• Applied Microscopy
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• v.46 no.3
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• pp.150-154
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• 2016

The ultrastructure of fertilized egg envelope from Pseudobagrus fulvidraco belongs to Bagridae was investigated using light and electron microscopes. The fertilized egg was compressed spherical, light-yellowish, demersal, and adhesive. The size of fertilized egg is about $1.85{\pm}0.13mm$, perivitelline space is not well developed, and there were no appendicular structures on the outer surface of egg envelope and oil droplets in vitelline membrane under light microscope. The micropyle was located in the animal pole of fertilized egg. Adhesive reticular fiber was covered fertilized egg envelope. The thickness of egg envelope was about $3.7{\sim}4.2{\mu}m$, and the egg envelope consisted of two layers: an outer, electron-dense adhesive fibers layer and an simple inner layer with pore. Therefore, the ultrastructure of cross section of the fertilized egg envelope showed species specificity, but studies on the other species belongs to Bagridae were need to get correct information about common traits in family.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.102-109
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• 2013

The purpose of this study is to express imagination which is not limited to the description of the facts and reproduce the photos as a media to explore the new possibilities for creative expression and the experience of the day-to-day operations for the implementation of the scheme of art genre. The art work for this study using digital images in Autodesk Combustion Workspace as the upper and lower layers were synthesized using the Transfer Mode feature. This study proposed a new photomontage production model, and challenged for the Possibility of a variety of visual representations of media art. Especially the production presents in this study can be applied to various video.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.1
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• pp.19-25
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• 2001

A novel approach for the feature extraction of handwritten characters is proposed by using spatial filtering neural networks with 4 layers. The proposed system first removes rough pixels which are easy to occur in handwritten characters. The system then extracts and removes the boundary information which have no influence on characters recognition. Finally, The system extracts feature information and removes the noises from feature information. The spatial filters adapted in the system correspond to the receptive fields of ganglion cells in retina and simple cells in visual cortex. With PE2 Hangul database, we perform experiments extracting features of handwritten characters recognition. It will be shown that the network can extract feature informations from handwritten characters successfully.

• Korean Institute of Interior Design Journal
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• v.16 no.6
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• pp.36-46
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• 2007

Regeneration of old buildings is one of the most imperative responses to the 21th century issue of sustainable urban architectural environment. In particular, creative circulation of generation which conversion means highlights the conversion as a new design method. In this study, by examining buildings built over the last decade, the mutual relationship between old elements of existing buildings and new elements of newly required functions was analyzed and types of relationships such as 'alien insertion', 'mediate intervention', 'endogenous expansional enveloping', 'contrastive confliction' and 'over-layering' were defined. In addition, design strategies including the paradoxical curio, fore-grounding and unification were derived from each relationship. Finally, according to the relation type and design strategy, this study suggests several features of conversion design; (1) maximization of symbolism using unfamiliarities - emphasizing futuristic or contextual symbol with intentional contrasts by preserving the work or using contemporary addition; (2) time confusion using neutral space - meeting the need by harmonizing and cooperating existing elements and new elements; (3) mutual emphasizing by individualization - revealing differences between old and new for an aesthetical tension; (4) synchronism by constructional combination - making the one unity of different layers; (5) expansion by enveloping - experience of visual reverse and creation of extra space by roofing above building groups. The reconversion should be continuously researched in the future since conversion is a sustainable design method for the future of architecture.

• Smart Media Journal
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• v.5 no.1
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• pp.104-113
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• 2016

A new design method for multi-functional pull-down menu based on stacking rules is proposed. The importance of a design point of view has been emphasized in many previous studies on web navigation. Taking technical aspects with an emphasis on programming techniques into consideration in this paper, multiple elements, which are used for constructing main menu of the pull-down menu, are capable of performing their unique functions independently in addition to basic classification function by disposing them to separated layers using stacking rules. Furthermore, the improvement of visual effects and efficiency for information navigation can be expected by implementing submenu selection-bar using animation techniques and function to automatically search submenu item. Finally, the effectiveness of the proposed method is identified by implementing multi-functional pull-down menu using CSS and jQuery.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.113-117
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• 2020

