacher ratings. Our findings show that the T-D training group and the T-D + CAI group improved significantly on math word problem solving and on marks in Maths from pre- to post-testing. In addition, the results indicated that the students of the T-D + CAI group solved more real-life problems and developed more internal attributions compared to both control and CAI groups. Finally, with regard to school behaviours, improvements in school adjustment and learning problems were observed in the students of the group with a combined instructional format (T-D + CAI).

Physical Principle for Generation of Randomness

NASA Technical Reports Server (NTRS)

Zak, Michail

2009-01-01

A physical principle (more precisely, a principle that incorporates mathematical models used in physics) has been conceived as the basis of a method of generating randomness in Monte Carlo simulations. The principle eliminates the need for conventional random-number generators. The Monte Carlo simulation method is among the most powerful computational methods for solving high-dimensional problems in physics, chemistry, economics, and information processing. The Monte Carlo simulation method is especially effective for solving problems in which computational complexity increases exponentially with dimensionality. The main advantage of the Monte Carlo simulation method over other methods is that the demand on computational resources becomes independent of dimensionality. As augmented by the present principle, the Monte Carlo simulation method becomes an even more powerful computational method that is especially useful for solving problems associated with dynamics of fluids, planning, scheduling, and combinatorial optimization. The present principle is based on coupling of dynamical equations with the corresponding Liouville equation. The randomness is generated by non-Lipschitz instability of dynamics triggered and controlled by feedback from the Liouville equation. (In non-Lipschitz dynamics, the derivatives of solutions of the dynamical equations are not required to be bounded.)

ISE: An Integrated Search Environment. The manual

NASA Technical Reports Server (NTRS)

Chu, Lon-Chan

1992-01-01

Integrated Search Environment (ISE), a software package that implements hierarchical searches with meta-control, is described in this manual. ISE is a collection of problem-independent routines to support solving searches. Mainly, these routines are core routines for solving a search problem and they handle the control of searches and maintain the statistics related to searches. By separating the problem-dependent and problem-independent components in ISE, new search methods based on a combination of existing methods can be developed by coding a single master control program. Further, new applications solved by searches can be developed by coding the problem-dependent parts and reusing the problem-independent parts already developed. Potential users of ISE are designers of new application solvers and new search algorithms, and users of experimental application solvers and search algorithms. The ISE is designed to be user-friendly and information rich. In this manual, the organization of ISE is described and several experiments carried out on ISE are also described.

KIPSE1: A Knowledge-based Interactive Problem Solving Environment for data estimation and pattern classification

NASA Technical Reports Server (NTRS)

Han, Chia Yung; Wan, Liqun; Wee, William G.

1990-01-01

A knowledge-based interactive problem solving environment called KIPSE1 is presented. The KIPSE1 is a system built on a commercial expert system shell, the KEE system. This environment gives user capability to carry out exploratory data analysis and pattern classification tasks. A good solution often consists of a sequence of steps with a set of methods used at each step. In KIPSE1, solution is represented in the form of a decision tree and each node of the solution tree represents a partial solution to the problem. Many methodologies are provided at each node to the user such that the user can interactively select the method and data sets to test and subsequently examine the results. Otherwise, users are allowed to make decisions at various stages of problem solving to subdivide the problem into smaller subproblems such that a large problem can be handled and a better solution can be found.

A homotopy method based on WENO schemes for solving steady state problems of hyperbolic conservation laws

DTIC Science & Technology

2012-09-03

prac- tice to solve these initial value problems. Additionally, the predictor / corrector methods are combined with adaptive stepsize and adaptive ...for implementing a numerical path tracking algorithm is to decide which predictor / corrector method to employ, how large to take the step ∆t, and what...the endgame algorithm . Output: A steady state solution Set ǫ = 1 while ǫ >= ǫend do set the stepsize ∆ǫ by using adaptive stepsize control algorithm

An interior-point method-based solver for simulation of aircraft parts riveting

NASA Astrophysics Data System (ADS)

Stefanova, Maria; Yakunin, Sergey; Petukhova, Margarita; Lupuleac, Sergey; Kokkolaras, Michael

2018-05-01

The particularities of the aircraft parts riveting process simulation necessitate the solution of a large amount of contact problems. A primal-dual interior-point method-based solver is proposed for solving such problems efficiently. The proposed method features a worst case polynomial complexity bound ? on the number of iterations, where n is the dimension of the problem and ε is a threshold related to desired accuracy. In practice, the convergence is often faster than this worst case bound, which makes the method applicable to large-scale problems. The computational challenge is solving the system of linear equations because the associated matrix is ill conditioned. To that end, the authors introduce a preconditioner and a strategy for determining effective initial guesses based on the physics of the problem. Numerical results are compared with ones obtained using the Goldfarb-Idnani algorithm. The results demonstrate the efficiency of the proposed method.

An effective pseudospectral method for constraint dynamic optimisation problems with characteristic times

NASA Astrophysics Data System (ADS)

Xiao, Long; Liu, Xinggao; Ma, Liang; Zhang, Zeyin

2018-03-01

Dynamic optimisation problem with characteristic times, widely existing in many areas, is one of the frontiers and hotspots of dynamic optimisation researches. This paper considers a class of dynamic optimisation problems with constraints that depend on the interior points either fixed or variable, where a novel direct pseudospectral method using Legendre-Gauss (LG) collocation points for solving these problems is presented. The formula for the state at the terminal time of each subdomain is derived, which results in a linear combination of the state at the LG points in the subdomains so as to avoid the complex nonlinear integral. The sensitivities of the state at the collocation points with respect to the variable characteristic times are derived to improve the efficiency of the method. Three well-known characteristic time dynamic optimisation problems are solved and compared in detail among the reported literature methods. The research results show the effectiveness of the proposed method.

A Unified Approach for Solving Nonlinear Regular Perturbation Problems

ERIC Educational Resources Information Center

Khuri, S. A.

2008-01-01

This article describes a simple alternative unified method of solving nonlinear regular perturbation problems. The procedure is based upon the manipulation of Taylor's approximation for the expansion of the nonlinear term in the perturbed equation. An essential feature of this technique is the relative simplicity used and the associated unified…

Monte Carlo Simulation for Perusal and Practice.

ERIC Educational Resources Information Center

Brooks, Gordon P.; Barcikowski, Robert S.; Robey, Randall R.

The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…

A Design To Improve Children's Competencies in Solving Mathematical Word Problems.

ERIC Educational Resources Information Center

Zimmerman, Helene

A discrepancy exists between children's ability to compute and their ability to solve mathematical word problems. The literature suggests a variety of methods that have been attempted to improve this skill with varying success. The utilization of manipulatives, visualization, illustration, and emphasis on improving listening skills all were…

A "Hands on" Strategy for Teaching Genetic Algorithms to Undergraduates

ERIC Educational Resources Information Center

Venables, Anne; Tan, Grace

2007-01-01

Genetic algorithms (GAs) are a problem solving strategy that uses stochastic search. Since their introduction (Holland, 1975), GAs have proven to be particularly useful for solving problems that are "intractable" using classical methods. The language of genetic algorithms (GAs) is heavily laced with biological metaphors from evolutionary…

Facilitating Problem Solving in High School Chemistry.

ERIC Educational Resources Information Center

Gabel, Dorothy L.

The major purpose of this study was to determine whether certain types of instructional strategies (factor-label method, use of analogies, use of diagrams, and proportionality) were superior to others in teaching problem solving in four topics (mole concept, gas laws, stoichiometry, and molarity). Also of major interest was whether particular…

Productive Failure in STEM Education

ERIC Educational Resources Information Center

Trueman, Rebecca J.

2014-01-01

Science education is criticized because it often fails to support problem-solving skills in students. Instead, the instructional methods primarily emphasize didactic models that fail to engage students and reveal how the material can be applied to solve real problems. To overcome these limitations, this study asked participants in a general…

Group Discussions in the Chemistry Classroom and the Problem-Solving Skills of Students.

ERIC Educational Resources Information Center

Fasching, James L.; Erickson, Bette LaSere

1985-01-01

Five years ago, an introductory chemistry course for chemists and chemical engineers was redesigned to stress the scientific method, problem-solving, and reasoning skills. Describes: (1) changes made in the course; (2) impacts on student achievement; and (3) student ratings of the course. (JN)

Problem-Solving Therapy for Depression in Adults: A Systematic Review

ERIC Educational Resources Information Center

Gellis, Zvi D.; Kenaley, Bonnie

2008-01-01

Objectives: This article presents a systematic review of the evidence on problem-solving therapy (PST) for depressive disorders in noninstitutionalized adults. Method: Intervention studies using randomized controlled designs are included and methodological quality is assessed using a standard set of criteria from the Cochrane Collaborative Review…

Graph cuts via l1 norm minimization.

PubMed

Bhusnurmath, Arvind; Taylor, Camillo J

2008-10-01

Graph cuts have become an increasingly important tool for solving a number of energy minimization problems in computer vision and other fields. In this paper, the graph cut problem is reformulated as an unconstrained l1 norm minimization that can be solved effectively using interior point methods. This reformulation exposes connections between the graph cuts and other related continuous optimization problems. Eventually the problem is reduced to solving a sequence of sparse linear systems involving the Laplacian of the underlying graph. The proposed procedure exploits the structure of these linear systems in a manner that is easily amenable to parallel implementations. Experimental results obtained by applying the procedure to graphs derived from image processing problems are provided.

An exact algorithm for optimal MAE stack filter design.

PubMed

Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior

2007-02-01

We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.

Numerical solution of the electron transport equation

NASA Astrophysics Data System (ADS)

Woods, Mark

The electron transport equation has been solved many times for a variety of reasons. The main difficulty in its numerical solution is that it is a very stiff boundary value problem. The most common numerical methods for solving boundary value problems are symmetric collocation methods and shooting methods. Both of these types of methods can only be applied to the electron transport equation if the boundary conditions are altered with unrealistic assumptions because they require too many points to be practical. Further, they result in oscillating and negative solutions, which are physically meaningless for the problem at hand. For these reasons, all numerical methods for this problem to date are a bit unusual because they were designed to try and avoid the problem of extreme stiffness. This dissertation shows that there is no need to introduce spurious boundary conditions or invent other numerical methods for the electron transport equation. Rather, there already exists methods for very stiff boundary value problems within the numerical analysis literature. We demonstrate one such method in which the fast and slow modes of the boundary value problem are essentially decoupled. This allows for an upwind finite difference method to be applied to each mode as is appropriate. This greatly reduces the number of points needed in the mesh, and we demonstrate how this eliminates the need to define new boundary conditions. This method is verified by showing that under certain restrictive assumptions, the electron transport equation has an exact solution that can be written as an integral. We show that the solution from the upwind method agrees with the quadrature evaluation of the exact solution. This serves to verify that the upwind method is properly solving the electron transport equation. Further, it is demonstrated that the output of the upwind method can be used to compute auroral light emissions.

