• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.13 no.6
• /
• pp.33-43
• /
• 2003

In this paper, we proposed a real-time watermarking algorithm to be combined and to work with a DWT(Discrete Wavelet Transform)-based image compressor. To reduce the amount of computation in selecting the watermarking positions, the proposed algorithm uses a pre-established look-up table for critical values, which was established statistically by computing the correlation according to the energy values of the corresponding wavelet coefficients. That is, watermark is embedded into the coefficients whose values are greater than the critical value in the look-up table which is searched on the basis of the energy values of the corresponding level-1 subband coefficients. Therefore, the proposed algorithm can operate in a real-time because the watermarking process operates in parallel with the compression procession without affecting the operation of the image compression. Also it improved the property of losing the watermark and the efficiency of image compression by watermark inserting, which results from the quantization and Huffman-Coding during the image compression. Visual recognizable patterns such as binary image were used as a watermark The experimental results showed that the proposed algorithm satisfied the properties of robustness and imperceptibility that are the major conditions of watermarking.

• Journal of the Korean Society for information Management
• /
• v.39 no.2
• /
• pp.233-254
• /
• 2022

Link reduction algorithms such as pathfinder network are the widely used methods to overcome problems with the visualization of weighted networks for knowledge domain analysis. This study proposed NetRSQ, an indicator to measure the goodness of fit of a link reduction algorithm for the network visualization. NetRSQ is developed to calculate the fitness of a network based on the rank correlation between the path length and the degree of association between entities. The validity of NetRSQ was investigated with data from previous research which qualitatively evaluated several network generation algorithms. As the primary test result, the higher degree of NetRSQ appeared in the network with better intellectual structures in the quality evaluation of networks built by various methods. The performance of 4 link reduction algorithms was tested in 40 datasets from various domains and compared with NetRSQ. The test shows that there is no specific link reduction algorithm that performs better over others in all cases. Therefore, the NetRSQ can be a useful tool as a basis of reliability to select the most fitting algorithm for the network visualization of intellectual structures.

• Land and Housing Review
• /
• v.14 no.3
• /
• pp.93-106
• /
• 2023

This study attempted to simulate changes in the thermal environment according to the type of apartment complex in Korea using CFD techniques and evaluate the thermal environment by type of apartment. First, apartment complex types in the 2000s and 2010s were referred from previous studies and four types of apartment complex were extracted from. Second, the layout of the apartment complex and temperature changes were analyzed by the direction of wind inflow. Third, a standardized model was created from each type using tower type, plate type, and mixed driving. Last, CFD simulations were performed by setting up the inflow of wind from a total of eight directions. The temperature was relatively low in the type consisting of only the tower type and the type of placing the tower type in the center of the complex, regardless of the direction of the wind. It was due to the good inflow of wind from these types to the inside of the complex. It can be interpreted because wind flows easily into the complex in these types. The findings showed that wind flow and resulting temperature distribution patterns differed depending on the building type and complex layout type, confirming the need for careful consideration of the complex layout in the early design stage. The results are expected to be used as basic data for creating a sustainable residential environment in the early design stage of apartment complexes in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.27-30
• /
• 2022

The plasma process, which has many advantages in terms of efficiency and environment compared to conventional process methods, is widely used in semiconductor manufacturing. Plasma Sheath is a dark region observed between the plasma bulk and the chamber wall surrounding it or the electrode. The Plasma Sheath Monitoring Sensor (PSMS) measures the difference in voltage between the plasma and the electrode and the RF power applied to the electrode in real time. The PSMS data, therefore, are expected to have a high correlation with the state of plasma in the plasma chamber. In this study, a model for predicting the state of nitrogen ions in the plasma chamber is training by a deep learning machine learning techniques using PSMS data. For the data used in the study, PSMS data measured in an experiment with different power and pressure settings were used as training data, and the ratio, flux, and density of nitrogen ions measured in plasma bulk and Si substrate were used as labels. The results of this study are expected to be the basis of artificial intelligence technology for the optimization of plasma processes and real-time precise control in the future.

• Journal of the Korean Geotechnical Society
• /
• v.22 no.12
• /
• pp.67-76
• /
• 2006

The reasonable assessment of the shear stiffness of a dredged soft ground and soft clay is difficult due to the soil disturbance. This study addresses the development and application of a new in-situ shear wave measuring apparatus (field velocity probe: FVP), which overcomes several of the limitations of conventional methods. Design concerns of this new apparatus include the disturbance of soils, cross-talking between transducers, electromagnetic coupling between cables, self acoustic insulation, the constant travel distance of S-wave, the rotation of the transducer, directly transmitted wave through a frame from transducer to transducer, and protection of the transducer and the cable. These concerns are effectively eliminated by continuous improvements through performing field and laboratory tests. The shear wave velocity of the FVP is simply calculated, without any inversion process, by using the travel distance and the first arrival time. The developed FVP Is tested in soil up to 30m in depth. The experimental results show that the FVP can produce every detailed shear wave velocity profiles in sand and clay layers. In addition, the shear wave velocity at the tested site correlates well with the cone tip resistance. This study suggests that the FVP may be an effective technique for measuring the shear wave velocity in the field to assess dynamic soil properties in soft ground.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.3
• /
• pp.145-151
• /
• 2023

