• Title/Summary/Keyword: Two-Stream Network

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Flood Disaster Prediction and Prevention through Hybrid BigData Analysis (하이브리드 빅데이터 분석을 통한 홍수 재해 예측 및 예방)

  • Ki-Yeol Eom;Jai-Hyun Lee
    • The Journal of Bigdata
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    • v.8 no.1
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    • pp.99-109
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    • 2023
  • Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.

Analysis and Evaluation of Frequent Pattern Mining Technique based on Landmark Window (랜드마크 윈도우 기반의 빈발 패턴 마이닝 기법의 분석 및 성능평가)

  • Pyun, Gwangbum;Yun, Unil
    • Journal of Internet Computing and Services
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    • v.15 no.3
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    • pp.101-107
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    • 2014
  • With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

An Analysis of IT Trends Using Tweet Data (트윗 데이터를 활용한 IT 트렌드 분석)

  • Yi, Jin Baek;Lee, Choong Kwon;Cha, Kyung Jin
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.143-159
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    • 2015
  • Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

Analysis of Twitter for 2012 South Korea Presidential Election by Text Mining Techniques (텍스트 마이닝을 이용한 2012년 한국대선 관련 트위터 분석)

  • Bae, Jung-Hwan;Son, Ji-Eun;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.141-156
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    • 2013
  • Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

HTTP Adaptive Streaming Method for Service-compatible 3D Contents Based on MPEG DASH (MPEG DASH 기반 service-compatible 3D 콘텐츠 대상 HTTP adaptive streaming 적용방안)

  • Park, Gi-Jun;Lee, Gil-Bok;Lee, Jang-Won;Kim, Kyu-Heon
    • Journal of Broadcast Engineering
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    • v.17 no.2
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    • pp.207-222
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    • 2012
  • Recently, many consumer electronics manufacturers have produced 3D devices such as 3DTVs and 3D monitors as interests in a stereoscopic video service are getting increased. However, most of 3D services are focused on local storage or bandwidth guaranteed service since 3D stereoscopic video service require bandwidth more stable and larger. This property causes difficulties in seamless stereoscopic video streaming services under IP based open network environment that cannot guarantee quality of services. In order to achieve a seamless video streaming service the international standard organization MPEG (Moving Pictures Experts Group) has developed the adaptive HTTP streaming technology called as DASH (Dynamic Adaptive Streaming over HTTP). However, the DASH doesn't have obvious scheme which can express the two elementary video streams based service-compatible stereoscopic contents in one segment. Therefore, this paper proposes a scheme of efficient 3D adaptive streaming service based on the DASH, which covers not only frame-packing stereoscopic contents but also service-compatible ones. The 3D adaptive HTTP streaming scheme introduced in this paper is able to provide 3D contents with various qualities to user and also has benefit that single 3D content can be applied to a variety of devices.

Assessment of the Effect of Geographic Factors and Rainfall on Erosion and Deposition (지형학적 인자 및 강우량에 따른 침식 및 퇴적의 영향 평가)

  • Yu, Wan-Sik;Lee, Gi-Ha;Jung, Kwan-Sue
    • Journal of the Korean Society of Hazard Mitigation
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    • v.11 no.2
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    • pp.103-112
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    • 2011
  • This study aims to demonstrate the relationship between various factors and soil erosion or deposition, simulated from distributed rainfall-sediment-runoff model applications. We selected area, overland flow length, local slope as catchment representative characteristics among many important geographic factors and also used the grid-based accumulated rainfall as a representative hydro-climatic factor to assess the effect of these two different types of factors on erosion and deposition. The study catchment was divided based on the Strahler's stream order method for analysis of the relationship between area and erosion or deposition. Both erosion and deposition increased linearly as the catchment area became larger. Erosion occurred widely throughout the catchment, whereas deposition was observed at the grid-cells near the channel network with short overland flow lengths and mild slopes. In addition, the relationship results between grid-based accumulated rainfall and soil erosion or deposition showed that erosion increased gradually as rainfall amount increased, whereas deposition responded irregularly to variations in rainfall. Within the context of these results, it can be concluded that deposition is closely related with the geographic factors used in this study while erosion is significantly affected by rainfall.

Influences of the devastated forest lands on flood damages (Observed at Chonbo and the neighbouring Mt. Jook-yop area) (황폐임야(荒廢林野)가 수해참상(水害慘狀)에 미치는 영향(影響) (천보산(天寶山)과 인접(隣接) 죽엽산(竹葉山)을 중심(中心)으로))

