• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.97-100
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• 2015

In this paper, we propose an efficient method of transmitting data according to size using the Zigbee and Wifi in a wireless sensor network. In existing wireless sensor network using Zigbee and Wifi, Zigbee transmits text and Wifi transmits image and video. Existing research methods in this way is caused a problem that the transmission by selecting a transmission method according to data type. In the case of aggregated data, Zigbee is less efficient than Wifi in some case because of limitation of zigbee's transmission rate, even if data type is text. In this paper, we propose a method for selecting a transmission method by considering the size of the data and transfer efficiency not by data type. It was obtained results that appear to be convenient, according to the linkage algorithm structure of the image and sensing data by selecting a transmission method from data size, not the type of the given data.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.1-8
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• 2004

When the PCI 2.2 bus master requests data using Memory Read command, the target device my hold PCI bus without data transfer for a long time because the target device requires time to prefetch data internally. Because the PCI bus usage efficiency and the data transfer efficiency are decreased due to this situation, the PCI specification recommends to use the Delayed Transaction mechanism to improve the performance. But the mechanism doesn't fully improve performance because the target device doesn't blow prefetch data size exactly. In this paper, we propose a new method to transfer data efficiently when the bus master reads data from the target device. The bus master informs the target device the exact read data size using prefetch request using Memory Write command. The simulation result shows that the proposed method has the higher data transfer efficiency than the Delayed Transaction about 10%.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1155-1166
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• 2015

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies, so Hadoop is a new technology to make that possible. In recent R is using as an engine for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with various data sizes of actual data and simulated data. Experimental results showed our RHadoop system was faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and biglm packages available on bigmemory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.471-477
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• 2022

In this study, an educational program was developed that allows students who take data science courses in the high school credit system to explore related fields after learning data science education. Accordingly, the existing research and requirements for data science education were analyzed, a learning plan was designed, and an educational program was developed in accordance with a step-by-step educational program. In addition, since there is no research on data science education for the high school credit system in existing studies, the research was conducted in the stages of problem definition, data collection, data preprocessing, data analysis, data visualization, and simulation, and referred to studies on data science education that have been conducted in existing schools. Through this study, it is expected that research on data science education in the high school credit system will become more active.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.609-616
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• 2017

National Geographic Information Institute has established a plan that preoccupies UCPs (Unified Control Points) at 2~3km intervals in urban areas by considering the distance between existing UCPs by satellite images and aerial photographs in 2015. In this study, we discussed the method of selecting the locations of optimal UCPs by simulating GPS reception environment in candidate sites for UCPs using GIS. For this purpose, we selected new candidate sites for installing UCPs using satellite images and aerial photographs, and analyzed the GPS reception environment by calculating the visibility distance from buildings around UCPs using GIS skyline analysis. The number of and the arrangement of visible satellites that are capable of GPS satellite reception from the viewpoint of sky view were showed by GIS skyline analysis. Quality evaluation results of GPS observation data were compared with average PDOP calculated from hourly PDOP and TEQC in two points of Sungkyunkwan University during 8 hours. As a result of GPS reception environment using GIS, if the PDOP increases, the data acquisition rate is lowed, and the multipath error and the cycle slip are increased. Thus, this study verified that the quality of GPS observation data can be secured by constructing three-dimensional spatial information and simulating PDOP when preoccupying multiple UCPs using GIS.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1121-1125
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• 2006