Effect of training problem-solving skill on decision-making and critical thinking of personnel at medical emergencies

PubMed Central

Heidari, Mohammad; Shahbazi, Sara

2016-01-01

Background: The aim of this study was to determine the effect of problem-solving training on decision-making skill and critical thinking in emergency medical personnel. Materials and Methods: This study is an experimental study that performed in 95 emergency medical personnel in two groups of control (48) and experimental (47). Then, a short problem-solving course based on 8 sessions of 2 h during the term, was performed for the experimental group. Of data gathering was used demographic and researcher made decision-making and California critical thinking skills questionnaires. Data were analyzed using SPSS software. Results: The finding revealed that decision-making and critical thinking score in emergency medical personnel are low and problem-solving course, positively affected the personnel’ decision-making skill and critical thinking after the educational program (P < 0.05). Conclusions: Therefore, this kind of education on problem-solving in various emergency medicine domains such as education, research, and management, is recommended. PMID:28149823

The profile of problem-solving ability of students of distance education in science learning

NASA Astrophysics Data System (ADS)

Widiasih; Permanasari, A.; Riandi; Damayanti, T.

2018-05-01

This study aims to analyze the students' problem-solving ability in science learning and lesson-planning ability. The method used is descriptive-quantitative. The subjects of the study were undergraduate students of Distance Higher Education located in Serang, majoring in Primary Teacher Education in-service training. Samples were taken thoroughly from 2 groups taking the course of Science Learning in Primary School in the first term of 2017, amounted to 39 students. The technique of data collection used is essay test of problem solving from case study done at the beginning of lecture in February 2017. The results of this research can be concluded that In-service Training of Primary School Teacher Education Program are categorized as quite capable (score 66) in solving science learning problem and planning science lesson. Therefore, efforts need to be done to improve the ability of students in problem solving, for instance through online tutorials with the basis of interactive discussions.

Assessment of students' critical-thinking and problem-solving abilities across a 6-year doctor of pharmacy program.

PubMed

Gleason, Brenda L; Gaebelein, Claude J; Grice, Gloria R; Crannage, Andrew J; Weck, Margaret A; Hurd, Peter; Walter, Brenda; Duncan, Wendy

2013-10-14

To determine the feasibility of using a validated set of assessment rubrics to assess students' critical-thinking and problem-solving abilities across a doctor of pharmacy (PharmD) curriculum. Trained faculty assessors used validated rubrics to assess student work samples for critical-thinking and problem-solving abilities. Assessment scores were collected and analyzed to determine student achievement of these 2 ability outcomes across the curriculum. Feasibility of the process was evaluated in terms of time and resources used. One hundred sixty-one samples were assessed for critical thinking, and 159 samples were assessed for problem-solving. Rubric scoring allowed assessors to evaluate four 5- to 7-page work samples per hour. The analysis indicated that overall critical-thinking scores improved over the curriculum. Although low yield for problem-solving samples precluded meaningful data analysis, it was informative for identifying potentially needed curricular improvements. Use of assessment rubrics for program ability outcomes was deemed authentic and feasible. Problem-solving was identified as a curricular area that may need improving. This assessment method has great potential to inform continuous quality improvement of a PharmD program.

Planning and problem-solving training for patients with schizophrenia: a randomized controlled trial

PubMed Central

2011-01-01

Background The purpose of this study was to assess whether planning and problem-solving training is more effective in improving functional capacity in patients with schizophrenia than a training program addressing basic cognitive functions. Methods Eighty-nine patients with schizophrenia were randomly assigned either to a computer assisted training of planning and problem-solving or a training of basic cognition. Outcome variables included planning and problem-solving ability as well as functional capacity, which represents a proxy measure for functional outcome. Results Planning and problem-solving training improved one measure of planning and problem-solving more strongly than basic cognition training, while two other measures of planning did not show a differential effect. Participants in both groups improved over time in functional capacity. There was no differential effect of the interventions on functional capacity. Conclusion A differential effect of targeting specific cognitive functions on functional capacity could not be established. Small differences on cognitive outcome variables indicate a potential for differential effects. This will have to be addressed in further research including longer treatment programs and other settings. Trial registration ClinicalTrials.gov NCT00507988 PMID:21527028

A dual method for optimal control problems with initial and final boundary constraints.

NASA Technical Reports Server (NTRS)

Pironneau, O.; Polak, E.

1973-01-01

This paper presents two new algorithms belonging to the family of dual methods of centers. The first can be used for solving fixed time optimal control problems with inequality constraints on the initial and terminal states. The second one can be used for solving fixed time optimal control problems with inequality constraints on the initial and terminal states and with affine instantaneous inequality constraints on the control. Convergence is established for both algorithms. Qualitative reasoning indicates that the rate of convergence is linear.

Improved Quasi-Newton method via PSB update for solving systems of nonlinear equations

NASA Astrophysics Data System (ADS)

Mamat, Mustafa; Dauda, M. K.; Waziri, M. Y.; Ahmad, Fadhilah; Mohamad, Fatma Susilawati

2016-10-01

The Newton method has some shortcomings which includes computation of the Jacobian matrix which may be difficult or even impossible to compute and solving the Newton system in every iteration. Also, the common setback with some quasi-Newton methods is that they need to compute and store an n × n matrix at each iteration, this is computationally costly for large scale problems. To overcome such drawbacks, an improved Method for solving systems of nonlinear equations via PSB (Powell-Symmetric-Broyden) update is proposed. In the proposed method, the approximate Jacobian inverse Hk of PSB is updated and its efficiency has improved thereby require low memory storage, hence the main aim of this paper. The preliminary numerical results show that the proposed method is practically efficient when applied on some benchmark problems.

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.

A new extrapolation cascadic multigrid method for three dimensional elliptic boundary value problems

NASA Astrophysics Data System (ADS)

Pan, Kejia; He, Dongdong; Hu, Hongling; Ren, Zhengyong

2017-09-01

In this paper, we develop a new extrapolation cascadic multigrid method, which makes it possible to solve three dimensional elliptic boundary value problems with over 100 million unknowns on a desktop computer in half a minute. First, by combining Richardson extrapolation and quadratic finite element (FE) interpolation for the numerical solutions on two-level of grids (current and previous grids), we provide a quite good initial guess for the iterative solution on the next finer grid, which is a third-order approximation to the FE solution. And the resulting large linear system from the FE discretization is then solved by the Jacobi-preconditioned conjugate gradient (JCG) method with the obtained initial guess. Additionally, instead of performing a fixed number of iterations as used in existing cascadic multigrid methods, a relative residual tolerance is introduced in the JCG solver, which enables us to obtain conveniently the numerical solution with the desired accuracy. Moreover, a simple method based on the midpoint extrapolation formula is proposed to achieve higher-order accuracy on the finest grid cheaply and directly. Test results from four examples including two smooth problems with both constant and variable coefficients, an H3-regular problem as well as an anisotropic problem are reported to show that the proposed method has much better efficiency compared to the classical V-cycle and W-cycle multigrid methods. Finally, we present the reason why our method is highly efficient for solving these elliptic problems.

[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.

A new Euler scheme based on harmonic-polygon approach for solving first order ordinary differential equation

NASA Astrophysics Data System (ADS)

Yusop, Nurhafizah Moziyana Mohd; Hasan, Mohammad Khatim; Wook, Muslihah; Amran, Mohd Fahmi Mohamad; Ahmad, Siti Rohaidah

2017-10-01

There are many benefits to improve Euler scheme for solving the Ordinary Differential Equation Problems. Among the benefits are simple implementation and low-cost computational. However, the problem of accuracy in Euler scheme persuade scholar to use complex method. Therefore, the main purpose of this research are show the construction a new modified Euler scheme that improve accuracy of Polygon scheme in various step size. The implementing of new scheme are used Polygon scheme and Harmonic mean concept that called as Harmonic-Polygon scheme. This Harmonic-Polygon can provide new advantages that Euler scheme could offer by solving Ordinary Differential Equation problem. Four set of problems are solved via Harmonic-Polygon. Findings show that new scheme or Harmonic-Polygon scheme can produce much better accuracy result.

Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.

PubMed

DiMaio, Frank

2017-01-01

Molecular replacement (MR), a method for solving the crystallographic phase problem using phases derived from a model of the target structure, has proven extremely valuable, accounting for the vast majority of structures solved by X-ray crystallography. However, when the resolution of data is low, or the starting model is very dissimilar to the target protein, solving structures via molecular replacement may be very challenging. In recent years, protein structure prediction methodology has emerged as a powerful tool in model building and model refinement for difficult molecular replacement problems. This chapter describes some of the tools available in Rosetta for model building and model refinement specifically geared toward difficult molecular replacement cases.

Providing Adaptation and Guidance for Design Learning by Problem Solving: The Design Planning Approach in DomoSim-TPC Environment

ERIC Educational Resources Information Center

Redondo, Miguel A.; Bravo, Crescencio; Ortega, Manuel; Verdejo, M. Felisa

2007-01-01

Experimental learning environments based on simulation usually require monitoring and adaptation to the actions the users carry out. Some systems provide this functionality, but they do so in a way which is static or cannot be applied to problem solving tasks. In response to this problem, we propose a method based on the use of intermediate…

Assessing the Effectiveness of STAD Model and Problem Based Learning in Mathematics Learning Achievement and Problem Solving Ability

ERIC Educational Resources Information Center

Rattanatumma, Tawachai; Puncreobutr, Vichian

2016-01-01

The objective of this study was to compare the effectiveness of teaching methods in improving Mathematics Learning Achievement and Problem solving ability of students at an international college. This is a Quasi-Experimental Research which was done the study with the first year students who have registered to study Mathematics subject at St.…

Group training in interpersonal problem-solving skills for workplace adaptation of adolescents and adults with Asperger syndrome: a preliminary study.

