• Title/Summary/Keyword: 현상파악 데이터

Search Result 275, Processing Time 0.025 seconds

Detection of Urban Trees Using YOLOv5 from Aerial Images (항공영상으로부터 YOLOv5를 이용한 도심수목 탐지)

  • Park, Che-Won;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.6_2
    • /
    • pp.1633-1641
    • /
    • 2022
  • Urban population concentration and indiscriminate development are causing various environmental problems such as air pollution and heat island phenomena, and causing human resources to deteriorate the damage caused by natural disasters. Urban trees have been proposed as a solution to these urban problems, and actually play an important role, such as providing environmental improvement functions. Accordingly, quantitative measurement and analysis of individual trees in urban trees are required to understand the effect of trees on the urban environment. However, the complexity and diversity of urban trees have a problem of lowering the accuracy of single tree detection. Therefore, we conducted a study to effectively detect trees in Dongjak-gu using high-resolution aerial images that enable effective detection of tree objects and You Only Look Once Version 5 (YOLOv5), which showed excellent performance in object detection. Labeling guidelines for the construction of tree AI learning datasets were generated, and box annotation was performed on Dongjak-gu trees based on this. We tested various scale YOLOv5 models from the constructed dataset and adopted the optimal model to perform more efficient urban tree detection, resulting in significant results of mean Average Precision (mAP) 0.663.

Temporal variation in the community structure of green tide forming macroalgae(Chlorophyta; genus Ulva) on the coast of Jeju Island, Korea based on DNA barcoding (DNA 바코드를 이용한 제주도 연안 파래대발생(green tide)을 형성하는 갈파래(genus Ulva) 군집구조 및 주요 종 구성의 시간적 변이)

  • Hye Jin Park;Seo Yeon Byeon;Sang Rul Park;Hyuk Je Lee
    • Korean Journal of Environmental Biology
    • /
    • v.40 no.4
    • /
    • pp.464-476
    • /
    • 2022
  • In recent years, macroalgal bloom occurs frequently in coastal oceans worldwide. It might be attributed to accelerating climate change. "Green tide" events caused by proliferation of green macroalgae (Ulva spp.) not only damage the local economy, but also harm coastal environments. These nuisance events have become common across several coastal regions of continents. In Korea, green tide incidences are readily seen throughout the year along the coastlines of Jeju Island, particularly the northeastern coast, since the 2000s. Ulva species are notorious to be difficult for morphology-based species identification due to their high degrees of phenotypic plasticity. In this study, to investigate temporal variation in Ulva community structure on Jeju Island between 2015 and 2020, chloroplast barcode tufA gene was sequenced and phylogenetically analyzed for 152 specimens from 24 sites. We found that Ulva ohnoi and Ulva pertusa known to be originated from subtropical regions were the most predominant all year round, suggesting that these two species contributed the most to local green tides in this region. While U. pertusa was relatively stable in frequency during 2015 to 2020, U. ohnoi increased 16% in frequency in 2020 (36.84%), which might be associated with rising sea surface temperature from which U. ohnoi could benefit. Two species (Ulva flexuosa, Ulva procera) of origins of Europe should be continuously monitored. The findings of this study provide valuable information and molecular genetic data of genus Ulva occurring in southern coasts of Korea, which will help mitigate negative influences of green tide events on Korea coast.

The Factors Affecting the Population Outflow from Busan to the Seoul Metropolitan Area (지역별 수도권으로의 인구유출에 영향을 미치는 요인 연구: 부산시 사례를 중심으로)

