The Efficacy of Using Diagrams When Solving Probability Word Problems in College

ERIC Educational Resources Information Center

Beitzel, Brian D.; Staley, Richard K.

2015-01-01

Previous experiments have shown a deleterious effect of visual representations on college students' ability to solve total- and joint-probability word problems. The present experiments used conditional-probability problems, known to be more difficult than total- and joint-probability problems. The diagram group was instructed in how to use tree…

Procedural versus Content-Related Hints for Word Problem Solving: An Exploratory Study

ERIC Educational Resources Information Center

Kock, W. D.; Harskamp, E. G.

2016-01-01

For primary school students, mathematical word problems are often more difficult to solve than straightforward number problems. Word problems require reading and analysis skills, and in order to explain their situational contexts, the proper mathematical knowledge and number operations have to be selected. To improve students' ability in solving…

A Cascade Optimization Strategy for Solution of Difficult Multidisciplinary Design Problems

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Hopkins, Dale A.; Berke, Laszlo

1996-01-01

A research project to comparatively evaluate 10 nonlinear optimization algorithms was recently completed. A conclusion was that no single optimizer could successfully solve all 40 problems in the test bed, even though most optimizers successfully solved at least one-third of the problems. We realized that improved search directions and step lengths, available in the 10 optimizers compared, were not likely to alleviate the convergence difficulties. For the solution of those difficult problems we have devised an alternative approach called cascade optimization strategy. The cascade strategy uses several optimizers, one followed by another in a specified sequence, to solve a problem. A pseudorandom scheme perturbs design variables between the optimizers. The cascade strategy has been tested successfully in the design of supersonic and subsonic aircraft configurations and air-breathing engines for high-speed civil transport applications. These problems could not be successfully solved by an individual optimizer. The cascade optimization strategy, however, generated feasible optimum solutions for both aircraft and engine problems. This paper presents the cascade strategy and solutions to a number of these problems.

An efficient and accurate solution methodology for bilevel multi-objective programming problems using a hybrid evolutionary-local-search algorithm.

PubMed

Deb, Kalyanmoy; Sinha, Ankur

2010-01-01

Bilevel optimization problems involve two optimization tasks (upper and lower level), in which every feasible upper level solution must correspond to an optimal solution to a lower level optimization problem. These problems commonly appear in many practical problem solving tasks including optimal control, process optimization, game-playing strategy developments, transportation problems, and others. However, they are commonly converted into a single level optimization problem by using an approximate solution procedure to replace the lower level optimization task. Although there exist a number of theoretical, numerical, and evolutionary optimization studies involving single-objective bilevel programming problems, not many studies look at the context of multiple conflicting objectives in each level of a bilevel programming problem. In this paper, we address certain intricate issues related to solving multi-objective bilevel programming problems, present challenging test problems, and propose a viable and hybrid evolutionary-cum-local-search based algorithm as a solution methodology. The hybrid approach performs better than a number of existing methodologies and scales well up to 40-variable difficult test problems used in this study. The population sizing and termination criteria are made self-adaptive, so that no additional parameters need to be supplied by the user. The study indicates a clear niche of evolutionary algorithms in solving such difficult problems of practical importance compared to their usual solution by a computationally expensive nested procedure. The study opens up many issues related to multi-objective bilevel programming and hopefully this study will motivate EMO and other researchers to pay more attention to this important and difficult problem solving activity.

Cognitive Development, Genetics Problem Solving, and Genetics Instruction: A Critical Review.

ERIC Educational Resources Information Center

Smith, Mike U.; Sims, O. Suthern, Jr.

1992-01-01

Review of literature concerning problem solving in genetics and Piagetian stage theory. Authors conclude the research suggests that formal-operational thought is not strictly required for the solution of the majority of classical genetics problems; however, some genetic concepts are difficult for concrete operational students to understand.…

Why Do Disadvantaged Filipino Children Find Word Problems in English Difficult?

ERIC Educational Resources Information Center

Bautista, Debbie; Mulligan, Joanne

2010-01-01

Young Filipino students are expected to solve mathematical word problems in English, a language that many encounter only in schools. Using individual interviews of 17 Filipino children, we investigated why word problems in English are difficult and the extent to which the language interferes with performance. Results indicate that children could…

Self-Affirmation Improves Problem-Solving under Stress

PubMed Central

Creswell, J. David; Dutcher, Janine M.; Klein, William M. P.; Harris, Peter R.; Levine, John M.

2013-01-01

High levels of acute and chronic stress are known to impair problem-solving and creativity on a broad range of tasks. Despite this evidence, we know little about protective factors for mitigating the deleterious effects of stress on problem-solving. Building on previous research showing that self-affirmation can buffer stress, we tested whether an experimental manipulation of self-affirmation improves problem-solving performance in chronically stressed participants. Eighty undergraduates indicated their perceived chronic stress over the previous month and were randomly assigned to either a self-affirmation or control condition. They then completed 30 difficult remote associate problem-solving items under time pressure in front of an evaluator. Results showed that self-affirmation improved problem-solving performance in underperforming chronically stressed individuals. This research suggests a novel means for boosting problem-solving under stress and may have important implications for understanding how self-affirmation boosts academic achievement in school settings. PMID:23658751

Self-affirmation improves problem-solving under stress.

PubMed

Creswell, J David; Dutcher, Janine M; Klein, William M P; Harris, Peter R; Levine, John M

2013-01-01

High levels of acute and chronic stress are known to impair problem-solving and creativity on a broad range of tasks. Despite this evidence, we know little about protective factors for mitigating the deleterious effects of stress on problem-solving. Building on previous research showing that self-affirmation can buffer stress, we tested whether an experimental manipulation of self-affirmation improves problem-solving performance in chronically stressed participants. Eighty undergraduates indicated their perceived chronic stress over the previous month and were randomly assigned to either a self-affirmation or control condition. They then completed 30 difficult remote associate problem-solving items under time pressure in front of an evaluator. Results showed that self-affirmation improved problem-solving performance in underperforming chronically stressed individuals. This research suggests a novel means for boosting problem-solving under stress and may have important implications for understanding how self-affirmation boosts academic achievement in school settings.

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

NASA Technical Reports Server (NTRS)

Bless, Robert R.; Hodges, Dewey H.

1991-01-01

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

Complex Problem Solving in Radiologic Technology: Understanding the Roles of Experience, Reflective Judgment, and Workplace Culture

ERIC Educational Resources Information Center

Yates, Jennifer L.

2011-01-01

The purpose of this research study was to explore the process of learning and development of problem solving skills in radiologic technologists. The researcher sought to understand the nature of difficult problems encountered in clinical practice, to identify specific learning practices leading to the development of professional expertise, and to…

Exploring students’ perceived and actual ability in solving statistical problems based on Rasch measurement tools

NASA Astrophysics Data System (ADS)

Azila Che Musa, Nor; Mahmud, Zamalia; Baharun, Norhayati

2017-09-01

One of the important skills that is required from any student who are learning statistics is knowing how to solve statistical problems correctly using appropriate statistical methods. This will enable them to arrive at a conclusion and make a significant contribution and decision for the society. In this study, a group of 22 students majoring in statistics at UiTM Shah Alam were given problems relating to topics on testing of hypothesis which require them to solve the problems using confidence interval, traditional and p-value approach. Hypothesis testing is one of the techniques used in solving real problems and it is listed as one of the difficult concepts for students to grasp. The objectives of this study is to explore students’ perceived and actual ability in solving statistical problems and to determine which item in statistical problem solving that students find difficult to grasp. Students’ perceived and actual ability were measured based on the instruments developed from the respective topics. Rasch measurement tools such as Wright map and item measures for fit statistics were used to accomplish the objectives. Data were collected and analysed using Winsteps 3.90 software which is developed based on the Rasch measurement model. The results showed that students’ perceived themselves as moderately competent in solving the statistical problems using confidence interval and p-value approach even though their actual performance showed otherwise. Item measures for fit statistics also showed that the maximum estimated measures were found on two problems. These measures indicate that none of the students have attempted these problems correctly due to reasons which include their lack of understanding in confidence interval and probability values.

A Research Methodology for Studying What Makes Some Problems Difficult to Solve

ERIC Educational Resources Information Center

Gulacar, Ozcan; Fynewever, Herb

2010-01-01

We present a quantitative model for predicting the level of difficulty subjects will experience with specific problems. The model explicitly accounts for the number of subproblems a problem can be broken into and the difficultly of each subproblem. Although the model builds on previously published models, it is uniquely suited for blending with…

Design and Implementation of the Game-Design and Learning Program

ERIC Educational Resources Information Center

Akcaoglu, Mete

2016-01-01

Design involves solving complex, ill-structured problems. Design tasks are consequently, appropriate contexts for children to exercise higher-order thinking and problem-solving skills. Although creating engaging and authentic design contexts for young children is difficult within the confines of traditional schooling, recently, game-design has…

Metacognition and Meta-Affect in Young Students: Does It Make a Difference in Mathematical Problem Solving?

ERIC Educational Resources Information Center

Tzohar-Rozen, Meirav; Kramarski, Bracha

2017-01-01

Mathematical problem solving is one of the most valuable aspects of mathematics education and the most difficult for elementary school students. Cognitive and metacognitive difficulties in this area cause students to develop negative attitudes and emotions as affective reactions, hampering their efforts and achievements. These metacognitive and…

Metacognition, Motivation, and Emotions: Contribution of Self-Regulated Learning to Solving Mathematical Problems

ERIC Educational Resources Information Center

Tzohar-Rozen, Meirav; Kramarski, Bracha

2014-01-01

Mathematical problem solving is one of the most valuable aspects of mathematics education. It is also the most difficult for elementary-school students (Verschaffel, Greer, & De Corte, 2000). Students experience cognitive and metacognitive difficulties in this area and develop negative emotions and poor motivation, which hamper their efforts…

Social cognition and social problem solving abilities in individuals with alcohol use disorder.

PubMed

Schmidt, Tobias; Roser, Patrik; Juckel, Georg; Brüne, Martin; Suchan, Boris; Thoma, Patrizia

2016-11-01

Up to now, little is known about higher order cognitive abilities like social cognition and social problem solving abilities in alcohol-dependent patients. However, impairments in these domains lead to an increased probability for relapse and are thus highly relevant in treatment contexts. This cross-sectional study assessed distinct aspects of social cognition and social problem solving in 31 hospitalized patients with alcohol use disorder (AUD) and 30 matched healthy controls (HC). Three ecologically valid scenario-based tests were used to gauge the ability to infer the mental state of story characters in complicated interpersonal situations, the capacity to select the best problem solving strategy among other less optimal alternatives, and the ability to freely generate appropriate strategies to handle difficult interpersonal conflicts. Standardized tests were used to assess executive function, attention, trait empathy, and memory, and correlations were computed between measures of executive function, attention, trait empathy, and tests of social problem solving. AUD patients generated significantly fewer socially sensitive and practically effective solutions for problematic interpersonal situations than the HC group. Furthermore, patients performed significantly worse when asked to select the best alternative among a list of presented alternatives for scenarios containing sarcastic remarks and had significantly more problems to interpret sarcastic remarks in difficult interpersonal situations. These specific patterns of impairments should be considered in treatment programs addressing impaired social skills in individuals with AUD.

Self-Explaining Steps in Problem-Solving Tasks to Improve Self-Regulation in Secondary Education

ERIC Educational Resources Information Center

Baars, Martine; Leopold, Claudia; Paas, Fred

2018-01-01

The ability to learn in a self-regulated way is important for adolescents' academic achievements. Monitoring one's own learning is a prerequisite skill for successful self-regulated learning. However, accurate monitoring has been found to be difficult for adolescents, especially for learning problem-solving tasks such as can be found in math and…

Classroom-tested Recommendations for Teaching Problem Solving within a Traditional College Course: Genetics.

ERIC Educational Resources Information Center

Smith, Mike U.

Both teachers and students alike acknowledge that genetics and genetics problem-solving are extremely difficult to learn and to teach. Therefore, a number of recommendations for teaching college genetics are offered. Although few of these ideas have as yet been tested in controlled experiments, they are supported by research and experience and may…

"The Strawberry Caper": Using Scenario-Based Problem Solving to Integrate Middle School Science Topics

ERIC Educational Resources Information Center

Gonda, Rebecca L.; DeHart, Kyle; Ashman, Tia-Lynn; Legg, Alison Slinskey

2015-01-01

Achieving a deep understanding of the many topics covered in middle school biology classes is difficult for many students. One way to help students learn these topics is through scenario-based learning, which enhances students' performance. The scenario-based problem-solving module presented here, "The Strawberry Caper," not only…

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

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

NASA Astrophysics Data System (ADS)

Rakkapao, S.; Prasitpong, S.

2018-03-01

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

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.

Reaction Workup Planning: A Structured Flowchart Approach, Exemplified in Difficult Aqueous Workup of Hydrophilic Products

ERIC Educational Resources Information Center

Hill, George B.; Sweeney, Joseph B.

2015-01-01

Reaction workup can be a complex problem for those facing novel synthesis of difficult compounds for the first time. Workup problem solving by systematic thinking should be inculcated as mid-graduate-level is reached. A structured approach is proposed, building decision tree flowcharts to analyze challenges, and an exemplar flowchart is presented…

Automation and adaptation: Nurses' problem-solving behavior following the implementation of bar coded medication administration technology.

PubMed

Holden, Richard J; Rivera-Rodriguez, A Joy; Faye, Héléne; Scanlon, Matthew C; Karsh, Ben-Tzion

2013-08-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses' operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA's impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians' work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign.

Automation and adaptation: Nurses’ problem-solving behavior following the implementation of bar coded medication administration technology

PubMed Central

Holden, Richard J.; Rivera-Rodriguez, A. Joy; Faye, Héléne; Scanlon, Matthew C.; Karsh, Ben-Tzion

2012-01-01

The most common change facing nurses today is new technology, particularly bar coded medication administration technology (BCMA). However, there is a dearth of knowledge on how BCMA alters nursing work. This study investigated how BCMA technology affected nursing work, particularly nurses’ operational problem-solving behavior. Cognitive systems engineering observations and interviews were conducted after the implementation of BCMA in three nursing units of a freestanding pediatric hospital. Problem-solving behavior, associated problems, and goals, were specifically defined and extracted from observed episodes of care. Three broad themes regarding BCMA’s impact on problem solving were identified. First, BCMA allowed nurses to invent new problem-solving behavior to deal with pre-existing problems. Second, BCMA made it difficult or impossible to apply some problem-solving behaviors that were commonly used pre-BCMA, often requiring nurses to use potentially risky workarounds to achieve their goals. Third, BCMA created new problems that nurses were either able to solve using familiar or novel problem-solving behaviors, or unable to solve effectively. Results from this study shed light on hidden hazards and suggest three critical design needs: (1) ecologically valid design; (2) anticipatory control; and (3) basic usability. Principled studies of the actual nature of clinicians’ work, including problem solving, are necessary to uncover hidden hazards and to inform health information technology design and redesign. PMID:24443642

Drilling Regolith: Why Is It So Difficult?

NASA Astrophysics Data System (ADS)

Schmitt, H. H.

2017-10-01

The Apollo rotary percussive drill system penetrated the lunar regolith with reasonable efficiency; however, extraction of the drill core stem proved to be very difficult on all three missions. Retractable drill stem flutes may solve this problem.

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.

Advancing water resource management in agricultural, rural, and urbanizing watersheds: Enhancing University involvement

USDA-ARS?s Scientific Manuscript database

In this research editorial we make four points relative to solving water resource issues: (1) they are complex problems and difficult to solve, (2) some progress has been made on solving these issues, (3) external non-stationary drivers such as land use changes, climate change and variability, and s...

The Social Essentials of Learning: An Experimental Investigation of Collaborative Problem Solving and Knowledge Construction in Mathematics Classrooms in Australia and China

ERIC Educational Resources Information Center

Chan, Man Ching Esther; Clarke, David; Cao, Yiming

2018-01-01

Interactive problem solving and learning are priorities in contemporary education, but these complex processes have proved difficult to research. This project addresses the question "How do we optimise social interaction for the promotion of learning in a mathematics classroom?" Employing the logic of multi-theoretic research design,…

Teachers' Conceptualization and Actual Practice in the Student Evaluation Process at the Upper Secondary School Level in Japan, Focusing on Problem Solving Skills.

ERIC Educational Resources Information Center

Wai, Nu Nu; Hirakawa, Yukiko

2001-01-01

Studied the participation and performance of upper secondary school teachers in Japan through surveys completed by 360 Geography teachers. Findings suggest that the importance of developing problem-solving skills is widely recognized among these teachers. Implementing training in such skills is much more difficult. Developing effective teaching…

Parameter estimation in astronomy through application of the likelihood ratio. [satellite data analysis techniques

NASA Technical Reports Server (NTRS)

Cash, W.

1979-01-01

Many problems in the experimental estimation of parameters for models can be solved through use of the likelihood ratio test. Applications of the likelihood ratio, with particular attention to photon counting experiments, are discussed. The procedures presented solve a greater range of problems than those currently in use, yet are no more difficult to apply. The procedures are proved analytically, and examples from current problems in astronomy are discussed.

Problem of glider models

NASA Technical Reports Server (NTRS)

Lippisch, Espenlaub

1922-01-01

Any one endeavoring to solve the problem of soaring flight is confronted not only by structural difficulties, but also by the often far more difficult aerodynamic problem of flight properties and efficiency, which can only be determined by experimenting with the finished glider.

Using the Competent Small Group Communicator Instrument to Assess Group Performance in the Classroom.

ERIC Educational Resources Information Center

Albert, Lawrence S.

If being a competent small group problem solver is difficult, it is even more difficult to impart those competencies to others. Unlike athletic coaches who are near their players during the real game, teachers of small group communication are not typically present for on-the-spot coaching when their students are doing their problem solving. That…

Teaching basic science to optimize transfer.

PubMed

Norman, Geoff

2009-09-01

Basic science teachers share the concern that much of what they teach is soon forgotten. Although some evidence suggests that relatively little basic science is forgotten, it may not appear so, as students commonly have difficulty using these concepts to solve or explain clinical problems: This phenomenon, using a concept learned in one context to solve a problem in a different context, is known to cognitive psychologists as transfer. The psychology literature shows that transfer is difficult; typically, even though students may know a concept, fewer than 30% will be able to use it to solve new problems. However a number of strategies to improve transfer can be adopted at the time of initial teaching of the concept, in the use of exemplars to illustrate the concept, and in practice with additional problems. In this article, we review the literature in psychology to identify practical strategies to improve transfer. Critical review of psychology literature to identify factors that enhance or impede transfer. There are a number of strategies available to teachers to facilitate transfer. These include active problem-solving at the time of initial learning, imbedding the concept in a problem context, using everyday analogies, and critically, practice with multiple dissimilar problems. Further, mixed practice, where problems illustrating different concepts are mixed together, and distributed practice, spread out over time, can result in significant and large gains. Transfer is difficult, but specific teaching strategies can enhance this skill by factors of two or three.

Some Issues about the Introduction of First Concepts in Linear Algebra during Tutorial Sessions at the Beginning of University

ERIC Educational Resources Information Center

Grenier-Boley, Nicolas

2014-01-01

Certain mathematical concepts were not introduced to solve a specific open problem but rather to solve different problems with the same tools in an economic formal way or to unify several approaches: such concepts, as some of those of linear algebra, are presumably difficult to introduce to students as they are potentially interwoven with many…

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.

Must "Hard Problems" Be Hard?

ERIC Educational Resources Information Center

Kolata, Gina

1985-01-01

To determine how hard it is for computers to solve problems, researchers have classified groups of problems (polynomial hierarchy) according to how much time they seem to require for their solutions. A difficult and complex proof is offered which shows that a combinatorial approach (using Boolean circuits) may resolve the problem. (JN)

Designs of goal-free problems for trigonometry learning

NASA Astrophysics Data System (ADS)

Retnowati, E.; Maulidya, S. R.

2018-03-01

This paper describes the designs of goal-free problems particularly for trigonometry, which may be considered a difficult topic for high school students.Goal-free problem is an instructional design developed based on a Cognitive load theory (CLT). Within the design, instead of asking students to solve a specific goal of a mathematics problem, the instruction is to solve as many Pythagoras as possible. It was assumed that for novice students, goal-free problems encourage students to pay attention more to the given information and the mathematical principles that can be applied to reveal the unknown variables. Hence, students develop more structured knowledge while solving the goal-free problems. The resulted design may be used in regular mathematics classroom with some adjustment on the difficulty level and the allocated lesson time.

Noticing relevant problem features: activating prior knowledge affects problem solving by guiding encoding

PubMed Central

Crooks, Noelle M.; Alibali, Martha W.

2013-01-01

This study investigated whether activating elements of prior knowledge can influence how problem solvers encode and solve simple mathematical equivalence problems (e.g., 3 + 4 + 5 = 3 + __). Past work has shown that such problems are difficult for elementary school students (McNeil and Alibali, 2000). One possible reason is that children's experiences in math classes may encourage them to think about equations in ways that are ultimately detrimental. Specifically, children learn a set of patterns that are potentially problematic (McNeil and Alibali, 2005a): the perceptual pattern that all equations follow an “operations = answer” format, the conceptual pattern that the equal sign means “calculate the total”, and the procedural pattern that the correct way to solve an equation is to perform all of the given operations on all of the given numbers. Upon viewing an equivalence problem, knowledge of these patterns may be reactivated, leading to incorrect problem solving. We hypothesized that these patterns may negatively affect problem solving by influencing what people encode about a problem. To test this hypothesis in children would require strengthening their misconceptions, and this could be detrimental to their mathematical development. Therefore, we tested this hypothesis in undergraduate participants. Participants completed either control tasks or tasks that activated their knowledge of the three patterns, and were then asked to reconstruct and solve a set of equivalence problems. Participants in the knowledge activation condition encoded the problems less well than control participants. They also made more errors in solving the problems, and their errors resembled the errors children make when solving equivalence problems. Moreover, encoding performance mediated the effect of knowledge activation on equivalence problem solving. Thus, one way in which experience may affect equivalence problem solving is by influencing what students encode about the equations. PMID:24324454

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.

When Your Child Is Difficult: Solve Your Toughest Child-Raising Problems with a Four-Step Plan That Works.

ERIC Educational Resources Information Center

Silberman, Mel

Written for parents, this book discusses four steps for dealing with children's difficult behavior. The book is divided into two parts. Part 1, "The Building Blocks," discusses baseline perspectives parents need to establish in order to effectively deal with difficult behavior. Topics covered include: (1) parents' dual roles as caregivers and…

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…

Brain Stretchers, Book 3 - Advanced.

ERIC Educational Resources Information Center

Stickels, Terry H.

Current thinking suggests that solving brainteasing puzzles uses the same critical thinking skills needed to solve difficult math, science, and business problems. This book is a non-intimidating exploration of the wonderful powers of the mind with an emphasis on the joy of thinking and learning. It contains 100 puzzles, presented in order of…

Fixing Ganache: Another Real-Life Use for Algebra

ERIC Educational Resources Information Center

Kalman, Adam M.

2011-01-01

This article presents a real-world application of proportional reasoning and equation solving. The author describes how students adjust ingredient amounts in a recipe for chocolate ganache. Using this real-world scenario provided students an opportunity to solve a difficult and nonstandard algebra problem, a lot of practice with fractions, a…

Cognitive Load Mediates the Effect of Emotion on Analytical Thinking.

PubMed

Trémolière, Bastien; Gagnon, Marie-Ève; Blanchette, Isabelle

2016-11-01

Although the detrimental effect of emotion on reasoning has been evidenced many times, the cognitive mechanism underlying this effect remains unclear. In the present paper, we explore the cognitive load hypothesis as a potential explanation. In an experiment, participants solved syllogistic reasoning problems with either neutral or emotional contents. Participants were also presented with a secondary task, for which the difficult version requires the mobilization of cognitive resources to be correctly solved. Participants performed overall worse and took longer on emotional problems than on neutral problems. Performance on the secondary task, in the difficult version, was poorer when participants were reasoning about emotional, compared to neutral contents, consistent with the idea that processing emotion requires more cognitive resources. Taken together, the findings afford evidence that the deleterious effect of emotion on reasoning is mediated by cognitive load.

Labour Market Policies.

ERIC Educational Resources Information Center

Danielsen, Reidar

Skilled labor has always been difficult to recruit, and in a tight labor market unskilled, low-paying jobs with low status are also difficult to fill. Recruitment from outside seems necessary to satisfy demands, but migration creates at least as many problems as it solves. The consumption of theoretical training through the university level (a…

Use of artificial bee colonies algorithm as numerical approximation of differential equations solution

NASA Astrophysics Data System (ADS)

Fikri, Fariz Fahmi; Nuraini, Nuning

2018-03-01

The differential equation is one of the branches in mathematics which is closely related to human life problems. Some problems that occur in our life can be modeled into differential equations as well as systems of differential equations such as the Lotka-Volterra model and SIR model. Therefore, solving a problem of differential equations is very important. Some differential equations are difficult to solve, so numerical methods are needed to solve that problems. Some numerical methods for solving differential equations that have been widely used are Euler Method, Heun Method, Runge-Kutta and others. However, some of these methods still have some restrictions that cause the method cannot be used to solve more complex problems such as an evaluation interval that we cannot change freely. New methods are needed to improve that problems. One of the method that can be used is the artificial bees colony algorithm. This algorithm is one of metaheuristic algorithm method, which can come out from local search space and do exploration in solution search space so that will get better solution than other method.

Social problem solving in carers of young people with a first episode of psychosis: a randomized controlled trial.

PubMed

McCann, Terence V; Cotton, Sue M; Lubman, Dan I

2017-08-01

Caring for young people with first-episode psychosis is difficult and demanding, and has detrimental effects on carers' well-being, with few evidence-based resources available to assist carers to deal with the problems they are confronted with in this situation. We aimed to examine if completion of a self-directed problem-solving bibliotherapy by first-time carers of young people with first-episode psychosis improved their social problem solving compared with carers who only received treatment as usual. A randomized controlled trial was carried out through two early intervention psychosis services in Melbourne, Australia. A sample of 124 carers were randomized to problem-solving bibliotherapy or treatment as usual. Participants were assessed at baseline, 6- and 16-week follow-up. Intent-to-treat analyses were used and showed that recipients of bibliotherapy had greater social problem-solving abilities than those receiving treatment as usual, and these effects were maintained at both follow-up time points. Our findings affirm that bibliotherapy, as a low-cost complement to treatment as usual for carers, had some effects in improving their problem-solving skills when addressing problems related to the care and support of young people with first-episode psychosis. © 2015 The Authors. Early Intervention in Psychiatry published by Wiley Publishing Asia Pty Ltd.

Constraint Programming to Solve Maximal Density Still Life

NASA Astrophysics Data System (ADS)

Chu, Geoffrey; Petrie, Karen Elizabeth; Yorke-Smith, Neil

The Maximum Density Still Life problem fills a finite Game of Life board with a stable pattern of cells that has as many live cells as possible. Although simple to state, this problem is computationally challenging for any but the smallest sizes of board. Especially difficult is to prove that the maximum number of live cells has been found. Various approaches have been employed. The most successful are approaches based on Constraint Programming (CP). We describe the Maximum Density Still Life problem, introduce the concept of constraint programming, give an overview on how the problem can be modelled and solved with CP, and report on best-known results for the problem.

Better without (lateral) frontal cortex? Insight problems solved by frontal patients.

PubMed

Reverberi, Carlo; Toraldo, Alessio; D'Agostini, Serena; Skrap, Miran

2005-12-01

A recently proposed theory on frontal lobe functions claims that the prefrontal cortex, particularly its dorso-lateral aspect, is crucial in defining a set of responses suitable for a particular task, and biasing these for selection. This activity is carried out for virtually any kind of non-routine tasks, without distinction of content. The aim of this study is to test the prediction of Frith's 'sculpting the response space' hypothesis by means of an 'insight' problem-solving task, namely the matchstick arithmetic task. Starting from Knoblich et al.'s interpretation for the failure of healthy controls to solve the matchstick problem, and Frith's theory on the role of dorsolateral frontal cortex, we derived the counterintuitive prediction that patients with focal damage to the lateral frontal cortex should perform better than a group of healthy participants on this rather difficult task. We administered the matchstick task to 35 patients (aged 26-65 years) with a single focal brain lesion as determined by a CT or an MRI scan, and to 23 healthy participants (aged 34-62 years). The findings seemed in line with theoretical predictions. While only 43% of healthy participants could solve the most difficult matchstick problems ('type C'), 82% of lateral frontal patients did so (Fisher's exact test, P < 0.05). In conclusion, the combination of Frith's and Knoblich et al.'s theories was corroborated.

Integrating Numerical Computation into the Modeling Instruction Curriculum

ERIC Educational Resources Information Center

Caballero, Marcos D.; Burk, John B.; Aiken, John M.; Thoms, Brian D.; Douglas, Scott S.; Scanlon, Erin M.; Schatz, Michael F.

2014-01-01

Numerical computation (the use of a computer to solve, simulate, or visualize a physical problem) has fundamentally changed the way scientific research is done. Systems that are too difficult to solve in closed form are probed using computation. Experiments that are impossible to perform in the laboratory are studied numerically. Consequently, in…

Young Children "Solve for X" Using the Approximate Number System

ERIC Educational Resources Information Center

Kibbe, Melissa M.; Feigenson, Lisa

2015-01-01

The Approximate Number System (ANS) supports basic arithmetic computation in early childhood, but it is unclear whether the ANS also supports the more complex computations introduced later in formal education. "Solving for x" in addend-unknown problems is notoriously difficult for children, who often struggle with these types of problems…

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).

Trading a Problem-solving Task

NASA Astrophysics Data System (ADS)

Matsubara, Shigeo

This paper focuses on a task allocation problem, especially cases where the task is to find a solution in a search problem or a constraint satisfaction problem. If the search problem is hard to solve, a contractor may fail to find a solution. Here, the more computational resources such as the CPU time the contractor invests in solving the search problem, the more a solution is likely to be found. This brings about a new problem that a contractee has to find an appropriate level of the quality in a task achievement as well as to find an efficient allocation of a task among contractors. For example, if the contractee asks the contractor to find a solution with certainty, the payment from the contractee to the contractor may exceed the contractee's benefit from obtaining a solution, which discourages the contractee from trading a task. However, solving this problem is difficult because the contractee cannot ascertain the contractor's problem-solving ability such as the amount of available resources and knowledge (e.g. algorithms, heuristics) or monitor what amount of resources are actually invested in solving the allocated task. To solve this problem, we propose a task allocation mechanism that is able to choose an appropriate level of the quality in a task achievement and prove that this mechanism guarantees that each contractor reveals its true information. Moreover, we show that our mechanism can increase the contractee's utility compared with a simple auction mechanism by using computer simulation.

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.

Performance impact of mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems.

PubMed

Liu, Chun; Kroll, Andreas

2016-01-01

Multi-robot task allocation determines the task sequence and distribution for a group of robots in multi-robot systems, which is one of constrained combinatorial optimization problems and more complex in case of cooperative tasks because they introduce additional spatial and temporal constraints. To solve multi-robot task allocation problems with cooperative tasks efficiently, a subpopulation-based genetic algorithm, a crossover-free genetic algorithm employing mutation operators and elitism selection in each subpopulation, is developed in this paper. Moreover, the impact of mutation operators (swap, insertion, inversion, displacement, and their various combinations) is analyzed when solving several industrial plant inspection problems. The experimental results show that: (1) the proposed genetic algorithm can obtain better solutions than the tested binary tournament genetic algorithm with partially mapped crossover; (2) inversion mutation performs better than other tested mutation operators when solving problems without cooperative tasks, and the swap-inversion combination performs better than other tested mutation operators/combinations when solving problems with cooperative tasks. As it is difficult to produce all desired effects with a single mutation operator, using multiple mutation operators (including both inversion and swap) is suggested when solving similar combinatorial optimization problems.

Identifying Common Mathematical Misconceptions from Actions in Educational Video Games. CRESST Report 838

ERIC Educational Resources Information Center

Kerr, Deirdre

2014-01-01

Educational video games provide an opportunity for students to interact with and explore complex representations of academic content and allow for the examination of problem-solving strategies and mistakes that can be difficult to capture in more traditional environments. However, data from such games are notoriously difficult to analyze. This…

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.

A novel heuristic algorithm for capacitated vehicle routing problem

NASA Astrophysics Data System (ADS)

Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre

2017-09-01

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

A noisy chaotic neural network for solving combinatorial optimization problems: stochastic chaotic simulated annealing.

PubMed

Wang, Lipo; Li, Sa; Tian, Fuyu; Fu, Xiuju

2004-10-01

Recently Chen and Aihara have demonstrated both experimentally and mathematically that their chaotic simulated annealing (CSA) has better search ability for solving combinatorial optimization problems compared to both the Hopfield-Tank approach and stochastic simulated annealing (SSA). However, CSA may not find a globally optimal solution no matter how slowly annealing is carried out, because the chaotic dynamics are completely deterministic. In contrast, SSA tends to settle down to a global optimum if the temperature is reduced sufficiently slowly. Here we combine the best features of both SSA and CSA, thereby proposing a new approach for solving optimization problems, i.e., stochastic chaotic simulated annealing, by using a noisy chaotic neural network. We show the effectiveness of this new approach with two difficult combinatorial optimization problems, i.e., a traveling salesman problem and a channel assignment problem for cellular mobile communications.

Graph pyramids as models of human problem solving

NASA Astrophysics Data System (ADS)

Pizlo, Zygmunt; Li, Zheng

2004-05-01

Prior theories have assumed that human problem solving involves estimating distances among states and performing search through the problem space. The role of mental representation in those theories was minimal. Results of our recent experiments suggest that humans are able to solve some difficult problems quickly and accurately. Specifically, in solving these problems humans do not seem to rely on distances or on search. It is quite clear that producing good solutions without performing search requires a very effective mental representation. In this paper we concentrate on studying the nature of this representation. Our theory takes the form of a graph pyramid. To verify the psychological plausibility of this theory we tested subjects in a Euclidean Traveling Salesman Problem in the presence of obstacles. The role of the number and size of obstacles was tested for problems with 6-50 cities. We analyzed the effect of experimental conditions on solution time per city and on solution error. The main result is that time per city is systematically affected only by the size of obstacles, but not by their number, or by the number of cities.

Focus group discussion in mathematical physics learning

NASA Astrophysics Data System (ADS)

Ellianawati; Rudiana, D.; Sabandar, J.; Subali, B.

2018-03-01

The Focus Group Discussion (FGD) activity in Mathematical Physics learning has helped students perform the stages of problem solving reflectively. The FGD implementation was conducted to explore the problems and find the right strategy to improve the students' ability to solve the problem accurately which is one of reflective thinking component that has been difficult to improve. The research method used is descriptive qualitative by using single subject response in Physics student. During the FGD process, one student was observed of her reflective thinking development in solving the physics problem. The strategy chosen in the discussion activity was the Cognitive Apprenticeship-Instruction (CA-I) syntax. Based on the results of this study, it is obtained the information that after going through a series of stages of discussion, the students' reflective thinking skills is increased significantly. The scaffolding stage in the CA-I model plays an important role in the process of solving physics problems accurately. Students are able to recognize and formulate problems by describing problem sketches, identifying the variables involved, applying mathematical equations that accord to physics concepts, executing accurately, and applying evaluation by explaining the solution to various contexts.

Dealing with the difficult older patient.

PubMed

Laurence, M K

1986-05-15

Physicians are often asked to intervene when elderly patients in acute or long-term care facilities are disruptive, demanding or abusive. Though medication may be the immediate response, it often fails to solve the problem, which, being situational and behavioural, calls for a situational and behavioural solution. An organized approach to solving such problems is presented that takes into account the interactions among the patient, family, staff, setting and circumstances. The role of the physician as leader in the process is also discussed.

Science of the science, drug discovery and artificial neural networks.

PubMed

Patel, Jigneshkumar

2013-03-01

Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

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

PubMed

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

2011-09-02

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

THE APPLICATION OF ENGLISH-WORD MORPHOLOGY TO AUTOMATIC INDEXING AND EXTRACTING. ANNUAL SUMMARY REPORT.

ERIC Educational Resources Information Center

DOLBY, J.L.; AND OTHERS

THE STUDY IS CONCERNED WITH THE LINGUISTIC PROBLEM INVOLVED IN TEXT COMPRESSION--EXTRACTING, INDEXING, AND THE AUTOMATIC CREATION OF SPECIAL-PURPOSE CITATION DICTIONARIES. IN SPITE OF EARLY SUCCESS IN USING LARGE-SCALE COMPUTERS TO AUTOMATE CERTAIN HUMAN TASKS, THESE PROBLEMS REMAIN AMONG THE MOST DIFFICULT TO SOLVE. ESSENTIALLY, THE PROBLEM IS TO…

Learning to See the (W)holes

ERIC Educational Resources Information Center

Burns, Barbara A.; Jordan, Thomas M.

2006-01-01

Business managers are faced with complex decisions involving a wide range of issues--technical, social, environmental, and financial--and their interaction. Our education system focuses heavily on presenting structured problems and teaching students to apply a set of tools or methods to solve these problems. Yet the most difficult thing to teach…

Teaching Database Design with Constraint-Based Tutors

ERIC Educational Resources Information Center

Mitrovic, Antonija; Suraweera, Pramuditha

2016-01-01

Design tasks are difficult to teach, due to large, unstructured solution spaces, underspecified problems, non-existent problem solving algorithms and stopping criteria. In this paper, we comment on our approach to develop KERMIT, a constraint-based tutor that taught database design. In later work, we re-implemented KERMIT as EER-Tutor, and…

Sociodrama: Group Creative Problem Solving in Action.

ERIC Educational Resources Information Center

Riley, John F.

1990-01-01

Sociodrama is presented as a structured, yet flexible, method of encouraging the use of creative thinking to examine a difficult problem. An example illustrates the steps involved in putting sociodrama into action. Production techniques useful in sociodrama include the soliloquy, double, role reversal, magic shop, unity of opposites, and audience…

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons

PubMed Central

Jonke, Zeno; Habenschuss, Stefan; Maass, Wolfgang

2016-01-01

Network of neurons in the brain apply—unlike processors in our current generation of computer hardware—an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event at a particular point in time. Such spike-based computations promise to be substantially more power-efficient than traditional clocked processing schemes. However, it turns out to be surprisingly difficult to design networks of spiking neurons that can solve difficult computational problems on the level of single spikes, rather than rates of spikes. We present here a new method for designing networks of spiking neurons via an energy function. Furthermore, we show how the energy function of a network of stochastically firing neurons can be shaped in a transparent manner by composing the networks of simple stereotypical network motifs. We show that this design approach enables networks of spiking neurons to produce approximate solutions to difficult (NP-hard) constraint satisfaction problems from the domains of planning/optimization and verification/logical inference. The resulting networks employ noise as a computational resource. Nevertheless, the timing of spikes plays an essential role in their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines) and Gibbs sampling. PMID:27065785

Autonomous Intersection Management

DTIC Science & Technology

2009-12-01

is irrelevant. Fortunately, researchers are attacking this problem with many techniques. In 2004, Honda introduced an intelligent night vision system...or less a solved problem . The problem itself is not too difficult: there are no pedestrians or cyclists and vehicles travel in the same direction at...organized according to the following subgoals, each of which is a contribution of the thesis. 1. Problem definition First, this thesis contributes a

Nanotechnology: Its Promise and Challenges

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

Colvin, Vicki

2009-05-14

Vicki Colvin of Rice University talks about how nanotechnology-enabled systems, with dimensions on the scale of a billionth of a meter, offer great promise for solving difficult social problems and creating enormous possibilities.

Simultaneous optimization of loading pattern and burnable poison placement for PWRs

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

Alim, F.; Ivanov, K.; Yilmaz, S.

2006-07-01

To solve in-core fuel management optimization problem, GARCO-PSU (Genetic Algorithm Reactor Core Optimization - Pennsylvania State Univ.) is developed. This code is applicable for all types and geometry of PWR core structures with unlimited number of fuel assembly (FA) types in the inventory. For this reason an innovative genetic algorithm is developed with modifying the classical representation of the genotype. In-core fuel management heuristic rules are introduced into GARCO. The core re-load design optimization has two parts, loading pattern (LP) optimization and burnable poison (BP) placement optimization. These parts depend on each other, but it is difficult to solve themore » combined problem due to its large size. Separating the problem into two parts provides a practical way to solve the problem. However, the result of this method does not reflect the real optimal solution. GARCO-PSU achieves to solve LP optimization and BP placement optimization simultaneously in an efficient manner. (authors)« less

Mexican high school students' social representations of mathematics, its teaching and learning

NASA Astrophysics Data System (ADS)

Martínez-Sierra, Gustavo; Miranda-Tirado, Marisa

2015-07-01

This paper reports a qualitative research that identifies Mexican high school students' social representations of mathematics. For this purpose, the social representations of 'mathematics', 'learning mathematics' and 'teaching mathematics' were identified in a group of 50 students. Focus group interviews were carried out in order to obtain the data. The constant comparative style was the strategy used for the data analysis because it allowed the categories to emerge from the data. The students' social representations are: (A) Mathematics is…(1) important for daily life, (2) important for careers and for life, (3) important because it is in everything that surrounds us, (4) a way to solve problems of daily life, (5) calculations and operations with numbers, (6) complex and difficult, (7) exact and (6) a subject that develops thinking skills; (B) To learn mathematics is…(1) to possess knowledge to solve problems, (2) to be able to solve everyday problems, (3) to be able to make calculations and operations, and (4) to think logically to be able to solve problems; and (C) To teach mathematics is…(1) to transmit knowledge, (2) to know to share it, (3) to transmit the reasoning ability, and (4) to show how to solve problems.

EPA Challenges & Prizes

EPA Pesticide Factsheets

EPA is a government leader in tapping the power of contributions from the public to help solve difficult problems that affect the environment and public health. Prize competitions allow federal agencies to pay only for successful solutions.

Preschoolers Grow Their Brains: Shifting Mindsets for Greater Resiliency and Better Problem Solving

ERIC Educational Resources Information Center

Pawlina, Shelby; Stanford, Christie

2011-01-01

Challenges, mistakes, and problems are inherent every day in learning activities and social interactions. How children think about and respond to those difficult situations has an impact on how they see themselves as being able to shape their own learning and on how they handle the next problem that comes their way. Building resilience means…

Initiative Games in Physical Education: A Practical Approach for Teaching Critical Thinking Skills--Part II

ERIC Educational Resources Information Center

Maina, Michael P.; Maina, Julie Schlegel; Hunt, Kevin

2016-01-01

Often students have a difficult time when asked to use critical thinking skills to solve a problem. Perhaps students have a difficult time adjusting because teachers frequently tell them exactly what to do and how to do it. When asked to use critical thinking skills, students may suddenly become confused and discouraged because the teacher no…

Exploiting replication in distributed systems

NASA Technical Reports Server (NTRS)

Birman, Kenneth P.; Joseph, T. A.

1989-01-01

Techniques are examined for replicating data and execution in directly distributed systems: systems in which multiple processes interact directly with one another while continuously respecting constraints on their joint behavior. Directly distributed systems are often required to solve difficult problems, ranging from management of replicated data to dynamic reconfiguration in response to failures. It is shown that these problems reduce to more primitive, order-based consistency problems, which can be solved using primitives such as the reliable broadcast protocols. Moreover, given a system that implements reliable broadcast primitives, a flexible set of high-level tools can be provided for building a wide variety of directly distributed application programs.

