• Journal of Information Processing Systems
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• v.7 no.4
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• pp.717-732
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• 2011

Classification in biomedical applications is an important task that predicts or classifies an outcome based on a given set of input variables such as diagnostic tests or the symptoms of a patient. Traditionally the classification algorithms would have to digest a stationary set of historical data in order to train up a decision-tree model and the learned model could then be used for testing new samples. However, a new breed of classification called stream-based classification can handle continuous data streams, which are ever evolving, unbound, and unstructured, for instance--biosignal live feeds. These emerging algorithms can potentially be used for real-time classification over biosignal data streams like EEG and ECG, etc. This paper presents a pioneer effort that studies the feasibility of classification algorithms for analyzing biosignals in the forms of infinite data streams. First, a performance comparison is made between traditional and stream-based classification. The results show that accuracy declines intermittently for traditional classification due to the requirement of model re-learning as new data arrives. Second, we show by a simulation that biosignal data streams can be processed with a satisfactory level of performance in terms of accuracy, memory requirement, and speed, by using a collection of stream-mining algorithms called Optimized Very Fast Decision Trees. The algorithms can effectively serve as a corner-stone technology for real-time classification in future biomedical applications.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.213-218
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• 2012

Abnormal dissolved oxygen concentration in aquatic habitat, both depletion and supersaturation, can be stress factor to aquatic animals. In this study the nationwide distribution of oxygen supersaturation was analyzed for three categories of streams (43 urban streams, 15 rural streams, and 14 forest streams) by using monitoring network data of the Korean Ministry of Environment. From the distribution analysis 30% of urban streams showed hyperoxic condition of eutrophic level, while no forest stream showed hyperoxic condition. The physiological effect of hyperoxia on fish was examined using two species of fish Zacco koreanus, which resulted in higher concentration of a stress hormone (cortisol) in fish exposed to hyperoxic concentration (196%) of oxygen. This study shows that hyperoxic condition is ubiquitous in urban and rural Korean streams, and it can be a stress factor to aquatic animals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4307-4325
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• 2016

With the aim of solving the problems of long processing times, high memory consumption and low event throughput in the current processing approaches in out-of-order RFID event streams, an efficient complex event processing method based on INFA-HTS (Improved Nondeterministic Finite Automaton-Hash Table Structure) is presented in this paper. The contribution of this paper lies in the fact that we use INFA and HTS to successfully realize the detection of complex events for out-of-order RFID event streams. Specifically, in our scheme, to detect the disorder of out-of-order event streams, we expand the traditional NFA model into a new INFA model to capture the related RFID primitive events from the out-of-order event stream. To high-efficiently manage the large intermediate capturing results, we use the HTS to store and process them. As a result, these problems in the existing methods can be effectively solved by our scheme. The simulation results of our experiments show that our proposed method in this paper outperforms some of the current general processing approaches used to process out-of-order RFID event streams.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.975-982
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• 2009

In this paper, we propose a novel mixing algorithm for multiple video streams, which can guarantee low complexity and low end-to-end delay. In the propose algorithm, we change the syntax bitstream in the compressed domain. And we mix the H.264/AVC video streams by coded slice unit. The syntax bitstream for a mixing changes according to the arrangement of videos streams in which it organizes the mixing screen layout. Experimental results show more than 4 video streams could be mixed at high speed. Moreover, it could display in the player which it supports the standard H.264/AVC without the picture quality loss.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.3
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• pp.69-81
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• 2006

In this paper, an adaptive algorithm is proposed in streaming MPEG-4 contents with fluctuating resource amount such as throughput of network conditions. In the area of adaptive streaming issue, a lot of researches have been made on how to represent encoded media(such as video) bitstream in scalable way. By contrast, MPEG-4 supports object-based multimedia content which is composed of various types of media streams such as audio, video, image and other graphical elements. Thus, it can be more effective to provide individual media streams in scalable way for streaming object-based content to heterogeneous environment. The proposed method provides the multiple media streams corresponding to an object with different qualities and bit rate in order to support object based scalability to the MPEG-4 content. In addition, an optimal selection of the multiple streams for each object to meet a given constraint is proposed. The selection process is adopted a multiple choice knapsack problem with multi-step selection for the MPEG-4 objects with different scalability levels. The proposed algorithm enforces the optimal selection process to maintain the perceptual qualities of more important objects at the best effort. The experimental results show that the set of selected media stream for presenting objects meets a current transmission condition with more high perceptual quality.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.115-123
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• 2012

