• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.187-193
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• 2021

In this paper, we propose an image watermarking technique that effectively hides confidential data in the LSB of image pixels by utilizing the characteristics of the image. In the proposed technique, the image is precisely divided into boundary surface and normal region other than the boundary surface and performs different processing. The boundary surface existing in the image is created by meeting different regions and contains important information of the image. One bit of confidential data is concealed in the LSB of the pixel at the boundary surface to preserve the characteristics of the boundary surface. In normal region other than the boundary surface, the pixel values are similar, and the change with the adjacent pixel values is smooth. Based on this property, even if the 2 bits of confidential data are hidden in the lower 2 bits of the pixel in the normal region, the difference cannot be visually distinguished. When confidential data is concealed in an image as described above, the amount of confidential data concealed in an image can be increased while maintaining excellent image quality. Concealing confidential data by applying the proposed method increases the amount of confidential data concealed by up to 84.6% compared to the existing method. The proposed technique can be effectively used for commercial image watermarking that hides copyright information.

• Journal of Industrial Convergence
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• v.20 no.3
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• pp.33-40
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• 2022

Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.

• Smart Media Journal
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• v.4 no.3
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• pp.16-23
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• 2015

As the IT technology advances, data processing system is required to handle and process large amounts of data. However, the existing On-Disk system has limit to process data which increase rapidly. For that reason, the In-Memory system is being used which saves and manages data on the fast memory not saving data into hard disk. Although it has fast processing capability, it is necessary to use the fault tolerance techniques in the In-Memory system because it has a risk of data loss due to volatility which is one of the memory characteristics. These fault tolerance techniques lead to performance degradation of In-Memory system. In this paper, we classify the data into Hot and Cold data in consideration of the data usage characteristics in the In-Memory system and propose compound backup technique to ensure data persistence. The proposed technique increases the persistence and improves performance degradation.

• Spatial Information Research
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• v.19 no.2
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• pp.19-28
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• 2011

Three dimensional modeling for seafloor topography is essential to monitoring displacements in underwater structures as well as all sorts of disasters along the shore. MBES is a system that is capable of high-density water depth measurement for seafloor topography and is in broad uses for gathering 3D data and detecting displacements. MBES data, however, contain random errors that take place in the equipment offset and surveying process and require systematic researches on the correction of wrong depth measurements. Thus this study set out to propose a post-processing technique to eliminate an array of random errors taking place after equipment offset correction and basic noise correction in the MBES system and analyze its applicability to seafloor topography modeling by applying it to the subject area.

• Applied Biological Chemistry
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• v.41 no.2
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• pp.160-165
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• 1998

Current discriminating technique of rice variety is known to be not objective till this time because of depending on naked eye of well trained inspector. DNA finger print method based on genetic character of rice has been indicated inappropriate for on-site application, because the method need much labor and skilled expert. The purpose of this study was to develops the identification technique of polished rice varieties using CCD camera images. To minimize the noise of the captured image, thresholding and median filtering were carried out, and edge was extracted from the image data. Image data after pretreatment of normalize and FFT(fast fourier transform) were used for library model and feedforward backpropagation neural network model. Image processing technique using CCD camera could discriminate the variety of rice with high accuracy in case of quite different rice of shape, but the accuracy was reached at 85% in the similar shape of rice.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.5
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• pp.798-807
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• 2021

The directivity characteristics of acoustic transducers for conventional single-beam echo sounders considerably limit the detection of fish-size information in acoustic field surveys. To overcome this limitation, using the split-aperture technique to estimate the direction of arrival of single-echo signals from individual fish distributed within the sound beam represents the most reliable method for fish-size classification. For this purpose, we design and develop a split-beam data acquisition and processing system to obtain fish-size information in conjunction with a 50-kHz single-beam echo sounder. This split-beam data acquisition and processing system consists of a notebook PC, a field-programmable gate array board, an external single-transmitter module with a matching network, and four-channel receiver modules operating at a frequency of 50-kHz. The functionality of the developed split-beam data processor is tested and evaluated. Acoustic measurements in an experimental water tank showed that the developed data acquisition and processing system can be used as a fish-sizing echo sounder to estimate the size distribution of individual fish, although an external single-transmitter module with a matching network is required.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.83-93
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• 1998

Three dimensional data acquisition system based on the structured light is developed in this work. The system is composed of a CCD camera, slide projector, and various image processing programs. Calibration procedures and several image processing steps which are necessary to get the rnage data are described. A new grid labeling technique and a grid pattern are devised to improve the accuracy of th eobtained data. Preliminary experimental result shows that the developed system may be used as a simple and cheap 3D data acquisition system. Severla suggestions are included for further research.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.181-185
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• 1990

In design of the plastic injection mold, most of drawings are composed of basic entities. It is very easy to produce many kinds of drawings by Group Technology. Group Technology is a technique In which part similarities are used to classify parts into part families according to either geometric shape and size or processing requirements. Almost data for the mold are decided during the assembly design. A system which shows a good interfaces between the design stage and producing part exploding Is developed using AutoCAD system and data conversion technique.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.42-53
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• 2020

With the development of social network services, graph structures have been utilized to represent relationships among objects in various applications. Recently, a demand of subgraph matching in real-time graph streams has been increased. Therefore, an efficient approximate Top-k subgraph matching scheme for low latency in real-time graph streams is required. In this paper, we propose an approximate Top-k subgraph matching scheme considering data reuse in graph stream environments. The proposed scheme utilizes the distributed stream processing platform, called Storm to handle a large amount of stream data. We also utilize an existing data reuse scheme to decrease stream processing costs. We propose a distance based summary indexing technique to generate Top-k subgraph matching results. The proposed summary indexing technique costs very low since it only stores distances among vertices that are selected in advance. Finally, we provide k subgraph matching results to users by performing an approximate Top-k matching on the summary indexing. In order to show the superiority of the proposed scheme, we conduct various performance evaluations in diverse real world datasets.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.435-441
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• 2024

In order for the large amount of collected data sets to be used as deep learning training data, sensitive personal information such as resident registration number and disease information must be changed or encrypted to prevent it from being exposed to hackers, and the data must be reconstructed to match the structure of the built deep learning model. Currently, these tasks are performed manually by experts, which takes a lot of time and money. To solve these problems, this paper proposes a technique that can automatically perform data processing tasks to protect personal information during the deep learning process. In the proposed technique, privacy protection tasks are performed based on data generalization and data reconstruction tasks are performed using circular queues. To verify the validity of the proposed technique, it was directly implemented using C language. As a result of the verification, it was confirmed that data generalization was performed normally and data reconstruction suitable for the deep learning model was performed properly.