• Spatial Information Research
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• v.23 no.5
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• pp.1-7
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• 2015

Twitter has the fast propagation and diffusion of information compare to other SNS. Therefore, many researches about detecting real-time event using twitter are progressing. Twitter real-time event detecting system assumes every twitter user as a sensor and analyzes their written tweet in order to detect the event. Researches that are related to this twitter have already obtained good results but confronted the limits because of some problems. Especially, many existing researches are using the method that can trace an event location by using GPS coordinate. However, it can be suggested a definite limitation through the present user's skeptical responses about making personal location information public. Therefore, this paper suggests the method that traces the location information in tweet contents text without using the provided location information from twitter. Associated words were grouped by using the keyword that extracted in tweet contents text. The place that the events have occurred and whether the events have surely occurred are detected by this experiment using this algorithm. Furthermore, this experiment demonstrated the necessity of the suggested methods by showing faster detection compare to the other existing media.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.37-48
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• 2005

The efficiency of power supply circuits such as DC-DC converters and batteries varies on the trend of the power consumption because their efficiencies are not fixed. To analyze the efficiency of power supply circuits, we need the temporal behavior of the power consumption of the loads, which is dependent on the activity factors of the devices during the operation. Since it is not easy to model every detail of those factors, one of the most accurate power consumption analyses of power supply circuits is measurement of a real system, which is expensive and time consuming. In this paper, we introduce an active load emulator for embedded systems which is capable of power measurement, logging, replaying and synthesis. We adopt a pattern recognition technique for data compression in that long-term behaviors of power consumption consist of numbers of repetitions of short-term behaviors, and the number of short-term behaviors is generally limited to a small number. We also devise a heterogeneous structure of active load elements so that low-speed, high-current active load elements and high-speed, low-current active load elements may emulate large amount and fast changing power consumption of digital systems. For the performance evaluation of our load emulator, we demonstrate power measurement and emulation of a hard drive. As an application of our load emulator, it is used for the analysis of a DC-DC converter efficiency and for the verification of a low-power frequency scaling policy for a real-time task.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1021-1023
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• 2013

Currently, aircraft and automobile simulator for training provides a variety of training by making hypothetical situation on a simulator Installed on the ground Currently. And the instructor maximizes the effectiveness of the training by Monitoring training and instructing the required training. When trainees are boarding the aircraft or automobile. The Instructor in the ground is not able to monitoring aircraft, automobile. The assessment of the training is not easy after the end of the training Therefore, it is difficult to provide high quality of education to the students. In this paper, Simulation software is to develop the following. Collecting GPS and real-time information for aircraft, automobile ${\grave{a}}implementing$ 3D simulation. Implementing Current image of the aircraft or automobile in the screen by 3D Real-time monitoring of training situation at the control center utilizing for training saving 3D video files Analysis, evaluation on training After the end of the training.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.1960-1971
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• 1998

The researches and developments to provide multimedia communication services such as Video on Demand(VoDJ), real time video phonc and multipoint vidco conferencing on broadband ISDN environmcnts have been proceeded with activity. Specifications for Vol) services which is worked by Digital Audio-Visual Council(DAVIC) to support detail technologies including total service system that is consist of VoD server. delive[\! networl, and Set-Top Box(STB) had been already finished and ITU-T SG16 also recommended the standards of H.300 series terminal aspects for conversational multimedia services, But the architectures of multimedia tenninals recommended and specified by these organizations do not have an efficient st11lcture to provide all of retrieval, distrihution and conversational service due to a different point of view about multimedia terminals and services. In this paper, we analyzed the recornmendatio!E and the specifications of intemational public and private organizations like lTU-T, DAVIC and ATM forum. As a result of these analysis. we propose an efficient terminal architecture, and then we have designed, lmplemented the multimedia communication terminal for offering VoI) and real- time conversation ,,, functional module test according to the individual commumication service session and confirined the validiry or terminal implemented to be used on broadband ISDK environments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.100-103
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• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.138-154
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• 2008

Geo-special technologies are being adopted in variety fields since the 3rd NGIS plan that was started at 1996. However, the required system or structure to guarantee the up-to-date validity and accuracy of the geospatial data - the most fundamental elements of the technology - was not constructed yet. All the activities related to geospatial data, including topographical map and numerical base map, are all implemented in separate way; from change of geographical objects and features, data gathering, and database construction to distribution, transfer and sharing of these data. The data model that links all the activities are required that enables consistent data-flow and effective and systematic work-flow. In this study, economic data renewal and exchange method was proposed, and benefit-cost analysis was implemented by comparing the conventional work-flow to newly proposed work-flow. The case study was implemented using the model that was adopted in Daegu metropolitan city, and the model was developed by reflecting these results.

