Working Memory, Attention, and Mathematical Problem Solving: A Longitudinal Study of Elementary School Children

ERIC Educational Resources Information Center

Swanson, H. Lee

2011-01-01

The role of working memory (WM) in children's growth in mathematical problem solving was examined in a longitudinal study of children (N = 127). A battery of tests was administered that assessed problem solving, achievement, WM, and cognitive processing (inhibition, speed, phonological coding) in Grade 1 children, with follow-up testing in Grades…

Organizational/Memory Tools: A Technique for Improving Problem Solving Skills.

ERIC Educational Resources Information Center

Steinberg, Esther R.; And Others

1986-01-01

This study was conducted to determine whether students would use a computer-presented organizational/memory tool as an aid in problem solving, and whether and how locus of control would affect tool use and problem-solving performance. Learners did use the tools, which were most effective in the learner control with feedback condition. (MBR)

After Being Challenged by a Video Game Problem, Sleep Increases the Chance to Solve It

PubMed Central

Beijamini, Felipe; Pereira, Sofia Isabel Ribeiro; Cini, Felipe Augusto; Louzada, Fernando Mazzilli

2014-01-01

In the past years many studies have demonstrated the role of sleep on memory consolidation. It is known that sleeping after learning a declarative or non-declarative task, is better than remaining awake. Furthermore, there are reports of a possible role for dreams in consolidation of declarative memories. Other studies have reported the effect of naps on memory consolidation. With similar protocols, another set of studies indicated that sleep has a role in creativity and problem-solving. Here we hypothesised that sleep can increase the likelihood of solving problems. After struggling to solve a video game problem, subjects who took a nap (n = 14) were almost twice as likely to solve it when compared to the wake control group (n = 15). It is interesting to note that, in the nap group 9 out 14 subjects engaged in slow-wave sleep (SWS) and all solved the problem. Surprisingly, we did not find a significant involvement of Rapid Eye Movement (REM) sleep in this task. Slow-wave sleep is believed to be crucial for the transfer of memory-related information to the neocortex and implement intentions. Sleep can benefit problem-solving through the generalisation of newly encoded information and abstraction of the gist. In conclusion, our results indicate that sleep, even a nap, can potentiate the solution of problems that involve logical reasoning. Thus, sleep's function seems to go beyond memory consolidation to include managing of everyday-life events. PMID:24416219

After being challenged by a video game problem, sleep increases the chance to solve it.

PubMed

Beijamini, Felipe; Pereira, Sofia Isabel Ribeiro; Cini, Felipe Augusto; Louzada, Fernando Mazzilli

2014-01-01

In the past years many studies have demonstrated the role of sleep on memory consolidation. It is known that sleeping after learning a declarative or non-declarative task, is better than remaining awake. Furthermore, there are reports of a possible role for dreams in consolidation of declarative memories. Other studies have reported the effect of naps on memory consolidation. With similar protocols, another set of studies indicated that sleep has a role in creativity and problem-solving. Here we hypothesised that sleep can increase the likelihood of solving problems. After struggling to solve a video game problem, subjects who took a nap (n = 14) were almost twice as likely to solve it when compared to the wake control group (n = 15). It is interesting to note that, in the nap group 9 out 14 subjects engaged in slow-wave sleep (SWS) and all solved the problem. Surprisingly, we did not find a significant involvement of Rapid Eye Movement (REM) sleep in this task. Slow-wave sleep is believed to be crucial for the transfer of memory-related information to the neocortex and implement intentions. Sleep can benefit problem-solving through the generalisation of newly encoded information and abstraction of the gist. In conclusion, our results indicate that sleep, even a nap, can potentiate the solution of problems that involve logical reasoning. Thus, sleep's function seems to go beyond memory consolidation to include managing of everyday-life events.

The Different Role of Working Memory in Open-Ended versus Closed-Ended Creative Problem Solving: A Dual-Process Theory Account

ERIC Educational Resources Information Center

Lin, Wei-Lun; Lien, Yunn-Wen

2013-01-01

This study examined how working memory plays different roles in open-ended versus closed-ended creative problem-solving processes, as represented by divergent thinking tests and insight problem-solving tasks. With respect to the analysis of different task demands and the framework of dual-process theories, the hypothesis was that the idea…

Mental Capacity and Working Memory in Chemistry: Algorithmic "versus" Open-Ended Problem Solving

ERIC Educational Resources Information Center

St Clair-Thompson, Helen; Overton, Tina; Bugler, Myfanwy

2012-01-01

Previous research has revealed that problem solving and attainment in chemistry are constrained by mental capacity and working memory. However, the terms mental capacity and working memory come from different theories of cognitive resources, and are assessed using different tasks. The current study examined the relationships between mental…

Memory inhibition as a critical factor preventing creative problem solving.

PubMed

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

2017-06-01

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

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

PubMed

Stamovlasis, Dimitrios; Tsaparlis, Georgios

2003-07-01

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

Role of autobiographical memory in social problem solving and depression.

PubMed

Goddard, L; Dritschel, B; Burton, A

1996-11-01

Depressed patients frequently exhibit deficiencies in social problem solving (SPS). A possible cause of this deficit is an impairment in patients' ability to retrieve specific autobiographical memories. A clinically depressed group and a hospital control group performed the Means-End Problem-Solving (MEPS; J. J. Platt & G. Spivack, 1975a) task, during which they were required to attend to the memories retrieved during solution generation. Memories were categorized according to whether they were specific, categoric, or extended and whether the valence of the memories was positive or negative. Results support the general hypothesis that SPS skill is a function of autobiographical memory retrieval as measured by a cuing task and by the types of memories retrieved during the MEPS. However, the dysfunctional nature of categoric memories in SPS, rather than the importance of specific memories, was highlighted in the depressed group. Valence proved to be an unimportant variable in SPS ability. The cyclical links among autobiographical memory retrieval, SPS skills, and depression are discussed.

The Quantum Binding Problem in the Context of Associative Memory

PubMed Central

Wichert, Andreas

2016-01-01

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

The role of retrieval practice in memory and analogical problem-solving.

PubMed

Hostetter, Autumn B; Penix, Elizabeth A; Norman, Mackenzie Z; Batsell, W Robert; Carr, Thomas H

2018-05-01

Retrieval practice (e.g., testing) has been shown to facilitate long-term retention of information. In two experiments, we examine whether retrieval practice also facilitates use of the practised information when it is needed to solve analogous problems. When retrieval practice was not limited to the information most relevant to the problems (Experiment 1), it improved memory for the information a week later compared with copying or rereading the information, although we found no evidence that it improved participants' ability to apply the information to the problems. In contrast, when retrieval practice was limited to only the information most relevant to the problems (Experiment 2), we found that retrieval practice enhanced memory for the critical information, the ability to identify the schematic similarities between the two sources of information, and the ability to apply that information to solve an analogous problem after a hint was given to do so. These results suggest that retrieval practice, through its effect on memory, can facilitate application of information to solve novel problems but has minimal effects on spontaneous realisation that the information is relevant.

Thinking can cause forgetting: memory dynamics in creative problem solving.

PubMed

Storm, Benjamin C; Angello, Genna; Bjork, Elizabeth Ligon

2011-09-01

Research on retrieval-induced forgetting has shown that retrieval can cause the forgetting of related or competing items in memory (Anderson, Bjork, & Bjork, 1994). In the present research, we examined whether an analogous phenomenon occurs in the context of creative problem solving. Using the Remote Associates Test (RAT; Mednick, 1962), we found that attempting to generate a novel common associate to 3 cue words caused the forgetting of other strong associates related to those cue words. This problem-solving-induced forgetting effect occurred even when participants failed to generate a viable solution, increased in magnitude when participants spent additional time problem solving, and was positively correlated with problem-solving success on a separate set of RAT problems. These results implicate a role for forgetting in overcoming fixation in creative problem solving. (c) 2011 APA, all rights reserved.

Working memory components that predict word problem solving: Is it merely a function of reading, calculation, and fluid intelligence?

PubMed

Fung, Wenson; Swanson, H Lee

2017-07-01

The purpose of this study was to assess whether the differential effects of working memory (WM) components (the central executive, phonological loop, and visual-spatial sketchpad) on math word problem-solving accuracy in children (N = 413, ages 6-10) are completely mediated by reading, calculation, and fluid intelligence. The results indicated that all three WM components predicted word problem solving in the nonmediated model, but only the storage component of WM yielded a significant direct path to word problem-solving accuracy in the fully mediated model. Fluid intelligence was found to moderate the relationship between WM and word problem solving, whereas reading, calculation, and related skills (naming speed, domain-specific knowledge) completely mediated the influence of the executive system on problem-solving accuracy. Our results are consistent with findings suggesting that storage eliminates the predictive contribution of executive WM to various measures Colom, Rebollo, Abad, & Shih (Memory & Cognition, 34: 158-171, 2006). The findings suggest that the storage component of WM, rather than the executive component, has a direct path to higher-order processing in children.

Problem Solving as an Encoding Task: A Special Case of the Generation Effect

ERIC Educational Resources Information Center

Kizilirmak, Jasmin M.; Wiegmann, Berit; Richardson-Klavehn, Alan

2016-01-01

Recent evidence suggests that solving problems through insight can enhance long-term memory for the problem and its solution. Previous findings have shown that generation of the solution as well as experiencing a feeling of Aha! can have a beneficial relationship to later memory. These findings lead to the question of how learning in…

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

NASA Technical Reports Server (NTRS)

Gomez, Fernando

1989-01-01

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

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

DTIC Science & Technology

1985-12-01

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

Spatial Working Memory Is Necessary for Actions to Guide Thought

ERIC Educational Resources Information Center

Thomas, Laura E.

2013-01-01

Directed actions can play a causal role in cognition, shaping thought processes. What drives this cross-talk between action and thought? I investigated the hypothesis that representations in spatial working memory mediate interactions between directed actions and problem solving. Participants attempted to solve an insight problem while…

The Relationship between Working Memory and Mathematical Problem Solving in Children at Risk and Not at Risk for Serious Math Difficulties

ERIC Educational Resources Information Center

Swanson, H. Lee; Beebe-Frankenberger, Margaret

2004-01-01

This study identified cognitive processes that underlie individual differences in working memory (WM) and mathematical problem-solution accuracy in elementary school children at risk and not at risk for serious math difficulties (SMD). A battery of tests was administered that assessed problem solving, achievement, and cognitive processing in…

Effect of Computer-Presented Organizational/Memory Aids on Problem Solving Behavior.

ERIC Educational Resources Information Center

Steinberg, Esther R.; And Others

This research studied the effects of computer-presented organizational/memory aids on problem solving behavior. The aids were either matrix or verbal charts shown on the display screen next to the problem. The 104 college student subjects were randomly assigned to one of the four conditions: type of chart (matrix or verbal chart) and use of charts…

On the adaptive function of children's and adults' false memories.

PubMed

Howe, Mark L; Wilkinson, Samantha; Garner, Sarah R; Ball, Linden J

2016-09-01

Recent research has shown that memory illusions can successfully prime both children's and adults' performance on complex, insight-based problems (compound remote associates tasks or CRATs). The current research aimed to clarify the locus of these priming effects. Like before, Deese-Roediger-McDermott (DRM) lists were selected to prime subsequent CRATs such that the critical lures were also the solution words to a subset of the CRATs participants attempted to solve. Unique to the present research, recognition memory tests were used and participants were either primed during the list study phase, during the memory test phase, or both. Across two experiments, primed problems were solved more frequently and significantly faster than unprimed problems. Moreover, when participants were primed during the list study phase, subsequent solution times and rates were considerably superior to those produced by those participants who were simply primed at test. Together, these are the first results to show that false-memory priming during encoding facilitates problem-solving in both children and adults.

On the adaptive function of children's and adults’ false memories

PubMed Central

Howe, Mark L.; Wilkinson, Samantha; Garner, Sarah R.; Ball, Linden J.

2016-01-01

ABSTRACT Recent research has shown that memory illusions can successfully prime both children's and adults' performance on complex, insight-based problems (compound remote associates tasks or CRATs). The current research aimed to clarify the locus of these priming effects. Like before, Deese–Roediger–McDermott (DRM) lists were selected to prime subsequent CRATs such that the critical lures were also the solution words to a subset of the CRATs participants attempted to solve. Unique to the present research, recognition memory tests were used and participants were either primed during the list study phase, during the memory test phase, or both. Across two experiments, primed problems were solved more frequently and significantly faster than unprimed problems. Moreover, when participants were primed during the list study phase, subsequent solution times and rates were considerably superior to those produced by those participants who were simply primed at test. Together, these are the first results to show that false-memory priming during encoding facilitates problem-solving in both children and adults. PMID:26230151

The influence of eating psychopathology on autobiographical memory specificity and social problem-solving.

PubMed

Ridout, Nathan; Matharu, Munveen; Sanders, Elizabeth; Wallis, Deborah J

2015-08-30

The primary aim was to examine the influence of subclinical disordered eating on autobiographical memory specificity (AMS) and social problem solving (SPS). A further aim was to establish if AMS mediated the relationship between eating psychopathology and SPS. A non-clinical sample of 52 females completed the autobiographical memory test (AMT), where they were asked to retrieve specific memories of events from their past in response to cue words, and the means-end problem-solving task (MEPS), where they were asked to generate means of solving a series of social problems. Participants also completed the Eating Disorders Inventory (EDI) and Hospital Anxiety and Depression Scale. After controlling for mood, high scores on the EDI subscales, particularly Drive-for-Thinness, were associated with the retrieval of fewer specific and a greater proportion of categorical memories on the AMT and with the generation of fewer and less effective means on the MEPS. Memory specificity fully mediated the relationship between eating psychopathology and SPS. These findings have implications for individuals exhibiting high levels of disordered eating, as poor AMS and SPS are likely to impact negatively on their psychological wellbeing and everyday social functioning and could represent a risk factor for the development of clinically significant eating disorders. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Sources of difficulty in the solution of verbal arithmetic problems by mentally retarded and nonretarded individuals.

PubMed

Bilsky, L H; Judd, T

1986-01-01

Effects of several logical (i.e., operation type and amount of extraneous information), memory (i.e., availability of memory aids and number of problem presentations), and semantic variables (i.e., problem text type) on verbal math problem-solving performance were assessed. Results revealed that the overall problem-solving performance of mildly mentally retarded adolescents was inferior to that of nonretarded fourth graders in spite of comparable performance on a computational screening test. Although the retarded individuals experienced particular difficulty with subtraction and static problem texts, the two groups responded similarly to the other experimental variables. The possibly important role of comprehension in problem-solving was discussed.

Sleep Does Not Promote Solving Classical Insight Problems and Magic Tricks

PubMed Central

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

2018-01-01

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

Self-organization and solution of shortest-path optimization problems with memristive networks

NASA Astrophysics Data System (ADS)

Pershin, Yuriy V.; Di Ventra, Massimiliano

2013-07-01

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.

Thinking Can Cause Forgetting: Memory Dynamics in Creative Problem Solving

ERIC Educational Resources Information Center

Storm, Benjamin C.; Angello, Genna; Bjork, Elizabeth Ligon

2011-01-01

Research on retrieval-induced forgetting has shown that retrieval can cause the forgetting of related or competing items in memory (Anderson, Bjork, & Bjork, 1994). In the present research, we examined whether an analogous phenomenon occurs in the context of creative problem solving. Using the Remote Associates Test (RAT; Mednick, 1962), we…

Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

ERIC Educational Resources Information Center

Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

2013-01-01

This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

Computer-Presented Organizational/Memory Aids as Instruction for Solving Pico-Fomi Problems.

ERIC Educational Resources Information Center

Steinberg, Esther R.; And Others

1985-01-01

Describes investigation of effectiveness of computer-presented organizational/memory aids (matrix and verbal charts controlled by computer or learner) as instructional technique for solving Pico-Fomi problems, and the acquisition of deductive inference rules when such aids are present. Results indicate chart use control should be adapted to…

The Contributions of Working Memory and Executive Functioning to Problem Representation and Solution Generation in Algebraic Word Problems

ERIC Educational Resources Information Center

Lee, Kerry; Ng, Ee Lynn; Ng, Swee Fong

2009-01-01

Solving algebraic word problems involves multiple cognitive phases. The authors used a multitask approach to examine the extent to which working memory and executive functioning are associated with generating problem models and producing solutions. They tested 255 11-year-olds on working memory (Counting Recall, Letter Memory, and Keep Track),…

The Relation between Test Anxiety and Need for Memory Support in Problem Solving. Revised Research Memorandum No. 11.

ERIC Educational Resources Information Center

Sieber, Joan E.; Kameya, Lawrence I.

Forty fifth and sixth graders, matched on sex and measures of test anxiety, defensiveness, and IQ, were divided into two groups, each of which solved Porteus maze tasks and a marble puzzle, with and without memory support, respectively. An anxiety-by-memory support interaction occurred in the number of errors made prior to solving the marble…

Applying Catastrophe Theory to an Information-Processing Model of Problem Solving in Science Education

ERIC Educational Resources Information Center

Stamovlasis, Dimitrios; Tsaparlis, Georgios

2012-01-01

In this study, we test an information-processing model (IPM) of problem solving in science education, namely the working memory overload model, by applying catastrophe theory. Changes in students' achievement were modeled as discontinuities within a cusp catastrophe model, where working memory capacity was implemented as asymmetry and the degree…

On the relationship between math anxiety and math achievement in early elementary school: The role of problem solving strategies.

PubMed

Ramirez, Gerardo; Chang, Hyesang; Maloney, Erin A; Levine, Susan C; Beilock, Sian L

2016-01-01

Even at young ages, children self-report experiencing math anxiety, which negatively relates to their math achievement. Leveraging a large dataset of first and second grade students' math achievement scores, math problem solving strategies, and math attitudes, we explored the possibility that children's math anxiety (i.e., a fear or apprehension about math) negatively relates to their use of more advanced problem solving strategies, which in turn relates to their math achievement. Our results confirm our hypothesis and, moreover, demonstrate that the relation between math anxiety and math problem solving strategies is strongest in children with the highest working memory capacity. Ironically, children who have the highest cognitive capacity avoid using advanced problem solving strategies when they are high in math anxiety and, as a result, underperform in math compared with their lower working memory peers. Copyright © 2015 Elsevier Inc. All rights reserved.

Hippocampal-neocortical functional reorganization underlies children's cognitive development

PubMed Central

Qin, Shaozheng; Cho, Soohyun; Chen, Tianwen; Rosenberg-Lee, Miriam; Geary, David C.; Menon, Vinod

2014-01-01

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development – the transition from procedure-based to memory-based problem solving strategies – are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal fMRI in children, ages 7 to 9, revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Critically, longitudinal improvements in retrieval strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval strategy use continued to improve through adolescence into adulthood, and was associated with decreased activation but more stable inter-problem representations in the hippocampus. Our findings provide novel insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving, and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development. PMID:25129076

Planning meals: Problem-solving on a real data-base

ERIC Educational Resources Information Center

Byrne, Richard

1977-01-01

Planning the menu for a dinner party, which involves problem-solving with a large body of knowledge, is used to study the daily operation of human memory. Verbal protocol analysis, a technique devised to investigate formal problem-solving, is examined theoretically and adapted for analysis of this task. (Author/MV)

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

PubMed

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

2015-09-01

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

Cognitive and psychomotor effects of risperidone in schizophrenia and schizoaffective disorder.

PubMed

Houthoofd, Sofie A M K; Morrens, Manuel; Sabbe, Bernard G C

2008-09-01

The aim of this review was to discuss data from double-blind, randomized controlled trials (RCTs) that have investigated the effects of oral and long-acting injectable risperidone on cognitive and psychomotor functioning in patients with schizophrenia or schizoaffective disorder. PubMed/MEDLINE and the Institute of Scientific Information Web of Science database were searched for relevant English-language double-blind RCTs published between March 2000 and July 2008, using the terms schizophrenia, schizoaffective disorder, cognition, risperidone, psychomotor, processing speed, attention, vigilance, working memory, verbal learning, visual learning, reasoning, problem solving, social cognition, MATRICS, and long-acting. Relevant studies included patients with schizophrenia or schizoaffective disorder. Cognitive domains were delineated at the Consensus Conferences of the National Institute of Mental Health-Measurement And Treatment Research to Improve Cognition in Schizophrenia (NIMH-MATRICS). The tests employed to assess each domain and psychomotor functioning, and the within-group and between-group comparisons of risperidone with haloperidol and other atypical antipsychotics, are presented. The results of individual tests were included when they were individually presented and interpretable for either drug; outcomes that were presented as cluster scores or factor structures were excluded. A total of 12 articles were included in this review. Results suggested that the use of oral risperidone appeared to be associated with within-group improvements on the cognitive domains of processing speed, attention/vigilance, verbal and visual learning and memory, and reasoning and problem solving in patients with schizophrenia or schizoaffective disorder. Risperidone and haloperidol seemed to generate similar beneficial effects (on the domains of processing speed, attention/vigilance, [verbal and nonverbal] working memory, and visual learning and memory, as well as psychomotor functioning), although the results for verbal fluency, verbal learning and memory, and reasoning and problem solving were not unanimous, and no comparative data on social cognition were available. Similar cognitive effects were found with risperidone, olanzapine, and quetiapine on the domains of verbal working memory and reasoning and problem solving, as well as verbal fluency. More research is needed on the domains in which study results were contradictory. For olanzapine versus risperidone, these were verbal and visual learning and memory and psychomotor functioning. No comparative data for olanzapine and risperidone were available for the social cognition domain. For quetiapine versus risperidone, the domains in which no unanimity was found were processing speed, attention/vigilance, nonverbal working memory, and verbal learning and memory. The limited available reports on risperidone versus clozapine suggest that: risperidone was associated with improved, and clozapine with worsened, performance on the nonverbal working memory domain; risperidone improved and clozapine did not improve reasoning and problem-solving performance; clozapine improved, and risperidone did not improve, social cognition performance. Use of long-acting injectable risperidone seemed to be associated with improved performance in the domains of attention/vigilance, verbal learning and memory, and reasoning and problem solving, as well as psychomotor functioning. The results for the nonverbal working memory domain were indeterminate, and no clear improvement was seen in the social cognition domain. The domains of processing speed, verbal working memory, and visual learning and memory, as well as verbal fluency, were not assessed. The results of this review of within-group comparisons of oral risperidone suggest that the agent appeared to be associated with improved functioning in the cognitive domains of processing speed, attention/vigilance, verbal and visual learning and memory, and reasoning and problem solving in patients with schizophrenia or schizoaffective disorder. Long-acting injectable risperidone seemed to be associated with improved functioning in the domains of attention/vigilance, verbal learning and memory, and reasoning and problem solving, as well as psychomotor functioning, in patients with schizophrenia or schizoaffective disorder.

The effectiveness of artificial intelligent 3-D virtual reality vocational problem-solving training in enhancing employment opportunities for people with traumatic brain injury.

PubMed

Man, David Wai Kwong; Poon, Wai Sang; Lam, Chow

2013-01-01

People with traumatic brain injury (TBI) often experience cognitive deficits in attention, memory, executive functioning and problem-solving. The purpose of the present research study was to examine the effectiveness of an artificial intelligent virtual reality (VR)-based vocational problem-solving skill training programme designed to enhance employment opportunities for people with TBI. This was a prospective randomized controlled trial (RCT) comparing the effectiveness of the above programme with that of the conventional psycho-educational approach. Forty participants with mild (n = 20) or moderate (n = 20) brain injury were randomly assigned to each training programme. Comparisons of problem-solving skills were performed with the Wisconsin Card Sorting Test, the Tower of London Test and the Vocational Cognitive Rating Scale. Improvement in selective memory processes and perception of memory function were found. Across-group comparison showed that the VR group performed more favourably than the therapist-led one in terms of objective and subjective outcome measures and better vocational outcomes. These results support the potential use of a VR-based approach in memory training in people with MCI. Further VR applications, limitations and future research are described.

The impact of perceived self-efficacy on mental time travel and social problem solving.

PubMed

Brown, Adam D; Dorfman, Michelle L; Marmar, Charles R; Bryant, Richard A

2012-03-01

Current models of autobiographical memory suggest that self-identity guides autobiographical memory retrieval. Further, the capacity to recall the past and imagine one's self in the future (mental time travel) can influence social problem solving. We examined whether manipulating self-identity, through an induction task in which students were led to believe they possessed high or low self-efficacy, impacted episodic specificity and content of retrieved and imagined events, as well as social problem solving. Compared to individuals in the low self efficacy group, individuals in the high self efficacy group generated past and future events with greater (a) specificity, (b) positive words, and (c) self-efficacious statements, and also performed better on social problem solving indices. A lack of episodic detail for future events predicted poorer performance on social problem solving tasks. Strategies that increase perceived self-efficacy may help individuals to selectively construct a past and future that aids in negotiating social problems. Copyright © 2011 Elsevier Inc. All rights reserved.

Working Memory and Literacy as Predictors of Performance on Algebraic Word Problems

ERIC Educational Resources Information Center

Lee, Kerry; Ng, Swee-Fong; Ng, Ee-Lynn; Lim, Zee-Ying

2004-01-01

Previous studies on individual differences in mathematical abilities have shown that working memory contributes to early arithmetic performance. In this study, we extended the investigation to algebraic word problem solving. A total of 151 10-year-olds were administered algebraic word problems and measures of working memory, intelligence quotient…

Autobiographical Memory and Social Problem-Solving in Asperger Syndrome

ERIC Educational Resources Information Center

Goddard, Lorna; Howlin, Patricia; Dritschel, Barbara; Patel, Trishna

2007-01-01

Difficulties in social interaction are a central feature of Asperger syndrome. Effective social interaction involves the ability to solve interpersonal problems as and when they occur. Here we examined social problem-solving in a group of adults with Asperger syndrome and control group matched for age, gender and IQ. We also assessed…

Effects of Cognitive Strategy Interventions on Word Problem Solving and Working Memory in Children with Math Disabilities

ERIC Educational Resources Information Center

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

2011-01-01

Although current categories of learning disabilities include as specific disabilities calculation and mathematical problem solving [see IDEA reauthorization, 2004, Sec. 300.8(c)(10)], the majority of research focuses on calculation disabilities. Previous studies have shown, however, that deficits in word problem solving difficulties are persistent…

Selective Spatial Working Memory Impairment in a Group of Children with Mathematics Learning Disabilities and Poor Problem-Solving Skills

ERIC Educational Resources Information Center

Passolunghi, Maria Chiara; Mammarella, Irene Cristina

2012-01-01

This study examines visual and spatial working memory skills in 35 third to fifth graders with both mathematics learning disabilities (MLD) and poor problem-solving skills and 35 of their peers with typical development (TD) on tasks involving both low and high attentional control. Results revealed that children with MLD, relative to TD children,…

Sleep promotes analogical transfer in problem solving.

PubMed

Monaghan, Padraic; Sio, Ut Na; Lau, Sum Wai; Woo, Hoi Kei; Linkenauger, Sally A; Ormerod, Thomas C

2015-10-01

Analogical problem solving requires using a known solution from one problem to apply to a related problem. Sleep is known to have profound effects on memory and information restructuring, and so we tested whether sleep promoted such analogical transfer, determining whether improvement was due to subjective memory for problems, subjective recognition of similarity across related problems, or by abstract generalisation of structure. In Experiment 1, participants were exposed to a set of source problems. Then, after a 12-h period involving sleep or wake, they attempted target problems structurally related to the source problems but with different surface features. Experiment 2 controlled for time of day effects by testing participants either in the morning or the evening. Sleep improved analogical transfer, but effects were not due to improvements in subjective memory or similarity recognition, but rather effects of structural generalisation across problems. Copyright © 2015 Elsevier B.V. All rights reserved.

Efficient ICCG on a shared memory multiprocessor

NASA Technical Reports Server (NTRS)

Hammond, Steven W.; Schreiber, Robert

1989-01-01

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

Working Memory and Reasoning Benefit from Different Modes of Large-scale Brain Dynamics in Healthy Older Adults.

PubMed

Lebedev, Alexander V; Nilsson, Jonna; Lövdén, Martin

2018-07-01

Researchers have proposed that solving complex reasoning problems, a key indicator of fluid intelligence, involves the same cognitive processes as solving working memory tasks. This proposal is supported by an overlap of the functional brain activations associated with the two types of tasks and by high correlations between interindividual differences in performance. We replicated these findings in 53 older participants but also showed that solving reasoning and working memory problems benefits from different configurations of the functional connectome and that this dissimilarity increases with a higher difficulty load. Specifically, superior performance in a typical working memory paradigm ( n-back) was associated with upregulation of modularity (increased between-network segregation), whereas performance in the reasoning task was associated with effective downregulation of modularity. We also showed that working memory training promotes task-invariant increases in modularity. Because superior reasoning performance is associated with downregulation of modular dynamics, training may thus have fostered an inefficient way of solving the reasoning tasks. This could help explain why working memory training does little to promote complex reasoning performance. The study concludes that complex reasoning abilities cannot be reduced to working memory and suggests the need to reconsider the feasibility of using working memory training interventions to attempt to achieve effects that transfer to broader cognition.

Aiding the search: Examining individual differences in multiply-constrained problem solving.

PubMed

Ellis, Derek M; Brewer, Gene A

2018-07-01

Understanding and resolving complex problems is of vital importance in daily life. Problems can be defined by the limitations they place on the problem solver. Multiply-constrained problems are traditionally examined with the compound remote associates task (CRAT). Performance on the CRAT is partially dependent on an individual's working memory capacity (WMC). These findings suggest that executive processes are critical for problem solving and that there are reliable individual differences in multiply-constrained problem solving abilities. The goals of the current study are to replicate and further elucidate the relation between WMC and CRAT performance. To achieve these goals, we manipulated preexposure to CRAT solutions and measured WMC with complex-span tasks. In Experiment 1, we report evidence that preexposure to CRAT solutions improved problem solving accuracy, WMC was correlated with problem solving accuracy, and that WMC did not moderate the effect of preexposure on problem solving accuracy. In Experiment 2, we preexposed participants to correct and incorrect solutions. We replicated Experiment 1 and found that WMC moderates the effect of exposure to CRAT solutions such that high WMC participants benefit more from preexposure to correct solutions than low WMC (although low WMC participants have preexposure benefits as well). Broadly, these results are consistent with theories of working memory and problem solving that suggest a mediating role of attention control processes. Published by Elsevier Inc.

The solution of large multi-dimensional Poisson problems

NASA Technical Reports Server (NTRS)

Stone, H. S.

1974-01-01

The Buneman algorithm for solving Poisson problems can be adapted to solve large Poisson problems on computers with a rotating drum memory so that the computation is done with very little time lost due to rotational latency of the drum.

Puzzling Science: Using the Rubik's Cube to Teach Problem Solving

ERIC Educational Resources Information Center

Rohrig, Brian

2010-01-01

A major goal of education is to help learners store information in long-term memory and use that information on later occasions to effectively solve problems (Vockell 2010). Therefore, this author began to use the Rubik's cube to help students learn to problem solve. There is something special about this colorful three-dimensional puzzle that…

Hippocampal-neocortical functional reorganization underlies children's cognitive development.

PubMed

Qin, Shaozheng; Cho, Soohyun; Chen, Tianwen; Rosenberg-Lee, Miriam; Geary, David C; Menon, Vinod

2014-09-01

The importance of the hippocampal system for rapid learning and memory is well recognized, but its contributions to a cardinal feature of children's cognitive development-the transition from procedure-based to memory-based problem-solving strategies-are unknown. Here we show that the hippocampal system is pivotal to this strategic transition. Longitudinal functional magnetic resonance imaging (fMRI) in 7-9-year-old children revealed that the transition from use of counting to memory-based retrieval parallels increased hippocampal and decreased prefrontal-parietal engagement during arithmetic problem solving. Longitudinal improvements in retrieval-strategy use were predicted by increased hippocampal-neocortical functional connectivity. Beyond childhood, retrieval-strategy use continued to improve through adolescence into adulthood and was associated with decreased activation but more stable interproblem representations in the hippocampus. Our findings provide insights into the dynamic role of the hippocampus in the maturation of memory-based problem solving and establish a critical link between hippocampal-neocortical reorganization and children's cognitive development.

Verification of Algebra Step Problems: A Chronometric Study of Human Problem Solving. Technical Report No. 253. Psychology and Education Series.

ERIC Educational Resources Information Center

Matthews, Paul G.; Atkinson, Richard C.

This paper reports an experiment designed to test theoretical relations among fast problem solving, more complex and slower problem solving, and research concerning fundamental memory processes. Using a cathode ray tube, subjects were presented with propositions of the form "Y is in list X" which they memorized. In later testing they were asked to…

Progression paths in children's problem solving: The influence of dynamic testing, initial variability, and working memory.

PubMed

Resing, Wilma C M; Bakker, Merel; Pronk, Christine M E; Elliott, Julian G

2017-01-01

The current study investigated developmental trajectories of analogical reasoning performance of 104 7- and 8-year-old children. We employed a microgenetic research method and multilevel analysis to examine the influence of several background variables and experimental treatment on the children's developmental trajectories. Our participants were divided into two treatment groups: repeated practice alone and repeated practice with training. Each child received an initial working memory assessment and was subsequently asked to solve figural analogies on each of several sessions. We examined children's analogical problem-solving behavior and their subsequent verbal accounts of their employed solving processes. We also investigated the influence of verbal and visual-spatial working memory capacity and initial variability in strategy use on analogical reasoning development. Results indicated that children in both treatment groups improved but that gains were greater for those who had received training. Training also reduced the influence of children's initial variability in the use of analogical strategies with the degree of improvement in reasoning largely unrelated to working memory capacity. Findings from this study demonstrate the value of a microgenetic research method and the use of multilevel analysis to examine inter- and intra-individual change in problem-solving processes. Copyright © 2016 Elsevier Inc. All rights reserved.

Learning to read aloud: A neural network approach using sparse distributed memory

NASA Technical Reports Server (NTRS)

Joglekar, Umesh Dwarkanath

1989-01-01

An attempt to solve a problem of text-to-phoneme mapping is described which does not appear amenable to solution by use of standard algorithmic procedures. Experiments based on a model of distributed processing are also described. This model (sparse distributed memory (SDM)) can be used in an iterative supervised learning mode to solve the problem. Additional improvements aimed at obtaining better performance are suggested.

Cognitive strategy interventions improve word problem solving and working memory in children with math disabilities.

PubMed

Swanson, H Lee

2015-01-01

This study investigated the role of strategy instruction and working memory capacity (WMC) on problem solving solution accuracy in children with and without math disabilities (MD). Children in grade 3 (N = 204) with and without MD subdivided into high and low WMC were randomly assigned to 1 of 4 conditions: verbal strategies (e.g., underlining question sentence), visual strategies (e.g., correctly placing numbers in diagrams), verbal + visual strategies, and an untreated control. The dependent measures for training were problem solving accuracy and two working memory transfer measures (operation span and visual-spatial span). Three major findings emerged: (1) strategy instruction facilitated solution accuracy but the effects of strategy instruction were moderated by WMC, (2) some strategies yielded higher post-test scores than others, but these findings were qualified as to whether children were at risk for MD, and (3) strategy training on problem solving measures facilitated transfer to working memory measures. The main findings were that children with MD, but high WM spans, were more likely to benefit from strategy conditions on target and transfer measures than children with lower WMC. The results suggest that WMC moderates the influence of cognitive strategies on both the targeted and non-targeted measures.

Cognitive strategy interventions improve word problem solving and working memory in children with math disabilities

PubMed Central

Swanson, H. Lee

2015-01-01

This study investigated the role of strategy instruction and working memory capacity (WMC) on problem solving solution accuracy in children with and without math disabilities (MD). Children in grade 3 (N = 204) with and without MD subdivided into high and low WMC were randomly assigned to 1 of 4 conditions: verbal strategies (e.g., underlining question sentence), visual strategies (e.g., correctly placing numbers in diagrams), verbal + visual strategies, and an untreated control. The dependent measures for training were problem solving accuracy and two working memory transfer measures (operation span and visual-spatial span). Three major findings emerged: (1) strategy instruction facilitated solution accuracy but the effects of strategy instruction were moderated by WMC, (2) some strategies yielded higher post-test scores than others, but these findings were qualified as to whether children were at risk for MD, and (3) strategy training on problem solving measures facilitated transfer to working memory measures. The main findings were that children with MD, but high WM spans, were more likely to benefit from strategy conditions on target and transfer measures than children with lower WMC. The results suggest that WMC moderates the influence of cognitive strategies on both the targeted and non-targeted measures. PMID:26300803

Brief reminiscence activities improve state well-being and self-concept in young adults: a randomised controlled experiment.

PubMed

Hallford, David John; Mellor, David

2016-11-01

Reminiscence-based psychotherapies have been demonstrated to have robust effects on a range of therapeutic outcomes. However, little research has been conducted on the immediate effects of guided activities they are composed of, or how these might differ dependent on the type of reminiscence. The current study utilised a controlled experimental design, whereby 321 young adults (mean age = 25.5 years, SD = 3.0) were randomised to one of four conditions of online reminiscence activity: problem-solving (successful coping experiences), identity (self-defining events contributing to a meaningful and continuous personal identity), bitterness revival (negative or adverse events), or a control condition (any memory from their past). Participants recalled autobiographical memories congruent with the condition, and answered questions to facilitate reflection on the memories. The results indicated that problem-solving and identity reminiscence activities caused significant improvements in self-esteem, meaning in life, self-efficacy and affect, whereas no effects were found in the bitterness revival and control conditions. Problem-solving reminiscence also caused a small effect in increasing perceptions of a life narrative/s. Differences between the conditions did not appear to be explained by the positive-valence of memories. These results provide evidence for the specific effects of adaptive types of problem-solving and identity reminiscence in young adults.

"I Think I Can, but I'm Afraid to Try": The Role of Self-Efficacy Beliefs and Mathematics Anxiety in Mathematics Problem-Solving Efficiency

ERIC Educational Resources Information Center

Hoffman, Bobby

2010-01-01

This study investigated the role of self-efficacy beliefs, mathematics anxiety, and working memory capacity in problem-solving accuracy, response time, and efficiency (the ratio of problem-solving accuracy to response time). Pre-service teachers completed a mathematics anxiety inventory measuring cognitive and affective dispositions for…

Understanding Memory Loss | NIH MedlinePlus the Magazine

MedlinePlus

... urine. She or he also checks your memory, problem solving, counting, and language skills. The doctor also may suggest a brain scan to show the normal and problem areas in the brain. Once the cause of ...

Individual differences in working memory and reasoning-remembering relationships in solving class-inclusion problems.

PubMed

Howe, M L; Rabinowitz, F M; Powell, T L

1998-09-01

In the present experiment, we evaluated the effects of individual differences in reading span and variation in memory demands on class-inclusion performance. One hundred twenty college students whose reading spans ranged from low to medium to high (as indexed by a computerized version of the Daneman and Carpenter [1980] reading-span task) solved 48 class-inclusion problems. Half of the subjects had the solution information available when the problems were presented; the other half performed a detection task between solution information and problem presentation. The results from both standard statistical analyses and from a mathematical model indicated that differences in reading span and memory load had predictable, similar effects. Specifically, the sophistication of reasoning strategies declined when memory demands increased or when reading spans decreased. Surprisingly, these effects were primarily additive. The results were interpreted in terms of global resource models and findings from the developmental literature.

CABINS: Case-based interactive scheduler

NASA Technical Reports Server (NTRS)

Miyashita, Kazuo; Sycara, Katia

1992-01-01

In this paper we discuss the need for interactive factory schedule repair and improvement, and we identify case-based reasoning (CBR) as an appropriate methodology. Case-based reasoning is the problem solving paradigm that relies on a memory for past problem solving experiences (cases) to guide current problem solving. Cases similar to the current case are retrieved from the case memory, and similarities and differences of the current case to past cases are identified. Then a best case is selected, and its repair plan is adapted to fit the current problem description. If a repair solution fails, an explanation for the failure is stored along with the case in memory, so that the user can avoid repeating similar failures in the future. So far we have identified a number of repair strategies and tactics for factory scheduling and have implemented a part of our approach in a prototype system, called CABINS. As a future work, we are going to scale up CABINS to evaluate its usefulness in a real manufacturing environment.

Attention and Multistep Problem Solving in 24-Month-Old Children

ERIC Educational Resources Information Center

Carrico, Renee L.

2013-01-01

The current study examined the role of increased attentional load in 24 month-old children's multistep problem-solving behavior. Children solved an object-based nonspatial working-memory search task, to which a motor component of varying difficulty was added. Significant disruptions in search performance were observed with the introduction of the…

Is Word-Problem Solving a Form of Text Comprehension?

ERIC Educational Resources Information Center

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

2015-01-01

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

Etiological Distinction of Working Memory Components in Relation to Mathematics

PubMed Central

Lukowski, Sarah L.; Soden, Brooke; Hart, Sara A.; Thompson, Lee A.; Kovas, Yulia; Petrill, Stephen A.

2014-01-01

Working memory has been consistently associated with mathematics achievement, although the etiology of these relations remains poorly understood. The present study examined the genetic and environmental underpinnings of math story problem solving, timed calculation, and untimed calculation alongside working memory components in 12-year-old monozygotic (n = 105) and same-sex dizygotic (n = 143) twin pairs. Results indicated significant phenotypic correlation between each working memory component and all mathematics outcomes (r = 0.18 – 0.33). Additive genetic influences shared between the visuo-spatial sketchpad and mathematics achievement was significant, accounting for roughly 89% of the observed correlation. In addition, genetic covariance was found between the phonological loop and math story problem solving. In contrast, despite there being a significant observed relationship between phonological loop and timed and untimed calculation, there was no significant genetic or environmental covariance between the phonological loop and timed or untimed calculation skills. Further analyses indicated that genetic overlap between the visuo-spatial sketchpad and math story problem solving and math fluency was distinct from general genetic factors, whereas g, phonological loop, and mathematics shared generalist genes. Thus, although each working memory component was related to mathematics, the etiology of their relationships may be distinct. PMID:25477699

Can False Memories Prime Problem Solutions for Healthy Older Adults and those with Alzheimer 's Disease?

PubMed

Akhtar, Shazia; Howe, Mark L; Hoepstine, Kedron

2018-06-05

Recent research has shown that false memories can have a positive consequence on human cognition in both children and young adults. The present experiment investigated whether false memories could have similar positive effects by priming solutions to insight-based problems in healthy older adults and people with Alzheimer's disease. Participants were asked to solve compound remote associate task (CRAT) problems, half of which had been preceded by the presentation of Deese/Roediger-McDermott (DRM) lists whose critical lures were also the solutions to those problems. The results showed that regardless of cognitive ability, when the critical lure was falsely recognized, CRAT problems were solved more often and reliably faster than problems that were not primed by a DRM list. When the critical lure was not falsely recognized, CRAT problem solution rates and times were no different from when there was no DRM priming. These findings are consistent with predictions from theories of associative activation and demonstrate the importance of automatic spreading activation processes in memory across the lifespan.

How Can One Learn Mathematical Word Problems in a Second Language? A Cognitive Load Perspective

ERIC Educational Resources Information Center

Moussa-Inaty, Jase; Causapin, Mark; Groombridge, Timothy

2015-01-01

Language may ordinarily account for difficulties in solving word problems and this is particularly true if mathematical word problems are taught in a language other than one's native language. Research into cognitive load may offer a clear theoretical framework when investigating word problems because memory, specifically working memory, plays a…

A Comparison of Computation Span and Reading Span Working Memory Measures' Relations With Problem-Solving Criteria.

PubMed

Perlow, Richard; Jattuso, Mia

2018-06-01

Researchers have operationalized working memory in different ways and although working memory-performance relationships are well documented, there has been relatively less attention devoted to determining whether seemingly similar measures yield comparable relations with performance outcomes. Our objective is to assess whether two working memory measures deploying the same processes but different item content yield different relations with two problem-solving criteria. Participants completed a computation-based working memory measure and a reading-based measure prior to performing a computerized simulation. Results reveal differential relations with one of the two criteria and support the notion that the two working memory measures tap working memory capacity and other cognitive abilities. One implication for theory development is that researchers should consider incorporating other cognitive abilities in their working memory models and that the selection of those abilities should correspond to the criterion of interest. One practical implication is that researchers and practitioners shouldn't automatically assume that different phonological loop-based working memory scales are interchangeable.

Lions (Panthera leo) solve, learn, and remember a novel resource acquisition problem.

PubMed

Borrego, Natalia; Dowling, Brian

2016-09-01

The social intelligence hypothesis proposes that the challenges of complex social life bolster the evolution of intelligence, and accordingly, advanced cognition has convergently evolved in several social lineages. Lions (Panthera leo) offer an ideal model system for cognitive research in a highly social species with an egalitarian social structure. We investigated cognition in lions using a novel resource task: the suspended puzzle box. The task required lions (n = 12) to solve a novel problem, learn the techniques used to solve the problem, and remember techniques for use in future trials. The majority of lions demonstrated novel problem-solving and learning; lions (11/12) solved the task, repeated success in multiple trials, and significantly reduced the latency to success across trials. Lions also demonstrated cognitive abilities associated with memory and solved the task after up to a 7-month testing interval. We also observed limited evidence for social facilitation of the task solution. Four of five initially unsuccessful lions achieved success after being partnered with a successful lion. Overall, our results support the presence of cognition associated with novel problem-solving, learning, and memory in lions. To date, our study is only the second experimental investigation of cognition in lions and further supports expanding cognitive research to lions.

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

PubMed

Chuderski, Adam; Jastrzębski, Jan

2018-02-01

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

What Are the Signs of Alzheimer's Disease? | NIH MedlinePlus the Magazine

MedlinePlus

... in behavior and personality Conduct tests of memory, problem solving, attention, counting, and language Carry out standard medical ... over and over having trouble paying bills or solving simple math problems getting lost losing things or putting them in ...

Immediate and Sustained Effects of Planning in a Problem-Solving Task

ERIC Educational Resources Information Center

Delaney, Peter F.; Ericsson, K. Anders; Knowles, Martin E.

2004-01-01

In 4 experiments, instructions to plan a task (water jugs) that normally produces little planning altered how participants solved the problems and resulted in enhanced learning and memory. Experiment 1 identified planning strategies that allowed participants to plan full solutions to water jugs problems. Experiment 2 showed that experience with…

Very Large Scale Optimization

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

What's the Problem? Familiarity Working Memory, and Transfer in a Problem-Solving Task.

