• Clinical Psychopharmacology and Neuroscience
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• v.16 no.4
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• pp.489-493
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• 2018

Objective: This study was to identify whether working memory (WM) can be clearly subdivided according to auditory and visual modality. To do this, we administered the most recent and universal clinical WM measures in a mixed psychiatric sample. Methods: A total of 115 patients were diagnosed on the basis of DSM-IV diagnostic criteria and with MINI-Plus 5.0, a structured diagnostic interview. WM subtests of Korean version of Wechsler Adult Intelligence Scale-IV and Korean version of Wechsler Memory Scale-IV were administered to assess WM. Confirmatory factor analysis (CFA) was used to observe whether WM measures fit better to a one-factor or two-factor model. Results: CFA results demonstrated that a two factor model fits the data better than one-factor model as expected. Conclusion: Our study supports a modality model of WM, or the existence of modality-specific WM systems, and thus poses a clinical significance of assessing both auditory and visual WM tests.

• Journal of Environmental Impact Assessment
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• v.2 no.1
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• pp.39-55
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• 1993

The importance of urban and regional natural park increases because of the needs for preserving the natural resources and providing with natural recreation space in nature. This planning of natural park management should be established based on the research of the various natural resources in the park. But for the lack of effective data synthesizing methods and concepts, only some restricted factors for zoning plan are considered even though GIS computer system for large complex simulation is used. Therefore, in this study three ecological zoning models such as Basic Factor Model (BFM), Visual Landscape Model (VLM) and Comprehensive Ecological Model (CEM) are proposed and applied to Byounsan Peninsula Nature Park(BPNP) for comparison with the current natural park zoning. The BFM has three components -elevation, slope and vegetation. The VLM has applied with six components -elevation, slope, vegetation, road type, and the visual distance. Finally the CEM's modelling factors have included all of BFM, VLM components are added with the land use type, nature and historic resource factors. The zoning concept of BPNP was based on "Minimization" focused on the specific factors. But introduced modelling concept is "Optimization" based on the total ecological environment. So the result of the modelling has larger area for preservation and development zoning compared with the current zoning whose characteristics are ambiguous which allows the environmental destruction. The future study issues will be the determination of the weighting factor, component reconsideration based on the ground truth data and the agriculture residential area zoning.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.477-482
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• 2020

The human visual cortex has the characteristic that reacts sensitively to stimuli with special directional or temporal frequency changes while it is insensitive to selective stimuli of spatial phases. In this paper we implemented the model of complex cell using an image estimation iterative algorithm by Gabor wavelet transform. The performance of implemented model evaluated the consistency between the physiological experimental results in related papers. The implemented model is limited in the complete model of the receptive field in the retina where simple cells and complex cells are distributed together. But the implemented model express the reaction of the complex cells from the point of view of the detection of corners and edges.

• Journal of the Ergonomics Society of Korea
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• v.30 no.2
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• pp.365-373
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• 2011

The existing GOMS model overestimates the performance time of mouse activities because it describes them in a serial sequence. However, parallel movements of eye and hand(eye-hand coordination) have been dominant in mouse activities and this eye-hand coordination is the main factor for the overestimation of performance time. In this study, therefore, the revised CGOMSL model was developed to implement eye-hand coordination to the mouse activity to overcome one of the limitations of GOMS model, the lack of capability for parallel processing. The suggested revised CGOMSL model for drag activity, as an example for one of mouse activities in this study, begins visual search processing before a hand movement but ends the visual search processing with the hand movement in the same time. The results show that the revised CGOMSL model made the prediction of human performance more accurately than the existing GOMS model. In other words, one of the limitations of GOMS model, the incapability of parallel processing, could be overcome with the revised CGOMSL model so that the performance time should be more accurately predicted.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.5
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• pp.255-265
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• 2013

3DTV is expected to be a promising next-generation broadcasting service. On the other hand, the visual discomfort/fatigue problems caused by viewing 3D videos have become an important issue. This paper proposes a perceptual quality assessment metric for a stereoscopic video (SV-PQAM). To model the SV-PQAM, this paper presents the following features: temporal variance, disparity variation in intra-frames, disparity variation in inter-frames and disparity distribution of frame boundary areas, which affect the human perception of depth and visual discomfort for stereoscopic views. The four features were combined into the SV-PQAM, which then becomes a no-reference stereoscopic video quality perception model, as an objective quality assessment metric. The proposed SV-PQAM does not require a depth map but instead uses the disparity information by a simple estimation. The model parameters were estimated based on linear regression from the mean score opinion values obtained from the subjective perception quality assessments. The experimental results showed that the proposed SV-PQAM exhibits high consistency with subjective perception quality assessment results in terms of the Pearson correlation coefficient value of 0.808, and the prediction performance exhibited good consistency with a zero outlier ratio value.

