• Title/Summary/Keyword: Information portal

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Extraction and Utilization of DEM based on UAV Photogrammetry for Flood Trace Investigation and Flood Prediction (침수흔적조사를 위한 UAV 사진측량 기반 DEM의 추출 및 활용)

  • Jung-Sik PARK;Yong-Jin CHOI;Jin-Duk LEE
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.237-250
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    • 2023
  • Orthophotos and DEMs were generated by UAV-based aerial photogrammetry and an attempt was made to apply them to detailed investigations for the production of flood traces. The cultivated area located in Goa-eup, Gumi, where the embankment collapsed and inundated inundation occurred due to the impact of 6th Typhoon Sanba in 2012, was selected as rhe target area. To obtain optimal accuracy of UAV photogrammetry performance, the UAV images were taken under the optimal placement of 19 GCPs and then point cloud, DEM, and orthoimages were generated through image processing using Pix4Dmapper software. After applying CloudCompare's CSF Filtering to separate the point cloud into ground elements and non-ground elements, a finally corrected DEM was created using only non-ground elements in GRASS GIS software. The flood level and flood depth data extracted from the final generated DEM were compared and presented with the flood level and flood depth data from existing data as of 2012 provided through the public data portal site of the Korea Land and Geospatial Informatix Corporation(LX).

Neutron dosimetry depending on the number of portals for prostate cancer IMRT(Intensity-Modulated Radiation Therapy) (전립선암의 세기조절 방사선치료 시 조사문수별 중성자선량 평가)

  • Lee, Joo-Ah;Son, Soon-Yong;Min, Jung-Whan;Choi, Kwan-Woo;Na, Sa-Ra;Jeong, Hoi-Woun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.6
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    • pp.3734-3740
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    • 2014
  • The aim of this study was provide basic information and establish the criteria in radiation therapy planning by measuring the absorbed neutron dose of normal tissues and lesions according to the number of portals. From September 2013 to January 2014, 20 patients who were diagnosed with prostate cancer and were previously treated with radiation therapy were replanned retrospectively to measure the absorbed neutron dose distribution according to the number of portals. The absorbed neutron dose was measured in each of the 5, 7 and 9 portals using a 15 MV energy, which meant a therapeutic dose of 220 cGy. The optical stimulation luminescence dosimeter was separated by 20cm and 60cm away from the center of the field of view. As a result, the average radiation dose in the abdomen appeared to have a positive relationship with the number of portals, which was statistically significant (p<.05). The average radiation dose was $4.34{\pm}1.08$. The average radiation dose in the thyroid was $2.71{\pm}.37$. Although it showed a positive relationship with the number of portals, it did not have statistical significance. The number of portals and the neutron dose depending on the position showed a significant positive relationship, particularly in the abdomen. As a result of linear regression analysis, as the number of the portal increased in steps, the average volume of the neutrons increased significantly (0.416 times). In conclusion, efficient selection of the number of portals is needed considering the difference in the absorbed neutron dose in the normal tissues depending on the number of the portals.

Liver Splitting Using 2 Points for Liver Graft Volumetry (간 이식편의 체적 예측을 위한 2점 이용 간 분리)

  • Seo, Jeong-Joo;Park, Jong-Won
    • The KIPS Transactions:PartB
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    • v.19B no.2
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    • pp.123-126
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    • 2012
  • This paper proposed a method to separate a liver into left and right liver lobes for simple and exact volumetry of the river graft at abdominal MDCT(Multi-Detector Computed Tomography) image before the living donor liver transplantation. A medical team can evaluate an accurate river graft with minimized interaction between the team and a system using this algorithm for ensuring donor's and recipient's safe. On the image of segmented liver, 2 points(PMHV: a point in Middle Hepatic Vein and PPV: a point at the beginning of right branch of Portal Vein) are selected to separate a liver into left and right liver lobes. Middle hepatic vein is automatically segmented using PMHV, and the cutting line is decided on the basis of segmented Middle Hepatic Vein. A liver is separated on connecting the cutting line and PPV. The volume and ratio of the river graft are estimated. The volume estimated using 2 points are compared with a manual volume that diagnostic radiologist processed and estimated and the weight measured during surgery to support proof of exact volume. The mean ${\pm}$ standard deviation of the differences between the actual weights and the estimated volumes was $162.38cm^3{\pm}124.39$ in the case of manual segmentation and $107.69cm^3{\pm}97.24$ in the case of 2 points method. The correlation coefficient between the actual weight and the manually estimated volume is 0.79, and the correlation coefficient between the actual weight and the volume estimated using 2 points is 0.87. After selection the 2 points, the time involved in separation a liver into left and right river lobe and volumetry of them is measured for confirmation that the algorithm can be used on real time during surgery. The mean ${\pm}$ standard deviation of the process time is $57.28sec{\pm}32.81$ per 1 data set ($149.17pages{\pm}55.92$).