3D-CNN is one of the deep learning techniques for learning time series data. Such three-dimensional learning can generate many parameters, so that high-performance machine learning is required or can have a large impact on the learning rate. When learning dynamic hand-gestures in spatiotemporal domain, it is necessary for the improvement of the efficiency of dynamic hand-gesture learning with 3D-CNN to find the optimal conditions of input video data by analyzing the learning accuracy according to the spatiotemporal change of input video data without structural change of the 3D-CNN model. First, the time ratio between dynamic hand-gesture actions is adjusted by setting the learning interval of image frames in the dynamic hand-gesture video data. Second, through 2D cross-correlation analysis between classes, similarity between image frames of input video data is measured and normalized to obtain an average value between frames and analyze learning accuracy. Based on this analysis, this work proposed two methods to effectively select input video data for 3D-CNN deep learning of dynamic hand-gestures. Experimental results showed that the learning interval of image data frames and the similarity of image frames between classes can affect the accuracy of the learning model.

• The Journal of Bigdata
• /
• v.8 no.1
• /
• pp.157-165
• /
• 2023

Seafood is a major source of protein in many countries and its consumption is increasing. In Korea, consumption of seafood is increasing, but self-sufficiency rate is decreasing, and the importance of safety management is increasing as the amount of imported seafood increases. There are hundreds of species of aquatic products imported into Korea from over 110 countries, and there is a limit to relying only on the experience of inspectors for safety management of imported aquatic products. Based on the data, a model that can predict the customs inspection results of imported aquatic products is developed, and a machine learning classification model that determines the non-conformity of aquatic products when an import declaration is submitted is created. As a result of customs inspection of imported marine products, the nonconformity rate is less than 1%, which is very low imbalanced data. Therefore, a sampling method that can complement these characteristics was comparatively studied, and a preprocessing method that can interpret the classification result was applied. Among various machine learning-based classification models, Random Forest and XGBoost showed good performance. The model that predicts both compliance and non-conformance well as a result of the clearance inspection is the basic random forest model to which ADASYN and one-hot encoding are applied, and has an accuracy of 99.88%, precision of 99.87%, recall of 99.89%, and AUC of 99.88%. XGBoost is the most stable model with all indicators exceeding 90% regardless of oversampling and encoding type.

• Journal of Industrial Convergence
• /
• v.21 no.8
• /
• pp.75-86
• /
• 2023

The purpose of this study was to provide basic data to increase happiness by verifying the mediating effect of career identity in the relationship between community consciousness, civic consciousness, career identity and happiness of high school students. Data analysis used data from the '2020 Generation Z Teenage Values Survey' conducted by the Korea Youth Policy Institute. Among the survey subjects, 2,959 out of 3,037 high school students who met the purpose of this study, excluding missing, were sampled and analyzed using the SPSS WIN 25.0 program. The analysis method used frequency analysis, descriptive statistical analysis, correlation analysis, and Bayron and Kenny's analysis methods to verify the mediating effect, and applied Sobel test techniques to analyze indirect effects and significance. The results of the study showed that, first, high school students' sense of community and citizenship increased their happiness. Second, career identity had a partial mediating effect in the relationship between community consciousness and happiness. Third, it shows a partial mediating effect of career identity in the relationship between citizenship and happiness. Based on this, this study is meaningful in that it suggests policy alternatives and practical programs to promote high school students' happiness.

• Journal of the Korean Society of Radiology
• /
• v.17 no.7
• /
• pp.1067-1073
• /
• 2023

Breast cancer is one of the top three most common cancers in modern women, and the incidence rate is increasing rapidly. Breast cancer has a high family history and a mortality rate of about 15%, making it a high-risk group. Therefore, breast cancer needs constant management after an early examination. Among the various equipment that can diagnose cancer, ultrasound has the advantage of low risk and being able to diagnose in real time. In addition, breast ultrasound will be more useful because Asian women's breasts are denser and less sensitive. However, the results of ultrasound examinations vary greatly depending on the technology of the examiner. To compensate for this, we intend to incorporate motion tracking technology. Motion tracking is a technology that specifies and analyzes a location according to the movement of an object in a three-dimensional space. Therefore, real-time control is possible, and complex and fast movements can be recorded in real time. We would like to present the production of an ultrasound examination guide using these advantages.

• Journal of the Korean Applied Science and Technology
• /
• v.40 no.5
• /
• pp.1149-1162
• /
• 2023

The purpose of this study is to study the mediating verification of self-efficacy in the effect of self-management of hair beauty experts on job performance and beauty continuity intention. The subjects of the study were surveyed and used for analysis of 256 beauty experts working as hair beauty experts in Seoul and Gyeonggi Province. The SPSS 28.0 and AMOS 28.0 statistical package programs were used for the analysis method, and descriptive statistics of mean, standard deviation, kurtosis, skewness, confirmatory factor analysis and reliability analysis, correlation, and mediating effect analysis were analyzed using bootstrapping techniques. The results of the study showed that the self-management of hair beauty experts had a significant positive (+) effect on self-efficacy, job performance, and intention to continue beauty. The self-efficacy of hair beauty experts had a significant (+) effect on job performance and beauty continuity intention. It was confirmed that there was a mediating effect of self-efficacy in the relationship between self-management and job performance of hair beauty experts. The statistical significance level is p<.It was analyzed by setting it at the level of 05.