PubMed

Kole, James A; Snyder, Hannah R; Brojde, Chandra L; Friend, Angela

2015-01-01

The contributions of familiarity and working memory to transfer were examined in the Tower of Hanoi task. Participants completed 3 different versions of the task: a standard 3-disk version, a clothing exchange task that included familiar semantic content, and a tea ceremony task that included unfamiliar semantic content. The constraints on moves were equivalent across tasks, and each could be solved with the same sequence of movements. Working memory demands were manipulated by the provision of a (static or dynamic) visual representation of the problem. Performance was equivalent for the standard Tower of Hanoi and clothing exchange tasks but worse for the tea ceremony task, and it decreased with increasing working memory demands. Furthermore, the standard Tower of Hanoi task and clothing exchange tasks independently, additively, and equivalently transferred to subsequent tasks, whereas the tea ceremony task did not. The results suggest that both familiarity and working memory demands determine overall level of performance, whereas familiarity influences transfer.

An optimized treatment for algorithmic differentiation of an important glaciological fixed-point problem

DOE PAGES

Goldberg, Daniel N.; Narayanan, Sri Hari Krishna; Hascoet, Laurent; ...

2016-05-20

We apply an optimized method to the adjoint generation of a time-evolving land ice model through algorithmic differentiation (AD). The optimization involves a special treatment of the fixed-point iteration required to solve the nonlinear stress balance, which differs from a straightforward application of AD software, and leads to smaller memory requirements and in some cases shorter computation times of the adjoint. The optimization is done via implementation of the algorithm of Christianson (1994) for reverse accumulation of fixed-point problems, with the AD tool OpenAD. For test problems, the optimized adjoint is shown to have far lower memory requirements, potentially enablingmore » larger problem sizes on memory-limited machines. In the case of the land ice model, implementation of the algorithm allows further optimization by having the adjoint model solve a sequence of linear systems with identical (as opposed to varying) matrices, greatly improving performance. Finally, the methods introduced here will be of value to other efforts applying AD tools to ice models, particularly ones which solve a hybrid shallow ice/shallow shelf approximation to the Stokes equations.« less

Text Comprehension and Oral Language as Predictors of Word-Problem Solving: Insights into Word-Problem Solving as a Form of Text Comprehension

ERIC Educational Resources Information Center

Fuchs, Lynn S.; Gilbert, Jennifer K.; Fuchs, Douglas; Seethaler, Pamela M.; N. Martin, BrittanyLee

2018-01-01

This study was designed to deepen insights on whether word-problem (WP) solving is a form of text comprehension (TC) and on the role of language in WPs. A sample of 325 second graders, representing high, average, and low reading and math performance, was assessed on (a) start-of-year TC, WP skill, language, nonlinguistic reasoning, working memory,…

Working Memory Capacity and Fluid Intelligence: Maintenance and Disengagement.

PubMed

Shipstead, Zach; Harrison, Tyler L; Engle, Randall W

2016-11-01

Working memory capacity and fluid intelligence have been demonstrated to be strongly correlated traits. Typically, high working memory capacity is believed to facilitate reasoning through accurate maintenance of relevant information. In this article, we present a proposal reframing this issue, such that tests of working memory capacity and fluid intelligence are seen as measuring complementary processes that facilitate complex cognition. Respectively, these are the ability to maintain access to critical information and the ability to disengage from or block outdated information. In the realm of problem solving, high working memory capacity allows a person to represent and maintain a problem accurately and stably, so that hypothesis testing can be conducted. However, as hypotheses are disproven or become untenable, disengaging from outdated problem solving attempts becomes important so that new hypotheses can be generated and tested. From this perspective, the strong correlation between working memory capacity and fluid intelligence is due not to one ability having a causal influence on the other but to separate attention-demanding mental functions that can be contrary to one another but are organized around top-down processing goals. © The Author(s) 2016.

Some Prerequisites in Learning to Solve Figural Analogy Problems.

ERIC Educational Resources Information Center

Wagner, James

A series of three experiments was conducted for the purposes of (1) clarifying problems of previous research on the relationship between working memory capacity and performance on figural analogy tasks, and (2) exploring developmental issues concerning executive strategies, working memory capacity, and perceptual processing. Directly manipulating…

Research Reporting Sections, Annual Meeting of the National Council of Teachers of Mathematics (57th, Boston, Massachusetts, April 18-21, 1979).

ERIC Educational Resources Information Center

Higgins, Jon L., Ed.

This document provides abstracts of 20 research reports. Topics covered include: children's comprehension of simple story problems; field independence and group instruction; problem-solving competence and memory; spatial visualization and the use of manipulative materials; effects of games on mathematical skills; problem-solving ability and right…

Roles of Variables in Teaching

ERIC Educational Resources Information Center

Sorva, Juha; Karavirta, Ville; Korhonen, Ari

2007-01-01

Expert programmers possess schemas, abstractions of concrete experiences, which help them solve programming problems and lessen the load on their working memory during problem solving. Possession of schemas is a key difference between novices and experts, which is why instructors need to help students construct them. One recent tool for…

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.

Controlling Uncertainty: A Review of Human Behavior in Complex Dynamic Environments

ERIC Educational Resources Information Center

Osman, Magda

2010-01-01

Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research…

Solving Large Problems with a Small Working Memory

ERIC Educational Resources Information Center

Pizlo, Zygmunt; Stefanov, Emil

2013-01-01

We describe an important elaboration of our multiscale/multiresolution model for solving the Traveling Salesman Problem (TSP). Our previous model emulated the non-uniform distribution of receptors on the human retina and the shifts of visual attention. This model produced near-optimal solutions of TSP in linear time by performing hierarchical…

Aspects of the Cognitive Model of Physics Problem Solving.

ERIC Educational Resources Information Center

Brekke, Stewart E.

Various aspects of the cognitive model of physics problem solving are discussed in detail including relevant cues, encoding, memory, and input stimuli. The learning process involved in the recognition of familiar and non-familiar sensory stimuli is highlighted. Its four components include selection, acquisition, construction, and integration. The…

Is Word-Problem Solving a Form of Text Comprehension?

PubMed Central

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

2015-01-01

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

Characteristic of cognitive decline in Parkinson's disease: a 1-year follow-up.

PubMed

McKinlay, Audrey; Grace, Randolph C

2011-10-01

The aim of this study was to track the evolution of cognitive decline in Parkinson's disease (PD) patients 1 year after baseline testing. Thirty-three PD patients, divided according to three previously determined subgroups based on their initial cognitive performance, and a healthy comparison group were reassessed after a 1-year interval. Participants were assessed in the following five domains: Executive Function, Problem Solving, Working Memory/Attention, Memory, and Visuospatial Ability. The PD groups differed on the domains of Executive Function, Problem Solving, and Working Memory, with the most severe deficits being evident for the group that had previously shown the greatest level of impairment. Increased cognitive problems were also associated with decreased functioning in activities of daily living. The most severely impaired group had evidence of global cognitive decline, possibly reflecting a stage of preclinical dementia.

How to Study: The Neglected Basic.

ERIC Educational Resources Information Center

Wilcox, Wayne C.; Wilson, Brent G.

This paper examines knowledge of studying--knowing how and when to apply study strategies. Study strategies may be classified into three categories: memory strategies, comprehension strategies, and problem-solving strategies. Memory-study strategies help students remember what they study. Five attributes often characterize memory strategies:…

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.

Memory Inhibition as a Critical Factor Preventing Creative Problem Solving

ERIC Educational Resources Information Center

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

2017-01-01

The hypothesis that reduced accessibility to relevant information can negatively affect problem solving in a remote associate test (RAT) was tested by using, immediately before the RAT, a retrieval practice procedure to hinder access to target solutions. The results of 2 experiments clearly showed that, relative to baseline, target words that had…

A Naturalistic Study of Executive Function and Mathematical Problem-Solving

ERIC Educational Resources Information Center

Kotsopoulos, Donna; Lee, Joanne

2012-01-01

Our goal in this research was to understand the specific challenges middle-school students face when engaging in mathematical problem-solving by using executive function (i.e., shifting, updating, and inhibiting) of working memory as a functional construct for the analysis. Using modified talk-aloud protocols, real-time naturalistic analysis of…

Gender Differences in Eye Movements in Solving Text-and-Diagram Science Problems

ERIC Educational Resources Information Center

Huang, Po-Sheng; Chen, Hsueh-Chih

2016-01-01

The main purpose of this study was to examine possible gender differences in how junior high school students integrate printed texts and diagrams while solving science problems. We proposed the response style hypothesis and the spatial working memory hypothesis to explain possible gender differences in the integration process. Eye-tracking…

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

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

Carleton, James Brian; Parks, Michael L.

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

Working memory, worry, and algebraic ability.

PubMed

Trezise, Kelly; Reeve, Robert A

2014-05-01

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

Planning paths to multiple targets: memory involvement and planning heuristics in spatial problem solving.

PubMed

Wiener, J M; Ehbauer, N N; Mallot, H A

2009-09-01

For large numbers of targets, path planning is a complex and computationally expensive task. Humans, however, usually solve such tasks quickly and efficiently. We present experiments studying human path planning performance and the cognitive processes and heuristics involved. Twenty-five places were arranged on a regular grid in a large room. Participants were repeatedly asked to solve traveling salesman problems (TSP), i.e., to find the shortest closed loop connecting a start location with multiple target locations. In Experiment 1, we tested whether humans employed the nearest neighbor (NN) strategy when solving the TSP. Results showed that subjects outperform the NN-strategy, suggesting that it is not sufficient to explain human route planning behavior. As a second possible strategy we tested a hierarchical planning heuristic in Experiment 2, demonstrating that participants first plan a coarse route on the region level that is refined during navigation. To test for the relevance of spatial working memory (SWM) and spatial long-term memory (LTM) for planning performance and the planning heuristics applied, we varied the memory demands between conditions in Experiment 2. In one condition the target locations were directly marked, such that no memory was required; a second condition required participants to memorize the target locations during path planning (SWM); in a third condition, additionally, the locations of targets had to retrieved from LTM (SWM and LTM). Results showed that navigation performance decreased with increasing memory demands while the dependence on the hierarchical planning heuristic increased.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Working Memory Underpins Cognitive Development, Learning, and Education

ERIC Educational Resources Information Center

Cowan, Nelson

2014-01-01

Working memory is the retention of a small amount of information in a readily accessible form. It facilitates planning, comprehension, reasoning, and problem solving. I examine the historical roots and conceptual development of the concept and the theoretical and practical implications of current debates about working memory mechanisms. Then, I…

Skills, Plans, and Self-Regulation. Technical Report No. 48.

ERIC Educational Resources Information Center

Brown, Ann L.; DeLoache, Judy S.

The first section of this report reviews traditional memory studies, which have provided much of our information concerning memory development. Major strengths and weaknesses of memory-development studies are illustrated by comparison with recent research into children's problem-solving skills. The report concentrates on one area of general…

Working from Memory: Artists and Actors

ERIC Educational Resources Information Center

Hurwitz, Al

2004-01-01

In this article, the author discusses the art of memory-based drawing. Memory-based drawing represents but one part of a broad range of activities used in drawing instruction. Other sources involve the use of fantasy, doodling, problem-solving, and illustrating. Other ways of working from one's personal history involve keeping illustrated…

Working Memory Capacity and Categorization: Individual Differences and Modeling

ERIC Educational Resources Information Center

Lewandowsky, Stephan

2011-01-01

Working memory is crucial for many higher-level cognitive functions, ranging from mental arithmetic to reasoning and problem solving. Likewise, the ability to learn and categorize novel concepts forms an indispensable part of human cognition. However, very little is known about the relationship between working memory and categorization, and…

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

ERIC Educational Resources Information Center

Champagne, Audrey B.; And Others

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

Non-Algorithmic Quantitative Problem Solving in University Physical Chemistry: A Correlation Study of the Role of Selective Cognitive Factors

ERIC Educational Resources Information Center

Tsaparlis, Georgios

2005-01-01

This work provides a correlation study of the role of the following cognitive variables on problem solving in elementary physical chemistry: scientific reasoning (level of intellectual development/developmental level), working-memory capacity, functional mental ("M") capacity, and disembedding ability (i.e., degree of perceptual field…

Fragmentation of Thinking Structure's Students to Solving the Problem of Application Definite Integral in Area

ERIC Educational Resources Information Center

Wibawa, Kadek Adi; Nusantara, Toto; Subanji; Parta, I. Nengah

2017-01-01

This study aims to reveal the fragmentation of thinking structure's students in solving the problems of application definite integral in area. Fragmentation is a term on the computer (storage) that is highly relevant correlated with theoretical constructions that occur in the human brain (memory). Almost every student has a different way to…

Students' Ability to Solve Process-Diagram Problems in Secondary Biology Education

ERIC Educational Resources Information Center

Kragten, Marco; Admiraal, Wilfried; Rijlaarsdam, Gert

2015-01-01

Process diagrams are important tools in biology for explaining processes such as protein synthesis, compound cycles and the like. The aim of the present study was to measure the ability to solve process-diagram problems in biology and its relationship with prior knowledge, spatial ability and working memory. For this purpose, we developed a test…

Parental Guidance and Children's Executive Function: Working Memory and Planning as Moderators during Joint Problem-Solving

ERIC Educational Resources Information Center

Eason, Sarah H.; Ramani, Geetha B.

2017-01-01

Cognitive aspects of children's executive function (EF) were examined as moderators of the effectiveness of parental guidance on children's learning. Thirty-two 5-year-old children and their parents were observed during joint problem-solving. Forms of guidance geared towards cognitive assistance were coded as directive or elaborative, and…

Inductive reasoning and implicit memory: evidence from intact and impaired memory systems.

PubMed

Girelli, Luisa; Semenza, Carlo; Delazer, Margarete

2004-01-01

In this study, we modified a classic problem solving task, number series completion, in order to explore the contribution of implicit memory to inductive reasoning. Participants were required to complete number series sharing the same underlying algorithm (e.g., +2), differing in both constituent elements (e.g., 2468 versus 57911) and correct answers (e.g., 10 versus 13). In Experiment 1, reliable priming effects emerged, whether primes and targets were separated by four or ten fillers. Experiment 2 provided direct evidence that the observed facilitation arises at central stages of problem solving, namely the identification of the algorithm and its subsequent extrapolation. The observation of analogous priming effects in a severely amnesic patient strongly supports the hypothesis that the facilitation in number series completion was largely determined by implicit memory processes. These findings demonstrate that the influence of implicit processes extends to higher level cognitive domain such as induction reasoning.

Set selection dynamical system neural networks with partial memories, with applications to Sudoku and KenKen puzzles.

PubMed

Boreland, B; Clement, G; Kunze, H

2015-08-01

After reviewing set selection and memory model dynamical system neural networks, we introduce a neural network model that combines set selection with partial memories (stored memories on subsets of states in the network). We establish that feasible equilibria with all states equal to ± 1 correspond to answers to a particular set theoretic problem. We show that KenKen puzzles can be formulated as a particular case of this set theoretic problem and use the neural network model to solve them; in addition, we use a similar approach to solve Sudoku. We illustrate the approach in examples. As a heuristic experiment, we use online or print resources to identify the difficulty of the puzzles and compare these difficulties to the number of iterations used by the appropriate neural network solver, finding a strong relationship. Copyright © 2015 Elsevier Ltd. All rights reserved.

Problem Solving and Learning

NASA Astrophysics Data System (ADS)

Singh, Chandralekha

2009-07-01

One finding of cognitive research is that people do not automatically acquire usable knowledge by spending lots of time on task. Because students' knowledge hierarchy is more fragmented, "knowledge chunks" are smaller than those of experts. The limited capacity of short term memory makes the cognitive load high during problem solving tasks, leaving few cognitive resources available for meta-cognition. The abstract nature of the laws of physics and the chain of reasoning required to draw meaningful inferences makes these issues critical. In order to help students, it is crucial to consider the difficulty of a problem from the perspective of students. We are developing and evaluating interactive problem-solving tutorials to help students in the introductory physics courses learn effective problem-solving strategies while solidifying physics concepts. The self-paced tutorials can provide guidance and support for a variety of problem solving techniques, and opportunity for knowledge and skill acquisition.

Mental Images and the Modification of Learning Defects.

ERIC Educational Resources Information Center

Patten, Bernard M.

Because human memory and thought involve extremely complex processes, it is possible to employ unusual modalities and specific visual strategies for remembering and problem-solving to assist patients with memory defects. This three-part paper discusses some of the research in the field of human memory and describes practical applications of these…

Does Cognitive Strategy Training on Word Problems Compensate for Working Memory Capacity in Children with Math Difficulties?

ERIC Educational Resources Information Center

Swanson, H. Lee

2014-01-01

Cognitive strategies are important tools for children with math difficulties (MD) in learning to solve word problems. The effectiveness of strategy training, however, depends on working memory capacity (WMC). Thus, children with MD but with relatively higher WMC are more likely to benefit from strategy training, whereas children with lower WMC may…

[Cognitive functions of school children with normal IQ and histories of severe and early malnutrition].

PubMed

Perales, C G; Heresi, E; Pizarro, F; Colombo, M

1996-12-01

This is a cross section study designed to evaluate the long lasting consequences of early and severe undernutrition on the development of basic cognitive functions. Attention, memory and problem-solving capacity were assessed in a group of 16 school children, who were severely undernourished during the first two years of age. They were compared with a group of 16 children with a normal growth. All subjects, age 8 to 10, had a normal intellectual coefficient and they belonged to the me same socioeconomical level. Memory was measured with a modified version of subtest of digits from WISC; attention was evaluated with a modified version of the Continuous Performance Task and problem-solving was measured with the Anstey Domino Test. A personal computer was used to assess the cognitive functions. The children who were undernourished during infancy presented lower scores in memory (number of the digits) and in problems solving (number of correct answers). They also had a worse performance than the control group in the same response time, when attention was evaluated. These results suggest that early severe undernutrition had deletereous effects on basic cognitive functions.

Learning and Cognition

ERIC Educational Resources Information Center

Gr ver Aukrust, Vibeke, Ed.

2011-01-01

This collection of 58 articles from the recently-published third edition of the International Encyclopedia of Education focuses on learning, memory, attention, problem solving, concept formation, and language. Learning and cognition is the foundation of cognitive psychology and encompasses many topics including attention, memory, categorization,…

INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

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

Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P

2012-10-01

It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms wemore » have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.« less

Aspects of GPU perfomance in algorithms with random memory access

NASA Astrophysics Data System (ADS)

Kashkovsky, Alexander V.; Shershnev, Anton A.; Vashchenkov, Pavel V.

2017-10-01

The numerical code for solving the Boltzmann equation on the hybrid computational cluster using the Direct Simulation Monte Carlo (DSMC) method showed that on Tesla K40 accelerators computational performance drops dramatically with increase of percentage of occupied GPU memory. Testing revealed that memory access time increases tens of times after certain critical percentage of memory is occupied. Moreover, it seems to be the common problem of all NVidia's GPUs arising from its architecture. Few modifications of the numerical algorithm were suggested to overcome this problem. One of them, based on the splitting the memory into "virtual" blocks, resulted in 2.5 times speed up.

Hopfield networks for solving Tower of Hanoi problems

NASA Astrophysics Data System (ADS)

Kaplan, G. B.; Güzeliş, Cüneyt

2001-08-01

In this paper, Hopfield neural networks have been considered in solving the Tower of Hanoi test which is used in the determining of deficit of planning capability of the human prefrontal cortex. The main difference between this paper and the ones in the literature which use neural networks is that the Tower of Hanoi problem has been formulated here as a special shortest-path problem. In the literature, some Hopfield networks are developed for solving the shortest path problem which is a combinatorial optimization problem having a diverse field of application. The approach given in this paper gives the possibility of solving the Tower of Hanoi problem using these Hopfield networks. Also, the paper proposes new Hopfield network models for the shortest path and hence the Tower of Hanoi problems and compares them to the available ones in terms of the memory and time (number of steps) needed in the simulations.

The Role of Executive Function in Arithmetic Problem-Solving Processes: A Study of Third Graders

ERIC Educational Resources Information Center

Viterbori, Paola; Traverso, Laura; Usai, M. Carmen

2017-01-01

This study investigated the roles of different executive function (EF) components (inhibition, shifting, and working memory) in 2-step arithmetic word problem solving. A sample of 139 children aged 8 years old and regularly attending the 3rd grade of primary school were tested on 6 EF tasks measuring different EF components, a reading task and a…

Working memory facilitates insight instead of hindering it: Comment on DeCaro, Van Stockum, and Wieth (2016).

PubMed

Chuderski, Adam; Jastrzębski, Jan

2017-12-01

The "nothing-special" account of insight predicts positive correlations of insight problem solving and working memory capacity (WMC), whereas the "special-process" account expects no, or even negative, correlations. In the latter vein, DeCaro, Van Stockum Jr., and Wieth (2016) have recently reported weak negative WMC correlations with 2 constraint relaxation matchstick problems and 3 insight problems, and thus they claim that WM hinders insight. Here, we report on 3 studies that investigated WMC and various matchstick and classical problems (including 1 study that precisely replicated DeCaro et al.'s procedure). All 3 studies yielded moderate positive correlations of WMC with both the constraint relaxation and the classical problems. WMC explained 10% variance in problem solving, no matter what problems were used or how they were applied. Thus, DeCaro et al.'s claim that WM hinders insight is unwarranted. The opposite is true: WM facilitates insight. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Distributed-Memory Fast Maximal Independent Set

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

Kanewala Appuhamilage, Thejaka Amila J.; Zalewski, Marcin J.; Lumsdaine, Andrew

The Maximal Independent Set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of MIS problems suggests the use of distributed-memory hardware as a cost-effective approach to providing necessary compute and memory resources. Luby proposed four randomized algorithms to solve the MIS problem. All those algorithms are designed focusing on shared-memory machines and are analyzed using the PRAM model. These algorithms do not have direct efficient distributed-memory implementations. In this paper, we extend two of Luby’s seminal MIS algorithms, “Luby(A)” and “Luby(B),” to distributed-memory execution, and we evaluatemore » their performance. We compare our results with the “Filtered MIS” implementation in the Combinatorial BLAS library for two types of synthetic graph inputs.« less

A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

NASA Technical Reports Server (NTRS)

Sartori, Michael A.; Passino, Kevin M.; Antsaklis, Panos J.

1992-01-01

In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

The Astrocentric Hypothesis: proposed role of astrocytes in consciousness and memory formation.

PubMed

Robertson, James M

2002-01-01

Consciousness is self-awareness. This process is closely associated with attention and working memory, a special form of short-term memory, which is vital when solving explicit task. Edelman has equated consciousness as the "remembered present" to highlight the importance of this form of memory (G.M. Edelman, Bright Air, Brilliant Fire, Basic Books, New York, 1992). The majority of other memories are recollections of past events that are encoded, stored, and brought back into consciousness if appropriate for solving new problems. Encoding prior experiences into memories is based on the salience of each event (A.R. Damasio, Descartes' Error, G.P. Putnam's Sons, New York, 1994; G.M. Edelman, Bright Air, Brilliant Fire, Basic Books, New York, 1992). It is proposed that protoplasmic astrocytes bind attended sensory information into consciousness and store encoded memories. This conclusion is supported by research conducted by gliobiologist over the past 15 years. Copyright 2002 Elsevier Science Ltd.

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

PubMed Central

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

2014-01-01

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

Deficits in episodic memory and mental time travel in patients with post-traumatic stress disorder.

PubMed

Zlomuzica, Armin; Woud, Marcella L; Machulska, Alla; Kleimt, Katharina; Dietrich, Lisa; Wolf, Oliver T; Assion, Hans-Joerg; Huston, Joseph P; De Souza Silva, Maria A; Dere, Ekrem; Margraf, Jürgen

2018-04-20

Post-traumatic stress disorder (PTSD) is characterized by impairments in mnestic functions, especially in the domain of episodic memory. These alterations might affect different aspects of episodic memory functioning. Here we tested PTSD patients and healthy controls (matched for age, sex and education) in a newly developed virtual reality episodic memory test (VR-EMT), a test for mental time travel, episodic future thinking, and prospective memory (M3xT). In a cross-validation experiment, their performance was further evaluated in the Rivermead Behavioral Memory Test (RBMT). PTSD patients demonstrated impairments in episodic memory formation and mental time travel and showed difficulties in utilizing information from episodic memory to solve problems. Diminished attention and concentration in PTSD did not account for performance deficits in these tasks but higher levels of negative arousal were found in PTSD patients. Furthermore, performance in the VR-EMT and RBMT in PTSD patients correlated negatively with self-reported measures of stress and depression. Our results suggest that deficits in episodic memory formation and mental time travel in PTSD lead to difficulties in utilizing the content of episodic memories for solving problems in the present or to plan future behavior. Clinical implications of these findings and suggestions for cognitive-behavioral treatment of PTSD are discussed. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed

Perczel Forintos, Dóra; Póos, Judit

2008-01-01

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

Stressors and Caregivers' Depression: Multiple Mediators of Self-Efficacy, Social Support, and Problem-Solving Skill.

PubMed

Tang, Fengyan; Jang, Heejung; Lingler, Jennifer; Tamres, Lisa K; Erlen, Judith A

2015-01-01

Caring for an older adult with memory loss is stressful. Caregiver stress could produce negative outcomes such as depression. Previous research is limited in examining multiple intermediate pathways from caregiver stress to depressive symptoms. This study addresses this limitation by examining the role of self-efficacy, social support, and problem solving in mediating the relationships between caregiver stressors and depressive symptoms. Using a sample of 91 family caregivers, we tested simultaneously multiple mediators between caregiver stressors and depression. Results indicate that self-efficacy mediated the pathway from daily hassles to depression. Findings point to the importance of improving self-efficacy in psychosocial interventions for caregivers of older adults with memory loss.

Constitutive modeling of glassy shape memory polymers

NASA Astrophysics Data System (ADS)

Khanolkar, Mahesh

The aim of this research is to develop constitutive models for non-linear materials. Here, issues related for developing constitutive model for glassy shape memory polymers are addressed in detail. Shape memory polymers are novel material that can be easily formed into complex shapes, retaining memory of their original shape even after undergoing large deformations. The temporary shape is stable and return to the original shape is triggered by a suitable mechanism such heating the polymer above a transition temperature. Glassy shape memory polymers are called glassy because the temporary shape is fixed by the formation of a glassy solid, while return to the original shape is due to the melting of this glassy phase. The constitutive model has been developed to capture the thermo-mechanical behavior of glassy shape memory polymers using elements of nonlinear mechanics and polymer physics. The key feature of this framework is that a body can exist stress free in numerous natural configurations, the underlying natural configuration of the body changing during the process, with the response of the body being elastic from these evolving natural configurations. The aim of this research is to formulate a constitutive model for glassy shape memory polymers (GSMP) which takes in to account the fact that the stress-strain response depends on thermal expansion of polymers. The model developed is for the original amorphous phase, the temporary glassy phase and transition between these phases. The glass transition process has been modeled using a framework that was developed recently for studying crystallization in polymers and is based on the theory of multiple natural configurations. Using the same frame work, the melting of the glassy phase to capture the return of the polymer to its original shape is also modeled. The effect of nanoreinforcement on the response of shape memory polymers (GSMP) is studied and a model is developed. In addition to modeling and solving boundary value problems for GSMP's, problems of importance for CSMP, specifically a shape memory cycle (Torsion of a Cylinder) is solved using the developed crystallizable shape memory polymer model. To solve complex boundary value problems in realistic geometries a user material subroutine (UMAT) for GSMP model has been developed for use in conjunction with the commercial finite element software ABAQUS. The accuracy of the UMAT has been verified by testing it against problems for which the results are known.

Why is working memory capacity related to matrix reasoning tasks?

PubMed

Harrison, Tyler L; Shipstead, Zach; Engle, Randall W

2015-04-01

One of the reasons why working memory capacity is so widely researched is its substantial relationship with fluid intelligence. Although this relationship has been found in numerous studies, researchers have been unable to provide a conclusive answer as to why the two constructs are related. In a recent study, researchers examined which attributes of Raven's Progressive Matrices were most strongly linked with working memory capacity (Wiley, Jarosz, Cushen, & Colflesh, Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 256-263, 2011). In that study, Raven's problems that required a novel combination of rules to solve were more strongly correlated with working memory capacity than were problems that did not. In the present study, we wanted to conceptually replicate the Wiley et al. results while controlling for a few potential confounds. Thus, we experimentally manipulated whether a problem required a novel combination of rules and found that repeated-rule-combination problems were more strongly related to working memory capacity than were novel-rule-combination problems. The relationship to other measures of fluid intelligence did not change based on whether the problem required a novel rule combination.

Coping with challenges to memory in people with mild to moderate Alzheimer's disease: observation of behaviour in response to analogues of everyday situations.

PubMed

Oyebode, Jan Rachel; Motala, Jamilah R; Hardy, Rachel M; Oliver, Chris

2009-01-01

To describe ways of coping in people with mild to moderate AD when faced with situations that are challenging to their memory. Twenty-four participants (12 with mild and 12 with moderate AD) were presented with a set of seven tasks that were analogues of everyday situations that tax memory. The participants' responses were videotaped and analysed. Participants' coping responses were grouped into seven categories to best reflect the main strategies. Individuals used a significantly greater frequency of effortful problem solving (self-reliance and reliance on carers) (p < 0.01) than other ways of coping. Positive acknowledgement of memory difficulties was used significantly more than negative acknowledgement and defensive coping (concealment and avoidance) (p < 0.01). This study used novel methodology of observation of behavioural responses in analogues of everyday situations. The predominance of effortful problem-solving emphasizes the role of the person with AD as an active agent in the management of memory loss. An emphasis in previous literature on defensive coping and denial is counter-balanced by the finding that participants commonly coped by acknowledging their memory impairment.

Dynamically programmable cache

NASA Astrophysics Data System (ADS)

Nakkar, Mouna; Harding, John A.; Schwartz, David A.; Franzon, Paul D.; Conte, Thomas

1998-10-01

Reconfigurable machines have recently been used as co- processors to accelerate the execution of certain algorithms or program subroutines. The problems with the above approach include high reconfiguration time and limited partial reconfiguration. By far the most critical problems are: (1) the small on-chip memory which results in slower execution time, and (2) small FPGA areas that cannot implement large subroutines. Dynamically Programmable Cache (DPC) is a novel architecture for embedded processors which offers solutions to the above problems. To solve memory access problems, DPC processors merge reconfigurable arrays with the data cache at various cache levels to create a multi-level reconfigurable machines. As a result DPC machines have both higher data accessibility and FPGA memory bandwidth. To solve the limited FPGA resource problem, DPC processors implemented multi-context switching (Virtualization) concept. Virtualization allows implementation of large subroutines with fewer FPGA cells. Additionally, DPC processors can parallelize the execution of several operations resulting in faster execution time. In this paper, the speedup improvement for DPC machines are shown to be 5X faster than an Altera FLEX10K FPGA chip and 2X faster than a Sun Ultral SPARC station for two different algorithms (convolution and motion estimation).

Mathematics Learning Development: The Role of Long-Term Retrieval

ERIC Educational Resources Information Center

Calderón-Tena, Carlos O.; Caterino, Linda C.

2016-01-01

This study assessed the relation between long-term memory retrieval and mathematics calculation and mathematics problem solving achievement among elementary, middle, and high school students in nationally representative sample of US students, when controlling for fluid and crystallized intelligence, short-term memory, and processing speed. As…

Soar: A Unified Theory of Cognition?

ERIC Educational Resources Information Center

Waldrop, M. Mitchell

1988-01-01

Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…

Brain Training Draws Questions about Benefits

ERIC Educational Resources Information Center

Sparks, Sarah D.

2012-01-01

While programs to improve students' working memory are among the hottest new education interventions, new studies are calling into question whether exercises to improve this foundational skill can actually translate into greater intelligence, problem-solving ability, or academic achievement. Working memory is the system the mind uses to hold…

Work Strategies: The Development and Testing of a Model.

DTIC Science & Technology

1986-03-01

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

Fractionating the neural correlates of individual working memory components underlying arithmetic problem solving skills in children

PubMed Central

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

2013-01-01

Baddeley and Hitch’s multi-component working memory (WM) model has played an enduring and influential role in our understanding of cognitive abilities. Very little is known, however, about the neural basis of this multi-component WM model and the differential role each component plays in mediating arithmetic problem solving abilities in children. Here, we investigate the neural basis of the central executive (CE), phonological (PL) and visuo-spatial (VS) components of WM during a demanding mental arithmetic task in 7–9 year old children (N=74). The VS component was the strongest predictor of math ability in children and was associated with increased arithmetic complexity-related responses in left dorsolateral and right ventrolateral prefrontal cortices as well as bilateral intra-parietal sulcus and supramarginal gyrus in posterior parietal cortex. Critically, VS, CE and PL abilities were associated with largely distinct patterns of brain response. Overlap between VS and CE components was observed in left supramarginal gyrus and no overlap was observed between VS and PL components. Our findings point to a central role of visuo-spatial WM during arithmetic problem-solving in young grade-school children and highlight the usefulness of the multi-component Baddeley and Hitch WM model in fractionating the neural correlates of arithmetic problem solving during development. PMID:24212504

Cultural differences in complex addition: efficient Chinese versus adaptive Belgians and Canadians.

PubMed

Imbo, Ineke; LeFevre, Jo-Anne

2009-11-01

In the present study, the authors tested the effects of working-memory load on math problem solving in 3 different cultures: Flemish-speaking Belgians, English-speaking Canadians, and Chinese-speaking Chinese currently living in Canada. Participants solved complex addition problems (e.g., 58 + 76) in no-load and working-memory load conditions, in which either the central executive or the phonological loop was loaded. The authors used the choice/no-choice method to obtain unbiased measures of strategy selection and strategy efficiency. The Chinese participants were faster than the Belgians, who were faster and more accurate than the Canadians. The Chinese also required fewer working-memory resources than did the Belgians and Canadians. However, the Chinese chose less adaptively from the available strategies than did the Belgians and Canadians. These cultural differences in math problem solving are likely the result of different instructional approaches during elementary school (practice and training in Asian countries vs. exploration and flexibility in non-Asian countries), differences in the number language, and informal cultural norms and standards. The relevance of being adaptive is discussed as well as the implications of the results in regards to the strategy choice and discovery simulation model of strategy selection (J. Shrager & R. S. Siegler, 1998).

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

NASA Astrophysics Data System (ADS)

Gulacar, Ozcan

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

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

Efficient Parallel Formulations of Hierarchical Methods and Their Applications

NASA Astrophysics Data System (ADS)

Grama, Ananth Y.

1996-01-01

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

Intellectual Abilities That Discriminate Good and Poor Problem Solvers.

ERIC Educational Resources Information Center

Meyer, Ruth Ann

1981-01-01

This study compared good and poor fourth-grade problem solvers on a battery of 19 "reference" tests for verbal, induction, numerical, word fluency, memory, perceptual speed, and simple visualization abilities. Results suggest verbal, numerical, and especially induction abilities are important to successful mathematical problem solving.…

The Relationship between Working Memory and Insight Depends on Moderators: Reply to Chuderski and Jastrzêbski (2017)

ERIC Educational Resources Information Center

DeCaro, Marci S.; Van Stockum, Charles A., Jr.; Wieth, Mareike B.

2017-01-01

Chuderski and Jastrzêbski (2017) found a positive relationship between working memory capacity and insight problem solving, and concluded that "people with less effective cognition" are therefore "less creative" (p. 2003). This interpretation discounts substantial evidence that devoting less executive control facilitates…

Cognitive Predictors of Everyday Problem Solving across the Lifespan.

PubMed

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

2017-01-01

An important aspect of successful aging is maintaining the ability to solve everyday problems encountered in daily life. The limited evidence today suggests that everyday problem solving ability increases from young adulthood to middle age, but decreases in older age. The present study examined age differences in the relative contributions of fluid and crystallized abilities to solving problems on the Everyday Problems Test (EPT). We hypothesized that due to diminishing fluid resources available with advanced age, crystallized knowledge would become increasingly important in predicting everyday problem solving with greater age. Two hundred and twenty-one healthy adults from the Dallas Lifespan Brain Study, aged 24-93 years, completed a cognitive battery that included measures of fluid ability (i.e., processing speed, working memory, inductive reasoning) and crystallized ability (i.e., multiple measures of vocabulary). These measures were used to predict performance on EPT. Everyday problem solving showed an increase in performance from young to early middle age, with performance beginning to decrease at about age of 50 years. As hypothesized, fluid ability was the primary predictor of performance on everyday problem solving for young adults, but with increasing age, crystallized ability became the dominant predictor. This study provides evidence that everyday problem solving ability differs with age, and, more importantly, that the processes underlying it differ with age as well. The findings indicate that older adults increasingly rely on knowledge to support everyday problem solving, whereas young adults rely almost exclusively on fluid intelligence. © 2017 S. Karger AG, Basel.

Age-related changes in strategic variations during arithmetic problem solving: The role of executive control.

PubMed

Hinault, T; Lemaire, P

2016-01-01

In this review, we provide an overview of how age-related changes in executive control influence aging effects in arithmetic processing. More specifically, we consider the role of executive control in strategic variations with age during arithmetic problem solving. Previous studies found that age-related differences in arithmetic performance are associated with strategic variations. That is, when they accomplish arithmetic problem-solving tasks, older adults use fewer strategies than young adults, use strategies in different proportions, and select and execute strategies less efficiently. Here, we review recent evidence, suggesting that age-related changes in inhibition, cognitive flexibility, and working memory processes underlie age-related changes in strategic variations during arithmetic problem solving. We discuss both behavioral and neural mechanisms underlying age-related changes in these executive control processes. © 2016 Elsevier B.V. All rights reserved.

Limited-memory trust-region methods for sparse relaxation

NASA Astrophysics Data System (ADS)

Adhikari, Lasith; DeGuchy, Omar; Erway, Jennifer B.; Lockhart, Shelby; Marcia, Roummel F.

2017-08-01

In this paper, we solve the l2-l1 sparse recovery problem by transforming the objective function of this problem into an unconstrained differentiable function and applying a limited-memory trust-region method. Unlike gradient projection-type methods, which uses only the current gradient, our approach uses gradients from previous iterations to obtain a more accurate Hessian approximation. Numerical experiments show that our proposed approach eliminates spurious solutions more effectively while improving computational time.

Independent Contributions of the Central Executive, Intelligence, and In-Class Attentive Behavior to Developmental Change in the Strategies Used to Solve Addition Problems

ERIC Educational Resources Information Center

Geary, David C.; Hoard, Mary K.; Nugent, Lara

2012-01-01

Children's (N = 275) use of retrieval, decomposition (e.g., 7 = 4+3 and thus 6+7 = 6+4+3), and counting to solve additional problems was longitudinally assessed from first grade to fourth grade, and intelligence, working memory, and in-class attentive behavior was assessed in one or several grades. The goal was to assess the relation between…

Relationship of Selected Abilities to Problem Solving Performance.

ERIC Educational Resources Information Center

Harmel, Sarah Jane

This study investigated five ability tests related to the water-jug problem. Previous analyses identified two processes used during solution: means-ends analysis and memory of visited states. Subjects were 240 undergraduate psychology students. A real-time computer system presented the problem and recorded responses. Ability tests were paper and…

Stressors and Caregivers’ Depression: Multiple Mediators of Self-Efficacy, Social Support, and Problem-solving Skill

PubMed Central

Tang, Fengyan; Jang, Heejung; Lingler, Jennifer; Tamres, Lisa K.; Erlen, Judith A.

2016-01-01

Caring for an older adult with memory loss is stressful. Caregiver stress could produce negative outcomes such as depression. Previous research is limited in examining multiple intermediate pathways from caregiver stress to depressive symptoms. This study addresses this limitation by examining the role of self-efficacy, social support, and problem-solving in mediating the relationships between caregiver stressors and depressive symptoms. Using a sample of 91 family caregivers, we tested simultaneously multiple mediators between caregiver stressors and depression. Results indicate that self-efficacy mediated the pathway from daily hassles to depression. Findings point to the importance of improving self-efficacy in psychosocial interventions for caregivers of older adults with memory loss. PMID:26317766

Cognitive functioning and everyday problem solving in older adults.

PubMed

Burton, Catherine L; Strauss, Esther; Hultsch, David F; Hunter, Michael A

2006-09-01

The relationship between cognitive functioning and a performance-based measure of everyday problem-solving, the Everyday Problems Test (EPT), thought to index instrumental activities of daily living (IADL), was examined in 291 community-dwelling non-demented older adults. Performance on the EPT was found to vary according to age, cognitive status, and education. Hierarchical regression analyses revealed that, after adjusting for demographic and health variables, measures of cognitive functioning accounted for 23.6% of the variance in EPT performance. In particular, measures of global cognitive status, cognitive decline, speed of processing, executive functioning, episodic memory, and verbal ability were significant predictors of EPT performance. These findings suggest that cognitive functioning along with demographic variables are important determinants of everyday problem-solving.

Enhancing chemistry problem-solving achievement using problem categorization

NASA Astrophysics Data System (ADS)

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

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

Parallel 3D-TLM algorithm for simulation of the Earth-ionosphere cavity

NASA Astrophysics Data System (ADS)

Toledo-Redondo, Sergio; Salinas, Alfonso; Morente-Molinera, Juan Antonio; Méndez, Antonio; Fornieles, Jesús; Portí, Jorge; Morente, Juan Antonio

2013-03-01

A parallel 3D algorithm for solving time-domain electromagnetic problems with arbitrary geometries is presented. The technique employed is the Transmission Line Modeling (TLM) method implemented in Shared Memory (SM) environments. The benchmarking performed reveals that the maximum speedup depends on the memory size of the problem as well as multiple hardware factors, like the disposition of CPUs, cache, or memory. A maximum speedup of 15 has been measured for the largest problem. In certain circumstances of low memory requirements, superlinear speedup is achieved using our algorithm. The model is employed to model the Earth-ionosphere cavity, thus enabling a study of the natural electromagnetic phenomena that occur in it. The algorithm allows complete 3D simulations of the cavity with a resolution of 10 km, within a reasonable timescale.

Intellectual system for images restoration

NASA Astrophysics Data System (ADS)

Mardare, Igor

2005-02-01

Intelligence systems on basis of artificial neural networks and associative memory allow to solve effectively problems of recognition and restoration of images. However, within analytical technologies there are no dominating approaches of deciding of intellectual problems. Choice of the best technology depends on nature of problem, features of objects, volume of represented information about the object, number of classes of objects, etc. It is required to determine opportunities, preconditions and field of application of neural networks and associative memory for decision of problem of restoration of images and to use their supplementary benefits for further development of intelligence systems.

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

PubMed Central

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

2016-01-01

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

Impact of ageing on problem size and proactive interference in arithmetic facts solving.

PubMed

Archambeau, Kim; De Visscher, Alice; Noël, Marie-Pascale; Gevers, Wim

2018-02-01

Arithmetic facts (AFs) are required when solving problems such as "3 × 4" and refer to calculations for which the correct answer is retrieved from memory. Currently, two important effects that modulate the performance in AFs have been highlighted: the problem size effect and the proactive interference effect. The aim of this study is to investigate possible age-related changes of the problem size effect and the proactive interference effect in AF solving. To this end, the performance of young and older adults was compared in a multiplication production task. Furthermore, an independent measure of proactive interference was assessed to further define the architecture underlying this effect in multiplication solving. The results indicate that both young and older adults were sensitive to the effects of interference and of the problem size. That is, both interference and problem size affected performance negatively: the time needed to solve a multiplication problem increases as the level of interference and the size of the problem increase. Regarding the effect of ageing, the problem size effect remains constant with age, indicating a preserved AF network in older adults. Interestingly, sensitivity to proactive interference in multiplication solving was less pronounced in older than in younger adults suggesting that part of the proactive interference has been overcome with age.

A Randomized Clinical Trial Comparing Affect Regulation and Social Problem-Solving Psychotherapies for Mothers with Victimization-Related PTSD

ERIC Educational Resources Information Center

Ford, Julian D.; Steinberg, Karen L.; Zhang, Wanli

2011-01-01

Addressing affect dysregulation may provide a complementary alternative or adjunctive approach to the empirically supported trauma memory processing models of cognitive behavior therapy (CBT) for posttraumatic stress disorder (PTSD). A CBT designed to enhance affect regulation without trauma memory processing--trauma affect regulation: guide for…

The Effect of Visual-Chunking-Representation Accommodation on Geometry Testing for Students with Math Disabilities

ERIC Educational Resources Information Center

Zhang, Dake; Ding, Yi; Stegall, Joanna; Mo, Lei

2012-01-01

Students who struggle with learning mathematics often have difficulties with geometry problem solving, which requires strong visual imagery skills. These difficulties have been correlated with deficiencies in visual working memory. Cognitive psychology has shown that chunking of visual items accommodates students' working memory deficits. This…

A Cognitive Model for Exposition of Human Deception and Counterdeception

DTIC Science & Technology

1987-10-01

for understanding deception and counterdeceptlon, for developing related tactics, and for stimulating research in cognitive processes. Further...Processing Resources; Attention) BUFFER MEMORY MANAGER (Local) (Problem Solving; Learning; Procedures) BUFFER MEMORY SENSORS Visual, Auditory ...Perception and Misperception in International Politics, Princeton University Press, Princeton, NJ, 1976. Key, W.B., Subliminal Seduction. New

Working Memory Facilitates Insight Instead of Hindering It: Comment on Decaro, Van Stockum, and Wieth (2016)

ERIC Educational Resources Information Center

Chuderski, Adam; Jastrzebski, Jan

2017-01-01

The "nothing-special" account of insight predicts positive correlations of insight problem solving and working memory capacity (WMC), whereas the "special-process" account expects no, or even negative, correlations. In the latter vein, DeCaro, Van Stockum Jr., and Wieth (2016) have recently reported weak negative WMC…

Theorizing and Measuring Working Memory in First and Second Language Research

ERIC Educational Resources Information Center

Wen, Zhisheng

2014-01-01

Working memory (WM) generally refers to the human ability to temporarily maintain and manipulate a limited amount of information in immediate consciousness when carrying out complex cognitive tasks such as problem-solving and language comprehension. Though much controversy has surrounded the WM concept since its inception by Baddeley & Hitch…

Math and numeracy in young adults with spina bifida and hydrocephalus.

PubMed

Dennis, Maureen; Barnes, Marcia

2002-01-01

The developmental stability of poor math skill was studied in 31 young adults with spina bifida and hydrocephalus (SBH), a neurodevelopmental disorder involving malformations of the brain and spinal cord. Longitudinally, individuals with poor math problem solving as children grew into adults with poor problem solving and limited functional numeracy. As a group, young adults with SBH had poor computation accuracy, computation speed, problem solving, a ndfunctional numeracy. Computation accuracy was related to a supporting cognitive system (working memory for numbers), and functional numeracy was related to one medical history variable (number of lifetime shunt revisions). Adult functional numeracy, but not functional literacy, was predictive of higher levels of social, personal, and community independence.