Beyond rules: The next generation of expert systems

NASA Technical Reports Server (NTRS)

Ferguson, Jay C.; Wagner, Robert E.

1987-01-01

The PARAGON Representation, Management, and Manipulation system is introduced. The concepts of knowledge representation, knowledge management, and knowledge manipulation are combined in a comprehensive system for solving real world problems requiring high levels of expertise in a real time environment. In most applications the complexity of the problem and the representation used to describe the domain knowledge tend to obscure the information from which solutions are derived. This inhibits the acquisition of domain knowledge verification/validation, places severe constraints on the ability to extend and maintain a knowledge base while making generic problem solving strategies difficult to develop. A unique hybrid system was developed to overcome these traditional limitations.

Some Legal Problems of Satellite Transmission.

ERIC Educational Resources Information Center

Siebert, Fred S.

Now that the technical aspects of satellite transmission have been solved, there remain the more complex and difficult problems of maintaining both order in outer space and the rights of nations and individuals as these rights may be affected by broadcasts transmitted by satellite stations. These broadcasts, whether beamed to a ground station or…

Interesting and Difficult Mathematical Problems: Changing Teachers' Views by Employing Multiple-Solution Tasks

ERIC Educational Resources Information Center

Guberman, Raisa; Leikin, Roza

2013-01-01

The study considers mathematical problem solving to be at the heart of mathematics teaching and learning, while mathematical challenge is a core element of any educational process. The study design addresses the complexity of teachers' knowledge. It is aimed at exploring the development of teachers' mathematical and pedagogical conceptions…

The Effect of Shift-Problem Lessons in the Mathematics Classroom

ERIC Educational Resources Information Center

Palha, Sonia; Dekker, Rijkje; Gravemeijer, Koeno

2015-01-01

It remains difficult to foster problem-solving and mathematical-reasoning capabilities in classrooms where students and teachers are accustomed to the more traditional forms of education. Several studies suggest that this difficulty might be related to the kind of knowledge students acquire in such environments, which could be fragmented and…

Guidance for modeling causes and effects in environmental problem solving

USGS Publications Warehouse

Armour, Carl L.; Williamson, Samuel C.

1988-01-01

Environmental problems are difficult to solve because their causes and effects are not easily understood. When attempts are made to analyze causes and effects, the principal challenge is organization of information into a framework that is logical, technically defensible, and easy to understand and communicate. When decisionmakers attempt to solve complex problems before an adequate cause and effect analysis is performed there are serious risks. These risks include: greater reliance on subjective reasoning, lessened chance for scoping an effective problem solving approach, impaired recognition of the need for supplemental information to attain understanding, increased chance for making unsound decisions, and lessened chance for gaining approval and financial support for a program/ Cause and effect relationships can be modeled. This type of modeling has been applied to various environmental problems, including cumulative impact assessment (Dames and Moore 1981; Meehan and Weber 1985; Williamson et al. 1987; Raley et al. 1988) and evaluation of effects of quarrying (Sheate 1986). This guidance for field users was written because of the current interest in documenting cause-effect logic as a part of ecological problem solving. Principal literature sources relating to the modeling approach are: Riggs and Inouye (1975a, b), Erickson (1981), and United States Office of Personnel Management (1986).

An Extension of Holographic Moiré to Micromechanics

NASA Astrophysics Data System (ADS)

Sciammarella, C. A.; Sciammarella, F. M.

The electronic Holographic Moiré is an ideal tool for micromechanics studies. It does not require a modification of the surface by the introduction of a reference grating. This is of particular advantage when dealing with materials such as solid propellant grains whose chemical nature and surface finish makes the application of a reference grating very difficult. Traditional electronic Holographic Moiré presents some difficult problems when large magnifications are needed and large rigid body motion takes place. This paper presents developments that solves these problems and extends the application of the technique to micromechanics.

Linear complementarity formulation for 3D frictional sliding problems

USGS Publications Warehouse

Kaven, Joern; Hickman, Stephen H.; Davatzes, Nicholas C.; Mutlu, Ovunc

2012-01-01

Frictional sliding on quasi-statically deforming faults and fractures can be modeled efficiently using a linear complementarity formulation. We review the formulation in two dimensions and expand the formulation to three-dimensional problems including problems of orthotropic friction. This formulation accurately reproduces analytical solutions to static Coulomb friction sliding problems. The formulation accounts for opening displacements that can occur near regions of non-planarity even under large confining pressures. Such problems are difficult to solve owing to the coupling of relative displacements and tractions; thus, many geomechanical problems tend to neglect these effects. Simple test cases highlight the importance of including friction and allowing for opening when solving quasi-static fault mechanics models. These results also underscore the importance of considering the effects of non-planarity in modeling processes associated with crustal faulting.

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.

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.

Investigating the psychological resilience, self-confidence and problem-solving skills of midwife candidates.

PubMed

Ertekin Pinar, Sukran; Yildirim, Gulay; Sayin, Neslihan

2018-05-01

The high level of psychological resilience, self-confidence and problem solving skills of midwife candidates play an important role in increasing the quality of health care and in fulfilling their responsibilities towards patients. This study was conducted to investigate the psychological resilience, self-confidence and problem-solving skills of midwife candidates. It is a convenience descriptive quantitative study. Students who study at Health Sciences Faculty in Turkey's Central Anatolia Region. Midwife candidates (N = 270). In collection of data, the Personal Information Form, Psychological Resilience Scale for Adults (PRSA), Self-Confidence Scale (SCS), and Problem Solving Inventory (PSI) were used. There was a negatively moderate-level significant relationship between the Problem Solving Inventory scores and the Psychological Resilience Scale for Adults scores (r = -0.619; p = 0.000), and between Self-Confidence Scale scores (r = -0.524; p = 0.000). There was a positively moderate-level significant relationship between the Psychological Resilience Scale for Adults scores and the Self-Confidence Scale scores (r = 0.583; p = 0.000). There was a statistically significant difference (p < 0.05) between the Problem Solving Inventory and the Psychological Resilience Scale for Adults scores according to getting support in a difficult situation. As psychological resilience and self-confidence levels increase, problem-solving skills increase; additionally, as self-confidence increases, psychological resilience increases too. Psychological resilience, self-confidence, and problem-solving skills of midwife candidates in their first-year of studies are higher than those who are in their fourth year. Self-confidence and psychological resilience of midwife candidates aged between 17 and 21, self-confidence and problem solving skills of residents of city centers, psychological resilience of those who perceive their monthly income as sufficient are high. Psychological resilience and problem-solving skills for midwife candidates who receive social support are also high. The fact that levels of self-confidence, problem-solving skills and psychological resilience of fourth-year students are found to be low presents a situation that should be taken into consideration. Copyright © 2018 Elsevier Ltd. All rights reserved.

Probabilistic data integration and computational complexity

NASA Astrophysics Data System (ADS)

Hansen, T. M.; Cordua, K. S.; Mosegaard, K.

2016-12-01

Inverse problems in Earth Sciences typically refer to the problem of inferring information about properties of the Earth from observations of geophysical data (the result of nature's solution to the `forward' problem). This problem can be formulated more generally as a problem of `integration of information'. A probabilistic formulation of data integration is in principle simple: If all information available (from e.g. geology, geophysics, remote sensing, chemistry…) can be quantified probabilistically, then different algorithms exist that allow solving the data integration problem either through an analytical description of the combined probability function, or sampling the probability function. In practice however, probabilistic based data integration may not be easy to apply successfully. This may be related to the use of sampling methods, which are known to be computationally costly. But, another source of computational complexity is related to how the individual types of information are quantified. In one case a data integration problem is demonstrated where the goal is to determine the existence of buried channels in Denmark, based on multiple sources of geo-information. Due to one type of information being too informative (and hence conflicting), this leads to a difficult sampling problems with unrealistic uncertainty. Resolving this conflict prior to data integration, leads to an easy data integration problem, with no biases. In another case it is demonstrated how imperfections in the description of the geophysical forward model (related to solving the wave-equation) can lead to a difficult data integration problem, with severe bias in the results. If the modeling error is accounted for, the data integration problems becomes relatively easy, with no apparent biases. Both examples demonstrate that biased information can have a dramatic effect on the computational efficiency solving a data integration problem and lead to biased results, and under-estimation of uncertainty. However, in both examples, one can also analyze the performance of the sampling methods used to solve the data integration problem to indicate the existence of biased information. This can be used actively to avoid biases in the available information and subsequently in the final uncertainty evaluation.

Urban African American Pre-Adolescent Social Problem Solving Skills: Family Influences and Association with Exposure to Situations of Sexual Possibility

PubMed Central

Traube, Dorian E.; Chasse, Kelly Taber; McKay, Mary M.; Bhorade, Anjali M.; Paikoff, Roberta; Young, Stacie D.

2010-01-01

SUMMARY The results of two studies focusing on the social problem solving skills of African American preadolescent youth are detailed. In the first study data from a sample of 150 African American children, ages 9 to 11 years, was used to examine the association between type of youth social problem solving approaches applied to hypothetical risk situations and time spent in unsupervised peer situations of sexual possibility. Findings revealed that children with more exposure to sexual possibility situations generated a wider range of social problem solving strategies, but these approaches tended to be unrealistic and ambiguous. Further, there was a positive association between the amount of time spent unsupervised and youth difficulty formulating a definitive response to hypothetical peer pressure situations. Children with less exposure to sexual possibility situations tended to be more aggressive when approaching situations of peer pressure. In the second study, data from a non-overlapping sample of 164 urban, African American adult caregivers and their 9 to 11 year old children was examined in order to explore the associations between child gender, family-level factors including family communication frequency and intensity, time spent in situations of sexual possibility, and youth social problem solving approaches. Results revealed that children were frequently using constructive problem solving and help seeking behaviors when confronted by difficult social situations and that there was a significant relationship between the frequency and intensity of parent child communication and youth help seeking social problem solving approaches. Implications for research and family-based interventions are highlighted. PMID:20871790

SOIL AND SEDIMENT SAMPLING METHODS

EPA Science Inventory

The EPA Office of Solid Waste and Emergency Response's (OSWER) Office of Superfund Remediation and Technology Innovation (OSRTI) needs innovative methods and techniques to solve new and difficult sampling and analytical problems found at the numerous Superfund sites throughout th...

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.

Practical Math Skills: Situations--Strategies--Solutions. Intermediate Level. Grades 4-5-6.

ERIC Educational Resources Information Center

Duncan, Jim

This material is a supplement to existing mathematics programs for young learners. The activities presented are based on assumptions about the young problem solver which are difficult to address in standard mathematics texts. In these pages it is assumed that each learner brings to the problem-solving effort a very personal experience base and a…

Analysis of Learning Behavior in a Flipped Programing Classroom Adopting Problem-Solving Strategies

ERIC Educational Resources Information Center

Chiang, Tosti Hsu-Cheng

2017-01-01

Programing is difficult for beginners because they need to learn the new language of computers. Developing software, especially complex software, is bound to result in problems, frustration, and the need to think in new ways. Identifying the learning behavior behind programing by way of empirical studies can help beginners learn more easily. In…

New Results in Astrodynamics Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Coverstone-Carroll, V.; Hartmann, J. W.; Williams, S. N.; Mason, W. J.

1998-01-01

Generic algorithms have gained popularity as an effective procedure for obtaining solutions to traditionally difficult space mission optimization problems. In this paper, a brief survey of the use of genetic algorithms to solve astrodynamics problems is presented and is followed by new results obtained from applying a Pareto genetic algorithm to the optimization of low-thrust interplanetary spacecraft missions.

Towards Detection of Learner Misconceptions in a Medical Learning Environment: A Subgroup Discovery Approach

ERIC Educational Resources Information Center

Poitras, Eric G.; Doleck, Tenzin; Lajoie, Susanne P.

2018-01-01

Ill-structured problems, by definition, have multiple paths to a solution and are multifaceted making automated assessment and feedback a difficult challenge. Diagnostic reasoning about medical cases meet the criteria of ill-structured problem solving since there are multiple solution paths. The goal of this study was to develop an adaptive…

"Growing" Education in Difficult Environments Promoting Problem Solving: A Case from Palestine

ERIC Educational Resources Information Center

Jabr, Dua

2009-01-01

This paper presents a collaborative educational experiment "The Death of the Dead Sea: A Problem Based Learning" that was applied in two governmental high schools in Ramallah, Palestine in the school year 2006-2007. The students' role was to raise awareness to the phenomenon of the saltiest lake that shrinks towards extinction. In spite…

A Step-by-Step Guide to Tier 2 Behavioral Progress Monitoring

ERIC Educational Resources Information Center

Bruhn, Allison L.; McDaniel, Sara C.; Rila, Ashley; Estrapala, Sara

2018-01-01

Students who are at risk for or show low-intensity behavioral problems may need targeted, Tier 2 interventions. Often, Tier 2 problem-solving teams are charged with monitoring student responsiveness to intervention. This process may be difficult for those who are not trained in data collection and analysis procedures. To aid practitioners in these…

Transforming a Business Statistics Course with Just-in-Time Teaching

ERIC Educational Resources Information Center

Bangs, Joann

2012-01-01

This paper describes changing the way a business statistics course is taught through the use of just-in-time teaching methods. Implementing this method allowed for more time in the class to be spent focused on problem solving, resulting in students being able to handle more difficult problems. Students' perceptions of the just-in-time assignments…

Competences of Mathematical Modelling of High School Students

ERIC Educational Resources Information Center

Sekerak, Josef

2010-01-01

Thanks to technological progress the world becomes more and more complicated. People stand in front of new and difficult problems that need to be solved. These are problems, the solutions of which are not universal, and cannot be learned. Many solutions require specific data that cannot be learned, as new data is part of the ongoing generation of…

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

Baker, Kyri; Toomey, Bridget

Evolving power systems with increasing levels of stochasticity call for a need to solve optimal power flow problems with large quantities of random variables. Weather forecasts, electricity prices, and shifting load patterns introduce higher levels of uncertainty and can yield optimization problems that are difficult to solve in an efficient manner. Solution methods for single chance constraints in optimal power flow problems have been considered in the literature, ensuring single constraints are satisfied with a prescribed probability; however, joint chance constraints, ensuring multiple constraints are simultaneously satisfied, have predominantly been solved via scenario-based approaches or by utilizing Boole's inequality asmore » an upper bound. In this paper, joint chance constraints are used to solve an AC optimal power flow problem while preventing overvoltages in distribution grids under high penetrations of photovoltaic systems. A tighter version of Boole's inequality is derived and used to provide a new upper bound on the joint chance constraint, and simulation results are shown demonstrating the benefit of the proposed upper bound. The new framework allows for a less conservative and more computationally efficient solution to considering joint chance constraints, specifically regarding preventing overvoltages.« less

Model-Based Optimal Experimental Design for Complex Physical Systems

DTIC Science & Technology

2015-12-03

for public release. magnitude reduction in estimator error required to make solving the exact optimal design problem tractable. Instead of using a naive...for designing a sequence of experiments uses suboptimal approaches: batch design that has no feedback, or greedy ( myopic ) design that optimally...approved for public release. Equation 1 is difficult to solve directly, but can be expressed in an equivalent form using the principle of dynamic programming

Heterogeneous quantum computing for satellite constellation optimization: solving the weighted k-clique problem

NASA Astrophysics Data System (ADS)

Bass, Gideon; Tomlin, Casey; Kumar, Vaibhaw; Rihaczek, Pete; Dulny, Joseph, III

2018-04-01

NP-hard optimization problems scale very rapidly with problem size, becoming unsolvable with brute force methods, even with supercomputing resources. Typically, such problems have been approximated with heuristics. However, these methods still take a long time and are not guaranteed to find an optimal solution. Quantum computing offers the possibility of producing significant speed-up and improved solution quality. Current quantum annealing (QA) devices are designed to solve difficult optimization problems, but they are limited by hardware size and qubit connectivity restrictions. We present a novel heterogeneous computing stack that combines QA and classical machine learning, allowing the use of QA on problems larger than the hardware limits of the quantum device. These results represent experiments on a real-world problem represented by the weighted k-clique problem. Through this experiment, we provide insight into the state of quantum machine learning.

Design of Intelligent Power Supply System for Expressway Tunnel

NASA Astrophysics Data System (ADS)

Wang, Li; Li, Yutong; Lin, Zimian

2018-01-01

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

Levels of Simplification. The Use of Assumptions, Restrictions, and Constraints in Engineering Analysis.

ERIC Educational Resources Information Center

Whitaker, Stephen

1988-01-01

Describes the use of assumptions, restrictions, and constraints in solving difficult analytical problems in engineering. Uses the Navier-Stokes equations as examples to demonstrate use, derivations, advantages, and disadvantages of the technique. (RT)

A connectionist model for diagnostic problem solving

NASA Technical Reports Server (NTRS)

Peng, Yun; Reggia, James A.

1989-01-01

A competition-based connectionist model for solving diagnostic problems is described. The problems considered are computationally difficult in that (1) multiple disorders may occur simultaneously and (2) a global optimum in the space exponential to the total number of possible disorders is sought as a solution. The diagnostic problem is treated as a nonlinear optimization problem, and global optimization criteria are decomposed into local criteria governing node activation updating in the connectionist model. Nodes representing disorders compete with each other to account for each individual manifestation, yet complement each other to account for all manifestations through parallel node interactions. When equilibrium is reached, the network settles into a locally optimal state. Three randomly generated examples of diagnostic problems, each of which has 1024 cases, were tested, and the decomposition plus competition plus resettling approach yielded very high accuracy.

A Roadmap of Innovative Nuclear Energy System

NASA Astrophysics Data System (ADS)

Sekimoto, Hiroshi

2017-01-01

Nuclear is a dense energy without CO2 emission. It can be used for more than 100,000 years using fast breeder reactors with uranium from the sea. However, it raises difficult problems associated with severe accidents, spent fuel waste and nuclear threats, which should be solved with acceptable costs. Some innovative reactors have attracted interest, and many designs have been proposed for small reactors. These reactors are considered much safer than conventional large reactors and have fewer technical obstructions. Breed-and-burn reactors have high potential to solve all inherent problems for peaceful use of nuclear energy. However, they have some technical problems with materials. A roadmap for innovative reactors is presented herein.

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Improving the learning of clinical reasoning through computer-based cognitive representation

PubMed Central

Wu, Bian; Wang, Minhong; Johnson, Janice M.; Grotzer, Tina A.

2014-01-01

Objective Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction. PMID:25518871

Improving the learning of clinical reasoning through computer-based cognitive representation.

PubMed

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

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

PubMed

Huebner, Franziska; Fichtel, Claudia

2015-05-01

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

On the Effectiveness of Nature-Inspired Metaheuristic Algorithms for Performing Phase Equilibrium Thermodynamic Calculations

PubMed Central

Fateen, Seif-Eddeen K.; Bonilla-Petriciolet, Adrian

2014-01-01

The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolution strategy (CMAES), magnetic charged system search (MCSS), and bare bones particle swarm optimization (BBPSO). The results clearly showed that CS is the most reliable of all methods as it successfully solved all thermodynamic problems tested in this study. CS proved to be a promising nature-inspired optimization method to perform applied thermodynamic calculations for process design. PMID:24967430

On the effectiveness of nature-inspired metaheuristic algorithms for performing phase equilibrium thermodynamic calculations.

PubMed

Fateen, Seif-Eddeen K; Bonilla-Petriciolet, Adrian

2014-01-01

The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolution strategy (CMAES), magnetic charged system search (MCSS), and bare bones particle swarm optimization (BBPSO). The results clearly showed that CS is the most reliable of all methods as it successfully solved all thermodynamic problems tested in this study. CS proved to be a promising nature-inspired optimization method to perform applied thermodynamic calculations for process design.

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.

Students’ Errors in Geometry Viewed from Spatial Intelligence

NASA Astrophysics Data System (ADS)

Riastuti, N.; Mardiyana, M.; Pramudya, I.

2017-09-01

Geometry is one of the difficult materials because students must have ability to visualize, describe images, draw shapes, and know the kind of shapes. This study aim is to describe student error based on Newmans’ Error Analysis in solving geometry problems viewed from spatial intelligence. This research uses descriptive qualitative method by using purposive sampling technique. The datas in this research are the result of geometri material test and interview by the 8th graders of Junior High School in Indonesia. The results of this study show that in each category of spatial intelligence has a different type of error in solving the problem on the material geometry. Errors are mostly made by students with low spatial intelligence because they have deficiencies in visual abilities. Analysis of student error viewed from spatial intelligence is expected to help students do reflection in solving the problem of geometry.

Educational Technology Research in a VUCA World

ERIC Educational Resources Information Center

Reeves, Thomas C.; Reeves, Patricia M.

2015-01-01

The status of educational technology research in a VUCA world is examined. The acronym, VUCA, stands for "Volatility" (rapidly changing contexts and conditions), "Uncertainty" (information missing that is critical to problem solving), "Complexity" (multiple factors difficult to categorize or control), and…

Heuristics in Problem Solving: The Role of Direction in Controlling Search Space

ERIC Educational Resources Information Center

Chu, Yun; Li, Zheng; Su, Yong; Pizlo, Zygmunt

2010-01-01

Isomorphs of a puzzle called m+m resulted in faster solution times and an easily reproduced solution path in a labeled version of the problem compared to a more difficult binary version. We conjecture that performance is related to a type of heuristic called direction that not only constrains search space in the labeled version, but also…

Reframing the Path to School Leadership: A Guide for Teachers and Principals.

ERIC Educational Resources Information Center

Bolman, Lee G.; Deal, Terrence E.

The best leaders use multiple frames or lenses to view common challenges and to solve their most difficult problems. This book contains a series of dialogs between a novice and a master teacher, and between a new and a seasoned principal as they demonstrate how framing and reframing challenges can bring clarity, help to anticipate problems, and…

Practical Math Skills: Situations--Strategies--Solutions. Junior High Level. Grades 7-8-9.

ERIC Educational Resources Information Center

Duncan, Jim

This material is a supplement to existing mathematics programs for young learners. The activities presented are based on assumptions about the young problem solver which are difficult to address in standard mathematics texts. In these pages it is assumed that each learner brings to the problem-solving effort a very personal experience base and a…

Problem-Oriented and Project-Based Learning (POPBL) as an Innovative Learning Strategy for Sustainable Development in Engineering Education

ERIC Educational Resources Information Center

Lehmann, M.; Christensen, P.; Du, X.; Thrane, M.

2008-01-01

In a world where systems are increasingly larger, where their boundaries are often difficult to identify, and where societal rather than technical issues play increasingly bigger roles, problems cannot be solved by applying a technical solution alone. It thus becomes important for engineers to be skilled not only in terms of their particular…

Bringing NASA Technology Down to Earth

NASA Technical Reports Server (NTRS)

Lockney, Daniel P.; Taylor, Terry L.

2018-01-01

Whether putting rovers on Mars or sustaining life in extreme conditions, NASA develops technologies to solve some of the most difficult challenges ever faced. Through its Technology Transfer Program, the agency makes the innovations behind space exploration available to industry, academia, and the general public. This paper describes the primary mechanisms through which NASA disseminates technology to solve real-life problems; illustrates recent program accomplishments; and provides examples of spinoff success stories currently impacting everyday life.

Extended precedence preservative crossover for job shop scheduling problems

NASA Astrophysics Data System (ADS)

Ong, Chung Sin; Moin, Noor Hasnah; Omar, Mohd

2013-04-01

Job shop scheduling problems (JSSP) is one of difficult combinatorial scheduling problems. A wide range of genetic algorithms based on the two parents crossover have been applied to solve the problem but multi parents (more than two parents) crossover in solving the JSSP is still lacking. This paper proposes the extended precedence preservative crossover (EPPX) which uses multi parents for recombination in the genetic algorithms. EPPX is a variation of the precedence preservative crossover (PPX) which is one of the crossovers that perform well to find the solutions for the JSSP. EPPX is based on a vector to determine the gene selected in recombination for the next generation. Legalization of children (offspring) can be eliminated due to the JSSP representation encoded by using permutation with repetition that guarantees the feasibility of chromosomes. The simulations are performed on a set of benchmarks from the literatures and the results are compared to ensure the sustainability of multi parents recombination in solving the JSSP.

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

Bicriteria Network Optimization Problem using Priority-based Genetic Algorithm

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin; Cheng, Runwei

Network optimization is being an increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. In many applications, however, there are several criteria associated with traversing each edge of a network. For example, cost and flow measures are both important in the networks. As a result, there has been recent interest in solving Bicriteria Network Optimization Problem. The Bicriteria Network Optimization Problem is known a NP-hard. The efficient set of paths may be very large, possibly exponential in size. Thus the computational effort required to solve it can increase exponentially with the problem size in the worst case. In this paper, we propose a genetic algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including maximum flow (MXF) model and minimum cost flow (MCF) model. The objective is to find the set of Pareto optimal solutions that give possible maximum flow with minimum cost. This paper also combines Adaptive Weight Approach (AWA) that utilizes some useful information from the current population to readjust weights for obtaining a search pressure toward a positive ideal point. Computer simulations show the several numerical experiments by using some difficult-to-solve network design problems, and show the effectiveness of the proposed method.

Young children's use of derived fact strategies for addition and subtraction

PubMed Central

Dowker, Ann

2014-01-01

Forty-four children between 6;0 and 7;11 took part in a study of derived fact strategy use. They were assigned to addition and subtraction levels on the basis of calculation pretests. They were then given Dowker's (1998) test of derived fact strategies in addition, involving strategies based on the Identity, Commutativity, Addend +1, Addend −1, and addition/subtraction Inverse principles; and test of derived fact strategies in subtraction, involving strategies based on the Identity, Minuend +1, Minuend −1, Subtrahend +1, Subtrahend −1, Complement and addition/subtraction Inverse principles. The exact arithmetic problems given varied according to the child's previously assessed calculation level and were selected to be just a little too difficult for the child to solve unaided. Children were given the answer to a problem and then asked to solve another problem that could be solved quickly by using this answer, together with the principle being assessed. The children also took the WISC Arithmetic subtest. Strategies differed greatly in difficulty, with Identity being the easiest, and the Inverse and Complement principles being most difficult. The Subtrahend +1 and Subtrahend −1 problems often elicited incorrect strategies based on an overextension of the principles of addition to subtraction. It was concluded that children may have difficulty with understanding and applying the relationships between addition and subtraction. Derived fact strategy use was significantly related to both calculation level and to WISC Arithmetic scaled score. PMID:24431996

Surveying Turkish high school and university students' attitudes and approaches to physics problem solving

NASA Astrophysics Data System (ADS)

Balta, Nuri; Mason, Andrew J.; Singh, Chandralekha

2016-06-01

Students' attitudes and approaches to physics problem solving can impact how well they learn physics and how successful they are in solving physics problems. Prior research in the U.S. using a validated Attitude and Approaches to Problem Solving (AAPS) survey suggests that there are major differences between students in introductory physics and astronomy courses and physics experts in terms of their attitudes and approaches to physics problem solving. Here we discuss the validation, administration, and analysis of data for the Turkish version of the AAPS survey for high school and university students in Turkey. After the validation and administration of the Turkish version of the survey, the analysis of the data was conducted by grouping the data by grade level, school type, and gender. While there are no statistically significant differences between the averages of various groups on the survey, overall, the university students in Turkey were more expertlike than vocational high school students. On an item by item basis, there are statistically differences between the averages of the groups on many items. For example, on average, the university students demonstrated less expertlike attitudes about the role of equations and formulas in problem solving, in solving difficult problems, and in knowing when the solution is not correct, whereas they displayed more expertlike attitudes and approaches on items related to metacognition in physics problem solving. A principal component analysis on the data yields item clusters into which the student responses on various survey items can be grouped. A comparison of the responses of the Turkish and American university students enrolled in algebra-based introductory physics courses shows that on more than half of the items, the responses of these two groups were statistically significantly different, with the U.S. students on average responding to the items in a more expertlike manner.

A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems

NASA Astrophysics Data System (ADS)

Thammano, Arit; Teekeng, Wannaporn

2015-05-01

The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.

Gold-Collar Workers. ERIC Digest.

ERIC Educational Resources Information Center

Wonacott, Michael E.

The gold-collar worker has problem-solving abilities, creativity, talent, and intelligence; performs non-repetitive and complex work difficult to evaluate; and prefers self management. Gold-collar information technology workers learn continually from experience; recognize the synergy of teams; can demonstrate leadership; and are strategic thinkers…

Mesopotamia, A Difficult but Interesting Topic.

ERIC Educational Resources Information Center

Kavett, Hyman

1979-01-01

Describes a method to help students become participants in historical analysis rather than observers of ancient history. Mesopotamia is used as a case study of a culture for which opportunities exist for conjecture, hypothesis formation, research, extrapolation, problem solving, and statements of causality. (Author/DB)

Solving fuzzy shortest path problem by genetic algorithm

NASA Astrophysics Data System (ADS)

Syarif, A.; Muludi, K.; Adrian, R.; Gen, M.

2018-03-01

Shortest Path Problem (SPP) is known as one of well-studied fields in the area Operations Research and Mathematical Optimization. It has been applied for many engineering and management designs. The objective is usually to determine path(s) in the network with minimum total cost or traveling time. In the past, the cost value for each arc was usually assigned or estimated as a deteministic value. For some specific real world applications, however, it is often difficult to determine the cost value properly. One way of handling such uncertainty in decision making is by introducing fuzzy approach. With this situation, it will become difficult to solve the problem optimally. This paper presents the investigations on the application of Genetic Algorithm (GA) to a new SPP model in which the cost values are represented as Triangular Fuzzy Number (TFN). We adopts the concept of ranking fuzzy numbers to determine how good the solutions. Here, by giving his/her degree value, the decision maker can determine the range of objective value. This would be very valuable for decision support system in the real world applications.Simulation experiments were carried out by modifying several test problems with 10-25 nodes. It is noted that the proposed approach is capable attaining a good solution with different degree of optimism for the tested problems.

Solving and Learning Soft Temporal Constraints: Experimental Scenario and Examples

NASA Technical Reports Server (NTRS)

Rossi, F.; Venable, K. B.; Sperduti, A.; Khatib, L.; Morris, P.; Morris, R.; Koga, Dennis (Technical Monitor)

2001-01-01

Soft temporal constraint problems allow to describe in a natural way scenarios where events happen over time and preferences are associated to event distances and durations. However, sometimes such local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. To model everything in a uniform way via local preferences only, and also to take advantage of the existing constraint solvers which exploit only local preference use machine learning techniques which learn the local preferences from the global ones. In this paper we describe the existing framework for both solving and learning preferences in temporal constraint problems, the implemented modules, the experimental scenario, and preliminary results on some examples.

The social essentials of learning: an experimental investigation of collaborative problem solving and knowledge construction in mathematics classrooms in Australia and China

NASA Astrophysics Data System (ADS)

Chan, Man Ching Esther; Clarke, David; Cao, Yiming

2018-03-01

Interactive problem solving and learning are priorities in contemporary education, but these complex processes have proved difficult to research. This project addresses the question "How do we optimise social interaction for the promotion of learning in a mathematics classroom?" Employing the logic of multi-theoretic research design, this project uses the newly built Science of Learning Research Classroom (ARC-SR120300015) at The University of Melbourne and equivalent facilities in China to investigate classroom learning and social interactions, focusing on collaborative small group problem solving as a way to make the social aspects of learning visible. In Australia and China, intact classes of local year 7 students with their usual teacher will be brought into the research classroom facilities with built-in video cameras and audio recording equipment to participate in purposefully designed activities in mathematics. The students will undertake a sequence of tasks in the social units of individual, pair, small group (typically four students) and whole class. The conditions for student collaborative problem solving and learning will be manipulated so that student and teacher contributions to that learning process can be distinguished. Parallel and comparative analyses will identify culture-specific interactive patterns and provide the basis for hypotheses about the learning characteristics underlying collaborative problem solving performance documented in the research classrooms in each country. The ultimate goals of the project are to generate, develop and test more sophisticated hypotheses for the optimisation of social interaction in the mathematics classroom in the interest of improving learning and, particularly, student collaborative problem solving.

NMESys: An expert system for network fault detection

NASA Technical Reports Server (NTRS)

Nelson, Peter C.; Warpinski, Janet

1991-01-01

The problem of network management is becoming an increasingly difficult and challenging task. It is very common today to find heterogeneous networks consisting of many different types of computers, operating systems, and protocols. The complexity of implementing a network with this many components is difficult enough, while the maintenance of such a network is an even larger problem. A prototype network management expert system, NMESys, implemented in the C Language Integrated Production System (CLIPS). NMESys concentrates on solving some of the critical problems encountered in managing a large network. The major goal of NMESys is to provide a network operator with an expert system tool to quickly and accurately detect hard failures, potential failures, and to minimize or eliminate user down time in a large network.

Bridging the Gap Between Planning and Scheduling

NASA Technical Reports Server (NTRS)

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

2000-01-01

Planning research in Artificial Intelligence (AI) has often focused on problems where there are cascading levels of action choice and complex interactions between actions. In contrast. Scheduling research has focused on much larger problems where there is little action choice, but the resulting ordering problem is hard. In this paper, we give an overview of M planning and scheduling techniques, focusing on their similarities, differences, and limitations. We also argue that many difficult practical problems lie somewhere between planning and scheduling, and that neither area has the right set of tools for solving these vexing problems.

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.

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

PubMed

Holmberg, Leif

2007-11-01

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

Artificial Intelligence Applications to Videodisc Technology

PubMed Central

Vries, John K.; Banks, Gordon; McLinden, Sean; Moossy, John; Brown, Melanie

1985-01-01

Much of medical information is visual in nature. Since it is not easy to describe pictorial information in linguistic terms, it has been difficult to store and retrieve this type of information. Coupling videodisc technology with artificial intelligence programming techniques may provide a means for solving this problem.

Positive Peer Culture with German Youth

ERIC Educational Resources Information Center

Steinebach, Christoph; Steinebach, Ursula

2009-01-01

Children and youth develop the ability to surmount difficult life challenges through a combination of external supports and internal strengths. Positive peers can contribute substantially to growth in resilient coping and problem-solving skills. Positive Peer Culture (PPC) programs are designed to strengthen supportive social bonds, competence,…

Improving Virtual Teams through Knowledge Management: A Case Study

ERIC Educational Resources Information Center

Laughridge, James F.

2012-01-01

Within the dynamic globalized operating environment, organizations are increasingly relying on virtual teams to solve their most difficult problems, leverage their expertise and expand their presence. The use of virtual teams by organizations continues to increase greatly as the technologies supporting them evolve. Despite improvements in…

Exact solution of large asymmetric traveling salesman problems.

PubMed

Miller, D L; Pekny, J F

1991-02-15

The traveling salesman problem is one of a class of difficult problems in combinatorial optimization that is representative of a large number of important scientific and engineering problems. A survey is given of recent applications and methods for solving large problems. In addition, an algorithm for the exact solution of the asymmetric traveling salesman problem is presented along with computational results for several classes of problems. The results show that the algorithm performs remarkably well for some classes of problems, determining an optimal solution even for problems with large numbers of cities, yet for other classes, even small problems thwart determination of a provably optimal solution.

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.

Insight and analysis problem solving in microbes to machines.

PubMed

Clark, Kevin B

2015-11-01

A key feature for obtaining solutions to difficult problems, insight is oftentimes vaguely regarded as a special discontinuous intellectual process and/or a cognitive restructuring of problem representation or goal approach. However, this nearly century-old state of art devised by the Gestalt tradition to explain the non-analytical or non-trial-and-error, goal-seeking aptitude of primate mentality tends to neglect problem-solving capabilities of lower animal phyla, Kingdoms other than Animalia, and advancing smart computational technologies built from biological, artificial, and composite media. Attempting to provide an inclusive, precise definition of insight, two major criteria of insight, discontinuous processing and problem restructuring, are here reframed using terminology and statistical mechanical properties of computational complexity classes. Discontinuous processing becomes abrupt state transitions in algorithmic/heuristic outcomes or in types of algorithms/heuristics executed by agents using classical and/or quantum computational models. And problem restructuring becomes combinatorial reorganization of resources, problem-type substitution, and/or exchange of computational models. With insight bounded by computational complexity, humans, ciliated protozoa, and complex technological networks, for example, show insight when restructuring time requirements, combinatorial complexity, and problem type to solve polynomial and nondeterministic polynomial decision problems. Similar effects are expected from other problem types, supporting the idea that insight might be an epiphenomenon of analytical problem solving and consequently a larger information processing framework. Thus, this computational complexity definition of insight improves the power, external and internal validity, and reliability of operational parameters with which to classify, investigate, and produce the phenomenon for computational agents ranging from microbes to man-made devices. Copyright © 2015 Elsevier Ltd. All rights reserved.

Parallel Preconditioning for CFD Problems on the CM-5

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Kremenetsky, Mark D.; Richardson, John; Lasinski, T. A. (Technical Monitor)

1994-01-01

Up to today, preconditioning methods on massively parallel systems have faced a major difficulty. The most successful preconditioning methods in terms of accelerating the convergence of the iterative solver such as incomplete LU factorizations are notoriously difficult to implement on parallel machines for two reasons: (1) the actual computation of the preconditioner is not very floating-point intensive, but requires a large amount of unstructured communication, and (2) the application of the preconditioning matrix in the iteration phase (i.e. triangular solves) are difficult to parallelize because of the recursive nature of the computation. Here we present a new approach to preconditioning for very large, sparse, unsymmetric, linear systems, which avoids both difficulties. We explicitly compute an approximate inverse to our original matrix. This new preconditioning matrix can be applied most efficiently for iterative methods on massively parallel machines, since the preconditioning phase involves only a matrix-vector multiplication, with possibly a dense matrix. Furthermore the actual computation of the preconditioning matrix has natural parallelism. For a problem of size n, the preconditioning matrix can be computed by solving n independent small least squares problems. The algorithm and its implementation on the Connection Machine CM-5 are discussed in detail and supported by extensive timings obtained from real problem data.

Branch-pipe-routing approach for ships using improved genetic algorithm

NASA Astrophysics Data System (ADS)

Sui, Haiteng; Niu, Wentie

2016-09-01

Branch-pipe routing plays fundamental and critical roles in ship-pipe design. The branch-pipe-routing problem is a complex combinatorial optimization problem and is thus difficult to solve when depending only on human experts. A modified genetic-algorithm-based approach is proposed in this paper to solve this problem. The simplified layout space is first divided into threedimensional (3D) grids to build its mathematical model. Branch pipes in layout space are regarded as a combination of several two-point pipes, and the pipe route between two connection points is generated using an improved maze algorithm. The coding of branch pipes is then defined, and the genetic operators are devised, especially the complete crossover strategy that greatly accelerates the convergence speed. Finally, simulation tests demonstrate the performance of proposed method.

High-frequency CAD-based scattering model: SERMAT

NASA Astrophysics Data System (ADS)

Goupil, D.; Boutillier, M.

1991-09-01

Specifications for an industrial radar cross section (RCS) calculation code are given: it must be able to exchange data with many computer aided design (CAD) systems, it must be fast, and it must have powerful graphic tools. Classical physical optics (PO) and equivalent currents (EC) techniques have proven their efficiency on simple objects for a long time. Difficult geometric problems occur when objects with very complex shapes have to be computed. Only a specific geometric code can solve these problems. We have established that, once these problems have been solved: (1) PO and EC give good results on complex objects of large size compared to wavelength; and (2) the implementation of these objects in a software package (SERMAT) allows fast and sufficiently precise domain RCS calculations to meet industry requirements in the domain of stealth.

Experimental Design for Estimating Unknown Hydraulic Conductivity in a Confined Aquifer using a Genetic Algorithm and a Reduced Order Model

NASA Astrophysics Data System (ADS)

Ushijima, T.; Yeh, W.

2013-12-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.

Designing worked examples for learning tangent lines to circles

NASA Astrophysics Data System (ADS)

Retnowati, E.; Marissa

2018-03-01

Geometry is a branch of mathematics that deals with shape and space, including the circle. A difficult topic in the circle may be the tangent line to circle. This is considered a complex material since students have to simultaneously apply several principles to solve the problems, these are the property of circle, definition of the tangent, measurement and Pythagorean theorem. This paper discusses designs of worked examples for learning tangent line to circles and how to apply this design to an effective and efficient instructional activity. When students do not have sufficient prior knowledge, solving tangent problems might be clumsy, and as a consequence, the problem-solving activity hinders learning. According to a Cognitive Load Theory, learning occurs when students can construct new knowledge based on the relevant knowledge previously learned. When the relevant knowledge is unavailable, providing students with the worked example is suggested. Worked example may reduce unproductive process during learning that causes extraneous cognitive load. Nevertheless, worked examples must be created in such a way facilitate learning.

Rotational-path decomposition based recursive planning for spacecraft attitude reorientation

NASA Astrophysics Data System (ADS)

Xu, Rui; Wang, Hui; Xu, Wenming; Cui, Pingyuan; Zhu, Shengying

2018-02-01

The spacecraft reorientation is a common task in many space missions. With multiple pointing constraints, it is greatly difficult to solve the constrained spacecraft reorientation planning problem. To deal with this problem, an efficient rotational-path decomposition based recursive planning (RDRP) method is proposed in this paper. The uniform pointing-constraint-ignored attitude rotation planning process is designed to solve all rotations without considering pointing constraints. Then the whole path is checked node by node. If any pointing constraint is violated, the nearest critical increment approach will be used to generate feasible alternative nodes in the process of rotational-path decomposition. As the planning path of each subdivision may still violate pointing constraints, multiple decomposition is needed and the reorientation planning is designed as a recursive manner. Simulation results demonstrate the effectiveness of the proposed method. The proposed method has been successfully applied in two SPARK microsatellites to solve onboard constrained attitude reorientation planning problem, which were developed by the Shanghai Engineering Center for Microsatellites and launched on 22 December 2016.

Searching for memories, Sudoku, implicit check bits, and the iterative use of not-always-correct rapid neural computation.

PubMed

Hopfield, J J

2008-05-01

The algorithms that simple feedback neural circuits representing a brain area can rapidly carry out are often adequate to solve easy problems but for more difficult problems can return incorrect answers. A new excitatory-inhibitory circuit model of associative memory displays the common human problem of failing to rapidly find a memory when only a small clue is present. The memory model and a related computational network for solving Sudoku puzzles produce answers that contain implicit check bits in the representation of information across neurons, allowing a rapid evaluation of whether the putative answer is correct or incorrect through a computation related to visual pop-out. This fact may account for our strong psychological feeling of right or wrong when we retrieve a nominal memory from a minimal clue. This information allows more difficult computations or memory retrievals to be done in a serial fashion by using the fast but limited capabilities of a computational module multiple times. The mathematics of the excitatory-inhibitory circuits for associative memory and for Sudoku, both of which are understood in terms of energy or Lyapunov functions, is described in detail.

Developmental trajectories of aggression, prosocial behavior, and social-cognitive problem solving in emerging adolescents with clinically elevated attention-deficit/hyperactivity disorder symptoms.

