• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.407-418
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• 2023

The Multi-Object Goal Visual Navigation(MultiOn) is a visual navigation task in which an agent must visit to multiple object goals in an unknown indoor environment in a given order. Existing models for the MultiOn task suffer from the limitation that they cannot utilize an integrated view of multimodal context because use only a unimodal context map. To overcome this limitation, in this paper, we propose a novel deep neural network-based agent model for MultiOn task. The proposed model, MCFMO, uses a multimodal context map, containing visual appearance features, semantic features of environmental objects, and goal object features. Moreover, the proposed model effectively fuses these three heterogeneous features into a global multimodal context map by using a point-wise convolutional neural network module. Lastly, the proposed model adopts an auxiliary task learning module to predict the observation status, goal direction and the goal distance, which can guide to learn the navigational policy efficiently. Conducting various quantitative and qualitative experiments using the Habitat-Matterport3D simulation environment and scene dataset, we demonstrate the superiority of the proposed model.

• Research in Community and Public Health Nursing
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• v.12 no.1
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• pp.142-149
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• 2001

The health education for elementary school students is a very important factor in the development of adult health practices. Particularly, eyesight is difficult to recover if lost. Therefore, prevention is better than cure. This study was conducted to investigate the factors that affect the visual health behavior of elementary school students and to furnish basic materials and directions for the promotion of elementary school health. The investigation was carried out for 4 days from 9. 18. 2000 to 9. 21. 2000 for 199 children in 3 elementary schools. A questionnaire was composed of 3 questions about general property. 20 questions about visual health behavior. 7 questions about visual self-efficacy. 5 questions about visual motivation. 16 questions about self-conception. 20 questions about the health locus of control. The data was analysed by an SAS program for t-test. ANOVA. correlation, and multiple regression tests. The results are as follows. 1. The visual health behavior of elementary school children was good (average 52.53). 2. For visual health behavior, school, year, and sex were influential factors. economic levels were not. 3. Visual health behavior had a significant correlation with visual self-efficacy, visual health motives and self-conception. but not with the locus of control. 4. In the multiple regression test, visual self-efficacy and self-conception were significant prediction factors -- the suitability of the regression model was 30.8%. Suggestions from the results are as follows: First, school year and sex had a significant influence on visual health behavior: therefore, it is necessary to consider these two factors when education programs are developed. Second, this study was carried out for students in a partial area only. Therefore, repeated studies for a large sample are necessary for the future.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.6
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• pp.937-943
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• 1990

In this paper, a subband coding scheme using the human visual system(HVS) model for encoding monochrome images is proposed to produce perceptually higher quality images compared with the regular subband coding scheme. The proposed approach first transforms the intensity image to the density image by a point nonlinear transformation. A frequency band dexomposition of the density image is carried out by means of 2-D seaprable quadrature mirror filters, which split the density image spectrum into 16 equall rate subbands. Bits are allocated among the subbands to minimize the weighted mean squar error (WMSE) for differential pulse code modulation(DPCM) coding of the subbands. The weight for each subband is calculated from the modulation transfer function (MTF) of the HVS model at corresponding frequencies. The performances of the proposed approach are evaluated for 256 * 256 monochrome images at the bit rates of 0.5, 0.75 and 1.0 bita per pixel. Computer simulation results indicate that using the HVS model yields more pleasing reconstructed images than regular subband coding approach which does not use HVS model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.141-150
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• 2013

This study proposes technology using Active Shape Model to track the object separating it by depth-sensors. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust object can be extracted. The proposed algorithm removes the horizontal component from the information of the initial depth map and separates the object using the vertical component. In addition, it is also a more efficient morphology, and labeling to perform image correction and object extraction. By applying Active Shape Model to the information of an extracted object, it can track the object more robustly. Active Shape Model has a robust feature-to-object occlusion phenomenon. In comparison to visual camera-based object tracking algorithms, the proposed technology, using the existing depth of the sensor, is more efficient and robust at object tracking. Experimental results, show that the proposed ASM-based algorithm using depth sensor can robustly track objects in real-time.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.210-218
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• 2021