Cognitive Predictors of Everyday Problem Solving across the Lifespan

PubMed Central

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

2017-01-01

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

The Mark III Hypercube-Ensemble Computers

NASA Technical Reports Server (NTRS)

Peterson, John C.; Tuazon, Jesus O.; Lieberman, Don; Pniel, Moshe

1988-01-01

Mark III Hypercube concept applied in development of series of increasingly powerful computers. Processor of each node of Mark III Hypercube ensemble is specialized computer containing three subprocessors and shared main memory. Solves problem quickly by simultaneously processing part of problem at each such node and passing combined results to host computer. Disciplines benefitting from speed and memory capacity include astrophysics, geophysics, chemistry, weather, high-energy physics, applied mechanics, image processing, oil exploration, aircraft design, and microcircuit design.

Development of Relational Memory Processes in Monkeys

PubMed Central

Alvarado, Maria C.; Malkova, Ludise; Bachevalier, Jocelyne

2016-01-01

The present study tested whether relational memory processes, as measured by the transverse patterning problem, are late-developing in nonhuman primates as they are in humans. Eighteen macaques ranging from 3–36 months of age, were trained to solve a set of visual discriminations that formed the transverse patterning problem. Subjects were trained at 3, 4–6, 12, 15–24 or 36 months of age to solve three discriminations as follows: 1) A+ vs. B-; 2) B+ vs. C-; 3) C+ vs. A. When trained concurrently, subject must adopt a relational strategy to perform accurately on all three problems. All 36 month old monkeys reached the criterion of 90% correct, but only one 24-month-old and one 15-month-old did, initially. Three-month-old infants performed at chance on all problems. Six and 12-month-olds performed at 75–80% correct but used a ‘linear’ or elemental solution (e.g. A>B>C), which only yields correct performance on two problems. Retraining the younger subjects at 12, 24 or 36 months yielded a quantitative improvement on speed of learning, and a qualitative improvement in 24–36 month old monkeys for learning strategy. The results suggest that nonspatial relational memory develops late in macaques (as in humans), maturing between 15 and 24 months of age. PMID:27833046

Fractionating the neural correlates of individual working memory components underlying arithmetic problem solving skills in children.

PubMed

Metcalfe, Arron W S; Ashkenazi, Sarit; Rosenberg-Lee, Miriam; Menon, Vinod

2013-10-01

Baddeley and Hitch's multi-component working memory (WM) model has played an enduring and influential role in our understanding of cognitive abilities. Very little is known, however, about the neural basis of this multi-component WM model and the differential role each component plays in mediating arithmetic problem solving abilities in children. Here, we investigate the neural basis of the central executive (CE), phonological (PL) and visuo-spatial (VS) components of WM during a demanding mental arithmetic task in 7-9 year old children (N=74). The VS component was the strongest predictor of math ability in children and was associated with increased arithmetic complexity-related responses in left dorsolateral and right ventrolateral prefrontal cortices as well as bilateral intra-parietal sulcus and supramarginal gyrus in posterior parietal cortex. Critically, VS, CE and PL abilities were associated with largely distinct patterns of brain response. Overlap between VS and CE components was observed in left supramarginal gyrus and no overlap was observed between VS and PL components. Our findings point to a central role of visuo-spatial WM during arithmetic problem-solving in young grade-school children and highlight the usefulness of the multi-component Baddeley and Hitch WM model in fractionating the neural correlates of arithmetic problem solving during development. Copyright © 2013 Elsevier Ltd. All rights reserved.

Memorizing: a test of untrained mildly mentally retarded children's problem-solving.

PubMed

Belmont, J M; Ferretti, R P; Mitchell, D W

1982-09-01

Forty untrained mildly mentally retarded and 32 untrained nonretarded junior high school students were given eight trails of practice on a self-paced memory problem with lists of letters or words. For each trail a new list was presented, requiring ordered recall of terminal list items followed by ordered recall of initial items. Subgroups of solvers and nonsolvers were identified at each IQ level by a criterion of strict recall accuracy. Direct measures of mnemonic activity showed that over trails, solvers at both IQ levels increasingly fit a theoretically ideal memorization method. At neither IQ level did nonsolvers show similar inventions. On early trials, for both IQ levels, fit to the ideal method was uncorrelated with recall accuracy. On late trials fit and recall were highly correlated at each IQ level and across levels. The results support a problem-solving theory of individual differences in retarded and nonretarded children's memory performances.

Having the Memory of an Elephant: Long-Term Retrieval and the Use of Analogues in Problem Solving

ERIC Educational Resources Information Center

Chen, Zhe; Mo, Lei; Honomichl, Ryan

2004-01-01

The authors report 4 experiments exploring long-term analogical transfer from problem solutions in folk tales participants heard during childhood, many years before encountering the target problems. Substantial culture-specific analogical transfer was found when American and Chinese participants' performance was compared on isomorphs of problems…

Spacing and the Transition from Calculation to Retrieval

ERIC Educational Resources Information Center

Rickard, Timothy C.; Lau, Jonas; Pashler, Harold

2008-01-01

Many arithmetic problems can be solved in two ways: by a calculation involving several steps, and by direct retrieval of the answer. With practice on particular problems, memory retrieval tends to supplant calculation--an important aspect of skill learning. We asked how the distribution of practice on particular problems affects this kind of…

The Contributions of Memory and Vocabulary to Non-Verbal Ability Scores in Adolescents with Intellectual Disability

PubMed Central

Mungkhetklang, Chantanee; Bavin, Edith L.; Crewther, Sheila G.; Goharpey, Nahal; Parsons, Carl

2016-01-01

It is usually assumed that performance on non-verbal intelligence tests reflects visual cognitive processing and that aspects of working memory (WM) will be involved. However, the unique contribution of memory to non-verbal scores is not clear, nor is the unique contribution of vocabulary. Thus, we aimed to investigate these contributions. Non-verbal test scores for 17 individuals with intellectual disability (ID) and 39 children with typical development (TD) of similar mental age were compared to determine the unique contribution of visual and verbal short-term memory (STM) and WM and the additional variance contributed by vocabulary scores. No significant group differences were found in the non-verbal test scores or receptive vocabulary scores, but there was a significant difference in expressive vocabulary. Regression analyses indicate that for the TD group STM and WM (both visual and verbal) contributed similar variance to the non-verbal scores. For the ID group, visual STM and verbal WM contributed most of the variance to the non-verbal test scores. The addition of vocabulary scores to the model contributed greater variance for both groups. More unique variance was contributed by vocabulary than memory for the TD group, whereas for the ID group memory contributed more than vocabulary. Visual and auditory memory and vocabulary contributed significantly to solving visual non-verbal problems for both the TD group and the ID group. However, for each group, there were different weightings of these variables. Our findings indicate that for individuals with TD, vocabulary is the major factor in solving non-verbal problems, not memory, whereas for adolescents with ID, visual STM, and verbal WM are more influential than vocabulary, suggesting different pathways to achieve solutions to non-verbal problems. PMID:28082922

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

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

NASA Technical Reports Server (NTRS)

Sohn, Andrew; Biswas, Rupak

1996-01-01

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

Assessing the role of memory in preschoolers' performance on episodic foresight tasks.

PubMed

Atance, Cristina M; Sommerville, Jessica A

2014-01-01

A total of 48 preschoolers (ages 3, 4, and 5) received four tasks modelled after prior work designed to assess the development of "episodic foresight". For each task, children encountered a problem in one room and, after a brief delay, were given the opportunity in a second room to select an item to solve the problem. Importantly, after selecting an item, children were queried about their memory for the problem. Age-related changes were found both in children's ability to select the correct item and their ability to remember the problem. However, when we controlled for children's memory for the problem, there were no longer significant age-related changes on the item choice measure. These findings suggest that age-related changes in children's performance on these tasks are driven by improvements in children's memory versus improvements in children's future-oriented thinking or "foresight" per se. Our results have important implications for how best to structure tasks to measure children's episodic foresight, and also for the relative role of memory in this task and in episodic foresight more broadly.

Efficient Parallelization of a Dynamic Unstructured Application on the Tera MTA

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak

1999-01-01

The success of parallel computing in solving real-life computationally-intensive problems relies on their efficient mapping and execution on large-scale multiprocessor architectures. Many important applications are both unstructured and dynamic in nature, making their efficient parallel implementation a daunting task. This paper presents the parallelization of a dynamic unstructured mesh adaptation algorithm using three popular programming paradigms on three leading supercomputers. We examine an MPI message-passing implementation on the Cray T3E and the SGI Origin2OOO, a shared-memory implementation using cache coherent nonuniform memory access (CC-NUMA) of the Origin2OOO, and a multi-threaded version on the newly-released Tera Multi-threaded Architecture (MTA). We compare several critical factors of this parallel code development, including runtime, scalability, programmability, and memory overhead. Our overall results demonstrate that multi-threaded systems offer tremendous potential for quickly and efficiently solving some of the most challenging real-life problems on parallel computers.

Cognitive Predictors of Achievement Growth in Mathematics: A Five Year Longitudinal Study

PubMed Central

Geary, David C.

2011-01-01

The study's goal was to identify the beginning of first grade quantitative competencies that predict mathematics achievement start point and growth through fifth grade. Measures of number, counting, and arithmetic competencies were administered in early first grade and used to predict mathematics achievement through fifth (n = 177), while controlling for intelligence, working memory, and processing speed. Multilevel models revealed intelligence, processing speed, and the central executive component of working memory predicted achievement or achievement growth in mathematics and, as a contrast domain, word reading. The phonological loop was uniquely predictive of word reading and the visuospatial sketch pad of mathematics. Early fluency in processing and manipulating numerical set size and Arabic numerals, accurate use of sophisticated counting procedures for solving addition problems, and accuracy in making placements on a mathematical number line were uniquely predictive of mathematics achievement. Use of memory-based processes to solve addition problems predicted mathematics and reading achievement but in different ways. The results identify the early quantitative competencies that uniquely contribute to mathematics learning. PMID:21942667

Binary phase locked loops for Omega receivers

NASA Technical Reports Server (NTRS)

Chamberlin, K.

1974-01-01

An all-digital phase lock loop (PLL) is considered because of a number of problems inherent in an employment of analog PLL. The digital PLL design presented solves these problems. A single loop measures all eight Omega time slots. Memory-aiding leads to the name of this design, the memory-aided phase lock loop (MAPLL). Basic operating principles are discussed and the superiority of MAPLL over the conventional digital phase lock loop with regard to the operational efficiency for Omega applications is demonstrated.

Investigating the role of future thinking in social problem solving.

PubMed

Noreen, Saima; Whyte, Katherine E; Dritschel, Barbara

2015-03-01

There is well-established evidence that both rumination and depressed mood negatively impact the ability to solve social problems. A preliminary stage of the social problem solving process may be the process of catapulting oneself forward in time to think about the consequences of a problem before attempting to solve it. The aim of the present study was to examine how thinking about the consequences of a social problem being resolved or unresolved prior to solving it influences the solution of the problem as a function of levels of rumination and dysphoric mood. Eighty six participants initially completed the Beck Depression Inventory- II (BDI-II) and the Ruminative Response Scale (RRS). They were then presented with six social problems and generated consequences for half of the problems being resolved and half of the problems remaining unresolved. Participants then solved some of the problems, and following a delay, were asked to recall all of the consequences previously generated. Participants reporting higher levels of depressed mood and rumination were less effective at generating problem solutions. Specifically, those reporting higher levels of rumination produced less effective solutions for social problems that they had previously generated unresolved than resolved consequences. We also found that individuals higher in rumination, irrespective of depressed mood recalled more of the unresolved consequences in a subsequent memory test. As participants did not solve problems for scenarios where no consequences were generated, no baseline measure of problem solving was obtained. Our results suggest thinking about the consequences of a problem remaining unresolved may impair the generation of effective solutions in individuals with higher levels of rumination. Copyright © 2014 Elsevier Ltd. All rights reserved.

Calculus Problem Solving Behavior of Mathematic Education Students

NASA Astrophysics Data System (ADS)

Rizal, M.; Mansyur, J.

2017-04-01

The purpose of this study is to obtain a description of the problem-solving behaviour of mathematics education students. The attainment of the purpose consisted of several stages: (1) to gain the subject from the mathematic education of first semester students, each of them who has a high, medium, and low competence of mathematic case. (2) To give two mathematical problems with different characteristics. The first problem (M1), the statement does not lead to a resolution. The second problem (M2), a statement leads to problem-solving. (3) To explore the behaviour of problem-solving based on the step of Polya (Rizal, 2011) by way of thinking aloud and in-depth interviews. The obtained data are analysed as suggested by Miles and Huberman (1994) but at first, time triangulation is done or data’s credibility by providing equivalent problem contexts and at different times. The results show that the behavioral problem solvers (mathematic education students) who are capable of high mathematic competency (ST). In understanding M1, ST is more likely to pay attention to an image first, read the texts piecemeal and repeatedly, then as a whole and more focus to the sentences that contain equations, numbers or symbols. As a result, not all information can be received well. When understanding the M2, ST can link the information from a problem that is stored in the working memory to the information on the long-term memory. ST makes planning to the solution of M1 and M2 by using a formula based on similar experiences which have been ever received before. Another case when implementing the troubleshooting plans, ST complete the M1 according to the plan, but not all can be resolved correctly. In contrast to the implementation of the solving plan of M2, ST can solve the problem according to plan quickly and correctly. According to the solving result of M1 and M2, ST conducts by reading the job based on an algorithm and reasonability. Furthermore, when SS and SR understand the problem of M1 and M2 similar to the ST’s, but both of the problem solvers read the questions with not complete so that they cannot pay attention to the questions of the problems. SS and SR create and execute M2 plan same as ST, but for M1, SS and SR cannot do it, but only active on reading the statement of the problem. On the checking of the M2 task, SS and SR retrace the task according to the used formula.

Short-Term Memories in "Drosophila" Are Governed by General and Specific Genetic Systems

ERIC Educational Resources Information Center

Zars, Troy

2010-01-01

In a dynamic environment, there is an adaptive value in the ability of animals to acquire and express memories. That both simple and complex animals can learn is therefore not surprising. How animals have solved this problem genetically and anatomically probably lies somewhere in a range between a single molecular/anatomical mechanism that applies…

Accounting for Individual Variability in Inversion Shortcut Use

ERIC Educational Resources Information Center

Dube, Adam K.; Robinson, Katherine M.

2010-01-01

This study investigated whether children's inversion shortcut use (i.e., reasoning that no calculations are required for the problem 4 x 8 divided by 8, as the answer is the first number) is related to their analogical reasoning ability, short-term memory capacity, and working memory capacity. Children from Grades 6 and 8 solved multiplication and…

Lesion mapping of social problem solving

PubMed Central

Colom, Roberto; Paul, Erick J.; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H.

2014-01-01

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion–symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. PMID:25070511

How Does a Child Solve 7 + 8? Decoding Brain Activity Patterns Associated with Counting and Retrieval Strategies

ERIC Educational Resources Information Center

Cho, Soohyun; Ryali, Srikanth; Geary, David C.; Menon, Vinod

2011-01-01

Cognitive development and learning are characterized by diminished reliance on effortful procedures and increased use of memory-based problem solving. Here we identify the neural correlates of this strategy shift in 7-9-year-old children at an important developmental period for arithmetic skill acquisition. Univariate and multivariate approaches…

Cognitive Psychology and Mathematical Thinking.

ERIC Educational Resources Information Center

Greer, Brian

1981-01-01

This review illustrates aspects of cognitive psychology relevant to the understanding of how people think mathematically. Developments in memory research, artificial intelligence, visually mediated processes, and problem-solving research are discussed. (MP)

Writing Plays Using Creative Problem-Solving.

ERIC Educational Resources Information Center

Raiser, Lynne; Hinson, Shirley

1995-01-01

This article describes a project which involved inner city elementary grade children with disabilities in writing and performing their own plays. A four-step playwriting process focuses on theme and character development, problem finding, and writing dialogue. The project has led to improved reading skills, attention, memory skills,…

[Subjective memory complaints, perceived stress and coping strategies in young adults].

PubMed

Molina-Rodriguez, Sergio; Pellicer-Porcar, Olga; Mirete-Fructuoso, Marcos; Martinez-Amoros, Estefanía

2016-04-16

Subjective memory complaints are becoming more and more frequent among young adults. There are currently no studies in the literature that analyse the relation among memory complaints, perceived stress and coping strategies as a whole in young adults. To determine the contribution made by perceived stress and different coping strategies on subjective memory complaints in healthy young adults. The sample consisted of 299 university students, of whom 71.6% were women, with a mean age of 22.54 ± 4.73 years. The variable 'memory complaints' was measured with the memory failures questionnaire; the variable 'perceived stress' was measured with the perceived stress scale, and the variables referring to coping strategies were measured using the coping strategies inventory. The variables that made a higher contribution to the variance of the memory complaints are, first, perceived stress and positive problem-focused coping strategies, and, second, negative coping strategies focused on the emotion and on the problem. The positive emotion-focused coping strategies do not make any contribution. Again we find evidence of the influence of stress on memory processes. The use of positive problem-focused coping strategies, such as cognitive restructuring and problem-solving, can be beneficial to lessen the presence of memory complaints. Further research on this matter is warranted.

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

PubMed

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

2016-07-01

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

Impaired memory for material related to a problem solved prior to encoding: suppression at learning or interference at recall?

PubMed

Kowalczyk, Marek

2017-07-01

Earlier research by the author revealed that material encoded incidentally in a speeded affective classification task and related to the demands of a divergent problem tends to be recalled worse in participants who solved the problem prior to encoding than in participants in the control, no-problem condition. The aim of the present experiment was to replicate this effect with a new, size-comparison orienting task, and to test for possible mechanisms of impaired recall. Participants either solved a problem before the orienting task or not, and classified each item in this task either once or three times. There was a reliable effect of impaired recall of problem-related items in the repetition condition, but not in the no-repetition condition. Solving the problem did not influence repetition priming for these items. These results support an account that attributes the impaired recall to inhibitory processes at learning and speak against a proactive interference explanation. However, they can be also accommodated by an account that refers to inefficient context cues and competitor interference at retrieval.

Optical memory development. Volume 2: Gain-assisted holographic storage media

NASA Technical Reports Server (NTRS)

Gange, R. A.; Mezrich, R. S.

1972-01-01

Thin deformable films were investigated for use as the storage medium in a holographic optical memory. The research was directed toward solving the problems of material fatigue, selective heat addressing, electrical charging of the film surface and charge patterning by light. A number of solutions to these problems were found but the main conclusion to be drawn from the work is that deformable media which employ heat in the recording process are not satisfactory for use in a high-speed random-access read/write holographic memory. They are, however, a viable approach in applications where either high speed or random-access is not required.

A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State

PubMed Central

2016-01-01

Identifying the hidden state is important for solving problems with hidden state. We prove any deterministic partially observable Markov decision processes (POMDP) can be represented by a minimal, looping hidden state transition model and propose a heuristic state transition model constructing algorithm. A new spatiotemporal associative memory network (STAMN) is proposed to realize the minimal, looping hidden state transition model. STAMN utilizes the neuroactivity decay to realize the short-term memory, connection weights between different nodes to represent long-term memory, presynaptic potentials, and synchronized activation mechanism to complete identifying and recalling simultaneously. Finally, we give the empirical illustrations of the STAMN and compare the performance of the STAMN model with that of other methods. PMID:27891146

Cognitive and Linguistic Predictors of Mathematical Word Problems With and Without Irrelevant Information.

PubMed

Wang, Amber Y; Fuchs, Lynn S; Fuchs, Douglas

2016-12-01

The purpose of this study was to identify cognitive and linguistic predictors of word problems with versus without irrelevant information. The sample was 701 2nd-grade students who received no specialized intervention on word problems. In the fall, they were assessed on initial arithmetic and word-problem skill as well as language ability, working memory capacity, and processing speed; in the spring, they were tested on a word-problem measure that included items with versus without irrelevant information. Significant predictors common to both forms of word problems were initial arithmetic and word problem-solving skill as well as language and working memory. Nonverbal reasoning predicted word problems with irrelevant information, but not word problems without irrelevant information. Findings are discussed in terms of implications for intervention and future research.

ADD, LD and Extended Information Processing.

ERIC Educational Resources Information Center

Stolzenberg, J. B.; Cherkes-Julkowski, M.

This study examines executive function and its relationship to attention dysfunction and working memory. It attempts to document the manifestations of executive function problems in school-related extended processing tasks, such as verbal problem-solving in math and reading of extended passages. Subjects (in grades 1-12) included 49 children with…

Adaptive Memory: Ancestral Priorities and the Mnemonic Value of Survival Processing

ERIC Educational Resources Information Center

Nairne, James S.; Pandeirada, Josefa N. S.

2010-01-01

Evolutionary psychologists often propose that humans carry around "stone-age" brains, along with a toolkit of cognitive adaptations designed originally to solve hunter-gatherer problems. This perspective predicts that optimal cognitive performance might sometimes be induced by ancestrally-based problems, those present in ancestral environments,…

Memory flexibility training for autobiographical memory as an intervention for maintaining social and mental well-being in older adults.

PubMed

Leahy, Fiona; Ridout, Nathan; Holland, Carol

2018-05-07

Autobiographical memory specificity (AMS) reduces with increasing age and is associated with depression, social problem-solving and functional limitations. However, ability to switch between general and specific, as well as between positive and negative retrieval, may be more important for the strategic use of autobiographical information in everyday life. Ability to switch between retrieval modes is likely to rely on aspects of executive function. We propose that age-related deficits in cognitive flexibility impair AMS, but the "positivity effect" protects positively valenced memories from impaired specificity. A training programme to improve the ability to flexibly retrieve different types of memories in depressed adults (MemFlex) was examined in non-depressed older adults to determine effects on AMS, valence and the executive functions underlying cognitive flexibility. Thirty-nine participants aged 70+ (MemFlex, n = 20; control, n = 19) took part. AMS and the inhibition aspect of executive function improved in both groups, suggesting these abilities are amenable to change, although not differentially affected by this type of training. Lower baseline inhibition scores correlated with increased negative, but not positive AMS, suggesting that positive AMS is an automatic process in older adults. Changes in AMS correlated with changes in social problem-solving, emphasising the usefulness of AMs in a social environment.

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.

Efficient checkpointing schemes for depletion perturbation solutions on memory-limited architectures

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

Stripling, H. F.; Adams, M. L.; Hawkins, W. D.

2013-07-01

We describe a methodology for decreasing the memory footprint and machine I/O load associated with the need to access a forward solution during an adjoint solve. Specifically, we are interested in the depletion perturbation equations, where terms in the adjoint Bateman and transport equations depend on the forward flux solution. Checkpointing is the procedure of storing snapshots of the forward solution to disk and using these snapshots to recompute the parts of the forward solution that are necessary for the adjoint solve. For large problems, however, the storage cost of just a few copies of an angular flux vector canmore » exceed the available RAM on the host machine. We propose a methodology that does not checkpoint the angular flux vector; instead, we write and store converged source moments, which are typically of a much lower dimension than the angular flux solution. This reduces the memory footprint and I/O load of the problem, but requires that we perform single sweeps to reconstruct flux vectors on demand. We argue that this trade-off is exactly the kind of algorithm that will scale on advanced, memory-limited architectures. We analyze the cost, in terms of FLOPS and memory footprint, of five checkpointing schemes. We also provide computational results that support the analysis and show that the memory-for-work trade off does improve time to solution. (authors)« less

The representation of multiplication and division facts in memory.

PubMed

De Brauwer, Jolien; Fias, Wim

2011-01-01

Recently, using a training paradigm, Campbell and Agnew (2009) observed cross-operation response time savings with nonidentical elements (e.g., practice 3 + 2, test 5 - 2) for addition and subtraction, showing that a single memory representation underlies addition and subtraction performance. Evidence for cross-operation savings between multiplication and division have been described frequently (e.g., Campbell, Fuchs-Lacelle, & Phenix, 2006) but they have always been attributed to a mediation strategy (reformulating a division problem as a multiplication problem, e.g., Campbell et al., 2006). Campbell and Agnew (2009) therefore concluded that there exists a fundamental difference between addition and subtraction on the one hand and multiplication and division on the other hand. However, our results suggest that retrieval savings between inverse multiplication and division problems can be observed. Even for small problems (solved by direct retrieval) practicing a division problem facilitated the corresponding multiplication problem and vice versa. These findings indicate that shared memory representations underlie multiplication and division retrieval. Hence, memory and learning processes do not seem to differ fundamentally between addition-subtraction and multiplication-division.

The Co-Development of Skill at and Preference for Use of Retrieval-Based Processes for Solving Addition Problems: Individual and Sex Differences from First to Sixth Grade

PubMed Central

Bailey, Drew H.; Littlefield, Andrew; Geary, David C.

2012-01-01

The ability to retrieve basic arithmetic facts from long-term memory contributes to individual and perhaps sex differences in mathematics achievement. The current study tracked the co-development of preference for using retrieval over other strategies to solve single-digit addition problems, independent of accuracy, and skilled use of retrieval (i.e., accuracy and RT) from first to sixth grade, inclusive (n = 311). Accurate retrieval in first grade was related to working memory capacity and intelligence and predicted a preference for retrieval in second grade. In later grades, the relation between skill and preference changed such that preference in one grade predicted accuracy and RT in the next, as RT and accuracy continued to predict future gains in preference. In comparison to girls, boys had a consistent preference for retrieval over other strategies and had faster retrieval speeds, but the sex difference in retrieval accuracy varied across grades. Results indicate ability influences early skilled retrieval but both practice and skill influence each other in a feedback loop later in development, and provide insights into the source of the sex difference in problem solving approaches. PMID:22704036

Executive Functions Contribute Uniquely to Reading Competence in Minority Youth.

PubMed

Jacobson, Lisa A; Koriakin, Taylor; Lipkin, Paul; Boada, Richard; Frijters, Jan C; Lovett, Maureen W; Hill, Dina; Willcutt, Erik; Gottwald, Stephanie; Wolf, Maryanne; Bosson-Heenan, Joan; Gruen, Jeffrey R; Mahone, E Mark

Competent reading requires various skills beyond those for basic word reading (i.e., core language skills, rapid naming, phonological processing). Contributing "higher-level" or domain-general processes include information processing speed and executive functions (working memory, strategic problem solving, attentional switching). Research in this area has relied on largely Caucasian samples, with limited representation of children from racial or ethnic minority groups. This study examined contributions of executive skills to reading competence in 761 children of minority backgrounds. Hierarchical linear regressions examined unique contributions of executive functions (EF) to word reading, fluency, and comprehension. EF contributed uniquely to reading performance, over and above reading-related language skills; working memory contributed uniquely to all components of reading; while attentional switching, but not problem solving, contributed to isolated and contextual word reading and reading fluency. Problem solving uniquely predicted comprehension, suggesting that this skill may be especially important for reading comprehension in minority youth. Attentional switching may play a unique role in development of reading fluency in minority youth, perhaps as a result of the increased demand for switching between spoken versus written dialects. Findings have implications for educational and clinical practice with regard to reading instruction, remedial reading intervention, and assessment of individuals with reading difficulty.

Toward High-Performance Communications Interfaces for Science Problem Solving

NASA Astrophysics Data System (ADS)

Oviatt, Sharon L.; Cohen, Adrienne O.

2010-12-01

From a theoretical viewpoint, educational interfaces that facilitate communicative actions involving representations central to a domain can maximize students' effort associated with constructing new schemas. In addition, interfaces that minimize working memory demands due to the interface per se, for example by mimicking existing non-digital work practice, can preserve students' attentional focus on their learning task. In this research, we asked the question: What type of interface input capabilities provide best support for science problem solving in both low- and high- performing students? High school students' ability to solve a diverse range of biology problems was compared over longitudinal sessions while they used: (1) hardcopy paper and pencil (2) a digital paper and pen interface (3) pen tablet interface, and (4) graphical tablet interface. Post-test evaluations revealed that time to solve problems, meta-cognitive control, solution correctness, and memory all were significantly enhanced when using the digital pen and paper interface, compared with tablet interfaces. The tangible pen and paper interface also was the only alternative that significantly facilitated skill acquisition in low-performing students. Paradoxically, all students nonetheless believed that the tablet interfaces provided best support for their performance, revealing a lack of self-awareness about how to use computational tools to best advantage. Implications are discussed for how pen interfaces can be optimized for future educational purposes, and for establishing technology fluency curricula to improve students' awareness of the impact of digital tools on their performance.

Optimization of memory use of fragment extension-based protein-ligand docking with an original fast minimum cost flow algorithm.

PubMed

Yanagisawa, Keisuke; Komine, Shunta; Kubota, Rikuto; Ohue, Masahito; Akiyama, Yutaka

2018-06-01

The need to accelerate large-scale protein-ligand docking in virtual screening against a huge compound database led researchers to propose a strategy that entails memorizing the evaluation result of the partial structure of a compound and reusing it to evaluate other compounds. However, the previous method required frequent disk accesses, resulting in insufficient acceleration. Thus, more efficient memory usage can be expected to lead to further acceleration, and optimal memory usage could be achieved by solving the minimum cost flow problem. In this research, we propose a fast algorithm for the minimum cost flow problem utilizing the characteristics of the graph generated for this problem as constraints. The proposed algorithm, which optimized memory usage, was approximately seven times faster compared to existing minimum cost flow algorithms. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Improving Problem Solving in Primary School Students: The Effect of a Training Programme Focusing on Metacognition and Working Memory

ERIC Educational Resources Information Center

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

2015-01-01

Background: Despite doubts voiced on their efficacy, a series of studies has been carried out on the capacity of training programmes to improve academic and reasoning skills by focusing on underlying cognitive abilities and working memory in particular. No systematic efforts have been made, however, to test training programmes that involve both…

Effects of Visual Working Memory Training and Direct Instruction on Geometry Problem Solving in Students with Geometry Difficulties

ERIC Educational Resources Information Center

Zhang, Dake

2017-01-01

We examined the effectiveness of (a) a working memory (WM) training program and (b) a combination program involving both WM training and direct instruction for students with geometry difficulties (GD). Four students with GD participated. A multiple-baseline design across participants was employed. During the Phase 1, students received six sessions…

ConfChem Conference on Flipped Classroom: Time-Saving Resources Aligned with Cognitive Science to Help Instructors

ERIC Educational Resources Information Center

Hartman, JudithAnn R.; Dahm, Donald J.; Nelson, Eric A.

2015-01-01

Studies in cognitive science have verified that working memory (where the brain solves problems) can manipulate nearly all elements of knowledge that can be recalled automatically from long-term memory, but only a few elements that have not previously been well memorized. Research in reading comprehension has found that "lecture notes with…

The Effect of Pressure on High- and Low-Working-Memory Students: An Elaboration of the Choking under Pressure Hypothesis

ERIC Educational Resources Information Center

Wang, Zuowei; Shah, Priti

2014-01-01

Sample: Fifty-three third and fourth graders from China participated in this study. Method: Participants' working memory (WM) was assessed by the Automated Operation Span task. Then, they solved mental addition problems of different types under low- and high-pressure conditions. Performance was analysed as a function of pressure condition, working…

Remembering the past and imagining the future: Identifying and enhancing the contribution of episodic memory

PubMed Central

Schacter, Daniel L; Madore, Kevin P

2016-01-01

Recent studies have shown that imagining or simulating future events relies on many of the same cognitive and neural processes as remembering past events. According to the constructive episodic simulation hypothesis (Schacter and Addis, 2007), such overlap indicates that both remembered past and imagined future events rely heavily on episodic memory: future simulations are built on retrieved details of specific past experiences that are recombined into novel events. An alternative possibility is that commonalities between remembering and imagining reflect the influence of more general, non-episodic factors such as narrative style or communicative goals that shape the expression of both memory and imagination. We consider recent studies that distinguish the contributions of episodic and non-episodic processes in remembering the past and imagining the future by using an episodic specificity induction – brief training in recollecting the details of a past experience – and also extend this approach to the domains of problem solving and creative thinking. We conclude by suggesting that the specificity induction may target a process of scene construction that contributes to episodic memory as well as to imagination, problem solving, and creative thinking. PMID:28163775

Reduced memory specificity predicts the acquisition of problem solving skills in psychoeducation.

PubMed

Van Daele, Tom; Van den Bergh, Omer; Van Audenhove, Chantal; Raes, Filip; Hermans, Dirk

2013-03-01

Research has shown that overgeneral autobiographical memory (OGM) is a valid predictor for the course of depression. It is not known, however, whether OGM also moderates information uptake and consolidation in a psychoeducation program to prevent stress, anxiety and depression. The present study was designed to investigate whether the Autobiographical Memory Test (AMT; Williams, & Broadbent, 1986) is a valid predictor for the actual unfolding of skills learned through psychoeducation. The questionnaire included primarily the AMT and the Stress Anxiety Depression Means-Ends Problem Solving Questionnaire (SAD-MEPS). It was filled in prior to and after the psychoeducational course by 23 participants. Correlations were calculated for the AMT at baseline and the differences between the pre and post measurements on the SAD-MEPS. Significant correlations were observed between the number of specific responses and the changes in the number of relevant means (r = .49, p < .01). The sample size was rather small, but several checks were able to reduce the chance of spurious findings. These findings may have important implications for the guidance to and the setup of psychoeducational interventions. Suggestions include screening and memory specificity training prior to course commencement. Copyright © 2011 Elsevier Ltd. All rights reserved.

Spatial anxiety relates to spatial abilities as a function of working memory in children.

PubMed

Ramirez, Gerardo; Gunderson, Elizabeth A; Levine, Susan C; Beilock, Sian L

2012-01-01

Spatial ability is a strong predictor of students' pursuit of higher education in science and mathematics. However, very little is known about the affective factors that influence individual differences in spatial ability, particularly at a young age. We examine the role of spatial anxiety in young children's performance on a mental rotation task. We show that even at a young age, children report experiencing feelings of nervousness at the prospect of engaging in spatial activities. Moreover, we show that these feelings are associated with reduced mental rotation ability among students with high but not low working memory (WM). Interestingly, this WM × spatial anxiety interaction was only found among girls. We discuss these patterns of results in terms of the problem-solving strategies that boys versus girls use in solving mental rotation problems.

Burn Injuries and Their Impact on Cognitive-Communication Skills in the Inpatient Rehabilitation Setting.

PubMed

Hendricks, Carla Tierney; Camara, Kristin; Violick Boole, Kathryn; Napoli, Maureen F; Goldstein, Richard; Ryan, Colleen M; Schneider, Jeffrey C

The prevalence and extent of cognitive-communication disorders and factors that have impact on outcomes are examined in the burn population within an inpatient rehabilitation facility. A retrospective data analysis was conducted on adults diagnosed with burn injury (n = 144). Descriptive statistics were used to identify the prevalence of cognitive-communication deficits on admission and discharge. The main outcomes were cognitive-communication ratings on discharge from inpatient rehabilitation as measured by the memory and problem-solving domains of the Functional Independence Measure (FIM) and composite score of the Functional Communication Measure (FCM). Medical, demographic and rehabilitation predictors of the main outcomes were assessed using regression analyses. On admission to inpatient rehabilitation, 79% of the total population presented with cognitive-communication impairments, and of them, 27% presented with persistent deficits on discharge. Admission FIM memory score, marital status, and age were significant predictors of discharge FIM memory score. Admission FIM problem-solving score, age, marital status, and prehospital living-with were significant predictors of discharge FIM problem-solving score. Admission FCM score and age were significant predictors of discharge FCM cognitive score. Persons with burn injuries are at risk for cognitive-communication impairments, which may persist after inpatient rehabilitation. FIM data obtained on admission can be used as a screening tool to identify these at-risk patients. Future work is needed to assess the efficacy of speech-language pathologist intervention for cognitive-communication deficits within the burn injury population.

FOURTH SEMINAR TO THE MEMORY OF D.N. KLYSHKO: Algebraic solution of the synthesis problem for coded sequences

NASA Astrophysics Data System (ADS)

Leukhin, Anatolii N.

2005-08-01

The algebraic solution of a 'complex' problem of synthesis of phase-coded (PC) sequences with the zero level of side lobes of the cyclic autocorrelation function (ACF) is proposed. It is shown that the solution of the synthesis problem is connected with the existence of difference sets for a given code dimension. The problem of estimating the number of possible code combinations for a given code dimension is solved. It is pointed out that the problem of synthesis of PC sequences is related to the fundamental problems of discrete mathematics and, first of all, to a number of combinatorial problems, which can be solved, as the number factorisation problem, by algebraic methods by using the theory of Galois fields and groups.

A Comparison of Updating Processes in Children Good or Poor in Arithmetic Word Problem-Solving

ERIC Educational Resources Information Center

Passolunghi, Maria Chiara; Pazzaglia, Francesca

2005-01-01

This study examines the updating ability of poor or good problem solvers. Seventy-eight fourth-graders, 43 good and 35 poor arithmetic word problem-solvers, performed the Updating Test used in Palladino et al. [Palladino, P., Cornoldi, C., De Beni, R., and Pazzaglia F. (2002). Working memory and updating processes in reading comprehension. Memory…

An illustrated heuristic prototype facilitates scientific inventive problem solving: A functional magnetic resonance imaging study.

PubMed

Tong, Dandan; Li, Wenfu; Tang, Chaoying; Yang, Wenjing; Tian, Yan; Zhang, Lei; Zhang, Meng; Qiu, Jiang; Liu, Yijun; Zhang, Qinglin

2015-07-01

Many scientific inventions (SI) throughout history were inspired by heuristic prototypes (HPs). For instance, an event or piece of knowledge similar to displaced water from a tub inspired Archimedes' principle. However, the neural mechanisms underlying this insightful problem solving are not very clear. Thus, the present study explored the neural correlates used to solve SI problems facilitated by HPs. Each HP had two versions: a literal description with an illustration (LDI) and a literal description with no illustration (LDNI). Thirty-two participants were divided randomly into these two groups. Blood oxygenation level-dependent fMRI contrasts between LDI and LDNI groups were measured. Greater activity in the right middle occipital gyrus (RMOG, BA19), right precentral gyrus (RPCG, BA4), and left middle frontal gyrus (LMFG, BA46) were found within the LDI group as compared to the LDNI group. We discuss these results in terms cognitive functions within these regions related to problem solving and memory retrieval. Copyright © 2015 Elsevier Inc. All rights reserved.

Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

NASA Technical Reports Server (NTRS)

Sues, R. H.; Lua, Y. J.; Smith, M. D.

1994-01-01

The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations.

Content-addressable read/write memories for image analysis

NASA Technical Reports Server (NTRS)

Snyder, W. E.; Savage, C. D.

1982-01-01

The commonly encountered image analysis problems of region labeling and clustering are found to be cases of search-and-rename problem which can be solved in parallel by a system architecture that is inherently suitable for VLSI implementation. This architecture is a novel form of content-addressable memory (CAM) which provides parallel search and update functions, allowing speed reductions down to constant time per operation. It has been proposed in related investigations by Hall (1981) that, with VLSI, CAM-based structures with enhanced instruction sets for general purpose processing will be feasible.

Self-help memory training for healthy older adults in a residential care center: specific and transfer effects on performance and beliefs.

PubMed

Cavallini, Elena; Bottiroli, Sara; Capotosto, Emanuela; De Beni, Rossana; Pavan, Giorgio; Vecchi, Tomaso; Borella, Erika

2015-08-01

Cognitive flexibility has repeatedly been shown to improve after training programs in community-dwelling older adults, but few studies have focused on healthy older adults living in other settings. This study investigated the efficacy of self-help training for healthy older adults in a residential care center on memory tasks they practiced (associative and object list learning tasks) and any transfer to other tasks (grocery lists, face-name learning, figure-word pairing, word lists, and text learning). Transfer effects on everyday life (using a problem-solving task) and on participants' beliefs regarding their memory (efficacy and control) were also examined. With the aid of a manual, the training adopted a learner-oriented approach that directly encouraged learners to generalize strategic behavior to new tasks. The maintenance of any training benefits was assessed after 6 months. The study involved 34 residential care center residents (aged 70-99 years old) with no cognitive impairments who were randomly assigned to two programs: the experimental group followed the self-help training program, whereas the active control group was involved in general cognitive stimulation activities. Training benefits emerged in the trained group for the tasks that were practiced. Transfer effects were found in memory and everyday problem-solving tasks and on memory beliefs. The effects of training were generally maintained in both practiced and unpracticed memory tasks. These results demonstrate that learner-oriented self-help training enhances memory performance and memory beliefs, in the short term at least, even in residential care center residents. Copyright © 2014 John Wiley & Sons, Ltd.

GASOLINE: Smoothed Particle Hydrodynamics (SPH) code

NASA Astrophysics Data System (ADS)

N-Body Shop

2017-10-01

Gasoline solves the equations of gravity and hydrodynamics in astrophysical problems, including simulations of planets, stars, and galaxies. It uses an SPH method that features correct mixing behavior in multiphase fluids and minimal artificial viscosity. This method is identical to the SPH method used in the ChaNGa code (ascl:1105.005), allowing users to extend results to problems requiring >100,000 cores. Gasoline uses a fast, memory-efficient O(N log N) KD-Tree to solve Poisson's Equation for gravity and avoids artificial viscosity in non-shocking compressive flows.

21st Century Human Performance.

ERIC Educational Resources Information Center

Clark, Ruth Colvin

1995-01-01

Technology can extend human memory and improve performance, but bypassing human intelligence has its dangers. Cognitive apprenticeships that compress learning experiences, provide coaching, and allow trial and error can build complex problem-solving skills and develop expertise. (SK)

Parallel Optimization of Polynomials for Large-scale Problems in Stability and Control

NASA Astrophysics Data System (ADS)

Kamyar, Reza

In this thesis, we focus on some of the NP-hard problems in control theory. Thanks to the converse Lyapunov theory, these problems can often be modeled as optimization over polynomials. To avoid the problem of intractability, we establish a trade off between accuracy and complexity. In particular, we develop a sequence of tractable optimization problems --- in the form of Linear Programs (LPs) and/or Semi-Definite Programs (SDPs) --- whose solutions converge to the exact solution of the NP-hard problem. However, the computational and memory complexity of these LPs and SDPs grow exponentially with the progress of the sequence - meaning that improving the accuracy of the solutions requires solving SDPs with tens of thousands of decision variables and constraints. Setting up and solving such problems is a significant challenge. The existing optimization algorithms and software are only designed to use desktop computers or small cluster computers --- machines which do not have sufficient memory for solving such large SDPs. Moreover, the speed-up of these algorithms does not scale beyond dozens of processors. This in fact is the reason we seek parallel algorithms for setting-up and solving large SDPs on large cluster- and/or super-computers. We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to efficiently utilize hundreds and potentially thousands of processors, and analyze systems with 100+ dimensional state-space. Furthermore, we extend our algorithms to analyze robust stability over more complicated geometries such as hypercubes and arbitrary convex polytopes. Our algorithms can be readily extended to address a wide variety of problems in control such as Hinfinity synthesis for systems with parametric uncertainty and computing control Lyapunov functions.

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.

Cognitive and Linguistic Predictors of Mathematical Word Problems With and Without Irrelevant Information

PubMed Central

Fuchs, Lynn S.; Fuchs, Douglas

2016-01-01

The purpose of this study was to identify cognitive and linguistic predictors of word problems with versus without irrelevant information. The sample was 701 2nd-grade students who received no specialized intervention on word problems. In the fall, they were assessed on initial arithmetic and word-problem skill as well as language ability, working memory capacity, and processing speed; in the spring, they were tested on a word-problem measure that included items with versus without irrelevant information. Significant predictors common to both forms of word problems were initial arithmetic and word problem-solving skill as well as language and working memory. Nonverbal reasoning predicted word problems with irrelevant information, but not word problems without irrelevant information. Findings are discussed in terms of implications for intervention and future research. PMID:28190942

Working Memory Underpins Cognitive Development, Learning, and Education

PubMed Central

Cowan, Nelson

2014-01-01

Working memory is the retention of a small amount of information in a readily accessible form. It facilitates planning, comprehension, reasoning, and problem-solving. I examine the historical roots and conceptual development of the concept and the theoretical and practical implications of current debates about working memory mechanisms. Then I explore the nature of cognitive developmental improvements in working memory, the role of working memory in learning, and some potential implications of working memory and its development for the education of children and adults. The use of working memory is quite ubiquitous in human thought, but the best way to improve education using what we know about working memory is still controversial. I hope to provide some directions for research and educational practice. PMID:25346585

Text Comprehension and Oral Language as Predictors of Word-Problem Solving: Insights into Word-Problem Solving as a Form of Text Comprehension

PubMed Central

Fuchs, Lynn S.; Gilbert, Jennifer K.; Fuchs, Douglas; Seethaler, Pamela M.; Martin, BrittanyLee N.

2018-01-01

This study was designed to deepen insights on whether word-problem (WP) solving is a form of text comprehension (TC) and on the role of language in WPs. A sample of 325 second graders, representing high, average, and low reading and math performance, was assessed on (a) start-of-year TC, WP skill, language, nonlinguistic reasoning, working memory, and foundational skill (word identification, arithmetic) and (b) year-end WP solving, WP-language processing (understanding WP statements, without calculation demands), and calculations. Multivariate, multilevel path analysis, accounting for classroom and school effects, indicated that TC was a significant and comparably strong predictor of all outcomes. Start-of-year language was a significantly stronger predictor of both year-end WP outcomes than of calculations, whereas start-of-year arithmetic was a significantly stronger predictor of calculations than of either WP measure. Implications are discussed in terms of WP solving as a form of TC and a theoretically coordinated approach, focused on language, for addressing TC and WP-solving instruction. PMID:29643723

Vertical Launch System Loadout Planner

DTIC Science & Technology

2015-03-01

United States Navy USS United States’ Ship VBA Visual Basic for Applications VLP VLS Loadout Planner VLS Vertical Launch System...with 32 gigabytes of random access memory and eight processors, General Algebraic Modeling System (GAMS) CPLEX version 24 (GAMS, 2015) solves this...problem in ten minutes to an integer tolerance of 10%. The GAMS interpreter and CPLEX solver require 75 Megabytes of random access memory for this

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

NASA Technical Reports Server (NTRS)

Shaeffer, John

2008-01-01

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

A Large-scale Distributed Indexed Learning Framework for Data that Cannot Fit into Memory

DTIC Science & Technology

2015-03-27

learn a classifier. Integrating three learning techniques (online, semi-supervised and active learning ) together with a selective sampling with minimum communication between the server and the clients solved this problem.

Cognitive profile in Duchenne muscular dystrophy boys without intellectual disability: The role of executive functions.

