• Korean Journal of Child Studies
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• v.33 no.5
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• pp.53-70
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• 2012

The purpose of this study was to investigate the effects of task conditions (physical similarity between the spatial product and the reference space, presentation place of the spatial product) on children's spatial representation. The participants consisted of 40 3-year-olds and 40 4-year-olds. The results of this study are as follows. Both 3-year-olds and 4-year-olds were capable of a greater degree of spatial representation when there was a high level of physical similarity between the spatial product and the reference space, and when the presentation place of the spatial product was in the reference space. 4-year-olds were capable of more accurate spatial representation than 3-year-olds. There was no significant difference in the children's spatial representation depending on the type of spatial product (scale model, map). The results revealed that the physical similarity between the spatial product and the reference space and the presentation place of the spatial product are essential in young children's spatial representation. Additionally, the results indicated that spatial representation of children develops gradually from when they are three to when they turn four.

• Speech Sciences
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• v.13 no.2
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• pp.107-120
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• 2006

The main purpose of this study is to investigate whether Korean learners can use the vowel duration cue to distinguish voicing contrasts in word-final consonants in English. Given that the Korean group's performance on the auditory task was much better than their performance on the identification task or on the production task, we conclude that the AX discrimination task makes contact with a different layer of perception. In particular, the AX discrimination task can be done at the auditory or phonetic level, where differences in vowel length are still encoded in the representation. In contrast, the identification and production tasks are probing the mental representation of vowel length and voicing. It was also founded that Korean speakers stored neither vowel length nor voicing in memorized representations and did not internalize the lengthening of the preceding vowel as a rule to differentiate the voicing contrasts of final consonants, even though they were able to detect the acoustic differences in vowel duration provided that they were tested in an appropriate task.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.196-202
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• 2024

The ability to understand given environments and plan a sequence of actions leading to goal state is crucial for personal service robots. With recent advancements in deep learning, numerous studies have proposed methods for state representation in planning. However, previous works lack explicit information about relationships between objects when the state observation is converted to a single visual embedding containing all state information. In this paper, we introduce graph-based state representation that incorporates both object and relationship features. To leverage these advantages in addressing the task planning problem, we propose a Graph Neural Network (GNN)-based subgoal prediction model. This model can extract rich information about object and their interconnected relationships from given state graph. Moreover, a search-based algorithm is integrated with pre-trained subgoal prediction model and state transition module to explore diverse states and find proper sequence of subgoals. The proposed method is trained with synthetic task dataset collected in simulation environment, demonstrating a higher success rate with fewer additional searches compared to baseline methods.

• Journal of Gifted/Talented Education
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• v.5 no.2
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• pp.17-36
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• 1995

The present study examined preschooler's (3-5yrs) representation and evaluation skills in a puzzle completion task. The puzzle contained panels of four children dressed for each seacon and the key to success was using a body scheme to reconstruct the panels (head, torso, legs, feet and sky on top). Baseline data (Study 1) revealed a developmental pattern of increasing bydy scheme representation along with more careful attention to season consitent construction. Spontaneous verbalization also shifted from more guiding statements (where'the head?) to move evaluative statements (this isn't right). Study 2 examined different intervention techniques for increasing representation (verbal laveling) and evaluative processes (error detection practice), along with a control group that had unassisted practice. Three year olds benefited from verbal labeling, four year olds from both types of training. Verbalizations also showed appropriated shifts toward increasing evaluation, particularly for the older children. These findings are discussed in terms of a developmental hypothesis that representation precedes evaluation skills and that training techniques should take into account the relative balance between representation and evaluation skills in the individual for the task at hand.

