• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.807-816
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• 2005

Sequential pattern mining finds all of the frequent sequences satisfying a minimum support threshold in a large database. However, when mining long frequent sequences, or when using very low support thresholds, the performance of currently reported algorithms often degrades dramatically. In this paper, we propose a novel sequential pattern algorithm using only closed frequent sequences which are small subset of very large frequent sequences. Our algorithm generates the candidate sequences by depth-first search strategy in order to effectively prune. using bitmap representation of underlying databases, we can effectively calculate supports in terms of bit operations and prune sequences in much less time. Performance study shows that our algorithm outperforms the previous algorithms.

• Journal of Industrial Technology
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• v.25 no.A
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• pp.163-173
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• 2005

Recent sequential pattern mining algorithms mine all of the frequent sequences satisfying a minimum support threshold in a large database. However, when a frequent sequence becomes very long, such mining will generate an explosive number of frequent sequence, which is prohibitively expensive in time. In this paper, we proposed a novel sequential pattern algorithm using only closed frequent sequences which are small subset of very large frequent sequences. Our algorithm extends the sequence by depth-first search strategy with effective pruning. Using bitmap representation of underlying databases, we can obtain a closed frequent sequence considerably faster than the currently reported methods.

• Annual Conference of KIPS
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• 2010.11a
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• pp.148-151
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• 2010

분류 기법은 데이터 마이닝 기술 중 가장 잘 알려진 방법으로서, Decision tree, SVM(Support Vector Machine), ANN(Artificial Neural Network) 등 기법을 포함한다. 분류 기법은 이미 알려진 상호 배반적인 몇 개 그룹에 속하는 다변량 관측치로부터 각각의 그룹이 어떤 특징을 가지고 있는지 분류 모델을 만들고, 소속 그룹이 알려지지 않은 새로운 관측치가 어떤 그룹에 분류될 것인가를 결정하는 분석 방법이다. 분류기법을 수행할 때에 기본적으로 특징 공간이 잘 표현되어 있다고 가정한다. 그러나 실제 응용에서는 단일 특징으로 구성된 특징공간이 분명하지 않기 때문에 분류를 잘 수행하지 못하는 문제점이 있다. 본 논문에서는 이 문제에 대한 해결방안으로써 많은 정보를 포함하면서 빈발패턴에 대한 정보의 순실이 없는 닫힌 빈발패턴 기반 분류에 대한 연구를 진행하였다. 본 실험에서는 ${\chi}^2$(Chi-square)과 정보이득(Information Gain) 속성 선택 척도를 사용하여 의미있는 특징 선택을 수행하였다. 그 결과, 이 연구에서 제시한 척도를 사용하여 특징 선택을 수행한 경우, C4.5, SVM 과 같은 분류기법보다 더 향상된 분류 성능을 보였다.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.

• PNF and Movement
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• v.15 no.3
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• pp.237-246
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• 2017

Purpose: The purpose of this study was to investigate the effects of forward-and-backward shift trunk exercise using a proprioceptive neuromuscular facilitation (PNF) diagonal pattern in a closed kinematic chain exercise on the upper limb function and activity of daily living (ADL) in a stroke patient. Methods: One subject participated in this study. The study used a reversal A-B-A' design, where A and A' were the baseline period (no intervention), and B was the intervention period. The intervention was a forward-and-backward trunk shift exercise, using a PNF diagonal pattern on both a stand-on-hand position and a quadruped position of closed kinematic chain exercises, for 20 min per day for 2 weeks. The range of motion (ROM) of the shoulder joint was measured and a Fugl-Meyer assessment of upper extremity (FMA-UE) and a functional independence measure (FIM) were performed to measure upper limb function and activity of daily living (ADL). Results: ROMs of shoulder joint (flexion, extension, abduction, and external rotation) increased in the intervention phase. The FMA-UE score increased (from 28 to 36) in the intervention phase. The FIM score increased (from 20 to 25) in the intervention phase. These increases were maintained after intervention (Baseline II). Conclusion: These results suggest that forward-and-backward shift trunk exercises using a PNF diagonal pattern in a closed kinematic chain exercise have a positive effect on stroke patients' upper limb function and ADL ability.