PubMed

Battini, R; Chieffo, D; Bulgheroni, S; Piccini, G; Pecini, C; Lucibello, S; Lenzi, S; Moriconi, F; Pane, M; Astrea, G; Baranello, G; Alfieri, P; Vicari, S; Riva, D; Cioni, G; Mercuri, E

2018-02-01

The aim of our prospective observational study was to assess profiles of cognitive function and a possible impairment of executive functions in a cohort of boys with Duchenne muscular dystrophy without intellectual and behavior disability. Forty Duchenne boys (range of age: 6 years to 11 years and 6 months) were assessed by Wechsler Intelligence scale and battery of tests including tasks assessing working memory and executive functions (inhibition and switching, problem solving and planning). In our cohort some aspects of cognitive function were often impaired. These included multitasking, problem solving, inhibition and working memory necessary to plan and direct goal oriented behavior. Our results support the suggestion that aspects of cognitive function could be impaired even in boys without intellectual disability and support the hypothesis that executive functions may play an important role in specific aspects of cognitive impairment in Duchenne muscular dystrophy. Copyright © 2017 Elsevier B.V. All rights reserved.

Qualitative Understanding of Magnetism at Three Levels of Expertise

NASA Astrophysics Data System (ADS)

Stefani, Francesco; Marshall, Jill

2010-03-01

This work set out to investigate the state of qualitative understanding of magnetism at various stages of expertise, and what approaches to problem-solving are used across the spectrum of expertise. We studied three groups: 10 novices, 10 experts-in-training, and 11 experts. Data collection involved structured interviews during which participants solved a series of non-standard problems designed to test for conceptual understanding of magnetism. The interviews were analyzed using a grounded theory approach. None of the novices and only a few of the experts in training showed a strong understanding of inductance, magnetic energy, and magnetic pressure; and for the most part they tended not to approach problems visually. Novices frequently described gist memories of demonstrations, text book problems, and rules (heuristics). However, these fragmentary mental models were not complete enough to allow them to reason productively. Experts-in-training were able to solve problems that the novices were not able to solve, many times simply because they had greater recall of the material, and therefore more confidence in their facts. Much of their thinking was concrete, based on mentally manipulating objects. The experts solved most of the problems in ways that were both effective and efficient. Part of the efficiency derived from their ability to visualize and thus reason in terms of field lines.

Qualitative Understanding of Magnetism at Three Levels of Expertise

NASA Astrophysics Data System (ADS)

Stefani, Francesco; Marshall, Jill

2009-04-01

This work set out to investigate the state of qualitative understanding of magnetism at various stages of expertise, and what approaches to problem-solving are used across the spectrum of expertise. We studied three groups: 10 novices, 10 experts-in-training, and 11 experts. Data collection involved structured interviews during which participants solved a series of non-standard problems designed to test for conceptual understanding of magnetism. The interviews were analyzed using a grounded theory approach. None of the novices and only a few of the experts in training showed a strong understanding of inductance, magnetic energy, and magnetic pressure; and for the most part they tended not to approach problems visually. Novices frequently described gist memories of demonstrations, text book problems, and rules (heuristics). However, these fragmentary mental models were not complete enough to allow them to reason productively. Experts-in-training were able to solve problems that the novices were not able to solve, many times simply because they had greater recall of the material, and therefore more confidence in their facts. Much of their thinking was concrete, based on mentally manipulating objects. The experts solved most of the problems in ways that were both effective and efficient. Part of the efficiency derived from their ability to visualize and thus reason in terms of field lines.

Frontal and Parietal Cortices Show Different Spatiotemporal Dynamics across Problem-solving Stages.

PubMed

Tschentscher, Nadja; Hauk, Olaf

2016-08-01

Arithmetic problem-solving can be conceptualized as a multistage process ranging from task encoding over rule and strategy selection to step-wise task execution. Previous fMRI research suggested a frontal-parietal network involved in the execution of complex numerical and nonnumerical tasks, but evidence is lacking on the particular contributions of frontal and parietal cortices across time. In an arithmetic task paradigm, we evaluated individual participants' "retrieval" and "multistep procedural" strategies on a trial-by-trial basis and contrasted those in time-resolved analyses using combined EEG and MEG. Retrieval strategies relied on direct retrieval of arithmetic facts (e.g., 2 + 3 = 5). Procedural strategies required multiple solution steps (e.g., 12 + 23 = 12 + 20 + 3 or 23 + 10 + 2). Evoked source analyses revealed independent activation dynamics within the first second of problem-solving in brain areas previously described as one network, such as the frontal-parietal cognitive control network: The right frontal cortex showed earliest effects of strategy selection for multistep procedural strategies around 300 msec, before parietal cortex activated around 700 msec. In time-frequency source power analyses, memory retrieval and multistep procedural strategies were differentially reflected in theta, alpha, and beta frequencies: Stronger beta and alpha desynchronizations emerged for procedural strategies in right frontal, parietal, and temporal regions as function of executive demands. Arithmetic fact retrieval was reflected in right prefrontal increases in theta power. Our results demonstrate differential brain dynamics within frontal-parietal networks across the time course of a problem-solving process, and analyses of different frequency bands allowed us to disentangle cortical regions supporting the underlying memory and executive functions.

Worrying about the Future: An Episodic Specificity Induction Impacts Problem Solving, Reappraisal, and Well-Being

PubMed Central

Jing, Helen G.; Madore, Kevin P.; Schacter, Daniel L.

2015-01-01

Previous research has demonstrated that an episodic specificity induction – brief training in recollecting details of a recent experience – enhances performance on various subsequent tasks thought to draw upon episodic memory processes. Existing work has also shown that mental simulation can be beneficial for emotion regulation and coping with stressors. Here we focus on understanding how episodic detail can affect problem solving, reappraisal, and psychological well-being regarding worrisome future events. In Experiment 1, an episodic specificity induction significantly improved participants’ performance on a subsequent means-end problem solving task (i.e., more relevant steps) and an episodic reappraisal task (i.e., more episodic details) involving personally worrisome future events compared with a control induction not focused on episodic specificity. Imagining constructive behaviors with increased episodic detail via the specificity induction was also related to significantly larger decreases in anxiety, perceived likelihood of a bad outcome, and perceived difficulty to cope with a bad outcome, as well as larger increases in perceived likelihood of a good outcome and indicated use of active coping behaviors compared with the control. In Experiment 2, we extended these findings using a more stringent control induction, and found preliminary evidence that the specificity induction was related to an increase in positive affect and decrease in negative affect compared with the control. Our findings support the idea that episodic memory processes are involved in means-end problem solving and episodic reappraisal, and that increasing the episodic specificity of imagining constructive behaviors regarding worrisome events may be related to improved psychological well-being. PMID:26820166

Tool use in neurodegenerative diseases: Planning or technical reasoning?

PubMed

Baumard, Josselin; Lesourd, Mathieu; Remigereau, Chrystelle; Jarry, Christophe; Etcharry-Bouyx, Frédérique; Chauviré, Valérie; Osiurak, François; Le Gall, Didier

2017-04-29

Recent works showed that tool use can be impaired in stroke patients because of either planning or technical reasoning deficits, but these two hypotheses have not yet been compared in the field of neurodegenerative diseases. The aim of this study was to address the relationships between real tool use, mechanical problem-solving, and planning skills in patients with Alzheimer's disease (AD, n = 32), semantic dementia (SD, n = 16), and corticobasal syndrome (CBS, n = 9). Patients were asked to select and use ten common tools, to solve three mechanical problems, and to complete the Tower of London test. Motor function and episodic memory were controlled using the Purdue Pegboard Test and the BEC96 questionnaire, respectively. A data-transformation method was applied to avoid ceiling effects, and single-case analysis was performed based on raw scores and completion time. All groups demonstrated either impaired or slowed tool use. Planning deficits were found only in the AD group. Mechanical problem-solving deficits were observed only in the AD and CBS groups. Performance in the Tower of London test was the best predictor of tool use skills in the AD group, suggesting these patients had general rather than mechanical problem-solving deficits. Episodic memory seemed to play little role in performance. Motor dysfunction tended to be associated with tool use skills in CBS patients, while tool use disorders are interpreted as a consequence of the semantic loss in SD in line with previous works. These findings may encourage caregivers to set up disease-centred interventions. © 2017 The British Psychological Society.

Design of a memory-access controller with 3.71-times-enhanced energy efficiency for Internet-of-Things-oriented nonvolatile microcontroller unit

NASA Astrophysics Data System (ADS)

Natsui, Masanori; Hanyu, Takahiro

2018-04-01

In realizing a nonvolatile microcontroller unit (MCU) for sensor nodes in Internet-of-Things (IoT) applications, it is important to solve the data-transfer bottleneck between the central processing unit (CPU) and the nonvolatile memory constituting the MCU. As one circuit-oriented approach to solving this problem, we propose a memory access minimization technique for magnetoresistive-random-access-memory (MRAM)-embedded nonvolatile MCUs. In addition to multiplexing and prefetching of memory access, the proposed technique realizes efficient instruction fetch by eliminating redundant memory access while considering the code length of the instruction to be fetched and the transition of the memory address to be accessed. As a result, the performance of the MCU can be improved while relaxing the performance requirement for the embedded MRAM, and compact and low-power implementation can be performed as compared with the conventional cache-based one. Through the evaluation using a system consisting of a general purpose 32-bit CPU and embedded MRAM, it is demonstrated that the proposed technique increases the peak efficiency of the system up to 3.71 times, while a 2.29-fold area reduction is achieved compared with the cache-based one.

Lesion mapping of social problem solving.

PubMed

Barbey, Aron K; Colom, Roberto; Paul, Erick J; Chau, Aileen; Solomon, Jeffrey; Grafman, Jordan H

2014-10-01

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion-symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

PubMed Central

Maisto, Domenico; Donnarumma, Francesco; Pezzulo, Giovanni

2015-01-01

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

Unstructured Adaptive (UA) NAS Parallel Benchmark. Version 1.0

NASA Technical Reports Server (NTRS)

Feng, Huiyu; VanderWijngaart, Rob; Biswas, Rupak; Mavriplis, Catherine

2004-01-01

We present a complete specification of a new benchmark for measuring the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. It complements the existing NAS Parallel Benchmark suite. The benchmark involves the solution of a stylized heat transfer problem in a cubic domain, discretized on an adaptively refined, unstructured mesh.

Executive Functions Contribute Uniquely to Reading Competence in Minority Youth

PubMed Central

Jacobson, Lisa A.; Koriakin, Taylor; Lipkin, Paul; Boada, Richard; Frijters, Jan; Lovett, Maureen; Hill, Dina; Willcutt, Erik; Gottwald, Stephanie; Wolf, Maryanne; Bosson-Heenan, Joan; Gruen, Jeffrey R.; Mahone, E. Mark

2018-01-01

Competent reading requires various skills beyond those for basic word reading (i.e., core language skills, rapid naming, phonological processing). Contributing “higher-level” or domain-general processes include information processing speed and executive functions (working memory, strategic problem solving, attentional switching). Research in this area has relied on largely Caucasian samples, with limited representation of children from racial or ethnic minority groups. This study examined contributions of executive skills to reading competence in 761 children of minority backgrounds. Hierarchical linear regressions examined unique contributions of executive functions (EF) to word reading, fluency, and comprehension. EF contributed uniquely to reading performance, over and above reading-related language skills; working memory contributed uniquely to all components of reading; while attentional switching, but not problem solving, contributed to isolated and contextual word reading and reading fluency. Problem solving uniquely predicted comprehension, suggesting that this skill may be especially important for reading comprehension in minority youth. Attentional switching may play a unique role in development of reading fluency in minority youth, perhaps as a result of the increased demand for switching between spoken versus written dialects. Findings have implications for educational and clinical practice with regard to reading instruction, remedial reading intervention, and assessment of individuals with reading difficulty. PMID:26755569

Unified implicit kinetic scheme for steady multiscale heat transfer based on the phonon Boltzmann transport equation

NASA Astrophysics Data System (ADS)

Zhang, Chuang; Guo, Zhaoli; Chen, Songze

2017-12-01

An implicit kinetic scheme is proposed to solve the stationary phonon Boltzmann transport equation (BTE) for multiscale heat transfer problem. Compared to the conventional discrete ordinate method, the present method employs a macroscopic equation to accelerate the convergence in the diffusive regime. The macroscopic equation can be taken as a moment equation for phonon BTE. The heat flux in the macroscopic equation is evaluated from the nonequilibrium distribution function in the BTE, while the equilibrium state in BTE is determined by the macroscopic equation. These two processes exchange information from different scales, such that the method is applicable to the problems with a wide range of Knudsen numbers. Implicit discretization is implemented to solve both the macroscopic equation and the BTE. In addition, a memory reduction technique, which is originally developed for the stationary kinetic equation, is also extended to phonon BTE. Numerical comparisons show that the present scheme can predict reasonable results both in ballistic and diffusive regimes with high efficiency, while the memory requirement is on the same order as solving the Fourier law of heat conduction. The excellent agreement with benchmark and the rapid converging history prove that the proposed macro-micro coupling is a feasible solution to multiscale heat transfer problems.

[Delayed reactions of active avoidance in white rats under conditions of an alternative choice].

PubMed

Ioseliani, T K; Sikharulidze, N I; Kadagishvili, A Ia; Mitashvili, E G

1995-01-01

It was shown that if the rats had been learned and then tested using conventional pain punishment of erroneous choice they were able to solve the problem of alternative choice only in the period of immediate action of conditioned stimuli. If the pain punishment for erroneously chosen compartment had not been applied in animal learning and testing, rats successfully solved the problem of alternative choice even after 5-second delay. Introduction of pain punishment led to the frustration of earlier elaborated delayed avoidance reactions. Analysis of the obtained results allows us to argue that the apparent incapability of white rats for solving the problems of delayed avoidance is caused by simultaneous action of two different mechanisms, i.e., those of the active and passive avoidance rather than short-term memory deficit.

Structure preserving parallel algorithms for solving the Bethe–Salpeter eigenvalue problem

DOE PAGES

Shao, Meiyue; da Jornada, Felipe H.; Yang, Chao; ...

2015-10-02

The Bethe–Salpeter eigenvalue problem is a dense structured eigenvalue problem arising from discretized Bethe–Salpeter equation in the context of computing exciton energies and states. A computational challenge is that at least half of the eigenvalues and the associated eigenvectors are desired in practice. In this paper, we establish the equivalence between Bethe–Salpeter eigenvalue problems and real Hamiltonian eigenvalue problems. Based on theoretical analysis, structure preserving algorithms for a class of Bethe–Salpeter eigenvalue problems are proposed. We also show that for this class of problems all eigenvalues obtained from the Tamm–Dancoff approximation are overestimated. In order to solve large scale problemsmore » of practical interest, we discuss parallel implementations of our algorithms targeting distributed memory systems. Finally, several numerical examples are presented to demonstrate the efficiency and accuracy of our algorithms.« less

Exploration versus exploitation in space, mind, and society

PubMed Central

Hills, Thomas T.; Todd, Peter M.; Lazer, David; Redish, A. David; Couzin, Iain D.

2015-01-01

Search is a ubiquitous property of life. Although diverse domains have worked on search problems largely in isolation, recent trends across disciplines indicate that the formal properties of these problems share similar structures and, often, similar solutions. Moreover, internal search (e.g., memory search) shows similar characteristics to external search (e.g., spatial foraging), including shared neural mechanisms consistent with a common evolutionary origin across species. Search problems and their solutions also scale from individuals to societies, underlying and constraining problem solving, memory, information search, and scientific and cultural innovation. In summary, search represents a core feature of cognition, with a vast influence on its evolution and processes across contexts and requiring input from multiple domains to understand its implications and scope. PMID:25487706

Processes of Similarity Judgment

ERIC Educational Resources Information Center

Larkey, Levi B.; Markman, Arthur B.

2005-01-01

Similarity underlies fundamental cognitive capabilities such as memory, categorization, decision making, problem solving, and reasoning. Although recent approaches to similarity appreciate the structure of mental representations, they differ in the processes posited to operate over these representations. We present an experiment that…

Solving the Swath Segment Selection Problem

NASA Technical Reports Server (NTRS)

Knight, Russell; Smith, Benjamin

2006-01-01

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

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

NASA Astrophysics Data System (ADS)

Muruganandam, P.; Adhikari, S. K.

2009-10-01

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

Brain hyper-connectivity and operation-specific deficits during arithmetic problem solving in children with developmental dyscalculia

PubMed Central

Rosenberg-Lee, Miriam; Ashkenazi, Sarit; Chen, Tianwen; Young, Christina B.; Geary, David C.; Menon, Vinod

2014-01-01

Developmental dyscalculia (DD) is marked by specific deficits in processing numerical and mathematical information despite normal intelligence (IQ) and reading ability. We examined how brain circuits used by young children with DD to solve simple addition and subtraction problems differ from those used by typically developing (TD) children who were matched on age, IQ, reading ability, and working memory. Children with DD were slower and less accurate during problem solving than TD children, and were especially impaired on their ability to solve subtraction problems. Children with DD showed significantly greater activity in multiple parietal, occipito-temporal and prefrontal cortex regions while solving addition and subtraction problems. Despite poorer performance during subtraction, children with DD showed greater activity in multiple intra-parietal sulcus (IPS) and superior parietal lobule subdivisions in the dorsal posterior parietal cortex as well as fusiform gyrus in the ventral occipito-temporal cortex. Critically, effective connectivity analyses revealed hyper-connectivity, rather than reduced connectivity, between the IPS and multiple brain systems including the lateral fronto-parietal and default mode networks in children with DD during both addition and subtraction. These findings suggest the IPS and its functional circuits are a major locus of dysfunction during both addition and subtraction problem solving in DD, and that inappropriate task modulation and hyper-connectivity, rather than under-engagement and under-connectivity, are the neural mechanisms underlying problem solving difficulties in children with DD. We discuss our findings in the broader context of multiple levels of analysis and performance issues inherent in neuroimaging studies of typical and atypical development. PMID:25098903

Brain hyper-connectivity and operation-specific deficits during arithmetic problem solving in children with developmental dyscalculia.

PubMed

Rosenberg-Lee, Miriam; Ashkenazi, Sarit; Chen, Tianwen; Young, Christina B; Geary, David C; Menon, Vinod

2015-05-01

Developmental dyscalculia (DD) is marked by specific deficits in processing numerical and mathematical information despite normal intelligence (IQ) and reading ability. We examined how brain circuits used by young children with DD to solve simple addition and subtraction problems differ from those used by typically developing (TD) children who were matched on age, IQ, reading ability, and working memory. Children with DD were slower and less accurate during problem solving than TD children, and were especially impaired on their ability to solve subtraction problems. Children with DD showed significantly greater activity in multiple parietal, occipito-temporal and prefrontal cortex regions while solving addition and subtraction problems. Despite poorer performance during subtraction, children with DD showed greater activity in multiple intra-parietal sulcus (IPS) and superior parietal lobule subdivisions in the dorsal posterior parietal cortex as well as fusiform gyrus in the ventral occipito-temporal cortex. Critically, effective connectivity analyses revealed hyper-connectivity, rather than reduced connectivity, between the IPS and multiple brain systems including the lateral fronto-parietal and default mode networks in children with DD during both addition and subtraction. These findings suggest the IPS and its functional circuits are a major locus of dysfunction during both addition and subtraction problem solving in DD, and that inappropriate task modulation and hyper-connectivity, rather than under-engagement and under-connectivity, are the neural mechanisms underlying problem solving difficulties in children with DD. We discuss our findings in the broader context of multiple levels of analysis and performance issues inherent in neuroimaging studies of typical and atypical development. © 2014 John Wiley & Sons Ltd.

Design of Unstructured Adaptive (UA) NAS Parallel Benchmark Featuring Irregular, Dynamic Memory Accesses

NASA Technical Reports Server (NTRS)

Feng, Hui-Yu; VanderWijngaart, Rob; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

We describe the design of a new method for the measurement of the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. The method involves the solution of a stylized heat transfer problem on an unstructured, adaptive grid. A Spectral Element Method (SEM) with an adaptive, nonconforming mesh is selected to discretize the transport equation. The relatively high order of the SEM lowers the fraction of wall clock time spent on inter-processor communication, which eases the load balancing task and allows us to concentrate on the memory accesses. The benchmark is designed to be three-dimensional. Parallelization and load balance issues of a reference implementation will be described in detail in future reports.

Impact of memory bottleneck on the performance of graphics processing units

NASA Astrophysics Data System (ADS)

Son, Dong Oh; Choi, Hong Jun; Kim, Jong Myon; Kim, Cheol Hong

2015-12-01

Recent graphics processing units (GPUs) can process general-purpose applications as well as graphics applications with the help of various user-friendly application programming interfaces (APIs) supported by GPU vendors. Unfortunately, utilizing the hardware resource in the GPU efficiently is a challenging problem, since the GPU architecture is totally different to the traditional CPU architecture. To solve this problem, many studies have focused on the techniques for improving the system performance using GPUs. In this work, we analyze the GPU performance varying GPU parameters such as the number of cores and clock frequency. According to our simulations, the GPU performance can be improved by 125.8% and 16.2% on average as the number of cores and clock frequency increase, respectively. However, the performance is saturated when memory bottleneck problems incur due to huge data requests to the memory. The performance of GPUs can be improved as the memory bottleneck is reduced by changing GPU parameters dynamically.

Distributed memory compiler design for sparse problems

NASA Technical Reports Server (NTRS)

Wu, Janet; Saltz, Joel; Berryman, Harry; Hiranandani, Seema

1991-01-01

A compiler and runtime support mechanism is described and demonstrated. The methods presented are capable of solving a wide range of sparse and unstructured problems in scientific computing. The compiler takes as input a FORTRAN 77 program enhanced with specifications for distributing data, and the compiler outputs a message passing program that runs on a distributed memory computer. The runtime support for this compiler is a library of primitives designed to efficiently support irregular patterns of distributed array accesses and irregular distributed array partitions. A variety of Intel iPSC/860 performance results obtained through the use of this compiler are presented.

Neural-Network Simulator

NASA Technical Reports Server (NTRS)

Mitchell, Paul H.

1991-01-01

F77NNS (FORTRAN 77 Neural Network Simulator) computer program simulates popular back-error-propagation neural network. Designed to take advantage of vectorization when used on computers having this capability, also used on any computer equipped with ANSI-77 FORTRAN Compiler. Problems involving matching of patterns or mathematical modeling of systems fit class of problems F77NNS designed to solve. Program has restart capability so neural network solved in stages suitable to user's resources and desires. Enables user to customize patterns of connections between layers of network. Size of neural network F77NNS applied to limited only by amount of random-access memory available to user.

Learning Aids for Students Taking Physics

ERIC Educational Resources Information Center

Voroshilov, Valentin

2015-01-01

If a person has "a problem" to solve and knows the solution and just has to apply it (retrieve it from memory and re-act), it is not a problem--it is a task; if a person does not know the solution and has to create it--this is a problem. Using this language, there are only two situations: (a) one has to perform a task; or (b) one has to…

The effect of visual representation style in problem-solving: a perspective from cognitive processes.

PubMed

Nyamsuren, Enkhbold; Taatgen, Niels A

2013-01-01

Using results from a controlled experiment and simulations based on cognitive models, we show that visual presentation style can have a significant impact on performance in a complex problem-solving task. We compared subject performances in two isomorphic, but visually different, tasks based on a card game of SET. Although subjects used the same strategy in both tasks, the difference in presentation style resulted in radically different reaction times and significant deviations in scanpath patterns in the two tasks. Results from our study indicate that low-level subconscious visual processes, such as differential acuity in peripheral vision and low-level iconic memory, can have indirect, but significant effects on decision making during a problem-solving task. We have developed two ACT-R models that employ the same basic strategy but deal with different presentations styles. Our ACT-R models confirm that changes in low-level visual processes triggered by changes in presentation style can propagate to higher-level cognitive processes. Such a domino effect can significantly affect reaction times and eye movements, without affecting the overall strategy of problem solving.

The Effect of Visual Representation Style in Problem-Solving: A Perspective from Cognitive Processes

PubMed Central

Nyamsuren, Enkhbold; Taatgen, Niels A.

2013-01-01

Using results from a controlled experiment and simulations based on cognitive models, we show that visual presentation style can have a significant impact on performance in a complex problem-solving task. We compared subject performances in two isomorphic, but visually different, tasks based on a card game of SET. Although subjects used the same strategy in both tasks, the difference in presentation style resulted in radically different reaction times and significant deviations in scanpath patterns in the two tasks. Results from our study indicate that low-level subconscious visual processes, such as differential acuity in peripheral vision and low-level iconic memory, can have indirect, but significant effects on decision making during a problem-solving task. We have developed two ACT-R models that employ the same basic strategy but deal with different presentations styles. Our ACT-R models confirm that changes in low-level visual processes triggered by changes in presentation style can propagate to higher-level cognitive processes. Such a domino effect can significantly affect reaction times and eye movements, without affecting the overall strategy of problem solving. PMID:24260415

Think globally and solve locally: secondary memory-based network learning for automated multi-species function prediction

PubMed Central

2014-01-01

Background Network-based learning algorithms for automated function prediction (AFP) are negatively affected by the limited coverage of experimental data and limited a priori known functional annotations. As a consequence their application to model organisms is often restricted to well characterized biological processes and pathways, and their effectiveness with poorly annotated species is relatively limited. A possible solution to this problem might consist in the construction of big networks including multiple species, but this in turn poses challenging computational problems, due to the scalability limitations of existing algorithms and the main memory requirements induced by the construction of big networks. Distributed computation or the usage of big computers could in principle respond to these issues, but raises further algorithmic problems and require resources not satisfiable with simple off-the-shelf computers. Results We propose a novel framework for scalable network-based learning of multi-species protein functions based on both a local implementation of existing algorithms and the adoption of innovative technologies: we solve “locally” the AFP problem, by designing “vertex-centric” implementations of network-based algorithms, but we do not give up thinking “globally” by exploiting the overall topology of the network. This is made possible by the adoption of secondary memory-based technologies that allow the efficient use of the large memory available on disks, thus overcoming the main memory limitations of modern off-the-shelf computers. This approach has been applied to the analysis of a large multi-species network including more than 300 species of bacteria and to a network with more than 200,000 proteins belonging to 13 Eukaryotic species. To our knowledge this is the first work where secondary-memory based network analysis has been applied to multi-species function prediction using biological networks with hundreds of thousands of proteins. Conclusions The combination of these algorithmic and technological approaches makes feasible the analysis of large multi-species networks using ordinary computers with limited speed and primary memory, and in perspective could enable the analysis of huge networks (e.g. the whole proteomes available in SwissProt), using well-equipped stand-alone machines. PMID:24843788

Is self-generated thought a means of social problem solving?

PubMed Central

Ruby, Florence J. M.; Smallwood, Jonathan; Sackur, Jerome; Singer, Tania

2013-01-01

Appropriate social problem solving constitutes a critical skill for individuals and may rely on processes important for self-generated thought (SGT). The aim of the current study was to investigate the link between SGT and social problem solving. Using the Means-End Problem Solving task (MEPS), we assessed participants' abilities to resolve daily social problems in terms of overall efficiency and number of relevant means they provided to reach the given solution. Participants also performed a non-demanding choice reaction time task (CRT) and a moderately-demanding working memory task (WM) as a context in which to measure their SGT (assessed via thought sampling). We found that although overall SGT was associated with lower MEPS efficiency, it was also associated with higher relevant means, perhaps because both depend on the capacity to generate cognition that is independent from the hear and now. The specific content of SGT did not differentially predict individual differences in social problem solving, suggesting that the relationship may depend on SGT regardless of its content. In addition, we also found that performance at the WM but not the CRT was linked to overall better MEPS performance, suggesting that individuals good at social processing are also distinguished by their capacity to constrain attention to an external task. Our results provide novel evidence that the capacity for SGT is implicated in the process by which solutions to social problems are generated, although optimal problem solving may be achieved by individuals who display a suitable balance between SGT and cognition derived from perceptual input. PMID:24391621

Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

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

The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

Cognitive Impairment Assessment through Visuospatial Memory Can Be Performed with a Modified Walking Corsi Test Using the ‘Magic Carpet’

PubMed Central

Perrochon, Anaïck; Kemoun, Gilles; Dugué, Benoit; Berthoz, Alain

2014-01-01

Background Subjects with mild cognitive impairment (MCI) have disturbances in their spatial navigation abilities and exhibit early deficits in visuospatial short-term memory. The purpose of the present study was to determine whether a quantitative (span score) and qualitative (evaluating navigation strategies used) analysis of the Corsi test (usual condition and complex navigation task) would be useful to reveal cognitive decline. Methods We evaluated the performance of 15 young adults, 21 healthy elderly subjects and 15 subjects with MCI using the electronic version of the Corsi test (the Modified Corsi Block-Tapping Test, MCBT) and the complex navigation task (the Modified Walking Corsi Test, MWCT). The MWCT, which is an adaptation of the Corsi test, assesses spatial memory when the subject walks in a complex environment. We used Richard et al.'s model [Cogn Sci 1993;17:497-529] to investigate problem-solving strategies during the Corsi tests. Results The span scores obtained on the MCBT and the MWCT were significantly lower in the healthy elderly subjects (MCBT = 5.0 ± 0.7; MWCT = 4.0 ± 0.7) and the subjects with MCI (MCBT = 4.7 ± 0.8; MWCT = 4.1 ± 0.9) than in the younger adults (MCBT = 6.2 ± 0.6; MWCT = 5.3 ± 1.0). The visuospatial working memory was more impaired in the complex navigation task (MWCT = 4.3 ± 0.9) than in the modified Corsi test (MCBT = 5.3 ± 0.8). Finally, the subjects with greater cognitive impairment were more likely to have inadequate or absence of problem-solving strategies. Conclusions Investigating the problem-solving strategies used during the MWCT appears to be a promising way to differentiate between the subjects with MCI and the healthy elderly subjects. PMID:24575112

Reminiscence and adaptation to critical life events in older adults with mild to moderate depressive symptoms.

PubMed

Korte, Jojanneke; Bohlmeijer, Ernst T; Westerhof, Gerben J; Pot, Anne Margriet; Pot, Anne M

2011-07-01

The role of reminiscence as a way of adapting to critical life events and chronic medical conditions was investigated in older adults with mild to moderate depressive symptoms. Reminiscence is the (non)volitional act or process of recollecting memories of one's self in the past. 171 Dutch older adults with a mean age of 64 years (SD = 7.4) participated in this study. All of them had mild to moderate depressive symptoms. Participants completed measures on critical life events, chronic medical conditions, depressive symptoms, symptoms of anxiety and satisfaction with life. The reminiscence functions included were: identity, problem solving, bitterness revival and boredom reduction. Critical life events were positively correlated with identity and problem solving. Bitterness revival and boredom reduction were both positively correlated with depressive and anxiety symptoms, and negatively to satisfaction with life. Problem solving had a negative relation with anxiety symptoms. When all the reminiscence functions were included, problem solving was uniquely associated with symptoms of anxiety, and bitterness revival was uniquely associated with depressive symptoms and satisfaction with life. Interestingly, problem solving mediated the relation of critical life events with anxiety. This study corroborates the theory that reminiscence plays a role in coping with critical life events, and thereby maintaining mental health. Furthermore, it is recommended that therapists focus on techniques which reduce bitterness revival in people with depressive symptoms, and focus on problem-solving reminiscences among people with anxiety symptoms.

The Convergence of Intelligences

NASA Astrophysics Data System (ADS)

Diederich, Joachim

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

Amnestic mild cognitive impairment: functional MR imaging study of response in posterior cingulate cortex and adjacent precuneus during problem-solving tasks.

PubMed

Jin, Guangwei; Li, Kuncheng; Hu, Yingying; Qin, Yulin; Wang, Xiangqing; Xiang, Jie; Yang, Yanhui; Lu, Jie; Zhong, Ning

2011-11-01

To compare the blood oxygen level-dependent (BOLD) response, measured with functional magnetic resonance (MR) imaging, in the posterior cingulate cortex (PCC) and adjacent precuneus regions between healthy control subjects and patients with amnestic mild cognitive impairment (MCI) during problem-solving tasks. This study was approved by the institutional review board. Each subject provided written informed consent. Thirteen patients with amnestic MCI and 13 age- and sex-matched healthy control subjects participated in the study. The functional magnetic resonance (MR) imaging tasks were simplified 4 × 4-grid number placement puzzles that were divided into a simple task (using the row rule or the column rule to solve the puzzle) and a complex task (using both the row and column rules to solve the puzzle). Behavioral results and functional imaging results between the healthy control group and the amnestic MCI group were analyzed. The accuracy for the complex task in the healthy control group was significantly higher than that in the amnestic MCI group (P < .05). The healthy control group exhibited a deactivated BOLD signal intensity (SI) change in the bilateral PCC and adjacent precuneus regions during the complex task, whereas the amnestic MCI group showed activation. The positive linear correlations between the BOLD SI change in bilateral PCC and adjacent precuneus regions and in bilateral hippocampi in the amnestic MCI group were significant (P < .001), while in the healthy control group, they were not (P ≥ .23). These findings suggest that an altered BOLD response in amnestic MCI patients during complex tasks might be related to a decline in problem-solving ability and to memory impairment and, thus, may indicate a compensatory response to memory impairment. RSNA, 2011

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

PubMed

Maisto, Domenico; Donnarumma, Francesco; Pezzulo, Giovanni

2015-03-06

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

Computational Study for Planar Connected Dominating Set Problem

NASA Astrophysics Data System (ADS)

Marzban, Marjan; Gu, Qian-Ping; Jia, Xiaohua

The connected dominating set (CDS) problem is a well studied NP-hard problem with many important applications. Dorn et al. [ESA2005, LNCS3669,pp95-106] introduce a new technique to generate 2^{O(sqrt{n})} time and fixed-parameter algorithms for a number of non-local hard problems, including the CDS problem in planar graphs. The practical performance of this algorithm is yet to be evaluated. We perform a computational study for such an evaluation. The results show that the size of instances can be solved by the algorithm mainly depends on the branchwidth of the instances, coinciding with the theoretical result. For graphs with small or moderate branchwidth, the CDS problem instances with size up to a few thousands edges can be solved in a practical time and memory space. This suggests that the branch-decomposition based algorithms can be practical for the planar CDS problem.

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.

Microcomputers and Preschoolers.

ERIC Educational Resources Information Center

Evans, Dina

Preschool children can benefit by working with microcomputers. Thinking skills are enhanced by software games that focus on logic, memory, problem solving, and pattern recognition. Counting, sequencing, and matching games develop mathematics skills, and word games focusing on basic letter symbol and word recognition develop language skills.…

A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems

DOE PAGES

Song, Fengguang; Dongarra, Jack

2014-10-01

Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasksmore » without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.« less

A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems

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

Song, Fengguang; Dongarra, Jack

Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasksmore » without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.« less

Novices and Experts in Geoinformatics: the Cognitive Gap.

NASA Astrophysics Data System (ADS)

Zhilin, M.

2012-04-01

Modern geoinformatics is an extremely powerful tool for problem analysis and decision making in various fields. Currently general public uses geoinformatics predominantly for navigating (GPS) and sharing information about particular places (GoogleMaps, Wikimapia). Communities also use geoinformatics for particular purposes: fans of history use it to correspond historical and actual maps (www.retromap.ru), birdwatchers point places where they met birds (geobirds.com/rangemaps) etc. However the majority of stakeholders local authorities are not aware of advantages and possibilities of geoinformatics. The same problem is observed for students. At the same time many professional geoinformatic tools are developed, but sometimes the experts even can't explain their purpose to non-experts. So the question is how to shrink the gap between experts and non-experts in understanding and application of geoinformatics. We think that this gap has a cognitive basis. According to modern cognitive theories (Shiffrin-Atkinson and descending) the information primary has to pass through the perceptual filter that cuts off the information that seems to be irrelevant. The mind estimates the relevance implicitly (unconsciously) basing on previous knowledge and judgments what is important. Then it comes to the working memory which is used (a) for proceeding and (b) for problem solving. The working memory has limited capacity and can operate only with about 7 objects simultaneously. Then information passes to the long-term memory that is of unlimited capacity. There it is stored as more or less complex structures with associative links. When necessary it is extracted into the working memory. If great amount of information is linked ("chunked") the working memory operates with it as one object of seven thus overcoming the limitations of the working memory capacity. To adopt any information it should (a) pass through the perceptual filter, (b) not to overload the working memory and (c) to be structured in the long-term memory. Expert easily adopt domain-specific information because they (a) understand terminology and consider the information to be important thus passing it through the perceptual filter and (b) have a lot of complex domain-specific chunks that are processed by the working memory as a whole thus avoiding to overload it. Novices (students and general public) have neither understanding and feeling importance nor necessary chunks. The following measures should be taken to bridge experts' and novices' understanding of geoinformatics. Expert community should popularize geoscientific problems developing understandable language and available tools for their solving. This requires close collaboration with educational system (especially second education). If students understand a problem, they can find and apply appropriate tool for it. Geoscientific problems and models are extremely complex. In cognitive terms, they require hierarchy of chunks. This hierarchy should coherently develop beginning from simple ones later joining them to complex. It requires an appropriate sequence of learning tasks. There is no necessity in correct solutions - the students should understand how are they solved and realize limitations of models. We think that tasks of weather forecast, global climate modeling etc are suitable. The first step on bridging experts and novices is the elaboration of a set and a sequence of learning tasks and its sequence as well as tools for their solution. The tools should be easy for everybody who understands the task and as versatile as possible - otherwise students will waste a lot of time mastering it. This development requires close collaboration between geoscientists and educators.

Coping style and memory specificity in adolescents and adults with histories of child sexual abuse.

PubMed

Harris, Latonya S; Block, Stephanie D; Ogle, Christin M; Goodman, Gail S; Augusti, Else-Marie; Larson, Rakel P; Culver, Michelle A; Pineda, Annarheen R; Timmer, Susan G; Urquiza, Anthony

2016-09-01

Individuals with histories of childhood trauma may adopt a nonspecific memory retrieval strategy to avoid unpleasant and intrusive memories. In a sample of 93 adolescents and adults with or without histories of child sexual abuse (CSA), we tested the hypothesis that nonspecific memory retrieval is related to an individual's general tendency to use avoidant (i.e., distancing) coping as a personal problem-solving or coping strategy, especially in victims of CSA. We also examined age differences and other individual differences (e.g., trauma-related psychopathology) as predictors of nonspecific memories. Distancing coping was significantly associated with less specific autobiographical memory. Younger age, lower vocabulary scores, and non-CSA childhood maltreatment (i.e., physical and emotional abuse) also uniquely predicted less autobiographical memory specificity, whereas trauma-related psychopathology was associated with more specific memory. Implications for the development of autobiographical memory retrieval in the context of coping with childhood maltreatment are discussed.

Learning to forget: continual prediction with LSTM.

PubMed

Gers, F A; Schmidhuber, J; Cummins, F

2000-10-01

Long short-term memory (LSTM; Hochreiter & Schmidhuber, 1997) can solve numerous tasks not solvable by previous learning algorithms for recurrent neural networks (RNNs). We identify a weakness of LSTM networks processing continual input streams that are not a priori segmented into subsequences with explicitly marked ends at which the network's internal state could be reset. Without resets, the state may grow indefinitely and eventually cause the network to break down. Our remedy is a novel, adaptive "forget gate" that enables an LSTM cell to learn to reset itself at appropriate times, thus releasing internal resources. We review illustrative benchmark problems on which standard LSTM outperforms other RNN algorithms. All algorithms (including LSTM) fail to solve continual versions of these problems. LSTM with forget gates, however, easily solves them, and in an elegant way.

Optimal Planning and Problem-Solving

NASA Technical Reports Server (NTRS)

Clemet, Bradley; Schaffer, Steven; Rabideau, Gregg

2008-01-01

CTAEMS MDP Optimal Planner is a problem-solving software designed to command a single spacecraft/rover, or a team of spacecraft/rovers, to perform the best action possible at all times according to an abstract model of the spacecraft/rover and its environment. It also may be useful in solving logistical problems encountered in commercial applications such as shipping and manufacturing. The planner reasons around uncertainty according to specified probabilities of outcomes using a plan hierarchy to avoid exploring certain kinds of suboptimal actions. Also, planned actions are calculated as the state-action space is expanded, rather than afterward, to reduce by an order of magnitude the processing time and memory used. The software solves planning problems with actions that can execute concurrently, that have uncertain duration and quality, and that have functional dependencies on others that affect quality. These problems are modeled in a hierarchical planning language called C_TAEMS, a derivative of the TAEMS language for specifying domains for the DARPA Coordinators program. In realistic environments, actions often have uncertain outcomes and can have complex relationships with other tasks. The planner approaches problems by considering all possible actions that may be taken from any state reachable from a given, initial state, and from within the constraints of a given task hierarchy that specifies what tasks may be performed by which team member.

Partitioning problems in parallel, pipelined and distributed computing

NASA Technical Reports Server (NTRS)

Bokhari, S.

1985-01-01

The problem of optimally assigning the modules of a parallel program over the processors of a multiple computer system is addressed. A Sum-Bottleneck path algorithm is developed that permits the efficient solution of many variants of this problem under some constraints on the structure of the partitions. In particular, the following problems are solved optimally for a single-host, multiple satellite system: partitioning multiple chain structured parallel programs, multiple arbitrarily structured serial programs and single tree structured parallel programs. In addition, the problems of partitioning chain structured parallel programs across chain connected systems and across shared memory (or shared bus) systems are also solved under certain constraints. All solutions for parallel programs are equally applicable to pipelined programs. These results extend prior research in this area by explicitly taking concurrency into account and permit the efficient utilization of multiple computer architectures for a wide range of problems of practical interest.

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.

Clinical and Cognitive Characteristics Associated with Mathematics Problem Solving in Adolescents with Autism Spectrum Disorder.

PubMed

Oswald, Tasha M; Beck, Jonathan S; Iosif, Ana-Maria; McCauley, James B; Gilhooly, Leslie J; Matter, John C; Solomon, Marjorie

2016-04-01

Mathematics achievement in autism spectrum disorder (ASD) has been understudied. However, the ability to solve applied math problems is associated with academic achievement, everyday problem-solving abilities, and vocational outcomes. The paucity of research on math achievement in ASD may be partly explained by the widely-held belief that most individuals with ASD are mathematically gifted, despite emerging evidence to the contrary. The purpose of the study was twofold: to assess the relative proportions of youth with ASD who demonstrate giftedness versus disability on applied math problems, and to examine which cognitive (i.e., perceptual reasoning, verbal ability, working memory) and clinical (i.e., test anxiety) characteristics best predict achievement on applied math problems in ASD relative to typically developing peers. Twenty-seven high-functioning adolescents with ASD and 27 age- and Full Scale IQ-matched typically developing controls were assessed on standardized measures of math problem solving, perceptual reasoning, verbal ability, and test anxiety. Results indicated that 22% of the ASD sample evidenced a mathematics learning disability, while only 4% exhibited mathematical giftedness. The parsimonious linear regression model revealed that the strongest predictor of math problem solving was perceptual reasoning, followed by verbal ability and test anxiety, then diagnosis of ASD. These results inform our theories of math ability in ASD and highlight possible targets of intervention for students with ASD struggling with mathematics. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

On the Evolutionary Origins of Executive Functions

ERIC Educational Resources Information Center

Ardila, Alfredo

2008-01-01

In this paper it is proposed that the prefrontal lobe participates in two closely related but different executive function abilities: (1) "metacognitive executive functions": problem solving, planning, concept formation, strategy development and implementation, controlling attention, working memory, and the like; that is, executive functions as…

A Cognitive Architecture for Solving Ill-Structured Problems

DTIC Science & Technology

1997-08-01

R. C. (1982). Dynamic memory. Cambridge, Mass.: Cambridge University Press. Selfridge, 0. G., & Neisser , U . (1960). Pattern recognition by machine...Page 1 . In tro d u ctio n...1 1.1 Relevance to the ARI M ission ............................................................................... 1 1.2 Components of Analogy U se

Executive Functions Contribute Uniquely to Reading Competence in Minority Youth

ERIC Educational Resources Information Center

Jacobson, Lisa A.; Koriakin, Taylor; Lipkin, Paul; Boada, Richard; Frijters, Jan C.; Lovett, Maureen W.; Hill, Dina; Willcutt, Erik; Gottwald, Stephanie; Wolf, Maryanne; Bosson-Heenan, Joan; Gruen, Jeffrey R.; Mahone, E. Mark

2017-01-01

Competent reading requires various skills beyond those for basic word reading (i.e., core language skills, rapid naming, phonological processing). Contributing "higher-level" or domain-general processes include information processing speed and executive functions (working memory, strategic problem solving, attentional switching).…

Investigating Insight as Sudden Learning

ERIC Educational Resources Information Center

Ash, Ivan K.; Jee, Benjamin D.; Wiley, Jennifer

2012-01-01

Gestalt psychologists proposed two distinct learning mechanisms. Associative learning occurs gradually through the repeated co-occurrence of external stimuli or memories. Insight learning occurs suddenly when people discover new relationships within their prior knowledge as a result of reasoning or problem solving processes that re-organize or…

Top-Down Computerized Cognitive Remediation in Schizophrenia: A Case Study of an Individual with Impairment in Verbal Fluency

PubMed Central

Masson, Marjolaine; Wykes, Til; Maziade, Michel; Reeder, Clare; Gariépy, Marie-Anne; Roy, Marc-André; Ivers, Hans; Cellard, Caroline

2015-01-01

The objective of this case study was to assess the specific effect of cognitive remediation for schizophrenia on the pattern of cognitive impairments. Case A is a 33-year-old man with a schizophrenia diagnosis and impairments in visual memory, inhibition, problem solving, and verbal fluency. He was provided with a therapist delivered cognitive remediation program involving practice and strategy which was designed to train attention, memory, executive functioning, visual-perceptual processing, and metacognitive skills. Neuropsychological and clinical assessments were administered at baseline and after three months of treatment. At posttest assessment, Case A had improved significantly on targeted (visual memory and problem solving) and nontargeted (verbal fluency) cognitive processes. The results of the current case study suggest that (1) it is possible to improve specific cognitive processes with targeted exercises, as seen by the improvement in visual memory due to training exercises targeting this cognitive domain; (2) cognitive remediation can produce improvements in cognitive processes not targeted during remediation since verbal fluency was improved while there was no training exercise on this specific cognitive process; and (3) including learning strategies in cognitive remediation increases the value of the approach and enhances participant improvement, possibly because strategies using verbalization can lead to improvement in verbal fluency even if it was not practiced. PMID:25949840

Cognitive Strategies, Working Memory, and Growth in Word Problem Solving in Children With Math Difficulties.

