• Journal of Multimedia Information System
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• v.8 no.2
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• pp.111-120
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• 2021

As recent virtual reality technologies provide a more natural three-dimensional interactive environment, users naturally learn to explore space and interact with synthetic objects. The virtual reality researcher develops a technique that realizes realistic sensory feedback to get appropriate feedback to sense input behavior. Although much recent virtual reality research works extensively consider the human factor, it is not easy to adapt to all new virtual environment contents. Among many human factors, distance perception has been treated as very important in virtual environment interaction accuracy. We study the experiential virtual environment with the feature of the virtual object connected with the real object. We divide the three-dimensional interaction, in which distance perception and behavior have a significant influence, into two types (whole-body movement and direct manipulation) and analyze the real and virtual visual distance perception heterogeneity phenomenon. Also, we propose a statistical correction method that can reduce a near-body movement and manipulation error when changing the interaction location and report the experiment results proving its effectiveness.

• Education of Primary School Mathematics
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• v.25 no.2
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• pp.197-211
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• 2022

In this study, we tried to find a way to improve the pedagogical decision-making practices related to the presentation order of 'large number' and 'small number' in problem situations of subtraction of the natural number. For this purpose, the elementary school teachers' perception about problem situations in real-life context of subtraction of natural numbers was investigated, and the collected data were analyzed qualitatively and quantitatively to identify teachers' pedagogical perceptions. As a result of this study, it was confirmed the need for consideration on how to set up a problem situations in real-life context of subtraction so that students can develop their ability to solve various types of problems. To this end, not only in a problem situation of subtraction where you have to think of 'large number' first and 'small number' later, but also about the introduction of problem situations in real-life context of subtraction in which you think about 'small number' first and 'large number' later, which often appears in real-life. You will need to recognize the need. And you should have a pedagogical view on this. The results of this study will be able to contribute to the preparation of pedagogical method that can expand the understanding of various problem situations where subtraction is applied from the lower grades of elementary school.

• Korean Institute of Interior Design Journal
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• v.15 no.3 s.56
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• pp.56-64
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• 2006

Human Being is being that have the reason as well as body, and first liaison consists through this body justly with outside. The essence of environmental problem such as today can speak that is a harmful traces for health that leave in air, water, soil that pass body. Actual nature is 'Ecological nature', that is necessary for human life directly in survival and offer the integrated relations with harmony. This grafting of principle, that is a construction for architecture and interior architecture in environment furtherance, is required. This is not a subject of usefulness and contemplation, but essential approach the cogredience, that is forming connection directly with nature, is required. Therefore, this research does Questel about 'Nature epistemology, which nature and human's relation can be integrated by alive practical relation. Through this, the Relatedness of 'Natural environment and construction surrounding' is accomplished 'the whole unity' and this research wish to investigate basis that a actual human work's environment can be completed as 'Ecological nature'.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.371-384
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• 2019

Motion perception has been tremendously improved in neuroscience and computer vision. The baseline motion perception model is mediated by the dorsal visual pathway involving the cortex areas the primary visual cortex (V1) and the middle temporal (V5 or MT) visual area. However, few works have been done on the extension of neural models to improve the efficacy and robustness of motion perception of real sequences. To overcome shortcomings in situations, such as varying illumination and large displacement, an adaptive V1-MT motion perception (Ad-V1MTMP) algorithm enriched to deal with real sequences is proposed and analyzed. First, the total variation semi-norm model based on Gabor functions (TV-Gabor) for structure-texture decomposition is performed to manage the illumination and color changes. And then, we study the impact of image local context, which is processed in extra-striate visual areas II (V2), on spatial motion integration by MT neurons, and propose a V1-V2 method to extract the image contrast information at a given location. Furthermore, we take feedback inputs from V2 into account during the polling stage. To use the algorithm on natural scenes, finally, multi-scale approach has been used to handle the frequency range, and adaptive pyramidal decomposition and decomposed spatio-temporal filters have been used to diminish computational cost. Theoretical analysis and experimental results suggest the new Ad-V1MTMP algorithm which mimics human primary motion pathway has universal, effective and robust performance.

• Journal of the Korean association of regional geographers
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• v.8 no.2
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• pp.247-255
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• 2002

In recent decades, the characteristics of natural hazard has been changed and the global cost of natural disasters has increased substantially. There are several trends in society and nature that suggest this pattern may continue, with more frequent mega-disasters occurring in the future. In particular, risk perception that is at odds with the "real" risk underlies the process of risk transference increases long-term vulnerability. Therefore investigating the correct risk transference and adjustments according to regional socio-economic structure can mitigate and reduce environmental, so called man-made hazard.