PubMed

Bonete, Saray; Calero, María Dolores; Fernández-Parra, Antonio

2015-05-01

Adults with Asperger syndrome show persistent difficulties in social situations which psychosocial treatments may address. Despite the multiple studies focusing on social skills interventions, only some have focused specifically on problem-solving skills and have not targeted workplace adaptation training in the adult population. This study describes preliminary data from a group format manual-based intervention, the Interpersonal Problem-Solving for Workplace Adaptation Programme, aimed at improving the cognitive and metacognitive process of social problem-solving skills focusing on typical social situations in the workplace based on mediation as the main strategy. A total of 50 adults with Asperger syndrome received the programme and were compared with a control group of typical development. The feasibility and effectiveness of the treatment were explored. Participants were assessed at pre-treatment and post-treatment on a task of social problem-solving skills and two secondary measures of socialisation and work profile using self- and caregiver-report. Using a variety of methods, the results showed that scores were significantly higher at post-treatment in the social problem-solving task and socialisation skills based on reports by parents. Differences in comparison to the control group had decreased after treatment. The treatment was acceptable to families and subject adherence was high. The Interpersonal Problem-Solving for Workplace Adaptation Programme appears to be a feasible training programme. © The Author(s) 2014.

Development and Validation of the Diabetes Adolescent Problem Solving Questionnaire

PubMed Central

Mulvaney, Shelagh A.; Jaser, Sarah S.; Rothman, Russell L.; Russell, William; Pittel, Eric J.; Lybarger, Cindy; Wallston, Kenneth A.

2014-01-01

Objective Problem solving is a critical diabetes self-management skill. Because of a lack of clinically feasible measures, our aim was to develop and validate a self-report self-management problem solving questionnaire for adolescents with type 1 diabetes (T1D). Methods A multidisciplinary team of diabetes experts generated questionnaire items that addressed diabetes self-management problem solving. Iterative feedback from parents and adolescents resulted in 27 items. Adolescents from two studies (N=156) aged 13–17 were recruited through a pediatric diabetes clinic and completed measures through an online survey. Glycemic control was measured by HbA1c recorded in the medical record. Results Empirical elimination of items using Principal Components Analyses resulted in a 13-item unidimensional measure, the Diabetes Adolescent Problem Solving Questionnaire (DAPSQ) that explained 57% of the variance. The DAPSQ demonstrated internal consistency (Cronbach’s alpha = 0.92) and was correlated with diabetes self-management (r=0.53, p<.001), self-efficacy (r=0.54, p<.001), and glycemic control (r= −0.24, p<.01). Conclusion The DAPSQ is a brief instrument for assessment of diabetes self-management problem solving in youth with T1D associated with better self-management behaviors and glycemic control. Practice Implications The DAPSQ is a clinically feasible self-report measure that can provide valuable information regarding level of self-management problem solving and guide patient education. PMID:25063715

What relates newspaper, definite, and clothing? An article describing deficits in convergent problem solving and creativity following hippocampal damage.

PubMed

Warren, David E; Kurczek, Jake; Duff, Melissa C

2016-07-01

Creativity relies on a diverse set of cognitive processes associated with distinct neural correlates, and one important aspect of creativity, divergent thinking, has been associated with the hippocampus. However, hippocampal contributions to another important aspect of creativity, convergent problem solving, have not been investigated. We tested the necessity of hippocampus for convergent problem solving using a neuropsychological method. Participants with amnesia due to hippocampal damage (N = 5) and healthy normal comparison participants (N = 5) were tested using a task that promoted solutions based on existing knowledge (Bowden and Jung-Beeman, 2003). During each trial, participants were given a list of three words (e.g., fly, man, place) and asked to respond with a word that could be combined with each of the three words (e.g., fire). The amnesic group produced significantly fewer correct responses than the healthy comparison group. These findings indicate that the hippocampus is necessary for normal convergent problem solving and that changes in the status of the hippocampus should affect convergent problem solving in the context of creative problem-solving across short intervals. This proposed contribution of the hippocampus to convergent problem solving is consistent with an expanded perspective on hippocampal function that acknowledges its role in cognitive processes beyond declarative memory. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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

Computation of Pressurized Gas Bearings Using CE/SE Method

NASA Technical Reports Server (NTRS)

Cioc, Sorin; Dimofte, Florin; Keith, Theo G., Jr.; Fleming, David P.

2003-01-01

The space-time conservation element and solution element (CE/SE) method is extended to compute compressible viscous flows in pressurized thin fluid films. This numerical scheme has previously been used successfully to solve a wide variety of compressible flow problems, including flows with large and small discontinuities. In this paper, the method is applied to calculate the pressure distribution in a hybrid gas journal bearing. The formulation of the problem is presented, including the modeling of the feeding system. the numerical results obtained are compared with experimental data. Good agreement between the computed results and the test data were obtained, and thus validate the CE/SE method to solve such problems.

Proportional Topology Optimization: A New Non-Sensitivity Method for Solving Stress Constrained and Minimum Compliance Problems and Its Implementation in MATLAB

PubMed Central

Biyikli, Emre; To, Albert C.

2015-01-01

A new topology optimization method called the Proportional Topology Optimization (PTO) is presented. As a non-sensitivity method, PTO is simple to understand, easy to implement, and is also efficient and accurate at the same time. It is implemented into two MATLAB programs to solve the stress constrained and minimum compliance problems. Descriptions of the algorithm and computer programs are provided in detail. The method is applied to solve three numerical examples for both types of problems. The method shows comparable efficiency and accuracy with an existing optimality criteria method which computes sensitivities. Also, the PTO stress constrained algorithm and minimum compliance algorithm are compared by feeding output from one algorithm to the other in an alternative manner, where the former yields lower maximum stress and volume fraction but higher compliance compared to the latter. Advantages and disadvantages of the proposed method and future works are discussed. The computer programs are self-contained and publicly shared in the website www.ptomethod.org. PMID:26678849

Computational alternatives to obtain time optimal jet engine control. M.S. Thesis

NASA Technical Reports Server (NTRS)

Basso, R. J.; Leake, R. J.

1976-01-01

Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.

Classical versus Computer Algebra Methods in Elementary Geometry

ERIC Educational Resources Information Center

Pech, Pavel

2005-01-01

Computer algebra methods based on results of commutative algebra like Groebner bases of ideals and elimination of variables make it possible to solve complex, elementary and non elementary problems of geometry, which are difficult to solve using a classical approach. Computer algebra methods permit the proof of geometric theorems, automatic…

Multigrid method for stability problems

NASA Technical Reports Server (NTRS)

Taasan, Shlomo

1988-01-01

The problem of calculating the stability of steady state solutions of differential equations is treated. Leading eigenvalues (i.e., having maximal real part) of large matrices that arise from discretization are to be calculated. An efficient multigrid method for solving these problems is presented. The method begins by obtaining an initial approximation for the dominant subspace on a coarse level using a damped Jacobi relaxation. This proceeds until enough accuracy for the dominant subspace has been obtained. The resulting grid functions are then used as an initial approximation for appropriate eigenvalue problems. These problems are being solved first on coarse levels, followed by refinement until a desired accuracy for the eigenvalues has been achieved. The method employs local relaxation on all levels together with a global change on the coarsest level only, which is designed to separate the different eigenfunctions as well as to update their corresponding eigenvalues. Coarsening is done using the FAS formulation in a non-standard way in which the right hand side of the coarse grid equations involves unknown parameters to be solved for on the coarse grid. This in particular leads to a new multigrid method for calculating the eigenvalues of symmetric problems. Numerical experiments with a model problem demonstrate the effectiveness of the method proposed. Using an FMG algorithm a solution to the level of discretization errors is obtained in just a few work units (less than 10), where a work unit is the work involved in one Jacobi relization on the finest level.

An accelerated lambda iteration method for multilevel radiative transfer. I - Non-overlapping lines with background continuum

NASA Technical Reports Server (NTRS)

Rybicki, G. B.; Hummer, D. G.

1991-01-01

A method is presented for solving multilevel transfer problems when nonoverlapping lines and background continuum are present and active continuum transfer is absent. An approximate lambda operator is employed to derive linear, 'preconditioned', statistical-equilibrium equations. A method is described for finding the diagonal elements of the 'true' numerical lambda operator, and therefore for obtaining the coefficients of the equations. Iterations of the preconditioned equations, in conjunction with the transfer equation's formal solution, are used to solve linear equations. Some multilevel problems are considered, including an eleven-level neutral helium atom. Diagonal and tridiagonal approximate lambda operators are utilized in the problems to examine the convergence properties of the method, and it is found to be effective for the line transfer problems.

P1 Nonconforming Finite Element Method for the Solution of Radiation Transport Problems

NASA Technical Reports Server (NTRS)

Kang, Kab S.

2002-01-01

The simulation of radiation transport in the optically thick flux-limited diffusion regime has been identified as one of the most time-consuming tasks within large simulation codes. Due to multimaterial complex geometry, the radiation transport system must often be solved on unstructured grids. In this paper, we investigate the behavior and the benefits of the unstructured P(sub 1) nonconforming finite element method, which has proven to be flexible and effective on related transport problems, in solving unsteady implicit nonlinear radiation diffusion problems using Newton and Picard linearization methods. Key words. nonconforrning finite elements, radiation transport, inexact Newton linearization, multigrid preconditioning

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.

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 globally convergent LCL method for nonlinear optimization.

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

Friedlander, M. P.; Saunders, M. A.; Mathematics and Computer Science

2005-01-01

For optimization problems with nonlinear constraints, linearly constrained Lagrangian (LCL) methods solve a sequence of subproblems of the form 'minimize an augmented Lagrangian function subject to linearized constraints.' Such methods converge rapidly near a solution but may not be reliable from arbitrary starting points. Nevertheless, the well-known software package MINOS has proved effective on many large problems. Its success motivates us to derive a related LCL algorithm that possesses three important properties: it is globally convergent, the subproblem constraints are always feasible, and the subproblems may be solved inexactly. The new algorithm has been implemented in Matlab, with an optionmore » to use either MINOS or SNOPT (Fortran codes) to solve the linearly constrained subproblems. Only first derivatives are required. We present numerical results on a subset of the COPS, HS, and CUTE test problems, which include many large examples. The results demonstrate the robustness and efficiency of the stabilized LCL procedure.« less

Teaching genetics using hands-on models, problem solving, and inquiry-based methods

NASA Astrophysics Data System (ADS)

Hoppe, Stephanie Ann

Teaching genetics can be challenging because of the difficulty of the content and misconceptions students might hold. This thesis focused on using hands-on model activities, problem solving, and inquiry-based teaching/learning methods in order to increase student understanding in an introductory biology class in the area of genetics. Various activities using these three methods were implemented into the classes to address any misconceptions and increase student learning of the difficult concepts. The activities that were implemented were shown to be successful based on pre-post assessment score comparison. The students were assessed on the subjects of inheritance patterns, meiosis, and protein synthesis and demonstrated growth in all of the areas. It was found that hands-on models, problem solving, and inquiry-based activities were more successful in learning concepts in genetics and the students were more engaged than tradition styles of lecture.

