• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1236-1241
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• 2016

Cancer has been the most frequent in Korea, and pathogenesis and progression of cancer have been known to be occurred through various causes and stages. Recently, the research of chromosomal and genetic disorder and the research about prognostic factor to predict occurrence, recurrence and progress of chromosomal and genetic disorder have been performed actively. In this paper, we analyzed DNA methylation data downloaded from TCGA (The Cancer Genome Atlas), open database, to research bladder cancer which is the most frequent among urinary system cancers. Using three level of methylation data which had the most preprocessing, 59 candidate CpG island were extracted from 480,000 CpG island, and then we analyzed extracted CpG island applying data mining technique. As a result, cg12840719 CpG island were analyzed significant, and in Cox's regression we can find the CpG island with high relative risk in comparison with other CpG island. Shown in the result of classification analysis, the CpG island which have high correlation with bladder cancer are cg03146993, cg07323648, cg12840719, cg14676825 and classification accuracy is about 76%. Also we found out that positive predictive value, the probability which predicts cancer in case of cancer was 72.4%. Through the verification of candidate CpG island from the result, we can utilize this method for diagnosing and treating cancer.

• Journal of Korean Society on Water Environment
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• v.34 no.4
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• pp.382-390
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• 2018

In this study, the LIDMOD3 was developed to design and evaluate low impact development (LIDMOD). In the same fashion, the LIDMOD3 employs a curve number (NRCS-CN) method to estimate the surface runoff, infiltration and event mean concentration as applicable to pollutant loads which are based on a daily time step. In these terms, the LIDMOD3 can consider a hydrologic soil group for each land use type LID-BMP, and the applied removal efficiency of the surface runoff and pollutant loads by virtue of the stored capacity, which was calculated by analyzing the recorded water balance. As a result of Model development, the LIDMOD3 is based on an Excel spread sheet and consists of 8 sheets of information data, including: General information, Annual precipitation, Land use, Drainage area, LID-BMPs, Cals-cap, Parameters, and the Results. In addition, the LIDMOD3 can estimate the annual hydrology and annual pollutant loads including surface runoff and infiltration, the LID efficiency of the estimated surface runoff for a design rainfall event, and an analysis of the peak flow and time to peak using a unit hydrolograph for pre-development, post-development without LID, and as calculated with LID. As a result of the model application as applied to an apartment, the LIDMOD3 can estimate LID-BMPs considering a well spatical distributed hydroloic soil group as realized on land use and with the LID-BMPs. Essentially, the LIDMOD3 is a screen level and simple model which is easy to use because it is an Excel based model, as are most parameters in the database. This system can be expected to be widely used at the LID site to collect data within various programmable model parameters for the processing of a detail LID model simulation.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.75-82
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• 2002

The information system fields of spatial applications have rapidly grown during the last decade in Korea. Spatial data has been produced for a variety of systems without common standards until national GIS Committee defined the data exchange formats among spatial databases in the middle of 1990's. It aimed at promoting data sharing between the different systems in similar application fields. However, a considerable number of databases built prior to the introduction of the standards are not yet standard compliant but still play the roles of the main producers/consumers in the data collection field such as early developed huge AM/FM systems maintained by governmental organizations. The strong autonomy of these databases keeps their own data models, formats and descriptions from being standardized, which leads the sharing to a more difficult stage. Sharing is another way of data acquisition with least efforts and time away from direct collection. A data clearinghouse is the core module which directs users to the relevant data resources. The contents of datasets should be described with predefined metadata standards for precise indexing. Moreover, a number of technical problems have to be resolved for the common use of data between heterogeneous spatial database systems. However, the technical issues can be covered by the present information technologies. The difficulties persist in the political/institutional issues. Institutional issues are derived from the diverse sources such as political background, governmental policies, related laws and/or regulations. The paper will firstly make an analysis of current situation in terms of Korean policies, laws and regulations, secondly abstract the institutional issues from the situation analysis, lastly present guidelines for promoting spatial data sharing in Korea.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.629-634
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• 2009

In real-time system application, the feature extraction and scoring algorithm for classification of the passive sonar target has the following problems: it requires an accurate and efficient feature extraction method because it is very difficult to distinguish the features of the propeller shaft rate (PSR) and the blade rate (BR) from the frequency spectrum in real-time, it requires a robust and effective feature scoring method because the classification database (DB) composed of extracted features is noised and incomplete, and further, it requires an easy design procedure in terms of structures and parameters. To solve these problems, an intelligent feature extraction and scoring algorithm using the evolution strategy (ES) and the fuzzy theory is proposed here. To verify the performance of the proposed algorithm, a passive sonar target classification is performed in real-time. Simulation results show that the proposed algorithm effectively solves sonar classification problems in real-time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.5
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• pp.430-437
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• 2021

