• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.177-183
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• 2020

Steganography uses digital images as a medium for sending secret messages over insecure networks. There is also a least significant bit(LSB) that is a popular method of embedding secret messages in digital images. The goal of steganography is to securely and flawlessly transmit secret messages using stego media over a communication channel. There is a need for a method to improve resistance to reduce the risk of exposure to third parties. To safely hide secret messages, I propose new algorithms that go through crossing, encryption, chaos and concealment steps. After separating Hangul syllables into choseong, jungseong and jongseong, the bitwised message information is encrypted. After applying the logistic map, bitwised information is reconstructed using the position of the chaotic sequence. The secret message is inserted into the randomly selected RGB channel. PSNR and SSIM were used to confirm the effectiveness of the applied results. It was confirmed as 44.392(dB) and 0.9884, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9B
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• pp.1259-1265
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• 2010

Recently, on-line social network has been increasing according to development of internet. The most representative service is blog. A Blog is a type of personal web site, usually maintained by an individual with regular entries of commentary. These blogs are related to each other, and it is called Blog Network in this paper. In a blog network, posts in a blog can be diffused to other blogs. Analyzing information diffusion in a blog world is a very useful research issue, which can be used for predicting information diffusion, abnormally detection, marketing, and revitalizing the blog world. Existing studies on network analysis have no consideration for the passage of time and these approaches can only measure network activity for a node by the number of direct connections that a given node has. As one solution, this paper suggests the new method of measuring the blog network activity using logistic curve model and Cosine-similarity in key words by the Map/Reduce programming model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.898-903
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• 2020

In this paper, we propose an indoor logistic tracking system that identifies the location and inventory of the logistics in the room based on fingerprints. Through this, we constructed the actual infrastructure of the logistics center and designed and implemented the logistics management system. The proposed system collects the signal strength through the location terminal and generates the signal map to locate the goods. The location terminal is composed of a UHF RFID reader and a wireless LAN card, reads the peripheral RFID signal and the signal of the wireless AP, and transmits it to the web server. The web server processes the signal received from the location terminal and stores it in the database, and the user uses the data to produce the signal map. The proposed system combines UHF RFID with existing fingerprinting method to improve performance in the environment of querying multiple objects.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.107-115
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• 2024

This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.

• Journal of Environmental Impact Assessment
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• v.22 no.3
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• pp.231-240
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• 2013

The Purpose of this research was to propose positioning strategies of urban park (UP) based on the assessment of location characteristics at cheongju city. To do that, this research found out urban park service area (UPSA) using GIS network analysis and built socio-economic attribute database, UP map, and other public service thematic maps such as public transportation, education, child-care, and convenience services. And this research analyzed spatial and attribute data using Pearson's correlation analysis, multiple linear regression, and binary logistic regression methods. As a result of this analysis, 1) the nearer neighborhood park and children's park, the higher land price and assumption income level (AIL). 2) children's parks were closed to living convenience facilities such as bank, hospital, and convenience store. 3) land price, AIL, population, and other public services level (PSL) in UPSA were higher than that of non-UPSA. 4) The higher land price, AIL, population, and other PSL, the higher urban park service level. The results of this research may contribute to resolve the regional UP unbalance and to improve UP service level as public service.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.713-723
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• 2019

Due to the climate change and various rainfall pattern, it is difficult to estimate a rainfall criterion which cause inundation for urban drainage districts. It is necessary to examine the result of inundation analysis by considering the detailed topography of the watershed, drainage system, and various rainfall scenarios. In this study, various rainfall scenarios were considered with the probabilistic rainfall and Huff's time distribution method in order to identify the rainfall characteristics affecting the inundation of the Hyoja drainage basin. Flood analysis was performed with SWMM and two-dimensional inundation analysis model and the parameters of SWMM were optimized with flood trace map and GA (Genetic Algorithm). By linking SWMM and two-dimensional flood analysis model, the fitness ratio between the existing flood trace and simulated inundation map turned out to be 73.6 %. The occurrence of inundation according to each rainfall scenario was identified, and the rainfall criterion could be estimated through the logistic regression method. By reflecting the results of one/two dimensional flood analysis, and AWS/ASOS data during 2010~2018, the rainfall criteria for inundation occurrence were estimated as 72.04 mm, 146.83 mm, 203.06 mm in 1, 2 and 3 hr of rainfall duration repectively. The rainfall criterion could be re-estimated through input of continuously observed rainfall data. The methodology presented in this study is expected to provide a quantitative rainfall criterion for urban drainage area, and the basic data for flood warning and evacuation plan.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.507-514
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• 2018