The Stock Portfolio Recommendation System based on the Correlation between the Stock Message Boards and the Stock Market (인터넷 주식 토론방 게시물과 주식시장의 상관관계 분석을 통한 투자 종목 선정 시스템)

  • Lee, Yun-Jung;Kim, Gun-Woo;Woo, Gyun
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.10
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    • pp.441-450
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    • 2014
  • The stock market is constantly changing and sometimes the stock prices unaccountably plummet or surge. So, the stock market is recognized as a complex system and the change on the stock prices is unpredictable. Recently, many researchers try to understand the stock market as the network among individual stocks and to find a clue about the change of the stock prices from big data being created in real time from Internet. We focus on the correlation between the stock prices and the human interactions in Internet especially in the stock message boards. To uncover this correlation, we collected and investigated the articles concerning with 57 target companies, members of KOSPI200. From the analysis result, we found that there is no significant correlation between the stock prices and the article volume, but the strength of correlation between the article volume and the stock prices is relevant to the stock return. We propose a new method for recommending stock portfolio base on the result of our analysis. According to the simulated investment test using the article data from the stock message boards in 'Daum' portal site, the returns of our portfolio is about 1.55% per month, which is about 0.72% and 1.21% higher than that of the Markowitz's efficient portfolio and that of the KOSPI average respectively. Also, the case using the data from 'Naver' portal site, the stock returns of our proposed portfolio is about 0.90%, which is 0.35%, 0.40%, and 0.58% higher than those of our previous portfolio, Markowitz's efficient portfolio, and KOSPI average respectively. This study presents that collective human behavior on Internet stock message board can be much helpful to understand the stock market and the correlation between the stock price and the collective human behavior can be used to invest in stocks.

Evaluation of the Jaw-Tracking Technique for Volume-Modulated Radiation Therapy in Brain Cancer and Head and Neck Cancer (뇌암 및 두경부암 체적변조방사선치료시 Jaw-Tracking 기법의 선량학적 유용성 평가)

  • Kim, Hee Sung;Moon, Jae Hee;Kim, Koon Joo;Seo, Jung Min;Lee, Joung Jin;Choi, Jae Hoon;Kim, Sung Ki;Jang, In-Gi
    • The Journal of Korean Society for Radiation Therapy
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    • v.30 no.1_2
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    • pp.177-183
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    • 2018
  • Purpose : Volumetric Modulated Arc Therapy(VMAT) has the advantage of uniformly and precisely irradiating the tumor to the shape of the tumor while reducing the risk of radiation damage to normal tissues. such as brain cancer, head and neck cancer and prostate cancer, It is being used for treatment. The purpose of this study is to evaluate the usefulness of the Jaw-Tracking technique(JTT) in VMAT for brain and head and neck cancer. Materials and Methods : We selected eight patients with brain and head and neck cancer(4 Brain, 4 head and neck) who were treated with the VMAT treatment technique. Contouring information of the patient's tumor and normal organ was fused to the Rando phantom using the deformable registration of Velocity(Varian, USA). A treatment plan was developed using the Varian Eclipse(ver 15.5, Varian, USA) with the same patient actual beam parameters except for the use of jaw-tracking. As the evaluation index, the maximum dose and mean dose of target and OAR were compared and a portal dosimetry was performed for the treatment plan verification. Results : When using JTT, the relative dose of OAR decreased by 5.24 % and the maximum dose by 7.05 %, respectively, compared with the Static-Jaw technique(SJT). In the various OARs, the mean dose and maximum dose reduction ranges ranged from 0.01 to 3.16 Gy and from 0.12 to 6.27 Gy, respectively. In the case of the target, the maximum dose of GTV, CTV, PTV decreased by 0.17 %, 0.43 %, and 0.37 % in JTT, and the mean dose decreased by 0.24 %, 0.47 % and 0.47 %, respectively. Gamma analysis The JTT and SJT passing rates were $98{\pm}1.73%$ and $97{\pm}1.83%$ on the basis of 3 % / 3 mm, respectively. Comparing the doses of all OARs applied to the experiment, it was found that the use of JTT resulted in a significant decrease in dose due to additional jaw shielding besides MLC than SJT. Conclusion : In radiation therapy using VMAT treatment plan, we can apply JTT in the case of adjacent tumor and normal organs such as brain cancer and head and neck cancer, and in radiotherapy required large field and high energy caused increase leakage dose through MLC. It is considered that the target dose of PTV can be increased by lowering the dose of normal tissue surrounding the tumor.