• (The)Korea Educational Review
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• v.23 no.1
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• pp.35-56
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• 2017

This study is to examine the effects of gesture based interface and display methods to make an effective virtual learning environment. The gesture based interface can provide interactive interface to make objects in the virtual learning environment by generating natural movement of users' gesture. This natural functionality leads users to apply natural movements as they do in real actions. Because of the natural user interface, the gesture based interface is expected to maximize learning outcomes. This study examined how the gesture based interface can be used when a head mounted display is applied for a virtual reality learning environment. For this study 44 colleagues students were participated. Two display methods (head mounted display vs. monitor) and two interface (gesture based interface vs. joystick) were tested to identify which might be more effective. The study was applied to different learning tasks which require different levels of spatial perception. The dependent variables are three constructs of virtual presence (spatial perception, immersiveness, and realness) and task completion time and recall tests. This study discussed potential disadvantages of gesture based interface while it showed positive usages of gesture based interface.

• Journal of Korea Game Society
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• v.12 no.4
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• pp.45-51
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• 2012

Current virtual game interfaces cannot comprehend our metaphor, cannot reflect on our natural behavior aspect, cannot make us immerse into a game, and makes a barrier between virtual game space and our real behavior. It is very meaningful issue to use real objects tightly related to human-being's behaviors or reactions for interacting with game applications. Interactive Augmented Reality interfaces may augment users' perception of the real world by adding virtual information to it. We attempted an experiment on camera-based non-marker interface for online TCG application. This experiment uses real TCG cards which are recognized by our two phases Image KeyPoint Extraction/Matching Algorithm. These initiative experiments not only enlarge immersion and reality to the game, but also make real and virtual world seamless.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.21-28
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• 2019

Recent years with the development of artificial intelligence and the success of the deep model, they have been deployed in all fields of computer vision. Action recognition, as an important branch of human perception and computer vision system research, has attracted more and more attention. Action recognition is a challenging task due to the special complexity of human movement, the same movement may exist between multiple individuals. The human action exists as a continuous image frame in the video, so action recognition requires more computational power than processing static images. And the simple use of the CNN network cannot achieve the desired results. Recently, the attention model has achieved good results in computer vision and natural language processing. In particular, for video action classification, after adding the attention model, it is more effective to focus on motion features and improve performance. It intuitively explains which part the model attends to when making a particular decision, which is very helpful in real applications. In this paper, we proposed a 3D dense convolutional network based on attention mechanism(ADD-Net), recognition of human motion behavior in the video.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.293-297
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• 2021

This paper applies the natural history contents of the Science Museum and combines the Gestalt theory to develop the butterfly arrangement structure of the butterfly sample box and the butterfly sample information necessary for the sample box as AR (Augmented Reality). Existing analog sample information is expressed as digital information by combining place, butterfly information, and graph to maximize the effect of digital diorama exhibition. Digital natural history information is increased or decreased, and an environment optimized for real samples and suitability is constructed, and natural history contents are arranged in the principles of collectiveness, closure, simplicity, and continuity using the Gestalt visual perception principle to increase attention and increase the attention of butterfly collection information. Was applied as an application plan of AR.

• Journal of Advanced Research in Ocean Engineering
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• v.3 no.3
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• pp.136-148
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• 2017

The paper presents dual arm ROV manipulation using deep reinforcement learning. The purpose of this underwater manipulator is to investigate and excavate natural resources in ocean, finding lost aircraft blackboxes and for performing other extremely dangerous tasks without endangering humans. This research work emphasizes on a self-learning approach using Deep Reinforcement Learning (DRL). DRL technique allows ROV to learn the policy of performing manipulation task directly, from raw image data. Our proposed architecture maps the visual inputs (images) to control actions (output) and get reward after each action, which allows an agent to learn manipulation skill through trial and error method. We have trained our network in simulation. The raw images and rewards are directly provided by our simple Lua simulator. Our simulator achieve accuracy by considering underwater dynamic environmental conditions. Major goal of this research is to provide a smart self-learning way to achieve manipulation in highly dynamic underwater environment. The results showed that a dual robotic arm trained for a 3DOF movement successfully achieved target reaching task in a 2D space by considering real environmental factor.