• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.454-457
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• 2005

Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns. And calendar based on temporal association rules proposes the discovery of association rules along with their temporal patterns in terms of calendar schemas, but this approach is also adopt an Apriori-like candidate set generation. In this paper, we propose an efficient temporal frequent pattern mining using TFP-tree (Temporal Frequent Pattern tree). This approach has three advantages: (1) this method separates many partitions by according to maximum size domain and only scans the transaction once for reducing the I/O cost. (2) This method maintains all of transactions using FP-trees. (3) We only have the FP-trees of I-star pattern and other star pattern nodes only link them step by step for efficient mining and the saving memory. Our performance study shows that the TFP-tree is efficient and scalable for mining, and is about an order of magnitude faster than the Apriori algorithm and also faster than calendar based on temporal frequent pattern mining methods.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.294-304
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• 2011

Enhancing continuous queries over data streams with temporal functions and predicates enriches the expressive power of those queries. While traditional continuous queries retrieve only the values of attributes, temporal continuous queries retrieve the valid time intervals of those values as well. Correctly evaluating such queries requires the coalescing of adjacent timestamps for value-equivalent tuples prior to evaluating temporal functions and predicates. For many stream applications, the available computing resources may be too limited to produce exact query results. These limitations are commonly addressed through load shedding and produce approximated query results. There have been many load shedding mechanisms proposed so far, but for temporal continuous queries, the presence of coalescing makes theses existing methods unsuitable. In this paper, we propose a new accuracy metric and load shedding algorithm that are suitable for temporal query processing when memory is insufficient. The accuracy metric uses a combination of the Jaccard coefficient to measure the accuracy of attribute values and $\mathcal{PQI}$ interval orders to measure the accuracy of the valid time intervals in the approximate query result. The algorithm employs a greedy strategy combining two objectives reflecting the two accuracy metrics (i.e., value and interval). In the performance study, the proposed greedy algorithm outperforms a conventional random load shedding algorithm by up to an order of magnitude in its achieved accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.81-91
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• 2012

As the recent development of the ubiquitous computing environment, u-GIS is being highlighted as the core technology of the ubiquitous computing environment, and thereby, studies on spatio-temporal data are being actively conducted. In this u-GIS environment, it is still difficult for existing mobile devices to efficiently manage the massive spatio-temporal data of u-GIS that are increasing day by day. Therefore, this paper develops a spatio-temporal query processing system for mobile devices in order to solve the problem. The system provides various spatio-temporal operators to insert/delete/update/search spatio-temporal data and supports a query optimization function that uses a spatio-temporal index for the flash memory and a spatio-temporal histogram for guaranteeing query execution speed. Lastly, by applying the spatio-temporal query processing system developed in this paper to the virtual scenario, this paper has proved that the system can be utilized in various application fields necessary to process spatio-temporal data in the mobile environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.169-189
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• 2015

Detection of anomalous events from video streams is a challenging problem in many video surveillance applications. One such application that has received significant attention from the computer vision community is traffic video surveillance. In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences of video streams. The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern. In order to detect each object in every frame, the input video is first pre-processed by applying Gaussian Mixture Models. After the detection of foreground objects, the tracking is carried out using block motion estimation by the three-step search method. The primitive events of the object are represented by assigning spatial and temporal symbols corresponding to their location and time information. These primitive events are analyzed to form a temporal pattern in a sequence of video frames, representing temporal relation between various object's primitive events. This is repeated for each window of sequences, and the support for temporal sequence is obtained based on LC-STP to discover regular patterns of normal events. Events deviating from these patterns are identified as anomalies. Unlike the traditional frequent item set mining methods, the proposed method generates maximal frequent patterns without candidate generation. Furthermore, experimental results show that the proposed method performs well and can detect video anomalies in real traffic video data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6C
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• pp.471-479
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• 2008