PubMed

Swanson, H Lee; Lussier, Catherine M; Orosco, Michael J

2015-01-01

This study investigated the role of strategy instruction and working memory capacity (WMC) on word problem solving accuracy in children with (n = 100) and without (n = 92) math difficulties (MD). Within classrooms, children in Grades 2 and 3 were randomly assigned to one of four treatment conditions: verbal-only strategies (e.g., underlining question sentence), verbal + visual strategies, visual-only strategies (e.g., correctly placing numbers in diagrams), or untreated control. Strategy interventions included 20 sessions in both Year 1 and Year 2. The intent-to-treat as well as the "as-treated" analyses showed that treatment effects were significantly moderated by WMC. In general, treatment outcomes were higher when WMC was set to a high rather than low level. When set to a relatively high WMC level, children with MD performed significantly better under visual-only strategy conditions and children without MD performed better under verbal + visual conditions when compared to control conditions. © Hammill Institute on Disabilities 2013.

What can robots tell us about brains? A synthetic approach towards the study of learning and problem solving.

PubMed

Voegtlin, T; Verschure, P F

1999-01-01

This paper argues for the development of synthetic approaches towards the study of brain and behavior as a complement to the more traditional empirical mode of research. As an example we present our own work on learning and problem solving which relates to the behavioral paradigms of classical and operant conditioning. We define the concept of learning in the context of behavior and lay out the basic methodological requirements a model needs to satisfy, which includes evaluations using robots. In addition, we define a number of design principles neuronal models should obey to be considered relevant. We present in detail the construction of a neural model of short- and long-term memory which can be applied to an artificial behaving system. The presented model (DAC4) provides a novel self-consistent implementation of these processes, which satisfies our principles. This model will be interpreted towards the present understanding of the neuronal substrate of memory.

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

A Framework for Distributed Problem Solving

NASA Astrophysics Data System (ADS)

Leone, Joseph; Shin, Don G.

1989-03-01

This work explores a distributed problem solving (DPS) approach, namely the AM/AG model, to cooperative memory recall. The AM/AG model is a hierarchic social system metaphor for DPS based on the Mintzberg's model of organizations. At the core of the model are information flow mechanisms, named amplification and aggregation. Amplification is a process of expounding a given task, called an agenda, into a set of subtasks with magnified degree of specificity and distributing them to multiple processing units downward in the hierarchy. Aggregation is a process of combining the results reported from multiple processing units into a unified view, called a resolution, and promoting the conclusion upward in the hierarchy. The combination of amplification and aggregation can account for a memory recall process which primarily relies on the ability of making associations between vast amounts of related concepts, sorting out the combined results, and promoting the most plausible ones. The amplification process is discussed in detail. An implementation of the amplification process is presented. The process is illustrated by an example.

Improved Linear Algebra Methods for Redshift Computation from Limited Spectrum Data - II

NASA Technical Reports Server (NTRS)

Foster, Leslie; Waagen, Alex; Aijaz, Nabella; Hurley, Michael; Luis, Apolo; Rinsky, Joel; Satyavolu, Chandrika; Gazis, Paul; Srivastava, Ashok; Way, Michael

2008-01-01

Given photometric broadband measurements of a galaxy, Gaussian processes may be used with a training set to solve the regression problem of approximating the redshift of this galaxy. However, in practice solving the traditional Gaussian processes equation is too slow and requires too much memory. We employed several methods to avoid this difficulty using algebraic manipulation and low-rank approximation, and were able to quickly approximate the redshifts in our testing data within 17 percent of the known true values using limited computational resources. The accuracy of one method, the V Formulation, is comparable to the accuracy of the best methods currently used for this problem.

Functional fixedness in a technologically sparse culture.

PubMed

German, Tim P; Barrett, H Clark

2005-01-01

Problem solving can be inefficient when the solution requires subjects to generate an atypical function for an object and the object's typical function has been primed. Subjects become "fixed" on the design function of the object, and problem solving suffers relative to control conditions in which the object's function is not demonstrated. In the current study, such functional fixedness was demonstrated in a sample of adolescents (mean age of 16 years) among the Shuar of Ecuadorian Amazonia, whose technologically sparse culture provides limited access to large numbers of artifacts with highly specialized functions. This result suggests that design function may universally be the core property of artifact concepts in human semantic memory.

Reasoning and dyslexia: is visual memory a compensatory resource?

PubMed

Bacon, Alison M; Handley, Simon J

2014-11-01

Effective reasoning is fundamental to problem solving and achievement in education and employment. Protocol studies have previously suggested that people with dyslexia use reasoning strategies based on visual mental representations, whereas non-dyslexics use abstract verbal strategies. This research presents converging evidence from experimental and individual differences perspectives. In Experiment 1, dyslexic and non-dyslexic participants were similarly accurate on reasoning problems, but scores on a measure of visual memory ability only predicted reasoning accuracy for dyslexics. In Experiment 2, a secondary task loaded visual memory resources during concurrent reasoning. Dyslexics were significantly less accurate when reasoning under conditions of high memory load and showed reduced ability to subsequently recall the visual stimuli, suggesting that the memory and reasoning tasks were competing for the same visual cognitive resource. The results are consistent with an explanation based on limitations in the verbal and executive components of working memory in dyslexia and the use of compensatory visual strategies for reasoning. There are implications for cognitive activities that do not readily support visual thinking, whether in education, employment or less formal everyday settings. Copyright © 2014 John Wiley & Sons, Ltd.

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.

Massively parallel support for a case-based planning system

NASA Technical Reports Server (NTRS)

Kettler, Brian P.; Hendler, James A.; Anderson, William A.

1993-01-01

Case-based planning (CBP), a kind of case-based reasoning, is a technique in which previously generated plans (cases) are stored in memory and can be reused to solve similar planning problems in the future. CBP can save considerable time over generative planning, in which a new plan is produced from scratch. CBP thus offers a potential (heuristic) mechanism for handling intractable problems. One drawback of CBP systems has been the need for a highly structured memory to reduce retrieval times. This approach requires significant domain engineering and complex memory indexing schemes to make these planners efficient. In contrast, our CBP system, CaPER, uses a massively parallel frame-based AI language (PARKA) and can do extremely fast retrieval of complex cases from a large, unindexed memory. The ability to do fast, frequent retrievals has many advantages: indexing is unnecessary; very large case bases can be used; memory can be probed in numerous alternate ways; and queries can be made at several levels, allowing more specific retrieval of stored plans that better fit the target problem with less adaptation. In this paper we describe CaPER's case retrieval techniques and some experimental results showing its good performance, even on large case bases.

Multiresolution strategies for the numerical solution of optimal control problems

NASA Astrophysics Data System (ADS)

Jain, Sachin

There exist many numerical techniques for solving optimal control problems but less work has been done in the field of making these algorithms run faster and more robustly. The main motivation of this work is to solve optimal control problems accurately in a fast and efficient way. Optimal control problems are often characterized by discontinuities or switchings in the control variables. One way of accurately capturing the irregularities in the solution is to use a high resolution (dense) uniform grid. This requires a large amount of computational resources both in terms of CPU time and memory. Hence, in order to accurately capture any irregularities in the solution using a few computational resources, one can refine the mesh locally in the region close to an irregularity instead of refining the mesh uniformly over the whole domain. Therefore, a novel multiresolution scheme for data compression has been designed which is shown to outperform similar data compression schemes. Specifically, we have shown that the proposed approach results in fewer grid points in the grid compared to a common multiresolution data compression scheme. The validity of the proposed mesh refinement algorithm has been verified by solving several challenging initial-boundary value problems for evolution equations in 1D. The examples have demonstrated the stability and robustness of the proposed algorithm. The algorithm adapted dynamically to any existing or emerging irregularities in the solution by automatically allocating more grid points to the region where the solution exhibited sharp features and fewer points to the region where the solution was smooth. Thereby, the computational time and memory usage has been reduced significantly, while maintaining an accuracy equivalent to the one obtained using a fine uniform mesh. Next, a direct multiresolution-based approach for solving trajectory optimization problems is developed. The original optimal control problem is transcribed into a nonlinear programming (NLP) problem that is solved using standard NLP codes. The novelty of the proposed approach hinges on the automatic calculation of a suitable, nonuniform grid over which the NLP problem is solved, which tends to increase numerical efficiency and robustness. Control and/or state constraints are handled with ease, and without any additional computational complexity. The proposed algorithm is based on a simple and intuitive method to balance several conflicting objectives, such as accuracy of the solution, convergence, and speed of the computations. The benefits of the proposed algorithm over uniform grid implementations are demonstrated with the help of several nontrivial examples. Furthermore, two sequential multiresolution trajectory optimization algorithms for solving problems with moving targets and/or dynamically changing environments have been developed. For such problems, high accuracy is desirable only in the immediate future, yet the ultimate mission objectives should be accommodated as well. An intelligent trajectory generation for such situations is thus enabled by introducing the idea of multigrid temporal resolution to solve the associated trajectory optimization problem on a non-uniform grid across time that is adapted to: (i) immediate future, and (ii) potential discontinuities in the state and control variables.

Algorithms for Performance, Dependability, and Performability Evaluation using Stochastic Activity Networks

NASA Technical Reports Server (NTRS)

Deavours, Daniel D.; Qureshi, M. Akber; Sanders, William H.

1997-01-01

Modeling tools and technologies are important for aerospace development. At the University of Illinois, we have worked on advancing the state of the art in modeling by Markov reward models in two important areas: reducing the memory necessary to numerically solve systems represented as stochastic activity networks and other stochastic Petri net extensions while still obtaining solutions in a reasonable amount of time, and finding numerically stable and memory-efficient methods to solve for the reward accumulated during a finite mission time. A long standing problem when modeling with high level formalisms such as stochastic activity networks is the so-called state space explosion, where the number of states increases exponentially with size of the high level model. Thus, the corresponding Markov model becomes prohibitively large and solution is constrained by the the size of primary memory. To reduce the memory necessary to numerically solve complex systems, we propose new methods that can tolerate such large state spaces that do not require any special structure in the model (as many other techniques do). First, we develop methods that generate row and columns of the state transition-rate-matrix on-the-fly, eliminating the need to explicitly store the matrix at all. Next, we introduce a new iterative solution method, called modified adaptive Gauss-Seidel, that exhibits locality in its use of data from the state transition-rate-matrix, permitting us to cache portions of the matrix and hence reduce the solution time. Finally, we develop a new memory and computationally efficient technique for Gauss-Seidel based solvers that avoids the need for generating rows of A in order to solve Ax = b. This is a significant performance improvement for on-the-fly methods as well as other recent solution techniques based on Kronecker operators. Taken together, these new results show that one can solve very large models without any special structure.

The Deterministic Information Bottleneck

NASA Astrophysics Data System (ADS)

Strouse, D. J.; Schwab, David

2015-03-01

A fundamental and ubiquitous task that all organisms face is prediction of the future based on past sensory experience. Since an individual's memory resources are limited and costly, however, there is a tradeoff between memory cost and predictive payoff. The information bottleneck (IB) method (Tishby, Pereira, & Bialek 2000) formulates this tradeoff as a mathematical optimization problem using an information theoretic cost function. IB encourages storing as few bits of past sensory input as possible while selectively preserving the bits that are most predictive of the future. Here we introduce an alternative formulation of the IB method, which we call the deterministic information bottleneck (DIB). First, we argue for an alternative cost function, which better represents the biologically-motivated goal of minimizing required memory resources. Then, we show that this seemingly minor change has the dramatic effect of converting the optimal memory encoder from stochastic to deterministic. Next, we propose an iterative algorithm for solving the DIB problem. Additionally, we compare the IB and DIB methods on a variety of synthetic datasets, and examine the performance of retinal ganglion cell populations relative to the optimal encoding strategy for each problem.

Slime mold uses an externalized spatial "memory" to navigate in complex environments.

PubMed

Reid, Chris R; Latty, Tanya; Dussutour, Audrey; Beekman, Madeleine

2012-10-23

Spatial memory enhances an organism's navigational ability. Memory typically resides within the brain, but what if an organism has no brain? We show that the brainless slime mold Physarum polycephalum constructs a form of spatial memory by avoiding areas it has previously explored. This mechanism allows the slime mold to solve the U-shaped trap problem--a classic test of autonomous navigational ability commonly used in robotics--requiring the slime mold to reach a chemoattractive goal behind a U-shaped barrier. Drawn into the trap, the organism must rely on other methods than gradient-following to escape and reach the goal. Our data show that spatial memory enhances the organism's ability to navigate in complex environments. We provide a unique demonstration of a spatial memory system in a nonneuronal organism, supporting the theory that an externalized spatial memory may be the functional precursor to the internal memory of higher organisms.

Understanding and Accommodating Students with Depression in the Classroom

ERIC Educational Resources Information Center

Crundwell, R. Marc; Killu, Kim

2007-01-01

Depression and mood disorders present a significant challenge in the classroom; resulting symptoms can impact memory, recall, motivation, problem solving, task completion, physical and motor skills, and social interactions. Little information is available on practical instructional accommodations and modifications for use by the classroom teacher.…

Exploring Individual Differences in Preschoolers' Causal Stance

ERIC Educational Resources Information Center

Alvarez, Aubry; Booth, Amy E.

2016-01-01

Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In…

Teaching with Technology: Literature and Software.

ERIC Educational Resources Information Center

Allen, Denise

1994-01-01

Reviews five computer programs and compact disc-read only memory (CD-ROM) products designed to improve students' reading and problem-solving skills: (1) "Reading Realities" (Teacher Support Software); (2) "Kid Rhymes" (Creative Pursuits); (3) "First-Start Biographies" (Troll Associates); (4) "My Silly CD of ABCs" (Discis Classroom Editions); and…

The characteristics of failure among students who experienced pseudo thinking

NASA Astrophysics Data System (ADS)

Anggraini, D.; Kusmayadi, T. A.; Pramudya, I.

2018-04-01

The purpose of this research is to describe the thinking process of students who experienced pseudo thinking when solving the straight line equation. The result of this study shows the characteristics of error that caused students to experience pseudo thinking when solving the problem and their relation with students’ metacognition skill. This qualitative research was conducted in State 16 Junior High School in Surakarta, Indonesia during the odd semester of 2017/2018 academic year. The subjects of the study were students Junior High School students of 8th grade chosen using purposive sampling technique. Data were collected through the administration of think aloud method. The result showed that the characteristics of errors among the subjects are: 1) the answers resulted from pseudo thinking when solving the problem were obtained from the spontaneous, fast, unconscious and uncontrolled thinking process; 2) students had misconception; 3) students had tendency to memorize the formula and imitate the completion procedure; 4) students experienced fuzzy memory when solving the problem. From the mistakes among students who experienced pseudo thinking, their metacognition ability could be inferred.

Visual thinking networking promotes long-term meaningful learning and achievement for 9th grade earth science students

NASA Astrophysics Data System (ADS)

Longo, Palma Joni

2001-12-01

An experimental and interview-based design was used to test the efficacy of visual thinking networking (VTN), a new generation of metacognitive learning strategies. Students constructed network diagrams using semantic and figural elements to represent knowledge relationships. The findings indicated the importance of using color in VTN strategies. The use of color promoted the encoding and reconstruction of earth science knowledge in memory and enhanced higher order thinking skills of problem solving. Fifty-six ninth grade earth science students (13--15 years of age) in a suburban school district outside New York City were randomly assigned to three classes with the same instructor. Five major positive findings emerged in the areas of problem solving achievement, organization of knowledge in memory, problem solving strategy dimensionality, conceptual understanding, and gender differences. A multi-covariate analysis was conducted on the pre-post gain scores of the AGI/NSTA Earth Science Examination (Part 1). Students who used the color VTN strategies had a significantly higher mean gain score on the problem solving criterion test items than students who used the black/white VTN (p = .003) and the writing strategies for learning science (p < .001). During a think-out-loud problem solving interview, students who used the color VTN strategies: (1) significantly recalled more earth science knowledge than students who used the black/white VTN (p = .021) and the writing strategies (p < .001); (2) significantly recalled more interrelated earth science knowledge than students who used black/white VTN strategies (p = .048) and the writing strategy (p < .001); (3) significantly used a greater number of action verbs than students who used the writing strategy (p = .033). Students with low abstract reasoning aptitude who used the color VTNs had a significantly higher mean number of conceptually accurate propositions than students who used the black/white VTN (p = .018) and the writing strategies (p = .010). Gender influenced the choice of VTN strategy. Females used significantly more color VTN strategies, while males used predominately black/white VTN strategies (p = .01). A neurocognitive model, the encoding activation theory of the anterior cingulate (ENACT-AC), is proposed as an explanation for these findings.

Computational efficiency improvements for image colorization

NASA Astrophysics Data System (ADS)

Yu, Chao; Sharma, Gaurav; Aly, Hussein

2013-03-01

We propose an efficient algorithm for colorization of greyscale images. As in prior work, colorization is posed as an optimization problem: a user specifies the color for a few scribbles drawn on the greyscale image and the color image is obtained by propagating color information from the scribbles to surrounding regions, while maximizing the local smoothness of colors. In this formulation, colorization is obtained by solving a large sparse linear system, which normally requires substantial computation and memory resources. Our algorithm improves the computational performance through three innovations over prior colorization implementations. First, the linear system is solved iteratively without explicitly constructing the sparse matrix, which significantly reduces the required memory. Second, we formulate each iteration in terms of integral images obtained by dynamic programming, reducing repetitive computation. Third, we use a coarseto- fine framework, where a lower resolution subsampled image is first colorized and this low resolution color image is upsampled to initialize the colorization process for the fine level. The improvements we develop provide significant speedup and memory savings compared to the conventional approach of solving the linear system directly using off-the-shelf sparse solvers, and allow us to colorize images with typical sizes encountered in realistic applications on typical commodity computing platforms.

[Organization of out-patient psychiatric care in dementia and cognitive impairment in aged. Part II: Clinical and economic efficacy of memory clinics and Alzheimer's disease centers].

PubMed

Mikhaylova, N M

The part II of the review is focused on a history of developing of memory clinics and Alzheimer's disease centers as well as on the indices of their activity in various countries and in Russia. Approaches to the evaluation of clinical and economic efficacy of new technologies of organization of care and a role of the national programs in solving of the problem of old age dementias were considered.

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.

An Intervention to Maximize Medication Management by Caregivers of Persons with Memory Loss: Intervention Overview and Two-Month Outcomes

PubMed Central

Lingler, Jennifer H.; Arida, Janet; Houze, Martin; Kaufman, Robert; Knox, Melissa; Sereika, Susan M.; Tamres, Lisa; Erlen, Judith; Amspaugh, Carolyn; Tang, Fengyan; Happ, Mary Beth

2016-01-01

Overseeing medication-taking is a critical aspect of dementia caregiving. This randomized controlled trial examined the efficacy of a tailored, problem-solving intervention designed to maximize medication management practices among caregivers of persons with memory loss. Eighty-three community-dwelling dyads (patient + informal caregiver) with a baseline average of 3 medication deficiencies participated. Home- and telephone-based sessions were delivered by nurse or social worker interventionists and addressed basic aspects of managing medications, plus tailored problem solving for specific challenges. The outcome of medication management practices was assessed using the Medication Management Instrument for Deficiencies in the Elderly (MedMaIDE) and an investigator-developed Medication Deficiency Checklist (MDC). Linear mixed modeling showed both the intervention and usual care groups had decreases in medication management problems as measured by the MedMaIDE (F=6.91, p<.01) and MDC (F=9.72, p<.01) at 2 months post-intervention. The phenomenon of reduced medication deficiencies in both groups suggests that when nurses or social workers merely raise awareness of the importance of medication adherence, there may be benefit. PMID:26804450

Sparse distributed memory: understanding the speed and robustness of expert memory

PubMed Central

Brogliato, Marcelo S.; Chada, Daniel M.; Linhares, Alexandre

2014-01-01

How can experts, sometimes in exacting detail, almost immediately and very precisely recall memory items from a vast repertoire? The problem in which we will be interested concerns models of theoretical neuroscience that could explain the speed and robustness of an expert's recollection. The approach is based on Sparse Distributed Memory, which has been shown to be plausible, both in a neuroscientific and in a psychological manner, in a number of ways. A crucial characteristic concerns the limits of human recollection, the “tip-of-tongue” memory event—which is found at a non-linearity in the model. We expand the theoretical framework, deriving an optimization formula to solve this non-linearity. Numerical results demonstrate how the higher frequency of rehearsal, through work or study, immediately increases the robustness and speed associated with expert memory. PMID:24808842

Executive Function and Mathematics Achievement: Are Effects Construct- and Time-General or Specific?

ERIC Educational Resources Information Center

Duncan, Robert; Nguyen, Tutrang; Miao, Alicia; McClelland, Megan; Bailey, Drew

2016-01-01

Executive function (EF) is considered a set of interrelated cognitive processes, including inhibitory control, working memory, and attentional shifting, that are connected to the development of the prefrontal cortex and contribute to children's problem solving skills and self regulatory behavior (Best & Miller, 2010; Garon, Bryson, &…

Developing Cognition with Collaborative Robotic Activities

ERIC Educational Resources Information Center

Mitnik, Ruben; Nussbaum, Miguel; Recabarren, Matias

2009-01-01

Cognition, faculty related to perception, imagination, memory, and problem solving, refers to internal mental processes through which sensorial input is acquired, elaborated, used, and stored. One of its importances relies on the fact that it affects in a direct way the learning potential. It has been shown that, even thou cognitive processes…

An Information Theoretic Model for the Human Processing of Cognitive Tasks.

ERIC Educational Resources Information Center

Moser, Gene W.

An information-theory model of human memory was tested in thirteen experiments which involved children (six years and older) and graduate students. The subjects conducted science investigations in laboratory and non-laboratory settings, solved problems of electrical circuits, and participated in classroom science lessons. The tasks used involved…

Presenting: Research and Educational Innovation with Video Games

ERIC Educational Resources Information Center

Méndez, Laura; del Moral, M. Esther

2015-01-01

Video games are starting to be considered for uses other than mere entertainment or recreation--as vehicles that promote implicit learning, given their attractive formula for training different types of cognitive skills (observation, memory, problem solving, etc.); as catalysts for learning processes; and even as learning contexts in themselves.…

Toward High-Performance Communications Interfaces for Science Problem Solving

ERIC Educational Resources Information Center

Oviatt, Sharon L.; Cohen, Adrienne O.

2010-01-01

From a theoretical viewpoint, educational interfaces that facilitate communicative actions involving representations central to a domain can maximize students' effort associated with constructing new schemas. In addition, interfaces that minimize working memory demands due to the interface per se, for example by mimicking existing non-digital work…

Enclothed Cognition and Controlled Attention during Insight Problem-Solving

ERIC Educational Resources Information Center

Van Stockum, Charles A., Jr.; DeCaro, Marci S.

2014-01-01

Individual differences in working memory capacity (WMC) increase the ability and tendency to devote greater attentional control to a task--improving performance on a wide range of skills. In addition, recent research on enclothed cognition demonstrates that the situational influence of wearing a white lab coat increases controlled attention, due…

Schemas in Problem Solving: An Integrated Model of Learning, Memory, and Instruction

DTIC Science & Technology

1992-01-01

article: "Hybrid Computation in Cognitive Science: Neural Networks and Symbols" (J. A. Anderson, 1990). And, Marvin Minsky echoes the sentiment in his...distributed processing: A handbook of models, programs, and exercises. Cambridge, MA: The MIT Press. Minsky , M. (1991). Logical versus analogical or symbolic

Adaptive Memory: Young Children Show Enhanced Retention of Fitness-Related Information

ERIC Educational Resources Information Center

Aslan, Alp; Bauml, Karl-Heinz T.

2012-01-01

Evolutionary psychologists propose that human cognition evolved through natural selection to solve adaptive problems related to survival and reproduction, with its ultimate function being the enhancement of reproductive fitness. Following this proposal and the evolutionary-developmental view that ancestral selection pressures operated not only on…

On the effective implementation of a boundary element code on graphics processing units unsing an out-of-core LU algorithm

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

D'Azevedo, Ed F; Nintcheu Fata, Sylvain

2012-01-01

A collocation boundary element code for solving the three-dimensional Laplace equation, publicly available from \\url{http://www.intetec.org}, has been adapted to run on an Nvidia Tesla general purpose graphics processing unit (GPU). Global matrix assembly and LU factorization of the resulting dense matrix were performed on the GPU. Out-of-core techniques were used to solve problems larger than available GPU memory. The code achieved over eight times speedup in matrix assembly and about 56~Gflops/sec in the LU factorization using only 512~Mbytes of GPU memory. Details of the GPU implementation and comparisons with the standard sequential algorithm are included to illustrate the performance ofmore » the GPU code.« less

Memory as behavior: The importance of acquisition and remembering strategies

PubMed Central

Delaney, Peter F.; Austin, John

1998-01-01

The study of memory has traditionally been the province of cognitive psychology, which has postulated different memory systems that store memory traces to explain remembering. Behavioral psychologists have been unsuccessful at empirically identifying the behavior that occurs during remembering because so much of it occurs rapidly and covertly. In addition, behavior analysts have generally been disinterested in studying transient phenomena such as memory. As a result, the cognitive interpretation has been the only one that has made and tested useful predictions. Recent experimental evidence acquired while having participants “think aloud” suggests that a behavioral approach to memory may provide a superior account of memory performance and allow applied scientists to observe and modify memory-related behavior with well-known applied behavior-analytic techniques. We review evidence supporting and extending the interpretation of memory provided by Palmer (1991), who described memory in terms of precurrent behavior that occurs at the time of acquisition in preparation for problem solving that occurs at the time of remembering. ImagesFig. 1 PMID:22477129

The role of sleep in cognitive processing: focusing on memory consolidation.

PubMed

Chambers, Alexis M

2017-05-01

Research indicates that sleep promotes various cognitive functions, such as decision-making, language, categorization, and memory. Of these, most work has focused on the influence of sleep on memory, with ample work showing that sleep enhances memory consolidation, a process that stores new memories in the brain over time. Recent psychological and neurophysiological research has vastly increased understanding of this process. Such work not only suggests that consolidation relies on plasticity-related mechanisms that reactivate and stabilize memory representations, but also that this process may be experimentally manipulated by methods that target which memory traces are reactivated during sleep. Furthermore, aside from memory storage capabilities, memory consolidation also appears to reorganize and integrate memories with preexisting knowledge, which may facilitate the discovery of underlying rules and associations that benefit other cognitive functioning, including problem solving and creativity. WIREs Cogn Sci 2017, 8:e1433. doi: 10.1002/wcs.1433 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

Reducing computational costs in large scale 3D EIT by using a sparse Jacobian matrix with block-wise CGLS reconstruction.

PubMed

Yang, C L; Wei, H Y; Adler, A; Soleimani, M

2013-06-01

Electrical impedance tomography (EIT) is a fast and cost-effective technique to provide a tomographic conductivity image of a subject from boundary current-voltage data. This paper proposes a time and memory efficient method for solving a large scale 3D EIT inverse problem using a parallel conjugate gradient (CG) algorithm. The 3D EIT system with a large number of measurement data can produce a large size of Jacobian matrix; this could cause difficulties in computer storage and the inversion process. One of challenges in 3D EIT is to decrease the reconstruction time and memory usage, at the same time retaining the image quality. Firstly, a sparse matrix reduction technique is proposed using thresholding to set very small values of the Jacobian matrix to zero. By adjusting the Jacobian matrix into a sparse format, the element with zeros would be eliminated, which results in a saving of memory requirement. Secondly, a block-wise CG method for parallel reconstruction has been developed. The proposed method has been tested using simulated data as well as experimental test samples. Sparse Jacobian with a block-wise CG enables the large scale EIT problem to be solved efficiently. Image quality measures are presented to quantify the effect of sparse matrix reduction in reconstruction results.

NAS technical summaries: Numerical aerodynamic simulation program, March 1991 - February 1992

NASA Technical Reports Server (NTRS)

1992-01-01

NASA created the Numerical Aerodynamic Simulation (NAS) Program in 1987 to focus resources on solving critical problems in aeroscience and related disciplines by utilizing the power of the most advanced supercomputers available. The NAS Program provides scientists with the necessary computing power to solve today's most demanding computational fluid dynamics problems and serves as a pathfinder in integrating leading-edge supercomputing technologies, thus benefiting other supercomputer centers in Government and industry. This report contains selected scientific results from the 1991-92 NAS Operational Year, March 4, 1991 to March 3, 1992, which is the fifth year of operation. During this year, the scientific community was given access to a Cray-2 and a Cray Y-MP. The Cray-2, the first generation supercomputer, has four processors, 256 megawords of central memory, and a total sustained speed of 250 million floating point operations per second. The Cray Y-MP, the second generation supercomputer, has eight processors and a total sustained speed of one billion floating point operations per second. Additional memory was installed this year, doubling capacity from 128 to 256 megawords of solid-state storage-device memory. Because of its higher performance, the Cray Y-MP delivered approximately 77 percent of the total number of supercomputer hours used during this year.

HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization

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

Kannan, Ramakrishnan; Sukumar, Sreenivas R.; Ballard, Grey M.

NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems formore » $$\\WW$$ and $$\\HH$$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $$\\WW$$ and $$\\HH$$ within the alternating iterations.« less

Age and Gender Differences in Emotion Regulation Strategies: Autobiographical Memory, Rumination, Problem Solving and Distraction.

PubMed

Ricarte Trives, Jorge Javier; Navarro Bravo, Beatriz; Latorre Postigo, José Miguel; Ros Segura, Laura; Watkins, Ed

2016-07-18

Our study tested the hypothesis that older adults and men use more adaptive emotion regulatory strategies but fewer negative emotion regulatory strategies than younger adults and women. In addition, we tested the hypothesis that rumination acts as a mediator variable for the effect of age and gender on depression scores. Differences in rumination, problem solving, distraction, autobiographical recall and depression were assessed in a group of young adults (18-29 years) compared to a group of older adults (50-76 years). The older group used more problem solving and distraction strategies when in a depressed state than their younger counterparts (ps .06). Ordinary least squares regression analyses with bootstrapping showed that rumination mediated the association between age, gender and depression scores. These results suggest that older adults and men select more adaptive strategies to regulate emotions than young adults and women with rumination acting as a significant mediator variable in the association between age, gender, and depression.

Performance comparison of a new hybrid conjugate gradient method under exact and inexact line searches

NASA Astrophysics Data System (ADS)

Ghani, N. H. A.; Mohamed, N. S.; Zull, N.; Shoid, S.; Rivaie, M.; Mamat, M.

2017-09-01

Conjugate gradient (CG) method is one of iterative techniques prominently used in solving unconstrained optimization problems due to its simplicity, low memory storage, and good convergence analysis. This paper presents a new hybrid conjugate gradient method, named NRM1 method. The method is analyzed under the exact and inexact line searches in given conditions. Theoretically, proofs show that the NRM1 method satisfies the sufficient descent condition with both line searches. The computational result indicates that NRM1 method is capable in solving the standard unconstrained optimization problems used. On the other hand, the NRM1 method performs better under inexact line search compared with exact line search.

Parallel algorithms for boundary value problems

NASA Technical Reports Server (NTRS)

Lin, Avi

1990-01-01

A general approach to solve boundary value problems numerically in a parallel environment is discussed. The basic algorithm consists of two steps: the local step where all the P available processors work in parallel, and the global step where one processor solves a tridiagonal linear system of the order P. The main advantages of this approach are two fold. First, this suggested approach is very flexible, especially in the local step and thus the algorithm can be used with any number of processors and with any of the SIMD or MIMD machines. Secondly, the communication complexity is very small and thus can be used as easily with shared memory machines. Several examples for using this strategy are discussed.

Concurrent validity and clinical usefulness of several individually administered tests of children's social-emotional cognition.

PubMed

McKown, Clark

2007-03-01

In this study, the validity of 5 tests of children's social-emotional cognition, defined as their encoding, memory, and interpretation of social information, was tested. Participants were 126 clinic-referred children between the ages of 5 and 17. All 5 tests were evaluated in terms of their (a) concurrent validity, (b) incremental validity, and (c) clinical usefulness in predicting social functioning. Tests included measures of nonverbal sensitivity, social language, and social problem solving. Criterion measures included parent and teacher report of social functioning. Analyses support the concurrent validity of all measures, and the incremental validity and clinical usefulness of tests of pragmatic language and problem solving.

A comparison of several methods of solving nonlinear regression groundwater flow problems

USGS Publications Warehouse

Cooley, Richard L.

1985-01-01

Computational efficiency and computer memory requirements for four methods of minimizing functions were compared for four test nonlinear-regression steady state groundwater flow problems. The fastest methods were the Marquardt and quasi-linearization methods, which required almost identical computer times and numbers of iterations; the next fastest was the quasi-Newton method, and last was the Fletcher-Reeves method, which did not converge in 100 iterations for two of the problems. The fastest method per iteration was the Fletcher-Reeves method, and this was followed closely by the quasi-Newton method. The Marquardt and quasi-linearization methods were slower. For all four methods the speed per iteration was directly related to the number of parameters in the model. However, this effect was much more pronounced for the Marquardt and quasi-linearization methods than for the other two. Hence the quasi-Newton (and perhaps Fletcher-Reeves) method might be more efficient than either the Marquardt or quasi-linearization methods if the number of parameters in a particular model were large, although this remains to be proven. The Marquardt method required somewhat less central memory than the quasi-linearization metilod for three of the four problems. For all four problems the quasi-Newton method required roughly two thirds to three quarters of the memory required by the Marquardt method, and the Fletcher-Reeves method required slightly less memory than the quasi-Newton method. Memory requirements were not excessive for any of the four methods.

Large-scale inverse model analyses employing fast randomized data reduction

NASA Astrophysics Data System (ADS)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

Multiagent optimization system for solving the traveling salesman problem (TSP).

PubMed

Xie, Xiao-Feng; Liu, Jiming

2009-04-01

The multiagent optimization system (MAOS) is a nature-inspired method, which supports cooperative search by the self-organization of a group of compact agents situated in an environment with certain sharing public knowledge. Moreover, each agent in MAOS is an autonomous entity with personal declarative memory and behavioral components. In this paper, MAOS is refined for solving the traveling salesman problem (TSP), which is a classic hard computational problem. Based on a simplified MAOS version, in which each agent manipulates on extremely limited declarative knowledge, some simple and efficient components for solving TSP, including two improving heuristics based on a generalized edge assembly recombination, are implemented. Compared with metaheuristics in adaptive memory programming, MAOS is particularly suitable for supporting cooperative search. The experimental results on two TSP benchmark data sets show that MAOS is competitive as compared with some state-of-the-art algorithms, including the Lin-Kernighan-Helsgaun, IBGLK, PHGA, etc., although MAOS does not use any explicit local search during the runtime. The contributions of MAOS components are investigated. It indicates that certain clues can be positive for making suitable selections before time-consuming computation. More importantly, it shows that the cooperative search of agents can achieve an overall good performance with a macro rule in the switch mode, which deploys certain alternate search rules with the offline performance in negative correlations. Using simple alternate rules may prevent the high difficulty of seeking an omnipotent rule that is efficient for a large data set.

CSOLNP: Numerical Optimization Engine for Solving Non-linearly Constrained Problems.

PubMed

Zahery, Mahsa; Maes, Hermine H; Neale, Michael C

2017-08-01

We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://ab-initio.mit.edu/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.

Crystallized verbal skills in schizophrenia: relationship to neurocognition, symptoms, and functional status.

PubMed

Kurtz, Matthew M; Donato, Jad; Rose, Jennifer

2011-11-01

To study the relationship of superior (i.e., ≥ 90th percentile), average (11th-89th percentile) or extremely low (i.e., ≤ 10th percentile) crystallized verbal skills to neurocognitive profiles, symptoms and everyday life function in schizophrenia. Crystallized verbal skill was derived from Vocabulary subtest scores from the Wechsler Adult Intelligence Scale (WAIS). Out of a sample of 165 stable outpatients with schizophrenia we identified 25 participants with superior crystallized verbal skill, 104 participants with average verbal skill, and 36 participants with extremely low crystallized verbal skill. Each participant was administered measures of attention, working memory, verbal learning and memory, problem-solving and processing speed, as well as symptom and performance-based adaptive life skill assessments. The magnitude of neuropsychological impairment across the three groups was different, after adjusting for group differences in education and duration of illness. Working memory, and verbal learning and memory skills were different across all three groups, while processing speed differentiated the extremely low verbal skill group from the other two groups and problem-solving differentiated the very low verbal skill group from the superior verbal skill group. There were no group differences in sustained attention. Capacity measures of everyday life skills were different across each of the three groups. Crystallized verbal skill in schizophrenia is related to the magnitude of impairment in neurocognitive function and performance-based skills in everyday life function. Patterns of neuropsychological impairment were similar across different levels of crystallized verbal skill.

Electronic shift register memory based on molecular electron-transfer reactions

NASA Technical Reports Server (NTRS)

Hopfield, J. J.; Onuchic, Jose Nelson; Beratan, David N.

1989-01-01

The design of a shift register memory at the molecular level is described in detail. The memory elements are based on a chain of electron-transfer molecules incorporated on a very large scale integrated (VLSI) substrate, and the information is shifted by photoinduced electron-transfer reactions. The design requirements for such a system are discussed, and several realistic strategies for synthesizing these systems are presented. The immediate advantage of such a hybrid molecular/VLSI device would arise from the possible information storage density. The prospect of considerable savings of energy per bit processed also exists. This molecular shift register memory element design solves the conceptual problems associated with integrating molecular size components with larger (micron) size features on a chip.

Human sex differences in solving a virtual navigation problem.

PubMed

Astur, Robert S; Purton, Andrea J; Zaniewski, Melanie J; Cimadevilla, Jose; Markus, Etan J

2016-07-15

The current study examined sex differences in initial and subsequent strategies in solving a navigational problem within a virtual reality environment. We tested 163 undergraduates on a virtual T-maze task that included probe trials designed to assess whether participants were responding using either a place or response strategy. Participants were also tested on a mental rotation task and memory of the details of the virtual room. There were no differences between the sexes in copying or recalling a map of the room or on first trial performance of the T-maze. However, at trial two, males show a significant advantage in solving the task, and approximately 80% of the males adopt a place strategy to solve the T-maze whereas females at that point showed no strategy preference. Across all testing, both males and females preferentially used a place strategy. We discuss how factors such as spatial priming affect strategy preferences and how such factors may differentially affect males and females. Copyright © 2016 Elsevier B.V. All rights reserved.

Efficient Inversion of Mult-frequency and Multi-Source Electromagnetic Data

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

Gary D. Egbert

2007-03-22

The project covered by this report focused on development of efficient but robust non-linear inversion algorithms for electromagnetic induction data, in particular for data collected with multiple receivers, and multiple transmitters, a situation extremely common in eophysical EM subsurface imaging methods. A key observation is that for such multi-transmitter problems each step in commonly used linearized iterative limited memory search schemes such as conjugate gradients (CG) requires solution of forward and adjoint EM problems for each of the N frequencies or sources, essentially generating data sensitivities for an N dimensional data-subspace. These multiple sensitivities allow a good approximation to themore » full Jacobian of the data mapping to be built up in many fewer search steps than would be required by application of textbook optimization methods, which take no account of the multiplicity of forward problems that must be solved for each search step. We have applied this idea to a develop a hybrid inversion scheme that combines features of the iterative limited memory type methods with a Newton-type approach using a partial calculation of the Jacobian. Initial tests on 2D problems show that the new approach produces results essentially identical to a Newton type Occam minimum structure inversion, while running more rapidly than an iterative (fixed regularization parameter) CG style inversion. Memory requirements, while greater than for something like CG, are modest enough that even in 3D the scheme should allow 3D inverse problems to be solved on a common desktop PC, at least for modest (~ 100 sites, 15-20 frequencies) data sets. A secondary focus of the research has been development of a modular system for EM inversion, using an object oriented approach. This system has proven useful for more rapid prototyping of inversion algorithms, in particular allowing initial development and testing to be conducted with two-dimensional example problems, before approaching more computationally cumbersome three-dimensional problems.« less

Cognition-emotion interactions: patterns of change and implications for math problem solving

PubMed Central

Trezise, Kelly; Reeve, Robert A.

2014-01-01

Surprisingly little is known about whether relationships between cognitive and emotional states remain stable or change over time, or how different patterns of stability and/or change in the relationships affect problem solving abilities. Nevertheless, cross-sectional studies show that anxiety/worry may reduce working memory (WM) resources, and the ability to minimize the effects anxiety/worry is higher in individuals with greater WM capacity. To investigate the patterns of stability and/or change in cognition-emotion relations over time and their implications for problem solving, 126 14-year-olds’ algebraic WM and worry levels were assessed twice in a single day before completing an algebraic math problem solving test. We used latent transition analysis to identify stability/change in cognition-emotion relations, which yielded a six subgroup solution. Subgroups varied in WM capacity, worry, and stability/change relationships. Among the subgroups, we identified a high WM/low worry subgroup that remained stable over time and a high WM/high worry, and a moderate WM/low worry subgroup that changed to low WM subgroups over time. Patterns of stability/change in subgroup membership predicted algebraic test results. The stable high WM/low worry subgroup performed best and the low WM capacity-high worry “unstable across time” subgroup performed worst. The findings highlight the importance of assessing variations in cognition-emotion relationships over time (rather than assessing cognition or emotion states alone) to account for differences in problem solving abilities. PMID:25132830

Route selection by rats and humans in a navigational traveling salesman problem.

PubMed

Blaser, Rachel E; Ginchansky, Rachel R

2012-03-01

Spatial cognition is typically examined in non-human animals from the perspective of learning and memory. For this reason, spatial tasks are often constrained by the time necessary for training or the capacity of the animal's short-term memory. A spatial task with limited learning and memory demands could allow for more efficient study of some aspects of spatial cognition. The traveling salesman problem (TSP), used to study human visuospatial problem solving, is a simple task with modifiable learning and memory requirements. In the current study, humans and rats were characterized in a navigational version of the TSP. Subjects visited each of 10 baited targets in any sequence from a set starting location. Unlike similar experiments, the roles of learning and memory were purposely minimized; all targets were perceptually available, no distracters were used, and each configuration was tested only once. The task yielded a variety of behavioral measures, including target revisits and omissions, route length, and frequency of transitions between each pair of targets. Both humans and rats consistently chose routes that were more efficient than chance, but less efficient than optimal, and generally less efficient than routes produced by the nearest-neighbor strategy. We conclude that the TSP is a useful and flexible task for the study of spatial cognition in human and non-human animals.

Hybrid multicore/vectorisation technique applied to the elastic wave equation on a staggered grid

NASA Astrophysics Data System (ADS)

Titarenko, Sofya; Hildyard, Mark

2017-07-01

In modern physics it has become common to find the solution of a problem by solving numerically a set of PDEs. Whether solving them on a finite difference grid or by a finite element approach, the main calculations are often applied to a stencil structure. In the last decade it has become usual to work with so called big data problems where calculations are very heavy and accelerators and modern architectures are widely used. Although CPU and GPU clusters are often used to solve such problems, parallelisation of any calculation ideally starts from a single processor optimisation. Unfortunately, it is impossible to vectorise a stencil structured loop with high level instructions. In this paper we suggest a new approach to rearranging the data structure which makes it possible to apply high level vectorisation instructions to a stencil loop and which results in significant acceleration. The suggested method allows further acceleration if shared memory APIs are used. We show the effectiveness of the method by applying it to an elastic wave propagation problem on a finite difference grid. We have chosen Intel architecture for the test problem and OpenMP (Open Multi-Processing) since they are extensively used in many applications.

Parallel structures in human and computer memory

NASA Astrophysics Data System (ADS)

Kanerva, Pentti

1986-08-01

If we think of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library: We recognize a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. This paper is about how to construct a computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do. Such a memory is remarkably similar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. The paper concludes that the frame problem of artificial intelligence could be solved by the use of such a memory if we were able to encode information about the world properly.

Adaptive constructive processes and the future of memory.

PubMed

Schacter, Daniel L

2012-11-01

Memory serves critical functions in everyday life but is also prone to error. This article examines adaptive constructive processes, which play a functional role in memory and cognition but can also produce distortions, errors, and illusions. The article describes several types of memory errors that are produced by adaptive constructive processes and focuses in particular on the process of imagining or simulating events that might occur in one's personal future. Simulating future events relies on many of the same cognitive and neural processes as remembering past events, which may help to explain why imagination and memory can be easily confused. The article considers both pitfalls and adaptive aspects of future event simulation in the context of research on planning, prediction, problem solving, mind-wandering, prospective and retrospective memory, coping and positivity bias, and the interconnected set of brain regions known as the default network. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Implicit memory. Retention without remembering.

PubMed

Roediger, H L

1990-09-01

Explicit measures of human memory, such as recall or recognition, reflect conscious recollection of the past. Implicit tests of retention measure transfer (or priming) from past experience on tasks that do not require conscious recollection of recent experiences for their performance. The article reviews research on the relation between explicit and implicit memory. The evidence points to substantial differences between standard explicit and implicit tests, because many variables create dissociations between these tests. For example, although pictures are remembered better than words on explicit tests, words produce more priming than do pictures on several implicit tests. These dissociations may implicate different memory systems that subserve distinct memorial functions, but the present argument is that many dissociations can be understood by appealing to general principles that apply to both explicit and implicit tests. Phenomena studied under the rubric of implicit memory may have important implications in many other fields, including social cognition, problem solving, and cognitive development.

Making Memories Matter

PubMed Central

Gold, Paul E.; Korol, Donna L.

2012-01-01

This article reviews some of the neuroendocrine bases by which emotional events regulate brain mechanisms of learning and memory. In laboratory rodents, there is extensive evidence that epinephrine influences memory processing through an inverted-U relationship, at which moderate levels enhance and high levels impair memory. These effects are, in large part, mediated by increases in blood glucose levels subsequent to epinephrine release, which then provide support for the brain processes engaged by learning and memory. These brain processes include augmentation of neurotransmitter release and of energy metabolism, the latter apparently including a key role for astrocytic glycogen. In addition to up- and down-regulation of learning and memory in general, physiological concomitants of emotion and arousal can also switch the neural system that controls learning at a particular time, at once improving some attributes of learning and impairing others in a manner that results in a change in the strategy used to solve a problem. PMID:23264764

Parallel structures in human and computer memory

NASA Technical Reports Server (NTRS)

Kanerva, P.

1986-01-01

If one thinks of our experiences as being recorded continuously on film, then human memory can be compared to a film library that is indexed by the contents of the film strips stored in it. Moreover, approximate retrieval cues suffice to retrieve information stored in this library. One recognizes a familiar person in a fuzzy photograph or a familiar tune played on a strange instrument. A computer memory that would allow a computer to recognize patterns and to recall sequences the way humans do is constructed. Such a memory is remarkably similiar in structure to a conventional computer memory and also to the neural circuits in the cortex of the cerebellum of the human brain. It is concluded that the frame problem of artificial intelligence could be solved by the use of such a memory if one were able to encode information about the world properly.

