• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1104-1109
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• 2019

Business utilization of holograms is widely used as a similar hologram. The use of holograms has been proposed in many cases. In this paper, we present an outline of similar holograms using up to 3 or 4 facets, and express the similar holograms using the results produced by 3D modeling for a building from dealing with the representation of buildings from hololens to pseudo-hologram by using 3D modeling results. In addition, to reflect the real image of the disadvantage of modeling, we propose a method to enhance the 3D expression of the object by reflecting the actual building surface on the 3D model through photographing. Virtual building seen by the human eye can be virtually shown in space through a hologram among various methods shown in a virtual space such as AR / VR / MR. Through this study, it will be possible to express holograms of various materials such as buildings or cultural properties with enhanced realism.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.55-62
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• 2019

We examined the Audit Quality on the Socially Responsible Investment(SRI) Corporate. We used 1,497 sample data from 2014 to 2016. In short, the result of this paper's is as followed. Socially Responsible Investment(SRI) has a positive relevance with Audit Quality. Socially Responsible Investment(SRI) has a positive relevance with Audit Fee, Audit Time and Audit Size specifically. Therefore we can support that a firm has a high level of Socially Responsible Investment(SRI) will have the better the Audit Quality according to this study. This study contributes as follow. We can verify that the more Socially Responsible Investment(SRI) the better Quality of Accounting Information. We expect that this study can be helped positive image enhancement of Socially Responsible Investment(SRI) Corporate. So we hope that our paper can contribute sound capital market's development.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.403-413
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• 2021

This paper emphasizes the effect of using poetry in the University General English education and suggests the teaching method of English education with a Frost's poem, "Out, Out- ." These days, learner-centered English education and integrative study of four linguistic functions, reading, listening, speaking and writing are considered important in the University General English class. Poetry is very effective text for the education purposes. Poetry techniques like a visual image, rhythm, rhyme, or repetition are actually mnemonics and strongly connected to the enhancement of memory and oral linguistic function. This paper suggests the specific education methods in the poetry selection, pre-reading step, reading step and after- reading step with concrete examples of "Out, Out-." These education methods through the 'oral text' can be a good and sustainable model for learner-centered education.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.180-186
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• 2022

Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.110-117
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• 2023

Reconstructing underwater geometry in real time with forward-looking sonar is critical for applications such as localization, mapping, and path planning. Geometrical data must be repeatedly calculated and overwritten in real time because the reliability of the acoustic data is affected by various factors. Moreover, scattering of signal data during the coordinate conversion process may lead to geometrical errors, which lowers the accuracy of the information obtained by the sensor system. In this study, we propose a three-step data processing method with low computational cost for real-time operation. First, the number of data points to be interpolated is determined with respect to the distance between each point and the size of the data grid in a Cartesian coordinate system. Then, the data are processed with a nonlinear interpolation so that they exhibit linear properties in the coordinate system. Finally, the data are transformed based on variations in the position and orientation of the sonar over time. The results of an evaluation of our proposed approach in a simulation show that the nonlinear interpolation operation constructed a continuous underwater geometry dataset with low geometrical error.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.701-720
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• 2023

Aerial objects are more challenging to segment than normal objects, which are usually smaller and have less textural detail. In the process of segmentation, target objects are easily omitted and misdetected, which is problematic. To alleviate these issues, we propose local aggregation feature pyramid networks (LAFPNs) and pyramid integrated context modules (PICMs) for aerial object segmentation. First, using an LAFPN, while strengthening the deep features, the extent to which low-level features interfere with high-level features is reduced, and numerous dense and small aerial targets are prevented from being mistakenly detected as a whole. Second, the PICM uses global information to guide local features, which enhances the network's comprehensive understanding of an entire image and reduces the missed detection of small aerial objects due to insufficient texture information. We evaluate our network with the MS COCO dataset using three categories: airplanes, birds, and kites. Compared with Mask R-CNN, our network achieves performance improvements of 1.7%, 4.9%, and 7.7% in terms of the AP metrics for the three categories. Without pretraining or any postprocessing, the segmentation performance of our network for aerial objects is superior to that of several recent methods based on classic algorithms.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.61-71
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• 2009