급속한 산업화와 도시화로 인하여 이상기후의 발생빈도가 높아지고 기후가 불안정해져서 예전보다 많은 집중호우가 발생되고 있다. 그리고 최근 홍수의 규모와 발생빈도가 증가하면서 홍수로 인한 인명과 재산상의 손실이 반복되고 있다. 이에 따른 홍수피해의 위험을 줄이기 위한 홍수방지시스템의 구축이 절실히 요구되고 있으며 홍수범람구역의 정확한 추정을 위해서는 홍수범람도 작성이 필요하다. 또한 정보통신산업이 급속도로 발전하면서 인터넷 사용의 증가로 많은 사용자들이 웹(Web)을 통해 다양한 데이터를 공유할 수 있고 정보를 검색할 수 있게 되면서 수자원 분야에도 정보의 공유와 자료의 통합을 위하여 Open GIS(The Open Geodata Interoperability Specification) 개념이 도입되고 있다. 따라서 본 연구에서는 Web기반으로 홍수범람모의 시스템을 구축하기 위한 기초연구로서 홍수 발생시 침수피해지역을 대상으로 실시간 3차원 홍수범람모의해석이 가능하도록 함으로써 연안지역 피해주민들의 피해를 줄일 수 있도록 하였다. 먼저, 본 연구에서는 이전의 시스템 상에서 정적인 지도로서 표현만 가능하던 것을 시공간적으로 유동성 있는 자료의 분석을 시각화하는 GIS 공간정보기술과 접목시켜 Web상에 동적인 지도형태로 표현함으로써 피해주민들이 쉽게 접할 수 있도록 하여 다양한 정보의 제공이 가능하게 될 것이다. 둘째, Web을 이용함으로써 실시간 홍수재해 정보를 수집하고 분석할 수 있어 인명과 재산의 피해를 줄일 수 있을 것으로 판단된다. 본 논문은 홍수범람시스템을 구축하기 위한 기초연구로서 현재는 GIS DB를 구축하는 단계에 있으며, 향후 다양한 유역을 대상으로 홍수범람모의시스템을 구축하여 분석결과를 피해지역주민 및 관련기관 실무자들에게 제공함으로써 시간과 공간에 구애받지 않는 재해관리와 신속한 재해 상황 대처가 가능해 질 것으로 사료된다.는 또 다른 형태의 주제도라고 볼 수 있으며, 이를 구축하기 위해서는 자료변환 및 가공이 필요하다. 즉, 각 상습침수지구에 필요한 지형도는 국립지리원에서 제작된 1:5,000 수치지형도가 있으나 이는 자료가 방대하고 상습침수지구에 필요하지 않은 자료들을 많이 포함하고 있으므로 상습침수지구의 데이터를 인터넷을 통해 서비스하기 위해서는 많은 불필요한 레이어의 삭제, 서비스 속도를 고려한 데이터의 일반화작업, 지도의 축소.확대 등 자료제공 방식에 따른 작업 그리고 가시성을 고려한 심볼 및 색채 디자인 등의 작업이 수반되어야 하며, 이들을 고려한 인터넷용 GIS기본도를 신규 제작한다. 상습침수지구와 관련된 각종 GIS데이타와 각 기관이 보유하고 있는 공공정보 가운데 공간정보와 연계되어야 하는 자료를 인터넷 GIS를 이용하여 효율적으로 관리하기 위해서는 단계별 구축전략이 필요하다. 따라서 본 논문에서는 인터넷 GIS를 이용하여 상습침수구역관련 정보를 검색, 처리 및 분석할 수 있는 상습침수 구역 종합정보화 시스템을 구축토록 하였다.N, 항목에서 보 상류가 높게 나타났으나, 철거되지 않은 검전보나 안양대교보에 비해 그 차이가 크지 않은 것으로 나타났다.의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전략이고, 이 전략의 유용성은 투자자가

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.145-153
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• 2001

The Pyramid-Technique is based on mapping n-dimensional space data into one-dimensional data and expressing it as B-tree ; and by solving the problem of search time complexity the pyramid technique also prevents the effect \"phenomenon of dimensional curse\" which is caused by treatment of hypercube range query in n-dimensional data space. The Spherical Pyramid-Technique applies the pyramid method’s space division strategy, uses spherical range query and improves the search performance to make it suitable for similarity search. However, depending on the size of data and change in dimensions, the two above technique demonstrate significantly inferior search performance for data sizes greater than one million and dimensions greater than sixteen. In this paper, we propose a new index-structured PdR-Tree to improve the search performance for high dimensional data such as multimedia data. Test results using simulation data as well as real data demonstrate that PdR-Tree surpasses both the Pyramid-Technique and Spherical Pyramid-Technique in terms of search performance.

• Journal of Korea Multimedia Society
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• v.12 no.3
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• pp.372-382
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• 2009

When the range of projection angles is limited, tomographic reconstruction suffers from artifacts caused by incomplete data. One can consider a data completion technique, which estimates projection data at unobserved angles using a prior knowledge or mathematical exploration, but the result is often not improved; the improvement by the data completion often undermined by the artifacts by inaccurate estimation, In this paper, we propose an iterative method, which computes projection data at unobserved angles by using the current estimate on the image, links the computed projection data to the observed ones by using the consistence condition of Radon transform, and reconstruct the next estimate on the image by filtered backprojection. The proposed method does not require a prior knowledge on the image, and has much faster approximation rate than the expectation maximization method. The performance of the proposed method was tested through several simulation studies.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.911-923
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• 2016

Machine learning becomes increasingly important in the big data era. Logistic regression is a type of classification in machine leaning, and has been widely used in various fields, including medicine, economics, marketing, and social sciences. Rhipe that integrates R and Hadoop environment, has not been discussed by many researchers owing to the difficulty of its installation and MapReduce implementation. In this paper, we present the MapReduce implementation of Gradient Descent algorithm and Newton-Raphson algorithm for logistic regression using Rhipe. The Newton-Raphson algorithm does not require a learning rate, while Gradient Descent algorithm needs to manually pick a learning rate. We choose the learning rate by performing the mixed procedure of grid search and binary search for processing big data efficiently. In the performance study, our Newton-Raphson algorithm outpeforms Gradient Descent algorithm in all the tested data.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.876-880
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• 2008

Outliers are the observations which are very larger or smaller than most observations in the given data set. These are shown by some sources. The result of the analysis with outliers may be depended on them. In general, we do data analysis after removing outliers. But, in data mining applications such as fraud detection and intrusion detection, outliers are included in training data because they have crucial information. In regression models, simple and multiple regression models need to eliminate outliers from given training data by standadized and studentized residuals to construct good model. In this paper, we use support vector regression(SVR) based on statistical teaming theory to analyze data with outliers in regression. We verify the improved performance of our work by the experiment using synthetic data sets.