• Journal of the Korea Computer Graphics Society
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• v.20 no.4
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• pp.1-7
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• 2014

The volume rendering has become an important technique in many applications along with hardware development. Understanding and perception of volume visualization benefit from visual cues which are available from shading. Better visual cues can be obtained from global illumination models but it's huge amount of computation and extra GPU memory need cause a lack of interactivity. In this paper, in order to improve visual cues on volume rendering, we propose an image space occlusion shading model which requires no additional resources.

• Smart Structures and Systems
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• v.13 no.6
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• Journal of information and communication convergence engineering
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• v.2 no.2
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• pp.132-137
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• 2004

Most of the current computer vision theories are based on hypotheses that are difficult to apply to the real world, and they simply imitate a coarse form of the human visual system. As a result, they have not been showing satisfying results. In the human visual system, there is a mechanism that processes information due to memory degradation with time and limited storage space. Starting from research on the human visual system, this study analyzes a mechanism that processes input information when information is transferred from the retina to ganglion cells. In this study, a model for the characteristics of ganglion cells in the retina is proposed after considering the structure of the retina and the efficiency of storage space. The MNIST database of handwritten letters is used as data for this research, and ART2 and SOM as recognizers. The results of this study show that the proposed recognition model is not much different from the general recognition model in terms of recognition rate, but the efficiency of storage space can be improved by constructing a mechanism that processes input information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4476-4491
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• 2021

Video service providers tend to face user network problems in the process of transmitting video streams. They strive to provide user with superior video quality in a limited bitrate environment. It is necessary to accurately determine the target bitrate range of the video under different quality requirements. Recently, several schemes have been proposed to meet this requirement. However, they do not take the impact of visual influence into account. In this paper, we propose a new multi-category model to accurately predict the target bitrate range with target visual quality by machine learning. Firstly, a dataset is constructed to generate multi-category models by machine learning. The quality score ladders and the corresponding bitrate-interval categories are defined in the dataset. Secondly, several types of spatial-temporal features related to VMAF evaluation metrics and visual factors are extracted and processed statistically for classification. Finally, bitrate prediction models trained on the dataset by RandomForest classifier can be used to accurately predict the target bitrate of the input videos with target video quality. The classification prediction accuracy of the model reaches 0.705 and the encoded video which is compressed by the bitrate predicted by the model can achieve the target perceptual quality.

• The Korean Journal of Archival Studies
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• no.33
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• pp.155-206
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• 2012

Interests in archives management are getting expanded from the public sector into the cultural and artistic field for the ten years after legislation of "Act on the Management of Public Archives" in 1999. However, due to lack of recognition on the importance of archives in the cultural and artistic field, it is rather frequent that information is kept scattered or archives are lost. As an example, absence of precise contract documents or notes of bestowal keeps people from locating great amount of cultural properties, and because of it these creative properties are in the risk of thefts, the closed-door auctioning, or trades in unofficial channels. As how a nation manages cultural and artistic creation inside the nation reflects its cultural level, it can be said that one of the indexes to notice the extent of a nation's cultural level is to take a look at how they are circulated. This study started from this point. Growing economy and rising interests in culture and art made the society more cognizant of the importance and value that visual artworks have, but the archives and information which are showing the context of these artworks and are produced in the course of social interaction are relatively disregarded because too much emphasis lies on the work itself. It is harder to find archives or documentations in Korea than in other advanced countries about the artists themselves or philosophical discourse on the background of the artworks. There is not so much interest to preserve the archives and information produced after the exhibition also, and they are used for no more than promotion or reference. Hereupon, the researcher recognized the importance of visual arts archives and believed that systemic management on them are high in need. And metadata is an essential way for the systemic management, as recently management on artworks or their archives are conducted using the system of the agencies even though they are not produced electronically. The objective of this study is to manage visual arts archives systematically by designing a data model reflecting traits of visual arts archives. Metadata are needed in the every course of archives from acquisition to management, preservation and application. Visual arts archives find its rich value only when a systemic relationship is established among information on artist, artwork and events including exhibition. By establishing a Multiple Entity Data Model, in which artworks, artists and events (exhibitions) make relationship all together, metadata for management on visual arts archive gets more efficiency and at the same time explanatory trait of the archive gets higher. For this reason we, in the study, tried to design a data model by setting each as an independent entities and designating relations between them, in order to find a way to manage visual arts archives more systematically.