A video analysis system used to detect events in video streams generally has several processes, including object detection, object trajectories analysis, and recognition of the trajectories by comparison with an a priori trained model. However, these processes do not work well in a complex environment that has many occlusions, mirror effects, and/or shadow effects. We propose a new approach to a context-aware video surveillance system to detect predefined contexts in video streams. The proposed system consists of two modules: a feature extractor and a context recognizer. The feature extractor calculates the moving energy that represents the amount of moving objects in a video stream and the stationary energy that represents the amount of still objects in a video stream. We represent situations and events as motion changes and stationary energy in video streams. The context recognizer determines whether predefined contexts are included in video streams using the extracted moving and stationary energies from a feature extractor. To train each context model and recognize predefined contexts in video streams, we propose and use a new ensemble classifier based on the AdaBoost algorithm, DAdaBoost, which is one of the most famous ensemble classifier algorithms. Our proposed approach is expected to be a robust method in more complex environments that have a mirror effect and/or a shadow effect.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.407-410
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• 2010

This paper is to implement a RTSP based streaming server in order to provide streaming service. When a client requests a stream from a server, transmission speed is measured on a regular basis through communications between the client and the server. Server will send different encoded movie clip streams based on measured transmission speeds. Different streams are sent to a server depending on the transmission speed and their locations are saved when streams are sent. Even though different streams are sent, the streams will be sent without any interruptions because they are sent from their original locations.

• Journal of the Korean Society for information Management
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• v.30 no.3
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• pp.71-87
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• 2013

In this study, we analyze the agenda setting and policy making process of the establishment of Gyeonggido Cyber Library, which has played an important role for development of public libraries in Gyeonggido since its launching, based on Kingdon's policy streams model. According to the model, policy formation is described as the result from the convergence of the three streams, such as problem, policy and politics streams. When these streams converge on a specific time point, a policy window is created so that the issues become policy agenda. At this moment, policy entrepreneurs propose their alternatives, which have been prepared already, and try to pass it through the window. We identify coupling of the streams in the policy window and the role of policy entrepreneurs in the process of agenda setting and selection of alternatives of Gyeonggido Cyber Library policy. Suggestions are provided based on the analysis for public policy formation in public libraries domain.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.521-528
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• 2016

Web-based services are used widely in many computer application fields due to the increasing use of PCs and mobile devices. Accordingly, topics on the analysis of access logs generated in the application fields have been researched actively to support personalized services in the field, and analyzing techniques based on the weight differentiation of information in access logs have been proposed. This paper outlines an analysis technique for web-click streams, which is useful for finding high utility old item sets in web-click streams, whose data elements are generated at a rapid rate. Using the technique, interesting information can be found, which is difficult to find in conventional techniques for analyzing web-click streams and is used effectively in target marketing. The proposed technique can be adapted widely to analyzing the data generated in a range of computing application fields, such as IoT environments, bio-informatics, etc., which generated data as a form of data streams.

• Journal of Communications and Networks
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• v.5 no.3
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• pp.258-265
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• 2003

Transmission of continuous media streams has been a challenging problem of multimedia service. Lots of works have been done trying to figure out the best solution for this problem, and some works presented the optimal solution for transmitting the stored video using smoothing schemes applied to each individual stream. But those smoothing schemes considered only one stream, not the whole streams being serviced, to apply themselves, which could only achieve local optimum not the global optimum. Most of all, they did not exploit statistical multiplexing gain that can be obtained before smoothing. In this paper, we propose a new smoothing scheme that deals with not an individual stream but the whole streams being serviced simultaneously to achieve the optimal network bandwidth utilization and maximize the number of streams that can be serviced simultaneously. We formally proved that the proposed scheme not only provides deterministic QoS for each client but also maximizes number of clients that can be serviced simultaneously and hence achieves maximum utilization of transmission bandwidth.