• Journal of Information Science Theory and Practice
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• v.4 no.2
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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.

• Journal of Environmental Science International
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• v.21 no.8
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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.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.59-67
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• 2015

When planning for streams, adequate and definite flood control should be in the primary consideration of the planner; likewise, flood control is the basic prerequisite for the recent river restoration taking place nationwide. Planning 'safe' streams and rivers that are predictable and controllable begins from accurate survey data. In this research, we will create streams in 3D terrain models and apply them through hydraulic analysis and restoration using smart geospatial information. This process allows the extraction of more accurate data regarding streams and rivers, which makes possible precise hydraulic analysis that is superior in details to the conventional methods. The study also proposes optimal vertical section interval for efficient data processing on hydraulic analysis, applicable when LiDAR data is utilized on hydraulic analysis of urban streams. The study proposes 3D design plan and various applications for spatially planning and restoring rivers and streams.

• Journal of information and communication convergence engineering
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• v.7 no.2
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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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• v.13 no.3
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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.

• Proceedings of the KSRS Conference
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• 1999.11a
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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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• v.6 no.1
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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.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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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.