• Journal of Information Science Theory and Practice
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• 제4권2호
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• pp.6-20
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• 2016

In the last few years, a new type of synchronous social networking services (SNSs) has emerged—social live streaming services (SLSSs). Studying SLSSs is a new and exciting research field in information science. What information behaviors do users of live streaming platforms exhibit? In our empirical study we analyzed information production behavior (i.e., broadcasting) as well as information reception behavior (watching streams and commenting on them). We conducted two quantitative investigations, namely an online survey with YouNow users (N = 123) and observations of live streams on YouNow (N = 434). YouNow is a service with video streams mostly made by adolescents for adolescents. YouNow users like to watch streams, to chat while watching, and to reward performers by using emoticons. While broadcasting, there is no anonymity (as in nearly all other WWW services). Synchronous SNSs remind us of the film The Truman Show, as anyone has the chance to consciously broadcast his or her own life real-time.

• 한국환경과학회지
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• 제21권8호
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• pp.939-951
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• 2012

This study is conducted to estimate the air temperature decreasing effects by restoring urban streams using WRF/CALMET coupled system. The types of land use on covered streams are constructed with the land cover map from Korea ministry of environment. Restoring covered streams changes the types of land use on covered areas to water. Two different types of land use(CASE 1 and CASE 2) are inputted to the WRF/CALMET coupled system in order to calculate the temperature difference. The results of the WRF/CALMET coupled system are similar to the observed values at automatic weather stations(AWS) in Busan area. Restoring covered streams causes temperature to be decreased by about $0.34{\sim}2^{\circ}C$ according to the locations of streams and the regions that temperature is reduced are widely distributed over the restored area. Reduction of temperature is increased rapidly from morning and maximus at 13LST. Natural restoration of streams will reduce the built-up area within urban. With this, temperature reductions which are the cause to weaken the urban heat island appear. Relief of urban heat island will help to improve the air quality such as accumulation of air pollutants in within urban area.

• 대한공간정보학회지
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• 제23권2호
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• pp.59-67
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• 2015

치수적 안전은 하천의 계획에 있어 가장 먼저 고려해야 할 사항이며 최근 폭넓게 진행 중인 하천의 복원에 있어서도 치수적 안전은 기본적인 전제조건이 된다. 안전한 하천의 계획은 정확한 측량자료로부터 시작된다. 본 연구에서는 스마트 지형공간정보를 이용하여 하천의 3차원 지형모델을 제작하고 제작된 3차원 지형모델을 이용하여 하천의 수리해석 및 하천 복원에 적용하였다. 이를 통해 상세한 하천 현황 데이터를 추출함으로써 보다 정확한 수리해석이 가능하였다. 또한, LiDAR 데이터를 도시하천의 수리해석에 이용할 경우 적용할 수 있도록 효율적인 데이터 처리와 수리해석의 정확성을 고려한 최적 횡단면 간격을 결정하였다. 하천 복원 설계를 위한 3차원 설계방안과 하천의 다양한 공간계획에 3차원 지형모델을 이용할 수 있는 활용 방안을 제시하였다.

• Journal of information and communication convergence engineering
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• 제7권2호
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• pp.199-202
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• 2009

Adaptive memory management is a serious issue in data stream management. Data stream differ from the traditional stored relational model in several aspect such as the stream arrives online, high volume in size, skewed data distributions. Data skew is a common property of massive data streams. We propose the predicted allocation strategy, which uses predictive processing to cope with time varying data skew. This processing includes memory usage estimation and indexing with timestamp. Our experimental study shows that the predictive strategy reduces both required memory space and latency time for skewed data over varying time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1385-1402
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• 2019

Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.310-315
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• 1999

We extracted narrow open water streams from JERS-1 SAR images of the Amazon rain forest. The extracted range of these streams were almost comparable to a high level extraction of the same streams from near-IR images of JERS-1 VNIR data notwithstanding that these features in SAR images show the strong dependence of the observation angle. Large water bodies are relatively easy to extract from JERS-1 SAR images, as they tend to appear as very dark areas; but streams whose width is nearly equal to or less than the spatial resolution no longer appear as very dark features. By using strong scatterers distributed sparsely along the radar facing sides of the streams, we can successfully estimate approximate ranges of waterways and then extract relatively dark line-like features within these ranges.

• Journal of Information Processing Systems
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• 제6권1호
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• pp.79-90
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• 2010

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. The continuous characteristic of streaming data necessitates the use of algorithms that require only one scan over the stream for knowledge discovery. Data mining over data streams should support the flexible trade-off between processing time and mining accuracy. In many application areas, mining frequent itemsets has been suggested to find important frequent itemsets by considering the weight of itemsets. In this paper, we present an efficient algorithm WSFI (Weighted Support Frequent Itemsets)-Mine with normalized weight over data streams. Moreover, we propose a novel tree structure, called the Weighted Support FP-Tree (WSFP-Tree), that stores compressed crucial information about frequent itemsets. Empirical results show that our algorithm outperforms comparative algorithms under the windowed streaming model.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.251-253
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• 2005

In this paper, an adaptive algorithm is proposed in streaming MPEG-4 contents with fluctuating resource amount such as throughput of network conditions. MPEG-4 is the international standard for audiovisual presentation which is composed of object based media streams. The proposed technique provides the media stream corresponding an object with multiple media streams with different qualities and bit rate in order to support object based scalability to the MPEG-4 content. In addition, making the object streams adaptable, a feasible stream set selected from the multiple streams for transmission with optimal quality in the form of the current status.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.1122-1125
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• 2015

자연언어 분석에 있어서 형태소 분석은 핵심적인 기술로 요구되고 있다. 한글 형태소 분석기는 한글을 분석하기 위한 알고리즘을 활용하여 형태소 단위로 분석한다. 하지만 한글과 문장부호가 혼용된 특수어절은 한글을 분석하는 알고리즘을 통하여 정확한 결과를 도출할 수가 없으므로 별도의 알고리즘이 필요하다. 본 논문에서는 이러한 문제점을 특수어절에 공백을 삽입하여 다시 어절로 분리해 내는 알고리즘을 적용하여 해결하고자 한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2008년도 추계학술발표대회
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• pp.874-877
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• 2008

Nowadays the existing data processing systems can only support some simple query for sensor network. It is increasingly important to process the vast data streams in sensor network, and achieve effective acknowledges for users. In this paper, we propose a holistic distributed k-means algorithm for sensor network. In order to verify the effectiveness of this method, we compare it with central k-means algorithm to process the data streams in sensor network. From the evaluation experiments, we can verify that the proposed algorithm is highly capable of processing vast data stream with less computation time. This algorithm prefers to cluster the data streams at the distributed nodes, and therefore it largely reduces redundant data communications compared to the central processing algorithm.