In this paper, we propose a novel algorithm to automatically generate an RTP timestamp value that is required for the RTP packetization in order to transmit SVC video over various If networks such as Internet. Unlike the conventional single layer coding algorithms such as H.263, MPEG-4 and H.264, SVC generates a multi-layered single bitstream which is composed of a base layer and one or more enhancement layers in order to simultaneously provide temporal, spatial, and SNR scalability. Especially, in order to provide temporal scalability based on hierarchical B-picture prediction structure, the encoding (or transmission) and display order of pictures in SVC coding is completely decoupled. Thus, the timestamp value to be specified at the header of each RTP packet in video transmission does not increase monotonically according to the display time instant of each picture. Until now, no method for automatically generating an RTP timestamp when SVC video is loaded in a RTP packet has teen introduced. In this paper, a novel automatic RTP timestamp generation method exploiting the TID (temporal ID) field of the SVC NAL unit header is proposed to accommodate the SVC video transmission.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.352-357
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• 2007

This paper deals with modeling method and application of Fuzzy Discrete Event System(FDES). FDES have characteristics which Crisp Discrete Event System(CDES) can't deals with and is constituted with the events that is determined by vague and uncertain judgement like biomedical or traffic control. We proposed Real-time Fuzzy Temporal Logic Framework(RFTLF) to model Fuzzy Discrete Event System. It combines Temporal Logic Framework with Fuzzy Theory. We represented the model of traffic signal systems for intersection to have the property of Fuzzy Discrete Event System with Real-time Fuzzy Temporal Logic Framework and designed a traffic signal controller for smooth traffic flow. Moreover, we proposed the method to find the minimum-time route to reach the desired destination with information obtained in each intersection. In order to evaluate the performance of Real-time Fuzzy Temporal Logic Framework model proposed in this paper, we simulated unit-time extension traffic signal controller model of the latest signal control method on the same condition.

• Korean Journal of Cognitive Science
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• v.18 no.3
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• pp.285-303
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• 2007

Transient attention impairs observers' temporal resolution in a cued location. This detrimental effect of attention was ascribed to inhibitory connections from parvocellular to magnocellular neurons [1]. Alternatively, the difficulty might arise because attention facilitates the temporal summation of two successive stimuli. The current study examined this hypothesis by manipulating the luminance polarity of the stimuli against a background. Attention should not modulate temporal summation of two anti-polar stimuli because these are processed in separate channels. Indeed, observers judged the temporal order of two successive stimuli better in the cued location than in the uncued location when the stimuli were opposite in polarity, but temporal resolution was worse in the cued location when the stimuli had the same polarity. Thus, attentional effects on temporal resolution may be attributed to temporal summation rather than parvocellular inhibition of magnocellular activity.

• Journal of KIISE:Databases
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• v.27 no.1
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• pp.101-112
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• 2000

In Geographic Information System, spatial object can be changed in the attribute information, spatial location and the topological relation between them with the change of time. However traditional GIS deletes the old value of aspatial information and replaces them with new value. Therefore. it is difficult to manage thc history of changed spatial object and can not support the spatio-temporal queries including temporal queries. In this paper, we propose a spatio-temporal objected model to solve this problem. We implement the proposed model with spatio-temporal class using Gothic GIS tool. The historical information of an object is stored into the object itself for the effective history management. And, in order to provide the queries for the history of an object and spatio-temporal relationship, we add temporal operators, spatio-temporal operators, and spatio-temporal query operations into Gothic, and improve the facility of the Gothic.

• Ocean Science Journal
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• v.40 no.4
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• pp.201-208
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• 2005

An accurate particle tracking method for a finite difference method model is developed using a constant acceleration method. Being assumed constant temporal and spatial gradients, the new method permits temporal-spatial variability of particle velocity. Test results in a solid rotating flow show that the new method has second-order accuracy. The performance of the new method is compared with that of other methods; the first-order Euler forward method, and the second-order Euler predictor-corrector method. The new method is the most efficient method among the three. It is more accurate and efficient than the other two.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.301-306
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• 2007

The people information is distributed in various forms such as database, web page, text, and so on, where the world wide web is one of the main sources of publicly-available people information. It has a characteristic that the information on people is intrinsically temporal. Therefore, the reconstruction of the information is needed for an individual or a company to use it efficiently. In order to maintain or manage the temporal people information, it must distinguish the variable information from invariable information of people. In this paper, we propose a method that constructs an ontology based on events to manage the variable people information efficiently. In addition, we present a system which reconstructs people information that satisfies the users' demand with the ontology.