Rate and power efficient image compressed sensing and transmission

NASA Astrophysics Data System (ADS)

Olanigan, Saheed; Cao, Lei; Viswanathan, Ramanarayanan

2016-01-01

This paper presents a suboptimal quantization and transmission scheme for multiscale block-based compressed sensing images over wireless channels. The proposed method includes two stages: dealing with quantization distortion and transmission errors. First, given the total transmission bit rate, the optimal number of quantization bits is assigned to the sensed measurements in different wavelet sub-bands so that the total quantization distortion is minimized. Second, given the total transmission power, the energy is allocated to different quantization bit layers based on their different error sensitivities. The method of Lagrange multipliers with Karush-Kuhn-Tucker conditions is used to solve both optimization problems, for which the first problem can be solved with relaxation and the second problem can be solved completely. The effectiveness of the scheme is illustrated through simulation results, which have shown up to 10 dB improvement over the method without the rate and power optimization in medium and low signal-to-noise ratio cases.

Theory and computation of optimal low- and medium-thrust transfers

NASA Technical Reports Server (NTRS)

Chuang, C.-H.

1994-01-01

This report describes the current state of development of methods for calculating optimal orbital transfers with large numbers of burns. Reported on first is the homotopy-motivated and so-called direction correction method. So far this method has been partially tested with one solver; the final step has yet to be implemented. Second is the patched transfer method. This method is rooted in some simplifying approximations made on the original optimal control problem. The transfer is broken up into single-burn segments, each single-burn solved as a predictor step and the whole problem then solved with a corrector step.

The Relationship of Social Problem-Solving Skills and Dysfunctional Attitudes with Risk of Drug Abuse among Dormitory Students at Isfahan University of Medical Sciences.

PubMed

Nasrazadani, Ehteram; Maghsoudi, Jahangir; Mahrabi, Tayebeh

2017-01-01

Dormitory students encounter multiple social factors which cause pressure, such as new social relationships, fear of the future, and separation from family, which could cause serious problems such as tendency toward drug abuse. This research was conducted with the goal to determine social problem-solving skills, dysfunctional attitudes, and risk of drug abuse among dormitory students of Isfahan University of Medical Sciences, Iran. This was a descriptive-analytical, correlational, and cross-sectional research. The research sample consisted of 211 students living in dormitories. The participants were selected using randomized quota sampling method. The data collection tools included the Social Problem-Solving Inventory (SPSI), Dysfunctional Attitude Scale (DAS), and Identifying People at Risk of Addiction Questionnaire. The results indicated an inverse relationship between social problem-solving skills and risk of drug abuse ( P = 0.0002), a direct relationship between dysfunctional attitude and risk of drug abuse ( P = 0.030), and an inverse relationship between social problem-solving skills and dysfunctional attitude among students ( P = 0.0004). Social problem-solving skills have a correlation with dysfunctional attitudes. As a result, teaching these skills and the way to create efficient attitudes should be considered in dormitory students.

Nuclear reactor transient analysis via a quasi-static kinetics Monte Carlo method

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

Jo, YuGwon; Cho, Bumhee; Cho, Nam Zin, E-mail: nzcho@kaist.ac.kr

2015-12-31

The predictor-corrector quasi-static (PCQS) method is applied to the Monte Carlo (MC) calculation for reactor transient analysis. To solve the transient fixed-source problem of the PCQS method, fission source iteration is used and a linear approximation of fission source distributions during a macro-time step is introduced to provide delayed neutron source. The conventional particle-tracking procedure is modified to solve the transient fixed-source problem via MC calculation. The PCQS method with MC calculation is compared with the direct time-dependent method of characteristics (MOC) on a TWIGL two-group problem for verification of the computer code. Then, the results on a continuous-energy problemmore » are presented.« less

Development of parallel algorithms for electrical power management in space applications

NASA Technical Reports Server (NTRS)

Berry, Frederick C.

1989-01-01

The application of parallel techniques for electrical power system analysis is discussed. The Newton-Raphson method of load flow analysis was used along with the decomposition-coordination technique to perform load flow analysis. The decomposition-coordination technique enables tasks to be performed in parallel by partitioning the electrical power system into independent local problems. Each independent local problem represents a portion of the total electrical power system on which a loan flow analysis can be performed. The load flow analysis is performed on these partitioned elements by using the Newton-Raphson load flow method. These independent local problems will produce results for voltage and power which can then be passed to the coordinator portion of the solution procedure. The coordinator problem uses the results of the local problems to determine if any correction is needed on the local problems. The coordinator problem is also solved by an iterative method much like the local problem. The iterative method for the coordination problem will also be the Newton-Raphson method. Therefore, each iteration at the coordination level will result in new values for the local problems. The local problems will have to be solved again along with the coordinator problem until some convergence conditions are met.

Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention

PubMed Central

Fisher, Brian; Smith, Jennifer; Pike, Ian

2017-01-01

Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods: Inspired by the Delphi method, we introduced a novel methodology—group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders’ observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results: The GA methodology triggered the emergence of ‘common ground’ among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders’ verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusions: Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ‘common ground’ among diverse stakeholders about health data and their implications. PMID:28895928

Efficient operator splitting algorithm for joint sparsity-regularized SPIRiT-based parallel MR imaging reconstruction.

PubMed

Duan, Jizhong; Liu, Yu; Jing, Peiguang

2018-02-01

Self-consistent parallel imaging (SPIRiT) is an auto-calibrating model for the reconstruction of parallel magnetic resonance imaging, which can be formulated as a regularized SPIRiT problem. The Projection Over Convex Sets (POCS) method was used to solve the formulated regularized SPIRiT problem. However, the quality of the reconstructed image still needs to be improved. Though methods such as NonLinear Conjugate Gradients (NLCG) can achieve higher spatial resolution, these methods always demand very complex computation and converge slowly. In this paper, we propose a new algorithm to solve the formulated Cartesian SPIRiT problem with the JTV and JL1 regularization terms. The proposed algorithm uses the operator splitting (OS) technique to decompose the problem into a gradient problem and a denoising problem with two regularization terms, which is solved by our proposed split Bregman based denoising algorithm, and adopts the Barzilai and Borwein method to update step size. Simulation experiments on two in vivo data sets demonstrate that the proposed algorithm is 1.3 times faster than ADMM for datasets with 8 channels. Especially, our proposal is 2 times faster than ADMM for the dataset with 32 channels. Copyright © 2017 Elsevier Inc. All rights reserved.

Collaborative Visual Analytics: A Health Analytics Approach to Injury Prevention.

PubMed

Al-Hajj, Samar; Fisher, Brian; Smith, Jennifer; Pike, Ian

2017-09-12

Background : Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods : Inspired by the Delphi method, we introduced a novel methodology-group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders' observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results : The GA methodology triggered the emergence of ' common g round ' among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders' verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusion s : Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ' common ground' among diverse stakeholders about health data and their implications.

A study of fuzzy logic ensemble system performance on face recognition problem

NASA Astrophysics Data System (ADS)

Polyakova, A.; Lipinskiy, L.

2017-02-01

Some problems are difficult to solve by using a single intelligent information technology (IIT). The ensemble of the various data mining (DM) techniques is a set of models which are able to solve the problem by itself, but the combination of which allows increasing the efficiency of the system as a whole. Using the IIT ensembles can improve the reliability and efficiency of the final decision, since it emphasizes on the diversity of its components. The new method of the intellectual informational technology ensemble design is considered in this paper. It is based on the fuzzy logic and is designed to solve the classification and regression problems. The ensemble consists of several data mining algorithms: artificial neural network, support vector machine and decision trees. These algorithms and their ensemble have been tested by solving the face recognition problems. Principal components analysis (PCA) is used for feature selection.

Sparse time-frequency decomposition based on dictionary adaptation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions. © 2016 The Author(s).

A two-level stochastic collocation method for semilinear elliptic equations with random coefficients

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

Chen, Luoping; Zheng, Bin; Lin, Guang

In this work, we propose a novel two-level discretization for solving semilinear elliptic equations with random coefficients. Motivated by the two-grid method for deterministic partial differential equations (PDEs) introduced by Xu, our two-level stochastic collocation method utilizes a two-grid finite element discretization in the physical space and a two-level collocation method in the random domain. In particular, we solve semilinear equations on a coarse meshmore » $$\\mathcal{T}_H$$ with a low level stochastic collocation (corresponding to the polynomial space $$\\mathcal{P}_{P}$$) and solve linearized equations on a fine mesh $$\\mathcal{T}_h$$ using high level stochastic collocation (corresponding to the polynomial space $$\\mathcal{P}_p$$). We prove that the approximated solution obtained from this method achieves the same order of accuracy as that from solving the original semilinear problem directly by stochastic collocation method with $$\\mathcal{T}_h$$ and $$\\mathcal{P}_p$$. The two-level method is computationally more efficient, especially for nonlinear problems with high random dimensions. Numerical experiments are also provided to verify the theoretical results.« less

Application of the perturbation iteration method to boundary layer type problems.

PubMed

Pakdemirli, Mehmet

2016-01-01

The recently developed perturbation iteration method is applied to boundary layer type singular problems for the first time. As a preliminary work on the topic, the simplest algorithm of PIA(1,1) is employed in the calculations. Linear and nonlinear problems are solved to outline the basic ideas of the new solution technique. The inner and outer solutions are determined with the iteration algorithm and matched to construct a composite expansion valid within all parts of the domain. The solutions are contrasted with the available exact or numerical solutions. It is shown that the perturbation-iteration algorithm can be effectively used for solving boundary layer type problems.

Efficient numerical method for solving Cauchy problem for the Gamma equation

NASA Astrophysics Data System (ADS)

Koleva, Miglena N.

2011-12-01

In this work we consider Cauchy problem for the so called Gamma equation, derived by transforming the fully nonlinear Black-Scholes equation for option price into a quasilinear parabolic equation for the second derivative (Greek) Γ = VSS of the option price V. We develop an efficient numerical method for solving the model problem concerning different volatility terms. Using suitable change of variables the problem is transformed on finite interval, keeping original behavior of the solution at the infinity. Then we construct Picard-Newton algorithm with adaptive mesh step in time, which can be applied also in the case of non-differentiable functions. Results of numerical simulations are given.