PubMed

Kofler, Michael J; Larsen, Ross; Sarver, Dustin E; Tolan, Patrick H

2015-11-01

Middle school is a critical yet understudied period of social behavioral risks and opportunities that may be particularly difficult for emerging adolescents with attention-deficit/hyperactivity disorder (ADHD) given their childhood social difficulties. Relatively few ADHD studies have examined social behavior and social-cognitive problem solving beyond the elementary years, or examined aspects of positive (prosocial) behavior. The current study examined how middle school students with clinically elevated ADHD symptoms differ from their non-ADHD peers on baseline (6th grade) and age-related changes in prosocial and aggressive behavior, and the extent to which social-cognitive problem solving strategies mediate these relations. Emerging adolescents with (n = 178) and without (n = 3,806) clinically elevated, teacher-reported ADHD-combined symptoms were compared longitudinally across 6th through 8th grades using parallel process latent growth curve modeling, accounting for student demographic characteristics, oppositional-defiant disorder (ODD) symptoms, deviant peer association, school climate, and parental monitoring. Sixth graders with elevated ADHD symptoms engaged in somewhat fewer prosocial behaviors (d = -0.44) and more aggressive behavior (d = 0.20) relative to their peers. These small social behavioral deficits decreased but were not normalized across the middle school years. Contrary to hypotheses, social-cognitive problem solving was not impaired in the ADHD group after accounting for co-occurring ODD symptoms and did not mediate the association between ADHD and social behavior during the middle school years. ADHD and social-cognitive problem solving contributed independently to social behavior, both in 6th grade and across the middle school years; the influence of social-cognitive problem solving on social behavior was highly similar for the ADHD and non-ADHD groups. (c) 2015 APA, all rights reserved).

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

Graf, Peter; Dykes, Katherine; Scott, George

The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. Furthermore, this document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

Bringing Them in: The Experiences of Imported and Overseas-Qualified Teachers

ERIC Educational Resources Information Center

Sharplin, Elaine

2009-01-01

This qualitative multiple-site case study explores the experiences of imported and overseas-qualified teachers appointed to fill "difficult-to-staff" Western Australian rural schools. In a climate of global teacher shortages, investigation of the strategies adopted to solve this problem requires empirical examination. The study of six…

Resilience Strategies for New Teachers in High-Needs Areas

ERIC Educational Resources Information Center

Castro, Antonio J.; Kelly, John; Shih, Minyi

2010-01-01

This qualitative study investigates strategies of resilience exhibited by fifteen novice teachers employed in high-needs areas, such as in urban and rural contexts and in special education. Findings indicated that teachers utilised a variety of strategies, including help-seeking, problem-solving, managing difficult relationships, and seeking…

Responding to Bullying: What Works?

ERIC Educational Resources Information Center

Craig, Wendy; Pepler, Debra; Blais, Julie

2007-01-01

Children who are bullied are often told to "solve the problems themselves"; however, when bullying is repeated over time, it becomes increasingly difficult for victimized children to stop the torment because of their relative lack of power. We examine the ways in which children respond to bullying and their evaluations of the…

An Empirical Exploration of Metacognitive Assessment Activities in a Third-Year Civil Engineering Hydraulics Course

ERIC Educational Resources Information Center

Meyer, Jan H. F.; Knight, David B.; Callaghan, David P.; Baldock, Tom E.

2015-01-01

Threshold concepts are transformative, integrative, and provocative; understanding these difficult concepts allows students to be capable of solving advanced problems. This investigation and evaluation of a metacognitive curricular approach explore variation in students' and teachers' discernment of structural complexity of concepts and its…

The Logic of the Theoretical and Practical Products of Design Research

ERIC Educational Resources Information Center

Easterday, Matthew W.; Rees Lewis, Daniel G.; Gerber, Elizabeth M.

2016-01-01

Design research (DR) promises to simultaneously solve practical problems of education and develop theory to guide future interventions. However, educational DR remains paradigmatically underdeveloped, making it difficult to train new researchers, to agree upon what makes a theoretical contribution, and to promise clear outputs to funders--all of…

Changing University Students' Alternative Conceptions of Optics by Active Learning

ERIC Educational Resources Information Center

Hadžibegovic, Zalkida; Sliško, Josip

2013-01-01

Active learning is individual and group participation in effective activities such as in-class observing, writing, experimenting, discussion, solving problems, and talking about to-be-learned topics. Some instructors believe that active learning is impossible, or at least extremely difficult to achieve in large lecture sessions. Nevertheless, the…

Location-Aware Mobile Learning of Spatial Algorithms

ERIC Educational Resources Information Center

Karavirta, Ville

2013-01-01

Learning an algorithm--a systematic sequence of operations for solving a problem with given input--is often difficult for students due to the abstract nature of the algorithms and the data they process. To help students understand the behavior of algorithms, a subfield in computing education research has focused on algorithm…

Predicting Phenotypes from Genetic Crosses: A Mathematical Concept to Help Struggling Biology Students

ERIC Educational Resources Information Center

Baurhoo, Neerusha; Darwish, Shireef

2012-01-01

Predicting phenotypic outcomes from genetic crosses is often very difficult for biology students, especially those with learning disabilities. With our mathematical concept, struggling students in inclusive biology classrooms are now better equipped to solve genetic problems and predict phenotypes, because of improved understanding of dominance…

Developing Intuitive Reasoning with Graphs to Support Science Arguments

ERIC Educational Resources Information Center

Grueber, David

2011-01-01

Graphs are important for supporting critical thinking and scientific argumentation because students can use them to reason, make judgments and decisions, and solve problems like a scientist (Connery 2007). Yet teaching students how to use math to actually think critically continues to be difficult for teachers. This article describes two…

Early Verb Learning: How Do Children Learn How to Compare Events?

ERIC Educational Resources Information Center

Childers, Jane B.; Parrish, Rebecca; Olson, Christina V.; Burch, Clare; Fung, Gavin; McIntyre, Kevin P.

2016-01-01

An important problem verb learners must solve is how to extend verbs. Children could use cross-situational information to guide their extensions; however, comparing events is difficult. In 2 studies, researchers tested whether children benefit from initially seeing a pair of similar events ("progressive alignment") while learning new…

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

NASA Astrophysics Data System (ADS)

Wu, Dongjun

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

Resource-aware taxon selection for maximizing phylogenetic diversity.

PubMed

Pardi, Fabio; Goldman, Nick

2007-06-01

Phylogenetic diversity (PD) is a useful metric for selecting taxa in a range of biological applications, for example, bioconservation and genomics, where the selection is usually constrained by the limited availability of resources. We formalize taxon selection as a conceptually simple optimization problem, aiming to maximize PD subject to resource constraints. This allows us to take into account the different amounts of resources required by the different taxa. Although this is a computationally difficult problem, we present a dynamic programming algorithm that solves it in pseudo-polynomial time. Our algorithm can also solve many instances of the Noah's Ark Problem, a more realistic formulation of taxon selection for biodiversity conservation that allows for taxon-specific extinction risks. These instances extend the set of problems for which solutions are available beyond previously known greedy-tractable cases. Finally, we discuss the relevance of our results to real-life scenarios.

Optimizing a realistic large-scale frequency assignment problem using a new parallel evolutionary approach

NASA Astrophysics Data System (ADS)

Chaves-González, José M.; Vega-Rodríguez, Miguel A.; Gómez-Pulido, Juan A.; Sánchez-Pérez, Juan M.

2011-08-01

This article analyses the use of a novel parallel evolutionary strategy to solve complex optimization problems. The work developed here has been focused on a relevant real-world problem from the telecommunication domain to verify the effectiveness of the approach. The problem, known as frequency assignment problem (FAP), basically consists of assigning a very small number of frequencies to a very large set of transceivers used in a cellular phone network. Real data FAP instances are very difficult to solve due to the NP-hard nature of the problem, therefore using an efficient parallel approach which makes the most of different evolutionary strategies can be considered as a good way to obtain high-quality solutions in short periods of time. Specifically, a parallel hyper-heuristic based on several meta-heuristics has been developed. After a complete experimental evaluation, results prove that the proposed approach obtains very high-quality solutions for the FAP and beats any other result published.

A Simple Label Switching Algorithm for Semisupervised Structural SVMs.

PubMed

Balamurugan, P; Shevade, Shirish; Sundararajan, S

2015-10-01

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

Improving extreme-scale problem solving: assessing electronic brainstorming effectiveness in an industrial setting.

PubMed

Dornburg, Courtney C; Stevens, Susan M; Hendrickson, Stacey M L; Davidson, George S

2009-08-01

An experiment was conducted to compare the effectiveness of individual versus group electronic brainstorming to address difficult, real-world challenges. Although industrial reliance on electronic communications has become ubiquitous, empirical and theoretical understanding of the bounds of its effectiveness have been limited. Previous research using short-term laboratory experiments have engaged small groups of students in answering questions irrelevant to an industrial setting. The present experiment extends current findings beyond the laboratory to larger groups of real-world employees addressing organization-relevant challenges during the course of 4 days. Employees and contractors at a national laboratory participated, either in a group setting or individually, in an electronic brainstorm to pose solutions to a real-world problem. The data demonstrate that (for this design) individuals perform at least as well as groups in producing quantity of electronic ideas, regardless of brainstorming duration. However, when judged with respect to quality along three dimensions (originality, feasibility, and effectiveness), the individuals significantly (p < .05) outperformed the group. When quality is used to benchmark success, these data indicate that work-relevant challenges are better solved by aggregating electronic individual responses rather than by electronically convening a group. This research suggests that industrial reliance on electronic problem-solving groups should be tempered, and large nominal groups may be more appropriate corporate problem-solving vehicles.

Engineering data management: Experience and projections

NASA Technical Reports Server (NTRS)

Jefferson, D. K.; Thomson, B.

1978-01-01

Experiences in developing a large engineering data management system are described. Problems which were encountered are presented and projected to future systems. Business applications involving similar types of data bases are described. A data base management system architecture proposed by the business community is described and its applicability to engineering data management is discussed. It is concluded that the most difficult problems faced in engineering and business data management can best be solved by cooperative efforts.

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

NASA Astrophysics Data System (ADS)

Zou, Xueli

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

Evolving neural networks for strategic decision-making problems.

PubMed

Kohl, Nate; Miikkulainen, Risto

2009-04-01

Evolution of neural networks, or neuroevolution, has been a successful approach to many low-level control problems such as pole balancing, vehicle control, and collision warning. However, certain types of problems-such as those involving strategic decision-making-have remained difficult for neuroevolution to solve. This paper evaluates the hypothesis that such problems are difficult because they are fractured: The correct action varies discontinuously as the agent moves from state to state. A method for measuring fracture using the concept of function variation is proposed and, based on this concept, two methods for dealing with fracture are examined: neurons with local receptive fields, and refinement based on a cascaded network architecture. Experiments in several benchmark domains are performed to evaluate how different levels of fracture affect the performance of neuroevolution methods, demonstrating that these two modifications improve performance significantly. These results form a promising starting point for expanding neuroevolution to strategic tasks.

Tips for safety in endoscopic submucosal dissection for colorectal tumors

PubMed Central

Naito, Yuji; Murakami, Takaaki; Hirose, Ryohei; Ogiso, Kiyoshi; Inada, Yutaka; Abdul Rani, Rafiz; Kishimoto, Mitsuo; Nakanishi, Masayoshi; Itoh, Yoshito

2017-01-01

In Japan, endoscopic submucosal dissection (ESD) becomes one of standard therapies for large colorectal tumors. Recently, the efficacy of ESD has been reported all over the world. However, it is still difficult even for Japanese experts in some situations. Right-sided location, large tumor size, high degree of fibrosis, difficult manipulation is related with the difficulty. However, improvements on ESD devices, suitable strategies, and increase of operators’ experiences enable us to solve these problems. In this chapter, we introduce recent topics about various difficult factors of colorectal ESD and the tips such as strategy, devices, injection, and traction method [Pocket-creation method (PCM) etc.]. PMID:28616400

Solving optimization problems on computational grids.

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

Wright, S. J.; Mathematics and Computer Science

2001-05-01

Multiprocessor computing platforms, which have become more and more widely available since the mid-1980s, are now heavily used by organizations that need to solve very demanding computational problems. Parallel computing is now central to the culture of many research communities. Novel parallel approaches were developed for global optimization, network optimization, and direct-search methods for nonlinear optimization. Activity was particularly widespread in parallel branch-and-bound approaches for various problems in combinatorial and network optimization. As the cost of personal computers and low-end workstations has continued to fall, while the speed and capacity of processors and networks have increased dramatically, 'cluster' platforms havemore » become popular in many settings. A somewhat different type of parallel computing platform know as a computational grid (alternatively, metacomputer) has arisen in comparatively recent times. Broadly speaking, this term refers not to a multiprocessor with identical processing nodes but rather to a heterogeneous collection of devices that are widely distributed, possibly around the globe. The advantage of such platforms is obvious: they have the potential to deliver enormous computing power. Just as obviously, however, the complexity of grids makes them very difficult to use. The Condor team, headed by Miron Livny at the University of Wisconsin, were among the pioneers in providing infrastructure for grid computations. More recently, the Globus project has developed technologies to support computations on geographically distributed platforms consisting of high-end computers, storage and visualization devices, and other scientific instruments. In 1997, we started the metaneos project as a collaborative effort between optimization specialists and the Condor and Globus groups. Our aim was to address complex, difficult optimization problems in several areas, designing and implementing the algorithms and the software infrastructure need to solve these problems on computational grids. This article describes some of the results we have obtained during the first three years of the metaneos project. Our efforts have led to development of the runtime support library MW for implementing algorithms with master-worker control structure on Condor platforms. This work is discussed here, along with work on algorithms and codes for integer linear programming, the quadratic assignment problem, and stochastic linear programmming. Our experiences in the metaneos project have shown that cheap, powerful computational grids can be used to tackle large optimization problems of various types. In an industrial or commercial setting, the results demonstrate that one may not have to buy powerful computational servers to solve many of the large problems arising in areas such as scheduling, portfolio optimization, or logistics; the idle time on employee workstations (or, at worst, an investment in a modest cluster of PCs) may do the job. For the optimization research community, our results motivate further work on parallel, grid-enabled algorithms for solving very large problems of other types. The fact that very large problems can be solved cheaply allows researchers to better understand issues of 'practical' complexity and of the role of heuristics.« less

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.

A new class of problems in the calculus of variations

NASA Astrophysics Data System (ADS)

Ekeland, Ivar; Long, Yiming; Zhou, Qinglong

2013-11-01

This paper investigates an infinite-horizon problem in the one-dimensional calculus of variations, arising from the Ramsey model of endogeneous economic growth. Following Chichilnisky, we introduce an additional term, which models concern for the well-being of future generations. We show that there are no optimal solutions, but that there are equilibrium strateges, i.e. Nash equilibria of the leader-follower game between successive generations. To solve the problem, we approximate the Chichilnisky criterion by a biexponential criterion, we characterize its equilibria by a pair of coupled differential equations of HJB type, and we go to the limit. We find all the equilibrium strategies for the Chichilnisky criterion. The mathematical analysis is difficult because one has to solve an implicit differential equation in the sense of Thom. Our analysis extends earlier work by Ekeland and Lazrak.

The Role of Government and NGO in Promoting Wellness of People with Down Syndrome

ERIC Educational Resources Information Center

Jiar, Yeo Kee; Handayani, Lina; Xi, Lu

2014-01-01

People with Down Syndrome (PWDS) experience cognitive delays indicated by difficulties with cognition, long-term memory and non-verbal problem solving skills. PWDS have specific speech and language impairments which affect all aspects of development. Some children develop difficult behaviors which cause family stress and affect social and…

Calculus, Radio Dials and the Straight-Line Frequency Variable Capacitor

ERIC Educational Resources Information Center

Boyadzhiev, Khristo N.

2010-01-01

Most often radio dials of analogue radios are not uniformly graded; the frequencies are cramped on the left side or on the right side. This makes tuning more difficult. Why are dials made this way? We shall see here that simple calculus can help understand this problem and solve it. (Contains 7 figures.)

Applying Cognitive Science to Education: Thinking and Learning in Scientific and Other Complex Domains

ERIC Educational Resources Information Center

Reif, Frederick

2008-01-01

Many students find it difficult to learn the kinds of knowledge and thinking required by college or high school courses in mathematics, science, or other complex domains. Thus they often emerge with significant misconceptions, fragmented knowledge, and inadequate problem-solving skills. Most instructors or textbook authors approach their teaching…

Effects of the Application of Graphing Calculator on Students' Probability Achievement

ERIC Educational Resources Information Center

Tan, Choo-Kim

2012-01-01

A Graphing Calculator (GC) is one of the most portable and affordable technology in mathematics education. It quickens the mechanical procedure in solving mathematical problems and creates a highly interactive learning environment, which makes learning a seemingly difficult subject, easy. Since research on the use of GCs for the teaching and…

Building Your School's Capacity to Implement RTI: An ASCD Action Tool

ERIC Educational Resources Information Center

ASCD, 2011

2011-01-01

Once your school has established the reason and the will to move forward with Response to Intervention (RTI), you still have to navigate all the difficult steps of implementing core instruction with a multitiered system of supports, data-based problem solving, progress monitoring, and universal screening. That's where this ASCD (Association for…

The Use of a Daily Quiz "TOPday" as Supportive Learning Method for Medical Students

ERIC Educational Resources Information Center

Maessen, Martijn F. H.; Fluit, Cornelia R. M. G.; Holla, Micha; Drost, Gea; Vorstenbosch, Marc A. T. M.; de Waal Malefijt, Maarten C.; Kooloos, Jan G. M.; Tanck, Esther

2016-01-01

Medical students consider anatomy, neurology, and traumatology as difficult study topics. A recent study showed that the daily quiz "Two Opportunities to Practice per day (TOPday)" positively supported biomedical students in analyzing and solving biomechanical problems. The main purpose of this study was to investigate the effect of…

The ESA21 Project: A Model for Civic Engagement

ERIC Educational Resources Information Center

Pratte, John; Laposata, Matt

2005-01-01

There have been many systematic approaches to solving the problem of how to make science courses interesting to students. One that is currently receiving attention in the sciences is the use of civic engagement within the classroom. This approach works well in small enrollment courses, but it is logistically difficult to implement in large…

Undergraduate Students' Initial Conceptions of Factorials

ERIC Educational Resources Information Center

Lockwood, Elise; Erickson, Sarah

2017-01-01

Counting problems offer rich opportunities for students to engage in mathematical thinking, but they can be difficult for students to solve. In this paper, we present a study that examines student thinking about one concept within counting, factorials, which are a key aspect of many combinatorial ideas. In an effort to better understand students'…

Modeling Physical Systems Using Vensim PLE Systems Dynamics Software

ERIC Educational Resources Information Center

Widmark, Stephen

2012-01-01

Many physical systems are described by time-dependent differential equations or systems of such equations. This makes it difficult for students in an introductory physics class to solve many real-world problems since these students typically have little or no experience with this kind of mathematics. In my high school physics classes, I address…

bioboxes v510

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

Barton, Michael; Droge, Johannes; Belmann, Peter

2017-06-22

Software is now both central and essential to modern biology, yet lack of availability, difficult installations, and complex user interfaces make software hard to obtain and use. Containerisation, as exemplified by the Docker platform, has the potential to solve the problems associated with sharing software. The developers propose bioboxes: containers with standardised interfaces to make bioinformatics software interchangeable.

Solving wood chip transport problems with computer simulation.

Treesearch

Dennis P. Bradley; Sharon A. Winsauer

1976-01-01

Efficient chip transport operations are difficult to achieve due to frequent and often unpredictable changes in distance to market, chipping rate, time spent at the mill, and equipment costs. This paper describes a computer simulation model that allows a logger to design an efficient transport system in response to these changing factors.

Introducing the Boundary Element Method with MATLAB

ERIC Educational Resources Information Center

Ang, Keng-Cheng

2008-01-01

The boundary element method provides an excellent platform for learning and teaching a computational method for solving problems in physical and engineering science. However, it is often left out in many undergraduate courses as its implementation is deemed to be difficult. This is partly due to the perception that coding the method requires…

Vandalism and outdoor recreation: symposium proceedings

Treesearch

Sam S. Alfano; Arthur W. [tech. coord.] Magil

1976-01-01

Resource managers, law enforcement officers, designers, and social scientists provide 24 papers giving an overview of vandalism on outdoor recreation areas; a measure of the difficult control problems which must be solved; some insights for design of buildings, fixtures, and site layouts to reduce or repel vandalism; and a profile of vandals, with respect to the...

Art-Integration through Making Dioramas of Women Mathematicians' Lives Enhances Creativity and Motivation

ERIC Educational Resources Information Center

Rule, Audrey C.; Atwood-Blaine, Dana; Edwards, Clayton M.; Gordon, Mindy M.

2016-01-01

Creativity is essential for solving problems in the workplace, natural environment, and everyday life, necessitating that creativity be nurtured in schools. Identification of factors that intrinsically motivate students to learn difficult or initially unappealing content is also important. This project, in which 24 racially diverse fifth grade…

Learning through Process Drama in the First Grade

ERIC Educational Resources Information Center

Barnes, Mary Kathleen; Johnson, Edric C.; Neff, Lois

2010-01-01

A teaching team of three teachers aims to prepare students for 21st Century Learning Outcomes, which includes critical thinking, problem solving, and communication skills. Yet classroom experience has taught them that one of the most difficult aspects of teaching young children is that they have few experiences or prior knowledge to make sense of…

Linguistic Skills Involved in Learning to Spell: An Australian Study

ERIC Educational Resources Information Center

Daffern, Tessa

2017-01-01

Being able to accurately spell in Standard English requires efficient coordination of multiple knowledge sources. Therefore, spelling is a word-formation problem-solving process that can be difficult to learn. The present study uses Triple Word Form Theory as a conceptual framework to analyse Standard English spelling performance levels of…

[Whiplash lesions and temporomandibular joint disorders].

PubMed

Gola, R; Richard, O; Guyot, L; Cheynet, F

2004-11-01

Attributing dysfunction of the temporomandibular joint (TMJ) to whiplash injury is a difficult problem to solve. TMJ disorders do not seem to be secondary to direct articular trauma but rather caused by a postural disorder of the cervical spine. Occlusal disorders and stress further complicate the picture. Four clinical cases illustrate a new hypothetical approach.

A Mixed Integer Efficient Global Optimization Framework: Applied to the Simultaneous Aircraft Design, Airline Allocation and Revenue Management Problem

NASA Astrophysics Data System (ADS)

Roy, Satadru

Traditional approaches to design and optimize a new system, often, use a system-centric objective and do not take into consideration how the operator will use this new system alongside of other existing systems. This "hand-off" between the design of the new system and how the new system operates alongside other systems might lead to a sub-optimal performance with respect to the operator-level objective. In other words, the system that is optimal for its system-level objective might not be best for the system-of-systems level objective of the operator. Among the few available references that describe attempts to address this hand-off, most follow an MDO-motivated subspace decomposition approach of first designing a very good system and then provide this system to the operator who decides the best way to use this new system along with the existing systems. The motivating example in this dissertation presents one such similar problem that includes aircraft design, airline operations and revenue management "subspaces". The research here develops an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem. The monolithic approach makes the problem a Mixed Integer/Discrete Non-Linear Programming (MINLP/MDNLP) problem, which are extremely difficult to solve. The presence of expensive, sophisticated engineering analyses further aggravate the problem. To tackle this challenge problem, the work here presents a new optimization framework that simultaneously solves the subspaces to capture the "synergism" in the problem that the previous decomposition approaches may not have exploited, addresses mixed-integer/discrete type design variables in an efficient manner, and accounts for computationally expensive analysis tools. The framework combines concepts from efficient global optimization, Kriging partial least squares, and gradient-based optimization. This approach then demonstrates its ability to solve an 11 route airline network problem consisting of 94 decision variables including 33 integer and 61 continuous type variables. This application problem is a representation of an interacting group of systems and provides key challenges to the optimization framework to solve the MINLP problem, as reflected by the presence of a moderate number of integer and continuous type design variables and expensive analysis tool. The result indicates simultaneously solving the subspaces could lead to significant improvement in the fleet-level objective of the airline when compared to the previously developed sequential subspace decomposition approach. In developing the approach to solve the MINLP/MDNLP challenge problem, several test problems provided the ability to explore performance of the framework. While solving these test problems, the framework showed that it could solve other MDNLP problems including categorically discrete variables, indicating that the framework could have broader application than the new aircraft design-fleet allocation-revenue management problem.

Revisiting software specification and design for large astronomy projects

NASA Astrophysics Data System (ADS)

Wiant, Scott; Berukoff, Steven

2016-07-01

The separation of science and engineering in the delivery of software systems overlooks the true nature of the problem being solved and the organization that will solve it. Use of a systems engineering approach to managing the requirements flow between these two groups as between a customer and contractor has been used with varying degrees of success by well-known entities such as the U.S. Department of Defense. However, treating science as the customer and engineering as the contractor fosters unfavorable consequences that can be avoided and opportunities that are missed. For example, the "problem" being solved is only partially specified through the requirements generation process since it focuses on detailed specification guiding the parties to a technical solution. Equally important is the portion of the problem that will be solved through the definition of processes and staff interacting through them. This interchange between people and processes is often underrepresented and under appreciated. By concentrating on the full problem and collaborating on a strategy for its solution a science-implementing organization can realize the benefits of driving towards common goals (not just requirements) and a cohesive solution to the entire problem. The initial phase of any project when well executed is often the most difficult yet most critical and thus it is essential to employ a methodology that reinforces collaboration and leverages the full suite of capabilities within the team. This paper describes an integrated approach to specifying the needs induced by a problem and the design of its solution.

Solving geosteering inverse problems by stochastic Hybrid Monte Carlo method

DOE PAGES

Shen, Qiuyang; Wu, Xuqing; Chen, Jiefu; ...

2017-11-20

The inverse problems arise in almost all fields of science where the real-world parameters are extracted from a set of measured data. The geosteering inversion plays an essential role in the accurate prediction of oncoming strata as well as a reliable guidance to adjust the borehole position on the fly to reach one or more geological targets. This mathematical treatment is not easy to solve, which requires finding an optimum solution among a large solution space, especially when the problem is non-linear and non-convex. Nowadays, a new generation of logging-while-drilling (LWD) tools has emerged on the market. The so-called azimuthalmore » resistivity LWD tools have azimuthal sensitivity and a large depth of investigation. Hence, the associated inverse problems become much more difficult since the earth model to be inverted will have more detailed structures. The conventional deterministic methods are incapable to solve such a complicated inverse problem, where they suffer from the local minimum trap. Alternatively, stochastic optimizations are in general better at finding global optimal solutions and handling uncertainty quantification. In this article, we investigate the Hybrid Monte Carlo (HMC) based statistical inversion approach and suggest that HMC based inference is more efficient in dealing with the increased complexity and uncertainty faced by the geosteering problems.« less

Using Stochastic Spiking Neural Networks on SpiNNaker to Solve Constraint Satisfaction Problems

PubMed Central

Fonseca Guerra, Gabriel A.; Furber, Steve B.

2017-01-01

Constraint satisfaction problems (CSP) are at the core of numerous scientific and technological applications. However, CSPs belong to the NP-complete complexity class, for which the existence (or not) of efficient algorithms remains a major unsolved question in computational complexity theory. In the face of this fundamental difficulty heuristics and approximation methods are used to approach instances of NP (e.g., decision and hard optimization problems). The human brain efficiently handles CSPs both in perception and behavior using spiking neural networks (SNNs), and recent studies have demonstrated that the noise embedded within an SNN can be used as a computational resource to solve CSPs. Here, we provide a software framework for the implementation of such noisy neural solvers on the SpiNNaker massively parallel neuromorphic hardware, further demonstrating their potential to implement a stochastic search that solves instances of P and NP problems expressed as CSPs. This facilitates the exploration of new optimization strategies and the understanding of the computational abilities of SNNs. We demonstrate the basic principles of the framework by solving difficult instances of the Sudoku puzzle and of the map color problem, and explore its application to spin glasses. The solver works as a stochastic dynamical system, which is attracted by the configuration that solves the CSP. The noise allows an optimal exploration of the space of configurations, looking for the satisfiability of all the constraints; if applied discontinuously, it can also force the system to leap to a new random configuration effectively causing a restart. PMID:29311791

Wind Farm Turbine Type and Placement Optimization

NASA Astrophysics Data System (ADS)

Graf, Peter; Dykes, Katherine; Scott, George; Fields, Jason; Lunacek, Monte; Quick, Julian; Rethore, Pierre-Elouan

2016-09-01

The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. This document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

Wind farm turbine type and placement optimization

DOE PAGES

Graf, Peter; Dykes, Katherine; Scott, George; ...

2016-10-03

The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. Furthermore, this document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

Computer-aided programming for message-passing system; Problems and a solution

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

Wu, M.Y.; Gajski, D.D.

1989-12-01

As the number of processors and the complexity of problems to be solved increase, programming multiprocessing systems becomes more difficult and error-prone. Program development tools are necessary since programmers are not able to develop complex parallel programs efficiently. Parallel models of computation, parallelization problems, and tools for computer-aided programming (CAP) are discussed. As an example, a CAP tool that performs scheduling and inserts communication primitives automatically is described. It also generates the performance estimates and other program quality measures to help programmers in improving their algorithms and programs.

Optimal placement of excitations and sensors for verification of large dynamical systems

NASA Technical Reports Server (NTRS)

Salama, M.; Rose, T.; Garba, J.

1987-01-01

The computationally difficult problem of the optimal placement of excitations and sensors to maximize the observed measurements is studied within the framework of combinatorial optimization, and is solved numerically using a variation of the simulated annealing heuristic algorithm. Results of numerical experiments including a square plate and a 960 degrees-of-freedom Control of Flexible Structure (COFS) truss structure, are presented. Though the algorithm produces suboptimal solutions, its generality and simplicity allow the treatment of complex dynamical systems which would otherwise be difficult to handle.

A derived heuristics based multi-objective optimization procedure for micro-grid scheduling

NASA Astrophysics Data System (ADS)

Li, Xin; Deb, Kalyanmoy; Fang, Yanjun

2017-06-01

With the availability of different types of power generators to be used in an electric micro-grid system, their operation scheduling as the load demand changes with time becomes an important task. Besides satisfying load balance constraints and the generator's rated power, several other practicalities, such as limited availability of grid power and restricted ramping of power output from generators, must all be considered during the operation scheduling process, which makes it difficult to decide whether the optimization results are accurate and satisfactory. In solving such complex practical problems, heuristics-based customized optimization algorithms are suggested. However, due to nonlinear and complex interactions of variables, it is difficult to come up with heuristics in such problems off-hand. In this article, a two-step strategy is proposed in which the first task deciphers important heuristics about the problem and the second task utilizes the derived heuristics to solve the original problem in a computationally fast manner. Specifically, the specific operation scheduling is considered from a two-objective (cost and emission) point of view. The first task develops basic and advanced level knowledge bases offline from a series of prior demand-wise optimization runs and then the second task utilizes them to modify optimized solutions in an application scenario. Results on island and grid connected modes and several pragmatic formulations of the micro-grid operation scheduling problem clearly indicate the merit of the proposed two-step procedure.

An Automatic Medium to High Fidelity Low-Thrust Global Trajectory Toolchain; EMTG-GMAT

NASA Technical Reports Server (NTRS)

Beeson, Ryne T.; Englander, Jacob A.; Hughes, Steven P.; Schadegg, Maximillian

2015-01-01

Solving the global optimization, low-thrust, multiple-flyby interplanetary trajectory problem with high-fidelity dynamical models requires an unreasonable amount of computational resources. A better approach, and one that is demonstrated in this paper, is a multi-step process whereby the solution of the aforementioned problem is solved at a lower-fidelity and this solution is used as an initial guess for a higher-fidelity solver. The framework presented in this work uses two tools developed by NASA Goddard Space Flight Center: the Evolutionary Mission Trajectory Generator (EMTG) and the General Mission Analysis Tool (GMAT). EMTG is a medium to medium-high fidelity low-thrust interplanetary global optimization solver, which now has the capability to automatically generate GMAT script files for seeding a high-fidelity solution using GMAT's local optimization capabilities. A discussion of the dynamical models as well as thruster and power modeling for both EMTG and GMAT are given in this paper. Current capabilities are demonstrated with examples that highlight the toolchains ability to efficiently solve the difficult low-thrust global optimization problem with little human intervention.

A similarity score-based two-phase heuristic approach to solve the dynamic cellular facility layout for manufacturing systems

NASA Astrophysics Data System (ADS)

Kumar, Ravi; Singh, Surya Prakash

2017-11-01

The dynamic cellular facility layout problem (DCFLP) is a well-known NP-hard problem. It has been estimated that the efficient design of DCFLP reduces the manufacturing cost of products by maintaining the minimum material flow among all machines in all cells, as the material flow contributes around 10-30% of the total product cost. However, being NP hard, solving the DCFLP optimally is very difficult in reasonable time. Therefore, this article proposes a novel similarity score-based two-phase heuristic approach to solve the DCFLP optimally considering multiple products in multiple times to be manufactured in the manufacturing layout. In the first phase of the proposed heuristic, a machine-cell cluster is created based on similarity scores between machines. This is provided as an input to the second phase to minimize inter/intracell material handling costs and rearrangement costs over the entire planning period. The solution methodology of the proposed approach is demonstrated. To show the efficiency of the two-phase heuristic approach, 21 instances are generated and solved using the optimization software package LINGO. The results show that the proposed approach can optimally solve the DCFLP in reasonable time.

Evaluation of Learning Environments for Object-Oriented Programming: Measuring Cognitive Load with a Novel Measurement Technique

ERIC Educational Resources Information Center

Uysal, Murat Pasa

2016-01-01

Various methods and tools have been proposed to overcome the learning obstacles for Object-Oriented Programming (OOP). However, it remains difficult especially for novice learners. The problem may be not only adopting an instructional method, but also an Integrated Development Environment (IDE). Learners employ IDEs as a means to solve programming…

The Clock Project: Gears as Visual-Tangible Representations for Mathematical Concepts

ERIC Educational Resources Information Center

Andrade, Alejandro

2011-01-01

As we have noticed from our own classroom experiences, children often find it difficult to identify the adequate operations learned in mathematics class when they are solving mechanical-operators problems in Technology class. We wanted to design a project that exploits the idea of a hands-on relationship between mathematics and technology to teach…

A Computational Model of Word Segmentation from Continuous Speech Using Transitional Probabilities of Atomic Acoustic Events

ERIC Educational Resources Information Center

Rasanen, Okko

2011-01-01

Word segmentation from continuous speech is a difficult task that is faced by human infants when they start to learn their native language. Several studies indicate that infants might use several different cues to solve this problem, including intonation, linguistic stress, and transitional probabilities between subsequent speech sounds. In this…

Preservice Elementary School Teachers' Knowledge of Fractions: A Mirror of Students' Knowledge?

ERIC Educational Resources Information Center

Van Steenbrugge, H.; Lesage, E.; Valcke, M.; Desoete, A.

2014-01-01

This research analyses preservice teachers' knowledge of fractions. Fractions are notoriously difficult for students to learn and for teachers to teach. Previous studies suggest that student learning of fractions may be limited by teacher understanding of fractions. If so, teacher education has a key role in solving the problem. We first reviewed…

Changing Schools from the inside out: Small Wins in Hard Times. Third Edition

ERIC Educational Resources Information Center

Larson, Robert

2011-01-01

At any time, public schools labor under great economic, political, and social pressures that make it difficult to create large-scale, "whole school" change. But current top-down mandates require that schools close achievement gaps while teaching more problem solving, inquiry, and research skills--with fewer resources. Failure to meet test-based…

Bioboxes: standardised containers for interchangeable bioinformatics software.

PubMed

Belmann, Peter; Dröge, Johannes; Bremges, Andreas; McHardy, Alice C; Sczyrba, Alexander; Barton, Michael D

2015-01-01

Software is now both central and essential to modern biology, yet lack of availability, difficult installations, and complex user interfaces make software hard to obtain and use. Containerisation, as exemplified by the Docker platform, has the potential to solve the problems associated with sharing software. We propose bioboxes: containers with standardised interfaces to make bioinformatics software interchangeable.

Changing Jobs in Difficult Financial Times

ERIC Educational Resources Information Center

Brown, Wayne

2009-01-01

Starting a new CIO job is always a challenge. There is a new department and institution to learn about, people to meet, and problems to solve. There is always plenty to learn and projects to realize. Throwing in economic challenges to the new-job transition can feel like one is attempting to climb a mountain without any gear. Fortunately, there…

From a Museum Demonstration to Problem Solving: Promoting the Construction of Concepts

ERIC Educational Resources Information Center

Lee, Yeung Chung

2007-01-01

Physics is perceived by many students to be a difficult subject, and misconceptions about it are quite common not only among school students but also among undergraduates and pre-service postgraduate science teachers. In teaching the topic of gas pressure to primary student teachers studying in the Bachelor of Education programme at my institute,…

Algebra and Problem-Solving in Down Syndrome: A Study with 15 Teenagers

ERIC Educational Resources Information Center

Martinez, Elisabetta Monari; Pellegrini, Katia

2010-01-01

There is a common opinion that mathematics is difficult for persons with Down syndrome, because of a weakness in numeracy and in abstract thinking. Since 1996, some single case studies have suggested that new opportunities in mathematics are possible for these students: some of them learned algebra and also learned to use equations in…

A flow-injection mass spectrometry fingerprinting method for authentication and quality assessment of Scutellaria lateriflora-based dietary supplements

USDA-ARS?s Scientific Manuscript database

Identification and differentiation of anthocyanins and non-anthocyanin compounds in natural products can be very difficult by mass spectrometry. Using a ultra-violet/visible detector can be helpful, but not fool-proof, and it requires an additional detector. To solve the problem, a fast and reliab...

Using Assessments of Contextual Learning to Identify Characteristics of Adaptive Transfer in Medical Students

ERIC Educational Resources Information Center

Baer, Tom

2013-01-01

Transfer of learning from curricular experiences to non-academic settings is a primary goal of any academic institution. In cases where skills, knowledge, and attitudes learned in curricular experiences are used to solve complex problems, transfer is especially difficult to define and measure. This study attempts to better define transfer in…

Bullying in Schools: What Is the Problem, and How Can Educators Solve It?

ERIC Educational Resources Information Center

Strohmeier, Dagmar; Noam, Gil G.

2012-01-01

This chapter reviews recent research on bullying from an educator's perspective. It is well known that bullying, a serious issue in schools, can be prevented when educators intervene. But research has shown that it is difficult for educators to detect bullying situations in their school and intervene competently and effectively. This chapter…

Re-Purposing Google Maps Visualisation for Teaching Logistics Systems

ERIC Educational Resources Information Center

Cheong, France; Cheong, Christopher; Jie, Ferry

2012-01-01

Routing is the process of selecting appropriate paths and ordering waypoints in a network. It plays an important part in logistics and supply chain management as choosing the optimal route can minimise distribution costs. Routing optimisation, however, is a difficult problem to solve and computer software is often used to determine the best route.…

Tensions Teaching Science for Equity: Lessons Learned from the Case of Ms. Dawson

ERIC Educational Resources Information Center

Braaten, Melissa; Sheth, Manali

2017-01-01

When teachers engage in forms of science teaching that disrupt the status quo of typical school science practices, they often experience dilemmas as problems of practice that are difficult--or even impossible--to solve. This instrumental case study examines one teacher's efforts to teach science for equity across two contexts: a public middle…

Potential and Impact Factors of the Knowledge and Information Awareness Approach for Fostering Net-Based Collaborative Problem-Solving: An Overview

ERIC Educational Resources Information Center

Engelmann, Tanja

2014-01-01

For effective communication and collaboration in learning situations, it is important to know what the collaboration partners know. However, the acquisition of this knowledge is difficult, especially in collaborating groups with spatially distributed members. One solution is the "Knowledge and Information Awareness" approach developed by…

Piaget and psychotherapy.

PubMed

Friedman, T L

1978-04-01

It is difficult to apply Piaget's theory to psychotherapy because the place of affect in it is ambiguous. When the alternatives are considered, it seems most consistent with Piaget's ideas to regard both cognitive and affective phenomena as problem-solving organizations. Piaget's remarkable discoveries in the cognitive sphere are a consequence of the easy access in that sphere to the kind of problems that need solving, and the phasic development of solutions. But the nature of the problems to be solved or the values to be guarded by a patient in psychotherapy are not knowable independently of the patient's actual behavior. In one respect all that is left from Piaget's approach for psychotherapy generally is the truism that therapy fosters differentiation and integration. However, even if we cannot frame a peculiarly Piagetian paradigm of psychotherapy, Piaget is valuable in posing a subsidiary question, namely, what in therapy fosters problem-solving activity. A reading of Piaget suggests that a patient learns by acting on his therapist and tacitly interpreting the results of his actions, that difficulties in therapy are the material from which therapy proceeds, and that in order to grasp the situation of the patient, the therapist himself may need to act on him and not just think about him. An implied lesson for training would be that supervision should instill a professional identity that is reinforced rather than challenged by therapy difficulties, and does not rely solely on theoretical categorizing.

An overview of adaptive model theory: solving the problems of redundancy, resources, and nonlinear interactions in human movement control.

PubMed

Neilson, Peter D; Neilson, Megan D

2005-09-01

Adaptive model theory (AMT) is a computational theory that addresses the difficult control problem posed by the musculoskeletal system in interaction with the environment. It proposes that the nervous system creates motor maps and task-dependent synergies to solve the problems of redundancy and limited central resources. These lead to the adaptive formation of task-dependent feedback/feedforward controllers able to generate stable, noninteractive control and render nonlinear interactions unobservable in sensory-motor relationships. AMT offers a unified account of how the nervous system might achieve these solutions by forming internal models. This is presented as the design of a simulator consisting of neural adaptive filters based on cerebellar circuitry. It incorporates a new network module that adaptively models (in real time) nonlinear relationships between inputs with changing and uncertain spectral and amplitude probability density functions as is the case for sensory and motor signals.

Two-Stage Path Planning Approach for Designing Multiple Spacecraft Reconfiguration Maneuvers

NASA Technical Reports Server (NTRS)

Aoude, Georges S.; How, Jonathan P.; Garcia, Ian M.

2007-01-01

The paper presents a two-stage approach for designing optimal reconfiguration maneuvers for multiple spacecraft. These maneuvers involve well-coordinated and highly-coupled motions of the entire fleet of spacecraft while satisfying an arbitrary number of constraints. This problem is particularly difficult because of the nonlinearity of the attitude dynamics, the non-convexity of some of the constraints, and the coupling between the positions and attitudes of all spacecraft. As a result, the trajectory design must be solved as a single 6N DOF problem instead of N separate 6 DOF problems. The first stage of the solution approach quickly provides a feasible initial solution by solving a simplified version without differential constraints using a bi-directional Rapidly-exploring Random Tree (RRT) planner. A transition algorithm then augments this guess with feasible dynamics that are propagated from the beginning to the end of the trajectory. The resulting output is a feasible initial guess to the complete optimal control problem that is discretized in the second stage using a Gauss pseudospectral method (GPM) and solved using an off-the-shelf nonlinear solver. This paper also places emphasis on the importance of the initialization step in pseudospectral methods in order to decrease their computation times and enable the solution of a more complex class of problems. Several examples are presented and discussed.