• Tuberculosis and Respiratory Diseases
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• v.79 no.2
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• pp.85-90
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• 2016

Background: Lung cancer is the most common cause of cancer related death. Alterations in gene sequence, structure, and expression have an important role in the pathogenesis of lung cancer. Fusion genes and alternative splicing of cancer-related genes have the potential to be oncogenic. In the current study, we performed RNA-sequencing (RNA-seq) to investigate potential fusion genes and alternative splicing in non-small cell lung cancer. Methods: RNA was isolated from lung tissues obtained from 86 subjects with lung cancer. The RNA samples from lung cancer and normal tissues were processed with RNA-seq using the HiSeq 2000 system. Fusion genes were evaluated using Defuse and ChimeraScan. Candidate fusion transcripts were validated by Sanger sequencing. Alternative splicing was analyzed using multivariate analysis of transcript sequencing and validated using quantitative real time polymerase chain reaction. Results: RNA-seq data identified oncogenic fusion genes EML4-ALK and SLC34A2-ROS1 in three of 86 normal-cancer paired samples. Nine distinct fusion transcripts were selected using DeFuse and ChimeraScan; of which, four fusion transcripts were validated by Sanger sequencing. In 33 squamous cell carcinoma, 29 tumor specific skipped exon events and six mutually exclusive exon events were identified. ITGB4 and PYCR1 were top genes that showed significant tumor specific splice variants. Conclusion: In conclusion, RNA-seq data identified novel potential fusion transcripts and splice variants. Further evaluation of their functional significance in the pathogenesis of lung cancer is required.

• Journal of Korean Society on Water Environment
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• v.26 no.2
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• pp.215-224
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• 2010

This study was carried out to estimate effects of sediment reduction with net type sediment settling pond at highland agricultural areas. Flow and sediment monitoring system with rainfall gauge were installed at the study area for real-time monitoring and analysis. It was found that amount and intensity of rainfall events strongly affect sediment yield from the study area. With net type sediment settling pond, it was expected that approximately 61% of sediment could be removed. The correlation between heavy metals and SS were analyzed in this study. $R^2$ values were 0.644, 0.876, 0.945, and 0.928 for Fe, Mn, Al, and Si, respectively. This results indicate that heavy metals also could be removed with net type sediment settling pond. As shown in this study, the sediment settling pond will be an efficient sediment reduction facility at highland agricultural areas. For maximum reduction efficiencies of sediment and other pollutants at agricultural fields, simplified sediment settling pond should be designed and implemented.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.297-302
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• 2012

In this paper, we present a object detection and tracking method based on image context analysis. It is robust from the image variations such as complicated background, dynamic movement of the object. Image context analysis is carried out using the hybrid network of k-means and RBF. The proposed object detection employs context-driven adaptive Bayesian framework to relive the effect due to uneven object images. The proposed method used feature vector generator using 2D Haar wavelet transform and the Bayesian discriminant method in order to enhance the speed of learning. The system took less time to learn, and learning in a wide variety of data showed consistent results. After we developed the proposed method was applied to real-world environment. As a result, in the case of the object to detect pass outside expected area or other changes in the uncertain reaction showed that stable. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• The Korean Journal of Physiology and Pharmacology
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• v.24 no.1
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• pp.89-99
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• 2020

Although microscopic analysis of tissue slides has been the basis for disease diagnosis for decades, intra- and inter-observer variabilities remain issues to be resolved. The recent introduction of digital scanners has allowed for using deep learning in the analysis of tissue images because many whole slide images (WSIs) are accessible to researchers. In the present study, we investigated the possibility of a deep learning-based, fully automated, computer-aided diagnosis system with WSIs from a stomach adenocarcinoma dataset. Three different convolutional neural network architectures were tested to determine the better architecture for tissue classifier. Each network was trained to classify small tissue patches into normal or tumor. Based on the patch-level classification, tumor probability heatmaps can be overlaid on tissue images. We observed three different tissue patterns, including clear normal, clear tumor and ambiguous cases. We suggest that longer inspection time can be assigned to ambiguous cases compared to clear normal cases, increasing the accuracy and efficiency of histopathologic diagnosis by pre-evaluating the status of the WSIs. When the classifier was tested with completely different WSI dataset, the performance was not optimal because of the different tissue preparation quality. By including a small amount of data from the new dataset for training, the performance for the new dataset was much enhanced. These results indicated that WSI dataset should include tissues prepared from many different preparation conditions to construct a generalized tissue classifier. Thus, multi-national/multi-center dataset should be built for the application of deep learning in the real world medical practice.