Refractive Thinking Profile In Solving Mathematical Problem Reviewed from Students Math Capability

NASA Astrophysics Data System (ADS)

Maslukha, M.; Lukito, A.; Ekawati, R.

2018-01-01

Refraction is a mental activity experienced by a person to make a decision through reflective thinking and critical thinking. Differences in mathematical capability have an influence on the difference of student’s refractive thinking processes in solving math problems. This descriptive research aims to generate a picture of refractive thinking of students in solving mathematical problems in terms of students’ math skill. Subjects in this study consisted of three students, namely students with high, medium, and low math skills based on mathematics capability test. Data collection methods used are test-based methods and interviews. After collected data is analyzed through three stages that are, condensing and displaying data, data display, and drawing and verifying conclusion. Results showed refractive thinking profiles of three subjects is different. This difference occurs at the planning and execution stage of the problem. This difference is influenced by mathematical capability and experience of each subject.

Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1M Unknowns

NASA Technical Reports Server (NTRS)

Shaeffer, John

2008-01-01

Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.

Cuckoo search via Levy flights applied to uncapacitated facility location problem

NASA Astrophysics Data System (ADS)

Mesa, Armacheska; Castromayor, Kris; Garillos-Manliguez, Cinmayii; Calag, Vicente

2017-11-01

Facility location problem (FLP) is a mathematical way to optimally locate facilities within a set of candidates to satisfy the requirements of a given set of clients. This study addressed the uncapacitated FLP as it assures that the capacity of every selected facility is finite. Thus, even if the demand is not known, which often is the case, in reality, organizations may still be able to take strategic decisions such as locating the facilities. There are different approaches relevant to the uncapacitated FLP. Here, the cuckoo search via Lévy flight (CS-LF) was used to solve the problem. Though hybrid methods produce better results, this study employed CS-LF to determine first its potential in finding solutions for the problem, particularly when applied to a real-world problem. The method was applied to the data set obtained from a department store in Davao City, Philippines. Results showed that applying CS-LF yielded better facility locations compared to particle swarm optimization and other existing algorithms. Although these results showed that CS-LF is a promising method to solve this particular problem, further studies on other FLP are recommended to establish a strong foundation of the capability of CS-LF in solving FLP.

Simulating propagation of coherent light in random media using the Fredholm type integral equation

NASA Astrophysics Data System (ADS)

Kraszewski, Maciej; Pluciński, Jerzy

2017-06-01

Studying propagation of light in random scattering materials is important for both basic and applied research. Such studies often require usage of numerical method for simulating behavior of light beams in random media. However, if such simulations require consideration of coherence properties of light, they may become a complex numerical problems. There are well established methods for simulating multiple scattering of light (e.g. Radiative Transfer Theory and Monte Carlo methods) but they do not treat coherence properties of light directly. Some variations of these methods allows to predict behavior of coherent light but only for an averaged realization of the scattering medium. This limits their application in studying many physical phenomena connected to a specific distribution of scattering particles (e.g. laser speckle). In general, numerical simulation of coherent light propagation in a specific realization of random medium is a time- and memory-consuming problem. The goal of the presented research was to develop new efficient method for solving this problem. The method, presented in our earlier works, is based on solving the Fredholm type integral equation, which describes multiple light scattering process. This equation can be discretized and solved numerically using various algorithms e.g. by direct solving the corresponding linear equations system, as well as by using iterative or Monte Carlo solvers. Here we present recent development of this method including its comparison with well-known analytical results and a finite-difference type simulations. We also present extension of the method for problems of multiple scattering of a polarized light on large spherical particles that joins presented mathematical formalism with Mie theory.

Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem.

PubMed

Chen, Xiaopan; Kong, Yunfeng; Dang, Lanxue; Hou, Yane; Ye, Xinyue

2015-01-01

As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods.

Rupture Dynamics Simulation for Non-Planar fault by a Curved Grid Finite Difference Method

NASA Astrophysics Data System (ADS)

Zhang, Z.; Zhu, G.; Chen, X.

2011-12-01

We first implement the non-staggered finite difference method to solve the dynamic rupture problem, with split-node, for non-planar fault. Split-node method for dynamic simulation has been used widely, because of that it's more precise to represent the fault plane than other methods, for example, thick fault, stress glut and so on. The finite difference method is also a popular numeric method to solve kinematic and dynamic problem in seismology. However, previous works focus most of theirs eyes on the staggered-grid method, because of its simplicity and computational efficiency. However this method has its own disadvantage comparing to non-staggered finite difference method at some fact for example describing the boundary condition, especially the irregular boundary, or non-planar fault. Zhang and Chen (2006) proposed the MacCormack high order non-staggered finite difference method based on curved grids to precisely solve irregular boundary problem. Based upon on this non-staggered grid method, we make success of simulating the spontaneous rupture problem. The fault plane is a kind of boundary condition, which could be irregular of course. So it's convinced that we could simulate rupture process in the case of any kind of bending fault plane. We will prove this method is valid in the case of Cartesian coordinate first. In the case of bending fault, the curvilinear grids will be used.

A constraint optimization based virtual network mapping method

NASA Astrophysics Data System (ADS)

Li, Xiaoling; Guo, Changguo; Wang, Huaimin; Li, Zhendong; Yang, Zhiwen

2013-03-01

Virtual network mapping problem, maps different virtual networks onto the substrate network is an extremely challenging work. This paper proposes a constraint optimization based mapping method for solving virtual network mapping problem. This method divides the problem into two phases, node mapping phase and link mapping phase, which are all NP-hard problems. Node mapping algorithm and link mapping algorithm are proposed for solving node mapping phase and link mapping phase, respectively. Node mapping algorithm adopts the thinking of greedy algorithm, mainly considers two factors, available resources which are supplied by the nodes and distance between the nodes. Link mapping algorithm is based on the result of node mapping phase, adopts the thinking of distributed constraint optimization method, which can guarantee to obtain the optimal mapping with the minimum network cost. Finally, simulation experiments are used to validate the method, and results show that the method performs very well.

The covariance matrix for the solution vector of an equality-constrained least-squares problem

NASA Technical Reports Server (NTRS)

Lawson, C. L.

1976-01-01

Methods are given for computing the covariance matrix for the solution vector of an equality-constrained least squares problem. The methods are matched to the solution algorithms given in the book, 'Solving Least Squares Problems.'

Non-standard finite difference and Chebyshev collocation methods for solving fractional diffusion equation

NASA Astrophysics Data System (ADS)

Agarwal, P.; El-Sayed, A. A.

2018-06-01

In this paper, a new numerical technique for solving the fractional order diffusion equation is introduced. This technique basically depends on the Non-Standard finite difference method (NSFD) and Chebyshev collocation method, where the fractional derivatives are described in terms of the Caputo sense. The Chebyshev collocation method with the (NSFD) method is used to convert the problem into a system of algebraic equations. These equations solved numerically using Newton's iteration method. The applicability, reliability, and efficiency of the presented technique are demonstrated through some given numerical examples.

Teaching to Teach (with) Game Design: Game Design and Learning Workshops for Preservice Teachers

ERIC Educational Resources Information Center

Akcaoglu, Mete; Kale, Ugur

2016-01-01

Engagement in game design tasks can help preservice teachers develop pedagogical and technical skills for teaching and promoting critical thinking and problem-solving skills. Through the design process, preservice teachers not only exercise critical-thinking and problem-solving skills, but also learn about an instructional method to support their…

Concordancers and Dictionaries as Problem-Solving Tools for ESL Academic Writing

ERIC Educational Resources Information Center

Yoon, Choongil

2016-01-01

The present study investigated how 6 Korean ESL graduate students in Canada used a suite of freely available reference resources, consisting of Web-based corpus tools, Google search engines, and dictionaries, for solving linguistic problems while completing an authentic academic writing assignment in English. Using a mixed methods design, the…

Reciprocal and Complementary Sibling Interactions, Relationship Quality and Socio-Emotional Problem Solving

ERIC Educational Resources Information Center

Karos, Leigh Karavasilis; Howe, Nina; Aquan-Assee, Jasmin

2007-01-01

Associations between reciprocal and complementary sibling interactions, sibling relationship quality, and children's socio-emotional problem solving were examined in 40 grade 5-6 children (M age = 11.5 years) from middle class, Caucasian, Canadian families using a multi-method approach (i.e. interviews, self-report questionnaires, daily diary…

Pre-Service Science Teachers' Reflective Thinking Skills toward Problem Solving

ERIC Educational Resources Information Center

Can, Sendil

2015-01-01

The purpose of the present study is to investigate the pre-service science teachers' reflective thinking skills toward problem solving and the effects of gender, grade level, academic achievement, type of graduated high school and father and mother's education level on these skills. The study was conducted through the survey method with the…

Exploration of Mathematics Problem Solving Process Based on the Thinking Level of Students in Junior High School

ERIC Educational Resources Information Center

Rahman, Abdul; Ahmar, Ansari Saleh

2016-01-01

Several studies suggest that most students are not in the same level of development (Slavin, 2008). From concrete operation level to formal operation level, students experience lateness in the transition phase. Consequently, students feel difficulty in solving mathematics problems. Method research is a qualitatively descriptive-explorative…

Grading Homework to Emphasize Problem-Solving Process Skills

ERIC Educational Resources Information Center

Harper, Kathleen A.

2012-01-01

This article describes a grading approach that encourages students to employ particular problem-solving skills. Some strengths of this method, called "process-based grading," are that it is easy to implement, requires minimal time to grade, and can be used in conjunction with either an online homework delivery system or paper-based homework.

Prospective Teachers' Beliefs about Problem Solving in Multiple Ways

ERIC Educational Resources Information Center

Arikan, Elif Esra

2016-01-01

The purpose of this study is to analyze whether prospective teachers believe solving a mathematics problem involves in using different solution methods. 60 mathematics prospective teachers who take the pedagogic training program in a state university were participated in this study. Five open-ended questions were asked. The study was carried out…

Computer-Based Assessment of Complex Problem Solving: Concept, Implementation, and Application

ERIC Educational Resources Information Center

Greiff, Samuel; Wustenberg, Sascha; Holt, Daniel V.; Goldhammer, Frank; Funke, Joachim

2013-01-01

Complex Problem Solving (CPS) skills are essential to successfully deal with environments that change dynamically and involve a large number of interconnected and partially unknown causal influences. The increasing importance of such skills in the 21st century requires appropriate assessment and intervention methods, which in turn rely on adequate…

Cognitive Science and Instructional Technology: Improvements in Higher Order Thinking Strategies.