The inverse problem of sensing the mass and force induced by an adsorbate on a beam nanomechanical resonator

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

Liu, Yun; Zhang, Yin

2016-06-08

The mass sensing superiority of a micro/nanomechanical resonator sensor over conventional mass spectrometry has been, or at least, is being firmly established. Because the sensing mechanism of a mechanical resonator sensor is the shifts of resonant frequencies, how to link the shifts of resonant frequencies with the material properties of an analyte formulates an inverse problem. Besides the analyte/adsorbate mass, many other factors such as position and axial force can also cause the shifts of resonant frequencies. The in-situ measurement of the adsorbate position and axial force is extremely difficult if not impossible, especially when an adsorbate is as smallmore » as a molecule or an atom. Extra instruments are also required. In this study, an inverse problem of using three resonant frequencies to determine the mass, position and axial force is formulated and solved. The accuracy of the inverse problem solving method is demonstrated and how the method can be used in the real application of a nanomechanical resonator is also discussed. Solving the inverse problem is helpful to the development and application of mechanical resonator sensor on two things: reducing extra experimental equipments and achieving better mass sensing by considering more factors.« less

Developmental Trajectories of Aggression, Prosocial Behavior, and Social-Cognitive Problem Solving in Emerging Adolescents with Clinically Elevated ADHD Symptoms

PubMed Central

Kofler, Michael J.; Larsen, Ross; Sarver, Dustin E.; Tolan, Patrick H.

2015-01-01

Middle school is a critical yet understudied period of social behavioral risks and opportunities that may be particularly difficult for emerging adolescents with ADHD given their childhood social difficulties. Although childhood ADHD has been associated with increased aggression and peer relational difficulties, relatively few ADHD studies have examined social behavior beyond the elementary years, or examined aspects of positive (prosocial) behavior. In addition, social-cognitive problem solving has been implicated in ADHD; however, its longitudinal impact on prosocial and aggressive behavior is unclear. The current study examined how middle school students with clinically elevated ADHD symptoms differ from their non-ADHD peers on baseline (sixth grade) and age-related changes in prosocial and aggressive behavior, and the extent to which social-cognitive problem solving strategies mediate these relations. Emerging adolescents with (n = 178) and without (n = 3,806) clinically elevated, teacher-reported ADHD inattentive and hyperactive/impulsive symptoms were compared longitudinally across sixth through eighth grades using parallel process latent growth curve modeling, accounting for student demographic characteristics, ODD symptoms, deviant peer association, school climate, and parental monitoring. Sixth graders with elevated ADHD symptoms engaged in somewhat fewer prosocial behaviors (d= −0.44) and more aggressive behavior (d= 0.20) relative to their peers. These small social behavioral deficits decreased but were not normalized across the middle school years. Contrary to hypotheses, social-cognitive problem solving was not impaired in the ADHD group, and did not mediate the association between ADHD and social behavior during the middle school years. ADHD and social-cognitive problem solving contributed independently to social behavior, both in sixth grade and across the middle school years; the influence of social-cognitive problem solving on social behavior was highly similar for the ADHD and non-ADHD groups. PMID:26595479

Codes of professional responsibility for lawyers: ethics or law?

PubMed

Lawry, R P

1984-01-01

The American Bar Association has three times in this century produced a code of ethics for lawyers. The movement has clearly been from a general, hortatory format to one of a statement of principles of law. In the ABA's latest effort, the problems of client confidentiality loom as the most serious and most difficult to solve. The question of ethics versus law weighs heavily in this context, and the ABA's latest resolutions of the confidentiality problems are found to be unsatisfactory.

Design of continuous surface-relief phase plates by surface-based simulated annealing to achieve control of focal-plane irradiance

NASA Astrophysics Data System (ADS)

Lin, Y.; Kessler, T. J.; Lawrence, G. N.

1996-10-01

High-performance phase plates are of vital concern for controlling the far-field irradiance of laser-fusion systems. Several designs for solving this difficult problem have been reported in Optics Letters [e. g., S. N. Dixit et al., Opt. Lett. 19, 417 (1994)]. We report a surface-based form of simulated annealing that significantly improves the irradiance control while eliminating the high-scatter problems that have plagued other methods.

Active and Healthy Ageing as a Wicked Problem: The Contribution of a Multidisciplinary Research University.

PubMed

Riva, Giuseppe; Graffigna, Guendalina; Baitieri, Maddalena; Amato, Alessandra; Bonanomi, Maria Grazia; Valentini, Paolo; Castelli, Guido

2014-01-01

The quest for an active and healthy ageing can be considered a "wicked problem." It is a social and cultural problem, which is difficult to solve because of incomplete, changing, and contradictory requirements. These problems are tough to manage because of their social complexity. They are a group of linked problems embedded in the structure of the communities in which they occur. First, they require the knowledge of the social and cultural context in which they occur. They can be solved only by understanding of what people do and why they do it. Second, they require a multidisciplinary approach. Wicked problems can have different solutions, so it is critical to capture the full range of possibilities and interpretations. Thus, we suggest that Università Cattolica del Sacro Cuore (UCSC) is well suited for accepting and managing this challenge because of its applied research orientation, multidisciplinary approach, and integrated vision. After presenting the research activity of UCSC, we describe a possible "systems thinking" strategy to consider the complexity and interdependence of active ageing and healthy living.

Multitask SVM learning for remote sensing data classification

NASA Astrophysics Data System (ADS)

Leiva-Murillo, Jose M.; Gómez-Chova, Luis; Camps-Valls, Gustavo

2010-10-01

Many remote sensing data processing problems are inherently constituted by several tasks that can be solved either individually or jointly. For instance, each image in a multitemporal classification setting could be taken as an individual task but relation to previous acquisitions should be properly considered. In such problems, different modalities of the data (temporal, spatial, angular) gives rise to changes between the training and test distributions, which constitutes a difficult learning problem known as covariate shift. Multitask learning methods aim at jointly solving a set of prediction problems in an efficient way by sharing information across tasks. This paper presents a novel kernel method for multitask learning in remote sensing data classification. The proposed method alleviates the dataset shift problem by imposing cross-information in the classifiers through matrix regularization. We consider the support vector machine (SVM) as core learner and two regularization schemes are introduced: 1) the Euclidean distance of the predictors in the Hilbert space; and 2) the inclusion of relational operators between tasks. Experiments are conducted in the challenging remote sensing problems of cloud screening from multispectral MERIS images and for landmine detection.

Ultra-high-field fMRI insights on insight: Neural correlates of the Aha!-moment.

PubMed

Tik, Martin; Sladky, Ronald; Luft, Caroline Di Bernardi; Willinger, David; Hoffmann, André; Banissy, Michael J; Bhattacharya, Joydeep; Windischberger, Christian

2018-04-17

Finding creative solutions to difficult problems is a fundamental aspect of human culture and a skill highly needed. However, the exact neural processes underlying creative problem solving remain unclear. Insightful problem solving tasks were shown to be a valid method for investigating one subcomponent of creativity: the Aha!-moment. Finding insightful solutions during a remote associates task (RAT) was found to elicit specific cortical activity changes. Considering the strong affective components of Aha!-moments, as manifested in the subjectively experienced feeling of relief following the sudden emergence of the solution of the problem without any conscious forewarning, we hypothesized the subcortical dopaminergic reward network to be critically engaged during Aha. To investigate those subcortical contributions to insight, we employed ultra-high-field 7 T fMRI during a German Version of the RAT. During this task, subjects were exposed to word triplets and instructed to find a solution word being associated with all the three given words. They were supposed to press a button as soon as they felt confident about their solution without further revision, allowing us to capture the exact event of Aha!-moment. Besides the finding on cortical involvement of the left anterior middle temporal gyrus (aMTG), here we showed for the first time robust subcortical activity changes related to insightful problem solving in the bilateral thalamus, hippocampus, and the dopaminergic midbrain comprising ventral tegmental area (VTA), nucleus accumbens (NAcc), and caudate nucleus. These results shed new light on the affective neural mechanisms underlying insightful problem solving. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

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

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

Applications of Evolutionary Technology to Manufacturing and Logistics Systems : State-of-the Art Survey

NASA Astrophysics Data System (ADS)

Gen, Mitsuo; Lin, Lin

Many combinatorial optimization problems from industrial engineering and operations research in real-world are very complex in nature and quite hard to solve them by conventional techniques. Since the 1960s, there has been an increasing interest in imitating living beings to solve such kinds of hard combinatorial optimization problems. Simulating the natural evolutionary process of human beings results in stochastic optimization techniques called evolutionary algorithms (EAs), which can often outperform conventional optimization methods when applied to difficult real-world problems. In this survey paper, we provide a comprehensive survey of the current state-of-the-art in the use of EA in manufacturing and logistics systems. In order to demonstrate the EAs which are powerful and broadly applicable stochastic search and optimization techniques, we deal with the following engineering design problems: transportation planning models, layout design models and two-stage logistics models in logistics systems; job-shop scheduling, resource constrained project scheduling in manufacturing system.

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

It's a kind of magic-what self-reports can reveal about the phenomenology of insight problem solving.

PubMed

Danek, Amory H; Fraps, Thomas; von Müller, Albrecht; Grothe, Benedikt; Öllinger, Michael

2014-01-01

Magic tricks usually remain a mystery to the observer. For the sake of science, we offered participants the opportunity to discover the magician's secret method by repeatedly presenting the same trick and asking them to find out how the trick worked. In the context of insightful problem solving, the present work investigated the emotions that participants experience upon solving a magic trick. We assumed that these emotions form the typical "Aha! experience" that accompanies insightful solutions to difficult problems. We aimed to show that Aha! experiences can be triggered by magic tricks and to systematically explore the phenomenology of the Aha! experience by breaking it down into five previously postulated dimensions. 34 video clips of different magic tricks were presented up to three times to 50 participants who had to find out how the trick was accomplished, and to indicate whether they had experienced an Aha! during the solving process. Participants then performed a comprehensive quantitative and qualitative assessment of their Aha! experiences which was repeated after 14 days to control for its reliability. 41% of all suggested solutions were accompanied by an Aha! experience. The quantitative assessment remained stable across time in all five dimensions. Happiness was rated as the most important dimension. This primacy of positive emotions was also reflected in participants' qualitative self-reports which contained more emotional than cognitive aspects. Implementing magic tricks as problem solving task, we could show that strong Aha! experiences can be triggered if a trick is solved. We could at least partially capture the phenomenology of Aha! by identifying one prevailing aspect (positive emotions), a new aspect (release of tension upon gaining insight into a magic trick) and one less important aspect (impasse).

It's a kind of magic—what self-reports can reveal about the phenomenology of insight problem solving

PubMed Central

Danek, Amory H.; Fraps, Thomas; von Müller, Albrecht; Grothe, Benedikt; Öllinger, Michael

2014-01-01

Magic tricks usually remain a mystery to the observer. For the sake of science, we offered participants the opportunity to discover the magician's secret method by repeatedly presenting the same trick and asking them to find out how the trick worked. In the context of insightful problem solving, the present work investigated the emotions that participants experience upon solving a magic trick. We assumed that these emotions form the typical “Aha! experience” that accompanies insightful solutions to difficult problems. We aimed to show that Aha! experiences can be triggered by magic tricks and to systematically explore the phenomenology of the Aha! experience by breaking it down into five previously postulated dimensions. 34 video clips of different magic tricks were presented up to three times to 50 participants who had to find out how the trick was accomplished, and to indicate whether they had experienced an Aha! during the solving process. Participants then performed a comprehensive quantitative and qualitative assessment of their Aha! experiences which was repeated after 14 days to control for its reliability. 41% of all suggested solutions were accompanied by an Aha! experience. The quantitative assessment remained stable across time in all five dimensions. Happiness was rated as the most important dimension. This primacy of positive emotions was also reflected in participants' qualitative self-reports which contained more emotional than cognitive aspects. Implementing magic tricks as problem solving task, we could show that strong Aha! experiences can be triggered if a trick is solved. We could at least partially capture the phenomenology of Aha! by identifying one prevailing aspect (positive emotions), a new aspect (release of tension upon gaining insight into a magic trick) and one less important aspect (impasse). PMID:25538658

Solving Large Problems Quickly: Progress in 2001-2003

NASA Technical Reports Server (NTRS)

Mowry, Todd C.; Colohan, Christopher B.; Brown, Angela Demke; Steffan, J. Gregory; Zhai, Antonia

2004-01-01

This document describes the progress we have made and the lessons we have learned in 2001 through 2003 under the NASA grant entitled "Solving Important Problems Faster". The long-term goal of this research is to accelerate large, irregular scientific applications which have enormous data sets and which are difficult to parallelize. To accomplish this goal, we are exploring two complementary techniques: (i) using compiler-inserted prefetching to automatically hide the I/O latency of accessing these large data sets from disk; and (ii) using thread-level data speculation to enable the optimistic parallelization of applications despite uncertainty as to whether data dependences exist between the resulting threads which would normally make them unsafe to execute in parallel. Overall, we made significant progress in 2001 through 2003, and the project has gone well.

BBPH: Using progressive hedging within branch and bound to solve multi-stage stochastic mixed integer programs

DOE PAGES

Barnett, Jason; Watson, Jean -Paul; Woodruff, David L.

2016-11-27

Progressive hedging, though an effective heuristic for solving stochastic mixed integer programs (SMIPs), is not guaranteed to converge in this case. Here, we describe BBPH, a branch and bound algorithm that uses PH at each node in the search tree such that, given sufficient time, it will always converge to a globally optimal solution. Additionally, to providing a theoretically convergent “wrapper” for PH applied to SMIPs, computational results demonstrate that for some difficult problem instances branch and bound can find improved solutions after exploring only a few nodes.

Solving the Traveling Salesman's Problem Using the African Buffalo Optimization.

PubMed

Odili, Julius Beneoluchi; Mohmad Kahar, Mohd Nizam

2016-01-01

This paper proposes the African Buffalo Optimization (ABO) which is a new metaheuristic algorithm that is derived from careful observation of the African buffalos, a species of wild cows, in the African forests and savannahs. This animal displays uncommon intelligence, strategic organizational skills, and exceptional navigational ingenuity in its traversal of the African landscape in search for food. The African Buffalo Optimization builds a mathematical model from the behavior of this animal and uses the model to solve 33 benchmark symmetric Traveling Salesman's Problem and six difficult asymmetric instances from the TSPLIB. This study shows that buffalos are able to ensure excellent exploration and exploitation of the search space through regular communication, cooperation, and good memory of its previous personal exploits as well as tapping from the herd's collective exploits. The results obtained by using the ABO to solve these TSP cases were benchmarked against the results obtained by using other popular algorithms. The results obtained using the African Buffalo Optimization algorithm are very competitive.

Solving the Traveling Salesman's Problem Using the African Buffalo Optimization

PubMed Central

Odili, Julius Beneoluchi; Mohmad Kahar, Mohd Nizam

2016-01-01

This paper proposes the African Buffalo Optimization (ABO) which is a new metaheuristic algorithm that is derived from careful observation of the African buffalos, a species of wild cows, in the African forests and savannahs. This animal displays uncommon intelligence, strategic organizational skills, and exceptional navigational ingenuity in its traversal of the African landscape in search for food. The African Buffalo Optimization builds a mathematical model from the behavior of this animal and uses the model to solve 33 benchmark symmetric Traveling Salesman's Problem and six difficult asymmetric instances from the TSPLIB. This study shows that buffalos are able to ensure excellent exploration and exploitation of the search space through regular communication, cooperation, and good memory of its previous personal exploits as well as tapping from the herd's collective exploits. The results obtained by using the ABO to solve these TSP cases were benchmarked against the results obtained by using other popular algorithms. The results obtained using the African Buffalo Optimization algorithm are very competitive. PMID:26880872

Blind compressed sensing image reconstruction based on alternating direction method

NASA Astrophysics Data System (ADS)

Liu, Qinan; Guo, Shuxu

2018-04-01

In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

Use of NASTRAN as a teaching aid

NASA Technical Reports Server (NTRS)

Wilkinson, M. T.

1972-01-01

Recent experiences with incorporating NASTRAN as a teaching tool in undergraduate courses was found pedagogically sound. Students with no previous computerized structures background are able to readily grasp the program's logic and begin solving realistic problems rapidly. The educational benefit is significantly enhanced by NASTRAN's plotting feature. However, the cost of operating the level 12 version makes the program difficult to justify.

The Effects of Using Exploratory Computerized Environments in Grades 1 to 8 Mathematics: A Meta-Analysis of Research

ERIC Educational Resources Information Center

Sokolowski, Andrzej; Li, Yeping; Willson, Victor

2015-01-01

Background: The process of problem solving is difficult for students; thus, mathematics educators have made multiple attempts to seek ways of making this process more accessible to learners. The purpose of this study was to examine the effect size statistic of utilizing exploratory computerized environments (ECEs) to support the process of word…

The Courseware of Discontinuous Nature of Matter in Teaching the States of Matter and Their Changes

ERIC Educational Resources Information Center

Sopandi, Wahyu; Kadarohman, Asep; Rosbiono, Momo; Latip, Abdul; Sukardi, Rendi Restiana

2018-01-01

Among three levels of chemical representation, the sub-microscopic level is the most difficult to learn by students. To solve the problem, it is assumed that the concept of the discontinuous nature of matter or particle concept should be mastered initially by students before they learn sub-microscopic representations of further chemical phenomena.…

Watch the lights. A visual communication system.

PubMed

Rahtz, S K

1989-01-01

The trend for hospitals to market their emergency care services results in a greater demand on radiology departments, states Ms. Rahtz. Radiology must provide efficient service to both departments, even when it is difficult to predict patient flow in the emergency care center. Improved communication is the key, and a light system installed at Morton Plant Hospital is one alternative for solving the problem.

Everyday Expertise in Self-Management of Diabetes in the Dominican Republic: Implications for Learning and Performance Support Systems Design

ERIC Educational Resources Information Center

Reyes Paulino, Lisette G.

2012-01-01

An epidemic such as diabetes is an extremely complex public health, economic and social problem that is difficult to solve through medical expertise alone. Evidence-based models for improving healthcare delivery systems advocate educating patients to become more active participants in their own care. This shift demands preparing chronically ill…

Nice or effective? Social problem solving strategies in patients with major depressive disorder.

PubMed

Thoma, Patrizia; Schmidt, Tobias; Juckel, Georg; Norra, Christine; Suchan, Boris

2015-08-30

Our study addressed distinct aspects of social problem solving in 28 hospitalized patients with Major Depressive Disorder (MDD) and 28 matched healthy controls. Three scenario-based tests assessed the ability to infer the mental states of story characters in difficult interpersonal situations, the capacity to freely generate good strategies for dealing with such situations and the ability to identify the best solutions among less optimal alternatives. Also, standard tests assessing attention, memory, executive function and trait empathy were administered. Compared to controls, MDD patients showed impaired interpretation of other peoples' sarcastic remarks but not of the mental states underlying other peoples' actions. Furthermore, MDD patients generated fewer strategies that were socially sensitive and practically effective at the same time or at least only socially sensitive. Overall, while the free generation of adequate strategies for difficult social situations was impaired, recognition of optimal solutions among alternatives was spared in MDD patients. Higher generation scores were associated with higher trait empathy and cognitive flexibility scores. We suggest that this specific pattern of impairments ought to be considered in the development of therapies addressing impaired social skills in MDD. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The stories they tell: How third year medical students portray patients, family members, physicians, and themselves in difficult encounters.

PubMed

Shapiro, Johanna; Rakhra, Pavandeep; Wong, Adrianne

2016-10-01

Physicians have long had patients whom they have labeled "difficult", but little is known about how medical students perceive difficult encounters with patients. In this study, we analyzed 134 third year medical students' reflective essays written over an 18-month period about difficult student-patient encounters. We used a qualitative computerized software program, Atlas.ti to analyze students' observations and reflections. Main findings include that students described patients who were angry and upset; noncompliant with treatment plans; discussed "nonmedical" problems; fearful, worried, withdrawn, or "disinterested" in their health. Students often described themselves as anxious, uncertain, confused, and frustrated. Nevertheless, they saw themselves behaving in empathic and patient-centered ways while also taking refuge in "standard" behaviors not necessarily appropriate to the circumstances. Students rarely mentioned receiving guidance from attendings regarding how to manage these challenging interactions. These third-year medical students recognized the importance of behaving empathically in difficult situations and often did so. However, they often felt overwhelmed and frustrated, resorting to more reductive behaviors that did not match the needs of the patient. Students need more guidance from attending physicians in order to approach difficult interactions with specific problem-solving skills while maintaining an empathic, patient-centered context.

Optimal Control and Smoothing Techniques for Computing Minimum Fuel Orbital Transfers and Rendezvous

NASA Astrophysics Data System (ADS)

Epenoy, R.; Bertrand, R.

We investigate in this paper the computation of minimum fuel orbital transfers and rendezvous. Each problem is seen as an optimal control problem and is solved by means of shooting methods [1]. This approach corresponds to the use of Pontryagin's Maximum Principle (PMP) [2-4] and leads to the solution of a Two Point Boundary Value Problem (TPBVP). It is well known that this last one is very difficult to solve when the performance index is fuel consumption because in this case the optimal control law has a particular discontinuous structure called "bang-bang". We will show how to modify the performance index by a term depending on a small parameter in order to yield regular controls. Then, a continuation method on this parameter will lead us to the solution of the original problem. Convergence theorems will be given. Finally, numerical examples will illustrate the interest of our method. We will consider two particular problems: The GTO (Geostationary Transfer Orbit) to GEO (Geostationary Equatorial Orbit) transfer and the LEO (Low Earth Orbit) rendezvous.

Experience with Aero- and Fluid-Dynamic Testing for Engineering and CFD Validation

NASA Technical Reports Server (NTRS)

Ross, James C.

2016-01-01

Ever since computations have been used to simulate aerodynamics the need to ensure that the computations adequately represent real life has followed. Many experiments have been performed specifically for validation and as computational methods have improved, so have the validation experiments. Validation is also a moving target because computational methods improve requiring validation for the new aspect of flow physics that the computations aim to capture. Concurrently, new measurement techniques are being developed that can help capture more detailed flow features pressure sensitive paint (PSP) and particle image velocimetry (PIV) come to mind. This paper will present various wind-tunnel tests the author has been involved with and how they were used for validation of various kinds of CFD. A particular focus is the application of advanced measurement techniques to flow fields (and geometries) that had proven to be difficult to predict computationally. Many of these difficult flow problems arose from engineering and development problems that needed to be solved for a particular vehicle or research program. In some cases the experiments required to solve the engineering problems were refined to provide valuable CFD validation data in addition to the primary engineering data. All of these experiments have provided physical insight and validation data for a wide range of aerodynamic and acoustic phenomena for vehicles ranging from tractor-trailers to crewed spacecraft.

Solving inverse problem for Markov chain model of customer lifetime value using flower pollination algorithm

NASA Astrophysics Data System (ADS)

Al-Ma'shumah, Fathimah; Permana, Dony; Sidarto, Kuntjoro Adji

2015-12-01

Customer Lifetime Value is an important and useful concept in marketing. One of its benefits is to help a company for budgeting marketing expenditure for customer acquisition and customer retention. Many mathematical models have been introduced to calculate CLV considering the customer retention/migration classification scheme. A fairly new class of these models which will be described in this paper uses Markov Chain Models (MCM). This class of models has the major advantage for its flexibility to be modified to several different cases/classification schemes. In this model, the probabilities of customer retention and acquisition play an important role. From Pfeifer and Carraway, 2000, the final formula of CLV obtained from MCM usually contains nonlinear form of the transition probability matrix. This nonlinearity makes the inverse problem of CLV difficult to solve. This paper aims to solve this inverse problem, yielding the approximate transition probabilities for the customers, by applying metaheuristic optimization algorithm developed by Yang, 2013, Flower Pollination Algorithm. The major interpretation of obtaining the transition probabilities are to set goals for marketing teams in keeping the relative frequencies of customer acquisition and customer retention.

Based on the Theory of TRIZ Solving the Problem of 18650 Battery Electrolyte Filling

NASA Astrophysics Data System (ADS)

Shao-hua, Cui; Jiang-ping, Mei; Ling-hua, Zhang; Xiao, Du

2017-12-01

As a type of standardized battery cylindrical 18650 lithium-ion battery is widely used in new energy vehicle industry, It can be produced in large quantities without changing type. Because of its special advantages than others. But due to the pressure of rising capacity, electrolyte filling (which is short for E/L) process has become more and more difficult. While reducing the production efficiency eases the problem of E/L, it also poses performance and security problems. So the issue cannot be solved using the common knowledge of the industry. In this paper, This article does not use lean manufacturing or 6Sigma methods, we use TRIZ theory to analyze the E/L difficulty problem in detail (using causal analysis, technical contradiction analysis, substance - field analysis, physical contradiction analysis and other tools). By creating an atmosphere of vacuum and pressure replace the existing E/L tooling for single cell mechanical structure, through blowing hot air method to increase the temperature of electrolyte, Dissolving the J/R into a electrolyte tank which is full of 0.3Mpa nitrogen. Under the premise of not reducing the production efficiency, at the same time ensuring performance and safety, we try to find out a method to solve the E/L difficulty problem, and would get better application in the construction of new production lines in the new factory.

The Function Analysis of Informationization in New Rural Cooperatives Medical Service Management

NASA Astrophysics Data System (ADS)

Zhou, Yuefeng; Liu, Min

The establishment of new rural cooperative medical system is an important action for comprehensive affluent society. It is an important measure for Central Party Committee and State Council to solve "three rural" issue effectively and to overall urban and rural, regional, coordinated economic and social development, building a well-off society in the new situation. It has important role to alleviate farmers to see a doctor expensively, see a doctor difficultly, reduce the burden on farmers and improve their level of health protection and quality of life, solve the problem of poor because of illness and the problem of returning poor due to illness, promote the production and rural economic development and stability in the rural areas. This article will analyze the function of informationization in new rural cooperative medical service management selectively.

Synthetic depth data creation for sensor setup planning and evaluation of multi-camera multi-person trackers

NASA Astrophysics Data System (ADS)

Pattke, Marco; Martin, Manuel; Voit, Michael

2017-05-01

Tracking people with cameras in public areas is common today. However with an increasing number of cameras it becomes harder and harder to view the data manually. Especially in safety critical areas automatic image exploitation could help to solve this problem. Setting up such a system can however be difficult because of its increased complexity. Sensor placement is critical to ensure that people are detected and tracked reliably. We try to solve this problem using a simulation framework that is able to simulate different camera setups in the desired environment including animated characters. We combine this framework with our self developed distributed and scalable system for people tracking to test its effectiveness and can show the results of the tracking system in real time in the simulated environment.

Power System Reliability Assessment by Analysing Voltage Dips on the Blue Horizon Bay 22KV Overhead Line in the Nelson Mandela Bay Municipality

NASA Astrophysics Data System (ADS)

Lamour, B. G.; Harris, R. T.; Roberts, A. G.

2010-06-01

Power system reliability problems are very difficult to solve because the power systems are complex and geographically widely distributed and influenced by numerous unexpected events. It is therefore imperative to employ the most efficient optimization methods in solving the problems relating to reliability of the power system. This paper presents a reliability analysis and study of the power interruptions resulting from severe power outages in the Nelson Mandela Bay Municipality (NMBM), South Africa and includes an overview of the important factors influencing reliability, and methods to improve the reliability. The Blue Horizon Bay 22 kV overhead line, supplying a 6.6 kV residential sector has been selected. It has been established that 70% of the outages, recorded at the source, originate on this feeder.

Research on the Wire Network Signal Prediction Based on the Improved NNARX Model

NASA Astrophysics Data System (ADS)

Zhang, Zipeng; Fan, Tao; Wang, Shuqing

It is difficult to obtain accurately the wire net signal of power system's high voltage power transmission lines in the process of monitoring and repairing. In order to solve this problem, the signal measured in remote substation or laboratory is employed to make multipoint prediction to gain the needed data. But, the obtained power grid frequency signal is delay. In order to solve the problem, an improved NNARX network which can predict frequency signal based on multi-point data collected by remote substation PMU is describes in this paper. As the error curved surface of the NNARX network is more complicated, this paper uses L-M algorithm to train the network. The result of the simulation shows that the NNARX network has preferable predication performance which provides accurate real time data for field testing and maintenance.

Concept of a demonstrational hybrid reactor—a tokamak with molten-salt blanket for 233U fuel production: 1. Concept of a stationary Tokamak as a neutron source

NASA Astrophysics Data System (ADS)

Azizov, E. A.; Gladush, G. G.; Dokuka, V. N.; Khayrutdinov, R. R.

2015-12-01

On the basis of current understanding of physical processes in tokamaks and taking into account engineering constraints, it is shown that a low-cost facility of a moderate size can be designed within the adopted concept. This facility makes it possible to achieve the power density of neutron flux which is of interest, in particular, for solving the problem of 233U fuel production from thorium. By using a molten-salt blanket, the important task of ensuring the safe operation of such a reactor in the case of possible coolant loss is accomplished. Moreover, in a hybrid reactor with the blanket based on liquid salts, the problem of periodic refueling that is difficult to perform in solid blankets can be solved.

Design of continuous surface-relief phase plates by surface-based simulated annealing to achieve control of focal-plane irradiance

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

Lin, Y.; Kessler, T.J.; Lawrence, G.N.

1996-10-01

High-performance phase plates are of vital concern for controlling the far-field irradiance of laser-fusion systems. Several designs for solving this difficult problem have been reported in {ital Optics} {ital Letters} [e.g., S. N. Dixit {ital et} {ital al}., Opt. Lett. {bold 19}, 417 (1994)]. We report a surface-based form of simulated annealing that significantly improves the irradiance control while eliminating the high-scatter problems that have plagued other methods. {copyright} {ital 1996 Optical Society of America.}

Three-phase flow measurement in the petroleum industry

NASA Astrophysics Data System (ADS)

Thorn, R.; Johansen, G. A.; Hjertaker, B. T.

2013-01-01

The problem of how to accurately measure the flowrate of oil-gas-water mixtures in a pipeline remains one of the key challenges in the petroleum industry. This paper discusses why three-phase flow measurement is still important and why it remains a difficult problem to solve. The measurement strategies and principal base technologies currently used by commercial manufacturers are described, and research developments that could influence future flowmeter design are considered. Finally, future issues, which will need to be addressed by manufacturers and users of three-phase flowmeters, are discussed.

Acceptability of participatory social network analysis for problem-solving in Australian Aboriginal health service partnerships

PubMed Central

2012-01-01

Background While participatory social network analysis can help health service partnerships to solve problems, little is known about its acceptability in cross-cultural settings. We conducted two case studies of chronic illness service partnerships in 2007 and 2008 to determine whether participatory research incorporating social network analysis is acceptable for problem-solving in Australian Aboriginal health service delivery. Methods Local research groups comprising 13–19 partnership staff, policy officers and community members were established at each of two sites to guide the research and to reflect and act on the findings. Network and work practice surveys were conducted with 42 staff, and the results were fed back to the research groups. At the end of the project, 19 informants at the two sites were interviewed, and the researchers conducted critical reflection. The effectiveness and acceptability of the participatory social network method were determined quantitatively and qualitatively. Results Participants in both local research groups considered that the network survey had accurately described the links between workers related to the exchange of clinical and cultural information, team care relationships, involvement in service management and planning and involvement in policy development. This revealed the function of the teams and the roles of workers in each partnership. Aboriginal workers had a high number of direct links in the exchange of cultural information, illustrating their role as the cultural resource, whereas they had fewer direct links with other network members on clinical information exchange and team care. The problem of their current and future roles was discussed inside and outside the local research groups. According to the interview informants the participatory network analysis had opened the way for problem-solving by “putting issues on the table”. While there were confronting and ethically challenging aspects, these informants considered that with flexibility of data collection to account for the preferences of Aboriginal members, then the method was appropriate in cross-cultural contexts for the difficult discussions that are needed to improve partnerships. Conclusion Critical reflection showed that the preconditions for difficult discussions are, first, that partners have the capacity to engage in such discussions, second, that partners assess whether the effort required for these discussions is balanced by the benefits they gain from the partnership, and, third, that “boundary spanning” staff can facilitate commitment to partnership goals. PMID:22682504

Investigating the Role of Computer-Supported Annotation in Problem-Solving-Based Teaching: An Empirical Study of a Scratch Programming Pedagogy

ERIC Educational Resources Information Center

Su, Addison Y. S.; Yang, Stephen J. H.; Hwang, Wu-Yuin; Huang, Chester S. J.; Tern, Ming-Yu

2014-01-01

For more than 2 years, Scratch programming has been taught in Taiwanese elementary schools. However, past studies have shown that it is difficult to find appropriate learning methods or tools to boost students' Scratch programming performance. This inability to readily identify tutoring tools has become one of the primary challenges addressed in…

Local (L, [epsilon])-Approximation of a Function of Single Variable: An Alternative Way to Define Limit

ERIC Educational Resources Information Center

Bokhari, M. A.; Yushau, B.

2006-01-01

At the start of a freshman calculus course, many students conceive the classical definition of limit as the most problematic part of calculus. They not only find it difficult to understand, but also consider it of no use while solving most of the limit problems and therefore, skip it. This paper reformulates the rigorous definition of limit, which…

Developing a Graphical Tool for Students to Understand Air Resistance and Free Fall: When Heavier Objects "Do" Fall Faster

ERIC Educational Resources Information Center

Ferreira, Annalize; Seyffert, Albertus S.; Lemmer, Miriam

2017-01-01

Many students find it difficult to apply certain physics concepts to their daily lives. This is especially true when they perceive a principle taught in physics class as being in conflict with their experience. An important instance of this occurs when students are instructed to ignore the effect of air resistance when solving kinematics problems.…

Determination of Al Content in Commercial Samples through Stoichiometry: A Simple Experiment for an Advanced High-School Chemistry Olympiad Preparatory Course

ERIC Educational Resources Information Center

de Lima, Kassio M. G.; da Silva, Amison R. L.; de Souza, Joao P. F.; das Neves, Luiz S.; Gasparotto, Luiz H. S.

2014-01-01

Stoichiometry has always been a puzzling subject. This may be partially due to the way it is introduced to students, with stoichiometric coefficients usually provided in the reaction. If the stoichiometric coefficients are not given, students find it very difficult to solve problems. This article describes a simple 4-h laboratory experiment for…

When math operations have visuospatial meanings versus purely symbolic definitions: Which solving stages and brain regions are affected?

PubMed

Pyke, Aryn A; Fincham, Jon M; Anderson, John R

2017-06-01

How does processing differ during purely symbolic problem solving versus when mathematical operations can be mentally associated with meaningful (here, visuospatial) referents? Learners were trained on novel math operations (↓, ↑), that were defined strictly symbolically or in terms of a visuospatial interpretation (operands mapped to dimensions of shaded areas, answer = total area). During testing (scanner session), no visuospatial representations were displayed. However, we expected visuospatially-trained learners to form mental visuospatial representations for problems, and exhibit distinct activations. Since some solution intervals were long (~10s) and visuospatial representations might only be instantiated in some stages during solving, group differences were difficult to detect when treating the solving interval as a whole. However, an HSMM-MVPA process (Anderson and Fincham, 2014a) to parse fMRI data identified four distinct problem-solving stages in each group, dubbed: 1) encode; 2) plan; 3) compute; and 4) respond. We assessed stage-specific differences across groups. During encoding, several regions implicated in general semantic processing and/or mental imagery were more active in visuospatially-trained learners, including: bilateral supramarginal, precuneus, cuneus, parahippocampus, and left middle temporal regions. Four of these regions again emerged in the computation stage: precuneus, right supramarginal/angular, left supramarginal/inferior parietal, and left parahippocampal gyrus. Thus, mental visuospatial representations may not just inform initial problem interpretation (followed by symbolic computation), but may scaffold on-going computation. In the second stage, higher activations were found among symbolically-trained solvers in frontal regions (R. medial and inferior and L. superior) and the right angular and middle temporal gyrus. Activations in contrasting regions may shed light on solvers' degree of use of symbolic versus mental visuospatial strategies, even in absence of behavioral differences. Copyright © 2017 Elsevier Inc. All rights reserved.

Cost effective simulation-based multiobjective optimization in the performance of an internal combustion engine

NASA Astrophysics Data System (ADS)

Aittokoski, Timo; Miettinen, Kaisa

2008-07-01

Solving real-life engineering problems can be difficult because they often have multiple conflicting objectives, the objective functions involved are highly nonlinear and they contain multiple local minima. Furthermore, function values are often produced via a time-consuming simulation process. These facts suggest the need for an automated optimization tool that is efficient (in terms of number of objective function evaluations) and capable of solving global and multiobjective optimization problems. In this article, the requirements on a general simulation-based optimization system are discussed and such a system is applied to optimize the performance of a two-stroke combustion engine. In the example of a simulation-based optimization problem, the dimensions and shape of the exhaust pipe of a two-stroke engine are altered, and values of three conflicting objective functions are optimized. These values are derived from power output characteristics of the engine. The optimization approach involves interactive multiobjective optimization and provides a convenient tool to balance between conflicting objectives and to find good solutions.

Performance evaluation of firefly algorithm with variation in sorting for non-linear benchmark problems

NASA Astrophysics Data System (ADS)

Umbarkar, A. J.; Balande, U. T.; Seth, P. D.

2017-06-01

The field of nature inspired computing and optimization techniques have evolved to solve difficult optimization problems in diverse fields of engineering, science and technology. The firefly attraction process is mimicked in the algorithm for solving optimization problems. In Firefly Algorithm (FA) sorting of fireflies is done by using sorting algorithm. The original FA is proposed with bubble sort for ranking the fireflies. In this paper, the quick sort replaces bubble sort to decrease the time complexity of FA. The dataset used is unconstrained benchmark functions from CEC 2005 [22]. The comparison of FA using bubble sort and FA using quick sort is performed with respect to best, worst, mean, standard deviation, number of comparisons and execution time. The experimental result shows that FA using quick sort requires less number of comparisons but requires more execution time. The increased number of fireflies helps to converge into optimal solution whereas by varying dimension for algorithm performed better at a lower dimension than higher dimension.

An ethics dilemma: when parents and doctors disagree on the best treatment for the child.

PubMed

Oppenheim, Daniel; Brugières, Laurence; Corradini, Nadège; Vivant, Florence; Hartmann, Olivier

2004-09-01

The increasing complexity of present day medicine--with highly effective and yet risky treatments, individual and collective expectations, and evolving ideological and cultural landmarks--often gives rise to difficult ethical problems. Specific meetings are valuable for understanding such problems, acquiring the relevant skills and for gaining and transmitting experience on how to solve them. Parents and doctors may disagree about what is the best treatment. Such a difference of opinion is not rare but usually a solution can easily be found. This is not the case when the child is treated for a severe illness and when there is no clearly defined or satisfactory treatment for him\\her. We present how a dramatic conflict arose between the parents and the doctors faced with such a case (mostly because the staff failed to understand early enough the psychological factors at the root of the father's demands), how clinical, institutional and ethical problems were analysed during a meeting, and how they were solved.

Planning abilities and chess: a comparison of chess and non-chess players on the Tower of London task.

PubMed

Unterrainer, J M; Kaller, C P; Halsband, U; Rahm, B

2006-08-01

Playing chess requires problem-solving capacities in order to search through the chess problem space in an effective manner. Chess should thus require planning abilities for calculating many moves ahead. Therefore, we asked whether chess players are better problem solvers than non-chess players in a complex planning task. We compared planning performance between chess ( N=25) and non-chess players ( N=25) using a standard psychometric planning task, the Tower of London (ToL) test. We also assessed fluid intelligence (Raven Test), as well as verbal and visuospatial working memory. As expected, chess players showed better planning performance than non-chess players, an effect most strongly expressed in difficult problems. On the other hand, they showed longer planning and movement execution times, especially for incorrectly solved trials. No differences in fluid intelligence and verbal/visuospatial working memory were found between both groups. These findings indicate that better performance in chess players is associated with disproportionally longer solution times, although it remains to be investigated whether motivational or strategic differences account for this result.

Research on allocation efficiency of the daisy chain allocation algorithm

NASA Astrophysics Data System (ADS)

Shi, Jingping; Zhang, Weiguo

2013-03-01

With the improvement of the aircraft performance in reliability, maneuverability and survivability, the number of the control effectors increases a lot. How to distribute the three-axis moments into the control surfaces reasonably becomes an important problem. Daisy chain method is simple and easy to be carried out in the design of the allocation system. But it can not solve the allocation problem for entire attainable moment subset. For the lateral-directional allocation problem, the allocation efficiency of the daisy chain can be directly measured by the area of its subset of attainable moments. Because of the non-linear allocation characteristic, the subset of attainable moments of daisy-chain method is a complex non-convex polygon, and it is difficult to solve directly. By analyzing the two-dimensional allocation problems with a "micro-element" idea, a numerical calculation algorithm is proposed to compute the area of the non-convex polygon. In order to improve the allocation efficiency of the algorithm, a genetic algorithm with the allocation efficiency chosen as the fitness function is proposed to find the best pseudo-inverse matrix.

Side-branch technique for difficult guidewire placement in coronary bifurcation lesion.

PubMed

He, Xingwei; Gao, Bo; Liu, Yujian; Li, Zhuxi; Zeng, Hesong

2016-01-01

Despite tremendous advances in technology and skills, percutaneous coronary intervention (PCI) of bifurcation lesion (BL) remains a particular challenge for the interventionalist. During bifurcation PCI, safe guidewire placement in the main branch (MB) and the side branch (SB) is the first step for successful procedure. However, in certain cases, the complex pattern of vessel anatomy and the mix of plaque distribution may make target vessel wiring highly challenging. Therefore, specific techniques are required for solving this problem. Hereby, we describe a new use of side-branch technique for difficult guidewire placement in BL. Copyright © 2015 Elsevier Inc. All rights reserved.

Exact solution for the optimal neuronal layout problem.

PubMed

Chklovskii, Dmitri B

2004-10-01

Evolution perfected brain design by maximizing its functionality while minimizing costs associated with building and maintaining it. Assumption that brain functionality is specified by neuronal connectivity, implemented by costly biological wiring, leads to the following optimal design problem. For a given neuronal connectivity, find a spatial layout of neurons that minimizes the wiring cost. Unfortunately, this problem is difficult to solve because the number of possible layouts is often astronomically large. We argue that the wiring cost may scale as wire length squared, reducing the optimal layout problem to a constrained minimization of a quadratic form. For biologically plausible constraints, this problem has exact analytical solutions, which give reasonable approximations to actual layouts in the brain. These solutions make the inverse problem of inferring neuronal connectivity from neuronal layout more tractable.

Continuous Measurements and Quantitative Constraints: Challenge Problems for Discrete Modeling Techniques

NASA Technical Reports Server (NTRS)

Goodrich, Charles H.; Kurien, James; Clancy, Daniel (Technical Monitor)

2001-01-01

We present some diagnosis and control problems that are difficult to solve with discrete or purely qualitative techniques. We analyze the nature of the problems, classify them and explain why they are frequently encountered in systems with closed loop control. This paper illustrates the problem with several examples drawn from industrial and aerospace applications and presents detailed information on one important application: In-Situ Resource Utilization (ISRU) on Mars. The model for an ISRU plant is analyzed showing where qualitative techniques are inadequate to identify certain failure modes and to maintain control of the system in degraded environments. We show why the solution to the problem will result in significantly more robust and reliable control systems. Finally, we illustrate requirements for a solution to the problem by means of examples.