In this paper, we propose a robust face recognition method against soft errors with a deep convolutional generative adversarial network(DCGAN) based compensation method by a cross-layer approach. When soft-errors occur in block data of JPEG files, these blocks can be decoded inappropriately. In previous results, these blocks have been replaced using a mean face, thereby improving recognition ratio to a certain degree. This paper uses a DCGAN-based compensation approach to extend the previous results. When soft errors are detected in an embedded system layer using parity bit checkers, they are compensated in the application layer using compensated block data by a DCGAN-based compensation method. Regarding soft errors and block data loss in facial images, a DCGAN architecture is redesigned to compensate for the block data loss. Simulation results show that the proposed method effectively compensates for performance degradation due to soft errors.

• Journal of Industrial Convergence
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• v.17 no.2
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• pp.15-20
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• 2019

The purpose of this study is to provide customized experience learning service platform that enables consumers to easily search for various content information about on - site experiential learning, exhibitions, events, and culture, and to provide services. To provide customized experiential learning information that meets the requirements of the consumer. Beacon technology implemented through this study is a BLE technology that broadcasts a URL in Eddystone format developed by Google. This means that even if a user does not install a separate application, Making it easier and faster to access. Based on this, when the database of local cultural contents is completed, it will be expanded to the whole country, and it is expected that more diverse and high quality self - directed cultural contents experiential learning activity education programs will be provided to consumers by diversifying contents and expanding the market.

• Journal of Korean Society of Rural Planning
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• v.25 no.2
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• pp.15-21
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• 2019

The agricultural environment is changing and becoming more advanced due to the influence of the 4th Industrial Revolution. From the basic plan of Rural Informatics to the current level of 2nd generation smart farms aimed at improving productivity using Big data, cloud network and more IoT technology. We are continuing to provide support and research and development. However, many problems remain to be solved in order to supply and settle smart farms in Korea. The purpose of this study is to provide a method of collecting and sharing data on farming environment and to help improve the income and productivity of farmers based on collected data. In the case of hog farm, the multiple sensors for environmental data like temperature, humidity and gases and the network environment for connecting the internet were established. The environment sensor was made using the ESP8266 Node MCU board as micro-controller, DHT22 sensor for temperature and humidity, and MQ series sensors for various gases in the hog pens. The network sensor was applied experimentally for one month and the environmental data of the hog farm was stored on a web database. This study is expected to raise the importance of collecting and managing the agricultural and environmental data, for the next generation farmers to understand the smart farm more easily and to try it by themselves.

• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.86-96
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• 2019

The research efforts to modernize Hanok (Korean traditional housing) have been performed to improve the quality and cost-effectiveness through application of modern building methods and materials, and to disseminate it in various forms of sizes and facilities. In this study, in order to identify the variations of modernized Hanok, data from seven test-bed projects are analyzed based on the building work-section, element, method, and material. The data were standardized and managed through the modernized Hanok classification system (Hanclass) to facilitate systematic comparisons of the test-bed projects by the variation of building method and it's cost impact. Identified factors of the variation in terms of building methods were then itemized and quantified in terms of building cost. Findings of this study indicate that the timber structure is the most critical area for future variation for improving the quality and cost-effectiveness. The results of this study will be also used to systemize the Hanok database for further studies.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.682-690
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• 2020

Purpose: This study builds a database by collecting and refining disaster occurrence data and real-time weather and atmospheric data. In conjunction with the public data provided by the API, we propose a service model for the Big Data-based Urban Safety Index. Method: The plan is to provide a way to collect various information related to disaster occurrence by utilizing public data and SNS, and to identify and cope with disaster situations in areas of interest by real-time dashboards. Result: Compared with the prediction model by extracting the characteristics of the local safety index and weather and air relationship by area, the regional safety index in the area of traffic accidents confirmed that there is a significant correlation with weather and atmospheric data. Conclusion: It proposed a system that generates a prediction model for safety index based on machine learning algorithm and displays safety index by sector on a map in areas of interest to users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.37-43
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• 2020

Recently, many researches have been actively to diagnose symptoms of heart disease using ECG signal, which is an electrical signal measuring heart status. In particular, the electrocardiogram signal can be used to monitor and diagnose arrhythmias that indicates an abnormal heart status. In this paper, we proposed 1-D convolutional neural network for arrhythmias classification systems. The proposed model consists of deep 11 layers which can learn to extract features and classify 5 types of arrhythmias. The simulation results over MIT-BIH arrhythmia database show that the learned neural network has more than 99% classification accuracy. It is analyzed that the more the number of convolutional kernels the network has, the more detailed characteristics of ECG signal resulted in better performance. Moreover, we implemented a practical application based on the proposed one to classify arrythmias in real-time.