ERIC Educational Resources Information Center

Tennyson, Robert D.

This paper examines the cognitive processes associated with higher-order thinking strategies--i.e., cognitive processes directly associated with the employment of knowledge in the service of problem solving and creativity--in order to more clearly define a prescribed instructional method to improve problem-solving skills. The first section of the…

Assessing Students in Human-to-Agent Settings to Inform Collaborative Problem-Solving Learning

ERIC Educational Resources Information Center

Rosen, Yigal

2017-01-01

In order to understand potential applications of collaborative problem-solving (CPS) assessment tasks, it is necessary to examine empirically the multifaceted student performance that may be distributed across collaboration methods and purposes of the assessment. Ideally, each student should be matched with various types of group members and must…

Show, Don't Tell: Using Photographic "Snapsignments" to Advance and Assess Creative Problem Solving

ERIC Educational Resources Information Center

Machin, Jane E.

2016-01-01

Traditional assignments that aim to develop and evaluate creative problem solving skills are frequently foregone in large marketing classes due to the daunting grading prospect they present. Here, a new assessment method is introduced: the "snapsignment." Through photography, individual projects can be assigned that promote higher order…

Observing Student Working Styles when Using Graphic Calculators to Solve Mathematics Problems

ERIC Educational Resources Information Center

Berry, J.; Graham, E.; Smith, A.

2006-01-01

Some research studies, many of which used quantitative methods, have suggested that graphics calculators can be used to effectively enhance the learning of mathematics. More recently research studies have started to explore students' styles of working as they solve problems with technology. This paper describes the use of a software application…

Some observations on a new numerical method for solving Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Kumar, A.

1981-01-01

An explicit-implicit technique for solving Navier-Stokes equations is described which, is much less complex than other implicit methods. It is used to solve a complex, two-dimensional, steady-state, supersonic-flow problem. The computational efficiency of the method and the quality of the solution obtained from it at high Courant-Friedrich-Lewy (CFL) numbers are discussed. Modifications are discussed and certain observations are made about the method which may be helpful in using it successfully.

Applications of numerical methods to simulate the movement of contaminants in groundwater.

PubMed Central

Sun, N Z

1989-01-01

This paper reviews mathematical models and numerical methods that have been extensively used to simulate the movement of contaminants through the subsurface. The major emphasis is placed on the numerical methods of advection-dominated transport problems and inverse problems. Several mathematical models that are commonly used in field problems are listed. A variety of numerical solutions for three-dimensional models are introduced, including the multiple cell balance method that can be considered a variation of the finite element method. The multiple cell balance method is easy to understand and convenient for solving field problems. When the advection transport dominates the dispersion transport, two kinds of numerical difficulties, overshoot and numerical dispersion, are always involved in solving standard, finite difference methods and finite element methods. To overcome these numerical difficulties, various numerical techniques are developed, such as upstream weighting methods and moving point methods. A complete review of these methods is given and we also mention the problems of parameter identification, reliability analysis, and optimal-experiment design that are absolutely necessary for constructing a practical model. PMID:2695327

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

Honey bee-inspired algorithms for SNP haplotype reconstruction problem

NASA Astrophysics Data System (ADS)

PourkamaliAnaraki, Maryam; Sadeghi, Mehdi

2016-03-01

Reconstructing haplotypes from SNP fragments is an important problem in computational biology. There have been a lot of interests in this field because haplotypes have been shown to contain promising data for disease association research. It is proved that haplotype reconstruction in Minimum Error Correction model is an NP-hard problem. Therefore, several methods such as clustering techniques, evolutionary algorithms, neural networks and swarm intelligence approaches have been proposed in order to solve this problem in appropriate time. In this paper, we have focused on various evolutionary clustering techniques and try to find an efficient technique for solving haplotype reconstruction problem. It can be referred from our experiments that the clustering methods relying on the behaviour of honey bee colony in nature, specifically bees algorithm and artificial bee colony methods, are expected to result in more efficient solutions. An application program of the methods is available at the following link. http://www.bioinf.cs.ipm.ir/software/haprs/

Hierarchical semi-numeric method for pairwise fuzzy group decision making.

PubMed

Marimin, M; Umano, M; Hatono, I; Tamura, H

2002-01-01

Gradual improvements to a single-level semi-numeric method, i.e., linguistic labels preference representation by fuzzy sets computation for pairwise fuzzy group decision making are summarized. The method is extended to solve multiple criteria hierarchical structure pairwise fuzzy group decision-making problems. The problems are hierarchically structured into focus, criteria, and alternatives. Decision makers express their evaluations of criteria and alternatives based on each criterion by using linguistic labels. The labels are converted into and processed in triangular fuzzy numbers (TFNs). Evaluations of criteria yield relative criteria weights. Evaluations of the alternatives, based on each criterion, yield a degree of preference for each alternative or a degree of satisfaction for each preference value. By using a neat ordered weighted average (OWA) or a fuzzy weighted average operator, solutions obtained based on each criterion are aggregated into final solutions. The hierarchical semi-numeric method is suitable for solving a larger and more complex pairwise fuzzy group decision-making problem. The proposed method has been verified and applied to solve some real cases and is compared to Saaty's (1996) analytic hierarchy process (AHP) method.

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.

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

ADM For Solving Linear Second-Order Fredholm Integro-Differential Equations

NASA Astrophysics Data System (ADS)

Karim, Mohd F.; Mohamad, Mahathir; Saifullah Rusiman, Mohd; Che-Him, Norziha; Roslan, Rozaini; Khalid, Kamil

2018-04-01

In this paper, we apply Adomian Decomposition Method (ADM) as numerically analyse linear second-order Fredholm Integro-differential Equations. The approximate solutions of the problems are calculated by Maple package. Some numerical examples have been considered to illustrate the ADM for solving this equation. The results are compared with the existing exact solution. Thus, the Adomian decomposition method can be the best alternative method for solving linear second-order Fredholm Integro-Differential equation. It converges to the exact solution quickly and in the same time reduces computational work for solving the equation. The result obtained by ADM shows the ability and efficiency for solving these equations.

Acceleration of aircraft-level Traffic Flow Management

NASA Astrophysics Data System (ADS)

Rios, Joseph Lucio

This dissertation describes novel approaches to solving large-scale, high fidelity, aircraft-level Traffic Flow Management scheduling problems. Depending on the methods employed, solving these problems to optimality can take longer than the length of the planning horizon in question. Research in this domain typically focuses on the quality of the modeling used to describe the problem and the benefits achieved from the optimized solution, often treating computational aspects as secondary or tertiary. The work presented here takes the complementary view and considers the computational aspect as the primary concern. To this end, a previously published model for solving this Traffic Flow Management scheduling problem is used as starting point for this study. The model proposed by Bertsimas and Stock-Patterson is a binary integer program taking into account all major resource capacities and the trajectories of each flight to decide which flights should be held in which resource for what amount of time in order to satisfy all capacity requirements. For large instances, the solve time using state-of-the-art solvers is prohibitive for use within a potential decision support tool. With this dissertation, however, it will be shown that solving can be achieved in reasonable time for instances of real-world size. Five other techniques developed and tested for this dissertation will be described in detail. These are heuristic methods that provide good results. Performance is measured in terms of runtime and "optimality gap." We then describe the most successful method presented in this dissertation: Dantzig-Wolfe Decomposition. Results indicate that a parallel implementation of Dantzig-Wolfe Decomposition optimally solves the original problem in much reduced time and with better integrality and smaller optimality gap than any of the heuristic methods or state-of-the-art, commercial solvers. The solution quality improves in every measureable way as the number of subproblems solved in parallel increases. A maximal decomposition provides the best results of any method tested. The convergence qualities of Dantzig-Wolfe Decomposition have been criticized in the past, so we examine what makes the Bertsimas-Stock Patterson model so amenable to use of this method. These mathematical qualities of the model are generalized to provide guidance on other problems that may benefit from massively parallel Dantzig-Wolfe Decomposition. This result, together with the development of the software, and the experimental results indicating the feasibility of real-time, nationwide Traffic Flow Management scheduling represent the major contributions of this dissertation.

A computer program to find the kernel of a polynomial operator

NASA Technical Reports Server (NTRS)

Gejji, R. R.

1976-01-01

This paper presents a FORTRAN program written to solve for the kernel of a matrix of polynomials with real coefficients. It is an implementation of Sain's free modular algorithm for solving the minimal design problem of linear multivariable systems. The structure of the program is discussed, together with some features as they relate to questions of implementing the above method. An example of the use of the program to solve a design problem is included.

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.

Numerical study of signal propagation in corrugated coaxial cables

DOE PAGES

Li, Jichun; Machorro, Eric A.; Shields, Sidney

2017-01-01

Our article focuses on high-fidelity modeling of signal propagation in corrugated coaxial cables. Taking advantage of the axisymmetry, the authors reduce the 3-D problem to a 2-D problem by solving time-dependent Maxwell's equations in cylindrical coordinates.They then develop a nodal discontinuous Galerkin method for solving their model equations. We prove stability and error analysis for the semi-discrete scheme. We we present our numerical results, we demonstrate that our algorithm not only converges as our theoretical analysis predicts, but it is also very effective in solving a variety of signal propagation problems in practical corrugated coaxial cables.

The use of MACSYMA for solving elliptic boundary value problems

NASA Technical Reports Server (NTRS)

Thejll, Peter; Gilbert, Robert P.

1990-01-01

A boundary method is presented for the solution of elliptic boundary value problems. An approach based on the use of complete systems of solutions is emphasized. The discussion is limited to the Dirichlet problem, even though the present method can possibly be adapted to treat other boundary value problems.

Shooting method for solution of boundary-layer flows with massive blowing

NASA Technical Reports Server (NTRS)

Liu, T.-M.; Nachtsheim, P. R.

1973-01-01

A modified, bidirectional shooting method is presented for solving boundary-layer equations under conditions of massive blowing. Unlike the conventional shooting method, which is unstable when the blowing rate increases, the proposed method avoids the unstable direction and is capable of solving complex boundary-layer problems involving mass and energy balance on the surface.

Six-Degree-of-Freedom Trajectory Optimization Utilizing a Two-Timescale Collocation Architecture

NASA Technical Reports Server (NTRS)

Desai, Prasun N.; Conway, Bruce A.