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…

Psychometric Properties of a Newly Developed Learning Difficulties Scale in the Omani Society

ERIC Educational Resources Information Center

Al-Qaryout, Ibrahim A.; Abu-Hilal, Maher M.; Alsulaimani, Humaira

2013-01-01

Introduction: Learning difficulties (LD) is a recent construct. It has been agreed that the individual who suffers from learning difficulties has a disorder in one or more of the basis psychological processes, including attention, cognition, formation of concepts, memory, problem solving, understanding or reading, speaking or writing, or…

Play and Cognitive Development: Formal Operational Perspective of Piaget's Theory

ERIC Educational Resources Information Center

Ahmad, Saghir; Ch, Abid Hussain; Batool, Ayesha; Sittar, Khadija; Malik, Misbah

2016-01-01

Cognitive development is the construction of thought processes, including remembering, problem solving and decision making, from childhood through adolescence to adulthood. Play contributes to cognitive development in a number of ways. It helps children to develop imaginary and memory which is essential for thinking about past, present and future.…

The Effects of Distraction on Cognitive Task Performance during Toddlerhood

ERIC Educational Resources Information Center

Wyss, Nancy M.; Kannass, Kathleen N.; Haden, Catherine A.

2013-01-01

We investigated the effects of distraction on attention and task performance during toddlerhood. Thirty toddlers (24- to 26-month-olds) completed different tasks (2 of each: categorization, problem solving, memory, free play) in one of two conditions: No Distraction or Distraction. The results revealed that the distractor had varying effects on…

Memorisation Methods in Science Education: Tactics to Improve the Teaching and Learning Practice

ERIC Educational Resources Information Center

Pals, Frits F. B.; Tolboom, Jos L. J.; Suhre, Cor J. M.; van Geert, Paul L. C.

2018-01-01

How can science teachers support students in developing an appropriate declarative knowledge base for solving problems? This article focuses on the question whether the development of students' memory of scientific propositions is better served by writing propositions down on paper or by making drawings of propositions either by silent or…

Hippity Hops Velcroed to the Floor and Other Strategies to Educate Kids with FAS or FAE.

ERIC Educational Resources Information Center

Wescott, Siobhan

1991-01-01

Children with fetal alcohol syndrome may exhibit hyperactivity, hypersensitivity to touch, attention deficit disorder, stimulus overload, or an overtrusting nature. Educational strategies include consistent routines, multisensory cues to prompt memory, problem-solving training to recognize options, and emphasis on social skills and daily living…

Using Guided Participation to Support Young Children's Social Development

ERIC Educational Resources Information Center

Petty, Karen

2009-01-01

Families and teachers spend countless hours supporting preschoolers and primary age children in the development of mental tools like focus, memory, and other problem-solving skills that help children think better, pay attention, and remember what they have experienced. Children use these tools to succeed in reading, writing, math, science, and…

Schemas in Problem Solving: An Integrated Model of Learning, Memory, and Instruction

DTIC Science & Technology

1992-01-01

reflected in the title of a recent article: "lybid Coupation, in Cognitive Science: Neural Networks ad Symbl (3. A Andesson, 1990). And, Marvin Mtuky...Rumneihart, D. E (1989). Explorations in parallel distributed processing: A handbook of models, programs, and exercises. Cambridge, MA: The MrT Press. Minsky

The Importance of Additive Reasoning in Children's Mathematical Achievement: A Longitudinal Study

ERIC Educational Resources Information Center

Ching, Boby Ho-Hong; Nunes, Terezinha

2017-01-01

This longitudinal study examines the relative importance of counting ability, additive reasoning, and working memory in children's mathematical achievement (calculation and story problem solving). In Hong Kong, 115 Chinese children aged 6 years old participated in 2 waves of assessments (T1 = first grade and T2 = second grade). Multiple regression…

A Framework for Understanding Young Children with Severe Multiple Disabilities: The van Dijk Approach to Assessment.

ERIC Educational Resources Information Center

Nelson, Catherine; van Dijk, Jan; McDonnell, Andrea P.; Thompson, Kristina

2002-01-01

This article describes a framework for assessing young children with severe multiple disabilities. The assessment is child-led and examines underlying processes of learning, including biobehavioral state, orienting response, learning channels, approach-withdrawal, memory, interactions, communication, and problem solving. Case studies and a sample…

Diagnostic reasoning strategies and diagnostic success.

PubMed

Coderre, S; Mandin, H; Harasym, P H; Fick, G H

2003-08-01

Cognitive psychology research supports the notion that experts use mental frameworks or "schemes", both to organize knowledge in memory and to solve clinical problems. The central purpose of this study was to determine the relationship between problem-solving strategies and the likelihood of diagnostic success. Think-aloud protocols were collected to determine the diagnostic reasoning used by experts and non-experts when attempting to diagnose clinical presentations in gastroenterology. Using logistic regression analysis, the study found that there is a relationship between diagnostic reasoning strategy and the likelihood of diagnostic success. Compared to hypothetico-deductive reasoning, the odds of diagnostic success were significantly greater when subjects used the diagnostic strategies of pattern recognition and scheme-inductive reasoning. Two other factors emerged as independent determinants of diagnostic success: expertise and clinical presentation. Not surprisingly, experts outperformed novices, while the content area of the clinical cases in each of the four clinical presentations demonstrated varying degrees of difficulty and thus diagnostic success. These findings have significant implications for medical educators. It supports the introduction of "schemes" as a means of enhancing memory organization and improving diagnostic success.

Emotional Intelligence and cognitive abilities - associations and sex differences.

PubMed

Pardeller, Silvia; Frajo-Apor, Beatrice; Kemmler, Georg; Hofer, Alex

2017-09-01

In order to expand on previous research, this cross-sectional study investigated the relationship between Emotional Intelligence (EI) and cognitive abilities in healthy adults with a special focus on potential sex differences. EI was assessed by means of the Mayer-Salovey-Caruso-Emotional-Intelligence Test (MSCEIT), whereas cognitive abilities were investigated using the Brief Assessment of Cognition in Schizophrenia (BACS), which measures key aspects of cognitive functioning, i.e. verbal memory, working memory, motor speed, verbal fluency, attention and processing speed, and reasoning and problem solving. 137 subjects (65% female) with a mean age of 38.7 ± 11.8 years were included into the study. While males and females were comparable with regard to EI, men achieved significantly higher BACS composite scores and outperformed women in the BACS subscales motor speed, attention and processing speed, and reasoning and problem solving. Verbal fluency significantly predicted EI, whereas the MSCEIT subscale understanding emotions significantly predicted the BACS composite score. Our findings support previous research and emphasize the relevance of considering cognitive abilities when assessing ability EI in healthy individuals.

Adolescents’ Functional Numeracy Is Predicted by Their School Entry Number System Knowledge

PubMed Central

Geary, David C.; Hoard, Mary K.; Nugent, Lara; Bailey, Drew H.

2013-01-01

One in five adults in the United States is functionally innumerate; they do not possess the mathematical competencies needed for many modern jobs. We administered functional numeracy measures used in studies of young adults’ employability and wages to 180 thirteen-year-olds. The adolescents began the study in kindergarten and participated in multiple assessments of intelligence, working memory, mathematical cognition, achievement, and in-class attentive behavior. Their number system knowledge at the beginning of first grade was defined by measures that assessed knowledge of the systematic relations among Arabic numerals and skill at using this knowledge to solve arithmetic problems. Early number system knowledge predicted functional numeracy more than six years later (ß = 0.195, p = .0014) controlling for intelligence, working memory, in-class attentive behavior, mathematical achievement, demographic and other factors, but skill at using counting procedures to solve arithmetic problems did not. In all, we identified specific beginning of schooling numerical knowledge that contributes to individual differences in adolescents’ functional numeracy and demonstrated that performance on mathematical achievement tests underestimates the importance of this early knowledge. PMID:23382934

Convergent thinking and traumatic brain injury: an investigation of performance on the remote associate test.

PubMed

Rigon, Arianna; Reber, Justin; Patel, Nirav N; Duff, Melissa C

2018-06-08

While deficits in several cognitive domains following moderate-to-severe traumatic brain injury (TBI) have been well documented, little is known about the impact of TBI on creativity. In the current study, our goal is to determine whether convergent problem solving, which contributes to creative thinking, is impaired following TBI. We administered a test of convergent problem solving, the Remote Associate Task (RAT), as well as a battery of neuropsychological tests, to 29 individuals with TBI and 20 healthy comparisons. A mixed-effect regression analysis revealed that individuals with TBI were significantly less likely to produce a correct response, although on average they attempted to respond to the same number of items. Moreover, we found that the TBI (but not the comparison) group's performance on the RAT was significantly and positively associated with verbal learning and memory, providing further evidence supporting the association between declarative memory and creative convergent thinking. In summary, our findings reveal that convergent thinking can be compromised by moderate-to-severe TBI, furthering our understanding of the higher-level cognitive sequelae of TBI.

On improving linear solver performance: a block variant of GMRES

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

Baker, A H; Dennis, J M; Jessup, E R

2004-05-10

The increasing gap between processor performance and memory access time warrants the re-examination of data movement in iterative linear solver algorithms. For this reason, we explore and establish the feasibility of modifying a standard iterative linear solver algorithm in a manner that reduces the movement of data through memory. In particular, we present an alternative to the restarted GMRES algorithm for solving a single right-hand side linear system Ax = b based on solving the block linear system AX = B. Algorithm performance, i.e. time to solution, is improved by using the matrix A in operations on groups of vectors.more » Experimental results demonstrate the importance of implementation choices on data movement as well as the effectiveness of the new method on a variety of problems from different application areas.« less

Memory-dependent derivatives for photothermal semiconducting medium in generalized thermoelasticity with two-temperature

NASA Astrophysics Data System (ADS)

Lotfy, K.; Sarkar, N.

2017-11-01

In this work, a novel generalized model of photothermal theory with two-temperature thermoelasticity theory based on memory-dependent derivative (MDD) theory is performed. A one-dimensional problem for an elastic semiconductor material with isotropic and homogeneous properties has been considered. The problem is solved with a new model (MDD) under the influence of a mechanical force with a photothermal excitation. The Laplace transform technique is used to remove the time-dependent terms in the governing equations. Moreover, the general solutions of some physical fields are obtained. The surface taken into consideration is free of traction and subjected to a time-dependent thermal shock. The numerical Laplace inversion is used to obtain the numerical results of the physical quantities of the problem. Finally, the obtained results are presented and discussed graphically.

Recall Performance for Content-Addressable Memory Using Adiabatic Quantum Optimization

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

Imam, Neena; Humble, Travis S.; McCaskey, Alex

A content-addressable memory (CAM) stores key-value associations such that the key is recalled by providing its associated value. While CAM recall is traditionally performed using recurrent neural network models, we show how to solve this problem using adiabatic quantum optimization. Our approach maps the recurrent neural network to a commercially available quantum processing unit by taking advantage of the common underlying Ising spin model. We then assess the accuracy of the quantum processor to store key-value associations by quantifying recall performance against an ensemble of problem sets. We observe that different learning rules from the neural network community influence recallmore » accuracy but performance appears to be limited by potential noise in the processor. The strong connection established between quantum processors and neural network problems supports the growing intersection of these two ideas.« less

Data compression strategies for ptychographic diffraction imaging

NASA Astrophysics Data System (ADS)

Loetgering, Lars; Rose, Max; Treffer, David; Vartanyants, Ivan A.; Rosenhahn, Axel; Wilhein, Thomas

2017-12-01

Ptychography is a computational imaging method for solving inverse scattering problems. To date, the high amount of redundancy present in ptychographic data sets requires computer memory that is orders of magnitude larger than the retrieved information. Here, we propose and compare data compression strategies that significantly reduce the amount of data required for wavefield inversion. Information metrics are used to measure the amount of data redundancy present in ptychographic data. Experimental results demonstrate the technique to be memory efficient and stable in the presence of systematic errors such as partial coherence and noise.

Working Memory, Reasoning, and Task Switching Training: Transfer Effects, Limitations, and Great Expectations?

PubMed Central

Baniqued, Pauline L.; Ward, Nathan; Geyer, Alexandra; Kramer, Arthur F.

2015-01-01

Although some studies have shown that cognitive training can produce improvements to untrained cognitive domains (far transfer), many others fail to show these effects, especially when it comes to improving fluid intelligence. The current study was designed to overcome several limitations of previous training studies by incorporating training expectancy assessments, an active control group, and “Mind Frontiers,” a video game-based mobile program comprised of six adaptive, cognitively demanding training tasks that have been found to lead to increased scores in fluid intelligence (Gf) tests. We hypothesize that such integrated training may lead to broad improvements in cognitive abilities by targeting aspects of working memory, executive function, reasoning, and problem solving. Ninety participants completed 20 hour-and-a-half long training sessions over four to five weeks, 45 of whom played Mind Frontiers and 45 of whom completed visual search and change detection tasks (active control). After training, the Mind Frontiers group improved in working memory n-back tests, a composite measure of perceptual speed, and a composite measure of reaction time in reasoning tests. No training-related improvements were found in reasoning accuracy or other working memory tests, nor in composite measures of episodic memory, selective attention, divided attention, and multi-tasking. Perceived self-improvement in the tested abilities did not differ between groups. A general expectancy difference in problem-solving was observed between groups, but this perceived benefit did not correlate with training-related improvement. In summary, although these findings provide modest evidence regarding the efficacy of an integrated cognitive training program, more research is needed to determine the utility of Mind Frontiers as a cognitive training tool. PMID:26555341

A longitudinal study of higher-order thinking skills: working memory and fluid reasoning in childhood enhance complex problem solving in adolescence.

PubMed

Greiff, Samuel; Wüstenberg, Sascha; Goetz, Thomas; Vainikainen, Mari-Pauliina; Hautamäki, Jarkko; Bornstein, Marc H

2015-01-01

Scientists have studied the development of the human mind for decades and have accumulated an impressive number of empirical studies that have provided ample support for the notion that early cognitive performance during infancy and childhood is an important predictor of later cognitive performance during adulthood. As children move from childhood into adolescence, their mental development increasingly involves higher-order cognitive skills that are crucial for successful planning, decision-making, and problem solving skills. However, few studies have employed higher-order thinking skills such as complex problem solving (CPS) as developmental outcomes in adolescents. To fill this gap, we tested a longitudinal developmental model in a sample of 2,021 Finnish sixth grade students (M = 12.41 years, SD = 0.52; 1,041 female, 978 male, 2 missing sex). We assessed working memory (WM) and fluid reasoning (FR) at age 12 as predictors of two CPS dimensions: knowledge acquisition and knowledge application. We further assessed students' CPS performance 3 years later as a developmental outcome (N = 1696; M = 15.22 years, SD = 0.43; 867 female, 829 male). Missing data partly occurred due to dropout and technical problems during the first days of testing and varied across indicators and time with a mean of 27.2%. Results revealed that FR was a strong predictor of both CPS dimensions, whereas WM exhibited only a small influence on one of the two CPS dimensions. These results provide strong support for the view that CPS involves FR and, to a lesser extent, WM in childhood and from there evolves into an increasingly complex structure of higher-order cognitive skills in adolescence.

A longitudinal study of higher-order thinking skills: working memory and fluid reasoning in childhood enhance complex problem solving in adolescence

PubMed Central

Greiff, Samuel; Wüstenberg, Sascha; Goetz, Thomas; Vainikainen, Mari-Pauliina; Hautamäki, Jarkko; Bornstein, Marc H.

2015-01-01

Scientists have studied the development of the human mind for decades and have accumulated an impressive number of empirical studies that have provided ample support for the notion that early cognitive performance during infancy and childhood is an important predictor of later cognitive performance during adulthood. As children move from childhood into adolescence, their mental development increasingly involves higher-order cognitive skills that are crucial for successful planning, decision-making, and problem solving skills. However, few studies have employed higher-order thinking skills such as complex problem solving (CPS) as developmental outcomes in adolescents. To fill this gap, we tested a longitudinal developmental model in a sample of 2,021 Finnish sixth grade students (M = 12.41 years, SD = 0.52; 1,041 female, 978 male, 2 missing sex). We assessed working memory (WM) and fluid reasoning (FR) at age 12 as predictors of two CPS dimensions: knowledge acquisition and knowledge application. We further assessed students’ CPS performance 3 years later as a developmental outcome (N = 1696; M = 15.22 years, SD = 0.43; 867 female, 829 male). Missing data partly occurred due to dropout and technical problems during the first days of testing and varied across indicators and time with a mean of 27.2%. Results revealed that FR was a strong predictor of both CPS dimensions, whereas WM exhibited only a small influence on one of the two CPS dimensions. These results provide strong support for the view that CPS involves FR and, to a lesser extent, WM in childhood and from there evolves into an increasingly complex structure of higher-order cognitive skills in adolescence. PMID:26283992

Parallel satellite orbital situational problems solver for space missions design and control

NASA Astrophysics Data System (ADS)

Atanassov, Atanas Marinov

2016-11-01

Solving different scientific problems for space applications demands implementation of observations, measurements or realization of active experiments during time intervals in which specific geometric and physical conditions are fulfilled. The solving of situational problems for determination of these time intervals when the satellite instruments work optimally is a very important part of all activities on every stage of preparation and realization of space missions. The elaboration of universal, flexible and robust approach for situation analysis, which is easily portable toward new satellite missions, is significant for reduction of missions' preparation times and costs. Every situation problem could be based on one or more situation conditions. Simultaneously solving different kinds of situation problems based on different number and types of situational conditions, each one of them satisfied on different segments of satellite orbit requires irregular calculations. Three formal approaches are presented. First one is related to situation problems description that allows achieving flexibility in situation problem assembling and presentation in computer memory. The second formal approach is connected with developing of situation problem solver organized as processor that executes specific code for every particular situational condition. The third formal approach is related to solver parallelization utilizing threads and dynamic scheduling based on "pool of threads" abstraction and ensures a good load balance. The developed situation problems solver is intended for incorporation in the frames of multi-physics multi-satellite space mission's design and simulation tools.

Synaptic tagging, evaluation of memories, and the distal reward problem.

PubMed

Päpper, Marc; Kempter, Richard; Leibold, Christian

2011-01-01

Long-term synaptic plasticity exhibits distinct phases. The synaptic tagging hypothesis suggests an early phase in which synapses are prepared, or "tagged," for protein capture, and a late phase in which those proteins are integrated into the synapses to achieve memory consolidation. The synapse specificity of the tags is consistent with conventional neural network models of associative memory. Memory consolidation through protein synthesis, however, is neuron specific, and its functional role in those models has not been assessed. Here, using a theoretical network model, we test the tagging hypothesis on its potential to prolong memory lifetimes in an online-learning paradigm. We find that protein synthesis, though not synapse specific, prolongs memory lifetimes if it is used to evaluate memory items on a cellular level. In our model we assume that only "important" memory items evoke protein synthesis such that these become more stable than "unimportant" items, which do not evoke protein synthesis. The network model comprises an equilibrium distribution of synaptic states that is very susceptible to the storage of new items: Most synapses are in a state in which they are plastic and can be changed easily, whereas only those synapses that are essential for the retrieval of the important memory items are in the stable late phase. The model can solve the distal reward problem, where the initial exposure of a memory item and its evaluation are temporally separated. Synaptic tagging hence provides a viable mechanism to consolidate and evaluate memories on a synaptic basis.

Balance in machine architecture: Bandwidth on board and offboard, integer/control speed and flops versus memory

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

Fischler, M.

1992-04-01

The issues to be addressed here are those of balance'' in machine architecture. By this, we mean how much emphasis must be placed on various aspects of the system to maximize its usefulness for physics. There are three components that contribute to the utility of a system: How the machine can be used, how big a problem can be attacked, and what the effective capabilities (power) of the hardware are like. The effective power issue is a matter of evaluating the impact of design decisions trading off architectural features such as memory bandwidth and interprocessor communication capabilities. What is studiedmore » is the effect these machine parameters have on how quickly the system can solve desired problems. There is a reasonable method for studying this: One selects a few representative algorithms and computes the impact of changing memory bandwidths, and so forth. The only room for controversy here is in the selection of representative problems. The issue of how big a problem can be attacked boils down to a balance of memory size versus power. Although this is a balance issue it is very different than the effective power situation, because no firm answer can be given at this time. The power to memory ratio is highly problem dependent, and optimizing it requires several pieces of physics input, including: how big a lattice is needed for interesting results; what sort of algorithms are best to use; and how many sweeps are needed to get valid results. We seem to be at the threshold of learning things about these issues, but for now, the memory size issue will necessarily be addressed in terms of best guesses, rules of thumb, and researchers' opinions.« less

Balance in machine architecture: Bandwidth on board and offboard, integer/control speed and flops versus memory

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

Fischler, M.

1992-04-01

The issues to be addressed here are those of ``balance`` in machine architecture. By this, we mean how much emphasis must be placed on various aspects of the system to maximize its usefulness for physics. There are three components that contribute to the utility of a system: How the machine can be used, how big a problem can be attacked, and what the effective capabilities (power) of the hardware are like. The effective power issue is a matter of evaluating the impact of design decisions trading off architectural features such as memory bandwidth and interprocessor communication capabilities. What is studiedmore » is the effect these machine parameters have on how quickly the system can solve desired problems. There is a reasonable method for studying this: One selects a few representative algorithms and computes the impact of changing memory bandwidths, and so forth. The only room for controversy here is in the selection of representative problems. The issue of how big a problem can be attacked boils down to a balance of memory size versus power. Although this is a balance issue it is very different than the effective power situation, because no firm answer can be given at this time. The power to memory ratio is highly problem dependent, and optimizing it requires several pieces of physics input, including: how big a lattice is needed for interesting results; what sort of algorithms are best to use; and how many sweeps are needed to get valid results. We seem to be at the threshold of learning things about these issues, but for now, the memory size issue will necessarily be addressed in terms of best guesses, rules of thumb, and researchers` opinions.« less

Dynamic programming on a shared-memory multiprocessor

NASA Technical Reports Server (NTRS)

Edmonds, Phil; Chu, Eleanor; George, Alan

1993-01-01

Three new algorithms for solving dynamic programming problems on a shared-memory parallel computer are described. All three algorithms attempt to balance work load, while keeping synchronization cost low. In particular, for a multiprocessor having p processors, an analysis of the best algorithm shows that the arithmetic cost is O(n-cubed/6p) and that the synchronization cost is O(absolute value of log sub C n) if p much less than n, where C = (2p-1)/(2p + 1) and n is the size of the problem. The low synchronization cost is important for machines where synchronization is expensive. Analysis and experiments show that the best algorithm is effective in balancing the work load and producing high efficiency.

Solutions and debugging for data consistency in multiprocessors with noncoherent caches

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

Bernstein, D.; Mendelson, B.; Breternitz, M. Jr.

1995-02-01

We analyze two important problems that arise in shared-memory multiprocessor systems. The stale data problem involves ensuring that data items in local memory of individual processors are current, independent of writes done by other processors. False sharing occurs when two processors have copies of the same shared data block but update different portions of the block. The false sharing problem involves guaranteeing that subsequent writes are properly combined. In modern architectures these problems are usually solved in hardware, by exploiting mechanisms for hardware controlled cache consistency. This leads to more expensive and nonscalable designs. Therefore, we are concentrating on softwaremore » methods for ensuring cache consistency that would allow for affordable and scalable multiprocessing systems. Unfortunately, providing software control is nontrivial, both for the compiler writer and for the application programmer. For this reason we are developing a debugging environment that will facilitate the development of compiler-based techniques and will help the programmer to tune his or her application using explicit cache management mechanisms. We extend the notion of a race condition for IBM Shared Memory System POWER/4, taking into consideration its noncoherent caches, and propose techniques for detection of false sharing problems. Identification of the stale data problem is discussed as well, and solutions are suggested.« less

DESCRIPTION OF THE ENIAC CONVERTER CODE

DTIC Science & Technology

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

A case-based assistant for clinical psychiatry expertise.

PubMed

Bichindaritz, I

1994-01-01

Case-based reasoning is an artificial intelligence methodology for the processing of empirical knowledge. Recent case-based reasoning systems also use theoretic knowledge about the domain to constrain the case-based reasoning. The organization of the memory is the key issue in case-based reasoning. The case-based assistant presented here has two structures in memory: cases and concepts. These memory structures permit it to be as skilled in problem-solving tasks, such as diagnosis and treatment planning, as in interpretive tasks, such as clinical research. A prototype applied to clinical work about eating disorders in psychiatry, reasoning from the alimentary questionnaires of these patients, is presented as an example of the system abilities.

Comprehension and computation in Bayesian problem solving

PubMed Central

Johnson, Eric D.; Tubau, Elisabet

2015-01-01

Humans have long been characterized as poor probabilistic reasoners when presented with explicit numerical information. Bayesian word problems provide a well-known example of this, where even highly educated and cognitively skilled individuals fail to adhere to mathematical norms. It is widely agreed that natural frequencies can facilitate Bayesian inferences relative to normalized formats (e.g., probabilities, percentages), both by clarifying logical set-subset relations and by simplifying numerical calculations. Nevertheless, between-study performance on “transparent” Bayesian problems varies widely, and generally remains rather unimpressive. We suggest there has been an over-focus on this representational facilitator (i.e., transparent problem structures) at the expense of the specific logical and numerical processing requirements and the corresponding individual abilities and skills necessary for providing Bayesian-like output given specific verbal and numerical input. We further suggest that understanding this task-individual pair could benefit from considerations from the literature on mathematical cognition, which emphasizes text comprehension and problem solving, along with contributions of online executive working memory, metacognitive regulation, and relevant stored knowledge and skills. We conclude by offering avenues for future research aimed at identifying the stages in problem solving at which correct vs. incorrect reasoners depart, and how individual differences might influence this time point. PMID:26283976

Supervised guiding long-short term memory for image caption generation based on object classes

NASA Astrophysics Data System (ADS)

Wang, Jian; Cao, Zhiguo; Xiao, Yang; Qi, Xinyuan

2018-03-01

The present models of image caption generation have the problems of image visual semantic information attenuation and errors in guidance information. In order to solve these problems, we propose a supervised guiding Long Short Term Memory model based on object classes, named S-gLSTM for short. It uses the object detection results from R-FCN as supervisory information with high confidence, and updates the guidance word set by judging whether the last output matches the supervisory information. S-gLSTM learns how to extract the current interested information from the image visual se-mantic information based on guidance word set. The interested information is fed into the S-gLSTM at each iteration as guidance information, to guide the caption generation. To acquire the text-related visual semantic information, the S-gLSTM fine-tunes the weights of the network through the back-propagation of the guiding loss. Complementing guidance information at each iteration solves the problem of visual semantic information attenuation in the traditional LSTM model. Besides, the supervised guidance information in our model can reduce the impact of the mismatched words on the caption generation. We test our model on MSCOCO2014 dataset, and obtain better performance than the state-of-the- art models.

Preliminary assessment of cognitive impairments in canine idiopathic epilepsy.

PubMed

Winter, Joshua; Packer, Rowena Mary Anne; Volk, Holger Andreas

2018-06-02

In humans, epilepsy can induce or accelerate cognitive impairment (CI). There is emerging evidence of CI in dogs with idiopathic epilepsy (IE) from recent epidemiological studies. The aim of our study was to assess CI in dogs with IE using two tests of cognitive dysfunction designed for use in a clinical setting. Dogs with IE (n=17) were compared against controls (n=18) in their performance in two tasks; a spatial working memory task and a problem-solving task. In addition, owners completed the Canine Cognitive Dysfunction Rating (CCDR) scale for their dog. The groups did not differ statistically with respect to age and breed. Dogs with IE performed significantly worse than controls on the spatial working memory task (P = 0.016), but not on the problem solving task (P=0.683). CCDR scores were significantly higher in the IE group (P=0.016); however, no dogs reach the recommended threshold score for CCD diagnosis. Our preliminary data suggest that dogs with IE exhibit impairments in a spatial working memory task. Further research is required to explore the effect of IE on other cognitive abilities in dogs with a larger sample, characterising the age of onset, nature and progression of any impairments and the impact of anti-epileptic drugs. © British Veterinary Association (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Neuro-Cognitive Intervention for Working Memory: Preliminary Results and Future Directions.

PubMed

Bree, Kathleen D; Beljan, Paul

2016-01-01

Definitions of working memory identify it as a function of the executive function system in which an individual maintains two or more pieces of information in mind and uses that information simultaneously for some purpose. In academics, working memory is necessary for a variety of functions, including attending to the information one's teacher presents and then using that information simultaneously for problem solving. Research indicates difficulties with working memory are observed in children with mathematics learning disorder (MLD) and reading disorders (RD). To improve working memory and other executive function difficulties, and as an alternative to medication treatments for attention and executive function disorders, the Motor Cognition(2)® (MC(2)®)program was developed. Preliminary research on this program indicates statistically significant improvements in working memory, mathematics, and nonsense word decoding for reading. Further research on the MC(2)® program and its impact on working memory, as well as other areas of executive functioning, is warranted.

The Use of Computer Games as an Educational Tool: Identification of Appropriate Game Types and Game Elements.

ERIC Educational Resources Information Center

Amory, Alan; Naicker, Kevin; Vincent, Jacky; Adams, Claudia

1999-01-01

Describes research with college students that investigated commercial game types and game elements to determine what would be suitable for education. Students rated logic, memory, visualization, and problem solving as important game elements that are used to develop a model that links pedagogical issues with game elements. (Author/LRW)

Executive Functions as Moderators of the Worked Example Effect: When Shifting Is More Important than Working Memory Capacity

ERIC Educational Resources Information Center

Schwaighofer, Matthias; Bühner, Markus; Fischer, Frank

2016-01-01

Worked examples have proven to be effective for knowledge acquisition compared with problem solving, particularly when prior knowledge is low (e.g., Kalyuga, 2007). However, in addition to prior knowledge, executive functions and fluid intelligence might be potential moderators of the effectiveness of worked examples. The present study examines…

Spatial Reasoning: Improvement of Imagery and Abilities in Sophomore Organic Chemistry. Perspective to Enhance Student Learning

ERIC Educational Resources Information Center

Hornbuckle, Susan F.; Gobin, Latanya; Thurman, Stephanie N.

2014-01-01

Spatial reasoning has become a demanded skill for students pursuing a science emphasis to compete with the dynamic growth of our professional society. The ability to reason spatially includes explorations in memory recollection and problem solving capabilities as well as critical thinking and reasoning skills. With these advancements, educational…

Can People Recollect Well and Change Their Source Memory Bias of "Aha!" Experiences?

ERIC Educational Resources Information Center

Du, Xiumin; Zhang, Ke; Wang, Jiali; Luo, Junlong; Luo, Jing

2017-01-01

Although many scientific discoveries were frequently reported as kinds of insightful breakthrough that suddenly illuminated in one's mind, we can never exactly know whether these afterward reports were reliable or not. In this study, subjects were asked to solve a list of Remote Associate Test problems and got both subsets of the insightfully and…

Too Much Teaching, Not Enough Learning: What Is the Solution?

ERIC Educational Resources Information Center

Lujan, Heidi L.; DiCarlo, Stephen E.

2006-01-01

The curriculum is packed with so much content that teachers resort to telling students what they know and students simply commit facts to memory. The packed curriculum leaves little time for students to acquire a deep understanding of the subject or to develop life-long skills such as critical thinking, problem solving, and communication. However,…

Using Assistive Technology in Teaching Children with Learning Disabilities in the 21st Century

ERIC Educational Resources Information Center

Adebisi, Rufus Olanrewaju; Liman, Nalado Abubakar; Longpoe, Patricia Kwalzoom

2015-01-01

This paper was written to expose the meaning, benefits, and answer why the use of assistive technology for children with learning disabilities. The paper discussed the various types of assistive technology devices that were designed and used to solve written language, reading, listening, memory and mathematic problems of children with learning…

A comparison of spontaneous problem-solving abilities in three estrildid finch (Taeniopygia guttata, Lonchura striata var. domestica, Stagonopleura guttata) species.

PubMed

Schmelz, Martin; Krüger, Oliver; Call, Josep; Krause, E Tobias

2015-11-01

Cognition has been extensively studied in primates while other, more distantly related taxa have been neglected for a long time. More recently, there has been an increased interest in avian cognition, with the focus mostly on big-brained species like parrots and corvids. However, the majority of bird species has never systematically been studied in diverse cognitive tasks other than memory and learning tasks, so not much can yet be concluded about the relevant factors for the evolution of cognition. Here we examined 3 species of the estrildid finch family in problem-solving tasks. These granivorous, non-tool-using birds are distributed across 3 continents and are not known for high levels of innovation or spontaneous problem solving in the wild. In this study, our aim was to find such abilities in these species, assess what role domestication might play with a comparison of 4 genetically separated zebra finch strains, and to look for between-species differences between zebra finches, Bengalese finches, and diamond firetails. Furthermore, we established a 3-step spontaneous problem-solving procedure with increasing levels of complexity. Results showed that some estrildid finches were generally capable of spontaneously solving problems of variable complexity to obtain food. We found striking differences in these abilities between species, but not between strains within species, and offer a discussion of potential reasons. Our established methodology can now be applied to a larger number of bird species for phylogenetic comparisons on the behavioral level to get a deeper understanding of the evolution of cognitive abilities. (c) 2015 APA, all rights reserved).

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Loci-STREAM Version 0.9

NASA Technical Reports Server (NTRS)

Wright, Jeffrey; Thakur, Siddharth

2006-01-01

Loci-STREAM is an evolving computational fluid dynamics (CFD) software tool for simulating possibly chemically reacting, possibly unsteady flows in diverse settings, including rocket engines, turbomachines, oil refineries, etc. Loci-STREAM implements a pressure- based flow-solving algorithm that utilizes unstructured grids. (The benefit of low memory usage by pressure-based algorithms is well recognized by experts in the field.) The algorithm is robust for flows at all speeds from zero to hypersonic. The flexibility of arbitrary polyhedral grids enables accurate, efficient simulation of flows in complex geometries, including those of plume-impingement problems. The present version - Loci-STREAM version 0.9 - includes an interface with the Portable, Extensible Toolkit for Scientific Computation (PETSc) library for access to enhanced linear-equation-solving programs therein that accelerate convergence toward a solution. The name "Loci" reflects the creation of this software within the Loci computational framework, which was developed at Mississippi State University for the primary purpose of simplifying the writing of complex multidisciplinary application programs to run in distributed-memory computing environments including clusters of personal computers. Loci has been designed to relieve application programmers of the details of programming for distributed-memory computers.

Another look at retroactive and proactive interference: a quantitative analysis of conversion processes.

PubMed

Blank, Hartmut

2005-02-01

Traditionally, the causes of interference phenomena were sought in "real" or "hard" memory processes such as unlearning, response competition, or inhibition, which serve to reduce the accessibility of target items. I propose an alternative approach which does not deny the influence of such processes but highlights a second, equally important, source of interference-the conversion (Tulving, 1983) of accessible memory information into memory performance. Conversion is conceived as a problem-solving-like activity in which the rememberer tries to find solutions to a memory task. Conversion-based interference effects are traced to different conversion processes in the experimental and control conditions of interference designs. I present a simple theoretical model that quantitatively predicts the resulting amount of interference. In two paired-associate learning experiments using two different types of memory tests, these predictions were corroborated. Relations of the present approach to traditional accounts of interference phenomena and implications for eyewitness testimony are discussed.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Sleep does not facilitate insight in older adults.

PubMed

Debarnot, Ursula; Rossi, Marta; Faraguna, Ugo; Schwartz, Sophie; Sebastiani, Laura

2017-04-01

Sleep has been shown to foster the process of insight generation in young adults during problem solving activities. Aging is characterized by substantial changes in sleep architecture altering memory consolidation. Whether sleep might promote the occurrence of insight in older adults as well has not yet been tested experimentally. To address this issue, we tested healthy young and old volunteers on an insight problem solving task, involving both explicit and implicit features, before and after a night of sleep or a comparable wakefulness period. Data showed that insight emerged significantly less frequently after a night of sleep in older adults compared to young. Moreover, there was no difference in the magnitude of insight occurrence following sleep and daytime -consolidation in aged participants. We further found that acquisition of implicit knowledge in the task before sleep potentiated the gain of insight in young participants, but this effect was not observed in aged participants. Overall, present findings demonstrate that a period of sleep does not significantly promote insight in problem solving in older adults. Copyright © 2017 Elsevier Inc. All rights reserved.

Polynomial-time solution of prime factorization and NP-complete problems with digital memcomputing machines

NASA Astrophysics Data System (ADS)

Traversa, Fabio L.; Di Ventra, Massimiliano

2017-02-01

We introduce a class of digital machines, we name Digital Memcomputing Machines, (DMMs) able to solve a wide range of problems including Non-deterministic Polynomial (NP) ones with polynomial resources (in time, space, and energy). An abstract DMM with this power must satisfy a set of compatible mathematical constraints underlying its practical realization. We prove this by making a connection with the dynamical systems theory. This leads us to a set of physical constraints for poly-resource resolvability. Once the mathematical requirements have been assessed, we propose a practical scheme to solve the above class of problems based on the novel concept of self-organizing logic gates and circuits (SOLCs). These are logic gates and circuits able to accept input signals from any terminal, without distinction between conventional input and output terminals. They can solve boolean problems by self-organizing into their solution. They can be fabricated either with circuit elements with memory (such as memristors) and/or standard MOS technology. Using tools of functional analysis, we prove mathematically the following constraints for the poly-resource resolvability: (i) SOLCs possess a global attractor; (ii) their only equilibrium points are the solutions of the problems to solve; (iii) the system converges exponentially fast to the solutions; (iv) the equilibrium convergence rate scales at most polynomially with input size. We finally provide arguments that periodic orbits and strange attractors cannot coexist with equilibria. As examples, we show how to solve the prime factorization and the search version of the NP-complete subset-sum problem. Since DMMs map integers into integers, they are robust against noise and hence scalable. We finally discuss the implications of the DMM realization through SOLCs to the NP = P question related to constraints of poly-resources resolvability.

Knowledge Management: A Skeptic's Guide

NASA Technical Reports Server (NTRS)

Linde, Charlotte

2006-01-01

A viewgraph presentation discussing knowledge management is shown. The topics include: 1) What is Knowledge Management? 2) Why Manage Knowledge? The Presenting Problems; 3) What Gets Called Knowledge Management? 4) Attempts to Rethink Assumptions about Knowledgs; 5) What is Knowledge? 6) Knowledge Management and INstitutional Memory; 7) Knowledge Management and Culture; 8) To solve a social problem, it's easier to call for cultural rather than organizational change; 9) Will the Knowledge Management Effort Succeed? and 10) Backup: Metrics for Valuing Intellectural Capital i.e. Knowledge.

Modeling fault diagnosis as the activation and use of a frame system. [for pilot problem-solving rating

NASA Technical Reports Server (NTRS)

Smith, Philip J.; Giffin, Walter C.; Rockwell, Thomas H.; Thomas, Mark

1986-01-01

Twenty pilots with instrument flight ratings were asked to perform a fault-diagnosis task for which they had relevant domain knowledge. The pilots were asked to think out loud as they requested and interpreted information. Performances were then modeled as the activation and use of a frame system. Cognitive biases, memory distortions and losses, and failures to correctly diagnose the problem were studied in the context of this frame system model.

Accelerating large-scale simulation of seismic wave propagation by multi-GPUs and three-dimensional domain decomposition

NASA Astrophysics Data System (ADS)

Okamoto, Taro; Takenaka, Hiroshi; Nakamura, Takeshi; Aoki, Takayuki

2010-12-01

We adopted the GPU (graphics processing unit) to accelerate the large-scale finite-difference simulation of seismic wave propagation. The simulation can benefit from the high-memory bandwidth of GPU because it is a "memory intensive" problem. In a single-GPU case we achieved a performance of about 56 GFlops, which was about 45-fold faster than that achieved by a single core of the host central processing unit (CPU). We confirmed that the optimized use of fast shared memory and registers were essential for performance. In the multi-GPU case with three-dimensional domain decomposition, the non-contiguous memory alignment in the ghost zones was found to impose quite long time in data transfer between GPU and the host node. This problem was solved by using contiguous memory buffers for ghost zones. We achieved a performance of about 2.2 TFlops by using 120 GPUs and 330 GB of total memory: nearly (or more than) 2200 cores of host CPUs would be required to achieve the same performance. The weak scaling was nearly proportional to the number of GPUs. We therefore conclude that GPU computing for large-scale simulation of seismic wave propagation is a promising approach as a faster simulation is possible with reduced computational resources compared to CPUs.

Phase space simulation of collisionless stellar systems on the massively parallel processor

NASA Technical Reports Server (NTRS)

White, Richard L.

1987-01-01

A numerical technique for solving the collisionless Boltzmann equation describing the time evolution of a self gravitating fluid in phase space was implemented on the Massively Parallel Processor (MPP). The code performs calculations for a two dimensional phase space grid (with one space and one velocity dimension). Some results from calculations are presented. The execution speed of the code is comparable to the speed of a single processor of a Cray-XMP. Advantages and disadvantages of the MPP architecture for this type of problem are discussed. The nearest neighbor connectivity of the MPP array does not pose a significant obstacle. Future MPP-like machines should have much more local memory and easier access to staging memory and disks in order to be effective for this type of problem.

Efficient block preconditioned eigensolvers for linear response time-dependent density functional theory

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

Vecharynski, Eugene; Brabec, Jiri; Shao, Meiyue

We present two efficient iterative algorithms for solving the linear response eigen- value problem arising from the time dependent density functional theory. Although the matrix to be diagonalized is nonsymmetric, it has a special structure that can be exploited to save both memory and floating point operations. In particular, the nonsymmetric eigenvalue problem can be transformed into a product eigenvalue problem that is self-adjoint with respect to a K-inner product. This product eigenvalue problem can be solved efficiently by a modified Davidson algorithm and a modified locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm that make use of the K-innermore » product. The solution of the product eigenvalue problem yields one component of the eigenvector associated with the original eigenvalue problem. However, the other component of the eigenvector can be easily recovered in a postprocessing procedure. Therefore, the algorithms we present here are more efficient than existing algorithms that try to approximate both components of the eigenvectors simultaneously. The efficiency of the new algorithms is demonstrated by numerical examples.« less

Cognitive Remediation Strategies

PubMed Central

WEINSTEIN, CHERYL S.

1994-01-01

Evidence continues to emerge that childhood symptoms of attention-deficit hyperactivity disorder (ADHD) persist into adulthood. These symptoms include motoric hyperactivity, restlessness, attention deficits, poor organizational skills, impulsivity, and memory impairment. Poor academic and work performance, frustration, humiliation, and shame are also components of adult ADHD. Psychotherapists are challenged to understand the meaning of the disorder and its ramifications in all aspects of life. An active multimodal approach, including somatic treatment and psychotherapy, is needed. In addition, cognitive remediation strategies to enhance attention, organization, memory, and problem-solving skills are an important adjunct to treatment. These strategies serve as psychological tools to circumvent deficits. PMID:22700173

Scopolamine impairs memory recall in Octopus vulgaris.

PubMed

Fiorito, G; Agnisola, C; d'Addio, M; Valanzano, A; Calamandrei, G

1998-09-04

The involvement of the central cholinergic system in predatory performance, and on the recall of individual and observational memory in Octopus vulgaris was studied by treating the animals with the muscarinic antagonist scopolamine (2 mg/kg). The absence of the effects of the injection of scopolamine on blood circulation was also checked. Scopolamine did not affect the ability of octopuses to prey on live crabs. However, it interfered significantly with memory recall. In fact, the ability to solve the jar problem was impaired within the first hour after injection (short-term effects) and was only partially recovered after 24 h (long-term). Moreover, both individual and observational learning of a visual discrimination were significantly reduced at the short- and long-term testing. These results support a role of the cholinergic system in the processes of memory recall of O. vulgaris.

Individual differences in children's innovative problem-solving are not predicted by divergent thinking or executive functions

PubMed Central

2016-01-01

Recent studies of children's tool innovation have revealed that there is variation in children's success in middle-childhood. In two individual differences studies, we sought to identify personal characteristics that might predict success on an innovation task. In Study 1, we found that although measures of divergent thinking were related to each other they did not predict innovation success. In Study 2, we measured executive functioning including: inhibition, working memory, attentional flexibility and ill-structured problem-solving. None of these measures predicted innovation, but, innovation was predicted by children's performance on a receptive vocabulary scale that may function as a proxy for general intelligence. We did not find evidence that children's innovation was predicted by specific personal characteristics. PMID:26926280

The traveling salesman problem: a hierarchical model.

PubMed

Graham, S M; Joshi, A; Pizlo, Z

2000-10-01

Our review of prior literature on spatial information processing in perception, attention, and memory indicates that these cognitive functions involve similar mechanisms based on a hierarchical architecture. The present study extends the application of hierarchical models to the area of problem solving. First, we report results of an experiment in which human subjects were tested on a Euclidean traveling salesman problem (TSP) with 6 to 30 cities. The subject's solutions were either optimal or near-optimal in length and were produced in a time that was, on average, a linear function of the number of cities. Next, the performance of the subjects is compared with that of five representative artificial intelligence and operations research algorithms, that produce approximate solutions for Euclidean problems. None of these algorithms was found to be an adequate psychological model. Finally, we present a new algorithm for solving the TSP, which is based on a hierarchical pyramid architecture. The performance of this new algorithm is quite similar to the performance of the subjects.

PIPS-SBB: A Parallel Distributed-Memory Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs

DOE PAGES

Munguia, Lluis-Miquel; Oxberry, Geoffrey; Rajan, Deepak

2016-05-01

Stochastic mixed-integer programs (SMIPs) deal with optimization under uncertainty at many levels of the decision-making process. When solved as extensive formulation mixed- integer programs, problem instances can exceed available memory on a single workstation. In order to overcome this limitation, we present PIPS-SBB: a distributed-memory parallel stochastic MIP solver that takes advantage of parallelism at multiple levels of the optimization process. We also show promising results on the SIPLIB benchmark by combining methods known for accelerating Branch and Bound (B&B) methods with new ideas that leverage the structure of SMIPs. Finally, we expect the performance of PIPS-SBB to improve furthermore » as more functionality is added in the future.« less

Fast decoding techniques for extended single-and-double-error-correcting Reed Solomon codes

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.; Deng, H.; Lin, S.

1984-01-01

A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. For example, some 256K-bit dynamic random access memories are organized as 32K x 8 bit-bytes. Byte-oriented codes such as Reed Solomon (RS) codes provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. Some special high speed decoding techniques for extended single and double error correcting RS codes. These techniques are designed to find the error locations and the error values directly from the syndrome without having to form the error locator polynomial and solve for its roots.