Vehicle license plate is the only way to check the registrated information of a vehicle. Many works have been devoted to the vision system of recognizing the license plate, which has been widely used to control an illegal parking. However, it is difficult to correctly segment characters on the license plate since an illumination is affected by a weather change and a neighboring obstacles. This paper proposes a robust method of segmenting the character of the license plate on irregular illumination condition. The proposed method enhance the contrast of license plate images using the Chi-Square probability density function. For segmenting characters on the license plate, binary images with the high quality are gained by applying the adaptive threshold. Preprocessing and labeling algorithm are used to eliminate noises existing during the whole segmentation process. Finally, profiling method is applied to segment characters on license plate from binary images.

• Analytical Science and Technology
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• v.20 no.2
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• pp.155-163
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• 2007

Porosity paper evidence is encountered in case of forgery, kidnapping, fraud and terrorist activity. The present study was designed to evaluate the effect of three chemical reagents (Ninhydrin, 1,8-diazafluoren-9-one (DFO), Iodine fuming) to the quality of developed latent fingerprints on porosity printing papers and newspaper. In case of printing papers, print quality was better with Iodine fuming method than Ninhydrin and DFO treatment to developing latent fingerprints. Developing latent fingerprint on newspapers was achieved with Iodine fuming processing. The processing of Iodine fuming followed by DFO and by using blue light (orange red filter) exhibited better results with Iodine fuming. Enhancement of latent fingerprint detection image using Digital Imaging System was achieved.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.535-540
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• 2006

This paper presented an effective strategy to extract the buildings and to reconstruct 3-D buildings using high-resolution multispectral stereo satellite images. Proposed scheme contained three major steps: building enhancement and segmentation using both BDT (Background Discriminant Transformation) and ISODATA algorithm, conjugate building identification using the object matching with Hausdorff distance and color indexing, and 3-D building reconstruction using photogrammetric techniques. IKONOS multispectral stereo images were used to evaluate the scheme. As a result, the BDT technique was verified as an effective tool for enhancing building areas since BDT suppressed the dominance of background to enhance the building as a non-background. In building recognition, color information itself was not enough to identify the conjugate building pairs since most buildings are composed of similar materials such as concrete. When both Hausdorff distance for edge information and color indexing for color information were combined, most segmented buildings in the stereo images were correctly identified. Finally, 3-D building models were successfully generated using the space intersection by the forward RFM (Rational Function Model).

• Smart Structures and Systems
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• v.32 no.3
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• pp.135-151
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• 2023

Using 3D asphalt pavement surface data, a deep and multiscale network named CrackNet-M is proposed in this paper for pixel-level crack detection for improvements in both accuracy and robustness. The CrackNet-M consists of four function-specific architectural modules: a central branch net (CBN), a crack map enhancement (CME) module, three pooling feature pyramids (PFP), and an output layer. The CBN maintains crack boundaries using no pooling reductions throughout all convolutional layers. The CME applies a pooling layer to enhance potential thin cracks for better continuity, consuming no data loss and attenuation when working jointly with CBN. The PFP modules implement direct down-sampling and pyramidal up-sampling with multiscale contexts specifically for the detection of thick cracks and exclusion of non-crack patterns. Finally, the output layer is optimized with a skip layer supervision technique proposed to further improve the network performance. Compared with traditional supervisions, the skip layer supervision brings about not only significant performance gains with respect to both accuracy and robustness but a faster convergence rate. CrackNet-M was trained on a total of 2,500 pixel-wise annotated 3D pavement images and finely scaled with another 200 images with full considerations on accuracy and efficiency. CrackNet-M can potentially achieve crack detection in real-time with a processing speed of 40 ms/image. The experimental results on 500 testing images demonstrate that CrackNet-M can effectively detect both thick and thin cracks from various pavement surfaces with a high level of Precision (94.28%), Recall (93.89%), and F-measure (94.04%). In addition, the proposed CrackNet-M compares favorably to other well-developed networks with respect to the detection of thin cracks as well as the removal of shoulder drop-offs.