CNN (Convolutional Neural Network), a type of deep learning algorithm, is a type of artificial neural network used to analyze visual images. In deep learning, it is classified as a deep neural network and is most commonly used for visual image analysis. Accordingly, an AI autonomous driving model was constructed through real-time image processing, and a crosswalk image of a road was used as an obstacle. In this paper, we proposed a low-cost model that can actually implement autonomous driving based on the CNN model. The most well-known deep neural network technique for autonomous driving is investigated and an end-to-end model is applied. In particular, it was shown that training and self-driving on a simulated road is possible through a practical approach to realizing lane detection and keeping.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.4
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• pp.158-168
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• 2000

Vehicle driving simulators can provide engineers with benefits on the development and modification of vehicle models. One of the most important factors to realistic simulations is the fidelity given by a motion system and a real-time visual image generation system. Virtual reality technology has been widely used to achieve high fidelity. In this paper the virtual environment including a visual system like a head-mounted display is developed for a vehicle driving simulator system by employing the virtual reality technique. virtual vehicle and environment models are constructed using the object-oriented analysis and design approach. Accordint to the object model a three dimensional graphic model is developed with CAD tools such as Rhino and Pro/E. For the real-time image generation the optimized IRIS Performer 3D graphics library is embedded with the multi-thread methodology. Compared with the single loop apprach the proposed methodology yields an acceptable image generation speed 20 frames/sec for the simulator.

• Journal of Korean Society on Water Environment
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• v.24 no.3
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• pp.285-290
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• 2008

This study was done to explain the role of limestone which might intervene in the phosphorus cycle in a lake. The effects of limestone on the dissolution of phosphate were estimated by simulations with the computer model Visual MINTEQ, which is designed for the chemical equilibrium calculations. According to the calculations limestone shows remarkable effects for the suppression of phosphate dissolution. The limestone can suppress the dissolution of phosphates by sacrificing themselves to acids, and as a consequence can increase the hardness and alkalinity of the lake. Both hardness and alkalinity play an important role in reducing soluble P and thus alleviate the eutrophication potential.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.80-89
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• 2000

Driving simulators provide engineers with a power tool in the development and modification stages of vehicle models. One of the most important factors to realistic simulations is the fidelity obtained by a motion bed and a real-time visual image generation algorithm. Virtual reality technology has been widely used to enhance the fidelity of vehicle simulators. This paper develops the virtual environment for such visual system as head-mounted display for a vehicle driving simulator. Virtual vehicle and environment models are constructed using the object-oriented analysis and design approach. Based on the object model, a three-dimensional graphic model is completed with CAD tools such as Rhino and Pro/ENGINEER. For real-time image generation, the optimized IRIS Performer 3D graphics library is embedded with the multi-thread methodology. The developed software for a virtual driving simulator offers an effective interface to virtual reality devices.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.5-8
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• 2008

This study proposed the Knowledge Base Building method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. This research evaluated subject's preferences on the commercial spaces set to the hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose the methods of Navigation Knowledge Base (NKB). The NKB was composed by three elements; 1.the correlation model between emotional characteristics, 2.the causal relationship between visual characteristics and emotional characteristics, 3.the transformation model between visual characteristics and the physical characteristics.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.403-410
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• 1999

General1y, H-section is used for columns and beams in the middle and low steel building, But it has a strong and weak axis. Thus if H-section is used for columns, the structure needs reinforcement on the weak axis. Therefore recently, square holler section(S.H.S) is used for columns because it is able to coiler the vulnerability of H-section. Structural analysis is usually executed under the assumption that connections are either ideally pinned joint or fully rigid joint. Actually all connections are semi-rigid which possess a rotational stiffness. Therefore it can be designed economically as using the property of connections which has a rotational stiffness. This paper presents a prediction model curve which is fitted Kishi-Chen power Model about the behavior of connection between H-beam and S.H.S column. Non-linear analysis program was considered the non-linearity of semi-rigid connection and the geometrical non-linearity under the effect of axial force. It was programed by FORTRAN90 and Visual Basic.