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Term Mapping Methodology between Everyday Words and Legal Terms for Law Information Search System (법령정보 검색을 위한 생활용어와 법률용어 간의 대응관계 탐색 방법론)

  • Kim, Ji Hyun;Lee, Jong-Seo;Lee, Myungjin;Kim, Wooju;Hong, June Seok
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.137-152
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    • 2012
  • In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

Content-based Recommendation Based on Social Network for Personalized News Services (개인화된 뉴스 서비스를 위한 소셜 네트워크 기반의 콘텐츠 추천기법)

  • Hong, Myung-Duk;Oh, Kyeong-Jin;Ga, Myung-Hyun;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.57-71
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    • 2013
  • Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

Implementation Strategy of Global Framework for Climate Service through Global Initiatives in AgroMeteorology for Agriculture and Food Security Sector (선도적 농림기상 국제협력을 통한 농업과 식량안보분야 전지구기후 서비스체계 구축 전략)

  • Lee, Byong-Lyol;Rossi, Federica;Motha, Raymond;Stefanski, Robert
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.15 no.2
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    • pp.109-117
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    • 2013
  • The Global Framework on Climate Services (GFCS) will guide the development of climate services that link science-based climate information and predictions with climate-risk management and adaptation to climate change. GFCS structure is made up of 5 pillars; Observations/Monitoring (OBS), Research/ Modeling/ Prediction (RES), Climate Services Information System (CSIS) and User Interface Platform (UIP) which are all supplemented with Capacity Development (CD). Corresponding to each GFCS pillar, the Commission for Agricultural Meteorology (CAgM) has been proposing "Global Initiatives in AgroMeteorology" (GIAM) in order to facilitate GFCS implementation scheme from the perspective of AgroMeteorology - Global AgroMeteorological Outlook System (GAMOS) for OBS, Global AgroMeteorological Pilot Projects (GAMPP) for RES, Global Federation of AgroMeteorological Society (GFAMS) for UIP/RES, WAMIS next phase for CSIS/UIP, and Global Centers of Research and Excellence in AgroMeteorology (GCREAM) for CD, through which next generation experts will be brought up as virtuous cycle for human resource procurements. The World AgroMeteorological Information Service (WAMIS) is a dedicated web server in which agrometeorological bulletins and advisories from members are placed. CAgM is about to extend its service into a Grid portal to share computer resources, information and human resources with user communities as a part of GFCS. To facilitate ICT resources sharing, a specialized or dedicated Data Center or Production Center (DCPC) of WMO Information System for WAMIS is under implementation by Korea Meteorological Administration. CAgM will provide land surface information to support LDAS (Land Data Assimilation System) of next generation Earth System as an information provider. The International Society for Agricultural Meteorology (INSAM) is an Internet market place for agrometeorologists. In an effort to strengthen INSAM as UIP for research community in AgroMeteorology, it was proposed by CAgM to establish Global Federation of AgroMeteorological Society (GFAMS). CAgM will try to encourage the next generation agrometeorological experts through Global Center of Excellence in Research and Education in AgroMeteorology (GCREAM) including graduate programmes under the framework of GENRI as a governing hub of Global Initiatives in AgroMeteorology (GIAM of CAgM). It would be coordinated under the framework of GENRI as a governing hub for all global initiatives such as GFAMS, GAMPP, GAPON including WAMIS II, primarily targeting on GFCS implementations.