A, E, I, O, U and Always Y: A Simple Technique for Improving Communication and Assessment in the Mathematics Classroom

ERIC Educational Resources Information Center

Vazquez, Lorna Thomas

2008-01-01

This article describes the A, E, I, O, U technique, designed to help teachers ensure that teaching and learning are not mutually exclusive in the classroom. Most teachers would agree that motivating average teenagers to communicate how they got an answer or justify their problem-solving strategies can be as difficult as teaching a dog to whistle.…

Calculation Software

NASA Technical Reports Server (NTRS)

1994-01-01

MathSoft Plus 5.0 is a calculation software package for electrical engineers and computer scientists who need advanced math functionality. It incorporates SmartMath, an expert system that determines a strategy for solving difficult mathematical problems. SmartMath was the result of the integration into Mathcad of CLIPS, a NASA-developed shell for creating expert systems. By using CLIPS, MathSoft, Inc. was able to save the time and money involved in writing the original program.

A Dynamic Security Framework for Ambient Intelligent Systems: A Smart-Home Based eHealth Application

NASA Astrophysics Data System (ADS)

Compagna, Luca; El Khoury, Paul; Massacci, Fabio; Saidane, Ayda

Providing context-dependent security services is an important challenge for ambient intelligent systems. The complexity and the unbounded nature of such systems make it difficult even for the most experienced and knowledgeable security engineers, to foresee all possible situations and interactions when developing the system. In order to solve this problem context based self- diagnosis and reconfiguration at runtime should be provided.

Transient heat conduction in a heat fin

NASA Astrophysics Data System (ADS)

Brody, Jed; Brown, Max

2017-08-01

We immerse the bottom of a rod in ice water and record the time-dependent temperatures at positions along the length of the rod. Though the experiment is simple, a surprisingly difficult problem in heat conduction must be solved to obtain a theoretical fit to the measured data. The required equipment is very inexpensive and could be assigned as a homework exercise or a hands-on component of an online course.

Approximate method for calculating a thickwalled cylinder with rigidly clamped ends

NASA Astrophysics Data System (ADS)

Andreev, Vladimir

2018-03-01

Numerous papers dealing with the calculations of cylindrical bodies [1 -8 and others] have shown that analytic and numerical-analytical solutions in both homogeneous and inhomogeneous thick-walled shells can be obtained quite simply, using expansions in Fourier series on trigonometric functions, if the ends are hinged movable (sliding support). It is much more difficult to solve the problem of calculating shells with builtin ends.

Concept of a demonstrational hybrid reactor—a tokamak with molten-salt blanket for {sup 233}U fuel production: 1. Concept of a stationary Tokamak as a neutron source

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

Azizov, E. A.; Gladush, G. G., E-mail: gladush@triniti.ru; Dokuka, V. N.

2015-12-15

On the basis of current understanding of physical processes in tokamaks and taking into account engineering constraints, it is shown that a low-cost facility of a moderate size can be designed within the adopted concept. This facility makes it possible to achieve the power density of neutron flux which is of interest, in particular, for solving the problem of {sup 233}U fuel production from thorium. By using a molten-salt blanket, the important task of ensuring the safe operation of such a reactor in the case of possible coolant loss is accomplished. Moreover, in a hybrid reactor with the blanket basedmore » on liquid salts, the problem of periodic refueling that is difficult to perform in solid blankets can be solved.« less

Algorithm of probabilistic assessment of fully-mechanized longwall downtime

NASA Astrophysics Data System (ADS)

Domrachev, A. N.; Rib, S. V.; Govorukhin, Yu M.; Krivopalov, V. G.

2017-09-01

The problem of increasing the load on a long fully-mechanized longwall has several aspects, one of which is the improvement of efficiency in using available stoping equipment due to the increase in coefficient of the machine operating time of a shearer and other mining machines that form an integral part of the longwall set of equipment. The task of predicting the reliability indicators of stoping equipment is solved by the statistical evaluation of parameters of downtime exponential distribution and failure recovery. It is more difficult to solve the problems of downtime accounting in case of accidents in the face workings and, despite the statistical data on accidents in mine workings, no solution has been found to date. The authors have proposed a variant of probability assessment of workings caving using Poisson distribution and the duration of their restoration using normal distribution. The above results confirm the possibility of implementing the approach proposed by the authors.

When more of the same is better

NASA Astrophysics Data System (ADS)

Fontanari, José F.

2016-01-01

Problem solving (e.g., drug design, traffic engineering, software development) by task forces represents a substantial portion of the economy of developed countries. Here we use an agent-based model of cooperative problem-solving systems to study the influence of diversity on the performance of a task force. We assume that agents cooperate by exchanging information on their partial success and use that information to imitate the more successful agent in the system —the model. The agents differ only in their propensities to copy the model. We find that, for easy tasks, the optimal organization is a homogeneous system composed of agents with the highest possible copy propensities. For difficult tasks, we find that diversity can prevent the system from being trapped in sub-optimal solutions. However, when the system size is adjusted to maximize the performance the homogeneous systems outperform the heterogeneous systems, i.e., for optimal performance, sameness should be preferred to diversity.

Trajectory control method of stratospheric airship based on the sliding mode control and prediction in wind field

NASA Astrophysics Data System (ADS)

Zhang, Jia-shi; Yang, Xi-xiang

2017-11-01

The stratospheric airship has the characteristics of large inertia, long time delay and large disturbance of wind field , so the trajectory control is very difficult .Build the lateral three degrees of freedom dynamic model which consider the wind interference , the dynamics equation is linearized by the small perturbation theory, propose a trajectory control method Combine with the sliding mode control and prediction, design the trajectory controller , takes the HAA airship as the reference to carry out simulation analysis. Results show that the improved sliding mode control with front-feedback method not only can solve well control problems of airship trajectory in wind field, but also can effectively improve the control accuracy of the traditional sliding mode control method, solved problems that using the traditional sliding mode control to control. It provides a useful reference for dynamic modeling and trajectory control of stratospheric airship.

Optimal Integration of Departure and Arrivals in Terminal Airspace

NASA Technical Reports Server (NTRS)

Xue, Min; Zelinski, Shannon Jean

2012-01-01

Coordination of operations with spatially and temporally shared resources such as route segments, fixes, and runways improves the efficiency of terminal airspace management. Problems in this category include scheduling and routing, thus they are normally difficult to solve compared with pure scheduling problems. In order to reduce the computational time, a fast time algorithm formulation using a non-dominated sorting genetic algorithm (NSGA) was introduced in this work and applied to a test case based on existing literature. The experiment showed that new method can solve the whole problem in fast time instead of solving sub-problems sequentially with a window technique. The results showed a 60% or 406 second delay reduction was achieved by sharing departure fixes (more details on the comparison with MILP results will be presented in the final paper). Furthermore, the NSGA algorithm was applied to a problem in LAX terminal airspace, where interactions between 28% of LAX arrivals and 10% of LAX departures are resolved by spatial segregation, which may introduce unnecessary delays. In this work, spatial segregation, temporal segregation, and hybrid segregation were formulated using the new algorithm. Results showed that spatial and temporal segregation approaches achieved similar delay. Hybrid segregation introduced much less delay than the other two approaches. For a total of 9 interacting departures and arrivals, delay reduction varied from 4 minutes to 6.4 minutes corresponding flight time uncertainty from 0 to 60 seconds. Considering the amount of flights that could be affected, total annual savings with hybrid segregation would be significant.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2015-03-01

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

Tuning Parameters in Heuristics by Using Design of Experiments Methods

NASA Technical Reports Server (NTRS)

Arin, Arif; Rabadi, Ghaith; Unal, Resit

2010-01-01

With the growing complexity of today's large scale problems, it has become more difficult to find optimal solutions by using exact mathematical methods. The need to find near-optimal solutions in an acceptable time frame requires heuristic approaches. In many cases, however, most heuristics have several parameters that need to be "tuned" before they can reach good results. The problem then turns into "finding best parameter setting" for the heuristics to solve the problems efficiently and timely. One-Factor-At-a-Time (OFAT) approach for parameter tuning neglects the interactions between parameters. Design of Experiments (DOE) tools can be instead employed to tune the parameters more effectively. In this paper, we seek the best parameter setting for a Genetic Algorithm (GA) to solve the single machine total weighted tardiness problem in which n jobs must be scheduled on a single machine without preemption, and the objective is to minimize the total weighted tardiness. Benchmark instances for the problem are available in the literature. To fine tune the GA parameters in the most efficient way, we compare multiple DOE models including 2-level (2k ) full factorial design, orthogonal array design, central composite design, D-optimal design and signal-to-noise (SIN) ratios. In each DOE method, a mathematical model is created using regression analysis, and solved to obtain the best parameter setting. After verification runs using the tuned parameter setting, the preliminary results for optimal solutions of multiple instances were found efficiently.

Supervised Learning for Dynamical System Learning.

PubMed

Hefny, Ahmed; Downey, Carlton; Gordon, Geoffrey J

2015-01-01

Recently there has been substantial interest in spectral methods for learning dynamical systems. These methods are popular since they often offer a good tradeoff between computational and statistical efficiency. Unfortunately, they can be difficult to use and extend in practice: e.g., they can make it difficult to incorporate prior information such as sparsity or structure. To address this problem, we present a new view of dynamical system learning: we show how to learn dynamical systems by solving a sequence of ordinary supervised learning problems, thereby allowing users to incorporate prior knowledge via standard techniques such as L 1 regularization. Many existing spectral methods are special cases of this new framework, using linear regression as the supervised learner. We demonstrate the effectiveness of our framework by showing examples where nonlinear regression or lasso let us learn better state representations than plain linear regression does; the correctness of these instances follows directly from our general analysis.

An efficient strongly coupled immersed boundary method for deforming bodies

NASA Astrophysics Data System (ADS)

Goza, Andres; Colonius, Tim

2016-11-01

Immersed boundary methods treat the fluid and immersed solid with separate domains. As a result, a nonlinear interface constraint must be satisfied when these methods are applied to flow-structure interaction problems. This typically results in a large nonlinear system of equations that is difficult to solve efficiently. Often, this system is solved with a block Gauss-Seidel procedure, which is easy to implement but can require many iterations to converge for small solid-to-fluid mass ratios. Alternatively, a Newton-Raphson procedure can be used to solve the nonlinear system. This typically leads to convergence in a small number of iterations for arbitrary mass ratios, but involves the use of large Jacobian matrices. We present an immersed boundary formulation that, like the Newton-Raphson approach, uses a linearization of the system to perform iterations. It therefore inherits the same favorable convergence behavior. However, we avoid large Jacobian matrices by using a block LU factorization of the linearized system. We derive our method for general deforming surfaces and perform verification on 2D test problems of flow past beams. These test problems involve large amplitude flapping and a wide range of mass ratios. This work was partially supported by the Jet Propulsion Laboratory and Air Force Office of Scientific Research.

Spine lesion analysis in 3D CT data - Reporting on research progress

NASA Astrophysics Data System (ADS)

Jan, Jiri; Chmelik, Jiri; Jakubicek, Roman; Ourednicek, Petr; Amadori, Elena; Gavelli, Giampaolo

2018-04-01

The contribution describes progress in the long-term project concerning automatic diagnosis of spine bone lesions. There are two difficult problems: segmenting reliably possibly severely deformed vertebrae in the spine and then detect, segment and classify the lesions that are often hardly visible thus making even the medical expert decisions highly uncertain, with a large inter-expert variety. New approaches are described enabling to solve both problems with a success rate acceptable for clinical testing, at the same time speeding up the process substantially compared to the previous stage. The results are compared with previously published achievements.

A visual programming environment for the Navier-Stokes computer

NASA Technical Reports Server (NTRS)

Tomboulian, Sherryl; Crockett, Thomas W.; Middleton, David

1988-01-01

The Navier-Stokes computer is a high-performance, reconfigurable, pipelined machine designed to solve large computational fluid dynamics problems. Due to the complexity of the architecture, development of effective, high-level language compilers for the system appears to be a very difficult task. Consequently, a visual programming methodology has been developed which allows users to program the system at an architectural level by constructing diagrams of the pipeline configuration. These schematic program representations can then be checked for validity and automatically translated into machine code. The visual environment is illustrated by using a prototype graphical editor to program an example problem.

First-order convex feasibility algorithms for x-ray CT

PubMed Central

Sidky, Emil Y.; Jørgensen, Jakob S.; Pan, Xiaochuan

2013-01-01

Purpose: Iterative image reconstruction (IIR) algorithms in computed tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times, however, it is impractical to achieve accurate solution to the optimization of interest, which complicates design of IIR algorithms. This issue is particularly acute for CT with a limited angular-range scan, which leads to poorly conditioned system matrices and difficult to solve optimization problems. In this paper, we develop IIR algorithms which solve a certain type of optimization called convex feasibility. The convex feasibility approach can provide alternatives to unconstrained optimization approaches and at the same time allow for rapidly convergent algorithms for their solution—thereby facilitating the IIR algorithm design process. Methods: An accelerated version of the Chambolle−Pock (CP) algorithm is adapted to various convex feasibility problems of potential interest to IIR in CT. One of the proposed problems is seen to be equivalent to least-squares minimization, and two other problems provide alternatives to penalized, least-squares minimization. Results: The accelerated CP algorithms are demonstrated on a simulation of circular fan-beam CT with a limited scanning arc of 144°. The CP algorithms are seen in the empirical results to converge to the solution of their respective convex feasibility problems. Conclusions: Formulation of convex feasibility problems can provide a useful alternative to unconstrained optimization when designing IIR algorithms for CT. The approach is amenable to recent methods for accelerating first-order algorithms which may be particularly useful for CT with limited angular-range scanning. The present paper demonstrates the methodology, and future work will illustrate its utility in actual CT application. PMID:23464295

Semiclassical approach to finite-temperature quantum annealing with trapped ions

NASA Astrophysics Data System (ADS)

Raventós, David; Graß, Tobias; Juliá-Díaz, Bruno; Lewenstein, Maciej

2018-05-01

Recently it has been demonstrated that an ensemble of trapped ions may serve as a quantum annealer for the number-partitioning problem [Nat. Commun. 7, 11524 (2016), 10.1038/ncomms11524]. This hard computational problem may be addressed by employing a tunable spin-glass architecture. Following the proposal of the trapped-ion annealer, we study here its robustness against thermal effects; that is, we investigate the role played by thermal phonons. For the efficient description of the system, we use a semiclassical approach, and benchmark it against the exact quantum evolution. The aim is to understand better and characterize how the quantum device approaches a solution of an otherwise difficult to solve NP-hard problem.

Practical advantages of evolutionary computation

NASA Astrophysics Data System (ADS)

Fogel, David B.

1997-10-01

Evolutionary computation is becoming a common technique for solving difficult, real-world problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific advantages include the flexibility of the procedures, as well as their ability to self-adapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine.

I. Cognitive and Instructional Factors Relating to Students' Development of Personal Models of Chemical Systems in the General Chemistry Laboratory II. Solvation in Supercritical Carbon Dioxide/Ethanol Mixtures Studied by Molecular Dynamics Simulation

ERIC Educational Resources Information Center

Anthony, Seth

2014-01-01

Part I: Students' participation in inquiry-based chemistry laboratory curricula, and, in particular, engagement with key thinking processes in conjunction with these experiences, is linked with success at the difficult task of "transfer"--applying their knowledge in new contexts to solve unfamiliar types of problems. We investigate…

The analysis method of the DRAM cell pattern hotspot

NASA Astrophysics Data System (ADS)

Lee, Kyusun; Lee, Kweonjae; Chang, Jinman; Kim, Taeheon; Han, Daehan; Hong, Aeran; Kim, Yonghyeon; Kang, Jinyoung; Choi, Bumjin; Lee, Joosung; Lee, Jooyoung; Hong, Hyeongsun; Lee, Kyupil; Jin, Gyoyoung

2015-03-01

It is increasingly difficult to determine degree of completion of the patterning and the distribution at the DRAM Cell Patterns. When we research DRAM Device Cell Pattern, there are three big problems currently, it is as follows. First, due to etch loading, it is difficult to predict the potential defect. Second, due to under layer topology, it is impossible to demonstrate the influence of the hotspot. Finally, it is extremely difficult to predict final ACI pattern by the photo simulation, because current patterning process is double patterning technology which means photo pattern is completely different from final etch pattern. Therefore, if the hotspot occurs in wafer, it is very difficult to find it. CD-SEM is the most common pattern measurement tool in semiconductor fabrication site. CD-SEM is used to accurately measure small region of wafer pattern primarily. Therefore, there is no possibility of finding places where unpredictable defect occurs. Even though, "Current Defect detector" can measure a wide area, every chip has same pattern issue, the detector cannot detect critical hotspots. Because defect detecting algorithm of bright field machine is based on image processing, if same problems occur on compared and comparing chip, the machine cannot identify it. Moreover this instrument is not distinguished the difference of distribution about 1nm~3nm. So, "Defect detector" is difficult to handle the data for potential weak point far lower than target CD. In order to solve those problems, another method is needed. In this paper, we introduce the analysis method of the DRAM Cell Pattern Hotspot.

Frnakenstein: multiple target inverse RNA folding.

PubMed

Lyngsø, Rune B; Anderson, James W J; Sizikova, Elena; Badugu, Amarendra; Hyland, Tomas; Hein, Jotun

2012-10-09

RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein.

Frnakenstein: multiple target inverse RNA folding

PubMed Central

2012-01-01

Background RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard. Results In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets. Conclusions Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein. PMID:23043260

Easy way to determine quantitative spatial resolution distribution for a general inverse problem

NASA Astrophysics Data System (ADS)

An, M.; Feng, M.

2013-12-01

The spatial resolution computation of a solution was nontrivial and more difficult than solving an inverse problem. Most geophysical studies, except for tomographic studies, almost uniformly neglect the calculation of a practical spatial resolution. In seismic tomography studies, a qualitative resolution length can be indicatively given via visual inspection of the restoration of a synthetic structure (e.g., checkerboard tests). An effective strategy for obtaining quantitative resolution length is to calculate Backus-Gilbert resolution kernels (also referred to as a resolution matrix) by matrix operation. However, not all resolution matrices can provide resolution length information, and the computation of resolution matrix is often a difficult problem for very large inverse problems. A new class of resolution matrices, called the statistical resolution matrices (An, 2012, GJI), can be directly determined via a simple one-parameter nonlinear inversion performed based on limited pairs of random synthetic models and their inverse solutions. The total procedure were restricted to forward/inversion processes used in the real inverse problem and were independent of the degree of inverse skill used in the solution inversion. Spatial resolution lengths can be directly given during the inversion. Tests on 1D/2D/3D model inversion demonstrated that this simple method can be at least valid for a general linear inverse problem.

Composite solvers for linear saddle point problems arising from the incompressible Stokes equations with highly heterogeneous viscosity structure

NASA Astrophysics Data System (ADS)

Sanan, P.; Schnepp, S. M.; May, D.; Schenk, O.

2014-12-01

Geophysical applications require efficient forward models for non-linear Stokes flow on high resolution spatio-temporal domains. The bottleneck in applying the forward model is solving the linearized, discretized Stokes problem which takes the form of a large, indefinite (saddle point) linear system. Due to the heterogeniety of the effective viscosity in the elliptic operator, devising effective preconditioners for saddle point problems has proven challenging and highly problem-dependent. Nevertheless, at least three approaches show promise for preconditioning these difficult systems in an algorithmically scalable way using multigrid and/or domain decomposition techniques. The first is to work with a hierarchy of coarser or smaller saddle point problems. The second is to use the Schur complement method to decouple and sequentially solve for the pressure and velocity. The third is to use the Schur decomposition to devise preconditioners for the full operator. These involve sub-solves resembling inexact versions of the sequential solve. The choice of approach and sub-methods depends crucially on the motivating physics, the discretization, and available computational resources. Here we examine the performance trade-offs for preconditioning strategies applied to idealized models of mantle convection and lithospheric dynamics, characterized by large viscosity gradients. Due to the arbitrary topological structure of the viscosity field in geodynamical simulations, we utilize low order, inf-sup stable mixed finite element spatial discretizations which are suitable when sharp viscosity variations occur in element interiors. Particular attention is paid to possibilities within the decoupled and approximate Schur complement factorization-based monolithic approaches to leverage recently-developed flexible, communication-avoiding, and communication-hiding Krylov subspace methods in combination with `heavy' smoothers, which require solutions of large per-node sub-problems, well-suited to solution on hybrid computational clusters. To manage the combinatorial explosion of solver options (which include hybridizations of all the approaches mentioned above), we leverage the modularity of the PETSc library.

Fast optimization of binary clusters using a novel dynamic lattice searching method.

PubMed

Wu, Xia; Cheng, Wen

2014-09-28

Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd)79 clusters with DFT-fit parameters of Gupta potential.

Task-driven dictionary learning.

PubMed

Mairal, Julien; Bach, Francis; Ponce, Jean

2012-04-01

Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal processing. For signals such as natural images that admit such sparse representations, it is now well established that these models are well suited to restoration tasks. In this context, learning the dictionary amounts to solving a large-scale matrix factorization problem, which can be done efficiently with classical optimization tools. The same approach has also been used for learning features from data for other purposes, e.g., image classification, but tuning the dictionary in a supervised way for these tasks has proven to be more difficult. In this paper, we present a general formulation for supervised dictionary learning adapted to a wide variety of tasks, and present an efficient algorithm for solving the corresponding optimization problem. Experiments on handwritten digit classification, digital art identification, nonlinear inverse image problems, and compressed sensing demonstrate that our approach is effective in large-scale settings, and is well suited to supervised and semi-supervised classification, as well as regression tasks for data that admit sparse representations.

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data

NASA Astrophysics Data System (ADS)

Feng, Shou; Fu, Ping; Zheng, Wenbin

2018-03-01

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem. When using local approach methods to solve this problem, a preliminary results processing method is usually needed. This paper proposed a novel preliminary results processing method called the nodes interaction method. The nodes interaction method revises the preliminary results and guarantees that the predictions are consistent with the hierarchy constraint. This method exploits the label dependency and considers the hierarchical interaction between nodes when making decisions based on the Bayesian network in its first phase. In the second phase, this method further adjusts the results according to the hierarchy constraint. Implementing the nodes interaction method in the HMC framework also enhances the HMC performance for solving the gene function prediction problem based on the Gene Ontology (GO), the hierarchy of which is a directed acyclic graph that is more difficult to tackle. The experimental results validate the promising performance of the proposed method compared to state-of-the-art methods on eight benchmark yeast data sets annotated by the GO.

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

PubMed Central

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-01

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems. PMID:28079187

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems.

PubMed

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-12

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

NASA Astrophysics Data System (ADS)

Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

2017-01-01

Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

Numerical solution of a conspicuous consumption model with constant control delay☆

PubMed Central

Huschto, Tony; Feichtinger, Gustav; Hartl, Richard F.; Kort, Peter M.; Sager, Sebastian; Seidl, Andrea

2011-01-01

We derive optimal pricing strategies for conspicuous consumption products in periods of recession. To that end, we formulate and investigate a two-stage economic optimal control problem that takes uncertainty of the recession period length and delay effects of the pricing strategy into account. This non-standard optimal control problem is difficult to solve analytically, and solutions depend on the variable model parameters. Therefore, we use a numerical result-driven approach. We propose a structure-exploiting direct method for optimal control to solve this challenging optimization problem. In particular, we discretize the uncertainties in the model formulation by using scenario trees and target the control delays by introduction of slack control functions. Numerical results illustrate the validity of our approach and show the impact of uncertainties and delay effects on optimal economic strategies. During the recession, delayed optimal prices are higher than the non-delayed ones. In the normal economic period, however, this effect is reversed and optimal prices with a delayed impact are smaller compared to the non-delayed case. PMID:22267871

Concussion treatment after combat trauma: development of a telephone based, problem solving intervention for service members.

PubMed

Bell, Kathleen R; Brockway, Jo Ann; Fann, Jesse R; Cole, Wesley R; St De Lore, Jef; Bush, Nigel; Lang, Ariel J; Hart, Tessa; Warren, Michael; Dikmen, Sureyya; Temkin, Nancy; Jain, Sonia; Raman, Rema; Stein, Murray B

2015-01-01

Military service members (SMs) and veterans who sustain mild traumatic brain injuries (mTBI) during combat deployments often have co-morbid conditions but are reluctant to seek out therapy in medical or mental health settings. Efficacious methods of intervention that are patient-centered and adaptable to a mobile and often difficult-to-reach population would be useful in improving quality of life. This article describes a new protocol developed as part of a randomized clinical trial of a telephone-mediated program for SMs with mTBI. The 12-session program combines problem solving training (PST) with embedded modules targeting depression, anxiety, insomnia, and headache. The rationale and development of this behavioral intervention for implementation with persons with multiple co-morbidities is described along with the proposed analysis of results. In particular, we provide details regarding the creation of a treatment that is manualized yet flexible enough to address a wide variety of problems and symptoms within a standard framework. The methods involved in enrolling and retaining an often hard-to-study population are also highlighted. Copyright © 2014 Elsevier Inc. All rights reserved.

Application of Four-Point Newton-EGSOR iteration for the numerical solution of 2D Porous Medium Equations

NASA Astrophysics Data System (ADS)

Chew, J. V. L.; Sulaiman, J.

2017-09-01

Partial differential equations that are used in describing the nonlinear heat and mass transfer phenomena are difficult to be solved. For the case where the exact solution is difficult to be obtained, it is necessary to use a numerical procedure such as the finite difference method to solve a particular partial differential equation. In term of numerical procedure, a particular method can be considered as an efficient method if the method can give an approximate solution within the specified error with the least computational complexity. Throughout this paper, the two-dimensional Porous Medium Equation (2D PME) is discretized by using the implicit finite difference scheme to construct the corresponding approximation equation. Then this approximation equation yields a large-sized and sparse nonlinear system. By using the Newton method to linearize the nonlinear system, this paper deals with the application of the Four-Point Newton-EGSOR (4NEGSOR) iterative method for solving the 2D PMEs. In addition to that, the efficiency of the 4NEGSOR iterative method is studied by solving three examples of the problems. Based on the comparative analysis, the Newton-Gauss-Seidel (NGS) and the Newton-SOR (NSOR) iterative methods are also considered. The numerical findings show that the 4NEGSOR method is superior to the NGS and the NSOR methods in terms of the number of iterations to get the converged solutions, the time of computation and the maximum absolute errors produced by the methods.

Problem types used in math lessons: the relationship between student achievement and teacher preferences

NASA Astrophysics Data System (ADS)

Guven, Bulent; Aydin-Guc, Funda; Medine Ozmen, Zeynep

2016-08-01

The purpose of this study was to determine the relationship between the problems teachers preferred in mathematics lessons and student achievement in different types of problems. In accordance with this purpose, nine mathematics teachers were interviewed, and corresponding problems were prepared and administered to 225 eighth-grade students. The findings indicate that problem types are dependent on teacher preferences. It was found that curriculum-dependent and routine problems were dominant for teacher preferences. Students are more successful at with missing data, problems that are visual and do not require the use of different strategies. They have lower success at long problems, those that contain irrelevant data, problems that require the use of different strategies and difficult problem types. It was found that problem types at which students were successful and which teachers preferred were related. These results relay information about problems used in the learning environment and effect of problem-solving experiences on students' success.

Sequential decision making in computational sustainability via adaptive submodularity

USGS Publications Warehouse

Krause, Andreas; Golovin, Daniel; Converse, Sarah J.

2015-01-01

Many problems in computational sustainability require making a sequence of decisions in complex, uncertain environments. Such problems are generally notoriously difficult. In this article, we review the recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems. Problems exhibiting the adaptive submodularity property can be efficiently and provably near-optimally solved using simple myopic policies. We illustrate this concept in several case studies of interest in computational sustainability: First, we demonstrate how it can be used to efficiently plan for resolving uncertainty in adaptive management scenarios. Secondly, we show how it applies to dynamic conservation planning for protecting endangered species, a case study carried out in collaboration with the US Geological Survey and the US Fish and Wildlife Service.

Location-allocation models and new solution methodologies in telecommunication networks

NASA Astrophysics Data System (ADS)

Dinu, S.; Ciucur, V.

2016-08-01

When designing a telecommunications network topology, three types of interdependent decisions are combined: location, allocation and routing, which are expressed by the following design considerations: how many interconnection devices - consolidation points/concentrators should be used and where should they be located; how to allocate terminal nodes to concentrators; how should the voice, video or data traffic be routed and what transmission links (capacitated or not) should be built into the network. Including these three components of the decision into a single model generates a problem whose complexity makes it difficult to solve. A first method to address the overall problem is the sequential one, whereby the first step deals with the location-allocation problem and based on this solution the subsequent sub-problem (routing the network traffic) shall be solved. The issue of location and allocation in a telecommunications network, called "The capacitated concentrator location- allocation - CCLA problem" is based on one of the general location models on a network in which clients/demand nodes are the terminals and facilities are the concentrators. Like in a location model, each client node has a demand traffic, which must be served, and the facilities can serve these demands within their capacity limit. In this study, the CCLA problem is modeled as a single-source capacitated location-allocation model whose optimization objective is to determine the minimum network cost consisting of fixed costs for establishing the locations of concentrators, costs for operating concentrators and costs for allocating terminals to concentrators. The problem is known as a difficult combinatorial optimization problem for which powerful algorithms are required. Our approach proposes a Fuzzy Genetic Algorithm combined with a local search procedure to calculate the optimal values of the location and allocation variables. To confirm the efficiency of the proposed algorithm with respect to the quality of solutions, significant size test problems were considered: up to 100 terminal nodes and 50 concentrators on a 100 × 100 square grid. The performance of this hybrid intelligent algorithm was evaluated by measuring the quality of its solutions with respect to the following statistics: the standard deviation and the ratio of the best solution obtained.

Computational complexity in entanglement transformations

NASA Astrophysics Data System (ADS)

Chitambar, Eric A.

In physics, systems having three parts are typically much more difficult to analyze than those having just two. Even in classical mechanics, predicting the motion of three interacting celestial bodies remains an insurmountable challenge while the analogous two-body problem has an elementary solution. It is as if just by adding a third party, a fundamental change occurs in the structure of the problem that renders it unsolvable. In this thesis, we demonstrate how such an effect is likewise present in the theory of quantum entanglement. In fact, the complexity differences between two-party and three-party entanglement become quite conspicuous when comparing the difficulty in deciding what state changes are possible for these systems when no additional entanglement is consumed in the transformation process. We examine this entanglement transformation question and its variants in the language of computational complexity theory, a powerful subject that formalizes the concept of problem difficulty. Since deciding feasibility of a specified bipartite transformation is relatively easy, this task belongs to the complexity class P. On the other hand, for tripartite systems, we find the problem to be NP-Hard, meaning that its solution is at least as hard as the solution to some of the most difficult problems humans have encountered. One can then rigorously defend the assertion that a fundamental complexity difference exists between bipartite and tripartite entanglement since unlike the former, the full range of forms realizable by the latter is incalculable (assuming P≠NP). However, similar to the three-body celestial problem, when one examines a special subclass of the problem---invertible transformations on systems having at least one qubit subsystem---we prove that the problem can be solved efficiently. As a hybrid of the two questions, we find that the question of tripartite to bipartite transformations can be solved by an efficient randomized algorithm. Our results are obtained by encoding well-studied computational problems such as polynomial identity testing and tensor rank into questions of entanglement transformation. In this way, entanglement theory provides a physical manifestation of some of the most puzzling and abstract classical computation questions.

Unsolved problems in biology--The state of current thinking.

PubMed

Dev, Sukhendu B

2015-03-01

Many outstanding problems have been solved in biology and medicine for which scientists have been awarded prestigious prizes including the Nobel Prize, Lasker Award and Breakthrough Prizes in life sciences. These have been the fruits of years of basic research. From time to time, publications have appeared listing "unsolved" problems in biology. In this article, I ask the question whether it is possible to have such a list, if not a unique one, at least one that is analogous to the Millennium Prize in mathematics. My approach to finding an answer to this question was to gather views of leading biologists. I have also included my own views. Analysis of all the responses received over several years has convinced me that it is difficult, but not impossible, to have such a prize. Biology is complex and very interdisciplinary these days at times involving large numbers of teams, unlike mathematics, where Andrew Wiles spent seven years in complete isolation and secrecy solving Fermat's last theorem. Such an approach is simply not possible in biology. Still I would like to suggest that a similar prize can be established by a panel of distinguished scientists. It would be awarded to those who solved one of the listed problems in biology that warrant a verifiable solution. Despite many different opinions, I found that there is some commonality in the responses I received - I go on to discuss what these are and how they may impact future thinking. Copyright © 2015 Elsevier Ltd. All rights reserved.

Soviet Style in War. Revised Edition

DTIC Science & Technology

1992-01-01

Again, there may be "illusions that it is impossible to solve a certain problem... ," where in reality it is merely "difficult to resolve." 9 But...remarks of his superiors. However, in reality this is not the case. From higher levels orders come down, plans for measures to eliminate defects are...1943 ... there were virtually no powerful spearheads to deliver the main thrust." 354 The fall of 1943 in the Caucasus: "Combat actions during the

Zinc Bromide Flow Battery Installation for Islanding and Backup Power

DTIC Science & Technology

2017-08-09

predictably is in place. The ability to control generation has become more difficult with the increase of RE systems such as solar PV and wind turbines ...Both PV and wind systems generate power based on unpredictable cycles of nature. At very low levels of RE penetration the grid can be balanced by...Page Intentionally Left Blank 15 5.0 TEST DESIGN This goal of this demonstration was to solve two main problems . The first

Expert systems applied to spacecraft fire safety

NASA Technical Reports Server (NTRS)

Smith, Richard L.; Kashiwagi, Takashi

1989-01-01

Expert systems are problem-solving programs that combine a knowledge base and a reasoning mechanism to simulate a human expert. The development of an expert system to manage fire safety in spacecraft, in particular the NASA Space Station Freedom, is difficult but clearly advantageous in the long-term. Some needs in low-gravity flammability characteristics, ventilating-flow effects, fire detection, fire extinguishment, and decision models, all necessary to establish the knowledge base for an expert system, are discussed.

Multi exposure image fusion algorithm based on YCbCr space

NASA Astrophysics Data System (ADS)

Yang, T. T.; Fang, P. Y.

2018-05-01

To solve the problem that scene details and visual effects are difficult to be optimized in high dynamic image synthesis, we proposes a multi exposure image fusion algorithm for processing low dynamic range images in YCbCr space, and weighted blending of luminance and chromatic aberration components respectively. The experimental results show that the method can retain color effect of the fused image while balancing details of the bright and dark regions of the high dynamic image.

Quantum computing and probability.

PubMed

Ferry, David K

2009-11-25

Over the past two decades, quantum computing has become a popular and promising approach to trying to solve computationally difficult problems. Missing in many descriptions of quantum computing is just how probability enters into the process. Here, we discuss some simple examples of how uncertainty and probability enter, and how this and the ideas of quantum computing challenge our interpretations of quantum mechanics. It is found that this uncertainty can lead to intrinsic decoherence, and this raises challenges for error correction.

Dark Matter and the Galactic Center

NASA Astrophysics Data System (ADS)

Bergstrom, Lars

2017-01-01

The question of the identity of dark matter is one of the most outstanding enigmas of contemporary cosmology and particle astrophysics. An overview is given of the subject, a brief history, some proposed particle candidates, and the several methods now available for finally solving this difficult problem. The galactic center is one of the most interesting places for the dark matter search using γ-rays, but also one that has challenging, maybe confusing, other sources of GeV-scale radiation.

An efficient annealing in Boltzmann machine in Hopfield neural network

NASA Astrophysics Data System (ADS)

Kin, Teoh Yeong; Hasan, Suzanawati Abu; Bulot, Norhisam; Ismail, Mohammad Hafiz

2012-09-01

This paper proposes and implements Boltzmann machine in Hopfield neural network doing logic programming based on the energy minimization system. The temperature scheduling in Boltzmann machine enhancing the performance of doing logic programming in Hopfield neural network. The finest temperature is determined by observing the ratio of global solution and final hamming distance using computer simulations. The study shows that Boltzmann Machine model is more stable and competent in term of representing and solving difficult combinatory problems.

High Performance Parallel Analysis of Coupled Problems for Aircraft Propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Lanteri, S.; Maman, N.; Piperno, S.; Gumaste, U.

1994-01-01

In order to predict the dynamic response of a flexible structure in a fluid flow, the equations of motion of the structure and the fluid must be solved simultaneously. In this paper, we present several partitioned procedures for time-integrating this focus coupled problem and discuss their merits in terms of accuracy, stability, heterogeneous computing, I/O transfers, subcycling, and parallel processing. All theoretical results are derived for a one-dimensional piston model problem with a compressible flow, because the complete three-dimensional aeroelastic problem is difficult to analyze mathematically. However, the insight gained from the analysis of the coupled piston problem and the conclusions drawn from its numerical investigation are confirmed with the numerical simulation of the two-dimensional transient aeroelastic response of a flexible panel in a transonic nonlinear Euler flow regime.

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

NASA Astrophysics Data System (ADS)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

Vision-based stabilization of nonholonomic mobile robots by integrating sliding-mode control and adaptive approach

NASA Astrophysics Data System (ADS)

Cao, Zhengcai; Yin, Longjie; Fu, Yili

2013-01-01

Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so that these controllers are difficult to realize satisfactory control in practical application. Besides, many of the approaches suffer from the initial speed and torque jump which are not practical in the real world. Considering the kinematics and dynamics, a two-stage visual controller for solving the stabilization problem of a mobile robot is presented, applying the integration of adaptive control, sliding-mode control, and neural dynamics. In the first stage, an adaptive kinematic stabilization controller utilized to generate the command of velocity is developed based on Lyapunov theory. In the second stage, adopting the sliding-mode control approach, a dynamic controller with a variable speed function used to reduce the chattering is designed, which is utilized to generate the command of torque to make the actual velocity of the mobile robot asymptotically reach the desired velocity. Furthermore, to handle the speed and torque jump problems, the neural dynamics model is integrated into the above mentioned controllers. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, the simulation of the control law is implemented in perturbed case, and the results show that the control scheme can solve the stabilization problem effectively. The proposed control law can solve the speed and torque jump problems, overcome external disturbances, and provide a new solution for the vision-based stabilization of the mobile robot.

Major Thought Restructuring: The Roles of Different Prefrontal Cortical Regions.

PubMed

Seyed-Allaei, Shima; Avanaki, Zahra Nasiri; Bahrami, Bahador; Shallice, Tim

2017-07-01

An important question for understanding the neural basis of problem solving is whether the regions of human prefrontal cortices play qualitatively different roles in the major cognitive restructuring required to solve difficult problems. However, investigating this question using neuroimaging faces a major dilemma: either the problems do not require major cognitive restructuring, or if they do, the restructuring typically happens once, rendering repeated measurements of the critical mental process impossible. To circumvent these problems, young adult participants were challenged with a one-dimensional Subtraction (or Nim) problem [Bouton, C. L. Nim, a game with a complete mathematical theory. The Annals of Mathematics, 3, 35-39, 1901] that can be tackled using two possible strategies. One, often used initially, is effortful, slow, and error-prone, whereas the abstract solution, once achieved, is easier, quicker, and more accurate. Behaviorally, success was strongly correlated with sex. Using voxel-based morphometry analysis controlling for sex, we found that participants who found the more abstract strategy (i.e., Solvers) had more gray matter volume in the anterior medial, ventrolateral prefrontal, and parietal cortices compared with those who never switched from the initial effortful strategy (i.e., Explorers). Removing the sex covariate showed higher gray matter volume in Solvers (vs. Explorers) in the right ventrolateral prefrontal and left parietal cortex.

Multiple and Single Green Area Measurements and Classification Using Phantom Images in Comparison with Derived Experimental Law

NASA Astrophysics Data System (ADS)

Abu-Zaid, N. A. M.

2017-11-01

In many circumstances, it is difficult for humans to reach some areas, due to its topography, personal safety, or security regulations in the country. Governments and persons need to calculate those areas and classify the green parts for reclamation to benefit from it.To solve this problem, this research proposes to use a phantom air plane to capture a digital image for the targeted area, then use a segmentation algorithm to separate the green space and calculate it's area. It was necessary to deal with two problems. The first is the variable elevation at which an image was taken, which leads to a change in the physical area of each pixel. To overcome this problem a fourth degree polynomial was fit to some experimental data. The second problem was the existence of different unconnected pieces of green areas in a single image, but we might be interested only in one of them. To solve this problem, the probability of classifying the targeted area as green was increased, while the probability of other untargeted sections was decreased by the inclusion of parts of it as non-green. A practical law was also devised to measure the target area in the digital image for comparison purposes with practical measurements and the polynomial fit.

The System of Simulation and Multi-objective Optimization for the Roller Kiln

NASA Astrophysics Data System (ADS)

Huang, He; Chen, Xishen; Li, Wugang; Li, Zhuoqiu

It is somewhat a difficult researching problem, to get the building parameters of the ceramic roller kiln simulation model. A system integrated of evolutionary algorithms (PSO, DE and DEPSO) and computational fluid dynamics (CFD), is proposed to solve the problem. And the temperature field uniformity and the environment disruption are studied in this paper. With the help of the efficient parallel calculation, the ceramic roller kiln temperature field uniformity and the NOx emissions field have been researched in the system at the same time. A multi-objective optimization example of the industrial roller kiln proves that the system is of excellent parameter exploration capability.

Some insights on hard quadratic assignment problem instances

NASA Astrophysics Data System (ADS)

Hussin, Mohamed Saifullah

2017-11-01

Since the formal introduction of metaheuristics, a huge number Quadratic Assignment Problem (QAP) instances have been introduced. Those instances however are loosely-structured, and therefore made it difficult to perform any systematic analysis. The QAPLIB for example, is a library that contains a huge number of QAP benchmark instances that consists of instances with different size and structure, but with a very limited availability for every instance type. This prevents researchers from performing organized study on those instances, such as parameter tuning and testing. In this paper, we will discuss several hard instances that have been introduced over the years, and algorithms that have been used for solving them.

Global Optimization of Interplanetary Trajectories in the Presence of Realistic Mission Contraints

NASA Technical Reports Server (NTRS)

Hinckley, David, Jr.; Englander, Jacob; Hitt, Darren

2015-01-01

Interplanetary missions are often subject to difficult constraints, like solar phase angle upon arrival at the destination, velocity at arrival, and altitudes for flybys. Preliminary design of such missions is often conducted by solving the unconstrained problem and then filtering away solutions which do not naturally satisfy the constraints. However this can bias the search into non-advantageous regions of the solution space, so it can be better to conduct preliminary design with the full set of constraints imposed. In this work two stochastic global search methods are developed which are well suited to the constrained global interplanetary trajectory optimization problem.

Detection of lack of fusion using opaque additives

NASA Technical Reports Server (NTRS)

Cook, J. L.

1973-01-01

Reliable nondestructive inspection for incomplete weldment penetration and rapid oxidation of aluminum surfaces when exposed to the atmosphere are currently two major problems in welded aluminum spacecraft structure. Incomplete-penetration defects are extremely difficult to detect and can lead to catastrophic failure of the structure. The moisture absorbed by aluminum oxide on the surface can cause weldment porosity if the surface is not cleaned before welding. The approach employed in this program to solve both problems was to employ copper as a coating to prevent oxidation of the aluminum. Also, copper was used as an opaque additive in the weldment to enhance X-ray detection in the event of incomplete penetration.

Orthopaedic jack for scoliosis surgery purposes: Concept and design

NASA Astrophysics Data System (ADS)

Supriadi, Sugeng; Radhana, Rakha M.; Hidayanto, Taufik Eko; Whulanza, Yudan; Ali, Notario, Nanda; Rahyussalim

2017-02-01

Scoliosis surgery is one of the most difficult orthopedic surgery that have been committed today as the failure rate of orthopedic surgery for adult patients is 15%. Aside from the long duration of surgery, this surgical failure is caused by failure in biomedical instrumentation. Furthermore, this kind of failure is causing inefficiency of the surgery. With current known orthopedic surgery method, three surgeons are needed in a single orthopedic surgery. In fact, a single surgery can take up to 8 hours to be done, which increases the risk of surgical failure. Based on this problem, authors hope that our orthopedic jacks could solve the problem.