Images were taken under various weather such as rain, haze, snow often show low visibility, which can dramatically decrease accuracy of some tasks in computer vision: object detection, segmentation. Besides, previous work to enhance image usually downsample the image to receive consistency features but have not yet good upsample algorithm to recover original size. So, in this research, we jointly implement removal streak in heavy rain image and super resolution using a deep network. We put forth a 2-stage network: a multi-model network followed by a refinement network. The first stage using rain formula in the single image and two operation layers (addition, multiplication) removes rain streak and noise to get clean image in low resolution. The second stage uses refinement network to recover damaged background information as well as upsample, and receive high resolution image. Our method improves visual quality image, gains accuracy in human action recognition task in datasets. Extensive experiments show that our network outperforms the state of the art (SoTA) methods.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.13-22
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• 2020

Reinforcement steel fixing is a skilled and manually intensive construction trade. Current practice for the quality assessment of reinforcement steel fixing is normally performed by fabricators and has high potential in having errors due to the tedious nature of the work. In order to overcome the current inspection limitation, this study presents an approach that provides visual assistance and inspection enhancement for inspectors to assess the dimensional layout of reinforcement steel fixing. To this end, this study aims to establish an end-to-end framework for rebar layout quality inspection using laser scanning and Augmented Reality (AR). The proposed framework is composed of three parts: (1) the laser-scanned rebar data processing; (2) the rebar inspection procedure integrating with AR; and (3) the checking and fixing the rebar layout through AR visualization. In order to investigate the feasibility of the proposed framework, a case study assessing the rebar layout of a lab-scaled formwork containing two rebar layers is conducted. The results of the case studies demonstrate that the proposed approach using laser scanning and AR has the potential to produce an intuitive and accurate quality assessment for the rebar layout.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.270-278
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• 2023

We propose a container orchestration system for process workloads that combines the potential of big data and machine learning technologies to integrate enterprise process-centric workloads. This proposed system analyzes big data generated from industrial automation to identify hidden patterns and build a machine learning prediction model. For each machine learning case, training data is loaded into a data store and preprocessed for model training. In the next step, you can use the training data to select and apply an appropriate model. Then evaluate the model using the following test data: This step is called model construction and can be performed in a deployment framework. Additionally, a visual hierarchy is constructed to display prediction results and facilitate big data analysis. In order to implement parallel computing of PCA in the proposed system, several virtual systems were implemented to build the cluster required for the big data cluster. The implementation for evaluation and analysis built the necessary clusters by creating multiple virtual machines in a big data cluster to implement parallel computation of PCA. The proposed system is modeled as layers of individual components that can be connected together. The advantage of a system is that components can be added, replaced, or reused without affecting the rest of the system.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.203-210
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• 2017

In this paper, we propose an effective neural network model for image caption generation and model transfer. This model is a kind of multi-modal recurrent neural network models. It consists of five distinct layers: a convolution neural network layer for extracting visual information from images, an embedding layer for converting each word into a low dimensional feature, a recurrent neural network layer for learning caption sentence structure, and a multi-modal layer for combining visual and language information. In this model, the recurrent neural network layer is constructed by LSTM units, which are well known to be effective for learning and transferring sequence patterns. Moreover, this model has a unique structure in which the output of the convolution neural network layer is linked not only to the input of the initial state of the recurrent neural network layer but also to the input of the multimodal layer, in order to make use of visual information extracted from the image at each recurrent step for generating the corresponding textual caption. Through various comparative experiments using open data sets such as Flickr8k, Flickr30k, and MSCOCO, we demonstrated the proposed multimodal recurrent neural network model has high performance in terms of caption accuracy and model transfer effect.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.2
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• pp.189-196
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• 2005

Recently as map making skills developed and as digital maps prevailed, peoples began to take interest in the realistic 3dimension topography rather than the flat 2 dimension one. The experiment is done by using the topographical information from the digital maps, To analyze the preciseness of this 3dimension topography, analysis of the coordinate-changed standard map image and the location errors of the plane and height from digital values of the map's topography by layers and features, were done. The visual results of locational values differed by every programs of coordinate transformation. Errors of locations also appeared from the methods of correcting the visual sources, when deciding the standard source's datum point. The plan's accuracy of the image data coordinate transformation is about ${\pm}4.1m$. In ground distance, therefore, it is included in the allowed error of the 1:25,000 scale changed map, satisfying the plan's accuracy. Also, by the use of reasonably spaced grid, it satisfied the visual topographical accuracy. Because the 3 dimension topographical map can be produced effectively and rapidly by using various scale's standard map image and the digital map, the further practical use of 3 dimension topographic map made by using the existing topographies and changed maps has high expectations.