• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.185-190
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• 2009

The event sequence of the same type from a set of events having time property can be summarized in one event. But if the event sequence having an interval, It is reasonable to be summarized more than one in independent sub event sequence of each other. In this paper, we suggest a method of temporal data mining that summarizes the interval events based on Allen's interval algebra and finds out interval event association rule from interval events. It provides better knowledge than others by using concept of an independent sub sequence and finding interval event association rules.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.691-700
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• 2009

An event means a flow which has a time attribute such as the a symptom of patients, an interval event has the time period between the start-time-point and the end-time-point. Although there are many studies for temporal data mining, they do not deal with discovering knowledge from interval event such as patient histories and purchase histories. In this paper, we suggest a method of temporal data mining that finds association rules of event causal relationships and predicts an occurrence of effect event based on discovered rules. Our method can predict the occurrence of an event by summarizing an interval event using the time attribute of an event and finding the causal relationship of event. As a result of simulation, this method can discover better knowledge than others by considering a lot of supports of an event and finding the significant rare relation on interval events which means an essential cause of an event, regardless of an occurrence support of an event in comparison with conventional data mining techniques.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.201-209
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• 2012

The point-based complex event processing handled an instantaneous event by using one time stamp in each event. However, the activity period of the event plays the important role in the field which is the same as the finance, multimedia, medicine, and meteorology. The point-based event is insufficient for expressing the complex temporal relationship in this field. In the application field of the real-time world, the event has the period. The events more than two kinds can be temporally overlapped. In addition, one event can include the other event. The relation about the events of kind of these can not be successive like the point-based event. This thesis designs and implements the method detecting the patterns of the complex event by using the interval-based events. The interval-based events can express the overlapping relation between events. Furthermore, it can include the others. By using the end point of beginning and end point of the termination, the operator of interval-based events shows the interval-based events. It expresses the sequence of the interval-based events and can detect the complex event patterns. This thesis proposes the algorithm using the active instance stack in order to raise efficiency of detection of the complex event patterns. When comprising the event sequence, this thesis applies the window push down technique in order to reduce the number of intermediate results. It raises the utility factor of the running time and memory.

• Journal of Industrial Technology
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• v.27 no.B
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• pp.235-243
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• 2007

Sensor network is used to obtain sensing data in various area. The interval to sense the events depends on the type of target application and the amounts of data generated by sensor nodes are not constant. Many applications exploit long sensing interval to enhance the life time of network but there are specific applications that requires very short interval to obtain fine-grained, high-precision sensing data. If the number of nodes in the network is increased and the interval to sense data is shortened, the amounts of generated data are greatly increased and this leads to increased amount of packets to transfer to the network. To transfer large amount of packets fast, it is necessary that the delay between successive packet transmissions should be minimized as possible. In Sensor network, since the Operating Systems are worked on the event driven, the Timer Event is used to transfer packets successively. However, since the transferring time of packet completely is varies very much, it is very hard to set appropriate interval. The longer the interval, the higher the delay and the shorter the delay, the larger the fail of transfer request. In this paper, we propose ESTEO which reduces the delay between successive packet transmissions by using SendDone Event which informs that a packet transmission has been completed.In ESTEO, the delay between successive packet transmissions is shortened very much since the transmission of next packet starts at the time when the transmission of previous packet has completed, irrespective of the transmission timee. Therefore ESTEO could provide high packet transmission rate given large amount of packets.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.102-105
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• 2010

Traditional Pub/Sub(Publish/Subscribe) Systems search all subscriptions that match an incoming event by broker(i.e. it is not considering the accuracy of matching between an incoming event and subscriptions and only consider that an event either matches a subscription or not). However, subscriptions that match an event may have priority, therefore, we need priority Pub/Sub system. In this paper, we define what the accuracy means in order to prioritize among subscriptions and propose the Priority Retrieval Technique based on accuracy that able to search subscriptions. The Priority Retrieval Technique is based on IS-Lists. We can search the results ordered by accuracy.

• Journal of Korean Neurosurgical Society
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• v.63 no.5
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• pp.598-606
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• 2020