A Fixed-point Scheme for the Numerical Construction of Magnetohydrostatic Atmospheres in Three Dimensions

NASA Astrophysics Data System (ADS)

Gilchrist, S. A.; Braun, D. C.; Barnes, G.

2016-12-01

Magnetohydrostatic models of the solar atmosphere are often based on idealized analytic solutions because the underlying equations are too difficult to solve in full generality. Numerical approaches, too, are often limited in scope and have tended to focus on the two-dimensional problem. In this article we develop a numerical method for solving the nonlinear magnetohydrostatic equations in three dimensions. Our method is a fixed-point iteration scheme that extends the method of Grad and Rubin ( Proc. 2nd Int. Conf. on Peaceful Uses of Atomic Energy 31, 190, 1958) to include a finite gravity force. We apply the method to a test case to demonstrate the method in general and our implementation in code in particular.

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.

1998-01-01

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.

MapReduce in the Cloud: A Use Case Study for Efficient Co-Occurrence Processing of MEDLINE Annotations with MeSH.

PubMed

Kreuzthaler, Markus; Miñarro-Giménez, Jose Antonio; Schulz, Stefan

2016-01-01

Big data resources are difficult to process without a scaled hardware environment that is specifically adapted to the problem. The emergence of flexible cloud-based virtualization techniques promises solutions to this problem. This paper demonstrates how a billion of lines can be processed in a reasonable amount of time in a cloud-based environment. Our use case addresses the accumulation of concept co-occurrence data in MEDLINE annotation as a series of MapReduce jobs, which can be scaled and executed in the cloud. Besides showing an efficient way solving this problem, we generated an additional resource for the scientific community to be used for advanced text mining approaches.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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

1982-06-01

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

Large-scale brain network associated with creative insight: combined voxel-based morphometry and resting-state functional connectivity analyses.

PubMed

Ogawa, Takeshi; Aihara, Takatsugu; Shimokawa, Takeaki; Yamashita, Okito

2018-04-24

Creative insight occurs with an "Aha!" experience when solving a difficult problem. Here, we investigated large-scale networks associated with insight problem solving. We recruited 232 healthy participants aged 21-69 years old. Participants completed a magnetic resonance imaging study (MRI; structural imaging and a 10 min resting-state functional MRI) and an insight test battery (ITB) consisting of written questionnaires (matchstick arithmetic task, remote associates test, and insight problem solving task). To identify the resting-state functional connectivity (RSFC) associated with individual creative insight, we conducted an exploratory voxel-based morphometry (VBM)-constrained RSFC analysis. We identified positive correlations between ITB score and grey matter volume (GMV) in the right insula and middle cingulate cortex/precuneus, and a negative correlation between ITB score and GMV in the left cerebellum crus 1 and right supplementary motor area. We applied seed-based RSFC analysis to whole brain voxels using the seeds obtained from the VBM and identified insight-positive/negative connections, i.e. a positive/negative correlation between the ITB score and individual RSFCs between two brain regions. Insight-specific connections included motor-related regions whereas creative-common connections included a default mode network. Our results indicate that creative insight requires a coupling of multiple networks, such as the default mode, semantic and cerebral-cerebellum networks.

I thought we were good: social cognition, figurative language, and adolescent psychopathology.

PubMed

Im-Bolter, Nancie; Cohen, Nancy J; Farnia, Fataneh

2013-07-01

Language has been shown to play a critical role in social cognitive reasoning in preschool and school-aged children, but little research has been conducted with adolescents. During adolescence, the ability to understand figurative language becomes increasingly important for social relationships and may affect social adjustment. This study investigated the contribution of structural and figurative language to social cognitive skills in adolescents who present for mental health services and those who do not. One hundred and thirty-eight adolescents referred to mental health centers (clinic group) and 186 nonreferred adolescents (nonclinic group) aged 12-17 were administered measures of structural and figurative language, working memory, and social cognitive problem solving. We found that adolescents in the clinic group demonstrated less mature social problem solving overall, but particularly with respect to anticipating and overcoming potential obstacles and conflict resolution compared with the nonclinic group. In addition, results demonstrated that age, working memory, and structural and figurative language predicted social cognitive maturity in the clinic group, but only structural language was a predictor in the nonclinic group. Social problem solving may be particularly difficult for adolescents referred for mental health services and places higher demands on their cognitive and language skills compared with adolescents who have never been referred for mental health services. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

AI techniques for a space application scheduling problem

NASA Technical Reports Server (NTRS)

Thalman, N.; Sparn, T.; Jaffres, L.; Gablehouse, D.; Judd, D.; Russell, C.

1991-01-01

Scheduling is a very complex optimization problem which can be categorized as an NP-complete problem. NP-complete problems are quite diverse, as are the algorithms used in searching for an optimal solution. In most cases, the best solutions that can be derived for these combinatorial explosive problems are near-optimal solutions. Due to the complexity of the scheduling problem, artificial intelligence (AI) can aid in solving these types of problems. Some of the factors are examined which make space application scheduling problems difficult and presents a fairly new AI-based technique called tabu search as applied to a real scheduling application. the specific problem is concerned with scheduling application. The specific problem is concerned with scheduling solar and stellar observations for the SOLar-STellar Irradiance Comparison Experiment (SOLSTICE) instrument in a constrained environment which produces minimum impact on the other instruments and maximizes target observation times. The SOLSTICE instrument will gly on-board the Upper Atmosphere Research Satellite (UARS) in 1991, and a similar instrument will fly on the earth observing system (Eos).

Parenting and Independent Problem-Solving in Preschool Children With Food Allergy

PubMed Central

Power, Thomas G.; Hahn, Amy L.; Hoehn, Jessica L.; Thompson, Caitlin C.; Herbert, Linda J.; Law, Emily F.; Bollinger, Mary Elizabeth

2015-01-01

Objective To examine autonomy-promoting parenting and independent problem-solving in children with food allergy. Methods 66 children with food allergy, aged 3–6 years, and 67 age-matched healthy peers and their mothers were videotaped while completing easy and difficult puzzles. Coders recorded time to puzzle completion, children’s direct and indirect requests for help, and maternal help-giving behaviors. Results Compared with healthy peers, younger (3- to 4-year-old) children with food allergy made more indirect requests for help during the easy puzzle, and their mothers were more likely to provide unnecessary help (i.e., explain where to place a puzzle piece). Differences were not found for older children. Conclusions The results suggest that highly involved parenting practices that are medically necessary to manage food allergy may spill over into settings where high levels of involvement are not needed, and that young children with food allergy may be at increased risk for difficulties in autonomy development. PMID:25326001

Tool use disorders after left brain damage.

PubMed

Baumard, Josselin; Osiurak, François; Lesourd, Mathieu; Le Gall, Didier

2014-01-01

In this paper we review studies that investigated tool use disorders in left-brain damaged (LBD) patients over the last 30 years. Four tasks are classically used in the field of apraxia: Pantomime of tool use, single tool use, real tool use and mechanical problem solving. Our aim was to address two issues, namely, (1) the role of mechanical knowledge in real tool use and (2) the cognitive mechanisms underlying pantomime of tool use, a task widely employed by clinicians and researchers. To do so, we extracted data from 36 papers and computed the difference between healthy subjects and LBD patients. On the whole, pantomime of tool use is the most difficult task and real tool use is the easiest one. Moreover, associations seem to appear between pantomime of tool use, real tool use and mechanical problem solving. These results suggest that the loss of mechanical knowledge is critical in LBD patients, even if all of those tasks (and particularly pantomime of tool use) might put differential demands on semantic memory and working memory.

Tool use disorders after left brain damage

PubMed Central

Baumard, Josselin; Osiurak, François; Lesourd, Mathieu; Le Gall, Didier

2014-01-01

In this paper we review studies that investigated tool use disorders in left-brain damaged (LBD) patients over the last 30 years. Four tasks are classically used in the field of apraxia: Pantomime of tool use, single tool use, real tool use and mechanical problem solving. Our aim was to address two issues, namely, (1) the role of mechanical knowledge in real tool use and (2) the cognitive mechanisms underlying pantomime of tool use, a task widely employed by clinicians and researchers. To do so, we extracted data from 36 papers and computed the difference between healthy subjects and LBD patients. On the whole, pantomime of tool use is the most difficult task and real tool use is the easiest one. Moreover, associations seem to appear between pantomime of tool use, real tool use and mechanical problem solving. These results suggest that the loss of mechanical knowledge is critical in LBD patients, even if all of those tasks (and particularly pantomime of tool use) might put differential demands on semantic memory and working memory. PMID:24904487

Distributed parallel computing in stochastic modeling of groundwater systems.

PubMed

Dong, Yanhui; Li, Guomin; Xu, Haizhen

2013-03-01

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

Using immersive healthcare simulation for physiology education: initial experience in high school, college, and graduate school curricula.

PubMed

Oriol, Nancy E; Hayden, Emily M; Joyal-Mowschenson, Julie; Muret-Wagstaff, Sharon; Faux, Russell; Gordon, James A

2011-09-01

In the natural world, learning emerges from the joy of play, experimentation, and inquiry as part of everyday life. However, this kind of informal learning is often difficult to integrate within structured educational curricula. This report describes an educational program that embeds naturalistic learning into formal high school, college, and graduate school science class work. Our experience is based on work with hundreds of high school, college, and graduate students enrolled in traditional science classes in which mannequin simulators were used to teach physiological principles. Specific case scenarios were integrated into the curriculum as problem-solving exercises chosen to accentuate the basic science objectives of the course. This report also highlights the historic and theoretical basis for the use of mannequin simulators as an important physiology education tool and outlines how the authors' experience in healthcare education has been effectively translated to nonclinical student populations. Particular areas of focus include critical-thinking and problem-solving behaviors and student reflections on the impact of the teaching approach.

Effects of using multi-vide ruler kit in the acquisition of numeracy skills among PROTIM students

NASA Astrophysics Data System (ADS)

Arumugan, Hemalatha A./P.; Obeng, Sharifah Nasriah Wan; Talib, Corrienna Abdul; Bunyamin, Muhammad Abdul Hadi; Ali, Marlina; Ibrahim, Norhasniza; Zawadzki, Rainer

2017-08-01

One effective way to teach arithmetic more interestingly and make it easier to learn is through the use of instructional materials. These can help students master certain mathematical skills, particularly multiplication and division, often considered difficult amongst primary school pupils. Nevertheless, the insufficiency of appropriate instructional materials causes difficulty in understanding how to use the proper technique or apply the concept, especially in multiplication. With this in mind, this study investigated whether the innovative and creative instructional material designed to assist and enhance numeracy skills, namely the Multi-vide Ruler kit, could increase students' ability in solving multiplication and division questions and whether it affected their interest in solving numeracy problems. Participants in this study included ten PROTIM (Program Tiga M [Three M Program] - membaca [reading], menulis [writing] dan mengira [calculate]) students, 9-10 years old, who had difficulties in reading, writing and arithmetic. In order to get appropriate support for qualitative research, a pre and post-test containing ten basic mathematical operations, was implemented together with the Multi-vide Ruler Kit. The findings of the qualitative case study, with the pre and post-tests, showed significant differences in their achievement and interest in two-digit multiplication and division operations. The results suggest that this approach could improve PROTIM student's ability to solve basic mathematical operations. What was most encouraging was the increase in students' interest in solving numeracy problems.

Design of sewage treatment system by applying fuzzy adaptive PID controller

NASA Astrophysics Data System (ADS)

Jin, Liang-Ping; Li, Hong-Chan

2013-03-01

In the sewage treatment system, the dissolved oxygen concentration control, due to its nonlinear, time-varying, large time delay and uncertainty, is difficult to establish the exact mathematical model. While the conventional PID controller only works with good linear not far from its operating point, it is difficult to realize the system control when the operating point far off. In order to solve the above problems, the paper proposed a method which combine fuzzy control with PID methods and designed a fuzzy adaptive PID controller based on S7-300 PLC .It employs fuzzy inference method to achieve the online tuning for PID parameters. The control algorithm by simulation and practical application show that the system has stronger robustness and better adaptability.

Robust parallel iterative solvers for linear and least-squares problems, Final Technical Report

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

Saad, Yousef

2014-01-16

The primary goal of this project is to study and develop robust iterative methods for solving linear systems of equations and least squares systems. The focus of the Minnesota team is on algorithms development, robustness issues, and on tests and validation of the methods on realistic problems. 1. The project begun with an investigation on how to practically update a preconditioner obtained from an ILU-type factorization, when the coefficient matrix changes. 2. We investigated strategies to improve robustness in parallel preconditioners in a specific case of a PDE with discontinuous coefficients. 3. We explored ways to adapt standard preconditioners formore » solving linear systems arising from the Helmholtz equation. These are often difficult linear systems to solve by iterative methods. 4. We have also worked on purely theoretical issues related to the analysis of Krylov subspace methods for linear systems. 5. We developed an effective strategy for performing ILU factorizations for the case when the matrix is highly indefinite. The strategy uses shifting in some optimal way. The method was extended to the solution of Helmholtz equations by using complex shifts, yielding very good results in many cases. 6. We addressed the difficult problem of preconditioning sparse systems of equations on GPUs. 7. A by-product of the above work is a software package consisting of an iterative solver library for GPUs based on CUDA. This was made publicly available. It was the first such library that offers complete iterative solvers for GPUs. 8. We considered another form of ILU which blends coarsening techniques from Multigrid with algebraic multilevel methods. 9. We have released a new version on our parallel solver - called pARMS [new version is version 3]. As part of this we have tested the code in complex settings - including the solution of Maxwell and Helmholtz equations and for a problem of crystal growth.10. As an application of polynomial preconditioning we considered the problem of evaluating f(A)v which arises in statistical sampling. 11. As an application to the methods we developed, we tackled the problem of computing the diagonal of the inverse of a matrix. This arises in statistical applications as well as in many applications in physics. We explored probing methods as well as domain-decomposition type methods. 12. A collaboration with researchers from Toulouse, France, considered the important problem of computing the Schur complement in a domain-decomposition approach. 13. We explored new ways of preconditioning linear systems, based on low-rank approximations.« less

Toward Solving the Problem of Problem Solving: An Analysis Framework

ERIC Educational Resources Information Center

Roesler, Rebecca A.

2016-01-01

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

Quality data collection and management technology of aerospace complex product assembly process

NASA Astrophysics Data System (ADS)

Weng, Gang; Liu, Jianhua; He, Yongxi; Zhuang, Cunbo

2017-04-01

Aiming at solving problems of difficult management and poor traceability for discrete assembly process quality data, a data collection and management method is proposed which take the assembly process and BOM as the core. Data collection method base on workflow technology, data model base on BOM and quality traceability of assembly process is included in the method. Finally, assembly process quality data management system is developed and effective control and management of quality information for complex product assembly process is realized.

How the Success of the CSS Hunley Inspired the Development of the United States Naval Submarine Force

DTIC Science & Technology

2017-06-09

28. 16 Ibid., 37. 17 Ibid., 136. 12 unsuccessful due to wind and tide issues which enabled two British ships to elude the slow vessel.18...question of air supply was at one time one of the most difficult problems to solve on paper with which early experimenters with submarines had to contend...recently introduced the constant pressure engine. This engine was the basis for the gas turbine , and his design of constant pressure is now referred to

On Learning from Collective Data

DTIC Science & Technology

2013-12-01

Through it, we can inform the astronomers of the latest detection results and they can give us feedbacks on what these results means and how good they...we need p(Gmk|ηks) to be a goodness - of - fit (GoF) measurement. Unfortunately, GoF tests in high-dimensions are notoriously difficult. Here we take a...down-weigh the past, a lot of useful information would be lost, making the already very sparse data set even worse. To solve this problem, we propose

Methods for Multiplex Template Sampling in Digital PCR Assays

PubMed Central

Petriv, Oleh I.; Heyries, Kevin A.; VanInsberghe, Michael; Walker, David; Hansen, Carl L.

2014-01-01

The efficient use of digital PCR (dPCR) for precision copy number analysis requires high concentrations of target molecules that may be difficult or impossible to obtain from clinical samples. To solve this problem we present a strategy, called Multiplex Template Sampling (MTS), that effectively increases template concentrations by detecting multiple regions of fragmented target molecules. Three alternative assay approaches are presented for implementing MTS analysis of chromosome 21, providing a 10-fold concentration enhancement while preserving assay precision. PMID:24854517

Methods for multiplex template sampling in digital PCR assays.

PubMed

Petriv, Oleh I; Heyries, Kevin A; VanInsberghe, Michael; Walker, David; Hansen, Carl L

2014-01-01

The efficient use of digital PCR (dPCR) for precision copy number analysis requires high concentrations of target molecules that may be difficult or impossible to obtain from clinical samples. To solve this problem we present a strategy, called Multiplex Template Sampling (MTS), that effectively increases template concentrations by detecting multiple regions of fragmented target molecules. Three alternative assay approaches are presented for implementing MTS analysis of chromosome 21, providing a 10-fold concentration enhancement while preserving assay precision.

Integration for navigation on the UMASS mobile perception lab

NASA Technical Reports Server (NTRS)

Draper, Bruce; Fennema, Claude; Rochwerger, Benny; Riseman, Edward; Hanson, Allen

1994-01-01

Integration of real-time visual procedures for use on the Mobile Perception Lab (MPL) was presented. The MPL is an autonomous vehicle designed for testing visually guided behavior. Two critical areas of focus in the system design were data storage/exchange and process control. The Intermediate Symbolic Representation (ISR3) supported data storage and exchange, and the MPL script monitor provided process control. Resource allocation, inter-process communication, and real-time control are difficult problems which must be solved in order to construct strong autonomous systems.

East Lancashire Hospital Trust creates an open culture paving the way for service improvement 'Below ten thousand'.

PubMed

Tomlinson, Robert

2018-05-01

Reacting to a never event is difficult and often embarrassing for staff involved. East Lancashire Hospitals NHS Trust has demonstrated that treating staff with respect after a never event, creates an open culture that encourages problem solving and service improvement. The approach has allowed learning to be shared and paved the way for the trust to be the first in the UK to launch the patient centric behavioural noise reduction strategy 'Below ten thousand'.

Radar Control Optimal Resource Allocation

DTIC Science & Technology

2015-07-13

other tunable parameters of radars [17, 18]. Such radar resource scheduling usually demands massive computation. Even myopic 14 Distribution A: Approved...reduced validity of the optimal choice of radar resource. In the non- myopic context, the computational problem becomes exponentially more difficult...computed as t? = ασ2 q + σ r √ α q (σ + r + α q) α q2 r − 1ασ q2 + q r2 . (19) We are only interested in t? > 1 and solving the inequality we obtain the

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

PubMed

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

2008-07-01

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

Resources in Technology: Problem-Solving.

ERIC Educational Resources Information Center

Technology Teacher, 1986

1986-01-01

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

A cross-disciplinary introduction to quantum annealing-based algorithms

NASA Astrophysics Data System (ADS)

Venegas-Andraca, Salvador E.; Cruz-Santos, William; McGeoch, Catherine; Lanzagorta, Marco

2018-04-01

A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in quantum computation involves contributions from both physics and computer science; hence this article presents a concise introduction to basic concepts from both fields that are used in annealing-based quantum computation, an alternative to the more familiar quantum gate model. We introduce some concepts from computer science required to define difficult computational problems and to realise the potential relevance of quantum algorithms to find novel solutions to those problems. We introduce the structure of quantum annealing-based algorithms as well as two examples of this kind of algorithms for solving instances of the max-SAT and Minimum Multicut problems. An overview of the quantum annealing systems manufactured by D-Wave Systems is also presented.

Solving and Learning Soft Temporal Constraints: Experimental Setting and Results

NASA Technical Reports Server (NTRS)

Rossi, F.; Sperduti, A.; Venable, K. B.; Khatib, L.; Morris, P.; Morris, R.; Clancy, Daniel (Technical Monitor)

2002-01-01

Soft temporal constraints problems allow to describe in a natural way scenarios where events happen over time and preferences are associated to event distances and durations. However, sometimes such local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. Machine learning techniques can be useful in this respect. In this paper we describe two solvers (one more general and the other one more efficient) for tractable subclasses of soft temporal problems, and we show some experimental results. The random generator used to build the problems on which tests are performed is also described. We also compare the two solvers highlighting the tradeoff between performance and representational power. Finally, we present a learning module and we show its behavior on randomly-generated examples.

Cultural-based particle swarm for dynamic optimisation problems

NASA Astrophysics Data System (ADS)

Daneshyari, Moayed; Yen, Gary G.

2012-07-01

Many practical optimisation problems are with the existence of uncertainties, among which a significant number belong to the dynamic optimisation problem (DOP) category in which the fitness function changes through time. In this study, we propose the cultural-based particle swarm optimisation (PSO) to solve DOP problems. A cultural framework is adopted incorporating the required information from the PSO into five sections of the belief space, namely situational, temporal, domain, normative and spatial knowledge. The stored information will be adopted to detect the changes in the environment and assists response to the change through a diversity-based repulsion among particles and migration among swarms in the population space, and also helps in selecting the leading particles in three different levels, personal, swarm and global levels. Comparison of the proposed heuristics over several difficult dynamic benchmark problems demonstrates the better or equal performance with respect to most of other selected state-of-the-art dynamic PSO heuristics.

Maximum Range of a Projectile Thrown from Constant-Speed Circular Motion

NASA Astrophysics Data System (ADS)

Poljak, Nikola

2016-11-01

The problem of determining the angle θ at which a point mass launched from ground level with a given speed v0 will reach a maximum distance is a standard exercise in mechanics. There are many possible ways of solving this problem, leading to the well-known answer of θ = π/4, producing a maximum range of D max = v0 2 / g , with g being the free-fall acceleration. Conceptually and calculationally more difficult problems have been suggested to improve student proficiency in projectile motion, with the most famous example being the Tarzan swing problem. The problem of determining the maximum distance of a point mass thrown from constant-speed circular motion is presented and analyzed in detail in this text. The calculational results confirm several conceptually derived conclusions regarding the initial throw position and provide some details on the angles and the way of throwing (underhand or overhand) that produce the maximum throw distance.

A treatment goal checklist for people with personality disorder.

PubMed

Wood, Katherine; McMurran, Mary

2013-11-01

Agreement between client and therapist on treatment goals has been consistently linked with improved treatment outcomes. Having clear and collaborative goals may be particularly important when working with clients diagnosed with personality disorders who are often difficult to engage and test the boundaries of therapy. This paper outlines the development of a personality disorder treatment goal checklist aimed at helping clients and therapists to identify and prioritize their goals for therapy. The checklist was developed using self-reported problems of the first 90 participants randomized into the psychoeducation and problem solving (PEPS) trial. Problems were coded and categorized into problem areas. The checklist was viewed by two service users who gave suggestions for improvements. The final checklist consists of 161 items in 16 problem areas. The checklist may provide a clinically useful tool for working with this client group. Copyright © 2013 John Wiley & Sons, Ltd.

A genetic algorithm for dynamic inbound ordering and outbound dispatching problem with delivery time windows

NASA Astrophysics Data System (ADS)

Kim, Byung Soo; Lee, Woon-Seek; Koh, Shiegheun

2012-07-01

This article considers an inbound ordering and outbound dispatching problem for a single product in a third-party warehouse, where the demands are dynamic over a discrete and finite time horizon, and moreover, each demand has a time window in which it must be satisfied. Replenishing orders are shipped in containers and the freight cost is proportional to the number of containers used. The problem is classified into two cases, i.e. non-split demand case and split demand case, and a mathematical model for each case is presented. An in-depth analysis of the models shows that they are very complicated and difficult to find optimal solutions as the problem size becomes large. Therefore, genetic algorithm (GA) based heuristic approaches are designed to solve the problems in a reasonable time. To validate and evaluate the algorithms, finally, some computational experiments are conducted.

A new principle technic for the transformation from frequency domain to time domain

NASA Astrophysics Data System (ADS)

Gao, Ben-Qing

2017-03-01

A principle technic for the transformation from frequency domain to time domain is presented. Firstly, a special type of frequency domain transcendental equation is obtained for an expected frequency domain parameter which is a rational or irrational fraction expression. Secondly, the inverse Laplace transformation is performed. When the two time-domain factors corresponding to the two frequency domain factors at two sides of frequency domain transcendental equation are known quantities, a time domain transcendental equation is reached. At last, the expected time domain parameter corresponding to the expected frequency domain parameter can be solved by the inverse convolution process. Proceeding from rational or irrational fraction expression, all solving process is provided. In the meantime, the property of time domain sequence is analyzed and the strategy for choosing the parameter values is described. Numerical examples are presented to verify the proposed theory and technic. Except for rational or irrational fraction expressions, examples of complex relative permittivity of water and plasma are used as verification method. The principle method proposed in the paper can easily solve problems which are difficult to be solved by Laplace transformation.

Observed Human Errors in Interpreting 3D visualizations: implications for Teaching Students how to Comprehend Geological Block Diagrams

NASA Astrophysics Data System (ADS)

Bemis, K. G.; Pirl, E.; Chiang, J.; Tremaine, M.

2009-12-01

Block diagrams are commonly used to communicate three dimensional geological structures and other phenomena relevant to geological science (e.g., water bodies in the ocean). However, several recent studies have suggested that these 3D visualizations create difficulties for individuals with low to moderate spatial abilities. We have therefore initiated a series of studies to understand what it is about the 3D structures that make them so difficult for some people and also to determine if we can improve people’s understanding of these structures through web-based training not related to geology or other underlying information. Our first study examined what mistakes subjects made in a set of 3D block diagrams designed to represent progressively more difficult internal structures. Each block was shown bisected by a plane either perpendicular or at an angle to the block sides. Five low to medium spatial subjects were asked to draw the features that would appear on the bisecting plane. They were asked to talk aloud as they solved the problem. Each session was videotaped. Using the time it took subjects to solve the problems, the subject verbalizations of their problem solving and the drawings that were found to be in error, we have been able to find common patterns in the difficulties the subjects had with the diagrams. We have used these patterns to generate a set of strategies the subjects used in solving the problems. From these strategies, we are developing methods of teaching. A problem found in earlier work on geology structures was not observed in our study, that is, one of subjects failing to recognize the 2D representation of the block as 3D and drawing the cross-section as a combined version of the visible faces of the object. We attribute this to our experiment introduction, suggesting that even this simple training needs to be carried out with students encountering 3D block diagrams. Other problems subjects had included difficulties in perceptually recognizing variations in layer thicknesses, difficulties in recognizing an internal structure from the visible cues on the block walls, difficulties in mentally constructing objects and intersections that were not perpendicular, and difficulties in keeping track of the number of folds of a layer, and thus, the number of intersections of the layer with the bisecting plane. All of these problems suggest that web-based games giving mass practice with these variations in block diagram representations are likely to give any person appropriate skills in their interpretation. The time to complete the drawings and the errors in the drawings were also correlated with quantifiable properties of the diagrams, e.g., number of layers, number of folds in the layers, angle of bisection of the plane, etc. These will be used in further research to organize the training from easy to hard problems following what is known already about mass practice and developing abstracted skill sets. The plan is to also make the training adaptive, that is, to provide practice in those areas where an individual user is having the most problems.

Evaluation of Genetic Algorithm Concepts Using Model Problems. Part 2; Multi-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

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.

Design and Analysis Tools for Concurrent Blackboard Systems

NASA Technical Reports Server (NTRS)

McManus, John W.

1991-01-01

A blackboard system consists of a set of knowledge sources, a blackboard data structure, and a control strategy used to activate the knowledge sources. The blackboard model of problem solving is best described by Dr. H. Penny Nii of the Stanford University AI Laboratory: "A Blackboard System can be viewed as a collection of intelligent agents who are gathered around a blackboard, looking at pieces of information written on it, thinking about the current state of the solution, and writing their conclusions on the blackboard as they generate them. " The blackboard is a centralized global data structure, often partitioned in a hierarchical manner, used to represent the problem domain. The blackboard is also used to allow inter-knowledge source communication and acts as a shared memory visible to all of the knowledge sources. A knowledge source is a highly specialized, highly independent process that takes inputs from the blackboard data structure, performs a computation, and places the results of the computation in the blackboard data structure. This design allows for an opportunistic control strategy. The opportunistic problem-solving technique allows a knowledge source to contribute towards the solution of the current problem without knowing which of the other knowledge sources will use the information. The use of opportunistic problem-solving allows the data transfers on the blackboard to determine which processes are active at a given time. Designing and developing blackboard systems is a difficult process. The designer is trying to balance several conflicting goals and achieve a high degree of concurrent knowledge source execution while maintaining both knowledge and semantic consistency on the blackboard. Blackboard systems have not attained their apparent potential because there are no established tools or methods to guide in their construction or analyze their performance.

An endless research for 2016.

PubMed

Grammaticos, Philip C; Antoniou, Dimitrios E

2016-01-01

In a moment of reflection of the past year of 2015, as to what we have achieved in medical research and what we need to do in the future we realize that although we have performed an enormous progress in medical research in the past we still have to do much more. In nuclear medicine there are many problems to solve like, how can we differentiate between infection, inflammation and cancer or between lymphomas and adenocarcinomas. In bone scans we need to differentiate traumatic lesions acute or chronic and lesions from another origin. Dosimetry and radiation burden is another problem. In HJNM we have previously published related papers. Not to mention radiation sickness due to modern atomic or hydrogen bombs. Labeling antibodies and genetic material is another issue. Additionally, in general medical knowledge is still unable to solve many unknown, difficult or tragic problems of our lives, like cancer, some viral infections, research in immunology, collagen diseases, genetics, radiation treatment, psychological disorders, anesthetics, the Hayflick phenomenon, hypertension, asthma, the function of the gastrointestinal tract, infectious diseases, physical exercise, all of which are briefly mentioned. We hope that even under the present financial problems and considering that almost 90% of medical truth is still unknown, our research in 2016 will be very important. In this paper we also discuss means for a more genuine and effective research.

On Faraday's law in the presence of extended conductors

NASA Astrophysics Data System (ADS)

Bilbao, Luis

2018-06-01

The use of Faraday's Law of induction for calculating the induced currents in an extended conducting body is discussed. In a general case with arbitrary geometry, the solution to the problem of a moving metal object in the presence of a magnetic field is difficult and implies solving Maxwell's equations in a time-dependent situation. In many cases, including cases with good conductors (but not superconductors) Ampère's Law can be neglected and a simpler solution based solely in Faraday's law can be obtained. The integral form of Faraday's Law along any loop in the conducting body is equivalent to a Kirkhhoff's voltage law of a circuit. Therefore, a numerical solution can be obtained by solving a linear system of equations corresponding to a discrete number of loops in the body.

A tight upper bound for quadratic knapsack problems in grid-based wind farm layout optimization

NASA Astrophysics Data System (ADS)

Quan, Ning; Kim, Harrison M.

2018-03-01

The 0-1 quadratic knapsack problem (QKP) in wind farm layout optimization models possible turbine locations as nodes, and power loss due to wake effects between pairs of turbines as edges in a complete graph. The goal is to select up to a certain number of turbine locations such that the sum of selected node and edge coefficients is maximized. Finding the optimal solution to the QKP is difficult in general, but it is possible to obtain a tight upper bound on the QKP's optimal value which facilitates the use of heuristics to solve QKPs by giving a good estimate of the optimality gap of any feasible solution. This article applies an upper bound method that is especially well-suited to QKPs in wind farm layout optimization due to certain features of the formulation that reduce the computational complexity of calculating the upper bound. The usefulness of the upper bound was demonstrated by assessing the performance of the greedy algorithm for solving QKPs in wind farm layout optimization. The results show that the greedy algorithm produces good solutions within 4% of the optimal value for small to medium sized problems considered in this article.

Location of acoustic emission sources generated by air flow

PubMed

Kosel; Grabec; Muzic

2000-03-01

The location of continuous acoustic emission sources is a difficult problem of non-destructive testing. This article describes one-dimensional location of continuous acoustic emission sources by using an intelligent locator. The intelligent locator solves a location problem based on learning from examples. To verify whether continuous acoustic emission caused by leakage air flow can be located accurately by the intelligent locator, an experiment on a thin aluminum band was performed. Results show that it is possible to determine an accurate location by using a combination of a cross-correlation function with an appropriate bandpass filter. By using this combination, discrete and continuous acoustic emission sources can be located by using discrete acoustic emission sources for locator learning.

Cycle life machine for AX-5 space suit

NASA Technical Reports Server (NTRS)

Schenberger, Deborah S.

1990-01-01

In order to accurately test the AX-5 space suit, a complex series of motions needed to be performed which provided a unique opportunity for mechanism design. The cycle life machine design showed how 3-D computer images can enhance mechanical design as well as help in visualizing mechanisms before manufacturing them. In the early stages of the design, potential problems in the motion of the joint and in the four bar linkage system were resolved using CAD. Since these problems would have been very difficult and tedious to solve on a drawing board, they would probably not have been addressed prior to fabrication, thus limiting the final design or requiring design modification after fabrication.

The anti-fatigue driving system design based on the eye blink detect

NASA Astrophysics Data System (ADS)

Yang, Shuyu; Song, Xin; Zhang, Li; Yu, Jie

2017-01-01

Traffic accident is one of the severe social problems in the world, but the appraisal and prevention of the fatigue driving is still a difficult problem that can not be solved. This paper is to study the results of fatigue driving and the existing antifatigue driving products, collecting brain wave with the TGAM (ThinkGear AM) Brain Wave Sensor Chip. We analyze the collected waveform based on eye blink detect algorithm to work out current situation of the driver. According to the analysis results, Sound Module and controllable speed car will make a series of feedback. Finally, an effective Anti- Fatigue Driving System is designed based on all above.

Polarimetric SAR image classification based on discriminative dictionary learning model

NASA Astrophysics Data System (ADS)

Sang, Cheng Wei; Sun, Hong

2018-03-01

Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

Sustainer electric propulsion system application for spacecraft attitude control

NASA Astrophysics Data System (ADS)

Obukhov, V. A.; Pokryshkin, A. I.; Popov, G. A.; Yashina, N. V.

2010-07-01

Application of electric propulsion system (EPS) requires spacecraft (SC) equipping with large solar panels (SP) for the power supply to electric propulsions. This makes the problem of EPS-equipped SC control at the insertion stage more difficult to solve than in the case of SC equipped with chemical engines, because in addition to the SC attitude control associated with the mission there appears necessity in keeping SP orientation to Sun that is necessary for generation of electric power sufficient for the operation of service systems, purpose-oriented equipment, and EPS. The theoretical study of the control problem is the most interesting for a non-coplanar transfer from high elliptic orbit (HEO) to geostationary orbit (GSO).

Problem-solving variability in older spouses: how is it linked to problem-, person-, and couple-characteristics?

PubMed

Hoppmann, Christiane A; Blanchard-Fields, Fredda

2011-09-01

Problem-solving does not take place in isolation and often involves social others such as spouses. Using repeated daily life assessments from 98 older spouses (M age = 72 years; M marriage length = 42 years), the present study examined theoretical notions from social-contextual models of coping regarding (a) the origins of problem-solving variability and (b) associations between problem-solving and specific problem-, person-, and couple- characteristics. Multilevel models indicate that the lion's share of variability in everyday problem-solving is located at the level of the problem situation. Importantly, participants reported more proactive emotion regulation and collaborative problem-solving for social than nonsocial problems. We also found person-specific consistencies in problem-solving. That is, older spouses high in Neuroticism reported more problems across the study period as well as less instrumental problem-solving and more passive emotion regulation than older spouses low in Neuroticism. Contrary to expectations, relationship satisfaction was unrelated to problem-solving in the present sample. Results are in line with the stress and coping literature in demonstrating that everyday problem-solving is a dynamic process that has to be viewed in the broader context in which it occurs. Our findings also complement previous laboratory-based work on everyday problem-solving by underscoring the benefits of examining everyday problem-solving as it unfolds in spouses' own environment.

Resource Letter RPS-1: Research in problem solving

NASA Astrophysics Data System (ADS)

Hsu, Leonardo; Brewe, Eric; Foster, Thomas M.; Harper, Kathleen A.

2004-09-01

This Resource Letter provides a guide to the literature on research in problem solving, especially in physics. The references were compiled with two audiences in mind: physicists who are (or might become) engaged in research on problem solving, and physics instructors who are interested in using research results to improve their students' learning of problem solving. In addition to general references, journal articles and books are cited for the following topics: cognitive aspects of problem solving, expert-novice problem-solver characteristics, problem solving in mathematics, alternative problem types, curricular interventions, and the use of computers in problem solving.

Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System.

PubMed

Chinnadurai, Sunil; Selvaprabhu, Poongundran; Jeong, Yongchae; Jiang, Xueqin; Lee, Moon Ho

2017-09-18

In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE) maximization problem in a 5G massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) downlink system with imperfect channel state information (CSI) at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA) algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM). A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP) that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach's algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.

Worst-Case Energy Efficiency Maximization in a 5G Massive MIMO-NOMA System

PubMed Central

Jeong, Yongchae; Jiang, Xueqin; Lee, Moon Ho

2017-01-01

In this paper, we examine the robust beamforming design to tackle the energy efficiency (EE) maximization problem in a 5G massive multiple-input multiple-output (MIMO)-non-orthogonal multiple access (NOMA) downlink system with imperfect channel state information (CSI) at the base station. A novel joint user pairing and dynamic power allocation (JUPDPA) algorithm is proposed to minimize the inter user interference and also to enhance the fairness between the users. This work assumes imperfect CSI by adding uncertainties to channel matrices with worst-case model, i.e., ellipsoidal uncertainty model (EUM). A fractional non-convex optimization problem is formulated to maximize the EE subject to the transmit power constraints and the minimum rate requirement for the cell edge user. The designed problem is difficult to solve due to its nonlinear fractional objective function. We firstly employ the properties of fractional programming to transform the non-convex problem into its equivalent parametric form. Then, an efficient iterative algorithm is proposed established on the constrained concave-convex procedure (CCCP) that solves and achieves convergence to a stationary point of the above problem. Finally, Dinkelbach’s algorithm is employed to determine the maximum energy efficiency. Comprehensive numerical results illustrate that the proposed scheme attains higher worst-case energy efficiency as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme. PMID:28927019

Quantum algorithm for energy matching in hard optimization problems

NASA Astrophysics Data System (ADS)

Baldwin, C. L.; Laumann, C. R.

2018-06-01

We consider the ability of local quantum dynamics to solve the "energy-matching" problem: given an instance of a classical optimization problem and a low-energy state, find another macroscopically distinct low-energy state. Energy matching is difficult in rugged optimization landscapes, as the given state provides little information about the distant topography. Here, we show that the introduction of quantum dynamics can provide a speedup over classical algorithms in a large class of hard optimization problems. Tunneling allows the system to explore the optimization landscape while approximately conserving the classical energy, even in the presence of large barriers. Specifically, we study energy matching in the random p -spin model of spin-glass theory. Using perturbation theory and exact diagonalization, we show that introducing a transverse field leads to three sharp dynamical phases, only one of which solves the matching problem: (1) a small-field "trapped" phase, in which tunneling is too weak for the system to escape the vicinity of the initial state; (2) a large-field "excited" phase, in which the field excites the system into high-energy states, effectively forgetting the initial energy; and (3) the intermediate "tunneling" phase, in which the system succeeds at energy matching. The rate at which distant states are found in the tunneling phase, although exponentially slow in system size, is exponentially faster than classical search algorithms.

Mathematical Approach to Identification of Load Structure at the Nodes of the Distribution Grids 6-10 kV and 0.4 kV

NASA Astrophysics Data System (ADS)

Nizamutdinova, T.; Mukhlynin, N.

2017-06-01

A significant increasing energy efficiency of the full cycle of production, transmission and distribution of electricity in grids should be based on the management of separate consumers of electricity. The existing energy supply systems based on the concept of «smart things» do not allow to identify the technical structure of the electricity consumption in the load nodes from the grid side. It makes solving the tasks of energy efficiency more difficult. To solve this problem, the use of Wavelet transform to create a mathematical tool for monitoring the load composition in the nodes of the distribution grids of 6-10 kV, 0.4 kV is proposed in this paper. The authors have created a unique wavelet based functions for some consumers, based on their current consumption graphs of these power consumers. Possibility of determination of the characteristics of individual consumers of electricity in total nodal charts of load is shown in the test case. In future, creation of a unified technical and informational model of load control will allow to solve the problem of increasing the economic efficiency of not only certain consumers, but also the entire power supply system as a whole.

E-learning task analysis making temporal evolution graphics on symptoms of waves and the ability to solve problems

NASA Astrophysics Data System (ADS)

Rosdiana, L.; Widodo, W.; Nurita, T.; Fauziah, A. N. M.

2018-04-01

This study aimed to describe the ability of pre-service teachers to create graphs, solve the problem of spatial and temporal evolution on the symptoms of vibrations and waves. The learning was conducted using e-learning method. The research design is a quasi-experimental design with one-shot case study. The e-learning contained learning materials and tasks involving answering tasks, making questions, solving their own questions, and making graphs. The participants of the study was 28 students of Science Department, Universitas Negeri Surabaya. The results obtained by using the e-learning were that the students’ ability increase gradually from task 1 to task 3 (the tasks consisted of three tasks). Additionally, based on the questionnaire with 28 respondents, it showed that 24 respondents stated that making graphs via e-learning were still difficult. Four respondents said that it was easy to make graphs via e-learning. Nine respondents stated that the e-learning did not help them in making graphs and 19 respondents stated that the e-learning help in creating graphs. The conclusion of the study is that the students was able to make graphs on paper sheet, but they got difficulty to make the graphs in e-learning (the virtual form).

Goal-directed tail use in Colombian spider monkeys (Ateles fusciceps rufiventris) is highly lateralized.