  • Chung, In Koo
    • Journal of Korean Society of Forest Science
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    • v.5 no.1
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    • pp.4-9
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    • 1966
  • 1. On 13 September 1964 a storm raged for 3 hours and 20 minutes with pounding heavy rainfalls, and precipitation of 287.5 mm was recorded on that day. The numerous landslides were occured in the eroded forest land neighbouring Mt. Chunbo, while no landslides recorde at all on Mt. Jookyup within the premise of Kwangnung Experiment Station, the Forest Experiment Station. 2. Small-scalled Landslides were occured in 43 different places of watershed area (21.97 ha.) in which the survey had already been done, in and around Mt. Chunbo (378 m a.s.l.). The accumulated soil amount totaled $2,146,56m^3$ due to the above mentioned landslides, while soil accumulated from riverside erosion has reached to $24,168.79m^3$, consisting of soils, stones, and pebbles. However, no landslides were reported in the Mt. Jook yup area because of dense forest covers. The ratio of the eroded soil amount accumulated from the riversides to that of watershed area was 1 to 25. On the other hand, the loss and damage in the research area of Mt. Chonbo are as follows: 28 houses completly destroyed or missing 7 houses partially destroyed 51 men were dead 5 missing, and 57 wounded. It was a terrible human disaster However, no human casualties were recorded at all, 1 house-completly destroyed and missing, 2 houses-partially destroyed. Total:3 houses were destroyed or damaged, in The area of Mt. Jookyup 3. In the calculation of the quanty of accumulated soil, the or mula of "V=1/3h ($a+{\sqrt{ab}}+b$)" was used and it showed that 24, 168.79m of soil, sands, stones and pebbles carried away. 4. Average slope of the stream stood 15 at the time of accident and well found that there was a correlation between the 87% of cross-area sufferd valley erosion and the length of eroded valley, after a study on regression and correlation of the length and cross-area. In other works, the soil erosion was and severe as we approached to the down-stream, counting at a place of average ($15^{\circ}1^{\prime}$) and below. We might draw a correlation such as "Y=ax-b" in terms of the length and cross-area of the eroded valley. 5. Sites of char-coal pits were found in the upper part of the desert-like Mt. Chunbo and a professional opinion shows that the mountain was once covered by the oak three species. Furthermore, we found that the soil of both mountains have been kept the same soil system according to a research of the soil cross-area. In other words, we can draw out the fact that, originally, the forest type and soil type of both Mt. Chunbo (378m) and Mt. Jookyup (610m) have been and are the same. However, Mt. Chunbo has been much more devastated than Mt. Jookyup, and carried away its soil nutrition to the extent that the ratios of N. $P_2O_5K_2O$ and Humus C.E.C between these two mountains are 1:10;1:5 respectively. 6. Mt. Chunbo has been mostly eroded for the past 30 years, and it consists of gravels of 2mm or larger size in the upper part of the mountain, while in the lower foot part, the sandy loam was formulated due to the fact that the gluey soil has been carried and accumulated. On the hand, Mt. Jookyup has consitantly kept the all the same forest type and sandy loam of brown colour both in the upper and lower parts. 7. As for the capability of absorbing and saturating maximum humidity by the surface soil, the ratios of wet soil to dry soil are 42.8% in the hill side and lower part of the eroded Mt. Chunbo and 28.5% in the upper part. On the contrary, Mt. Jookyup on which the forest type has not been changed, shows that the ratio in 77.4% in the hill-side and 68.2% in the upper part, approximately twice as much humidity as Mt. Chunbo. This proves the fact that the forest lands with dense forest covers are much more capable of maintaining water by wood, vegitation, and an organic material. The strength of dreventing from carring away surface soil is great due to the vigorous network of the root systems. 8. As mentioned above, the devastated forest land cause not only much greater devastation, but also human loss and property damage. We must bear in mind that the eroded forest land has taken the valuable soil, which is the very existance of origin of both human being and all creatures. As for the prescription for preventing erosion of forest land, the trees for furtilization has to be planted in the hill,side with at least reasonable amount of aertilizer, in order to restore the strength of earth soil, while in the lower part, thorough erosion control and reforestation, and establishments along the riversides have to be made, so as to restore the forest type.

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Study on Change of Algae Occurrence Before & After Gangcheon and Ipoh Weir Construction at Namhan River (남한강 강천보와 이포보 건설 전·후 조류 발생의 변화에 대한 연구)

  • Chae, Soo-Kwon;Oh, Seung-Eun;Chun, Seung-Hoon;Ahn, Hong-Kyu
    • Journal of Wetlands Research
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    • v.18 no.4
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    • pp.394-403
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    • 2016
  • This study was carried out to verify change and relationship between the concentration of chlorophyll-a and environmental factors including weather, water quality and discharge at before & after Gangcheon and Ipoh weir construction at Namhan river, based on the weather and water quality data provided by the measuring network. We classified the period of before & after weir construction by the cluster analysis with Ward's method, and also through the correlation analysis between the concentration of chlorophyll-a and environmental factors, the influence factors related with algae occurrence(Chlorophyll-a) were analyzed. The result by cluster analysis based on data of the total 12 factors (water temperature, rainfall, daylight, pH, DO, BOD, COD, T-N, $NH_3-N$, $NO_3-N$, T-P, $PO_4-P$) from 2005 to 2015 indicated a clear classification into two periods, before(2006-2007) & after (2012-2013) weir construction. After weir construction, class of BOD at Gangcheon weir was better than before, changed from II class to Ia class, and likewise class of BOD at Ipoh weir was improved from II-III class to Ia-IIclass. Also T-P and T-N concentration also were to be improved in general after weir construction. Concentraion of Chlorophyll-a afterGangcheon and Ipoh weir construction was to be decreased. However, frequency of algae warning was increased from 9 to 15 after Ipoh weir construction due to increasing of HRT and water temperature. After weirs construction, the result of correlation analysis between weather, water quality and discharge and concentration of chlorophyll-a indicated a positive correlation, order of BOD(0.579) > COD(0.413) > temperature(0.237), and a negative correlation, order of $NO_3-N$(-0.344) > T-N(-0.293) at Gangcheon weir. And there were likewise positive correlation, order of BOD(0.795) > pH(0.581) > Water temperature(0.422), and negative correlation, order of $NO_3-N$(-0.457) > T-N(-0.371) > $NH_3-N$(-0.326) > $PO_4-P$(-0.288) > Discharge(-0.213) after Ipoh weir construction. Although water quality after Ipoh weir construction was generally improved, increase of frequency of algae warning occurrence was influenced by change of water conditions such as reduction of the velocity, increase of HRT and water temperature, etc impacted strongly by change of the stream flow more than change of water environments after weir construction.