  • LIM, Jaebin;Jeong, Kiseong
    • Land and Housing Review
    • /
    • v.12 no.2
    • /
    • pp.47-59
    • /
    • 2021
  • This study aims to review the trends of the population outflows in the metropolitan area of Busan and to investigate the factors that affect population out-migration to the Seoul metropolitan area. The following variables are considered for analysis: traditional population movement variables and quality of life variables, such as population, society, employment, housing, culture, safety, medical care, greenery, education, and childcare. The 'domestic population movement data', provided by the MDIS of the National Statistical Office, was used for this research. Out of the total of 57 million population movement data in the period 2012 - 2017, population outmigration from Busan to the Seoul metropolitan area was extracted. Independent variables were drawn from public data sources in accordance with the temporal and spatial settings of the study. The multiple linear regression model was specified based on the dataset, and the fit of the model was measured by the p-value, and the values of Adjusted R2, Durbin-Watson analysis, and F-statistics. The results of the analysis showed that the variables that have a significant effect on population movement from Busan to the Seoul metropolitan area were as follows: 'single-person households', 'the elderly population', 'the total birth rate', 'the number of companies', 'the number of employees', 'the housing sales price index', 'cultural facilities', and 'the number of students per teacher'. More positive (+) influences of the population out-movement were observed in areas with higher numbers of single-person households, lowers proportions of the elderly, lower numbers of businesses, higher numbers of employees, higher numbers of housing sales, lower numbers of cultural facilities, and lower numbers of students. The findings suggest that policies should enhance the environments such as quality jobs, culture, and welfare that can retain young people within Busan. Improvements in the quality of life and job creation are critical factors that can mitigate the outflows of the Busan residents to the Seoul metropolitan area.

Product Community Analysis Using Opinion Mining and Network Analysis: Movie Performance Prediction Case (오피니언 마이닝과 네트워크 분석을 활용한 상품 커뮤니티 분석: 영화 흥행성과 예측 사례)

  • Jin, Yu;Kim, Jungsoo;Kim, Jongwoo
    • Journal of Intelligence and Information Systems
    • /
    • v.20 no.1
    • /
    • pp.49-65
    • /
    • 2014
  • Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

Investigating Dynamic Mutation Process of Issues Using Unstructured Text Analysis (비정형 텍스트 분석을 활용한 이슈의 동적 변이과정 고찰)

  • Lim, Myungsu;Kim, Namgyu
    • Journal of Intelligence and Information Systems
    • /
    • v.22 no.1
    • /
    • pp.1-18
    • /
    • 2016
  • Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

Evaluation of Incident Detection Algorithms focused on APID, DES, DELOS and McMaster (돌발상황 검지알고리즘의 실증적 평가 (APID, DES, DELOS, McMaster를 중심으로))

  • Nam, Doo-Hee;Baek, Seung-Kirl;Kim, Sang-Gu
    • Journal of Korean Society of Transportation
    • /
    • v.22 no.7 s.78
    • /
    • pp.119-129
    • /
    • 2004
  • This paper is designed to report the results of development and validation procedures in relation to the Freeway Incident Management System (FIMS) prototype development as part of Intelligent Transportation Systems Research and Development program. The central core of the FIMS is an integration of the component parts and the modular, but the integrated system for freeway management. The whole approach has been component-orientated, with a secondary emphasis being placed on the traffic characteristics at the sites. The first action taken during the development process was the selection of the required data for each components within the existing infrastructure of Korean freeway system. After through review and analysis of vehicle detection data, the pilot site led to the utilization of different technologies in relation to the specific needs and character of the implementation. This meant that the existing system was tested in a different configuration at different sections of freeway, thereby increasing the validity and scope of the overall findings. The incident detection module has been performed according to predefined system validation specifications. The system validation specifications have identified two component data collection and analysis patterns which were outlined in the validation specifications; the on-line and off-line testing procedural frameworks. The off-line testing was achieved using asynchronous analysis, commonly in conjunction with simulation of device input data to take full advantage of the opportunity to test and calibrate the incident detection algorithms focused on APID, DES, DELOS and McMaster. The simulation was done with the use of synchronous analysis, thereby providing a means for testing the incident detection module.