Objective : The purpose of this study was to evaluate the impact of time interval between index event and stenting on the periprocedural risk of stenting for symptomatic carotid stenosis and to determine the optimal timing of stenting. Methods : This retrospective study included 491 (322 symptomatic [65.6%] and 169 asymptomatic [34.4%]) patients undergoing carotid stenting. The symptomatic patients were categorized into Day 0-3, 4-7, 8-10, 11-14, 15-21, and >21 groups according to the time interval between index event and stenting. Periprocedural (≤30 days) risk for clinical (any neurological deterioration) and radiological (new infarction on postprocedural diffusion-weighted imaging) events of stenting in each time interval versus asymptomatic stenosis was calculated with logistic regression analysis adjusted for confounders, and provided as odds ratio (OR) and 95% confidence interval (CI). Results : Overall clinical event rate (4.3%) of stenting for symptomatic carotid stenosis was higher than that for asymptomatic stenosis (1.2%; OR, 3.979 [95% CI, 1.093-14.489]; p=0.036). Stenting in Day 0-3 (13.2%; OR, 10.997 [95% CI, 2.333-51.826]; p=0.002) and Day 4-7 (8.3%; OR, 6.775 [95% CI, 1.382-33.227]; p=0.018) was associated with high risk for clinical events. However, the clinical event rates in stenting after 7 days from index event (Day 8-10, 1.8%; Day 11-14, 2.5%; Day 15-21, 0%; Day >21, 2.9%) were not different from that in stenting for asymptomatic stenosis. Overall radiological event rate (55.6%) in symptomatic stenosis was also higher than that in asymptomatic stenosis (35.5%; OR, 2.274 [95% CI, 1.553-3.352]; p<0.001). The high risk for radiological events was maintained in all time intervals (Day 0-3 : 55.3%; OR, 2.224 [95% CI, 1.103-4.627]; p=0.026; Day 4-7 : 58.3%; OR, 2.543 [95% CI, 1.329-4.949]; p=0.005; Day 8-10 : 53.6%; OR, 2.096 [95% CI, 1.138-3.889]; p=0.018; Day 11-14 : 57.5%; OR, 2.458 [95% CI, 1.225-5.021]; p=0.012; Day 15-21 : 55.6%; OR, 2.271 [95% CI, 1.099-4.764]; p=0.028; Day >21 : 54.8%; OR, 2.203 [95% CI, 1.342-3.641]; p=0.002). Conclusion : This study showed that as stenting was delayed, the periprocedural risk for clinical events decreased. The clinical event risk was high only in stenting within 7 days and comparable with that for asymptomatic stenosis in stenting after 7 days from index event, although the radiological event risk was not affected by stenting timing. Therefore, our results suggest that delayed stenting after 7 days from symptom onset is a safe strategy for symptomatic stenosis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.205-214
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• 2008

To transfer large amount of packets fast in sensor network, it is necessary that the delay between successive packet transmissions should be minimized as possible. In Sensor network, since the Operating Systems are worked on the event driven, the Timer Event is used to transfer packets successively. However, since the transferring time of packet completely is varies very much, it is very hard to set appropriate interval. If interval is too long, delay also becomes too long but if interval is too short, the fail of transfer request would increase. In this paper, we propose ESTEO which reduces the delay between successive packet transmissions by using SendDone Event which informs that a packet transmission has been completed. In ESTEO, the delay between successive packet transmissions is shortened very much since the transmission of next Packet starts at the time when the transmission of previous packet has completed, irrespective of the transmission time. Therefore ESTEO could provide high packet transmission rate given large amount of packets.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.565-570
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• 2013

Previous researches on mining sequential patterns mainly focused on discovering patterns from the point-based event. Interval events with a time interval occur in the real world that have the start and end point. Existing interval pattern mining methods that discover relationships among interval events based on the Allen operators have some problems. These are that interval patterns having three or more interval events can be interpreted as several meanings. In this paper, we propose the I_TPrefixSpan algorithm, which is an efficient sequence pattern mining technique for removing ambiguity in the Interval Patterns Mining. The proposed algorithm generates event sequences that have no ambiguity. Therefore, the size of generated candidate set can be minimized by searching sequential pattern mining entries that exist only in the event sequence. The performance evaluation shows that the proposed method is more efficient than existing methods.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.99-110
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• 2010

An event means a flow which has a time attribute such as a symptom of patient. Stream data collected by sensors can be summarized as an interval event which has a time interval between the start-time point and the end-time point in multiple stream data environment. Most of temporal mining techniques have considered only the frequent events. However, these approaches may ignore the infrequent event even if it is important. In this paper, we propose a new temporal data mining that can find association rules for the significant temporal relation based on interval events in multidimensional stream data environment. Our method considers the weight of events and stream data on the sensing time point of abnormal events. And we can discover association rules on the significant temporal relation regardless of the occurrence frequency of events. The experimental analysis has shown that our method provide more useful knowledge than other conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2535-2540
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• 2010

In traditional Publish/Subscribe system, the first procedure to deliver event from publisher to subscriber is that publisher publishes publisher's event to broker. Next step is that broker checks simple binary notion of matching : an event either matches a subscription or it does not. Lastly, broker delivers the event matched with subscriptions to the corresponding subscribers. In this system, information delivery has been accomplished in one way only. However, current some applications require two way delivery between subscriber and publisher. Therefore, we initiate an extended Publish/Subscribe system that supports two way delivery. Extended Publish/Subscribe system requires additional functions of delivering subscription to publisher and especially deciding top-n subscriptions using priority because broker might has a number of subscriptions. In this paper, we propose two priority retrieval techniques based on SIF using IS-List with deciding priority among subscriptions and defining SIF(Specific Interval First). The performance measurements show that RSO(resulting set sorting) technique results in better performance in index creation time and ITS&IS(insertion time sorting and inverse search using stack) technique results in better performance in search time.