2005-01-01

Six-degree-of-freedom (6DOF) trajectory optimization of a reentry vehicle is solved using a two-timescale collocation methodology. This class of 6DOF trajectory problems are characterized by two distinct timescales in their governing equations, where a subset of the states have high-frequency dynamics (the rotational equations of motion) while the remaining states (the translational equations of motion) vary comparatively slowly. With conventional collocation methods, the 6DOF problem size becomes extraordinarily large and difficult to solve. Utilizing the two-timescale collocation architecture, the problem size is reduced significantly. The converged solution shows a realistic landing profile and captures the appropriate high-frequency rotational dynamics. A large reduction in the overall problem size (by 55%) is attained with the two-timescale architecture as compared to the conventional single-timescale collocation method. Consequently, optimum 6DOF trajectory problems can now be solved efficiently using collocation, which was not previously possible for a system with two distinct timescales in the governing states.

Engineering neural systems for high-level problem solving.

PubMed

Sylvester, Jared; Reggia, James

2016-07-01

There is a long-standing, sometimes contentious debate in AI concerning the relative merits of a symbolic, top-down approach vs. a neural, bottom-up approach to engineering intelligent machine behaviors. While neurocomputational methods excel at lower-level cognitive tasks (incremental learning for pattern classification, low-level sensorimotor control, fault tolerance and processing of noisy data, etc.), they are largely non-competitive with top-down symbolic methods for tasks involving high-level cognitive problem solving (goal-directed reasoning, metacognition, planning, etc.). Here we take a step towards addressing this limitation by developing a purely neural framework named galis. Our goal in this work is to integrate top-down (non-symbolic) control of a neural network system with more traditional bottom-up neural computations. galis is based on attractor networks that can be "programmed" with temporal sequences of hand-crafted instructions that control problem solving by gating the activity retention of, communication between, and learning done by other neural networks. We demonstrate the effectiveness of this approach by showing that it can be applied successfully to solve sequential card matching problems, using both human performance and a top-down symbolic algorithm as experimental controls. Solving this kind of problem makes use of top-down attention control and the binding together of visual features in ways that are easy for symbolic AI systems but not for neural networks to achieve. Our model can not only be instructed on how to solve card matching problems successfully, but its performance also qualitatively (and sometimes quantitatively) matches the performance of both human subjects that we had perform the same task and the top-down symbolic algorithm that we used as an experimental control. We conclude that the core principles underlying the galis framework provide a promising approach to engineering purely neurocomputational systems for problem-solving tasks that in people require higher-level cognitive functions. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Moryakov, A. V., E-mail: sailor@yauza.ru; Pylyov, S. S.

This paper presents the formulation of the problem and the methodical approach for solving large systems of linear differential equations describing nonstationary processes with the use of CUDA technology; this approach is implemented in the ANGEL program. Results for a test problem on transport of radioactive products over loops of a nuclear power plant are given. The possibilities for the use of the ANGEL program for solving various problems that simulate arbitrary nonstationary processes are discussed.

Design and multi-physics optimization of rotary MRF brakes

NASA Astrophysics Data System (ADS)

Topcu, Okan; Taşcıoğlu, Yiğit; Konukseven, Erhan İlhan

2018-03-01

Particle swarm optimization (PSO) is a popular method to solve the optimization problems. However, calculations for each particle will be excessive when the number of particles and complexity of the problem increases. As a result, the execution speed will be too slow to achieve the optimized solution. Thus, this paper proposes an automated design and optimization method for rotary MRF brakes and similar multi-physics problems. A modified PSO algorithm is developed for solving multi-physics engineering optimization problems. The difference between the proposed method and the conventional PSO is to split up the original single population into several subpopulations according to the division of labor. The distribution of tasks and the transfer of information to the next party have been inspired by behaviors of a hunting party. Simulation results show that the proposed modified PSO algorithm can overcome the problem of heavy computational burden of multi-physics problems while improving the accuracy. Wire type, MR fluid type, magnetic core material, and ideal current inputs have been determined by the optimization process. To the best of the authors' knowledge, this multi-physics approach is novel for optimizing rotary MRF brakes and the developed PSO algorithm is capable of solving other multi-physics engineering optimization problems. The proposed method has showed both better performance compared to the conventional PSO and also has provided small, lightweight, high impedance rotary MRF brake designs.

Enhanced algorithms for stochastic programming

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

Krishna, Alamuru S.

1993-09-01

In this dissertation, we present some of the recent advances made in solving two-stage stochastic linear programming problems of large size and complexity. Decomposition and sampling are two fundamental components of techniques to solve stochastic optimization problems. We describe improvements to the current techniques in both these areas. We studied different ways of using importance sampling techniques in the context of Stochastic programming, by varying the choice of approximation functions used in this method. We have concluded that approximating the recourse function by a computationally inexpensive piecewise-linear function is highly efficient. This reduced the problem from finding the mean ofmore » a computationally expensive functions to finding that of a computationally inexpensive function. Then we implemented various variance reduction techniques to estimate the mean of a piecewise-linear function. This method achieved similar variance reductions in orders of magnitude less time than, when we directly applied variance-reduction techniques directly on the given problem. In solving a stochastic linear program, the expected value problem is usually solved before a stochastic solution and also to speed-up the algorithm by making use of the information obtained from the solution of the expected value problem. We have devised a new decomposition scheme to improve the convergence of this algorithm.« less

Solving a problem by using what you know: a physicist looks at a problem in ecology

NASA Astrophysics Data System (ADS)

Greenler, Robert

2015-08-01

Two philosophical ideas motivate this paper. The first is an answer to the question of what is an appropriate activity for a physicist. My answer is that an appropriate activity is anything where the tools of a physicist enable him or her to make a contribution to the solution of a significant problem. This may be obvious in areas that overlap physics (e.g. chemistry, engineering, geology) but also true in any endeavour where mathematical modelling may contribute insight to the solution of problems (e.g. timing of traffic lights, efficient ways to seat passengers on airplanes, whether it is better to walk or run in a rain shower). The second idea concerns an approach to problem solving. Before some people try to solve a problem, they think they first must learn everything that is known about the subject. However, sometimes an effective approach is to declare, ‘I’m going to solve this problem with what I know now!’ I see a relationship between this approach and the idea of back-of-the-envelope calculations, which many of us appreciate. Of course there are limitations to this method, but I believe that such an aggressive approach to a problem—uninfluenced by the methods everyone else has used—can be productive. This paper describes such an approach to a real-world problem, using only what is known by the teacher of the introductory, calculus-based physics course. The intent of this paper is to encourage students and teachers of physics to look for unconventional areas, outside of physics, where they might use the techniques they have learned to solve problems

Solving large sparse eigenvalue problems on supercomputers

NASA Technical Reports Server (NTRS)

Philippe, Bernard; Saad, Youcef

1988-01-01

An important problem in scientific computing consists in finding a few eigenvalues and corresponding eigenvectors of a very large and sparse matrix. The most popular methods to solve these problems are based on projection techniques on appropriate subspaces. The main attraction of these methods is that they only require the use of the matrix in the form of matrix by vector multiplications. The implementations on supercomputers of two such methods for symmetric matrices, namely Lanczos' method and Davidson's method are compared. Since one of the most important operations in these two methods is the multiplication of vectors by the sparse matrix, methods of performing this operation efficiently are discussed. The advantages and the disadvantages of each method are compared and implementation aspects are discussed. Numerical experiments on a one processor CRAY 2 and CRAY X-MP are reported. Possible parallel implementations are also discussed.

Multiple representations and free-body diagrams: Do students benefit from using them?

NASA Astrophysics Data System (ADS)

Rosengrant, David R.

2007-12-01

Introductory physics students have difficulties understanding concepts and solving problems. When they solve problems, they use surface features of the problems to find an equation to calculate a numerical answer often not understanding the physics in the problem. How do we help students approach problem solving in an expert manner? A possible answer is to help them learn to represent knowledge in multiple ways and then use these different representations for conceptual understanding and problem solving. This solution follows from research in cognitive science and in physics education. However, there are no studies in physics that investigate whether students who learn to use multiple representations are in fact better problem solvers. This study focuses on one specific representation used in physics--a free body diagram. A free-body diagram is a graphical representation of forces exerted on an object of interest by other objects. I used the free-body diagram to investigate five main questions: (1) If students are in a course where they consistently use free body diagrams to construct and test concepts in mechanics, electricity and magnetism and to solve problems in class and in homework, will they draw free-body diagrams on their own when solving exam problems? (2) Are students who use free-body diagrams to solve problems more successful then those who do not? (3) Why do students draw free-body diagrams when solving problems? (4) Are students consistent in constructing diagrams for different concepts in physics and are they consistent in the quality of their diagrams? (5) What are possible relationships between features of a problem and how likely a student will draw a free body diagram to help them solve the problem? I utilized a mixed-methods approach to answer these questions. Questions 1, 2, 4 and 5 required a quantitative approach while question 3 required a qualitative approach, a case study. When I completed my study, I found that if students are in an environment which fosters the use of representations for problem solving and for concept development, then the majority of students will consistently construct helpful free-body diagrams and use them on their own to solve problems. Additionally, those that construct correct free-body diagrams are significantly more likely to successfully solve the problem. Finally, those students that are high achieving tend to use diagrams more and for more reasons then students who have low course grades. These findings will have major impacts on how introductory physics instructors run their classes and how curriculums are designed. These results favor a problem solving strategy that is rich with representations.

Effective pedagogies for teaching math to nursing students: a literature review.

PubMed

Hunter Revell, Susan M; McCurry, Mary K

2013-11-01

Improving mathematical competency and problem-solving skills in undergraduate nursing students has been an enduring challenge for nurse educators. A number of teaching strategies have been used to address this problem with varying degrees of success. This paper discusses a literature review which examined undergraduate nursing student challenges to learning math, methods used to teach math and problem-solving skills, and the use of innovative pedagogies for teaching. The literature was searched using the Cumulative Index of Nursing and Allied Health Literature and Education Resource Information Center databases. Key search terms included: math*, nurs*, nursing student, calculation, technology, medication administration, challenges, problem-solving, personal response system, clickers, computer and multi-media. Studies included in the review were published in English from 1990 to 2011. Results support four major themes which include: student challenges to learning, traditional pedagogies, curriculum strategies, and technology and integrative methods as pedagogy. The review concludes that there is a need for more innovative pedagogical strategies for teaching math to student nurses. Nurse educators in particular play a central role in helping students learn the conceptual basis, as well as practical hands-on methods, to problem solving and math competency. It is recommended that an integrated approach inclusive of technology will benefit students through better performance, increased understanding, and improved student satisfaction. Copyright © 2012 Elsevier Ltd. All rights reserved.