Review of applicability of Turbidity-SS relationship in hyperspectral imaging-based turbid water monitoring (초분광영상 기반 탁수 모니터링에서의 탁도-SS 관계식 적용성 검토)

  • Kim, Jongmin;Kim, Gwang Soo;Kwon, Siyoon;Kim, Young Do
    • Journal of Korea Water Resources Association
    • /
    • v.56 no.12
    • /
    • pp.919-928
    • /
    • 2023
  • Rainfall characteristics in Korea are concentrated during the summer flood season. In particular, when a large amount of turbid water flows into the dam due to the increasing trend of concentrated rainfall due to abnormal rainfall and abnormal weather conditions, prolonged turbid water phenomenon occurs due to the overturning phenomenon. Much research is being conducted on turbid water prediction to solve these problems. To predict turbid water, turbid water data from the upstream inflow is required, but spatial and temporal data resolution is currently insufficient. To improve temporal resolution, the development of the Turbidity-SS conversion equation is necessary, and to improve spatial resolution, multi-item water quality measurement instrument (YSI), Laser In-Situ Scattering and Transmissometry (LISST), and hyperspectral sensors are needed. Sensor-based measurement can improve the spatial resolution of turbid water by measuring line and surface unit data. In addition, in the case of LISST-200X, it is possible to collect data on particle size, etc., so it can be used in the Turbidity-SS conversion equation for fraction (Clay: Silt: Sand). In addition, among recent remote sensing methods, the spatial distribution of turbid water can be presented when using UAVs with higher spatial and temporal resolutions than other payloads and hyperspectral sensors with high spectral and radiometric resolutions. Therefore, in this study, the Turbidity-SS conversion equation was calculated according to the fraction through laboratory analysis using LISST-200X and YSI-EXO, and sensor-based field measurements including UAV (Matrice 600) and hyperspectral sensor (microHSI 410 SHARK) were used. Through this, the spatial distribution of turbidity and suspended sediment concentration, and the turbidity calculated using the Turbidity-SS conversion equation based on the measured suspended sediment concentration, was presented. Through this, we attempted to review the applicability of the Turbidity-SS conversion equation and understand the current status of turbid water occurrence.

Development of a deep-learning based tunnel incident detection system on CCTVs (딥러닝 기반 터널 영상유고감지 시스템 개발 연구)

  • Shin, Hyu-Soung;Lee, Kyu-Beom;Yim, Min-Jin;Kim, Dong-Gyou
    • Journal of Korean Tunnelling and Underground Space Association
    • /
    • v.19 no.6
    • /
    • pp.915-936
    • /
    • 2017
  • In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.

Management Guidelines on the Large Old Trees as the Natural Monuments in Seoul, Incheon, and Gyeonggi Province through the Analysis of the Growing Environment (생육환경 분석을 통한 서울·인천·경기지역 천연기념물 노거수의 관리방안)