Issue tracking and voting rate prediction for 19th Korean president election candidates (댓글 분석을 통한 19대 한국 대선 후보 이슈 파악 및 득표율 예측)

  • Seo, Dae-Ho;Kim, Ji-Ho;Kim, Chang-Ki
    • Journal of Intelligence and Information Systems
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    • v.24 no.3
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    • pp.199-219
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    • 2018
  • With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

What happens after IT adoption?: Role of habits, confirmation, and computer self-efficacy formed by the experiences of use (정보기술 수용 후 주관적 지각 형성: 사용 경험에서 형성된 습관, 기대일치, 자기효능감의 역할)

  • Kim, Yong-Young;Oh, Sang-Jo;Ahn, Joong-Ho;Jahng, Jung-Joo
    • Asia pacific journal of information systems
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    • v.18 no.1
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    • pp.25-51
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    • 2008
  • Researchers have been continuously interested in the adoption of information technology (IT) since it is of great importance to the information systems success and it is also an important stage to the success. Adoption alone, however, does not ensure information systems success because it does not necessarily lead to achieving organizational or individual objectives. When an organization or an individual decide to adopt certain information technologies, they have objectives to accomplish by using those technologies. Adoption itself is not the ultimate goal. The period after adoption is when users continue to use IT and intended objectives can be accomplished. Therefore, continued IT use in the post-adoption period accounts more for the accomplishment of the objectives and thus information systems success. Previous studies also suggest that continued IT use in the post-adoption period is one of the important factors to improve long-term productivity. Despite the importance there are few empirical studies focusing on the user behavior of continued IT use in the post-adoption period. User behavior in the post-adoption period is different from that in the pre-adoption period. According to the technology acceptance model, which explains well about the IT adoption, users decide to adopt IT assessing the usefulness and the ease of use. After adoption, users are exposed to new experiences and they shape new beliefs different from the thoughts they had before. Users come to make decisions based on their experiences of IT use whether they will continue to use it or not. Most theories about the user behaviors in the pre-adoption period are limited in describing them after adoption since they do not consider user's experiences of using the adopted IT and the beliefs formed by those experiences. Therefore, in this study, we explore user's experiences and beliefs in the post-adoption period and examine how they affect user's intention to continue to use IT. Through deep literature reviews on the construction of subjective beliefs by experiences, we draw three meaningful constructs which theoretically have great impacts on the continued use of IT: perceived habit, confirmation, and computer self-efficacy. Then, we examine the role of the subjective beliefs on the cognitive/affective attitudes and intention to continue to use that IT. We set up a research model and conducted survey research. Since IT use implies interactions among a user, IT, and a task, we carefully selected the sample of users using same/similar IT to perform same/similar tasks, to exclude unwanted influences of other factors than subjective beliefs on the IT use. We also considered that the sample of users were able to make decisions to continue to use IT volitionally or at least quasi-volitionally. For each construct, we used measurement items recognized for reliability and widely used in the previous research. We slightly modified some items proper to the research context and a pilot test was carried out for forty users of a portal service in a university. We performed a full-scale survey after verifying the reliability of the measurement. The results show that the intention to continue to use IT is strongly influenced by cognitive/affective attitudes, perceived habits, and computer self-efficacy. Confirmation affects the intention to continue indirectly through cognitive/affective attitudes. All the constructs representing the subjective beliefs built by the experiences of IT use have direct and/or indirect impacts on the intention of users. The results also show that the attitudes in the post-adoption period are formed, at least partly, by the experiences of IT use and newly shaped beliefs after adoption. The findings suggest that subjective beliefs built by the experiences have deep impacts on the continued use. The results of the study signify that while experiencing IT in the post-adoption period users form new beliefs, attitudes, and intentions which may be different from those of the pre-adoption period. The results of this study partly demonstrate that the beliefs shaped by the behaviors, those are the experiences of IT use, influence users' attitudes and intention. The results also suggest that behaviors (experiences) also change attitudes while attitudes shape behaviors. If we combine the findings of this study with the results of the previous research on IT adoption, we can propose a cycle of IT adoption and use where behavior shapes attitude, the attitude forms new behavior, and that behavior shapes new attitude. Different from the previous research, the study focused on the user experience after IT adoption and empirically demonstrated the strong influence of the subjective beliefs formed in the post-adoption period on the continued use. This partly confirms the differences between attitudes in the pre-adoption and in the post-adoption period. Users continuously change their attitudes and intentions while experiencing (using) IT. Therefore, to make users adopt IT and to make them use IT after adoption is a different problem. To encourage users to use IT after adoption, experiential variables such as perceived habit, confirmation, and computer self-efficacy should be managed properly.