PubMed

Nelson, Eliza L; Kendall, Giulianna A

2018-02-01

Behavioral laterality refers to a bias in the use of one side of the body over the other and is commonly studied in paired organs (e.g., hands, feet, eyes, antennae). Less common are reports of laterality in unpaired organs (e.g., trunk, tongue, tail). The goal of the current study was to examine tail use biases across different tasks in the Colombian spider monkey ( Ateles fusciceps rufiventris ) for the first time (N = 14). We hypothesized that task context and task complexity influence tail laterality in spider monkeys, and we predicted that monkeys would exhibit strong preferences for using the tail for manipulation to solve out-of-reach feeding problems, but not for using the tail at rest. Our results show that a subset of spider monkeys solved each of the experimental problems through goal-directed tail use (N = 7). However, some tasks were more difficult than others, given the number of monkeys who solved the tasks. Our results supported our predictions regarding laterality in tail use and only partially replicated prior work on tail use preferences in Geoffroy's spider monkeys ( Ateles geoffroyi ). Overall, skilled tail use, but not resting tail use, was highly lateralized in Colombian spider monkeys. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Students' understandings of electrochemistry

NASA Astrophysics Data System (ADS)

O'Grady-Morris, Kathryn

Electrochemistry is considered by students to be a difficult topic in chemistry. This research was a mixed methods study guided by the research question: At the end of a unit of study, what are students' understandings of electrochemistry? The framework of analysis used for the qualitative and quantitative data collected in this study was comprised of three categories: types of knowledge used in problem solving, levels of representation of knowledge in chemistry (macroscopic, symbolic, and particulate), and alternative conceptions. Although individually each of the three categories has been reported in previous studies, the contribution of this study is the inter-relationships among them. Semi-structured, task-based interviews were conducted while students were setting up and operating electrochemical cells in the laboratory, and a two-tiered, multiple-choice diagnostic instrument was designed to identify alternative conceptions that students held at the end of the unit. For familiar problems, those involving routine voltaic cells, students used a working-forwards problem-solving strategy, two or three levels of representation of knowledge during explanations, scored higher on both procedural and conceptual knowledge questions in the diagnostic instrument, and held fewer alternative conceptions related to the operation of these cells. For less familiar problems, those involving non-routine voltaic cells and electrolytic cells, students approached problem-solving with procedural knowledge, used only one level of representation of knowledge when explaining the operation of these cells, scored higher on procedural knowledge than conceptual knowledge questions in the diagnostic instrument, and held a greater number of alternative conceptions. Decision routines that involved memorized formulas and procedures were used to solve both quantitative and qualitative problems and the main source of alternative conceptions in this study was the overgeneralization of theory related to the particulate level of representation of knowledge. The findings from this study may contribute further to our understanding of students' conceptions in electrochemistry. Furthermore, understanding the influence of the three categories in the framework of analysis and their inter-relationships on how students make sense of this field may result in a better understanding of classroom practice that could promote the acquisition of conceptual knowledge --- knowledge that is "rich in relationships".

Global convergence of inexact Newton methods for transonic flow

NASA Technical Reports Server (NTRS)

Young, David P.; Melvin, Robin G.; Bieterman, Michael B.; Johnson, Forrester T.; Samant, Satish S.

1990-01-01

In computational fluid dynamics, nonlinear differential equations are essential to represent important effects such as shock waves in transonic flow. Discretized versions of these nonlinear equations are solved using iterative methods. In this paper an inexact Newton method using the GMRES algorithm of Saad and Schultz is examined in the context of the full potential equation of aerodynamics. In this setting, reliable and efficient convergence of Newton methods is difficult to achieve. A poor initial solution guess often leads to divergence or very slow convergence. This paper examines several possible solutions to these problems, including a standard local damping strategy for Newton's method and two continuation methods, one of which utilizes interpolation from a coarse grid solution to obtain the initial guess on a finer grid. It is shown that the continuation methods can be used to augment the local damping strategy to achieve convergence for difficult transonic flow problems. These include simple wings with shock waves as well as problems involving engine power effects. These latter cases are modeled using the assumption that each exhaust plume is isentropic but has a different total pressure and/or temperature than the freestream.

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.

Development of a problem solving evaluation instrument; untangling of specific problem solving assets

NASA Astrophysics Data System (ADS)

Adams, Wendy Kristine

The purpose of my research was to produce a problem solving evaluation tool for physics. To do this it was necessary to gain a thorough understanding of how students solve problems. Although physics educators highly value problem solving and have put extensive effort into understanding successful problem solving, there is currently no efficient way to evaluate problem solving skill. Attempts have been made in the past; however, knowledge of the principles required to solve the subject problem are so absolutely critical that they completely overshadow any other skills students may use when solving a problem. The work presented here is unique because the evaluation tool removes the requirement that the student already have a grasp of physics concepts. It is also unique because I picked a wide range of people and picked a wide range of tasks for evaluation. This is an important design feature that helps make things emerge more clearly. This dissertation includes an extensive literature review of problem solving in physics, math, education and cognitive science as well as descriptions of studies involving student use of interactive computer simulations, the design and validation of a beliefs about physics survey and finally the design of the problem solving evaluation tool. I have successfully developed and validated a problem solving evaluation tool that identifies 44 separate assets (skills) necessary for solving problems. Rigorous validation studies, including work with an independent interviewer, show these assets identified by this content-free evaluation tool are the same assets that students use to solve problems in mechanics and quantum mechanics. Understanding this set of component assets will help teachers and researchers address problem solving within the classroom.

Evolutionary Steps in the Emergence of Life Deduced from the Bottom-Up Approach and GADV Hypothesis (Top-Down Approach)

PubMed Central

Ikehara, Kenji

2016-01-01

It is no doubt quite difficult to solve the riddle of the origin of life. So, firstly, I would like to point out the kinds of obstacles there are in solving this riddle and how we should tackle these difficult problems, reviewing the studies that have been conducted so far. After that, I will propose that the consecutive evolutionary steps in a timeline can be rationally deduced by using a common event as a juncture, which is obtained by two counter-directional approaches: one is the bottom-up approach through which many researchers have studied the origin of life, and the other is the top-down approach, through which I established the [GADV]-protein world hypothesis or GADV hypothesis on the origin of life starting from a study on the formation of entirely new genes in extant microorganisms. Last, I will describe the probable evolutionary process from the formation of Earth to the emergence of life, which was deduced by using a common event—the establishment of the first genetic code encoding [GADV]-amino acids—as a juncture for the results obtained from the two approaches. PMID:26821048

Evolutionary Steps in the Emergence of Life Deduced from the Bottom-Up Approach and GADV Hypothesis (Top-Down Approach).

PubMed

Ikehara, Kenji

2016-01-26

It is no doubt quite difficult to solve the riddle of the origin of life. So, firstly, I would like to point out the kinds of obstacles there are in solving this riddle and how we should tackle these difficult problems, reviewing the studies that have been conducted so far. After that, I will propose that the consecutive evolutionary steps in a timeline can be rationally deduced by using a common event as a juncture, which is obtained by two counter-directional approaches: one is the bottom-up approach through which many researchers have studied the origin of life, and the other is the top-down approach, through which I established the [GADV]-protein world hypothesis or GADV hypothesis on the origin of life starting from a study on the formation of entirely new genes in extant microorganisms. Last, I will describe the probable evolutionary process from the formation of Earth to the emergence of life, which was deduced by using a common event-the establishment of the first genetic code encoding [GADV]-amino acids-as a juncture for the results obtained from the two approaches.

New algorithms for field-theoretic block copolymer simulations: Progress on using adaptive-mesh refinement and sparse matrix solvers in SCFT calculations

NASA Astrophysics Data System (ADS)

Sides, Scott; Jamroz, Ben; Crockett, Robert; Pletzer, Alexander

2012-02-01

Self-consistent field theory (SCFT) for dense polymer melts has been highly successful in describing complex morphologies in block copolymers. Field-theoretic simulations such as these are able to access large length and time scales that are difficult or impossible for particle-based simulations such as molecular dynamics. The modified diffusion equations that arise as a consequence of the coarse-graining procedure in the SCF theory can be efficiently solved with a pseudo-spectral (PS) method that uses fast-Fourier transforms on uniform Cartesian grids. However, PS methods can be difficult to apply in many block copolymer SCFT simulations (eg. confinement, interface adsorption) in which small spatial regions might require finer resolution than most of the simulation grid. Progress on using new solver algorithms to address these problems will be presented. The Tech-X Chompst project aims at marrying the best of adaptive mesh refinement with linear matrix solver algorithms. The Tech-X code PolySwift++ is an SCFT simulation platform that leverages ongoing development in coupling Chombo, a package for solving PDEs via block-structured AMR calculations and embedded boundaries, with PETSc, a toolkit that includes a large assortment of sparse linear solvers.

Age differences in everyday problem-solving effectiveness: older adults select more effective strategies for interpersonal problems.

PubMed

Blanchard-Fields, Fredda; Mienaltowski, Andrew; Seay, Renee Baldi

2007-01-01

Using the Everyday Problem Solving Inventory of Cornelius and Caspi, we examined differences in problem-solving strategy endorsement and effectiveness in two domains of everyday functioning (instrumental or interpersonal, and a mixture of the two domains) and for four strategies (avoidance-denial, passive dependence, planful problem solving, and cognitive analysis). Consistent with past research, our research showed that older adults were more problem focused than young adults in their approach to solving instrumental problems, whereas older adults selected more avoidant-denial strategies than young adults when solving interpersonal problems. Overall, older adults were also more effective than young adults when solving everyday problems, in particular for interpersonal problems.

Spontaneous gestures influence strategy choices in problem solving.

PubMed

Alibali, Martha W; Spencer, Robert C; Knox, Lucy; Kita, Sotaro

2011-09-01

Do gestures merely reflect problem-solving processes, or do they play a functional role in problem solving? We hypothesized that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving. Participants in two experiments solved problems requiring the prediction of gear movement, either with gesture allowed or with gesture prohibited. Such problems can be correctly solved using either a perceptual-motor strategy (simulation of gear movements) or an abstract strategy (the parity strategy). Participants in the gesture-allowed condition were more likely to use perceptual-motor strategies than were participants in the gesture-prohibited condition. Gesture promoted use of perceptual-motor strategies both for participants who talked aloud while solving the problems (Experiment 1) and for participants who solved the problems silently (Experiment 2). Thus, spontaneous gestures influence strategy choices in problem solving.

Too upset to think: the interplay of borderline personality features, negative emotions, and social problem solving in the laboratory.

PubMed

Dixon-Gordon, Katherine L; Chapman, Alexander L; Lovasz, Nathalie; Walters, Kris

2011-10-01

Borderline personality disorder (BPD) is associated with poor social problem solving and problems with emotion regulation. In this study, the social problem-solving performance of undergraduates with high (n = 26), mid (n = 32), or low (n = 29) levels of BPD features was assessed with the Social Problem-Solving Inventory-Revised and using the means-ends problem-solving procedure before and after a social rejection stressor. The high-BP group, but not the low-BP group, showed a significant reduction in relevant solutions to social problems and more inappropriate solutions following the negative emotion induction. Increases in self-reported negative emotions during the emotion induction mediated the relationship between BP features and reductions in social problem-solving performance. In addition, the high-BP group demonstrated trait deficits in social problem solving on the Social Problem-Solving Inventory-Revised. These findings suggest that future research must examine social problem solving under differing emotional conditions, and that clinical interventions to improve social problem solving among persons with BP features should focus on responses to emotional contexts.

Proteomics, lipidomics, metabolomics: a mass spectrometry tutorial from a computer scientist's point of view.

PubMed

Smith, Rob; Mathis, Andrew D; Ventura, Dan; Prince, John T

2014-01-01

For decades, mass spectrometry data has been analyzed to investigate a wide array of research interests, including disease diagnostics, biological and chemical theory, genomics, and drug development. Progress towards solving any of these disparate problems depends upon overcoming the common challenge of interpreting the large data sets generated. Despite interim successes, many data interpretation problems in mass spectrometry are still challenging. Further, though these challenges are inherently interdisciplinary in nature, the significant domain-specific knowledge gap between disciplines makes interdisciplinary contributions difficult. This paper provides an introduction to the burgeoning field of computational mass spectrometry. We illustrate key concepts, vocabulary, and open problems in MS-omics, as well as provide invaluable resources such as open data sets and key search terms and references. This paper will facilitate contributions from mathematicians, computer scientists, and statisticians to MS-omics that will fundamentally improve results over existing approaches and inform novel algorithmic solutions to open problems.

Characterizing muscular activities using non-negative matrix factorization from EMG channels for driver swings in golf.

PubMed

Ozaki, Yasunori; Aoki, Ryosuke; Kimura, Toshitaka; Takashima, Youichi; Yamada, Tomohiro

2016-08-01

The goal of this study is to propose a data driven approach method to characterize muscular activities of complex actions in sports such as golf from a lot of EMG channels. Two problems occur in a many channel measurement. The first problem is that it takes a lot of time to check the many channel data because of combinatorial explosion. The second problem is that it is difficult to understand muscle activities related with complex actions. To solve these problems, we propose an analysis method of multi EMG channels using Non-negative Matrix Factorization and adopt the method to driver swings in golf. We measured 26 EMG channels about 4 professional coaches of golf. The results show that the proposed method detected 9 muscle synergies and the activation of each synergy were mostly fitted by sigmoid curve (R2=0.85).

Data parallel sorting for particle simulation

NASA Technical Reports Server (NTRS)

Dagum, Leonardo

1992-01-01

Sorting on a parallel architecture is a communications intensive event which can incur a high penalty in applications where it is required. In the case of particle simulation, only integer sorting is necessary, and sequential implementations easily attain the minimum performance bound of O (N) for N particles. Parallel implementations, however, have to cope with the parallel sorting problem which, in addition to incurring a heavy communications cost, can make the minimun performance bound difficult to attain. This paper demonstrates how the sorting problem in a particle simulation can be reduced to a merging problem, and describes an efficient data parallel algorithm to solve this merging problem in a particle simulation. The new algorithm is shown to be optimal under conditions usual for particle simulation, and its fieldwise implementation on the Connection Machine is analyzed in detail. The new algorithm is about four times faster than a fieldwise implementation of radix sort on the Connection Machine.

The Problem of Confounding in Studies of the Effect of Maternal Drug Use on Pregnancy Outcome

PubMed Central

Källén, Bengt

2012-01-01

In most epidemilogical studies, the problem of confounding adds to the uncertainty in conclusions drawn. This is also true for studies on the effect of maternal drug use on birth defect risks. This paper describes various types of such confounders and discusses methods to identify and adjust for them. Such confounders can be found in maternal characteristics like age, parity, smoking, use of alcohol, and body mass index, subfertility, and previous pregnancies including previous birth of a malformed child, socioeconomy, race/ethnicity, or country of birth. Confounding by concomitant maternal drug use may occur. A geographical or seasonal confounding can exist. In rare instances, infant sex and multiple birth can appear as confounders. The most difficult problem to solve is often confounding by indication. The problem of confounding is less important for congenital malformations than for many other pregnancy outcomes. PMID:22190949

An Investigation of Secondary Teachers’ Understanding and Belief on Mathematical Problem Solving

NASA Astrophysics Data System (ADS)

Yuli Eko Siswono, Tatag; Wachidul Kohar, Ahmad; Kurniasari, Ika; Puji Astuti, Yuliani

2016-02-01

Weaknesses on problem solving of Indonesian students as reported by recent international surveys give rise to questions on how Indonesian teachers bring out idea of problem solving in mathematics lesson. An explorative study was undertaken to investigate how secondary teachers who teach mathematics at junior high school level understand and show belief toward mathematical problem solving. Participants were teachers from four cities in East Java province comprising 45 state teachers and 25 private teachers. Data was obtained through questionnaires and written test. The results of this study point out that the teachers understand pedagogical problem solving knowledge well as indicated by high score of observed teachers‘ responses showing understanding on problem solving as instruction as well as implementation of problem solving in teaching practice. However, they less understand on problem solving content knowledge such as problem solving strategies and meaning of problem itself. Regarding teacher's difficulties, teachers admitted to most frequently fail in (1) determining a precise mathematical model or strategies when carrying out problem solving steps which is supported by data of test result that revealed transformation error as the most frequently observed errors in teachers’ work and (2) choosing suitable real situation when designing context-based problem solving task. Meanwhile, analysis of teacher's beliefs on problem solving shows that teachers tend to view both mathematics and how students should learn mathematics as body static perspective, while they tend to believe to apply idea of problem solving as dynamic approach when teaching mathematics.

The Impact of Teacher Training on Creative Writing and Problem-Solving Using Futuristic Scenarios for Creative Problem Solving and Creative Problem Solving Programs

ERIC Educational Resources Information Center

Hayel Al-Srour, Nadia; Al-Ali, Safa M.; Al-Oweidi, Alia

2016-01-01

The present study aims to detect the impact of teacher training on creative writing and problem-solving using both Futuristic scenarios program to solve problems creatively, and creative problem solving. To achieve the objectives of the study, the sample was divided into two groups, the first consist of 20 teachers, and 23 teachers to second…

Problem-solving skills in high school biology: The effectiveness of the IMMEX problem-solving assessment software

NASA Astrophysics Data System (ADS)

Palacio-Cayetano, Joycelin

"Problem-solving through reflective thinking should be both the method and valuable outcome of science instruction in America's schools" proclaimed John Dewey (Gabel, 1995). If the development of problem-solving is a primary goal of science education, more problem-solving opportunities must be an integral part of K-16 education. To examine the effective use of technology in developing and assessing problem-solving skills, a problem-solving authoring, learning, and assessment software, the UCLA IMMEX Program-Interactive Multimedia Exercises-was investigated. This study was a twenty-week quasi-experimental study that was implemented as a control-group time series design among 120 tenth grade students. Both the experimental group (n = 60) and the control group (n = 60) participated in a problem-based learning curriculum; however, the experimental group received regular intensive experiences with IMMEX problem-solving and the control group did not. Problem-solving pretest and posttest were administered to all students. The instruments used were a 35-item Processes of Biological Inquiry Test and an IMMEX problem-solving assessment test, True Roots. Students who participated in the IMMEX Program achieved significant (p <.05) gains in problem-solving skills on both problem-solving assessment instruments. This study provided evidence that IMMEX software is highly efficient in evaluating salient elements of problem-solving. Outputs of students' problem-solving strategies revealed that unsuccessful problem solvers primarily used the following four strategies: (1) no data search strategy, students simply guessed; (2) limited data search strategy leading to insufficient data and premature closing; (3) irrelevant data search strategy, students focus in areas bearing no substantive data; and (4) extensive data search strategy with inadequate integration and analysis. On the contrary, successful problem solvers used the following strategies; (1) focused search strategy coupled with the ability to fill in knowledge gaps by accessing the appropriate resources; (2) targeted search strategy coupled with high level of analytical and integration skills; and (3) focused search strategy coupled with superior discrimination, analytical, and integration skills. The strategies of students who were successful and unsuccessful solving IMMEX problems were consistent with those of expert and novice problem solvers identified in the literature on problem-solving.

Potential-splitting approach applied to the Temkin-Poet model for electron scattering off the hydrogen atom and the helium ion

NASA Astrophysics Data System (ADS)

Yarevsky, E.; Yakovlev, S. L.; Larson, Å; Elander, N.

2015-06-01

The study of scattering processes in few body systems is a difficult problem especially if long range interactions are involved. In order to solve such problems, we develop here a potential-splitting approach for three-body systems. This approach is based on splitting the reaction potential into a finite range core part and a long range tail part. The solution to the Schrödinger equation for the long range tail Hamiltonian is found analytically, and used as an incoming wave in the three body scattering problem. This reformulation of the scattering problem makes it suitable for treatment by the exterior complex scaling technique in the sense that the problem after the complex dilation is reduced to a boundary value problem with zero boundary conditions. We illustrate the method with calculations on the electron scattering off the hydrogen atom and the positive helium ion in the frame of the Temkin-Poet model.

Pre-Service Class Teacher' Ability in Solving Mathematical Problems and Skills in Solving Daily Problems

ERIC Educational Resources Information Center

Aljaberi, Nahil M.; Gheith, Eman

2016-01-01

This study aims to investigate the ability of pre-service class teacher at University of Petrain solving mathematical problems using Polya's Techniques, their level of problem solving skills in daily-life issues. The study also investigates the correlation between their ability to solve mathematical problems and their level of problem solving…

The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems.

PubMed

Baars, Martine; Wijnia, Lisette; Paas, Fred

2017-01-01

Self-regulated learning (SRL) skills are essential for learning during school years, particularly in complex problem-solving domains, such as biology and math. Although a lot of studies have focused on the cognitive resources that are needed for learning to solve problems in a self-regulated way, affective and motivational resources have received much less research attention. The current study investigated the relation between affect (i.e., Positive Affect and Negative Affect Scale), motivation (i.e., autonomous and controlled motivation), mental effort, SRL skills, and problem-solving performance when learning to solve biology problems in a self-regulated online learning environment. In the learning phase, secondary education students studied video-modeling examples of how to solve hereditary problems, solved hereditary problems which they chose themselves from a set of problems with different complexity levels (i.e., five levels). In the posttest, students solved hereditary problems, self-assessed their performance, and chose a next problem from the set of problems but did not solve these problems. The results from this study showed that negative affect, inaccurate self-assessments during the posttest, and higher perceptions of mental effort during the posttest were negatively associated with problem-solving performance after learning in a self-regulated way.

Interference and problem size effect in multiplication fact solving: Individual differences in brain activations and arithmetic performance.

PubMed

De Visscher, Alice; Vogel, Stephan E; Reishofer, Gernot; Hassler, Eva; Koschutnig, Karl; De Smedt, Bert; Grabner, Roland H

2018-05-15

In the development of math ability, a large variability of performance in solving simple arithmetic problems is observed and has not found a compelling explanation yet. One robust effect in simple multiplication facts is the problem size effect, indicating better performance for small problems compared to large ones. Recently, behavioral studies brought to light another effect in multiplication facts, the interference effect. That is, high interfering problems (receiving more proactive interference from previously learned problems) are more difficult to retrieve than low interfering problems (in terms of physical feature overlap, namely the digits, De Visscher and Noël, 2014). At the behavioral level, the sensitivity to the interference effect is shown to explain individual differences in the performance of solving multiplications in children as well as in adults. The aim of the present study was to investigate the individual differences in multiplication ability in relation to the neural interference effect and the neural problem size effect. To that end, we used a paradigm developed by De Visscher, Berens, et al. (2015) that contrasts the interference effect and the problem size effect in a multiplication verification task, during functional magnetic resonance imaging (fMRI) acquisition. Forty-two healthy adults, who showed high variability in an arithmetic fluency test, participated in our fMRI study. In order to control for the general reasoning level, the IQ was taken into account in the individual differences analyses. Our findings revealed a neural interference effect linked to individual differences in multiplication in the left inferior frontal gyrus, while controlling for the IQ. This interference effect in the left inferior frontal gyrus showed a negative relation with individual differences in arithmetic fluency, indicating a higher interference effect for low performers compared to high performers. This region is suggested in the literature to be involved in resolution of proactive interference. Besides, no correlation between the neural problem size effect and multiplication performance was found. This study supports the idea that the interference due to similarities/overlap of physical traits (the digits) is crucial in memorizing arithmetic facts and in determining individual differences in arithmetic. Copyright © 2018 Elsevier Inc. All rights reserved.

Methods and compositions for efficient nucleic acid sequencing

DOEpatents

Drmanac, Radoje

2006-07-04

Disclosed are novel methods and compositions for rapid and highly efficient nucleic acid sequencing based upon hybridization with two sets of small oligonucleotide probes of known sequences. Extremely large nucleic acid molecules, including chromosomes and non-amplified RNA, may be sequenced without prior cloning or subcloning steps. The methods of the invention also solve various current problems associated with sequencing technology such as, for example, high noise to signal ratios and difficult discrimination, attaching many nucleic acid fragments to a surface, preparing many, longer or more complex probes and labelling more species.

Methods and compositions for efficient nucleic acid sequencing

DOEpatents

Drmanac, Radoje

2002-01-01

Disclosed are novel methods and compositions for rapid and highly efficient nucleic acid sequencing based upon hybridization with two sets of small oligonucleotide probes of known sequences. Extremely large nucleic acid molecules, including chromosomes and non-amplified RNA, may be sequenced without prior cloning or subcloning steps. The methods of the invention also solve various current problems associated with sequencing technology such as, for example, high noise to signal ratios and difficult discrimination, attaching many nucleic acid fragments to a surface, preparing many, longer or more complex probes and labelling more species.

Fusion proteins as alternate crystallization paths to difficult structure problems

NASA Technical Reports Server (NTRS)

Carter, Daniel C.; Rueker, Florian; Ho, Joseph X.; Lim, Kap; Keeling, Kim; Gilliland, Gary; Ji, Xinhua

1994-01-01

The three-dimensional structure of a peptide fusion product with glutathione transferase from Schistosoma japonicum (SjGST) has been solved by crystallographic methods to 2.5 A resolution. Peptides or proteins can be fused to SjGST and expressed in a plasmid for rapid synthesis in Escherichia coli. Fusion proteins created by this commercial method can be purified rapidly by chromatography on immobilized glutathione. The potential utility of using SjGST fusion proteins as alternate paths to the crystallization and structure determination of proteins is demonstrated.

Study of Threat Scenario Reconstruction based on Multiple Correlation

NASA Astrophysics Data System (ADS)

Yuan, Xuejun; Du, Jing; Qin, Futong; Zhou, Yunyan

2017-10-01

The emergence of intrusion detection technology has solved many network attack problems, ensuring the safety of computer systems. However, because of the isolated output alarm information, large amount of data, and mixed events, it is difficult for the managers to understand the deep logic relationship between the alarm information, thus they cannot deduce the attacker’s true intentions. This paper presents a method of online threat scene reconstruction to handle the alarm information, which reconstructs of the threat scene. For testing, the standard data set is used.

Very High Speed Integrated Circuits - VHSIC - Final Program Repoort

DTIC Science & Technology

1990-09-30

emphasis ill ordeFr to (U hieci’ the i/ urease (I mIliitdF capa)(bility L’XI)L’t(’d /)1omn its resiuIh x.’ -Ricluard J). [)ehaitr. Undicer Sec reta/vy...Many new and difficult fabrication problems had to be solved, especially in the areas of silicon substrate material, fine-line lithography, multi- layer ...toward submicron geometries, even in the commercial world ." "Among the technical breakthrou hs spawned by VHSIC is the use of multiple layers of wetal

An entangled web of crime: Bell's theorem as a short story

NASA Astrophysics Data System (ADS)

Jacobs, Kurt; Wiseman, Howard M.

2005-10-01

Nonlocality of the type first elucidated by Bell in 1964 is a difficult concept to explain to nonspecialists and undergraduates. We attempt to do so by showing how nonlocality can be used to solve a problem in which someone might find themselves as the result of a series of normal, even if somewhat unlikely, events. Our story is told in the style of a Sherlock Holmes mystery, and is based on Mermin's formulation of the "paradoxical" illustration of quantum nonlocality discovered by Greenberger, Horne, and Zeilinger.

Merging Black Holes

NASA Technical Reports Server (NTRS)

Centrella, Joan; Baker, John G.; Kelly, Bernard J.; vanMeter, James R.

2010-01-01

Black-hole mergers take place in regions of very strong and dynamical gravitational fields, and are among the strongest sources of gravitational radiation. Probing these mergers requires solving the full set of Einstein's equations of general relativity numerically. For more than 40 years, progress towards this goal has been very slow, as numerical relativists encountered a host of difficult problems. Recently, several breakthroughs have led to dramatic progress, enabling stable and accurate calculations of black-hole mergers. This article presents an overview of this field, including impacts on astrophysics and applications in gravitational wave data analysis.

Recent heavy particle decay in a matter dominated universe

NASA Astrophysics Data System (ADS)

Olive, K. A.; Seckel, D.; Vishniac, E.

1984-09-01

The cold matter scenario for galaxy formation solves the dark matter problem very nicely on small scales corresponding to galaxies and clusters of galaxies. It is, however, difficult to reconcile with a Universe with an Einstein-deSitter value of (UC OMEGA) = 1. Cold matter and (UC OMEGA) = 1 can be made compatible while retaining the feature that the Universe is matter dominated today. This is done by means of heavy (cold) particles whose decay subsequently leads to the unbinding of a large fraction of lighter clustered matter.

Recent heavy-particle decay in a matter-dominated universe

NASA Astrophysics Data System (ADS)

Olive, K. A.; Seckel, D.; Vishniac, E.

1985-05-01

The cold-matter scenario for galaxy formation solves the dark-matter problem very nicely on small scales corresponding to galaxies and clusters of galaxies. It is, however, difficult to reconcile with a universe with an Einstein-deSitter value of Ω = 1. It is shown here that cold matter and Ω = 1 can be made compatible while retaining the feature that the universe is matter-dominated today. This is done by means of heavy (cold) particles whose decay subsequently leads to the unbinding of a large fraction of lighter clustered matter.

Bullying in schools: what is the problem, and how can educators solve it?

PubMed

Strohmeier, Dagmar; Noam, Gil G

2012-01-01

This chapter reviews recent research on bullying from an educator's perspective. It is well known that bullying, a serious issue in schools, can be prevented when educators intervene. But research has shown that it is difficult for educators to detect bullying situations in their school and intervene competently and effectively. This chapter examines how educators can detect bullying, how they can best tackle serious cases of bullying, and how they can best prevent bullying in the long run. Copyright © 2012 Wiley Periodicals, Inc., A Wiley Company.

Problem-solving strategies of women undergoing chemotherapy for breast cancer.

PubMed

Lyons, Kathleen D; Erickson, Kelly S; Hegel, Mark T

2012-02-01

Many women undergoing chemotherapy for breast cancer experience side effects that make it difficult to perform daily occupations. To summarize the types of challenges, goals, and adaptive strategies identified by women with stage 1-3 breast cancer participating in a pilot study of Problem-solving Treatment-Occupational Therapy (PST-OT). Content analysis of 80 PST-OT sessions. Women addressed 11 types of challenging activities, with exercise and instrumental activities of daily living (IADL) being the most common. Most women set a goal to adapt a current activity, but also set goals to find a new activity, plan the steps of a current activity, or gather information about a possible activity change in the future. The adaptive strategies generated by the women were grouped into five types. Most often they found ways to add a new step to an activity, but they also brainstormed about when, how, where, and with whom they could do activities. The women were usually trying to adapt familiar activities but also were looking for ways to include new, healthy occupations into their routines.

A practical approximation algorithm for solving massive instances of hybridization number for binary and nonbinary trees.

PubMed

van Iersel, Leo; Kelk, Steven; Lekić, Nela; Scornavacca, Celine

2014-05-05

Reticulate events play an important role in determining evolutionary relationships. The problem of computing the minimum number of such events to explain discordance between two phylogenetic trees is a hard computational problem. Even for binary trees, exact solvers struggle to solve instances with reticulation number larger than 40-50. Here we present CycleKiller and NonbinaryCycleKiller, the first methods to produce solutions verifiably close to optimality for instances with hundreds or even thousands of reticulations. Using simulations, we demonstrate that these algorithms run quickly for large and difficult instances, producing solutions that are very close to optimality. As a spin-off from our simulations we also present TerminusEst, which is the fastest exact method currently available that can handle nonbinary trees: this is used to measure the accuracy of the NonbinaryCycleKiller algorithm. All three methods are based on extensions of previous theoretical work (SIDMA 26(4):1635-1656, TCBB 10(1):18-25, SIDMA 28(1):49-66) and are publicly available. We also apply our methods to real data.

Parenting and independent problem-solving in preschool children with food allergy.

PubMed

Dahlquist, Lynnda M; Power, Thomas G; Hahn, Amy L; Hoehn, Jessica L; Thompson, Caitlin C; Herbert, Linda J; Law, Emily F; Bollinger, Mary Elizabeth

2015-01-01

To examine autonomy-promoting parenting and independent problem-solving in children with food allergy. 66 children with food allergy, aged 3-6 years, and 67 age-matched healthy peers and their mothers were videotaped while completing easy and difficult puzzles. Coders recorded time to puzzle completion, children's direct and indirect requests for help, and maternal help-giving behaviors. Compared with healthy peers, younger (3- to 4-year-old) children with food allergy made more indirect requests for help during the easy puzzle, and their mothers were more likely to provide unnecessary help (i.e., explain where to place a puzzle piece). Differences were not found for older children. The results suggest that highly involved parenting practices that are medically necessary to manage food allergy may spill over into settings where high levels of involvement are not needed, and that young children with food allergy may be at increased risk for difficulties in autonomy development. © The Author 2014. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Eddy-Current Sensors with Asymmetrical Point Spread Function

PubMed Central

Gajda, Janusz; Stencel, Marek

2016-01-01

This paper concerns a special type of eddy-current sensor in the form of inductive loops. Such sensors are applied in the measuring systems classifying road vehicles. They usually have a rectangular shape with dimensions of 1 × 2 m, and are installed under the surface of the traffic lane. The wide Point Spread Function (PSF) of such sensors causes the information on chassis geometry, contained in the measurement signal, to be strongly averaged. This significantly limits the effectiveness of the vehicle classification. Restoration of the chassis shape, by solving the inverse problem (deconvolution), is also difficult due to the fact that it is ill-conditioned. An original approach to solving this problem is presented in this paper. It is a hardware-based solution and involves the use of inductive loops with an asymmetrical PSF. Laboratory experiments and simulation tests, conducted with models of an inductive loop, confirmed the effectiveness of the proposed solution. In this case, the principle applies that the higher the level of sensor spatial asymmetry, the greater the effectiveness of the deconvolution algorithm. PMID:27782033

Research on the transfer learning of the vehicle logo recognition

NASA Astrophysics Data System (ADS)

Zhao, Wei

2017-08-01

The Convolutional Neural Network of Deep Learning has been a huge success in the field of image intelligent transportation system can effectively solve the traffic safety, congestion, vehicle management and other problems of traffic in the city. Vehicle identification is a vital part of intelligent transportation, and the effective information in vehicles is of great significance to vehicle identification. With the traffic system on the vehicle identification technology requirements are getting higher and higher, the vehicle as an important type of vehicle information, because it should not be removed, difficult to change and other features for vehicle identification provides an important method. The current vehicle identification recognition (VLR) is mostly used to extract the characteristics of the method of classification, which for complex classification of its generalization ability to be some constraints, if the use of depth learning technology, you need a lot of training samples. In this paper, the method of convolution neural network based on transfer learning can solve this problem effectively, and it has important practical application value in the task of vehicle mark recognition.

Eddy-Current Sensors with Asymmetrical Point Spread Function.

PubMed

Gajda, Janusz; Stencel, Marek

2016-10-04

This paper concerns a special type of eddy-current sensor in the form of inductive loops. Such sensors are applied in the measuring systems classifying road vehicles. They usually have a rectangular shape with dimensions of 1 × 2 m, and are installed under the surface of the traffic lane. The wide Point Spread Function (PSF) of such sensors causes the information on chassis geometry, contained in the measurement signal, to be strongly averaged. This significantly limits the effectiveness of the vehicle classification. Restoration of the chassis shape, by solving the inverse problem (deconvolution), is also difficult due to the fact that it is ill-conditioned. An original approach to solving this problem is presented in this paper. It is a hardware-based solution and involves the use of inductive loops with an asymmetrical PSF. Laboratory experiments and simulation tests, conducted with models of an inductive loop, confirmed the effectiveness of the proposed solution. In this case, the principle applies that the higher the level of sensor spatial asymmetry, the greater the effectiveness of the deconvolution algorithm.

Evaluation and Testing of the ADVANTG Code on SNM Detection

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

Shaver, Mark W.; Casella, Andrew M.; Wittman, Richard S.

2013-09-24

Pacific Northwest National Laboratory (PNNL) has been tasked with evaluating the effectiveness of ORNL’s new hybrid transport code, ADVANTG, on scenarios of interest to our NA-22 sponsor, specifically of detection of diversion of special nuclear material (SNM). PNNL staff have determined that acquisition and installation of ADVANTG was relatively straightforward for a code in its phase of development, but probably not yet sufficient for mass distribution to the general user. PNNL staff also determined that with little effort, ADVANTG generated weight windows that typically worked for the problems and generated results consistent with MCNP. With slightly greater effort of choosingmore » a finer mesh around detectors or sample reaction tally regions, the figure of merit (FOM) could be further improved in most cases. This does take some limited knowledge of deterministic transport methods. The FOM could also be increased by limiting the energy range for a tally to the energy region of greatest interest. It was then found that an MCNP run with the full energy range for the tally showed improved statistics in the region used for the ADVANTG run. The specific case of interest chosen by the sponsor is the CIPN project from Las Alamos National Laboratory (LANL), which is an active interrogation, non-destructive assay (NDA) technique to quantify the fissile content in a spent fuel assembly and is also sensitive to cases of material diversion. Unfortunately, weight windows for the CIPN problem cannot currently be properly generated with ADVANTG due to inadequate accommodations for source definition. ADVANTG requires that a fixed neutron source be defined within the problem and cannot account for neutron multiplication. As such, it is rendered useless in active interrogation scenarios. It is also interesting to note that this is a difficult problem to solve and that the automated weight windows generator in MCNP actually slowed down the problem. Therefore, PNNL had determined that there is not an effective tool available for speeding up MCNP for problems such as the CIPN scenario. With regard to the Benchmark scenarios, ADVANTG performed very well for most of the difficult, long-running, standard radiation detection scenarios. Specifically, run time speedups were observed for spatially large scenarios, or those having significant shielding or scattering geometries. ADVANTG performed on par with existing codes for moderate sized scenarios, or those with little to moderate shielding, or multiple paths to the detectors. ADVANTG ran slower than MCNP for very simply, spatially small cases with little to no shielding that run very quickly anyway. Lastly, ADVANTG could not solve problems that did not consist of fixed source to detector geometries. For example, it could not solve scenarios with multiple detectors or secondary particles, such as active interrogation, neutron induced gamma, or fission neutrons.« less

Extraction of a group-pair relation: problem-solving relation from web-board documents.

PubMed

Pechsiri, Chaveevan; Piriyakul, Rapepun

2016-01-01

This paper aims to extract a group-pair relation as a Problem-Solving relation, for example a DiseaseSymptom-Treatment relation and a CarProblem-Repair relation, between two event-explanation groups, a problem-concept group as a symptom/CarProblem-concept group and a solving-concept group as a treatment-concept/repair concept group from hospital-web-board and car-repair-guru-web-board documents. The Problem-Solving relation (particularly Symptom-Treatment relation) including the graphical representation benefits non-professional persons by supporting knowledge of primarily solving problems. The research contains three problems: how to identify an EDU (an Elementary Discourse Unit, which is a simple sentence) with the event concept of either a problem or a solution; how to determine a problem-concept EDU boundary and a solving-concept EDU boundary as two event-explanation groups, and how to determine the Problem-Solving relation between these two event-explanation groups. Therefore, we apply word co-occurrence to identify a problem-concept EDU and a solving-concept EDU, and machine-learning techniques to solve a problem-concept EDU boundary and a solving-concept EDU boundary. We propose using k-mean and Naïve Bayes to determine the Problem-Solving relation between the two event-explanation groups involved with clustering features. In contrast to previous works, the proposed approach enables group-pair relation extraction with high accuracy.

Students’ Mathematical Problem-Solving Abilities Through The Application of Learning Models Problem Based Learning

NASA Astrophysics Data System (ADS)

Nasution, M. L.; Yerizon, Y.; Gusmiyanti, R.

2018-04-01

One of the purpose mathematic learning is to develop problem solving abilities. Problem solving is obtained through experience in questioning non-routine. Improving students’ mathematical problem-solving abilities required an appropriate strategy in learning activities one of them is models problem based learning (PBL). Thus, the purpose of this research is to determine whether the problem solving abilities of mathematical students’ who learn to use PBL better than on the ability of students’ mathematical problem solving by applying conventional learning. This research included quasi experiment with static group design and population is students class XI MIA SMAN 1 Lubuk Alung. Class experiment in the class XI MIA 5 and class control in the class XI MIA 6. The instrument of final test students’ mathematical problem solving used essay form. The result of data final test in analyzed with t-test. The result is students’ mathematical problem solving abilities with PBL better then on the ability of students’ mathematical problem solving by applying conventional learning. It’s seen from the high percentage achieved by the group of students who learn to use PBL for each indicator of students’ mathematical problem solving.

Using a general problem-solving strategy to promote transfer.

PubMed

Youssef-Shalala, Amina; Ayres, Paul; Schubert, Carina; Sweller, John

2014-09-01

Cognitive load theory was used to hypothesize that a general problem-solving strategy based on a make-as-many-moves-as-possible heuristic could facilitate problem solutions for transfer problems. In four experiments, school students were required to learn about a topic through practice with a general problem-solving strategy, through a conventional problem solving strategy or by studying worked examples. In Experiments 1 and 2 using junior high school students learning geometry, low knowledge students in the general problem-solving group scored significantly higher on near or far transfer tests than the conventional problem-solving group. In Experiment 3, an advantage for a general problem-solving group over a group presented worked examples was obtained on far transfer tests using the same curriculum materials, again presented to junior high school students. No differences between conditions were found in Experiments 1, 2, or 3 using test problems similar to the acquisition problems. Experiment 4 used senior high school students studying economics and found the general problem-solving group scored significantly higher than the conventional problem-solving group on both similar and transfer tests. It was concluded that the general problem-solving strategy was helpful for novices, but not for students that had access to domain-specific knowledge. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Revising explanatory models to accommodate anomalous genetic phenomena: Problem solving in the context of discovery

NASA Astrophysics Data System (ADS)

Hafner, Robert; Stewart, Jim

Past problem-solving research has provided a basis for helping students structure their knowledge and apply appropriate problem-solving strategies to solve problems for which their knowledge (or mental models) of scientific phenomena is adequate (model-using problem solving). This research examines how problem solving in the domain of Mendelian genetics proceeds in situations where solvers' mental models are insufficient to solve problems at hand (model-revising problem solving). Such situations require solvers to use existing models to recognize anomalous data and to revise those models to accommodate the data. The study was conducted in the context of 9-week high school genetics course and addressed: the heuristics charactenstic of successful model-revising problem solving: the nature of the model revisions, made by students as well as the nature of model development across problem types; and the basis upon which solvers decide that a revised model is sufficient (that t has both predictive and explanatory power).

Parent-Teacher Communication about Children with Autism Spectrum Disorder: An Examination of Collaborative Problem-Solving

PubMed Central

Azad, Gazi F.; Kim, Mina; Marcus, Steven C.; Mandell, David S.; Sheridan, Susan M.

2016-01-01

Effective parent-teacher communication involves problem-solving concerns about students. Few studies have examined problem solving interactions between parents and teachers of children with autism spectrum disorder (ASD), with a particular focus on identifying communication barriers and strategies for improving them. This study examined the problem-solving behaviors of parents and teachers of children with ASD. Participants included 18 teachers and 39 parents of children with ASD. Parent-teacher dyads were prompted to discuss and provide a solution for a problem that a student experienced at home and at school. Parents and teachers also reported on their problem-solving behaviors. Results showed that parents and teachers displayed limited use of the core elements of problem-solving. Teachers displayed more problem-solving behaviors than parents. Both groups reported engaging in more problem-solving behaviors than they were observed to display during their discussions. Our findings suggest that teacher and parent training programs should include collaborative approaches to problem-solving. PMID:28392604

Parent-Teacher Communication about Children with Autism Spectrum Disorder: An Examination of Collaborative Problem-Solving.

PubMed

Azad, Gazi F; Kim, Mina; Marcus, Steven C; Mandell, David S; Sheridan, Susan M

2016-12-01

Effective parent-teacher communication involves problem-solving concerns about students. Few studies have examined problem solving interactions between parents and teachers of children with autism spectrum disorder (ASD), with a particular focus on identifying communication barriers and strategies for improving them. This study examined the problem-solving behaviors of parents and teachers of children with ASD. Participants included 18 teachers and 39 parents of children with ASD. Parent-teacher dyads were prompted to discuss and provide a solution for a problem that a student experienced at home and at school. Parents and teachers also reported on their problem-solving behaviors. Results showed that parents and teachers displayed limited use of the core elements of problem-solving. Teachers displayed more problem-solving behaviors than parents. Both groups reported engaging in more problem-solving behaviors than they were observed to display during their discussions. Our findings suggest that teacher and parent training programs should include collaborative approaches to problem-solving.