  • Lee, Seung Je
    • Korean Journal of Heritage: History & Science
    • /
    • v.42 no.1
    • /
    • pp.88-99
    • /
    • 2009
  • This study was conducted to formulate management guidelines for Natural monumental old trees in Korea through survey of tree vigor and analysis of growing environments. A total of 20 old trees designated as natural monuments in Seoul, Incheon, and Gyeonggi Province were surveyed. The biological characteristics were surveyed with 4 items of species, ages and height of trees. The surrounding environments were surveyed with 2 items of location types and surroundings. The root conditions were surveyed with 2 items of denudation and molding depth. The health conditions were surveyed with 5 items of withering rate, cavity size, bark breakaway rate, damages by blight and insects, and growing tips. The soil conditions were surveyed with 6 items of PH, organic contents, valid phosphoric acid, transposal cations(K, Ca) and soil compaction. On the basis of outcomes of these research items, mutual relations among locations, growings and soil conditions of old trees were analyzed by carring out cross tabulation, correlation, and simple and multiple regression. Management guidelines were presented searching the factors effecting on the health of the monumental old trees. On the biological characteristics, the old trees designated as natural monuments were Pinus bungeana(4 trees), Juniperus chinensis(3 trees), Ginkgo biloba(3 trees), Poncirus trifoliata(2 trees). Actinidia arguta, Wisteria floribunda, Thuja orientalis, Quercus mongolica, Sophora japonica, Fraxinus rhynchophylla, Zelkova serrata, and Pinus densiflora. The tree height ranged from 4.2 to 39.2m, and root collar rounds ranged from 1.01 to 15.2m. On the surrounding environments, The location types ; Gardens(4), historical sites(5), residental sections(3) open agricultural fields(3), mountain hills(3), and near ocean beaches(1) and stream site(1). The surroundings ; 75% denudation of roots, molded more than 10cm except 4 trees(25%). On the health conditions, 1)Withering rate ; Ginkgo biloba(20%) in Yongmoon temple, (5%) in Saki-ri, kanwha-gun, and others had no withering rate. 2) Cavity size ; all subject had $5{\sim}100cm^3$ of cavity. 3) Bark breakaway rate ; Pinus bungeana in Soosong-dong, in the shrine of Confucius, in Samchung-dong, especially high rate of cavity(5~50%) in Seoul area and in Saki-ri, Kangwha-gun were high 45% brakeaway rate. 4) Damages by blight and insects was slight due to managements. 5Growing tips ; In cases of Juniperus chinensis in Changdeok palace and SunnogDang, seoul, growing tips were 1/2, presumably cause by air pollution, and in cases of Fraxinus rhynchophylla in Paju city and Pinus densiflora in BacksaDorip-ri, Icheon city, growing tips were fine, presumably because there were no moldings. On the Soil conditions, Soil pH ranged from 5.2 to 8.3, organic matter contents from 12% to 56%, phosphorus contents from 104 to 618ppm, soil compaction ranged from 7 to 28mm( among them, Denudation was severe with 21~28mm soil compactions in cases of Pinus bungeana in Soosong -dong, Thuja orientalis in Samchung -dong, Ginkgo biloba in the shrine of Confucius and in Yongmoon temple.) Results of cross tabulation, correlation, and regression analysis showed that molding depth was the most serious factor to deteriorate the tree vigor and cambium conductivity. In addition, soil acidity, organic matter contents, disease and insect damages and cambial detachment were also related to the tree vigor. Additional research of these relationships will be needed to conduct more detailed studies. Based on the relationships between the tree vigor and growing environments, it is considered that old trees should be managed to give them more growing spaces and less abuses. Also, molded soils should be removed and further soil-molding around the tree collar should be prohibited. For the construction of systematic management and removal of harmful factors, appropriative management according to spices, persistent monitering of damaged cases and construction of management system through the accumulation of data on the relationships of soil conditions are required.

A comparison between the real and synthetic cohort of mortality for Korea (가상코호트와 실제코호트 사망력 비교)

  • Oh, Jinho
    • The Korean Journal of Applied Statistics
    • /
    • v.31 no.4
    • /
    • pp.427-446
    • /
    • 2018
  • Korea will have a super-aged society within only 30 years according to the United Nations' definition of an aging society and the statistics on Korea's Population projections (2016), indicates that Korea has the fastest ageing speed in the world. There is a lack of data on long-term time-series data on death as related to pension and welfare policies compared to the rapid rate of aging. This paper estimates life expectancy over 245 years (from 1955 to 2200) through past and future forecasts as well as compares the expected life expectancy of the synthetic cohort and the real cohort. In addition, an international comparisons were made to understand the level of aging in Korea. Estimates of the back-projection period were compared with previous studies and the LC model to improve accuracy and objectivity. In addition, the predictions after 2016 reflected the declined mortality rate effect of Korea using the LC-ER model. The results showed an increase in life expectancy of about 30 years over 60 years (1955-2015) with an expected life expectancy of the real cohort over the second century (1955-2155) higher than the synthetic cohort. The comparative advantage of life expectancy of real cohorts was confirmed to be a common trend among comparative countries. In addition, Japan and Korea have a higher life expectancy and starting from 85 to 90 years old, all comparative countries show that the growth rate for the life expectancy of synthetic and real cohorts is less than previous years.