TSI (TPI-Slope Index) which is the combination of TPI (Topographic Position Index) and slope was newly proposed for landslide and applied to a landslide susceptibility model. To do this, we first compared the TPIs with various scale factors and found that TPI350 was the best fit for the study area. TPI350 was combined with slope to create TSI. TSI was evaluated using logistic regression. The evaluation showed that TSI can be used as a landslide factor. Then a logistic regression model was developed to assess the landslide susceptibility by adding other topographic factors, geological factors, and forestial factors. For this, landslide-related factors that can be extracted from DEM (Digital Elevation Model), soil map, and forest type map were collected. We checked these factors and excluded those that were highly correlated with other factors or not significant. After these processes, 8 factors of TSI, elevation, slope length, slope aspect, effective soil depth, tree age, tree density, and tree type were selected to be entered into the regression analysis as independent variables. Three models through three variable selection methods of forward selection, backward elimination, and enter method were built and evaluated. Selected variables in the three models were slightly different, but in common, effective soil depth, tree density, and TSI was most significant.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.1
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• pp.94-105
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• 2016

This study was carried out to assess the distributional probability for Evergreen Broad-Leaved Forests(EBLFs) using the field data and digital climate data that were occurred during the period of 1980 to 2010. For the validation of logistic regression model, the probabilistic value ranged from 33 to 84%, especially the probabilistic value of growing distribution becomes lower patterns with higher altitude. In addition, it has been estimated that the probabilistic value of growing distribution is the highest with 63~83% among the regional units in temperate/warm-temperate forests.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.479-485
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• 2005

Recently the spread which RFID technology is overcomes the limit of existing recognition technology, it is forecast with the fact that it will bring a new renovation at the business and the industrial all over. Specially the case RFID technology of Port Logistic Industry will be applied it is forecast with the fact that it will bring a many effect. The government leads introduces a RFID technology of Port Logistic Industry through the various demonstration business. But it is many with the research insufficient the depression against an actuality improvement subject and the depression of technical know-how strategy and it is difficult it is undergoing. In order to solve this problems, we propose an introduction of technical know-how Road Map that we select ranking with Existing literature investigation and the present business demand anaylsis. In the future this research it it forecast in future the successful guide line to the RFID technology introduction of Port Logistic Industry will become.

• Korean Journal of Radiology
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• v.24 no.5
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• pp.395-405
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• 2023

Objective: This study aimed to develop and validate models using radiomics features on a native T1 map from cardiac magnetic resonance (CMR) to predict left ventricular reverse remodeling (LVRR) in patients with nonischemic dilated cardiomyopathy (NIDCM). Materials and Methods: Data from 274 patients with NIDCM who underwent CMR imaging with T1 mapping at Severance Hospital between April 2012 and December 2018 were retrospectively reviewed. Radiomic features were extracted from the native T1 maps. LVRR was determined using echocardiography performed ≥ 180 days after the CMR. The radiomics score was generated using the least absolute shrinkage and selection operator logistic regression models. Clinical, clinical + late gadolinium enhancement (LGE), clinical + radiomics, and clinical + LGE + radiomics models were built using a logistic regression method to predict LVRR. For internal validation of the result, bootstrap validation with 1000 resampling iterations was performed, and the optimism-corrected area under the receiver operating characteristic curve (AUC) with 95% confidence interval (CI) was computed. Model performance was compared using AUC with the DeLong test and bootstrap. Results: Among 274 patients, 123 (44.9%) were classified as LVRR-positive and 151 (55.1%) as LVRR-negative. The optimism-corrected AUC of the radiomics model in internal validation with bootstrapping was 0.753 (95% CI, 0.698-0.813). The clinical + radiomics model revealed a higher optimism-corrected AUC than that of the clinical + LGE model (0.794 vs. 0.716; difference, 0.078 [99% CI, 0.003-0.151]). The clinical + LGE + radiomics model significantly improved the prediction of LVRR compared with the clinical + LGE model (optimism-corrected AUC of 0.811 vs. 0.716; difference, 0.095 [99% CI, 0.022-0.139]). Conclusion: The radiomic characteristics extracted from a non-enhanced T1 map may improve the prediction of LVRR and offer added value over traditional LGE in patients with NIDCM. Additional external validation research is required.