Episodic Memory and Beyond: The Hippocampus and Neocortex in Transformation

PubMed Central

Moscovitch, Morris; Cabeza, Roberto; Winocur, Gordon; Nadel, Lynn

2016-01-01

The last decade has seen dramatic technological and conceptual changes in research on episodic memory and the brain. New technologies, and increased use of more naturalistic observations, have enabled investigators to delve deeply into the structures that mediate episodic memory, particularly the hippocampus, and to track functional and structural interactions among brain regions that support it. Conceptually, episodic memory is increasingly being viewed as subject to lifelong transformations that are reflected in the neural substrates that mediate it. In keeping with this dynamic perspective, research on episodic memory (and the hippocampus) has infiltrated domains, from perception to language and from empathy to problem solving, that were once considered outside its boundaries. Using the component process model as a framework, and focusing on the hippocampus, its subfields, and specialization along its longitudinal axis, along with its interaction with other brain regions, we consider these new developments and their implications for the organization of episodic memory and its contribution to functions in other domains. PMID:26726963

Episodic Memory and Beyond: The Hippocampus and Neocortex in Transformation.

PubMed

Moscovitch, Morris; Cabeza, Roberto; Winocur, Gordon; Nadel, Lynn

2016-01-01

The last decade has seen dramatic technological and conceptual changes in research on episodic memory and the brain. New technologies, and increased use of more naturalistic observations, have enabled investigators to delve deeply into the structures that mediate episodic memory, particularly the hippocampus, and to track functional and structural interactions among brain regions that support it. Conceptually, episodic memory is increasingly being viewed as subject to lifelong transformations that are reflected in the neural substrates that mediate it. In keeping with this dynamic perspective, research on episodic memory (and the hippocampus) has infiltrated domains, from perception to language and from empathy to problem solving, that were once considered outside its boundaries. Using the component process model as a framework, and focusing on the hippocampus, its subfields, and specialization along its longitudinal axis, along with its interaction with other brain regions, we consider these new developments and their implications for the organization of episodic memory and its contribution to functions in other domains.

Cognitive Developmental Phenomena of Pre-School Children in Relation to Socio-Economic Status, Anthropometric Status, and Home Environmental Status

ERIC Educational Resources Information Center

Jena, Ananta Kumar; Paul, Bhabatosh

2016-01-01

The present study was a causality study that investigate the effects of conditional factors; if x, y & z are the independent factors (e.g. socio-economic status, Anthropometric status, and home environmental status) on the dependent factors (e.g. memory, social skill, language acquisition, logical reasoning, and problem solving). The present…

A Test of Transitive Inferences in Free-Flying Honeybees: Unsuccessful Performance Due to Memory Constraints

ERIC Educational Resources Information Center

Benard, Julie; Giurfa, Martin

2004-01-01

We asked whether honeybees, "Apis mellifera," could solve a transitive inference problem. Individual free-flying bees were conditioned with four overlapping premise pairs of five visual patterns in a multiple discrimination task (A+ vs. B-, B+ vs. C-, C+ vs. D-, D+ vs. E-, where + and - indicate sucrose reward or absence of it,…

The Interaction Effects of Working Memory Capacity, Gaming Expertise, and Scaffolding Design on Attention and Comprehension in Digital Game Based Learning

ERIC Educational Resources Information Center

Lee, Yu-Hao

2013-01-01

Educational digital games are often complex problem-solving experiences that can facilitate systematic comprehension. However, empirical studies of digital game based learning (DGBL) have found mixed results regarding DGBL's effect in improving comprehension. While learners generally enjoyed the DGBL learning experience, they often failed to…

Your Family Land: Legacy or Memory? An Introduction to the Family Land Protection Process

Treesearch

USDA Forest Service, Northeastern Area, State and Private Forestry

2008-01-01

If you have this perspective, protecting your land from development is a task you certainly can accomplish. Virtually every situation is workable and every problem can be solved. It does require some planning and decisionmaking; however, so the sooner you start the better. Experience has shown that the number one obstacle to the protection of family land...

Box schemes and their implementation on the iPSC/860

NASA Technical Reports Server (NTRS)

Chattot, J. J.; Merriam, M. L.

1991-01-01

Research on algoriths for efficiently solving fluid flow problems on massively parallel computers is continued in the present paper. Attention is given to the implementation of a box scheme on the iPSC/860, a massively parallel computer with a peak speed of 10 Gflops and a memory of 128 Mwords. A domain decomposition approach to parallelism is used.

Mediated Learning Experience and Concept Maps: A Pedagogical Tool for Achieving Meaningful Learning in Medical Physiology Students

ERIC Educational Resources Information Center

Gonzalez, Hilda Leonor; Palencia, Alberto Pardo; Umana, Luis Alfredo; Galindo, Leonor; Villafrade M., Luz Adriana

2008-01-01

Even though comprehension of human physiology is crucial in the clinical setting, students frequently learn part of this subject using rote memory and then are unable to transfer knowledge to other contexts or to solve clinical problems. This study evaluated the impact of articulating the concept map strategy with the mediated learning experience…

When is working memory important for arithmetic? The impact of strategy and age.

PubMed

Cragg, Lucy; Richardson, Sophie; Hubber, Paula J; Keeble, Sarah; Gilmore, Camilla

2017-01-01

Our ability to perform arithmetic relies heavily on working memory, the manipulation and maintenance of information in mind. Previous research has found that in adults, procedural strategies, particularly counting, rely on working memory to a greater extent than retrieval strategies. During childhood there are changes in the types of strategies employed, as well as an increase in the accuracy and efficiency of strategy execution. As such it seems likely that the role of working memory in arithmetic may also change, however children and adults have never been directly compared. This study used traditional dual-task methodology, with the addition of a control load condition, to investigate the extent to which working memory requirements for different arithmetic strategies change with age between 9-11 years, 12-14 years and young adulthood. We showed that both children and adults employ working memory when solving arithmetic problems, no matter what strategy they choose. This study highlights the importance of considering working memory in understanding the difficulties that some children and adults have with mathematics, as well as the need to include working memory in theoretical models of mathematical cognition.

Power/Performance Trade-offs of Small Batched LU Based Solvers on GPUs

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

Villa, Oreste; Fatica, Massimiliano; Gawande, Nitin A.

In this paper we propose and analyze a set of batched linear solvers for small matrices on Graphic Processing Units (GPUs), evaluating the various alternatives depending on the size of the systems to solve. We discuss three different solutions that operate with different level of parallelization and GPU features. The first, exploiting the CUBLAS library, manages matrices of size up to 32x32 and employs Warp level (one matrix, one Warp) parallelism and shared memory. The second works at Thread-block level parallelism (one matrix, one Thread-block), still exploiting shared memory but managing matrices up to 76x76. The third is Thread levelmore » parallel (one matrix, one thread) and can reach sizes up to 128x128, but it does not exploit shared memory and only relies on the high memory bandwidth of the GPU. The first and second solution only support partial pivoting, the third one easily supports partial and full pivoting, making it attractive to problems that require greater numerical stability. We analyze the trade-offs in terms of performance and power consumption as function of the size of the linear systems that are simultaneously solved. We execute the three implementations on a Tesla M2090 (Fermi) and on a Tesla K20 (Kepler).« less

An efficient photogrammetric stereo matching method for high-resolution images

NASA Astrophysics Data System (ADS)

Li, Yingsong; Zheng, Shunyi; Wang, Xiaonan; Ma, Hao

2016-12-01

Stereo matching of high-resolution images is a great challenge in photogrammetry. The main difficulty is the enormous processing workload that involves substantial computing time and memory consumption. In recent years, the semi-global matching (SGM) method has been a promising approach for solving stereo problems in different data sets. However, the time complexity and memory demand of SGM are proportional to the scale of the images involved, which leads to very high consumption when dealing with large images. To solve it, this paper presents an efficient hierarchical matching strategy based on the SGM algorithm using single instruction multiple data instructions and structured parallelism in the central processing unit. The proposed method can significantly reduce the computational time and memory required for large scale stereo matching. The three-dimensional (3D) surface is reconstructed by triangulating and fusing redundant reconstruction information from multi-view matching results. Finally, three high-resolution aerial date sets are used to evaluate our improvement. Furthermore, precise airborne laser scanner data of one data set is used to measure the accuracy of our reconstruction. Experimental results demonstrate that our method remarkably outperforms in terms of time and memory savings while maintaining the density and precision of the 3D cloud points derived.

A modified form of conjugate gradient method for unconstrained optimization problems

NASA Astrophysics Data System (ADS)

Ghani, Nur Hamizah Abdul; Rivaie, Mohd.; Mamat, Mustafa

2016-06-01

Conjugate gradient (CG) methods have been recognized as an interesting technique to solve optimization problems, due to the numerical efficiency, simplicity and low memory requirements. In this paper, we propose a new CG method based on the study of Rivaie et al. [7] (Comparative study of conjugate gradient coefficient for unconstrained Optimization, Aus. J. Bas. Appl. Sci. 5(2011) 947-951). Then, we show that our method satisfies sufficient descent condition and converges globally with exact line search. Numerical results show that our proposed method is efficient for given standard test problems, compare to other existing CG methods.

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

Sparse distributed memory overview

NASA Technical Reports Server (NTRS)

Raugh, Mike

1990-01-01

The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.

Improving Memory Error Handling Using Linux

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

Carlton, Michael Andrew; Blanchard, Sean P.; Debardeleben, Nathan A.

As supercomputers continue to get faster and more powerful in the future, they will also have more nodes. If nothing is done, then the amount of memory in supercomputer clusters will soon grow large enough that memory failures will be unmanageable to deal with by manually replacing memory DIMMs. "Improving Memory Error Handling Using Linux" is a process oriented method to solve this problem by using the Linux kernel to disable (offline) faulty memory pages containing bad addresses, preventing them from being used again by a process. The process of offlining memory pages simplifies error handling and results in reducingmore » both hardware and manpower costs required to run Los Alamos National Laboratory (LANL) clusters. This process will be necessary for the future of supercomputing to allow the development of exascale computers. It will not be feasible without memory error handling to manually replace the number of DIMMs that will fail daily on a machine consisting of 32-128 petabytes of memory. Testing reveals the process of offlining memory pages works and is relatively simple to use. As more and more testing is conducted, the entire process will be automated within the high-performance computing (HPC) monitoring software, Zenoss, at LANL.« less

I/O efficient algorithms and applications in geographic information systems

NASA Astrophysics Data System (ADS)

Danner, Andrew

Modern remote sensing methods such a laser altimetry (lidar) and Interferometric Synthetic Aperture Radar (IfSAR) produce georeferenced elevation data at unprecedented rates. Many Geographic Information System (GIS) algorithms designed for terrain modelling applications cannot process these massive data sets. The primary problem is that these data sets are too large to fit in the main internal memory of modern computers and must therefore reside on larger, but considerably slower disks. In these applications, the transfer of data between disk and main memory, or I/O, becomes the primary bottleneck. Working in a theoretical model that more accurately represents this two level memory hierarchy, we can develop algorithms that are I/O-efficient and reduce the amount of disk I/O needed to solve a problem. In this thesis we aim to modernize GIS algorithms and develop a number of I/O-efficient algorithms for processing geographic data derived from massive elevation data sets. For each application, we convert a geographic question to an algorithmic question, develop an I/O-efficient algorithm that is theoretically efficient, implement our approach and verify its performance using real-world data. The applications we consider include constructing a gridded digital elevation model (DEM) from an irregularly spaced point cloud, removing topological noise from a DEM, modeling surface water flow over a terrain, extracting river networks and watershed hierarchies from the terrain, and locating polygons containing query points in a planar subdivision. We initially developed solutions to each of these applications individually. However, we also show how to combine individual solutions to form a scalable geo-processing pipeline that seamlessly solves a sequence of sub-problems with little or no manual intervention. We present experimental results that demonstrate orders of magnitude improvement over previously known algorithms.

Cognitive patterns of neuroanatomy concepts: Knowledge organizations that emerge from problem solving versus information gathering

NASA Astrophysics Data System (ADS)

Weidner, Jeanne Margaret O'malley

2000-10-01

This study was motivated by some of the claims that are found in the literature on Problem-Based Learning (PBL). This instructional technique, which uses case studies as its primary instructional tool, has been advanced as an alternative to traditional instruction in order to foster more meaningful, integrative learning of scientific concepts. Several of the advantages attributed to Problem-Based Learning are that it (1) is generally preferred by students because it appears to foster a more nurturing and enjoyable learning experience, (2) fosters greater retention of knowledge and concepts acquired, and (3) results in increased ability to apply this knowledge toward solving new problems. This study examines the differences that result when students learn neuroanatomy concepts under two instructional contexts: problem solving vs. information gathering. The technological resource provided to students to support learning under each of these contexts was the multimedia program BrainStorm: An Interactive Neuroanatomy Atlas (Coppa & Tancred, 1995). The study explores the influence of context with regard to subjects' performance on objective post-tests, organization of knowledge as measured by Pathfinder Networks, differential use of the multimedia software and discourse differences emerging from the transcripts. The findings support previous research in the literature that problem-solving results in less knowledge acquisition in the short term, greater retention of material over time, and a subjects' preference for the method. However, both the degree of retention and preference were influenced by subjects' prior knowledge of the material in the exercises, as there was a significant difference in performance between the two exercises: for the exercise about which subjects appeared to have greater background information, memory decay was less, and subject attitude toward the problem solving instructional format was more favorable, than for the exercise for which subjects had less prior knowledge. Subjects also used the software differently under each format with regard to modules accessed, time spent in modules, and types of information sought. In addition, analyses of the transcripts showed more numerous occurrences of explanations and summarizations in the problem-solving context, compared to the information gathering context. The attempts to show significant differences between the contexts by means of Pathfinder analyses were less than successful.

[A case of pure anarithmetia associated with disability in processing of abstract spatial relationship].

PubMed

Hirayama, Kazumi; Taguchi, Yuzuru; Tsukamoto, Tetsuro

2002-10-01

A 35-year-old right handed man developed pure anarithmetia after an left parieto-occipital subcortical hemorrhage. His intelligence, memory, language, and construction ability were all within normal limits. No hemispatial neglect, agraphia, finger agnosia, or right-left disorientation were noted. He showed no impairments in reading numbers aloud, pointing to written numbers, writing numbers to dictation, decomposition of numbers, estimation of numbers of dots, reading and writing of arithmetic signs, comprehension of arithmetic signs, appreciation of number values, appreciation of dots' number, counting aloud, alignment numbers, comprehension of the commulative law and the distributive law, retrieval of the table value (ku-ku), immediate memory for arithmetic problems, and use of electric calculator. He showed, however, remarkable difficulty even in addition and subtraction between one figure digits, and used counting on his fingers or intuitive strategy to solve the problems even when he could solve them. He could not execute multiplication and division, if the problems required other than the table value (ku-ku). Thus, he seemed to have difficulties in both of elemental arithmetic facts and calculating procedures. In addition, his backward digit span and reading of analogue clocks were deteriorated, and he showed logico-grammatical disorder of Luria. Our case supports the notion that there is a neural system which was shared in part between processing of abstract spatial relationship and calculation.

Prediction of Sea Surface Temperature Using Long Short-Term Memory

NASA Astrophysics Data System (ADS)

Zhang, Qin; Wang, Hui; Dong, Junyu; Zhong, Guoqiang; Sun, Xin

2017-10-01

This letter adopts long short-term memory(LSTM) to predict sea surface temperature(SST), which is the first attempt, to our knowledge, to use recurrent neural network to solve the problem of SST prediction, and to make one week and one month daily prediction. We formulate the SST prediction problem as a time series regression problem. LSTM is a special kind of recurrent neural network, which introduces gate mechanism into vanilla RNN to prevent the vanished or exploding gradient problem. It has strong ability to model the temporal relationship of time series data and can handle the long-term dependency problem well. The proposed network architecture is composed of two kinds of layers: LSTM layer and full-connected dense layer. LSTM layer is utilized to model the time series relationship. Full-connected layer is utilized to map the output of LSTM layer to a final prediction. We explore the optimal setting of this architecture by experiments and report the accuracy of coastal seas of China to confirm the effectiveness of the proposed method. In addition, we also show its online updated characteristics.

Research on fast Fourier transforms algorithm of huge remote sensing image technology with GPU and partitioning technology.

PubMed

Yang, Xue; Li, Xue-You; Li, Jia-Guo; Ma, Jun; Zhang, Li; Yang, Jan; Du, Quan-Ye

2014-02-01

Fast Fourier transforms (FFT) is a basic approach to remote sensing image processing. With the improvement of capacity of remote sensing image capture with the features of hyperspectrum, high spatial resolution and high temporal resolution, how to use FFT technology to efficiently process huge remote sensing image becomes the critical step and research hot spot of current image processing technology. FFT algorithm, one of the basic algorithms of image processing, can be used for stripe noise removal, image compression, image registration, etc. in processing remote sensing image. CUFFT function library is the FFT algorithm library based on CPU and FFTW. FFTW is a FFT algorithm developed based on CPU in PC platform, and is currently the fastest CPU based FFT algorithm function library. However there is a common problem that once the available memory or memory is less than the capacity of image, there will be out of memory or memory overflow when using the above two methods to realize image FFT arithmetic. To address this problem, a CPU and partitioning technology based Huge Remote Fast Fourier Transform (HRFFT) algorithm is proposed in this paper. By improving the FFT algorithm in CUFFT function library, the problem of out of memory and memory overflow is solved. Moreover, this method is proved rational by experiment combined with the CCD image of HJ-1A satellite. When applied to practical image processing, it improves effect of the image processing, speeds up the processing, which saves the time of computation and achieves sound result.

Gestures make memories, but what kind? Patients with impaired procedural memory display disruptions in gesture production and comprehension

PubMed Central

Klooster, Nathaniel B.; Cook, Susan W.; Uc, Ergun Y.; Duff, Melissa C.

2015-01-01

Hand gesture, a ubiquitous feature of human interaction, facilitates communication. Gesture also facilitates new learning, benefiting speakers and listeners alike. Thus, gestures must impact cognition beyond simply supporting the expression of already-formed ideas. However, the cognitive and neural mechanisms supporting the effects of gesture on learning and memory are largely unknown. We hypothesized that gesture's ability to drive new learning is supported by procedural memory and that procedural memory deficits will disrupt gesture production and comprehension. We tested this proposal in patients with intact declarative memory, but impaired procedural memory as a consequence of Parkinson's disease (PD), and healthy comparison participants with intact declarative and procedural memory. In separate experiments, we manipulated the gestures participants saw and produced in a Tower of Hanoi (TOH) paradigm. In the first experiment, participants solved the task either on a physical board, requiring high arching movements to manipulate the discs from peg to peg, or on a computer, requiring only flat, sideways movements of the mouse. When explaining the task, healthy participants with intact procedural memory displayed evidence of their previous experience in their gestures, producing higher, more arching hand gestures after solving on a physical board, and smaller, flatter gestures after solving on a computer. In the second experiment, healthy participants who saw high arching hand gestures in an explanation prior to solving the task subsequently moved the mouse with significantly higher curvature than those who saw smaller, flatter gestures prior to solving the task. These patterns were absent in both gesture production and comprehension experiments in patients with procedural memory impairment. These findings suggest that the procedural memory system supports the ability of gesture to drive new learning. PMID:25628556

Multigrid contact detection method

NASA Astrophysics Data System (ADS)

He, Kejing; Dong, Shoubin; Zhou, Zhaoyao

2007-03-01

Contact detection is a general problem of many physical simulations. This work presents a O(N) multigrid method for general contact detection problems (MGCD). The multigrid idea is integrated with contact detection problems. Both the time complexity and memory consumption of the MGCD are O(N) . Unlike other methods, whose efficiencies are influenced strongly by the object size distribution, the performance of MGCD is insensitive to the object size distribution. We compare the MGCD with the no binary search (NBS) method and the multilevel boxing method in three dimensions for both time complexity and memory consumption. For objects with similar size, the MGCD is as good as the NBS method, both of which outperform the multilevel boxing method regarding memory consumption. For objects with diverse size, the MGCD outperform both the NBS method and the multilevel boxing method. We use the MGCD to solve the contact detection problem for a granular simulation system based on the discrete element method. From this granular simulation, we get the density property of monosize packing and binary packing with size ratio equal to 10. The packing density for monosize particles is 0.636. For binary packing with size ratio equal to 10, when the number of small particles is 300 times as the number of big particles, the maximal packing density 0.824 is achieved.

Effectiveness and Adoption of a Drawing-to-Learn Study Tool for Recall and Problem Solving: Minute Sketches with Folded Lists

ERIC Educational Resources Information Center

Heideman, Paul D.; Flores, K. Adryan; Sevier, Lu M.; Trouton, Kelsey E.

2017-01-01

Drawing by learners can be an effective way to develop memory and generate visual models for higher-order skills in biology, but students are often reluctant to adopt drawing as a study method. We designed a nonclassroom intervention that instructed introductory biology college students in a drawing method, minute sketches in folded lists (MSFL),…

Predicting the Future as Bayesian Inference: People Combine Prior Knowledge with Observations when Estimating Duration and Extent

ERIC Educational Resources Information Center

Griffiths, Thomas L.; Tenenbaum, Joshua B.

2011-01-01

Predicting the future is a basic problem that people have to solve every day and a component of planning, decision making, memory, and causal reasoning. In this article, we present 5 experiments testing a Bayesian model of predicting the duration or extent of phenomena from their current state. This Bayesian model indicates how people should…

Integrated Cognitive Architectures For Robust Decision Making

DTIC Science & Technology

2010-09-20

groups differed significantly from the other three [W(5) > 5, p > 0.13, uncorrected]. Performance by Condition It is useful to look at the average...the research that pursues integrated theories of human cognition, two approaches have become particularly influencial : ACT-R and Leabra. ACT-R...a wide range of tasks involving attention, learning, memory, problem solving, decision making, and language processing. Under the pressure of

Operator Performance Measures for Assessing Voice Communication Effectiveness

DTIC Science & Technology

1989-07-01

performance and work- load assessment techniques have been based.I Broadbent (1958) described a limited capacity filter model of human information...INFORMATION PROCESSING 20 3.1.1. Auditory Attention 20 3.1.2. Auditory Memory 24 3.2. MODELS OF INFORMATION PROCESSING 24 3.2.1. Capacity Theories 25...Learning 0 Attention * Language Specialization • Decision Making• Problem Solving Auditory Information Processing Models of Processing Ooemtor

Cultural Development through the Interaction between Education, the Community, and Society at Large. Contributions of Education to Cultural Development.

ERIC Educational Resources Information Center

Engstrom, K.

Museums play an important role in the transmission of culture and traditions and provide a collective memory of a community. A number of museum related institutions, known as the Science Centra, have arisen to offer self-directed learning activities in problem solving and understanding the processes related to everyday life. In a modern society,…

Architecture of fluid intelligence and working memory revealed by lesion mapping.

PubMed

Barbey, Aron K; Colom, Roberto; Paul, Erick J; Grafman, Jordan

2014-03-01

Although cognitive neuroscience has made valuable progress in understanding the role of the prefrontal cortex in human intelligence, the functional networks that support adaptive behavior and novel problem solving remain to be well characterized. Here, we studied 158 human brain lesion patients to investigate the cognitive and neural foundations of key competencies for fluid intelligence and working memory. We administered a battery of neuropsychological tests, including the Wechsler Adult Intelligence Scale (WAIS) and the N-Back task. Latent variable modeling was applied to obtain error-free scores of fluid intelligence and working memory, followed by voxel-based lesion-symptom mapping to elucidate their neural substrates. The observed latent variable modeling and lesion results support an integrative framework for understanding the architecture of fluid intelligence and working memory and make specific recommendations for the interpretation and application of the WAIS and N-Back task to the study of fluid intelligence in health and disease.

Cognitive skill learning and schizophrenia: implications for cognitive remediation.

PubMed

Michel, L; Danion, J M; Grangé, D; Sandner, G

1998-10-01

The ability to acquire a motor and cognitive skill was investigated in 26 patients with schizophrenia and 26 normal participants using repeated testing on the Tower of Toronto puzzle. Seven patients with defective performance were retested using additional trials and immediate feedback designed to facilitate problem solving. A component analysis of performance was used based on J. R. Anderson's (1987) model of cognitive skill learning. Patients exhibited a performance deficit on both motor and cognitive skills. However, their acquisition rate was similar to that of normal participants on most parameters, indicating that skill learning suffered little or no impairment. Performance deficit was accounted for by poor problem-solving ability, explicit memory, and general intellectual capacities. It was remediable in some, but not all, patients. Remediation failure was also related to severe defects of cognitive functions.

Enhancing self-efficacy improves episodic future thinking and social-decision making in combat veterans with posttraumatic stress disorder.

PubMed

Brown, Adam D; Kouri, Nicole A; Rahman, Nadia; Joscelyne, Amy; Bryant, Richard A; Marmar, Charles R

2016-08-30

Posttraumatic Stress Disorder (PTSD) is associated with maladaptive changes in self-identity, including impoverished perceived self-efficacy. This study examined if enhancing perceptions of self-efficacy in combat veterans with and without symptoms of PTSD promotes cognitive strategies associated with positive mental health outcomes. Prior to completing a future thinking and social problem-solving task, sixty-two OEF/OIF veterans with and without symptoms of PTSD were randomized to either a high self-efficacy (HSE) induction in which they were asked to recall three autobiographical memories demonstrating self-efficacy or a control condition in which they recalled any three autobiographical events. An interaction between HSE and PTSD revealed that individuals with symptoms of PTSD in the HSE condition generated future events with more self-efficacious statements than those with PTSD in the control condition, whereas those without PTSD did not differ in self-efficacy content across the conditions. In addition, individuals in the HSE condition exhibited better social problem solving than those in the control condition. Increasing perceptions of self-efficacy may promote future thinking and problem solving in ways that are relevant to overcoming trauma and adversity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Methodology for sensitivity analysis, approximate analysis, and design optimization in CFD for multidisciplinary applications

NASA Technical Reports Server (NTRS)

Taylor, Arthur C., III; Hou, Gene W.

1993-01-01

In this study involving advanced fluid flow codes, an incremental iterative formulation (also known as the delta or correction form) together with the well-known spatially-split approximate factorization algorithm, is presented for solving the very large sparse systems of linear equations which are associated with aerodynamic sensitivity analysis. For smaller 2D problems, a direct method can be applied to solve these linear equations in either the standard or the incremental form, in which case the two are equivalent. Iterative methods are needed for larger 2D and future 3D applications, however, because direct methods require much more computer memory than is currently available. Iterative methods for solving these equations in the standard form are generally unsatisfactory due to an ill-conditioning of the coefficient matrix; this problem can be overcome when these equations are cast in the incremental form. These and other benefits are discussed. The methodology is successfully implemented and tested in 2D using an upwind, cell-centered, finite volume formulation applied to the thin-layer Navier-Stokes equations. Results are presented for two sample airfoil problems: (1) subsonic low Reynolds number laminar flow; and (2) transonic high Reynolds number turbulent flow.

Effect of quantum learning model in improving creativity and memory

NASA Astrophysics Data System (ADS)

Sujatmika, S.; Hasanah, D.; Hakim, L. L.

2018-04-01

Quantum learning is a combination of many interactions that exist during learning. This model can be applied by current interesting topic, contextual, repetitive, and give opportunities to students to demonstrate their abilities. The basis of the quantum learning model are left brain theory, right brain theory, triune, visual, auditorial, kinesthetic, game, symbol, holistic, and experiential learning theory. Creativity plays an important role to be success in the working world. Creativity shows alternatives way to problem-solving or creates something. Good memory plays a role in the success of learning. Through quantum learning, students will use all of their abilities, interested in learning and create their own ways of memorizing concepts of the material being studied. From this idea, researchers assume that quantum learning models can improve creativity and memory of the students.

Apraxia, mechanical problem solving and semantic knowledge: contributions to object usage in corticobasal degeneration.

PubMed

Spatt, Josef; Bak, Thomas; Bozeat, Sasha; Patterson, Karalyn; Hodges, John R

2002-05-01

To investigate the nature of the apraxia in corticobasal degeneration (CBD) five patients with CBD and five matched controls were compared on tests of: i) meaningless and symbolic gesture production, ii) a battery of semantic tasks based on 20 everyday items (involving naming and picture-picture matching according to semantic attributes, matching gestures-to-objects, object usage from name and with the real object) and iii) a novel tool test of mechanical problem solving. All five patients showed severe impairment in the production of meaningless and symbolic gestures from command, and by imitation, and were also impaired when using real objects. Deficits were not, however, restricted to action production: four were unable to match gestures to objects and all five showed impairment in the selection and usage of novel tools in the mechanical problem solving task. Surprising was the finding of an additional semantic knowledge breakdown in three cases, two of whom were markedly anomic. The apraxia in CBD is, therefore, multifactorial. There is profound breakdown in the organisation and co-ordination of motor programming. In addition, patients show central deficits in action knowledge and mechanical problem solving, which has been linked to parietal lobe pathology. General semantic memory may also be affected in CBD in some cases and this may then contribute to impaired object usage. This combination of more than one deficit relevant for object use may explain why CBD patients are far more disabled by their dyspraxia in everyday life than any other patient group.

Protein sequence comparison based on K-string dictionary.

PubMed

Yu, Chenglong; He, Rong L; Yau, Stephen S-T

2013-10-25

The current K-string-based protein sequence comparisons require large amounts of computer memory because the dimension of the protein vector representation grows exponentially with K. In this paper, we propose a novel concept, the "K-string dictionary", to solve this high-dimensional problem. It allows us to use a much lower dimensional K-string-based frequency or probability vector to represent a protein, and thus significantly reduce the computer memory requirements for their implementation. Furthermore, based on this new concept, we use Singular Value Decomposition to analyze real protein datasets, and the improved protein vector representation allows us to obtain accurate gene trees. © 2013.

First-Grade Predictors of Mathematical Learning Disability: A Latent Class Trajectory Analysis

PubMed Central

Geary, David C.; Bailey, Drew H.; Littlefield, Andrew; Wood, Phillip; Hoard, Mary K.; Nugent, Lara

2009-01-01

Kindergarten to 3rd grade mathematics achievement scores from a prospective study of mathematical development were subjected to latent growth trajectory analyses (n = 306). The four corresponding classes included children with mathematical learning disability (MLD, 6% of sample), and low (LA, 50%), typically (TA, 39%) and high (HA, 5%) achieving children. The groups were administered a battery of intelligence (IQ), working memory, and mathematical-cognition measures in 1st grade. The children with MLD had general deficits in working memory and IQ, and potentially more specific deficits on measures of number sense. The LA children did not have working memory or IQ deficits, but showed moderate deficits on these number sense measures and for addition fact retrieval. The distinguishing features of the HA children were a strong visuospatial working memory, a strong number sense, and frequent use of memory-based processes to solve addition problems. Implications for the early identification of children at risk for poor mathematics achievement are discussed. PMID:20046817

Determining the Mechanical Properties of Lattice Block Structures

NASA Technical Reports Server (NTRS)

Wilmoth, Nathan

2013-01-01

Lattice block structures and shape memory alloys possess several traits ideal for solving intriguing new engineering problems in industries such as aerospace, military, and transportation. Recent testing at the NASA Glenn Research Center has investigated the material properties of lattice block structures cast from a conventional aerospace titanium alloy as well as lattice block structures cast from nickel-titanium shape memory alloy. The lattice block structures for both materials were sectioned into smaller subelements for tension and compression testing. The results from the cast conventional titanium material showed that the expected mechanical properties were maintained. The shape memory alloy material was found to be extremely brittle from the casting process and only compression testing was completed. Future shape memory alloy lattice block structures will utilize an adjusted material composition that will provide a better quality casting. The testing effort resulted in baseline mechanical property data from the conventional titanium material for comparison to shape memory alloy materials once suitable castings are available.

Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3

PubMed Central

Savin, Cristina; Dayan, Peter; Lengyel, Máté

2014-01-01

A venerable history of classical work on autoassociative memory has significantly shaped our understanding of several features of the hippocampus, and most prominently of its CA3 area, in relation to memory storage and retrieval. However, existing theories of hippocampal memory processing ignore a key biological constraint affecting memory storage in neural circuits: the bounded dynamical range of synapses. Recent treatments based on the notion of metaplasticity provide a powerful model for individual bounded synapses; however, their implications for the ability of the hippocampus to retrieve memories well and the dynamics of neurons associated with that retrieval are both unknown. Here, we develop a theoretical framework for memory storage and recall with bounded synapses. We formulate the recall of a previously stored pattern from a noisy recall cue and limited-capacity (and therefore lossy) synapses as a probabilistic inference problem, and derive neural dynamics that implement approximate inference algorithms to solve this problem efficiently. In particular, for binary synapses with metaplastic states, we demonstrate for the first time that memories can be efficiently read out with biologically plausible network dynamics that are completely constrained by the synaptic plasticity rule, and the statistics of the stored patterns and of the recall cue. Our theory organises into a coherent framework a wide range of existing data about the regulation of excitability, feedback inhibition, and network oscillations in area CA3, and makes novel and directly testable predictions that can guide future experiments. PMID:24586137

Interface methods for using intranet portal organizational memory information system.

PubMed

Ji, Yong Gu; Salvendy, Gavriel

2004-12-01

In this paper, an intranet portal is considered as an information infrastructure (organizational memory information system, OMIS) supporting organizational learning. The properties and the hierarchical structure of information and knowledge in an intranet portal OMIS was identified as a problem for navigation tools of an intranet portal interface. The problem relates to navigation and retrieval functions of intranet portal OMIS and is expected to adversely affect user performance, satisfaction, and usefulness. To solve the problem, a conceptual model for navigation tools of an intranet portal interface was proposed and an experiment using a crossover design was conducted with 10 participants. In the experiment, a separate access method (tabbed tree tool) was compared to an unified access method (single tree tool). The results indicate that each information/knowledge repository for which a user has a different structural knowledge should be handled separately with a separate access to increase user satisfaction and the usefulness of the OMIS and to improve user performance in navigation.

A comparative study of history-based versus vectorized Monte Carlo methods in the GPU/CUDA environment for a simple neutron eigenvalue problem

NASA Astrophysics Data System (ADS)

Liu, Tianyu; Du, Xining; Ji, Wei; Xu, X. George; Brown, Forrest B.

2014-06-01

For nuclear reactor analysis such as the neutron eigenvalue calculations, the time consuming Monte Carlo (MC) simulations can be accelerated by using graphics processing units (GPUs). However, traditional MC methods are often history-based, and their performance on GPUs is affected significantly by the thread divergence problem. In this paper we describe the development of a newly designed event-based vectorized MC algorithm for solving the neutron eigenvalue problem. The code was implemented using NVIDIA's Compute Unified Device Architecture (CUDA), and tested on a NVIDIA Tesla M2090 GPU card. We found that although the vectorized MC algorithm greatly reduces the occurrence of thread divergence thus enhancing the warp execution efficiency, the overall simulation speed is roughly ten times slower than the history-based MC code on GPUs. Profiling results suggest that the slow speed is probably due to the memory access latency caused by the large amount of global memory transactions. Possible solutions to improve the code efficiency are discussed.

Matrix decomposition graphics processing unit solver for Poisson image editing

NASA Astrophysics Data System (ADS)

Lei, Zhao; Wei, Li

2012-10-01

In recent years, gradient-domain methods have been widely discussed in the image processing field, including seamless cloning and image stitching. These algorithms are commonly carried out by solving a large sparse linear system: the Poisson equation. However, solving the Poisson equation is a computational and memory intensive task which makes it not suitable for real-time image editing. A new matrix decomposition graphics processing unit (GPU) solver (MDGS) is proposed to settle the problem. A matrix decomposition method is used to distribute the work among GPU threads, so that MDGS will take full advantage of the computing power of current GPUs. Additionally, MDGS is a hybrid solver (combines both the direct and iterative techniques) and has two-level architecture. These enable MDGS to generate identical solutions with those of the common Poisson methods and achieve high convergence rate in most cases. This approach is advantageous in terms of parallelizability, enabling real-time image processing, low memory-taken and extensive applications.

A fast Fourier transform on multipoles (FFTM) algorithm for solving Helmholtz equation in acoustics analysis.

PubMed

Ong, Eng Teo; Lee, Heow Pueh; Lim, Kian Meng

2004-09-01

This article presents a fast algorithm for the efficient solution of the Helmholtz equation. The method is based on the translation theory of the multipole expansions. Here, the speedup comes from the convolution nature of the translation operators, which can be evaluated rapidly using fast Fourier transform algorithms. Also, the computations of the translation operators are accelerated by using the recursive formulas developed recently by Gumerov and Duraiswami [SIAM J. Sci. Comput. 25, 1344-1381(2003)]. It is demonstrated that the algorithm can produce good accuracy with a relatively low order of expansion. Efficiency analyses of the algorithm reveal that it has computational complexities of O(Na), where a ranges from 1.05 to 1.24. However, this method requires substantially more memory to store the translation operators as compared to the fast multipole method. Hence, despite its simplicity in implementation, this memory requirement issue may limit the application of this algorithm to solving very large-scale problems.

Evaluation of the eigenvalue method in the solution of transient heat conduction problems

NASA Astrophysics Data System (ADS)

Landry, D. W.

1985-01-01

The eigenvalue method is evaluated to determine the advantages and disadvantages of the method as compared to fully explicit, fully implicit, and Crank-Nicolson methods. Time comparisons and accuracy comparisons are made in an effort to rank the eigenvalue method in relation to the comparison schemes. The eigenvalue method is used to solve the parabolic heat equation in multidimensions with transient temperatures. Extensions into three dimensions are made to determine the method's feasibility in handling large geometry problems requiring great numbers of internal mesh points. The eigenvalue method proves to be slightly better in accuracy than the comparison routines because of an exact treatment, as opposed to a numerical approximation, of the time derivative in the heat equation. It has the potential of being a very powerful routine in solving long transient type problems. The method is not well suited to finely meshed grid arrays or large regions because of the time and memory requirements necessary for calculating large sets of eigenvalues and eigenvectors.

Dynamic Harmony Search with Polynomial Mutation Algorithm for Valve-Point Economic Load Dispatch

PubMed Central

Karthikeyan, M.; Sree Ranga Raja, T.

2015-01-01

Economic load dispatch (ELD) problem is an important issue in the operation and control of modern control system. The ELD problem is complex and nonlinear with equality and inequality constraints which makes it hard to be efficiently solved. This paper presents a new modification of harmony search (HS) algorithm named as dynamic harmony search with polynomial mutation (DHSPM) algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR) and pitch adjusting rate (PAR) are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods. PMID:26491710

Dynamic Harmony Search with Polynomial Mutation Algorithm for Valve-Point Economic Load Dispatch.

PubMed

Karthikeyan, M; Raja, T Sree Ranga

2015-01-01

Economic load dispatch (ELD) problem is an important issue in the operation and control of modern control system. The ELD problem is complex and nonlinear with equality and inequality constraints which makes it hard to be efficiently solved. This paper presents a new modification of harmony search (HS) algorithm named as dynamic harmony search with polynomial mutation (DHSPM) algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR) and pitch adjusting rate (PAR) are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods.

EUROPA2: Plan Database Services for Planning and Scheduling Applications

NASA Technical Reports Server (NTRS)

Bedrax-Weiss, Tania; Frank, Jeremy; Jonsson, Ari; McGann, Conor

2004-01-01

NASA missions require solving a wide variety of planning and scheduling problems with temporal constraints; simple resources such as robotic arms, communications antennae and cameras; complex replenishable resources such as memory, power and fuel; and complex constraints on geometry, heat and lighting angles. Planners and schedulers that solve these problems are used in ground tools as well as onboard systems. The diversity of planning problems and applications of planners and schedulers precludes a one-size fits all solution. However, many of the underlying technologies are common across planning domains and applications. We describe CAPR, a formalism for planning that is general enough to cover a wide variety of planning and scheduling domains of interest to NASA. We then describe EUROPA(sub 2), a software framework implementing CAPR. EUROPA(sub 2) provides efficient, customizable Plan Database Services that enable the integration of CAPR into a wide variety of applications. We describe the design of EUROPA(sub 2) from the perspective of both modeling, customization and application integration to different classes of NASA missions.

Flood inundation extent mapping based on block compressed tracing

NASA Astrophysics Data System (ADS)

Shen, Dingtao; Rui, Yikang; Wang, Jiechen; Zhang, Yu; Cheng, Liang

2015-07-01

Flood inundation extent, depth, and duration are important factors affecting flood hazard evaluation. At present, flood inundation analysis is based mainly on a seeded region-growing algorithm, which is an inefficient process because it requires excessive recursive computations and it is incapable of processing massive datasets. To address this problem, we propose a block compressed tracing algorithm for mapping the flood inundation extent, which reads the DEM data in blocks before transferring them to raster compression storage. This allows a smaller computer memory to process a larger amount of data, which solves the problem of the regular seeded region-growing algorithm. In addition, the use of a raster boundary tracing technique allows the algorithm to avoid the time-consuming computations required by the seeded region-growing. Finally, we conduct a comparative evaluation in the Chin-sha River basin, results show that the proposed method solves the problem of flood inundation extent mapping based on massive DEM datasets with higher computational efficiency than the original method, which makes it suitable for practical applications.

When is working memory important for arithmetic? The impact of strategy and age

PubMed Central

Richardson, Sophie; Hubber, Paula J.; Keeble, Sarah; Gilmore, Camilla

2017-01-01

Our ability to perform arithmetic relies heavily on working memory, the manipulation and maintenance of information in mind. Previous research has found that in adults, procedural strategies, particularly counting, rely on working memory to a greater extent than retrieval strategies. During childhood there are changes in the types of strategies employed, as well as an increase in the accuracy and efficiency of strategy execution. As such it seems likely that the role of working memory in arithmetic may also change, however children and adults have never been directly compared. This study used traditional dual-task methodology, with the addition of a control load condition, to investigate the extent to which working memory requirements for different arithmetic strategies change with age between 9–11 years, 12–14 years and young adulthood. We showed that both children and adults employ working memory when solving arithmetic problems, no matter what strategy they choose. This study highlights the importance of considering working memory in understanding the difficulties that some children and adults have with mathematics, as well as the need to include working memory in theoretical models of mathematical cognition. PMID:29228008

Hybrid chickadees are deficient in learning and memory.

PubMed

McQuillan, Michael A; Roth, Timothy C; Huynh, Alex V; Rice, Amber M

2018-05-01

Identifying the phenotypes underlying postzygotic reproductive isolation is crucial for fully understanding the evolution and maintenance of species. One potential postzygotic isolating barrier that has rarely been examined is learning and memory ability in hybrids. Learning and memory are important fitness-related traits, especially in scatter-hoarding species, where accurate retrieval of hoarded food is vital for winter survival. Here, we test the hypothesis that learning and memory ability can act as a postzygotic isolating barrier by comparing these traits among two scatter-hoarding songbird species, black-capped (Poecile atricapillus) and Carolina chickadees (Poecile carolinensis), and their naturally occurring hybrids. In an outdoor aviary setting, we find that hybrid chickadees perform significantly worse on an associative learning spatial task and are worse at solving a novel problem compared to both parental species. Deficiencies in learning and memory abilities could therefore contribute to postzygotic reproductive isolation between chickadee species. Given the importance of learning and memory for fitness, our results suggest that these traits may play an important, but as yet overlooked, role in postzygotic reproductive isolation. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.

Direct Observation of a Carbon Filament in Water-Resistant Organic Memory.

PubMed

Lee, Byung-Hyun; Bae, Hagyoul; Seong, Hyejeong; Lee, Dong-Il; Park, Hongkeun; Choi, Young Joo; Im, Sung-Gap; Kim, Sang Ouk; Choi, Yang-Kyu

2015-07-28

The memory for the Internet of Things (IoT) requires versatile characteristics such as flexibility, wearability, and stability in outdoor environments. Resistive random access memory (RRAM) to harness a simple structure and organic material with good flexibility can be an attractive candidate for IoT memory. However, its solution-oriented process and unclear switching mechanism are critical problems. Here we demonstrate iCVD polymer-intercalated RRAM (i-RRAM). i-RRAM exhibits robust flexibility and versatile wearability on any substrate. Stable operation of i-RRAM, even in water, is demonstrated, which is the first experimental presentation of water-resistant organic memory without any waterproof protection package. Moreover, the direct observation of a carbon filament is also reported for the first time using transmission electron microscopy, which puts an end to the controversy surrounding the switching mechanism. Therefore, reproducibility is feasible through comprehensive modeling. Furthermore, a carbon filament is superior to a metal filament in terms of the design window and selection of the electrode material. These results suggest an alternative to solve the critical issues of organic RRAM and an optimized memory type suitable for the IoT era.

Some Issues in Programming Multi-Mini-Processors

DTIC Science & Technology

1975-01-01

Hardware ^nd software are to be combined optimally to perform that specialized task. This in essence is the stategy followed by the BBN group in...large memory is directly addressable. MIXED SOLUTIONS The most promising approach appears to involve mixing several of the previous solutions...mini- or micro-computers. Possibly the problem will be solved by avoiding it. Some new minis are appearing on the market now with large physical

The Method of Loci as a Mnemonic Device to Facilitate Learning in Endocrinology Leads to Improvement in Student Performance as Measured by Assessments

ERIC Educational Resources Information Center

Qureshi, Ayisha; Rizvi, Farwa; Syed, Anjum; Shahid, Aqueel; Manzoor, Hana

2014-01-01

Cognitive psychology has demonstrated that the way knowledge is structured in memory determines the ability to retain, recall, and use it to solve problems. The method of loci (MOL) is a mnemonic device that relies on spatial relationships between "loci" (e.g., locations on a familiar route or rooms in a familiar building) to arrange and…

Beyond Risk and Protective Factors: An Adaptation-Based Approach to Resilience.

PubMed

Ellis, Bruce J; Bianchi, JeanMarie; Griskevicius, Vladas; Frankenhuis, Willem E

2017-07-01

How does repeated or chronic childhood adversity shape social and cognitive abilities? According to the prevailing deficit model, children from high-stress backgrounds are at risk for impairments in learning and behavior, and the intervention goal is to prevent, reduce, or repair the damage. Missing from this deficit approach is an attempt to leverage the unique strengths and abilities that develop in response to high-stress environments. Evolutionary-developmental models emphasize the coherent, functional changes that occur in response to stress over the life course. Research in birds, rodents, and humans suggests that developmental exposures to stress can improve forms of attention, perception, learning, memory, and problem solving that are ecologically relevant in harsh-unpredictable environments (as per the specialization hypothesis). Many of these skills and abilities, moreover, are primarily manifest in currently stressful contexts where they would provide the greatest fitness-relevant advantages (as per the sensitization hypothesis). This perspective supports an alternative adaptation-based approach to resilience that converges on a central question: "What are the attention, learning, memory, problem-solving, and decision-making strategies that are enhanced through exposures to childhood adversity?" At an applied level, this approach focuses on how we can work with, rather than against, these strengths to promote success in education, employment, and civic life.

Hip Hop Dance Experience Linked to Sociocognitive Ability.