Insight in the Brain: The Cognitive and Neural Bases of Eureka Moments

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

Beeman, Mark

Where do new ideas come from? Although all new ideas build on old, this can happen in different ways. Some new ideas, or solutions to old problems, are achieved through methodical, analytical processing. Other new ideas come about in a sudden burst of insight, often based on or generating a restructured view of the problem itself. Behavioral, brain imaging, and eye-tracking results all reveal distinct cortical networks contributing to insight solving, as contrasted with analytic solving. Consistently, the way in which people solve problems appears to relate to the way they engage attention and cognitive control: across time, across moods,more » and across individuals. Insight is favored when people can disengage from strong stimuli and associations - figuratively and literally looking "outside the box" of the problem to suddenly solve with a new idea.« less

Triz in Mems

NASA Astrophysics Data System (ADS)

Apte, Prakash R.

1999-11-01

TRIZ is a Russian abbreviation. Genrich Altshuller developed it fifty years ago in the former Soviet Union. He examined thousands of inventions made in different technological systems and formulated a 'Theory of Inventive problem solving' (TRIZ). Altshuller's research of over fifty years on Creativity and Inventive Problem Solving has led to many different classifications, methods and tools of invention. Some of these are, Contradictions table, Level of inventions, Patterns in evolution of technological systems, ARIZ-Algorithm for Inventive Problem Solving, Diagnostic problem solving and Anticipatory Failure Determination. MEMS research consists of conceptual design, process technology and including of various Mechanical, ELectrical, Thermal, Magnetic, Acoustic and other effects. MEMS system s are now rapidly growing in complexity. Each system will thus follow one or more 'patterns of evolution' as given by Altshuller. This paper attempts to indicate how various TRIZ tools can be used in MEMS research activities.

Split Bregman's optimization method for image construction in compressive sensing

NASA Astrophysics Data System (ADS)

Skinner, D.; Foo, S.; Meyer-Bäse, A.

2014-05-01

The theory of compressive sampling (CS) was reintroduced by Candes, Romberg and Tao, and D. Donoho in 2006. Using a priori knowledge that a signal is sparse, it has been mathematically proven that CS can defY Nyquist sampling theorem. Theoretically, reconstruction of a CS image relies on the minimization and optimization techniques to solve this complex almost NP-complete problem. There are many paths to consider when compressing and reconstructing an image but these methods have remained untested and unclear on natural images, such as underwater sonar images. The goal of this research is to perfectly reconstruct the original sonar image from a sparse signal while maintaining pertinent information, such as mine-like object, in Side-scan sonar (SSS) images. Goldstein and Osher have shown how to use an iterative method to reconstruct the original image through a method called Split Bregman's iteration. This method "decouples" the energies using portions of the energy from both the !1 and !2 norm. Once the energies are split, Bregman iteration is used to solve the unconstrained optimization problem by recursively solving the problems simultaneously. The faster these two steps or energies can be solved then the faster the overall method becomes. While the majority of CS research is still focused on the medical field, this paper will demonstrate the effectiveness of the Split Bregman's methods on sonar images.

Optimization of aerodynamic form of projectile for solving the problem of shooting range increasing

NASA Astrophysics Data System (ADS)

Lipanov, Alexey M.; Korolev, Stanislav A.; Rusyak, Ivan G.

2017-10-01

The article is devoted to the development of methods for solving the problem of external ballistics using a more complete system of motion equation taken into account the rotation and oscillation about the mass center and using aerodynamic coefficients of forces and moments which are calculated on the basis of modeling the hydrodynamics of flow around the projectile. Developed methods allows to study the basic ways of increasing the shooting range or artillery.

Improvement of statistical methods for detecting anomalies in climate and environmental monitoring systems

NASA Astrophysics Data System (ADS)

Yakunin, A. G.; Hussein, H. M.

2018-01-01

The article shows how the known statistical methods, which are widely used in solving financial problems and a number of other fields of science and technology, can be effectively applied after minor modification for solving such problems in climate and environment monitoring systems, as the detection of anomalies in the form of abrupt changes in signal levels, the occurrence of positive and negative outliers and the violation of the cycle form in periodic processes.

Hermite Functional Link Neural Network for Solving the Van der Pol-Duffing Oscillator Equation.

PubMed

Mall, Susmita; Chakraverty, S

2016-08-01

Hermite polynomial-based functional link artificial neural network (FLANN) is proposed here to solve the Van der Pol-Duffing oscillator equation. A single-layer hermite neural network (HeNN) model is used, where a hidden layer is replaced by expansion block of input pattern using Hermite orthogonal polynomials. A feedforward neural network model with the unsupervised error backpropagation principle is used for modifying the network parameters and minimizing the computed error function. The Van der Pol-Duffing and Duffing oscillator equations may not be solved exactly. Here, approximate solutions of these types of equations have been obtained by applying the HeNN model for the first time. Three mathematical example problems and two real-life application problems of Van der Pol-Duffing oscillator equation, extracting the features of early mechanical failure signal and weak signal detection problems, are solved using the proposed HeNN method. HeNN approximate solutions have been compared with results obtained by the well known Runge-Kutta method. Computed results are depicted in term of graphs. After training the HeNN model, we may use it as a black box to get numerical results at any arbitrary point in the domain. Thus, the proposed HeNN method is efficient. The results reveal that this method is reliable and can be applied to other nonlinear problems too.

Two Meanings of Algorithmic Mathematics.

ERIC Educational Resources Information Center

Maurer, Stephen B.

1984-01-01

Two mathematical topics are interpreted from the viewpoints of traditional (performing algorithms) and contemporary (creating algorithms and thinking in terms of them for solving problems and developing theory) algorithmic mathematics. The two topics are Horner's method for evaluating polynomials and Gauss's method for solving systems of linear…

Completed Beltrami-Michell formulation for analyzing mixed boundary value problems in elasticity

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Kaljevic, Igor; Hopkins, Dale A.; Saigal, Sunil

1995-01-01

In elasticity, the method of forces, wherein stress parameters are considered as the primary unknowns, is known as the Beltrami-Michell formulation (BMF). The existing BMF can only solve stress boundary value problems; it cannot handle the more prevalent displacement of mixed boundary value problems of elasticity. Therefore, this formulation, which has restricted application, could not become a true alternative to the Navier's displacement method, which can solve all three types of boundary value problems. The restrictions in the BMF have been alleviated by augmenting the classical formulation with a novel set of conditions identified as the boundary compatibility conditions. This new method, which completes the classical force formulation, has been termed the completed Beltrami-Michell formulation (CBMF). The CBMF can solve general elasticity problems with stress, displacement, and mixed boundary conditions in terms of stresses as the primary unknowns. The CBMF is derived from the stationary condition of the variational functional of the integrated force method. In the CBMF, stresses for kinematically stable structures can be obtained without any reference to the displacements either in the field or on the boundary. This paper presents the CBMF and its derivation from the variational functional of the integrated force method. Several examples are presented to demonstrate the applicability of the completed formulation for analyzing mixed boundary value problems under thermomechanical loads. Selected example problems include a cylindrical shell wherein membrane and bending responses are coupled, and a composite circular plate.

GASOLINE: Smoothed Particle Hydrodynamics (SPH) code

NASA Astrophysics Data System (ADS)

N-Body Shop

2017-10-01

Gasoline solves the equations of gravity and hydrodynamics in astrophysical problems, including simulations of planets, stars, and galaxies. It uses an SPH method that features correct mixing behavior in multiphase fluids and minimal artificial viscosity. This method is identical to the SPH method used in the ChaNGa code (ascl:1105.005), allowing users to extend results to problems requiring >100,000 cores. Gasoline uses a fast, memory-efficient O(N log N) KD-Tree to solve Poisson's Equation for gravity and avoids artificial viscosity in non-shocking compressive flows.

Analytical methods for solving boundary value heat conduction problems with heterogeneous boundary conditions on lines. I - Review

NASA Astrophysics Data System (ADS)

Kartashov, E. M.

1986-10-01

Analytical methods for solving boundary value problems for the heat conduction equation with heterogeneous boundary conditions on lines, on a plane, and in space are briefly reviewed. In particular, the method of dual integral equations and summator series is examined with reference to stationary processes. A table of principal solutions to dual integral equations and pair summator series is proposed which presents the known results in a systematic manner. Newly obtained results are presented in addition to the known ones.

Solving Fuzzy Optimization Problem Using Hybrid Ls-Sa Method

NASA Astrophysics Data System (ADS)

Vasant, Pandian

2011-06-01

Fuzzy optimization problem has been one of the most and prominent topics inside the broad area of computational intelligent. It's especially relevant in the filed of fuzzy non-linear programming. It's application as well as practical realization can been seen in all the real world problems. In this paper a large scale non-linear fuzzy programming problem has been solved by hybrid optimization techniques of Line Search (LS), Simulated Annealing (SA) and Pattern Search (PS). As industrial production planning problem with cubic objective function, 8 decision variables and 29 constraints has been solved successfully using LS-SA-PS hybrid optimization techniques. The computational results for the objective function respect to vagueness factor and level of satisfaction has been provided in the form of 2D and 3D plots. The outcome is very promising and strongly suggests that the hybrid LS-SA-PS algorithm is very efficient and productive in solving the large scale non-linear fuzzy programming problem.

Quality Tools and TRIZ Based Quality Improvement Case Study at PT ‘X’ A Plastic Moulding Manufacturing Industry

NASA Astrophysics Data System (ADS)

Wirawan, Christina; Chandra, Fory

2016-02-01

Theory of Inventive Problem Solving (TRIZ) is a creative encouraging problem solving method. TRIZ is prepared by Altshuller for product design. Altshuller prepared contradiction matrix and suggestion to solve contradictions usually occur in product design. This paper try to combine TRIZ with quality tools such as Pareto and Fault Tree Analysis (FTA) to solve contradiction in quality improvement problem, neither than product design problem. Pareto used to identify defect priority, FTA used to analysis and identify root cause of defect. When there is contradiction in solving defect causes, TRIZ used to find creative problem solving. As a case study, PT ’X’, a plastic molding manufacturing industry was taken. PT ‘X’ using traditional press machine to produce plastic thread cone. There are 5 defect types that might occur in plastic thread cone production, incomplete form, dirty, mottle, excessive form, rugged. Research about quality improvement effort using DMAIC at PT ‘X’ have been done by Fory Candra. From this research, defect types, priority, root cause from FTA, recommendation from FMEA. In this research, from FTA reviewed, contradictions found among causes troublesome quality improvement efforts. TRIZ used to solve the contradictions and quality improvement effort can be made effectively.