• Journal of the Korean Society of Physical Medicine
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• v.6 no.2
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• pp.215-223
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• 2011

Purpose: The purpose of this study was to determine the effect of leg muscle activation by applying proprioceptive neuromuscular facilitation (PNF) arm patterns to unilateral upper extremities under the condition of both open and closed kinetic chains in a seated position. Methods: Twenty-two healthy subjects participated in this study. Four PNF patterns were applied to each subject's unilateral upper extremity. EMG data were collected from the vastus medialis, biceps femoris, tibialis anterior and gastrocnemius. The measured EMG data were digitized and processed to root mean square (RMS) and expressed as percentage maximal voluntary isometric contraction (%MVIC). The data were analyzed using two-way analysis of variance (ANOVA) with repeated measures to determine the statistical significance. Results: The results of this study were summarized as follows: Firstly, in comparison to muscle activation of the biceps femoris, there was a significant increase in the D2 flexion pattern when it was compared with D2 extension pattern and when it was compared with D1 flexion pattern (p<.05). Secondly, there was a significant increase in the muscle activation of the vastus medialis and tibialis anterior with a closed kinetic chain rather than an open kinetic chain (p<.05). Conclusion: In conclusion, in order to increase muscle activation of the biceps femoris, the D2 flexion pattern can be applied, regardless of kinetic chain. In addition, in order to increase muscle activation of the vastus medialis and tibialis anterior, four arm patterns can be applied with a closed kinetic chain.

• The Journal of Korean Academy of Sensory Integration
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• v.15 no.2
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• pp.46-65
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• 2017

Objective : The purpose of this research is to find clinical effects of application of weighted vest during task-oriented training focused on gross motor performance and balance abilities of children with spastic diplegia. Methods : 34 subjects were divided by simple random sampling into two groups; experimental group (male : 9, female : 8, average age : 8.12) and placebo group (male : 9, female : 9, average age : 7.53). Both two groups underwent to 40 minute intervention, twice a week for 12 weeks. The intervention was task-oriented training focused on facilitating closed kinematic chain and multi-joint functional movement pattern. During the training, the experimental group received loaded-resistance weighted vest and placebo group also received weighted vest but without loaded-resistance. Participants in both groups underwent 8 to 10 reps of the task-oriented training and there were 3 minutes break time between tasks. There were pre-test of gross motor performance and balance abilities, and two times of post-tests were performed upon 6 weeks and 12 weeks after the intervention completed. And in final, an additional follow-up test was performed 12 weeks after the evaluation was finished in order to find any difference between the two groups over time. Results : There was significant difference in Gross Motor Performance Measure (GMPM) between two groups. It is found that average score of the experimental group increased more than the placebo group after 6 weeks and 12 weeks intervention (p<.05). There was significant difference in Pediatric Berg's Balance Scale (PBS) between two groups. It is found that average score of the experimental group increased more than the placebo group after 6 weeks and 12 weeks intervention (p<.05). Conclusion : Based on the results in this study, it is proposed that application of weighted vest into task-oriented training to facilitating closed kinematic chain and multi-joint movement can improve gross motor performance and balance abilities of children with cerebral palsy.

• Journal of Korean Elementary Science Education
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• v.26 no.4
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• pp.428-439
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• 2007

The purpose of this study was to investigate the effects of reflective thinking on verbal interaction of the pre-service teachers in elementary science classes. Two pre-service teachers were selected for this study and they respectively had gave three science classes. Every science class was recorded by using video/audio but only audio data of first and last science classes were transcribed for verbal interaction analysis. The result of this study revealed that the frequency of teacher's verbal interaction in last science class was increased rather than the case of first science class. The increasing patterns of interaction frequency were affected by the teacher's viewpoint and preparation for the science class. Teacher's verbal interactions were divided into low-level and high-level for the analysis of qualitative change. Low-level interactions are which leading students' convergent thinking, high-level interactions are which leading students' divergent thinking. Also the result of this study revealed that high-level interactions in last science class were increased rather than in first class. On the other hand, low-level interactions in last class were reduced rather than in first class. Therefore, this results implied that the effects of reflective thinking on verbal interaction of pre-service teachers in elementary science classes were appeared, but the effects were also affected by teacher's individual characteristics. Especially the changing degrees of qualitative interactions varies with the teacher's viewpoint and preparation for the science class.