PubMed

Bonny, Justin W; Lindberg, Jenna C; Pacampara, Marc C

2017-01-01

Expertise within gaming (e.g., chess, video games) and kinesthetic (e.g., sports, classical dance) activities has been found to be linked with specific cognitive skills. Some of these skills, working memory, mental rotation, problem solving, are linked to higher performance in science, technology, math, and engineering (STEM) disciplines. In the present study, we examined whether experience in a different activity, hip hop dance, is also linked to cognitive abilities connected with STEM skills as well as social cognition ability. Dancers who varied in hip hop and other dance style experience were presented with a set of computerized tasks that assessed working memory capacity, mental rotation speed, problem solving efficiency, and theory of mind. We found that, when controlling for demographic factors and other dance style experience, those with greater hip hop dance experience were faster at mentally rotating images of hands at greater angle disparities and there was a trend for greater accuracy at identifying positive emotions displayed by cropped images of human faces. We suggest that hip hop dance, similar to other more technical activities such as video gameplay, tap some specific cognitive abilities that underlie STEM skills. Furthermore, we suggest that hip hop dance experience can be used to reach populations who may not otherwise be interested in other kinesthetic or gaming activities and potentially enhance select sociocognitive skills.

Insight with hands and things.

PubMed

Vallée-Tourangeau, Frédéric; Steffensen, Sune Vork; Vallée-Tourangeau, Gaëlle; Sirota, Miroslav

2016-10-01

Two experiments examined whether different task ecologies influenced insight problem solving. The 17 animals problem was employed, a pure insight problem. Its initial formulation encourages the application of a direct arithmetic solution, but its solution requires the spatial arrangement of sets involving some degree of overlap. Participants were randomly allocated to either a tablet condition where they could use a stylus and an electronic tablet to sketch a solution or a model building condition where participants were given material with which to build enclosures and figurines. In both experiments, participants were much more likely to develop a working solution in the model building condition. The difference in performance elicited by different task ecologies was unrelated to individual differences in working memory, actively open-minded thinking, or need for cognition (Experiment 1), although individual differences in creativity were correlated with problem solving success in Experiment 2. The discussion focuses on the implications of these findings for the prevailing metatheoretical commitment to methodological individualism that places the individual as the ontological locus of cognition. Copyright © 2016 Elsevier B.V. All rights reserved.

Parallelized Three-Dimensional Resistivity Inversion Using Finite Elements And Adjoint State Methods

NASA Astrophysics Data System (ADS)

Schaa, Ralf; Gross, Lutz; Du Plessis, Jaco

2015-04-01

The resistivity method is one of the oldest geophysical exploration methods, which employs one pair of electrodes to inject current into the ground and one or more pairs of electrodes to measure the electrical potential difference. The potential difference is a non-linear function of the subsurface resistivity distribution described by an elliptic partial differential equation (PDE) of the Poisson type. Inversion of measured potentials solves for the subsurface resistivity represented by PDE coefficients. With increasing advances in multichannel resistivity acquisition systems (systems with more than 60 channels and full waveform recording are now emerging), inversion software require efficient storage and solver algorithms. We developed the finite element solver Escript, which provides a user-friendly programming environment in Python to solve large-scale PDE-based problems (see https://launchpad.net/escript-finley). Using finite elements, highly irregular shaped geology and topography can readily be taken into account. For the 3D resistivity problem, we have implemented the secondary potential approach, where the PDE is decomposed into a primary potential caused by the source current and the secondary potential caused by changes in subsurface resistivity. The primary potential is calculated analytically, and the boundary value problem for the secondary potential is solved using nodal finite elements. This approach removes the singularity caused by the source currents and provides more accurate 3D resistivity models. To solve the inversion problem we apply a 'first optimize then discretize' approach using the quasi-Newton scheme in form of the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method (see Gross & Kemp 2013). The evaluation of the cost function requires the solution of the secondary potential PDE for each source current and the solution of the corresponding adjoint-state PDE for the cost function gradients with respect to the subsurface resistivity. The Hessian of the regularization term is used as preconditioner which requires an additional PDE solution in each iteration step. As it turns out, the relevant PDEs are naturally formulated in the finite element framework. Using the domain decomposition method provided in Escript, the inversion scheme has been parallelized for distributed memory computers with multi-core shared memory nodes. We show numerical examples from simple layered models to complex 3D models and compare with the results from other methods. The inversion scheme is furthermore tested on a field data example to characterise localised freshwater discharge in a coastal environment.. References: L. Gross and C. Kemp (2013) Large Scale Joint Inversion of Geophysical Data using the Finite Element Method in escript. ASEG Extended Abstracts 2013, http://dx.doi.org/10.1071/ASEG2013ab306

Memory and accurate processing brain rehabilitation for the elderly: LEGO robot and iPad case study.

PubMed

Lopez-Samaniego, Leire; Garcia-Zapirain, Begonya; Mendez-Zorrilla, Amaia

2014-01-01

This paper presents the results of research that applies cognitive therapies associated with memory and mathematical problem-solving in elderly people. The exercises are programmed in an iPad and can be performed both from the Tablet and in an interactive format with a LEGO robot. The system has been tested with 2 men and 7 women over the age of 65 who have slight physical and cognitive impairment. Evaluation with the SUS resulted in a mean of 48.45 with a standard deviation of 5.82. The score of overall satisfaction was 84.37 with a standard deviation of 18.6. Interaction with the touch screen caused some usability problems due to the elderly people's visual difficulties and clicking accuracy. Future versions will include visualization with more color contrast and less use of the keyboard.

Intelligent holographic databases

NASA Astrophysics Data System (ADS)

Barbastathis, George

Memory is a key component of intelligence. In the human brain, physical structure and functionality jointly provide diverse memory modalities at multiple time scales. How could we engineer artificial memories with similar faculties? In this thesis, we attack both hardware and algorithmic aspects of this problem. A good part is devoted to holographic memory architectures, because they meet high capacity and parallelism requirements. We develop and fully characterize shift multiplexing, a novel storage method that simplifies disk head design for holographic disks. We develop and optimize the design of compact refreshable holographic random access memories, showing several ways that 1 Tbit can be stored holographically in volume less than 1 m3, with surface density more than 20 times higher than conventional silicon DRAM integrated circuits. To address the issue of photorefractive volatility, we further develop the two-lambda (dual wavelength) method for shift multiplexing, and combine electrical fixing with angle multiplexing to demonstrate 1,000 multiplexed fixed holograms. Finally, we propose a noise model and an information theoretic metric to optimize the imaging system of a holographic memory, in terms of storage density and error rate. Motivated by the problem of interfacing sensors and memories to a complex system with limited computational resources, we construct a computer game of Desert Survival, built as a high-dimensional non-stationary virtual environment in a competitive setting. The efficacy of episodic learning, implemented as a reinforced Nearest Neighbor scheme, and the probability of winning against a control opponent improve significantly by concentrating the algorithmic effort to the virtual desert neighborhood that emerges as most significant at any time. The generalized computational model combines the autonomous neural network and von Neumann paradigms through a compact, dynamic central representation, which contains the most salient features of the sensory inputs, fused with relevant recollections, reminiscent of the hypothesized cognitive function of awareness. The Declarative Memory is searched both by content and address, suggesting a holographic implementation. The proposed computer architecture may lead to a novel paradigm that solves 'hard' cognitive problems at low cost.

The efficiency of multimedia learning into old age.

PubMed

Van Gerven, Pascal W M; Paas, Fred; Van Merriënboer, Jeroen J G; Hendriks, Maaike; Schmidt, Henk G

2003-12-01

On the basis of a multimodal model of working memory, cognitive load theory predicts that a multimedia-based instructional format leads to a better acquisition of complex subject matter than a purely visual instructional format. This study investigated the extent to which age and instructional format had an impact on training efficiency among both young and old adults. It was hypothesised that studying worked examples that are presented as a narrated animation (multimedia condition) is a more efficient means of complex skill training than studying visually presented worked examples (unimodal condition) and solving conventional problems. Furthermore, it was hypothesised that multimedia-based worked examples are especially helpful for elderly learners, who have to deal with a general decline of working-memory resources, because they address both mode-specific working-memory stores. The sample consisted of 60 young (mean age = 15.98 years) and 60 old adults (mean age = 64.48 years). Participants of both age groups were trained in either a conventional, a unimodal, or a multimedia condition. Subsequently, they had to solve a series of test problems. Dependent variables were perceived cognitive load during the training, performance on the test, and efficiency in terms of the ratio between these two variables. Results showed that for both age groups multimedia-based worked examples were more efficient than the other training formats in that less cognitive load led to at least an equal performance level. Although no difference in the beneficial effect of multimedia learning was found between the age groups, multimedia-based instructions seem promising for the elderly.

nu-TRLan User Guide Version 1.0: A High-Performance Software Package for Large-Scale Harmitian Eigenvalue Problems

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

Yamazaki, Ichitaro; Wu, Kesheng; Simon, Horst

2008-10-27

The original software package TRLan, [TRLan User Guide], page 24, implements the thick restart Lanczos method, [Wu and Simon 2001], page 24, for computing eigenvalues {lambda} and their corresponding eigenvectors v of a symmetric matrix A: Av = {lambda}v. Its effectiveness in computing the exterior eigenvalues of a large matrix has been demonstrated, [LBNL-42982], page 24. However, its performance strongly depends on the user-specified dimension of a projection subspace. If the dimension is too small, TRLan suffers from slow convergence. If it is too large, the computational and memory costs become expensive. Therefore, to balance the solution convergence and costs,more » users must select an appropriate subspace dimension for each eigenvalue problem at hand. To free users from this difficult task, nu-TRLan, [LNBL-1059E], page 23, adjusts the subspace dimension at every restart such that optimal performance in solving the eigenvalue problem is automatically obtained. This document provides a user guide to the nu-TRLan software package. The original TRLan software package was implemented in Fortran 90 to solve symmetric eigenvalue problems using static projection subspace dimensions. nu-TRLan was developed in C and extended to solve Hermitian eigenvalue problems. It can be invoked using either a static or an adaptive subspace dimension. In order to simplify its use for TRLan users, nu-TRLan has interfaces and features similar to those of TRLan: (1) Solver parameters are stored in a single data structure called trl-info, Chapter 4 [trl-info structure], page 7. (2) Most of the numerical computations are performed by BLAS, [BLAS], page 23, and LAPACK, [LAPACK], page 23, subroutines, which allow nu-TRLan to achieve optimized performance across a wide range of platforms. (3) To solve eigenvalue problems on distributed memory systems, the message passing interface (MPI), [MPI forum], page 23, is used. The rest of this document is organized as follows. In Chapter 2 [Installation], page 2, we provide an installation guide of the nu-TRLan software package. In Chapter 3 [Example], page 3, we present a simple nu-TRLan example program. In Chapter 4 [trl-info structure], page 7, and Chapter 5 [trlan subroutine], page 14, we describe the solver parameters and interfaces in detail. In Chapter 6 [Solver parameters], page 21, we discuss the selection of the user-specified parameters. In Chapter 7 [Contact information], page 22, we give the acknowledgements and contact information of the authors. In Chapter 8 [References], page 23, we list reference to related works.« less

An efficient numerical method for solving the Boltzmann equation in multidimensions

NASA Astrophysics Data System (ADS)

Dimarco, Giacomo; Loubère, Raphaël; Narski, Jacek; Rey, Thomas

2018-01-01

In this paper we deal with the extension of the Fast Kinetic Scheme (FKS) (Dimarco and Loubère, 2013 [26]) originally constructed for solving the BGK equation, to the more challenging case of the Boltzmann equation. The scheme combines a robust and fast method for treating the transport part based on an innovative Lagrangian technique supplemented with conservative fast spectral schemes to treat the collisional operator by means of an operator splitting approach. This approach along with several implementation features related to the parallelization of the algorithm permits to construct an efficient simulation tool which is numerically tested against exact and reference solutions on classical problems arising in rarefied gas dynamic. We present results up to the 3 D × 3 D case for unsteady flows for the Variable Hard Sphere model which may serve as benchmark for future comparisons between different numerical methods for solving the multidimensional Boltzmann equation. For this reason, we also provide for each problem studied details on the computational cost and memory consumption as well as comparisons with the BGK model or the limit model of compressible Euler equations.

Case-based medical informatics

PubMed Central

Pantazi, Stefan V; Arocha, José F; Moehr, Jochen R

2004-01-01

Background The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning) and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. Discussion We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences of problem-solving and powerful case matching mechanisms), technical solutions are challenging. Finally, we discuss the major challenges for a technical solution: case record comprehensiveness, organization of information on similarity principles, development of pattern recognition and solving ethical issues. Summary Medical Informatics is an applied science that should be committed to advancing patient-centered medicine through individual knowledge processing. Case-based reasoning is the technical solution that enables a continuous individual knowledge processing and could be applied providing that challenges and ethical issues arising are addressed appropriately. PMID:15533257

Controlling uncertainty: a review of human behavior in complex dynamic environments.

PubMed

Osman, Magda

2010-01-01

Complex dynamic control (CDC) tasks are a type of problem-solving environment used for examining many cognitive activities (e.g., attention, control, decision making, hypothesis testing, implicit learning, memory, monitoring, planning, and problem solving). Because of their popularity, there have been many findings from diverse domains of research (economics, engineering, ergonomics, human-computer interaction, management, psychology), but they remain largely disconnected from each other. The objective of this article is to review theoretical developments and empirical work on CDC tasks, and to introduce a novel framework (monitoring and control framework) as a tool for integrating theory and findings. The main thesis of the monitoring and control framework is that CDC tasks are characteristically uncertain environments, and subjective judgments of uncertainty guide the way in which monitoring and control behaviors attempt to reduce it. The article concludes by discussing new insights into continuing debates and future directions for research on CDC tasks.

Cognitive mechanisms underlying third graders' arithmetic skills: Expanding the pathways to mathematics model.

PubMed

Träff, Ulf; Olsson, Linda; Skagerlund, Kenny; Östergren, Rickard

2018-03-01

A modified pathways to mathematics model was used to examine the cognitive mechanisms underlying arithmetic skills in third graders. A total of 269 children were assessed on tasks tapping the four pathways and arithmetic skills. A path analysis showed that symbolic number processing was directly supported by the linguistic and approximate quantitative pathways. The direct contribution from the four pathways to arithmetic proficiency varied; the linguistic pathway supported single-digit arithmetic and word problem solving, whereas the approximate quantitative pathway supported only multi-digit calculation. The spatial processing and verbal working memory pathways supported only arithmetic word problem solving. The notion of hierarchical levels of arithmetic was supported by the results, and the different levels were supported by different constellations of pathways. However, the strongest support to the hierarchical levels of arithmetic were provided by the proximal arithmetic skills. Copyright © 2017 Elsevier Inc. All rights reserved.

Looking for Creativity: Where Do We Look When We Look for New Ideas?

PubMed Central

Salvi, Carola; Bowden, Edward M.

2016-01-01

Recent work using the eye movement monitoring technique has demonstrated that when people are engaged in thought they tend to disengage from the external world by blinking or fixating on an empty portion of the visual field, such as a blank wall, or out the window at the sky. This ‘looking at nothing’ behavior has been observed during thinking that does not explicitly involve visual imagery (mind wandering, insight in problem solving, memory encoding and search) and it is associated with reduced analysis of the external visual environment. Thus, it appears to indicate (and likely facilitate) a shift of attention from external to internal stimuli that benefits creativity and problem solving by reducing the cognitive load and enhancing attention to internally evolving activation. We briefly mention some possible reasons to collect eye movement data in future studies of creativity. PMID:26913018

SALUTE Grid Application using Message-Oriented Middleware

NASA Astrophysics Data System (ADS)

Atanassov, E.; Dimitrov, D. Sl.; Gurov, T.

2009-10-01

Stochastic ALgorithms for Ultra-fast Transport in sEmiconductors (SALUTE) is a grid application developed for solving various computationally intensive problems which describe ultra-fast carrier transport in semiconductors. SALUTE studies memory and quantum effects during the relaxation process due to electronphonon interaction in one-band semiconductors or quantum wires. Formally, SALUTE integrates a set of novel Monte Carlo, quasi-Monte Carlo and hybrid algorithms for solving various computationally intensive problems which describe the femtosecond relaxation process of optically excited carriers in one-band semiconductors or quantum wires. In this paper we present application-specific job submission and reservation management tool named a Job Track Server (JTS). It is developed using Message-Oriented middleware to implement robust, versatile job submission and tracing mechanism, which can be tailored to application specific failover and quality of service requirements. Experience from using the JTS for submission of SALUTE jobs is presented.

Non-Boolean computing with nanomagnets for computer vision applications

NASA Astrophysics Data System (ADS)

Bhanja, Sanjukta; Karunaratne, D. K.; Panchumarthy, Ravi; Rajaram, Srinath; Sarkar, Sudeep

2016-02-01

The field of nanomagnetism has recently attracted tremendous attention as it can potentially deliver low-power, high-speed and dense non-volatile memories. It is now possible to engineer the size, shape, spacing, orientation and composition of sub-100 nm magnetic structures. This has spurred the exploration of nanomagnets for unconventional computing paradigms. Here, we harness the energy-minimization nature of nanomagnetic systems to solve the quadratic optimization problems that arise in computer vision applications, which are computationally expensive. By exploiting the magnetization states of nanomagnetic disks as state representations of a vortex and single domain, we develop a magnetic Hamiltonian and implement it in a magnetic system that can identify the salient features of a given image with more than 85% true positive rate. These results show the potential of this alternative computing method to develop a magnetic coprocessor that might solve complex problems in fewer clock cycles than traditional processors.

Composite Particle Swarm Optimizer With Historical Memory for Function Optimization.

PubMed

Li, Jie; Zhang, JunQi; Jiang, ChangJun; Zhou, MengChu

2015-10-01

Particle swarm optimization (PSO) algorithm is a population-based stochastic optimization technique. It is characterized by the collaborative search in which each particle is attracted toward the global best position (gbest) in the swarm and its own best position (pbest). However, all of particles' historical promising pbests in PSO are lost except their current pbests. In order to solve this problem, this paper proposes a novel composite PSO algorithm, called historical memory-based PSO (HMPSO), which uses an estimation of distribution algorithm to estimate and preserve the distribution information of particles' historical promising pbests. Each particle has three candidate positions, which are generated from the historical memory, particles' current pbests, and the swarm's gbest. Then the best candidate position is adopted. Experiments on 28 CEC2013 benchmark functions demonstrate the superiority of HMPSO over other algorithms.

Run-time scheduling and execution of loops on message passing machines

NASA Technical Reports Server (NTRS)

Crowley, Kay; Saltz, Joel; Mirchandaney, Ravi; Berryman, Harry

1989-01-01

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.

Run-time scheduling and execution of loops on message passing machines

NASA Technical Reports Server (NTRS)

Saltz, Joel; Crowley, Kathleen; Mirchandaney, Ravi; Berryman, Harry

1990-01-01

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.

A distributed-memory approximation algorithm for maximum weight perfect bipartite matching

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

Azad, Ariful; Buluc, Aydin; Li, Xiaoye S.

We design and implement an efficient parallel approximation algorithm for the problem of maximum weight perfect matching in bipartite graphs, i.e. the problem of finding a set of non-adjacent edges that covers all vertices and has maximum weight. This problem differs from the maximum weight matching problem, for which scalable approximation algorithms are known. It is primarily motivated by finding good pivots in scalable sparse direct solvers before factorization where sequential implementations of maximum weight perfect matching algorithms, such as those available in MC64, are widely used due to the lack of scalable alternatives. To overcome this limitation, we proposemore » a fully parallel distributed memory algorithm that first generates a perfect matching and then searches for weightaugmenting cycles of length four in parallel and iteratively augments the matching with a vertex disjoint set of such cycles. For most practical problems the weights of the perfect matchings generated by our algorithm are very close to the optimum. An efficient implementation of the algorithm scales up to 256 nodes (17,408 cores) on a Cray XC40 supercomputer and can solve instances that are too large to be handled by a single node using the sequential algorithm.« less

Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans.

PubMed

Stevens, Jeffrey R; Marewski, Julian N; Schooler, Lael J; Gilby, Ian C

2016-08-01

In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees ( Pan troglodytes ) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition.

Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans

PubMed Central

Marewski, Julian N.; Schooler, Lael J.; Gilby, Ian C.

2016-01-01

In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees (Pan troglodytes) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition. PMID:27853606

Triangular node for Transmission-Line Modeling (TLM) applied to bio-heat transfer.

PubMed

Milan, Hugo F M; Gebremedhin, Kifle G

2016-12-01

Transmission-Line Modeling (TLM) is a numerical method used to solve complex and time-domain bio-heat transfer problems. In TLM, rectangles are used to discretize two-dimensional problems. The drawback in using rectangular shapes is that instead of refining only the domain of interest, a large additional domain will also be refined in the x and y axes, which results in increased computational time and memory space. In this paper, we developed a triangular node for TLM applied to bio-heat transfer that does not have the drawback associated with the rectangular nodes. The model includes heat source, blood perfusion (advection), boundary conditions and initial conditions. The boundary conditions could be adiabatic, temperature, heat flux, or convection. A matrix equation for TLM, which simplifies the solution of time-domain problems or solves steady-state problems, was also developed. The predicted results were compared against results obtained from the solution of a simplified two-dimensional problem, and they agreed within 1% for a mesh length of triangular faces of 59µm±9µm (mean±standard deviation) and a time step of 1ms. Copyright © 2016 Elsevier Ltd. All rights reserved.

A functional neuroimaging study of the clinical reasoning of medical students.

PubMed

Chang, Hyung-Joo; Kang, June; Ham, Byung-Joo; Lee, Young-Mee

2016-12-01

As clinical reasoning is a fundamental competence of physicians for good clinical practices, medical academics have endeavored to teach reasoning skills to undergraduate students. However, our current understanding of student-level clinical reasoning is limited, mainly because of the lack of evaluation tools for this internal cognitive process. This functional magnetic resonance imaging (fMRI) study aimed to examine the clinical reasoning processes of medical students in response to problem-solving questions. We recruited 24 2nd-year medical students who had completed their preclinical curriculum. They answered 40 clinical vignette-based multiple-choice questions during fMRI scanning. We compared the imaging data for 20 problem-solving questions (reasoning task) and 20 recall questions (recall task). Compared to the recall task, the reasoning task resulted in significantly greater activation in nine brain regions, including the dorsolateral prefrontal cortex and inferior parietal cortex, which are known to be associated with executive function and deductive reasoning. During the recall task, significant activation was observed in the brain regions that are related to memory and emotions, including the amygdala and ventromedial prefrontal cortex. Our results support that medical students mainly solve clinical questions with deductive reasoning involving prior knowledge structures and executive functions. The problem-solving questions induced the students to utilize higher cognitive functions compared with the recall questions. Interestingly, the results suggested that the students experienced some emotional distress while they were solving the recall questions. In addition, these results suggest that fMRI is a promising research tool for investigating students' cognitive processes.

apGA: An adaptive parallel genetic algorithm

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

Liepins, G.E.; Baluja, S.

1991-01-01

We develop apGA, a parallel variant of the standard generational GA, that combines aggressive search with perpetual novelty, yet is able to preserve enough genetic structure to optimally solve variably scaled, non-uniform block deceptive and hierarchical deceptive problems. apGA combines elitism, adaptive mutation, adaptive exponential scaling, and temporal memory. We present empirical results for six classes of problems, including the DeJong test suite. Although we have not investigated hybrids, we note that apGA could be incorporated into other recent GA variants such as GENITOR, CHC, and the recombination stage of mGA. 12 refs., 2 figs., 2 tabs.

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

NASA Astrophysics Data System (ADS)

Kraszewski, Maciej; Pluciński, Jerzy

2017-06-01

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

The why, what, where, when and how of goal-directed choice: neuronal and computational principles

PubMed Central

Verschure, Paul F. M. J.; Pennartz, Cyriel M. A.; Pezzulo, Giovanni

2014-01-01

The central problems that goal-directed animals must solve are: ‘What do I need and Why, Where and When can this be obtained, and How do I get it?' or the H4W problem. Here, we elucidate the principles underlying the neuronal solutions to H4W using a combination of neurobiological and neurorobotic approaches. First, we analyse H4W from a system-level perspective by mapping its objectives onto the Distributed Adaptive Control embodied cognitive architecture which sees the generation of adaptive action in the real world as the primary task of the brain rather than optimally solving abstract problems. We next map this functional decomposition to the architecture of the rodent brain to test its consistency. Following this approach, we propose that the mammalian brain solves the H4W problem on the basis of multiple kinds of outcome predictions, integrating central representations of needs and drives (e.g. hypothalamus), valence (e.g. amygdala), world, self and task state spaces (e.g. neocortex, hippocampus and prefrontal cortex, respectively) combined with multi-modal selection (e.g. basal ganglia). In our analysis, goal-directed behaviour results from a well-structured architecture in which goals are bootstrapped on the basis of predefined needs, valence and multiple learning, memory and planning mechanisms rather than being generated by a singular computation. PMID:25267825

Artificial intelligence tools for pattern recognition

NASA Astrophysics Data System (ADS)

Acevedo, Elena; Acevedo, Antonio; Felipe, Federico; Avilés, Pedro

2017-06-01

In this work, we present a system for pattern recognition that combines the power of genetic algorithms for solving problems and the efficiency of the morphological associative memories. We use a set of 48 tire prints divided into 8 brands of tires. The images have dimensions of 200 x 200 pixels. We applied Hough transform to obtain lines as main features. The number of lines obtained is 449. The genetic algorithm reduces the number of features to ten suitable lines that give thus the 100% of recognition. Morphological associative memories were used as evaluation function. The selection algorithms were Tournament and Roulette wheel. For reproduction, we applied one-point, two-point and uniform crossover.

A modified conjugate gradient coefficient with inexact line search for unconstrained optimization

NASA Astrophysics Data System (ADS)

Aini, Nurul; Rivaie, Mohd; Mamat, Mustafa

2016-11-01

Conjugate gradient (CG) method is a line search algorithm mostly known for its wide application in solving unconstrained optimization problems. Its low memory requirements and global convergence properties makes it one of the most preferred method in real life application such as in engineering and business. In this paper, we present a new CG method based on AMR* and CD method for solving unconstrained optimization functions. The resulting algorithm is proven to have both the sufficient descent and global convergence properties under inexact line search. Numerical tests are conducted to assess the effectiveness of the new method in comparison to some previous CG methods. The results obtained indicate that our method is indeed superior.

China Report, Political, Sociological and Military Affairs

DTIC Science & Technology

1985-02-05

away long ago. However, their in- domitable spirit and their spirit of heroic struggle are still fresh in my memory. At that time, Cao Rui, the... Cao Rui were compelled to solve the problem through legal means by transferring the representatives in custody to the Hebei Provincial Court of...Zhang Ming, Tang Shudi, Want Zibo, Wang Jingmin, Li Baoqi. Wei Jinshan, and Chen Hui: advisers of the military region Sun Keji, Zhang Yuhua , and Wu

Generation and the subjective feeling of "aha!" are independently related to learning from insight.

PubMed

Kizilirmak, Jasmin M; Galvao Gomes da Silva, Joana; Imamoglu, Fatma; Richardson-Klavehn, Alan

2016-11-01

It has been proposed that sudden insight into the solutions of problems can enhance long-term memory for those solutions. However, the nature of insight has been operationalized differently across studies. Here, we examined two main aspects of insight problem-solving-the generation of a solution and the subjective "aha!" experience-and experimentally evaluated their respective relationships to long-term memory formation (encoding). Our results suggest that generation (generated solution vs. presented solution) and the "aha!" experience ("aha!" vs. no "aha!") are independently related to learning from insight, as well as to the emotional response towards understanding the solution during encoding. Moreover, we analyzed the relationship between generation and the "aha!" experience and two different kinds of later memory tests, direct (intentional) and indirect (incidental). Here, we found that the generation effect was larger for indirect testing, reflecting more automatic retrieval processes, while the relationship with the occurrence of an "aha!" experience was somewhat larger for direct testing. Our results suggest that both the generation of a solution and the subjective experience of "aha!" indicate processes that benefit long-term memory formation, though differently. This beneficial effect is possibly due to the intrinsic reward associated with sudden comprehension and the detection of schema-consistency, i.e., that novel information can be easily integrated into existing knowledge.

Pharmacological Interventions for the MATRICS Cognitive Domains in Schizophrenia: What’s the Evidence?

PubMed Central

Vingerhoets, Wilhelmina A. M.; Bloemen, Oswald J. N.; Bakker, Geor; van Amelsvoort, Therese A. M. J.

2013-01-01

Schizophrenia is a disabling, chronic psychiatric disorder with a prevalence rate of 0.5–1% in the general population. Symptoms include positive (e.g., delusions, hallucinations), negative (e.g., blunted affect, social withdrawal), as well as cognitive symptoms (e.g., memory and attention problems). Although 75–85% of patients with schizophrenia report cognitive impairments, the underlying neuropharmacological mechanisms are not well understood and currently no effective treatment is available for these impairments. This has led to the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) initiative, which established seven cognitive domains that are fundamentally impaired in schizophrenia. These domains include verbal learning and memory, visual learning and memory, working memory, attention and vigilance, processing speed, reasoning and problem solving, and social cognition. Recently, a growing number of studies have been conducted trying to identify the underlying neuropharmacological mechanisms of cognitive impairments in schizophrenia patients. Specific cognitive impairments seem to arise from different underlying neuropharmacological mechanisms. However, most review articles describe cognition in general and an overview of the mechanisms involved in these seven separate cognitive domains is currently lacking. Therefore, we reviewed the underlying neuropharmacological mechanisms focusing on the domains as established by the MATRICS initiative which are considered most crucial in schizophrenia. PMID:24363646

Neuropsychological Findings in Childhood Neglect and their Relationships to Pediatric PTSD

PubMed Central

De Bellis, Michael D.; Hooper, Stephen R.; Spratt, Eve G.; Woolley, Donald P.

2011-01-01

Statement of the problem Although child neglect is the most prevalent form of child maltreatment, the neurocognitive effects of neglect is understudied. Methods We examined IQ, reading, mathematics, and neurocognitive domains of fine-motor skills, language, visual-spatial, memory/learning, and attention/executive functions in two groups of non-sexually abused medically healthy neglected children, one with DSM-IV posttraumatic stress disorder (PTSD) and one without, and a demographically similar healthy non-maltreated control group. Key findings Significantly lower IQ, reading, mathematics, and selected differences in complex visual attention, visual memory, language, verbal memory and learning, planning, problem solving, and speeded naming were seen in Neglect Groups. The Neglect with PTSD Group performed worse than controls on NEPSY Design Copying, NEPSY Tower, and Mathematics; and performed worse than controls and Neglect without PTSD on NEPSY Memory for Faces-Delayed. Negative correlations were seen between PTSD symptoms, PTSD severity, and maltreatment variables, and IQ, Academic Achievement, and neurocognitive domains. Conclusions Neglected children demonstrated significantly lower neurocognitive outcomes and academic achievement than controls. Lower IQ, neurocognitive functions, and achievement may be associated with more PTSD symptoms (particularly re-experiencing symptoms), greater PTSD severity, and a greater number of maltreatment experiences. Trauma experiences may additionally contribute to subsequent neurodevelopmental risk in neglected children. PMID:19703321

Localization of synchronous cortical neural sources.

PubMed

Zerouali, Younes; Herry, Christophe L; Jemel, Boutheina; Lina, Jean-Marc

2013-03-01

Neural synchronization is a key mechanism to a wide variety of brain functions, such as cognition, perception, or memory. High temporal resolution achieved by EEG recordings allows the study of the dynamical properties of synchronous patterns of activity at a very fine temporal scale but with very low spatial resolution. Spatial resolution can be improved by retrieving the neural sources of EEG signal, thus solving the so-called inverse problem. Although many methods have been proposed to solve the inverse problem and localize brain activity, few of them target the synchronous brain regions. In this paper, we propose a novel algorithm aimed at localizing specifically synchronous brain regions and reconstructing the time course of their activity. Using multivariate wavelet ridge analysis, we extract signals capturing the synchronous events buried in the EEG and then solve the inverse problem on these signals. Using simulated data, we compare results of source reconstruction accuracy achieved by our method to a standard source reconstruction approach. We show that the proposed method performs better across a wide range of noise levels and source configurations. In addition, we applied our method on real dataset and identified successfully cortical areas involved in the functional network underlying visual face perception. We conclude that the proposed approach allows an accurate localization of synchronous brain regions and a robust estimation of their activity.

Effectiveness and Adoption of a Drawing-to-Learn Study Tool for Recall and Problem Solving: Minute Sketches with Folded Lists

PubMed Central

Heideman, Paul D.; Flores, K. Adryan; Sevier, Lu M.; Trouton, Kelsey E.

2017-01-01

Drawing by learners can be an effective way to develop memory and generate visual models for higher-order skills in biology, but students are often reluctant to adopt drawing as a study method. We designed a nonclassroom intervention that instructed introductory biology college students in a drawing method, minute sketches in folded lists (MSFL), and allowed them to self-assess their recall and problem solving, first in a simple recall task involving non-European alphabets and later using unfamiliar biology content. In two preliminary ex situ experiments, students had greater recall on the simple learning task, non-European alphabets with associated phonetic sounds, using MSFL in comparison with a preferred method, visual review (VR). In the intervention, students studying using MSFL and VR had ∼50–80% greater recall of content studied with MSFL and, in a subset of trials, better performance on problem-solving tasks on biology content. Eight months after beginning the intervention, participants had shifted self-reported use of drawing from 2% to 20% of study time. For a small subset of participants, MSFL had become a preferred study method, and 70% of participants reported continued use of MSFL. This brief, low-cost intervention resulted in enduring changes in study behavior. PMID:28495932

Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats

PubMed Central

Lloyd, Kevin; Becker, Nadine; Jones, Matthew W.; Bogacz, Rafal

2012-01-01

Learning to form appropriate, task-relevant working memory representations is a complex process central to cognition. Gating models frame working memory as a collection of past observations and use reinforcement learning (RL) to solve the problem of when to update these observations. Investigation of how gating models relate to brain and behavior remains, however, at an early stage. The current study sought to explore the ability of simple RL gating models to replicate rule learning behavior in rats. Rats were trained in a maze-based spatial learning task that required animals to make trial-by-trial choices contingent upon their previous experience. Using an abstract version of this task, we tested the ability of two gating algorithms, one based on the Actor-Critic and the other on the State-Action-Reward-State-Action (SARSA) algorithm, to generate behavior consistent with the rats'. Both models produced rule-acquisition behavior consistent with the experimental data, though only the SARSA gating model mirrored faster learning following rule reversal. We also found that both gating models learned multiple strategies in solving the initial task, a property which highlights the multi-agent nature of such models and which is of importance in considering the neural basis of individual differences in behavior. PMID:23115551

ADAPTIVE METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS VIA NATURAL EMBEDDINGS AND REJECTION SAMPLING WITH MEMORY.

PubMed

Rackauckas, Christopher; Nie, Qing

2017-01-01

Adaptive time-stepping with high-order embedded Runge-Kutta pairs and rejection sampling provides efficient approaches for solving differential equations. While many such methods exist for solving deterministic systems, little progress has been made for stochastic variants. One challenge in developing adaptive methods for stochastic differential equations (SDEs) is the construction of embedded schemes with direct error estimates. We present a new class of embedded stochastic Runge-Kutta (SRK) methods with strong order 1.5 which have a natural embedding of strong order 1.0 methods. This allows for the derivation of an error estimate which requires no additional function evaluations. Next we derive a general method to reject the time steps without losing information about the future Brownian path termed Rejection Sampling with Memory (RSwM). This method utilizes a stack data structure to do rejection sampling, costing only a few floating point calculations. We show numerically that the methods generate statistically-correct and tolerance-controlled solutions. Lastly, we show that this form of adaptivity can be applied to systems of equations, and demonstrate that it solves a stiff biological model 12.28x faster than common fixed timestep algorithms. Our approach only requires the solution to a bridging problem and thus lends itself to natural generalizations beyond SDEs.

ADAPTIVE METHODS FOR STOCHASTIC DIFFERENTIAL EQUATIONS VIA NATURAL EMBEDDINGS AND REJECTION SAMPLING WITH MEMORY

PubMed Central

Rackauckas, Christopher

2017-01-01

Adaptive time-stepping with high-order embedded Runge-Kutta pairs and rejection sampling provides efficient approaches for solving differential equations. While many such methods exist for solving deterministic systems, little progress has been made for stochastic variants. One challenge in developing adaptive methods for stochastic differential equations (SDEs) is the construction of embedded schemes with direct error estimates. We present a new class of embedded stochastic Runge-Kutta (SRK) methods with strong order 1.5 which have a natural embedding of strong order 1.0 methods. This allows for the derivation of an error estimate which requires no additional function evaluations. Next we derive a general method to reject the time steps without losing information about the future Brownian path termed Rejection Sampling with Memory (RSwM). This method utilizes a stack data structure to do rejection sampling, costing only a few floating point calculations. We show numerically that the methods generate statistically-correct and tolerance-controlled solutions. Lastly, we show that this form of adaptivity can be applied to systems of equations, and demonstrate that it solves a stiff biological model 12.28x faster than common fixed timestep algorithms. Our approach only requires the solution to a bridging problem and thus lends itself to natural generalizations beyond SDEs. PMID:29527134

Catching a glimpse of working memory: top-down capture as a tool for measuring the content of the mind.

PubMed

Lange, Nicholas D; Thomas, Rick P; Buttaccio, Daniel R; Davelaar, Eddy J

2012-11-01

This article outlines a methodology for probing working memory (WM) content in high-level cognitive tasks (e.g., decision making, problem solving, and memory retrieval) by capitalizing on attentional and oculomotor biases evidenced in top-down capture paradigms. This method would be of great use, as it could measure the information resident in WM at any point in a task and, hence, track information use over time as tasks dynamically evolve. Above and beyond providing a measure of information occupancy in WM, such a method would benefit from sensitivity to the specific activation levels of individual items in WM. This article additionally forwards a novel fusion of standard free recall and visual search paradigms in an effort to assess the sensitivity of eye movements in top-down capture, on which this new measurement technique relies, to item-specific memory activation (ISMA). The results demonstrate eye movement sensitivity to ISMA in some, but not all, cases.

Battery powered thought: enhancement of attention, learning, and memory in healthy adults using transcranial direct current stimulation.

PubMed

Coffman, Brian A; Clark, Vincent P; Parasuraman, Raja

2014-01-15

This article reviews studies demonstrating enhancement with transcranial direct current stimulation (tDCS) of attention, learning, and memory processes in healthy adults. Given that these are fundamental cognitive functions, they may also mediate stimulation effects on other higher-order processes such as decision-making and problem solving. Although tDCS research is still young, there have been a variety of methods used and cognitive processes tested. While these different methods have resulted in seemingly contradictory results among studies, many consistent and noteworthy effects of tDCS on attention, learning, and memory have been reported. The literature suggests that although tDCS as typically applied may not be as useful for localization of function in the brain as some other methods of brain stimulation, tDCS may be particularly well-suited for practical applications involving the enhancement of attention, learning, and memory, in both healthy subjects and in clinical populations. © 2013 Elsevier Inc. All rights reserved.

Adaptive memory: young children show enhanced retention of fitness-related information.

PubMed

Aslan, Alp; Bäuml, Karl-Heinz T

2012-01-01

Evolutionary psychologists propose that human cognition evolved through natural selection to solve adaptive problems related to survival and reproduction, with its ultimate function being the enhancement of reproductive fitness. Following this proposal and the evolutionary-developmental view that ancestral selection pressures operated not only on reproductive adults, but also on pre-reproductive children, the present study examined whether young children show superior memory for information that is processed in terms of its survival value. In two experiments, we found such survival processing to enhance retention in 4- to 10-year-old children, relative to various control conditions that also required deep, meaningful processing but were not related to survival. These results suggest that, already in very young children, survival processing is a special and extraordinarily effective form of memory encoding. The results support the functional-evolutionary proposal that young children's memory is "tuned" to process and retain fitness-related information. Copyright © 2011 Elsevier B.V. All rights reserved.

Advanced computational techniques for incompressible/compressible fluid-structure interactions

NASA Astrophysics Data System (ADS)

Kumar, Vinod

2005-07-01

Fluid-Structure Interaction (FSI) problems are of great importance to many fields of engineering and pose tremendous challenges to numerical analyst. This thesis addresses some of the hurdles faced for both 2D and 3D real life time-dependent FSI problems with particular emphasis on parachute systems. The techniques developed here would help improve the design of parachutes and are of direct relevance to several other FSI problems. The fluid system is solved using the Deforming-Spatial-Domain/Stabilized Space-Time (DSD/SST) finite element formulation for the Navier-Stokes equations of incompressible and compressible flows. The structural dynamics solver is based on a total Lagrangian finite element formulation. Newton-Raphson method is employed to linearize the otherwise nonlinear system resulting from the fluid and structure formulations. The fluid and structural systems are solved in decoupled fashion at each nonlinear iteration. While rigorous coupling methods are desirable for FSI simulations, the decoupled solution techniques provide sufficient convergence in the time-dependent problems considered here. In this thesis, common problems in the FSI simulations of parachutes are discussed and possible remedies for a few of them are presented. Further, the effects of the porosity model on the aerodynamic forces of round parachutes are analyzed. Techniques for solving compressible FSI problems are also discussed. Subsequently, a better stabilization technique is proposed to efficiently capture and accurately predict the shocks in supersonic flows. The numerical examples simulated here require high performance computing. Therefore, numerical tools using distributed memory supercomputers with message passing interface (MPI) libraries were developed.

Working Memory Maturation: Can We Get at the Essence of Cognitive Growth?

PubMed

Cowan, Nelson

2016-03-01

The theoretical and practical understanding of cognitive development depends on working memory, the limited information temporarily accessible for such daily activities as language processing and problem solving. In this article, I assess many possible reasons that working memory performance improves with development. A first glance at the literature leads to the weird impression that working memory capacity reaches adult levels during infancy but then regresses during childhood. In place of that unlikely explanation, I consider how infant studies may lead to overestimates of capacity if one neglects supports that the tasks provide, compared with adult-level tasks. Further development of working memory during the school years is also considered. Many investigators have come to suspect that working memory capacity may be constant after infancy because of various factors such as developmental increases in knowledge, filtering out of irrelevant distractions, encoding and rehearsal strategies, and pattern formation. With each of these factors controlled, though, working memory still improves during the school years. Suggestions are made for research to bridge the gap between infant and child developmental research, to understand the focus and control of attention in working memory and how these skills develop, and to pinpoint the nature of capacity and its development from infancy forward. © The Author(s) 2016.

Working Memory Maturation: Can We Get At the Essence of Cognitive Growth?

PubMed Central

Cowan, Nelson

2015-01-01

Our theoretical and practical understanding of cognitive development depends on working memory, the limited information temporarily accessible for such daily activities as language processing and problem-solving. Here I assess many possible reasons why working memory performance improves with development. A first glance at the literature leads to the weird impression that working memory capacity reaches adult-like levels during infancy but then regresses during childhood. In place of that unlikely surmise, I consider how infant studies may lead to overestimates of capacity if one neglects supports that the tasks provide, compared to adult-like tasks. Further development of working memory during the school years is also considered. Various confounding factors have led many investigators to suspect that working memory capacity may be constant after infancy; the factors include developmental increases in knowledge, filtering out of irrelevant distractions, encoding and rehearsal strategies, and pattern formation. With each of these factors controlled, though, working memory still improves during the school years. Suggestions are made for research to bridge the gap between infant and child developmental research, to understand the focus and control of attention in working memory and how they develop, and to pinpoint the nature of capacity and its development from infancy on. PMID:26993277

Heating 7.2 user`s manual

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

Childs, K.W.

1993-02-01

HEATING is a general-purpose conduction heat transfer program written in Fortran 77. HEATING can solve steady-state and/or transient heat conduction problems in one-, two-, or three-dimensional Cartesian, cylindrical, or spherical coordinates. A model may include multiple materials, and the thermal conductivity, density, and specific heat of each material may be both time- and temperature-dependent. The thermal conductivity may also be anisotropic. Materials may undergo change of phase. Thermal properties of materials may be input or may be extracted from a material properties library. Heat-generation rates may be dependent on time, temperature, and position, and boundary temperatures may be time- andmore » position-dependent. The boundary conditions, which may be surface-to-environment or surface-to-surface, may be specified temperatures or any combination of prescribed heat flux, forced convection, natural convection, and radiation. The boundary condition parameters may be time- and/or temperature-dependent. General gray-body radiation problems may be modeled with user-defined factors for radiant exchange. The mesh spacing may be variable along each axis. HEATING uses a runtime memory allocation scheme to avoid having to recompile to match memory requirements for each specific problem. HEATING utilizes free-form input. Three steady-state solution techniques are available: point-successive-overrelaxation iterative method with extrapolation, direct-solution, and conjugate gradient. Transient problems may be solved using any one of several finite-difference schemes: Crank-Nicolson implicit, Classical Implicit Procedure (CIP), Classical Explicit Procedure (CEP), or Levy explicit method. The solution of the system of equations arising from the implicit techniques is accomplished by point-successive-overrelaxation iteration and includes procedures to estimate the optimum acceleration parameter.« less

Heating 7. 2 user's manual

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

Childs, K.W.

1993-02-01

HEATING is a general-purpose conduction heat transfer program written in Fortran 77. HEATING can solve steady-state and/or transient heat conduction problems in one-, two-, or three-dimensional Cartesian, cylindrical, or spherical coordinates. A model may include multiple materials, and the thermal conductivity, density, and specific heat of each material may be both time- and temperature-dependent. The thermal conductivity may also be anisotropic. Materials may undergo change of phase. Thermal properties of materials may be input or may be extracted from a material properties library. Heat-generation rates may be dependent on time, temperature, and position, and boundary temperatures may be time- andmore » position-dependent. The boundary conditions, which may be surface-to-environment or surface-to-surface, may be specified temperatures or any combination of prescribed heat flux, forced convection, natural convection, and radiation. The boundary condition parameters may be time- and/or temperature-dependent. General gray-body radiation problems may be modeled with user-defined factors for radiant exchange. The mesh spacing may be variable along each axis. HEATING uses a runtime memory allocation scheme to avoid having to recompile to match memory requirements for each specific problem. HEATING utilizes free-form input. Three steady-state solution techniques are available: point-successive-overrelaxation iterative method with extrapolation, direct-solution, and conjugate gradient. Transient problems may be solved using any one of several finite-difference schemes: Crank-Nicolson implicit, Classical Implicit Procedure (CIP), Classical Explicit Procedure (CEP), or Levy explicit method. The solution of the system of equations arising from the implicit techniques is accomplished by point-successive-overrelaxation iteration and includes procedures to estimate the optimum acceleration parameter.« less