Errors analysis of problem solving using the Newman stage after applying cooperative learning of TTW type

NASA Astrophysics Data System (ADS)

Rr Chusnul, C.; Mardiyana, S., Dewi Retno

2017-12-01

Problem solving is the basis of mathematics learning. Problem solving teaches us to clarify an issue coherently in order to avoid misunderstanding information. Sometimes there may be mistakes in problem solving due to misunderstanding the issue, choosing a wrong concept or misapplied concept. The problem-solving test was carried out after students were given treatment on learning by using cooperative learning of TTW type. The purpose of this study was to elucidate student problem regarding to problem solving errors after learning by using cooperative learning of TTW type. Newman stages were used to identify problem solving errors in this study. The new research used a descriptive method to find out problem solving errors in students. The subject in this study were students of Vocational Senior High School (SMK) in 10th grade. Test and interview was conducted for data collection. Thus, the results of this study suggested problem solving errors in students after learning by using cooperative learning of TTW type for Newman stages.

Rejection Sensitivity and Depression: Indirect Effects Through Problem Solving.

PubMed

Kraines, Morganne A; Wells, Tony T

2017-01-01

Rejection sensitivity (RS) and deficits in social problem solving are risk factors for depression. Despite their relationship to depression and the potential connection between them, no studies have examined RS and social problem solving together in the context of depression. As such, we examined RS, five facets of social problem solving, and symptoms of depression in a young adult sample. A total of 180 participants completed measures of RS, social problem solving, and depressive symptoms. We used bootstrapping to examine the indirect effect of RS on depressive symptoms through problem solving. RS was positively associated with depressive symptoms. A negative problem orientation, impulsive/careless style, and avoidance style of social problem solving were positively associated with depressive symptoms, and a positive problem orientation was negatively associated with depressive symptoms. RS demonstrated an indirect effect on depressive symptoms through two social problem-solving facets: the tendency to view problems as threats to one's well-being and an avoidance problem-solving style characterized by procrastination, passivity, or overdependence on others. These results are consistent with prior research that found a positive association between RS and depression symptoms, but this is the first study to implicate specific problem-solving deficits in the relationship between RS and depression. Our results suggest that depressive symptoms in high RS individuals may result from viewing problems as threats and taking an avoidant, rather than proactive, approach to dealing with problems. These findings may have implications for problem-solving interventions for rejection sensitive individuals.

The Cyclic Nature of Problem Solving: An Emergent Multidimensional Problem-Solving Framework

ERIC Educational Resources Information Center

Carlson, Marilyn P.; Bloom, Irene

2005-01-01

This paper describes the problem-solving behaviors of 12 mathematicians as they completed four mathematical tasks. The emergent problem-solving framework draws on the large body of research, as grounded by and modified in response to our close observations of these mathematicians. The resulting "Multidimensional Problem-Solving Framework" has four…

Mathematical Problem Solving: A Review of the Literature.

ERIC Educational Resources Information Center

Funkhouser, Charles

The major perspectives on problem solving of the twentieth century are reviewed--associationism, Gestalt psychology, and cognitive science. The results of the review on teaching problem solving and the uses of computers to teach problem solving are included. Four major issues related to the teaching of problem solving are discussed: (1)…

Teaching Problem Solving Skills to Elementary Age Students with Autism

ERIC Educational Resources Information Center

Cote, Debra L.; Jones, Vita L.; Barnett, Crystal; Pavelek, Karin; Nguyen, Hoang; Sparks, Shannon L.

2014-01-01

Students with disabilities need problem-solving skills to promote their success in solving the problems of daily life. The research into problem-solving instruction has been limited for students with autism. Using a problem-solving intervention and the Self Determined Learning Model of Instruction, three elementary age students with autism were…

Learning problem-solving skills in a distance education physics course

NASA Astrophysics Data System (ADS)

Rampho, G. J.; Ramorola, M. Z.

2017-10-01

In this paper we present the results of a study on the effectiveness of combinations of delivery modes of distance education in learning problem-solving skills in a distance education introductory physics course. A problem-solving instruction with the explicit teaching of a problem-solving strategy and worked-out examples were implemented in the course. The study used the ex post facto research design with stratified sampling to investigate the effect of the learning of a problem-solving strategy on the problem-solving performance. The number of problems attempted and the mean frequency of using a strategy in solving problems in the three course presentation modes were compared. The finding of the study indicated that combining the different course presentation modes had no statistically significant effect in the learning of problem-solving skills in the distance education course.

Stabilisation of time-varying linear systems via Lyapunov differential equations

NASA Astrophysics Data System (ADS)

Zhou, Bin; Cai, Guang-Bin; Duan, Guang-Ren

2013-02-01

This article studies stabilisation problem for time-varying linear systems via state feedback. Two types of controllers are designed by utilising solutions to Lyapunov differential equations. The first type of feedback controllers involves the unique positive-definite solution to a parametric Lyapunov differential equation, which can be solved when either the state transition matrix of the open-loop system is exactly known, or the future information of the system matrices are accessible in advance. Different from the first class of controllers which may be difficult to implement in practice, the second type of controllers can be easily implemented by solving a state-dependent Lyapunov differential equation with a given positive-definite initial condition. In both cases, explicit conditions are obtained to guarantee the exponentially asymptotic stability of the associated closed-loop systems. Numerical examples show the effectiveness of the proposed approaches.

Structured background grids for generation of unstructured grids by advancing front method

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar

1991-01-01

A new method of background grid construction is introduced for generation of unstructured tetrahedral grids using the advancing-front technique. Unlike the conventional triangular/tetrahedral background grids which are difficult to construct and usually inadequate in performance, the new method exploits the simplicity of uniform Cartesian meshes and provides grids of better quality. The approach is analogous to solving a steady-state heat conduction problem with discrete heat sources. The spacing parameters of grid points are distributed over the nodes of a Cartesian background grid by interpolating from a few prescribed sources and solving a Poisson equation. To increase the control over the grid point distribution, a directional clustering approach is used. The new method is convenient to use and provides better grid quality and flexibility. Sample results are presented to demonstrate the power of the method.

Automated MAD and MIR structure solution

PubMed Central

Terwilliger, Thomas C.; Berendzen, Joel

1999-01-01

Obtaining an electron-density map from X-ray diffraction data can be difficult and time-consuming even after the data have been collected, largely because MIR and MAD structure determinations currently require many subjective evaluations of the qualities of trial heavy-atom partial structures before a correct heavy-atom solution is obtained. A set of criteria for evaluating the quality of heavy-atom partial solutions in macromolecular crystallography have been developed. These have allowed the conversion of the crystal structure-solution process into an optimization problem and have allowed its automation. The SOLVE software has been used to solve MAD data sets with as many as 52 selenium sites in the asymmetric unit. The automated structure-solution process developed is a major step towards the fully automated structure-determination, model-building and refinement procedure which is needed for genomic scale structure determinations. PMID:10089316

Economic aspects of rare diseases.

PubMed

Borski, Krzysztof

2015-01-01

Economic problems related to the prevention, diagnosis and treatment of rare diseases are presented paying particular attention to the costs of financing treatment, including the issue of its refund, which is a fundamental and difficult to solve economic problem of the health care system. Rare diseases, despite the low frequency of occurrence, together cover a large group of diseases being a serious medical, social and economic problem. The adoption of Polish National Plan for Rare Diseases resulting from the recommendations of the Council of the European Union, the extension of institutional activities related to the area of public health and social initiatives seeking innovative solutions to create a model of social support for patients and their families, with very high complexity of the issues regarding rare diseases, results in the need for a coherent, comprehensive, system operations and adoption of comprehensive solutions.

Collisional breakup in a quantum system of three charged particles

PubMed

Rescigno; Baertschy; Isaacs; McCurdy

1999-12-24

Since the invention of quantum mechanics, even the simplest example of the collisional breakup of a system of charged particles, e(-) + H --> H(+) + e(-) + e(-) (where e(-) is an electron and H is hydrogen), has resisted solution and is now one of the last unsolved fundamental problems in atomic physics. A complete solution requires calculation of the energies and directions for a final state in which all three particles are moving away from each other. Even with supercomputers, the correct mathematical description of this state has proved difficult to apply. A framework for solving ionization problems in many areas of chemistry and physics is finally provided by a mathematical transformation of the Schrodinger equation that makes the final state tractable, providing the key to a numerical solution of this problem that reveals its full dynamics.

Method for oil pipeline leak detection based on distributed fiber optic technology

NASA Astrophysics Data System (ADS)

Chen, Huabo; Tu, Yaqing; Luo, Ting

1998-08-01

Pipeline leak detection is a difficult problem to solve up to now. Some traditional leak detection methods have such problems as high rate of false alarm or missing detection, low location estimate capability. For the problems given above, a method for oil pipeline leak detection based on distributed optical fiber sensor with special coating is presented. The fiber's coating interacts with hydrocarbon molecules in oil, which alters the refractive indexed of the coating. Therefore the light-guiding properties of the fiber are modified. Thus pipeline leak location can be determined by OTDR. Oil pipeline lead detection system is designed based on the principle. The system has some features like real time, multi-point detection at the same time and high location accuracy. In the end, some factors that probably influence detection are analyzed and primary improving actions are given.

3D reconstruction of highly fragmented bone fractures

NASA Astrophysics Data System (ADS)

Willis, Andrew; Anderson, Donald; Thomas, Thad; Brown, Thomas; Marsh, J. Lawrence

2007-03-01

A system for the semi-automatic reconstruction of highly fragmented bone fractures, developed to aid in treatment planning, is presented. The system aligns bone fragment surfaces derived from segmentation of volumetric CT scan data. Each fragment surface is partitioned into intact- and fracture-surfaces, corresponding more or less to cortical and cancellous bone, respectively. A user then interactively selects fracture-surface patches in pairs that coarsely correspond. A final optimization step is performed automatically to solve the N-body rigid alignment problem. The work represents the first example of a 3D bone fracture reconstruction system and addresses two new problems unique to the reconstruction of fractured bones: (1) non-stationary noise inherent in surfaces generated from a difficult segmentation problem and (2) the possibility that a single fracture surface on a fragment may correspond to many other fragments.

Optimal routing of IP packets to multi-homed servers

NASA Astrophysics Data System (ADS)

Swartz, K. L.

1992-08-01

Multi-homing, or direct attachment to multiple networks, offers both performance and availability benefits for important servers on busy networks. Exploiting these benefits to their fullest requires a modicum of routing knowledge in the clients. Careful policy control must also be reflected in the routing used within the network to make best use of specialized and often scarce resources. While relatively straightforward in theory, this problem becomes much more difficult to solve in a real network containing often intractable implementations from a variety of vendors. This paper presents an analysis of the problem and proposes a useful solution for a typical campus network. Application of this solution at the Stanford Linear Accelerator Center is studied and the problems and pitfalls encountered are discussed, as are the workarounds used to make the system work in the real world.

Airplane detection based on fusion framework by combining saliency model with Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Dou, Hao; Sun, Xiao; Li, Bin; Deng, Qianqian; Yang, Xubo; Liu, Di; Tian, Jinwen

2018-03-01

Aircraft detection from very high resolution remote sensing images, has gained more increasing interest in recent years due to the successful civil and military applications. However, several problems still exist: 1) how to extract the high-level features of aircraft; 2) locating objects within such a large image is difficult and time consuming; 3) A common problem of multiple resolutions of satellite images still exists. In this paper, inspirited by biological visual mechanism, the fusion detection framework is proposed, which fusing the top-down visual mechanism (deep CNN model) and bottom-up visual mechanism (GBVS) to detect aircraft. Besides, we use multi-scale training method for deep CNN model to solve the problem of multiple resolutions. Experimental results demonstrate that our method can achieve a better detection result than the other methods.

Anodal transcranial direct current stimulation of the right anterior temporal lobe did not significantly affect verbal insight.

PubMed

Aihara, Takatsugu; Ogawa, Takeshi; Shimokawa, Takeaki; Yamashita, Okito

2017-01-01

Humans often utilize past experience to solve difficult problems. However, if past experience is insufficient to solve a problem, solvers may reach an impasse. Insight can be valuable for breaking an impasse, enabling the reinterpretation or re-representation of a problem. Previous studies using between-subjects designs have revealed a causal relationship between the anterior temporal lobes (ATLs) and non-verbal insight, by enhancing the right ATL while inhibiting the left ATL using transcranial direct current stimulation (tDCS). In addition, neuroimaging studies have reported a correlation between right ATL activity and verbal insight. Based on these findings, we hypothesized that the right ATL is causally related to both non-verbal and verbal insight. To test this hypothesis, we conducted an experiment with 66 subjects using a within-subjects design, which typically has greater statistical power than a between-subjects design. Subjects participated in tDCS experiments across 2 days, in which they solved both non-verbal and verbal insight problems under active or sham stimulation conditions. To dissociate the effects of right ATL stimulation from those of left ATL stimulation, we used two montage types; anodal tDCS of the right ATL together with cathodal tDCS of the left ATL (stimulating both ATLs) and anodal tDCS of the right ATL with cathodal tDCS of the left cheek (stimulating only the right ATL). The montage used was counterbalanced across subjects. Statistical analyses revealed that, regardless of the montage type, there were no significant differences between the active and sham conditions for either verbal or non-verbal insight, although the finding for non-verbal insight was inconclusive because of a lack of statistical power. These results failed to support previous findings suggesting that the right ATL is the central locus of insight.

Exact algorithms for haplotype assembly from whole-genome sequence data.

PubMed

Chen, Zhi-Zhong; Deng, Fei; Wang, Lusheng

2013-08-15

Haplotypes play a crucial role in genetic analysis and have many applications such as gene disease diagnoses, association studies, ancestry inference and so forth. The development of DNA sequencing technologies makes it possible to obtain haplotypes from a set of aligned reads originated from both copies of a chromosome of a single individual. This approach is often known as haplotype assembly. Exact algorithms that can give optimal solutions to the haplotype assembly problem are highly demanded. Unfortunately, previous algorithms for this problem either fail to output optimal solutions or take too long time even executed on a PC cluster. We develop an approach to finding optimal solutions for the haplotype assembly problem under the minimum-error-correction (MEC) model. Most of the previous approaches assume that the columns in the input matrix correspond to (putative) heterozygous sites. This all-heterozygous assumption is correct for most columns, but it may be incorrect for a small number of columns. In this article, we consider the MEC model with or without the all-heterozygous assumption. In our approach, we first use new methods to decompose the input read matrix into small independent blocks and then model the problem for each block as an integer linear programming problem, which is then solved by an integer linear programming solver. We have tested our program on a single PC [a Linux (x64) desktop PC with i7-3960X CPU], using the filtered HuRef and the NA 12878 datasets (after applying some variant calling methods). With the all-heterozygous assumption, our approach can optimally solve the whole HuRef data set within a total time of 31 h (26 h for the most difficult block of the 15th chromosome and only 5 h for the other blocks). To our knowledge, this is the first time that MEC optimal solutions are completely obtained for the filtered HuRef dataset. Moreover, in the general case (without the all-heterozygous assumption), for the HuRef dataset our approach can optimally solve all the chromosomes except the most difficult block in chromosome 15 within a total time of 12 days. For both of the HuRef and NA12878 datasets, the optimal costs in the general case are sometimes much smaller than those in the all-heterozygous case. This implies that some columns in the input matrix (after applying certain variant calling methods) still correspond to false-heterozygous sites. Our program, the optimal solutions found for the HuRef dataset available at http://rnc.r.dendai.ac.jp/hapAssembly.html.

The Association between Motivation, Affect, and Self-regulated Learning When Solving Problems

PubMed Central

Baars, Martine; Wijnia, Lisette; Paas, Fred

2017-01-01

Self-regulated learning (SRL) skills are essential for learning during school years, particularly in complex problem-solving domains, such as biology and math. Although a lot of studies have focused on the cognitive resources that are needed for learning to solve problems in a self-regulated way, affective and motivational resources have received much less research attention. The current study investigated the relation between affect (i.e., Positive Affect and Negative Affect Scale), motivation (i.e., autonomous and controlled motivation), mental effort, SRL skills, and problem-solving performance when learning to solve biology problems in a self-regulated online learning environment. In the learning phase, secondary education students studied video-modeling examples of how to solve hereditary problems, solved hereditary problems which they chose themselves from a set of problems with different complexity levels (i.e., five levels). In the posttest, students solved hereditary problems, self-assessed their performance, and chose a next problem from the set of problems but did not solve these problems. The results from this study showed that negative affect, inaccurate self-assessments during the posttest, and higher perceptions of mental effort during the posttest were negatively associated with problem-solving performance after learning in a self-regulated way. PMID:28848467

An experience sampling study of learning, affect, and the demands control support model.

PubMed

Daniels, Kevin; Boocock, Grahame; Glover, Jane; Holland, Julie; Hartley, Ruth

2009-07-01

The demands control support model (R. A. Karasek & T. Theorell, 1990) indicates that job control and social support enable workers to engage in problem solving. In turn, problem solving is thought to influence learning and well-being (e.g., anxious affect, activated pleasant affect). Two samples (N = 78, N = 106) provided data up to 4 times per day for up to 5 working days. The extent to which job control was used for problem solving was assessed by measuring the extent to which participants changed aspects of their work activities to solve problems. The extent to which social support was used to solve problems was assessed by measuring the extent to which participants discussed problems to solve problems. Learning mediated the relationship between changing aspects of work activities to solve problems and activated pleasant affect. Learning also mediated the relationship between discussing problems to solve problems and activated pleasant affect. The findings indicated that how individuals use control and support to respond to problem-solving demands is associated with organizational and individual phenomena, such as learning and affective well-being.

What Does (and Doesn't) Make Analogical Problem Solving Easy? A Complexity-Theoretic Perspective

ERIC Educational Resources Information Center

Wareham, Todd; Evans, Patricia; van Rooij, Iris

2011-01-01

Solving new problems can be made easier if one can build on experiences with other problems one has already successfully solved. The ability to exploit earlier problem-solving experiences in solving new problems seems to require several cognitive sub-abilities. Minimally, one needs to be able to retrieve relevant knowledge of earlier solved…

Synthesizing Huber's Problem Solving and Kolb's Learning Cycle: A Balanced Approach to Technical Problem Solving

ERIC Educational Resources Information Center

Kamis, Arnold; Khan, Beverly K.

2009-01-01

How do we model and improve technical problem solving, such as network subnetting? This paper reports an experimental study that tested several hypotheses derived from Kolb's experiential learning cycle and Huber's problem solving model. As subjects solved a network subnetting problem, they mapped their mental processes according to Huber's…

Generalization of Social Skills: Strategies and Results of a Training Program in Problem Solving Skills.

ERIC Educational Resources Information Center

Paraschiv, Irina; Olley, J. Gregory

This paper describes the "Problem Solving for Life" training program which trains adolescents and adults with mental retardation in skills for solving social problems. The program requires group participants to solve social problems by practicing two prerequisite skills (relaxation and positive self-statements) and four problem solving steps: (1)…

Young Children's Analogical Problem Solving: Gaining Insights from Video Displays

ERIC Educational Resources Information Center

Chen, Zhe; Siegler, Robert S.

2013-01-01

This study examined how toddlers gain insights from source video displays and use the insights to solve analogous problems. Two- to 2.5-year-olds viewed a source video illustrating a problem-solving strategy and then attempted to solve analogous problems. Older but not younger toddlers extracted the problem-solving strategy depicted in the video…

Investigating Problem-Solving Perseverance Using Lesson Study

ERIC Educational Resources Information Center

Bieda, Kristen N.; Huhn, Craig

2017-01-01

Problem solving has long been a focus of research and curriculum reform (Kilpatrick 1985; Lester 1994; NCTM 1989, 2000; CCSSI 2010). The importance of problem solving is not new, but the Common Core introduced the idea of making sense of problems and persevering in solving them (CCSSI 2010, p. 6) as an aspect of problem solving. Perseverance is…

[The historical experience of medical service in cooperation with state healthcare facilities during the Great Patriotic War 1941-1945].

PubMed

Budko, A A; Gribovskaia, G A; Zhuravlev, D A

2014-05-01

Cooperation issues between military-medical service and civil healthcare in the field of delivery of medical aid to patients in the rear of country are considered in the artic. The rear is a final stage of the care by echelon and the main medical reserve force for front and army areas. Wide hospital network in the rear consisted mainly of evacuation hospitals of the People's Commissariat of the USSR healthcare. Cooperation between military-medical service and civil healthcare facilities was required. Sometimes necessary cooperation failed and made mutual helming of evacuation hospitals difficult. But despite the problems the main problem - return of maximum wounded soldiers to active duty was solved during the Great Patriotic War.

Health providers' opinions on provider-client relations: results of a multi-country study to test Health Workers for Change.

PubMed

Fonn, S; Mtonga, A S; Nkoloma, H C; Bantebya Kyomuhendo, G; daSilva, L; Kazilimani, E; Davis, S; Dia, R

2001-09-01

A multi-centre study in four African countries was undertaken to test the acceptability and effectiveness of Health Workers for Change, a methodology to explore provider-client relations within a gender-sensitive context. This intervention addresses the interpersonal component of quality of care. The methodology, consisting of six workshops, was implemented by research teams in Zambia, Senegal, Mozambique and Uganda. It was found to be acceptable within in a range of cultural and primary health care settings. The workshops allowed difficult issues such as prejudice and bribery to be discussed openly, fostered problem solving and the development of practical plans to address problems that could strengthen district health systems.

Distributed computation: the new wave of synthetic biology devices.

PubMed

Macía, Javier; Posas, Francesc; Solé, Ricard V

2012-06-01

Synthetic biology (SB) offers a unique opportunity for designing complex molecular circuits able to perform predefined functions. But the goal of achieving a flexible toolbox of reusable molecular components has been shown to be limited due to circuit unpredictability, incompatible parts or random fluctuations. Many of these problems arise from the challenges posed by engineering the molecular circuitry: multiple wires are usually difficult to implement reliably within one cell and the resulting systems cannot be reused in other modules. These problems are solved by means of a nonstandard approach to single cell devices, using cell consortia and allowing the output signal to be distributed among different cell types, which can be combined in multiple, reusable and scalable ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

Problem-solving deficits in Iranian people with borderline personality disorder.

PubMed

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

2014-01-01

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. 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. 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. 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.

Impulsivity as a mediator in the relationship between problem solving and suicidal ideation.

PubMed

Gonzalez, Vivian M; Neander, Lucía L

2018-03-15

This study examined whether three facets of impulsivity previously shown to be associated with suicidal ideation and attempts (negative urgency, lack of premeditation, and lack of perseverance) help to account for the established association between problem solving deficits and suicidal ideation. Emerging adult college student drinkers with a history of at least passive suicidal ideation (N = 387) completed measures of problem solving, impulsivity, and suicidal ideation. A path analysis was conducted to examine the mediating role of impulsivity variables in the association between problem solving (rational problem solving, positive and negative problem orientation, and avoidance style) and suicidal ideation. Direct and indirect associations through impulsivity, particularly negative urgency, were found between problem solving and severity of suicidal ideation. Interventions aimed at teaching problem solving skills, as well as self-efficacy and optimism for solving life problems, may help to reduce impulsivity and suicidal ideation. © 2018 Wiley Periodicals, Inc.

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

NASA Astrophysics Data System (ADS)

de Siqueira, Alexandre Fioravante; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Tello Saenz, Carlos Alberto; Job, Aldo Eloizo

2014-08-01

Manual identification of fission tracks has practical problems, such as variation due to observe-observation efficiency. An automatic processing method that could identify fission tracks in a photomicrograph could solve this problem and improve the speed of track counting. However, separation of nontrivial images is one of the most difficult tasks in image processing. Several commercial and free softwares are available, but these softwares are meant to be used in specific images. In this paper, an automatic method based on starlet wavelets is presented in order to separate fission tracks in mineral photomicrographs. Automatization is obtained by the Matthews correlation coefficient, and results are evaluated by precision, recall and accuracy. This technique is an improvement of a method aimed at segmentation of scanning electron microscopy images. This method is applied in photomicrographs of epidote phenocrystals, in which accuracy higher than 89% was obtained in fission track segmentation, even for difficult images. Algorithms corresponding to the proposed method are available for download. Using the method presented here, a user could easily determine fission tracks in photomicrographs of mineral samples.

Gender and rapid alterations of hemispheric dominance during planning.

PubMed

Schuepbach, Daniel; Skotchko, Tatjana; Duschek, Stefan; Theodoridou, Anastasia; Grimm, Simone; Boeker, Heinz; Seifritz, Erich

2012-01-01

Mental planning and carrying out a plan provoke specific cerebral hemodynamic responses. Gender aspects of hemispheric laterality using rapid cerebral hemodynamics have not been reported. Here, we applied functional transcranial Doppler sonography to examine lateralization of cerebral hemodynamics of the middle cerebral arteries of 28 subjects (14 women and 14 men) performing a standard planning task. There were easy and difficult problems, and mental planning without motor activity was separated from movement execution. Difficult mental planning elicited lateralization to the right hemisphere after 2 or more seconds, a feature that was not observed during movement execution. In females, there was a dominance to the left hemisphere during movement execution. Optimized problem solving yielded an increased laterality change to the right during mental planning. Gender-related hemispheric dominance appears to be condition-dependent, and change of laterality to the right may play a role in optimized performance. Results are of relevance when considering laterality from a perspective of performance enhancement of higher cognitive functions, and also of psychiatric disorders with cognitive dysfunctions and abnormal lateralization patterns such as schizophrenia. Copyright © 2012 S. Karger AG, Basel.

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

Trędak, Przemysław, E-mail: przemyslaw.tredak@fuw.edu.pl; Rudnicki, Witold R.; Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, ul. Pawińskiego 5a, 02-106 Warsaw

The second generation Reactive Bond Order (REBO) empirical potential is commonly used to accurately model a wide range hydrocarbon materials. It is also extensible to other atom types and interactions. REBO potential assumes complex multi-body interaction model, that is difficult to represent efficiently in the SIMD or SIMT programming model. Hence, despite its importance, no efficient GPGPU implementation has been developed for this potential. Here we present a detailed description of a highly efficient GPGPU implementation of molecular dynamics algorithm using REBO potential. The presented algorithm takes advantage of rarely used properties of the SIMT architecture of a modern GPUmore » to solve difficult synchronizations issues that arise in computations of multi-body potential. Techniques developed for this problem may be also used to achieve efficient solutions of different problems. The performance of proposed algorithm is assessed using a range of model systems. It is compared to highly optimized CPU implementation (both single core and OpenMP) available in LAMMPS package. These experiments show up to 6x improvement in forces computation time using single processor of the NVIDIA Tesla K80 compared to high end 16-core Intel Xeon processor.« less

Improving mathematical problem solving skills through visual media

NASA Astrophysics Data System (ADS)

Widodo, S. A.; Darhim; Ikhwanudin, T.

2018-01-01

The purpose of this article was to find out the enhancement of students’ mathematical problem solving by using visual learning media. The ability to solve mathematical problems is the ability possessed by students to solve problems encountered, one of the problem-solving model of Polya. This preliminary study was not to make a model, but it only took a conceptual approach by comparing the various literature of problem-solving skills by linking visual learning media. The results of the study indicated that the use of learning media had not been appropriated so that the ability to solve mathematical problems was not optimal. The inappropriateness of media use was due to the instructional media that was not adapted to the characteristics of the learners. Suggestions that can be given is the need to develop visual media to increase the ability to solve problems.

The neural bases of the multiplication problem-size effect across countries

PubMed Central

Prado, Jérôme; Lu, Jiayan; Liu, Li; Dong, Qi; Zhou, Xinlin; Booth, James R.

2013-01-01

Multiplication problems involving large numbers (e.g., 9 × 8) are more difficult to solve than problems involving small numbers (e.g., 2 × 3). Behavioral research indicates that this problem-size effect might be due to different factors across countries and educational systems. However, there is no neuroimaging evidence supporting this hypothesis. Here, we compared the neural correlates of the multiplication problem-size effect in adults educated in China and the United States. We found a greater neural problem-size effect in Chinese than American participants in bilateral superior temporal regions associated with phonological processing. However, we found a greater neural problem-size effect in American than Chinese participants in right intra-parietal sulcus (IPS) associated with calculation procedures. Therefore, while the multiplication problem-size effect might be a verbal retrieval effect in Chinese as compared to American participants, it may instead stem from the use of calculation procedures in American as compared to Chinese participants. Our results indicate that differences in educational practices might affect the neural bases of symbolic arithmetic. PMID:23717274

The Relationship between Students' Problem Posing and Problem Solving Abilities and Beliefs: A Small-Scale Study with Chinese Elementary School Children

ERIC Educational Resources Information Center

Limin, Chen; Van Dooren, Wim; Verschaffel, Lieven

2013-01-01

The goal of the present study is to investigate the relationship between pupils' problem posing and problem solving abilities, their beliefs about problem posing and problem solving, and their general mathematics abilities, in a Chinese context. Five instruments, i.e., a problem posing test, a problem solving test, a problem posing questionnaire,…

An Investigation of the Effects on Students' Attitudes, Beliefs, and Abilities in Problem Solving and Mathematics after One Year of a Systematic Approach to the Learning of Problem Solving.

ERIC Educational Resources Information Center

Higgins, Karen M.

This study investigated the effects of Oregon's Lane County "Problem Solving in Mathematics" (PSM) materials on middle-school students' attitudes, beliefs, and abilities in problem solving and mathematics. The instructional approach advocated in PSM includes: the direct teaching of five problem-solving skills, weekly challenge problems,…

Flow Navigation by Smart Microswimmers via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Colabrese, Simona; Biferale, Luca; Celani, Antonio; Gustavsson, Kristian

2017-11-01

We have numerically modeled active particles which are able to acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. We show that those swimmers can learn effective strategies just by experience, using a reinforcement learning algorithm. As an example, we focus on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, exploiting the underlying flow whenever possible. The reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This work paves the way towards the engineering of smart microswimmers that solve difficult navigation problems. ERC AdG NewTURB 339032.

Computational complexity of ecological and evolutionary spatial dynamics

PubMed Central

Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

2015-01-01

There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

Evidence-based ergonomics: a model and conceptual structure proposal.

PubMed

Silveira, Dierci Marcio

2012-01-01

In Human Factors and Ergonomics Science (HFES), it is difficult to identify what is the best approach to tackle the workplace and systems design problems which needs to be solved, and it has been also advocated as transdisciplinary and multidisciplinary the issue of "How to solve the human factors and ergonomics problems that are identified?". The proposition on this study is to combine the theoretical approach for Sustainability Science, the Taxonomy of the Human Factors and Ergonomics (HFE) discipline and the framework for Evidence-Based Medicine in an attempt to be applied in Human Factors and Ergonomics. Applications of ontologies are known in the field of medical research and computer science. By scrutinizing the key requirements for the HFES structuring of knowledge, it was designed a reference model, First, it was identified the important requirements for HFES Concept structuring, as regarded by Meister. Second, it was developed an evidence-based ergonomics framework as a reference model composed of six levels based on these requirements. Third, it was devised a mapping tool using linguistic resources to translate human work, systems environment and the complexities inherent to their hierarchical relationships to support future development at Level 2 of the reference model and for meeting the two major challenges for HFES, namely, identifying what problems should be addressed in HFE as an Autonomous Science itself and proposing solutions by integrating concepts and methods applied in HFES for those problems.

Student’s scheme in solving mathematics problems

NASA Astrophysics Data System (ADS)

Setyaningsih, Nining; Juniati, Dwi; Suwarsono

2018-03-01

The purpose of this study was to investigate students’ scheme in solving mathematics problems. Scheme are data structures for representing the concepts stored in memory. In this study, we used it in solving mathematics problems, especially ratio and proportion topics. Scheme is related to problem solving that assumes that a system is developed in the human mind by acquiring a structure in which problem solving procedures are integrated with some concepts. The data were collected by interview and students’ written works. The results of this study revealed are students’ scheme in solving the problem of ratio and proportion as follows: (1) the content scheme, where students can describe the selected components of the problem according to their prior knowledge, (2) the formal scheme, where students can explain in construct a mental model based on components that have been selected from the problem and can use existing schemes to build planning steps, create something that will be used to solve problems and (3) the language scheme, where students can identify terms, or symbols of the components of the problem.Therefore, by using the different strategies to solve the problems, the students’ scheme in solving the ratio and proportion problems will also differ.

Factors of Problem-Solving Competency in a Virtual Chemistry Environment: The Role of Metacognitive Knowledge about Strategies

ERIC Educational Resources Information Center

Scherer, Ronny; Tiemann, Rudiger

2012-01-01

The ability to solve complex scientific problems is regarded as one of the key competencies in science education. Until now, research on problem solving focused on the relationship between analytical and complex problem solving, but rarely took into account the structure of problem-solving processes and metacognitive aspects. This paper,…

Same Old Problem, New Name? Alerting Students to the Nature of the Problem-Solving Process

ERIC Educational Resources Information Center

Yerushalmi, Edit; Magen, Esther

2006-01-01

Students frequently misconceive the process of problem-solving, expecting the linear process required for solving an exercise, rather than the convoluted search process required to solve a genuine problem. In this paper we present an activity designed to foster in students realization and appreciation of the nature of the problem-solving process,…

The Problem-Solving Process in Physics as Observed When Engineering Students at University Level Work in Groups

ERIC Educational Resources Information Center

Gustafsson, Peter; Jonsson, Gunnar; Enghag, Margareta

2015-01-01

The problem-solving process is investigated for five groups of students when solving context-rich problems in an introductory physics course included in an engineering programme. Through transcripts of their conversation, the paths in the problem-solving process have been traced and related to a general problem-solving model. All groups exhibit…

Asymmetry in search.

PubMed

Kaindl, H; Kainz, G; Radda, K

2001-01-01

Most of the work on search in artificial intelligence (AI) deals with one search direction only-mostly forward search-although it is known that a structural asymmetry of the search graph causes differences in the efficiency of searching in the forward or the backward direction, respectively. In the case of symmetrical graph structure, however, current theory would not predict such differences in efficiency. In several classes of job sequencing problems, we observed a phenomenon of asymmetry in search that relates to the distribution of the are costs in the search graph. This phenomenon can be utilized for improving the search efficiency by a new algorithm that automatically selects the search direction. We demonstrate fur a class of job sequencing problems that, through the utilization of this phenomenon, much more difficult problems can be solved-according to our best knowledge-than by the best published approach, and on the same problems, the running time is much reduced. As a consequence, we propose to check given problems for asymmetrical distribution of are costs that may cause asymmetry in search.

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.

Genetic influences on insight problem solving: the role of catechol-O-methyltransferase (COMT) gene polymorphisms

PubMed Central

Jiang, Weili; Shang, Siyuan; Su, Yanjie

2015-01-01

People may experience an “aha” moment, when suddenly realizing a solution of a puzzling problem. This experience is called insight problem solving. Several findings suggest that catecholamine-related genes may contribute to insight problem solving, among which the catechol-O-methyltransferase (COMT) gene is the most promising candidate. The current study examined 753 healthy individuals to determine the associations between 7 candidate single nucleotide polymorphisms on the COMT gene and insight problem-solving performance, while considering gender differences. The results showed that individuals carrying A allele of rs4680 or T allele of rs4633 scored significantly higher on insight problem-solving tasks, and the COMT gene rs5993883 combined with gender interacted with correct solutions of insight problems, specifically showing that this gene only influenced insight problem-solving performance in males. This study presents the first investigation of the genetic impact on insight problem solving and provides evidence that highlights the role that the COMT gene plays in insight problem solving. PMID:26528222

Genetic influences on insight problem solving: the role of catechol-O-methyltransferase (COMT) gene polymorphisms.

PubMed

Jiang, Weili; Shang, Siyuan; Su, Yanjie

2015-01-01

People may experience an "aha" moment, when suddenly realizing a solution of a puzzling problem. This experience is called insight problem solving. Several findings suggest that catecholamine-related genes may contribute to insight problem solving, among which the catechol-O-methyltransferase (COMT) gene is the most promising candidate. The current study examined 753 healthy individuals to determine the associations between 7 candidate single nucleotide polymorphisms on the COMT gene and insight problem-solving performance, while considering gender differences. The results showed that individuals carrying A allele of rs4680 or T allele of rs4633 scored significantly higher on insight problem-solving tasks, and the COMT gene rs5993883 combined with gender interacted with correct solutions of insight problems, specifically showing that this gene only influenced insight problem-solving performance in males. This study presents the first investigation of the genetic impact on insight problem solving and provides evidence that highlights the role that the COMT gene plays in insight problem solving.

Understanding Undergraduates’ Problem-Solving Processes †

PubMed Central

Nehm, Ross H.

2010-01-01

Fostering effective problem-solving skills is one of the most longstanding and widely agreed upon goals of biology education. Nevertheless, undergraduate biology educators have yet to leverage many major findings about problem-solving processes from the educational and cognitive science research literatures. This article highlights key facets of problem-solving processes and introduces methodologies that may be used to reveal how undergraduate students perceive and represent biological problems. Overall, successful problem-solving entails a keen sensitivity to problem contexts, disciplined internal representation or modeling of the problem, and the principled management and deployment of cognitive resources. Context recognition tasks, problem representation practice, and cognitive resource management receive remarkably little emphasis in the biology curriculum, despite their central roles in problem-solving success. PMID:23653710

An Automated Method to Compute Orbital Re-entry Trajectories with Heating Constraints

NASA Technical Reports Server (NTRS)

Zimmerman, Curtis; Dukeman, Greg; Hanson, John; Fogle, Frank R. (Technical Monitor)

2002-01-01

Determining how to properly manipulate the controls of a re-entering re-usable launch vehicle (RLV) so that it is able to safely return to Earth and land involves the solution of a two-point boundary value problem (TPBVP). This problem, which can be quite difficult, is traditionally solved on the ground prior to flight. If necessary, a nearly unlimited amount of time is available to find the 'best' solution using a variety of trajectory design and optimization tools. The role of entry guidance during flight is to follow the pre- determined reference solution while correcting for any errors encountered along the way. This guidance method is both highly reliable and very efficient in terms of onboard computer resources. There is a growing interest in a style of entry guidance that places the responsibility of solving the TPBVP in the actual entry guidance flight software. Here there is very limited computer time. The powerful, but finicky, mathematical tools used by trajectory designers on the ground cannot in general be converted to do the job. Non-convergence or slow convergence can result in disaster. The challenges of designing such an algorithm are numerous and difficult. Yet the payoff (in the form of decreased operational costs and increased safety) can be substantiaL This paper presents an algorithm that incorporates features of both types of guidance strategies. It takes an initial RLV orbital re-entry state and finds a trajectory that will safely transport the vehicle to Earth. During actual flight, the computed trajectory is used as the reference to be flown by a more traditional guidance method.

Thinking Process of Naive Problem Solvers to Solve Mathematical Problems

ERIC Educational Resources Information Center

Mairing, Jackson Pasini

2017-01-01

Solving problems is not only a goal of mathematical learning. Students acquire ways of thinking, habits of persistence and curiosity, and confidence in unfamiliar situations by learning to solve problems. In fact, there were students who had difficulty in solving problems. The students were naive problem solvers. This research aimed to describe…

Teaching Problem Solving without Modeling through "Thinking Aloud Pair Problem Solving."

ERIC Educational Resources Information Center

Pestel, Beverly C.

1993-01-01

Reviews research relevant to the problem of unsatisfactory student problem-solving abilities and suggests a teaching strategy that addresses the issue. Author explains how she uses teaching aloud problem solving (TAPS) in college chemistry and presents evaluation data. Among the findings are that the TAPS class got fewer problems completely right,…

Social Problem Solving, Conduct Problems, and Callous-Unemotional Traits in Children

ERIC Educational Resources Information Center

Waschbusch, Daniel A.; Walsh, Trudi M.; Andrade, Brendan F.; King, Sara; Carrey, Normand J.

2007-01-01

This study examined the association between social problem solving, conduct problems (CP), and callous-unemotional (CU) traits in elementary age children. Participants were 53 children (40 boys and 13 girls) aged 7-12 years. Social problem solving was evaluated using the Social Problem Solving Test-Revised, which requires children to produce…

Algebraic multigrid preconditioners for two-phase flow in porous media with phase transitions

NASA Astrophysics Data System (ADS)

Bui, Quan M.; Wang, Lu; Osei-Kuffuor, Daniel

2018-04-01

Multiphase flow is a critical process in a wide range of applications, including oil and gas recovery, carbon sequestration, and contaminant remediation. Numerical simulation of multiphase flow requires solving of a large, sparse linear system resulting from the discretization of the partial differential equations modeling the flow. In the case of multiphase multicomponent flow with miscible effect, this is a very challenging task. The problem becomes even more difficult if phase transitions are taken into account. A new approach to handle phase transitions is to formulate the system as a nonlinear complementarity problem (NCP). Unlike in the primary variable switching technique, the set of primary variables in this approach is fixed even when there is phase transition. Not only does this improve the robustness of the nonlinear solver, it opens up the possibility to use multigrid methods to solve the resulting linear system. The disadvantage of the complementarity approach, however, is that when a phase disappears, the linear system has the structure of a saddle point problem and becomes indefinite, and current algebraic multigrid (AMG) algorithms cannot be applied directly. In this study, we explore the effectiveness of a new multilevel strategy, based on the multigrid reduction technique, to deal with problems of this type. We demonstrate the effectiveness of the method through numerical results for the case of two-phase, two-component flow with phase appearance/disappearance. We also show that the strategy is efficient and scales optimally with problem size.

Automatic Combination of Operators in a Genetic Algorithm to Solve the Traveling Salesman Problem.

PubMed

Contreras-Bolton, Carlos; Parada, Victor

2015-01-01

Genetic algorithms are powerful search methods inspired by Darwinian evolution. To date, they have been applied to the solution of many optimization problems because of the easy use of their properties and their robustness in finding good solutions to difficult problems. The good operation of genetic algorithms is due in part to its two main variation operators, namely, crossover and mutation operators. Typically, in the literature, we find the use of a single crossover and mutation operator. However, there are studies that have shown that using multi-operators produces synergy and that the operators are mutually complementary. Using multi-operators is not a simple task because which operators to use and how to combine them must be determined, which in itself is an optimization problem. In this paper, it is proposed that the task of exploring the different combinations of the crossover and mutation operators can be carried out by evolutionary computing. The crossover and mutation operators used are those typically used for solving the traveling salesman problem. The process of searching for good combinations was effective, yielding appropriate and synergic combinations of the crossover and mutation operators. The numerical results show that the use of the combination of operators obtained by evolutionary computing is better than the use of a single operator and the use of multi-operators combined in the standard way. The results were also better than those of the last operators reported in the literature.

Automatic Combination of Operators in a Genetic Algorithm to Solve the Traveling Salesman Problem

PubMed Central

2015-01-01

Genetic algorithms are powerful search methods inspired by Darwinian evolution. To date, they have been applied to the solution of many optimization problems because of the easy use of their properties and their robustness in finding good solutions to difficult problems. The good operation of genetic algorithms is due in part to its two main variation operators, namely, crossover and mutation operators. Typically, in the literature, we find the use of a single crossover and mutation operator. However, there are studies that have shown that using multi-operators produces synergy and that the operators are mutually complementary. Using multi-operators is not a simple task because which operators to use and how to combine them must be determined, which in itself is an optimization problem. In this paper, it is proposed that the task of exploring the different combinations of the crossover and mutation operators can be carried out by evolutionary computing. The crossover and mutation operators used are those typically used for solving the traveling salesman problem. The process of searching for good combinations was effective, yielding appropriate and synergic combinations of the crossover and mutation operators. The numerical results show that the use of the combination of operators obtained by evolutionary computing is better than the use of a single operator and the use of multi-operators combined in the standard way. The results were also better than those of the last operators reported in the literature. PMID:26367182