• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.52-53
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• 2012

Belief propagation (BP) is a commonly used global energy minimization algorithm for solving stereo matching problem in 3D reconstruction. However, it requires large memory bandwidth and data size. In this paper, we propose a novel memory-efficient algorithm of BP in stereo matching on the Graphics Processing Units (GPU). The data size and transfer bandwidth are significantly reduced by storing only a part of the whole message. In order to maintain the accuracy of the matching result, the local messages are reconstructed using shared memory available in GPU. Experimental result shows that there is almost an order of reduction in the global memory consumption, and 21 to 46% saving in memory bandwidth when compared to the conventional algorithm. The implementation result on a recent GPU shows that we can obtain 22.8 times speedup in execution time compared to the execution on CPU.

• The Mathematical Education
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• v.31 no.2
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• pp.109-119
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• 1992

The primary purpose of the present study is to provide the sources to improve the mathematical problem solving performance by analyzing the effects of the belief systems and the misconceptions of the middle school students in solving the problems. To attain the purpose of this study, the reserch is designed to find out the belief systems of the middle school students in solving the mathematical problems, to analyze the effects of the belief systems and the attitude on the process of the problem solving, and to identify the misconceptions which are observed in the problem solving. The sample of 295 students (boys 145, girls 150) was drawn out of 9th grade students from three middle schools selected in the Kangdong district of Seoul. Three kinds of tests were administered in the present study: the tests to investigate (1) the belief systems, (2) the mathematical problem solving performance, and (3) the attitude in solving mathematical problems. The frequencies of each of the test items on belief systems and attitude, and the scores on the problem solving performance test were collected for statistical analyses. The protocals written by all subjects on the paper sheets to investigate the misconceptions were analyzed. The statistical analysis has been tabulated on the scale of 100. On the analysis of written protocals, misconception patterns has been identified. The conclusions drawn from the results obtained in the present study are as follows; First, the belief systems in solving problems is splited almost equally, 52.95% students with the belief vs 47.05% students with lack of the belief in their efforts to tackle the problems. Almost half of them lose their belief in solving the problems as soon as they given. Therefore, it is suggested that they should be motivated with the mathematical problems derived from the daily life which drew their interests, and the individual difference should be taken into account in teaching mathematical problem solving. Second. the students who readily approach the problems are full of confidence. About 56% students of all subjects told that they enjoyed them and studied hard, while about 26% students answered that they studied bard because of the importance of the mathematics. In total, 81.5% students built their confidence by studying hard. Meanwhile, the students who are poor in mathematics are lack of belief. Among are the students accounting for 59.4% who didn't remember how to solve the problems and 21.4% lost their interest in mathematics because of lack of belief. Consequently, the internal factor accounts for 80.8%. Thus, this suggests both of the cognitive and the affective objectives should be emphasized to help them build the belief on mathematical problem solving. Third, the effects of the belief systems in problem solving ability show that the students with high belief demonstrate higher ability despite the lack of the memory of the problem solving than the students who depend upon their memory. This suggests that we develop the mathematical problems which require the diverse problem solving strategies rather than depend upon the simple memory. Fourth, the analysis of the misconceptions shows that the students tend to depend upon the formula or technical computation rather than to approach the problems with efforts to fully understand them This tendency was generally observed in the processes of the problem solving. In conclusion, the students should be taught to clearly understand the mathematical concepts and the problems requiring the diverse strategies should be developed to improve the mathematical abilities.

• 재활복지
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• v.21 no.3
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• pp.209-226
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• 2017

The purpose of this study was to investigate the relationships between memory belief, depression and cognitive functioning for stroke patients. A total of 88 subjects were participated in this study and the questionnaire was composed with general characteristics and K-MoCA, Beck Depression Inventory(BDI), Memory Self Efficacy Qestionnaire(MSEQ), Memory Controllability Inventory(MCI). The results showed that, for the memory self efficacy by general characteristics, there were significant differences in terms of level of education, living and economic status, the number of onset of stroke (p<.05), the memory controllability showed significant differences in economic status (p<.05), and the depression showed significant differences in onset duration of stroke (p<.05), and the cognitive functioning showed significant differences in gender, age, education, living condition, and the number of onset of stroke (p<.05). In addition, there was a significant correlation between memory self efficacy and memory controllability, depression, and cognitive functioning (p<.05). Memory controllability was correlated with depression (p<.01), depression was correlated with cognitive functioning (p<.01). Memory self efficacy, memory controllability and depression were found to be factors, affecting the cognitive functioning (p<.05). Based on this results, it is recommended to develop a multifaceted rehabilitation program in order to induce the positive mood, to reduce the negative emotions such as depression and to promote the memory belief about recovery of cognitive functioning.