• Korean Journal of Child Studies
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• v.26 no.4
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• pp.247-247
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• 2005

The attachment representation of 40 36- to 52-month-old upper-middle class children was analyzed in relation to their attachment security and mother-child interaction behaviors. Instruments were the Attachment Story Completion Task(Bretherton, Ridgeway, & Cassidy, 1990), the Attachment Q-set, and the Vocabulary test of the K-WIPPSI. Mother-child interaction behaviors were observed at home during semi-structured problem-solving situations. The Attachment Story Completion Task classified Korean preshoolers from these upper-middle class families as securely attached to their mothers. Girls' representation of their attachment relationship was more secure than boys. Preschoolers' attachment representation was significantly related to vocabulary ability. Attachment security correlated positively with preschool children's attachment representation. Mother-child interaction behaviors related significantly to preschool children's attachment representation.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1587-1592
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• 2003

There are three kinds of singularity in controlling redundant manipulators. Kinematic, algorithmic and representation singularities are those. If manipulators fall into any singularity without proper action to avoid it, the control system must go away from our desire, and we can meet a dangerous situation. Hence, we have to deal the singularities very carefully. In this paper, we describe an on-line solution for avoiding the occurrence of both algorithmic and kinematic singularities in task-priority based kinematic controllers of robotic manipulators. Representation singularity can be easily avoided by using proper representation algorithm, so, in this paper, we only consider kinematic and algorithmic singularities. The proposed approach uses a desired task reconstruction and a successive task projection in order to maintain the measure for singularity over a user defined minimum value. It shows a gain in performance and a better task error especially when working in proximity of singular configurations. It is particularly suitable for autonomous systems where an off-line trajectory control scheme is often not applicable. The advantage and performance of the proposed controller is verified by simulation works. And, the experiment with real manipulator is remaining for the future works.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.728-732
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• 2008

In this study, we developed motor representation brain mechanism system using fMRI and pilot study is performed, fMRI task were composed two tasks, which provided visual feedback and hid visual feedback. Left superior orbital gyrus, bilateral precentral gyrus, left superior occipital gyrus, left supplementary motor area, right thalamus, right postcentral gyrus and right superior parietal lobule activated with visual feedback. Left precuneus, right middle temporal gyrus, bilateral supplementary motor area, right anterior cingulate cortex, left Inferior temporal gyrus, left insula lobe, right superior parietal lobule, bilateral postcentral gyrus and left precentral gyrus activated without visual feedback. We could found brain mechanism of motor representation using without visual feedback.

• Korean Journal of Child Studies
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• v.36 no.4
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• pp.229-242
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• 2015

The purpose of this study was to investigate young children's nonsymbolic arithmetic ability according to task difficulty. The participants in this study comprised 43 2-year-old children and 48 4-year-old children recruited from 5 childcare centers located in Seoul, Korea. All tasks were composed of comparison, addition, subtraction, multiplication and division tasks. In addition, each arithmetic task varied with the ratio of the two quantities; low level(1:2), middle level(2:3), high level(4:5). The results revealed that 2 & 4-year-old children could perform a large numerical range of nonsymbolic arithmetic tasks without influences from previously learned mathematics. This finding suggests that children have a degree of numerical capacity prior to symbolic mathematics instruction. Furthermore, children's performance on nonsymbolic arithmetic tasks indicated the ratio signature of large approximate numerical representation. This result implies that large approximate numerical representation can be used in arithmetical manipulations.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.652-657
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• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.64-71
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• 2004

A daily report is one of the critical documents in construction projects, since it helps them keep track of various as-built information. Despite the important role in progress management, the daily reporting process is time-consuming, and the representation of task information on daily reports are not effective enough to accumulate daily as-built information for further use in project management. Task information is composed of a specific work type and a location where the task is performed, which means that the same type of work is repeated over the locations. However, in many cases the task locations are described differently depending on a reporter's preference or experience. Without representing task location information effectively, it is difficult to accumulate and to reuse as-built information. The objective of this research is to build a framework for generating task information which can be efficiently accumulated and reused for progress management. To do so, this research built a task information model with focusing on the representation of task location associated with a work type, and developed an information system that supports automated and interactive generation of task information.