• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.125-148
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• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.7
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• pp.848-857
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• 2018

Recently, around the world, active development of new renewable energy sources including solar power, waves, and fuel cells, etc. has taken place. Particularly, floating offshore wind farms have been developed for saving costs through large scale production, using high-quality wind power and minimizing noise damage in the ocean area. The development of floating wind farms requires an evaluation of the Maritime Safety Audit Scheme under the Maritime Safety Act in Korea. Floating wind farms shall be assessed by applying the line and area concept for systematic development, management and utilization of specified sea water. The development of appropriate evaluation methods and standards is also required. In this study, proper standards for marine traffic surveys and assessments were established and a systemic treatment was studied for assessing marine spatial area. First, a marine traffic data collector using AIS or radar was designed to conduct marine traffic surveys. In addition, assessment methods were proposed such as historical tracks, traffic density and marine traffic pattern analysis applying the line and area concept. Marine traffic density can be evaluated by spatial and temporal means, with an adjusted grid-cell scale. Marine traffic pattern analysis was proposed for assessing ship movement patterns for transit or work in sea areas. Finally, conceptual design of a Marine Traffic and Safety Assessment Solution (MaTSAS) was competed that can be analyzed automatically to collect and assess the marine traffic data. It could be possible to minimize inaccurate estimation due to human errors such as data omission or misprints through automated and systematic collection, analysis and retrieval of marine traffic data. This study could provides reliable assessment results, reflecting the line and area concept, according to sea area usage.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.61-71
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• 2018

When triangular meshes are generated from the point clouds in global space reconstructed through camera pose estimation against captured RGB-D streams, the quality of the resulting meshes improves as more triangles are hired. However, for 3D reconstructed models beyond some size threshold, they become to suffer from the ugly-looking artefacts due to the insufficient precision of RGB-D sensors as well as significant burdens in memory requirement and rendering cost. In this paper, for the generation of 3D models appropriate for real-time applications, we propose an effective technique that extracts high-quality textures for moderate-sized meshes from the captured colors associated with the reconstructed point sets. In particular, we show that via a simple method based on the mapping between the 3D global space resulting from the camera pose estimation and the 2D texture space, textures can be generated effectively for the 3D models reconstructed from captured RGB-D image streams.

• Journal of Practical Engineering Education
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• v.7 no.1
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• pp.31-37
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• 2015

Terrestrial digital multimedia broadcasting (TDMB) is a method of bringing multimedia images, radio, internet, and television to portable devices through terrestrial digital radio transmissions. TDMB related educations being carried out in colleges are focusing on developing firmware which enables users to choose a wanted service. TDMB transmission frame is made up of synchronization channel (SC), fast information channel (FIC), and main service channel (MSC). Services such as video, audio and date are transmitted in the form of subchannel in the MSC. FIC carries information related to each services and subchannels. This paper presents a TDMB frame analysis simulator for analyzing and displaying FIC data on PC. TDMB frame analysis simulator contains functions such as controlling TDMB receiver through USB, establishing the frequency, bringing FIC to PC, displaying ensemble ID and levels, and displaying informations related to services and subchannels. In addition to that, this simulator has a function of being able to store FIC date and subchannel data. This simulator being developed with C++ is expected to be used to view those data visually so that it helps students to understand the TDMB system better and bring about the educational motivation.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.135-145
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• 2012

This study is a research development case study on the free-standing Network based camera video recording DVR. The DVR devices till now have recorded data by converting and compressing analogue video to digital, but in the future, digital videos will be recorded directly through the network camera. Also, digital compressing methods are progressing from MPEG-4, MJPEG, to H.264 method, with products considering high definition compression efficiency, minimized data size, network compatibility, and fast pending time. According to this, in 2012, it is predicted that network camera and video devices throughout the world will outrun the current analogue devices. With this transition of technological environment and fast product pending speed, a new, quality focused design is required for product development including technical realization, reliability, high-definition, compression technology, will be essential. Manufacturers are researching a new direction for the product appearance. This study considers the actual end-users as the design target and through consumer survey on preferences, design needs and required elements necessary in the design development process are extracted. Furthermore, usability and preferred images were explored through literature study and market research. Through this research process, appropriate forms for the network based DVR were analyzed, and applied into the design development process. This product will take into consideration its competitiveness and the significance of USP(Unique Selling Proposition) which is the design supremacy and professional technical skills.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.137-143
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• 2004

The electronic distance measurement(EDM) instrument, introduced first in the 1950s since those early days has, undergone continual refinement. Rapid advances established in related technologies have made it lighter, smaller and more precise equipment. Understanding for the principle, the standardized observation technique and the precision of EDM instrument is mostly important to improve the quality and the reliability of by-product in the field of engineering and industrial surveying. Periodical and accurate calibration is necessary to maintenance the precision of EDM instrument. This paper describes the calculated example of zero error and scale error as a correction of EDM by applying the least square method to baseline observations in test area. Also here we deal with the testing criteria for precision instrument testing according to different types of EDM instruments.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.696-706
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• 2008

In this paper we show the performance of the network-adaptive high-definition scalable video streaming using QWLAN board with IEEE 802.11e MAC monitoring and control. Realtime collected MAC parameters are used to determine which video data is extracted for the predicted available bandwidth. To achieve performance, extraction through R-D is proposed instead of the standard video packet extraction. It is shown through experiments that streaming video quality can be enhanced by fast adaptation to network conditions by using the proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.39-43
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• 2020

In this paper, we propose the multi-channel interference cancellation algorithm for visible light communication (VLC) in smart building. The VLC system is communication technology using visible rays that come out in Light Emitting Diode (LED) device. It has energy curtailment effect and possible to use in ubiquitous network service applications. When a large number of users communicate indoors, the performance can be reduced due to channel interference. To remove interference, at the first, the minimum mean square error (MMSE) scheme as interference cancellation methods used, and then the successive interference cancellation (SIC) is applied to obtain additional diversity gain and improve interference cancellation performance. Indoor VLC channel model is employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the previous systems. As a result, the proposed interference cancellation improves the signal quality of VLC systems by effectively removing the channel noise. The results of the paper can be applied to VLC for smart building and general communication systems.