• 한국노년학
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• v.36 no.3
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• pp.751-763
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• 2016

In this article, we conducted a literature review about cognitive aging and social-psychological factors that influence cognitive function in old age. As getting older, cognitive function was mostly seen as declining, even though the effect of aging is differential across domains of cognitive ability. The negative view about cognitive aging might be reflecting social-psychological factors such as age stereotypes. Age stereotypes vary among different cultures, but appear to be negative in general. Negative age stereotypes are related to lower level of memory performances. Older adults who were experimentally presented with positive age stereotypes exhibited better memory performances than those with negative age stereotypes. Self-referent belief, appraisals of one's own cognitive abilities, could also affect actual performance in cognitive tasks. Older adults showed lower self-referent belief than younger adults, and it might explain memory decline in old age. Theoretical explanation and implication about the relationship between social-psychological factors and cognitive abilities were discussed.

• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.33-40
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• 2014

Selecting appropriate features that products or services should provide for users has been a critical decision making problem for designers. However, the existing feature selection methods have prominent limitations when figuring out how they perceive the features. For example, selecting features based on the users' preference without analyzing users' mental models might lead to the 'feature creep' phenomenon. In this study, we suggest the 'False belief technique' that is able to detect users' mental model for the products/services that are formed after being provided with new features. This technique will be utilized as a way forward to help the designer to determine what features should be included in the new product development.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.87-97
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• 2007

This paper proposes drivers' rational belief formation under a bounded traffic environment. This is to escape the criticism that excessive rationality (e.g., a driver's calculating ability and memory capacity) is required of drivers. Under bounded traffic environments. drivers do not have structural knowledge of traffic conditions and others' decisions. Simulations are carried out using a program coded in C. Consequently, the author found the learning process of drivers and the value of information can be differentiated by route conditions and the characteristics of driver groups. Also, it was found that rational drivers form different beliefs about traffic conditions even though they have the same traffic environment in a bounded traffic environment.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.53-57
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• 2010

Low-density parity-check (LDPC) codes with belief-propagation (BP) algorithm achieve a remarkable performance close to the Shannon limit at reasonable decoding complexity. Conventionally, each iteration in decoding process contains two steps, the horizontal step and the vertical step. In this paper, an efficient implementation of the adaptive offset min-sum (AOMS) algorithm for decoding LDPC codes using the single-step method is proposed. Furthermore, the performances of the AOMS algorithm compared with belief-propagation (BP) algorithm are investigated. The algorithms using the single-step method reduce the implementation complexity, speed up the decoding process and have better efficiency in terms of memory requirements.

• Coupled systems mechanics
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• v.9 no.1
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• pp.5-28
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• 2020

Despite a widely-held belief that the finite element method is the method for the solution of solid mechanics problems, which has for 30 years dissuaded solid mechanics scientists from paying any attention to the finite volume method, it is argued that finite volume methods can be a viable alternative. It is shown that it is simple to understand and implement, strongly conservative, memory efficient, and directly applicable to nonlinear problems. A number of examples are presented and, when available, comparison with finite element methods is made, showing that finite volume methods can be not only equal to, but outperform finite element methods for many applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4246-4267
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• 2020

As the network goes deep into all aspects of people's lives, the number and the complexity of network traffic is increasing, and traffic classification becomes more and more important. How to classify them effectively is an important prerequisite for network management and planning, and ensuring network security. With the continuous development of deep learning, more and more traffic classification begins to use it as the main method, which achieves better results than traditional classification methods. In this paper, we provide a comprehensive review of network traffic classification based on deep learning. Firstly, we introduce the research background and progress of network traffic classification. Then, we summarize and compare traffic classification based on deep learning such as stack autoencoder, one-dimensional convolution neural network, two-dimensional convolution neural network, three-dimensional convolution neural network, long short-term memory network and Deep Belief Networks. In addition, we compare traffic classification based on deep learning with other methods such as based on port number, deep packets detection and machine learning. Finally, the future research directions of network traffic classification based on deep learning are prospected.

• Korean Journal of Child Studies
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• v.29 no.6
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• pp.177-191
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• 2008

Prior studies were limited in the comparison of false belief tasks with desire tasks due to lack of consideration of level of executive functions. To compensate for this, executive functions were included in new preference-related and game-related tasks of conflicting desire. These tasks were administered to 246 preschoolers ranging from 2.5 to 4 years of age. Statistical analysis was by one-way ANOVA and repeated measures ANOVA. Results showed significant main effects depending on age and task type. Younger children lacked ability of executive function, such as inhibition and working memory. Older preschoolers averaged better scores on task performance, showing that it is difficult for younger children to control their own desires and select the contradicted view.