• 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.

• Korean Journal of Applied Biomechanics
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• v.16 no.3
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• pp.85-94
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• 2006

The purpose of this study was to analyze the kinematics variables of during forehand stroke by stance patterns. Eight high school tennis players were chosen for the study, who have never been injured for last six months, in Busan. They performed horizontal swing and vertical swing that it was done each five consecutive trial in the condition of square, open and semi-open stance. It was filmed by 6 video camera and used with 3-dimensional motion analyzer system. The following kinematic variables were analyzed in relation to angle of segment( shoulder, hip and knee joint). The conclusion were as follow: 1. The angle of hip joint represented at impact that horizontal swing was not significant difference by stance patterns but vertical swing was increased in open stance than square and semi-open stance. 2. The angle of both knee was not significant difference between all stance types and swing patterns. 3. The angle of shoulder, hip and knee joint rotation showed that open stance was increased than square and semi-open stance in all swing types and event.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.63.3-64
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• 2015

In our previous work (Kim et al., 2015), we suggested a new classification scheme, which categorizes the SPEs into four groups based on association with flare or CME inferred from onset timings as well as proton acceleration patterns using multienergy observations. In this study, we have tried to find whether there are any typical characteristics of associated events and acceleration sites in each group using 42 SPEs from 1997 to 2012. We find: (i) if the proton acceleration starts from a lower energy, a SPE has a higher chance to be a strong event (>5000pfu) even if the associated flare and CME are not so strong. The only difference between the SPEs associated with flare and CME is the location of the acceleration site. For the former, the sites are very low (~1Rs) and close to the western limb, while the latter has a relatively higher and wider acceleration sites. (ii) When the proton acceleration starts from the higher energy, a SPE tends to be a relatively weak event (<1000pfu), in spite of its associated CME is relatively stronger than previous group. (iii) The SPEs categorized by the simultaneous proton acceleration in whole energy range within 10 minutes, tend to show the weakest proton flux in spite of strong related eruptions. Their acceleration heights are very close to the locations of type II radio bursts. Based on those results, we suggest that the different characteristics of the four groups are mainly due to the different mechanisms governing the acceleration pattern and interval, and different condition such as the acceleration location.

• Journal of Biomedical Engineering Research
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• v.33 no.1
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• pp.15-24
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• 2012

Classification of human thought is an emerging research field that may allow us to understand human brain functions and further develop advanced brain-computer interface (BCI) systems. In the present study, we introduce a new approach to classify various mental states from noninvasive electrophysiological recordings of human brain activity. We utilized the full spatial and spectral information contained in the electroencephalography (EEG) signals recorded while a subject is performing a specific mental task. For this, the EEG data were converted into a 2D spatiospectral pattern map, of which each element was filled with 1, 0, and -1 reflecting the degrees of event-related synchronization (ERS) and event-related desynchronization (ERD). We evaluated the similarity between a current (input) 2D pattern map and the template pattern maps (database), by taking the inner-product of pattern matrices. Then, the current 2D pattern map was assigned to a class that demonstrated the highest similarity value. For the verification of our approach, eight participants took part in the present study; their EEG data were recorded while they performed four different cognitive imagery tasks. Consistent ERS/ERD patterns were observed more frequently between trials in the same class than those in different classes, indicating that these spatiospectral pattern maps could be used to classify different mental states. The classification accuracy was evaluated for each participant from both the proposed approach and a conventional mental state classification method based on the inter-hemispheric spectral power asymmetry, using the leave-one-out cross-validation (LOOCV). An average accuracy of 68.13% (${\pm}9.64%$) was attained for the proposed method; whereas an average accuracy of 57% (${\pm}5.68%$) was attained for the conventional method (significance was assessed by the one-tail paired $t$-test, $p$ < 0.01), showing that the proposed simple classification approach might be one of the promising methods in discriminating various mental states.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1148-1161
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• 2017

The success of a business process management system stands or falls on the quality of the business processes. Many experiments therefore have been devoting considerable attention to the modeling and analysis of business processes in process-centered organizations. One of those experiments is to apply the probabilistic theories to the analytical evaluations of business process models in order to improve their qualities. In this paper, we excogitate a conceptual way of applying a probability theory of proportions into modeling business processes. There are three types of routing patterns such as sequential, disjunctive, conjunctive and iterative routing patterns in modeling business processes, into which the proportion theory is applicable. This paper focuses on applying the proportion theory to the disjunctive routing patterns, in particular, and formally named proportional information control net that is the formal representation of a corresponding business process model. In this paper, we propose a conceptual approach to discover a proportional information control net from the enactment event histories of the corresponding business process, and describe the details of a series of procedural frameworks and operational mechanisms formally and graphically supporting the proposed approach. We strongly believe that the conceptual approach with the proportional information control net ought to be very useful to improve the quality of business processes by adapting to the reengineering and redesigning the corresponding business processes.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.272-277
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• 2008

Functional MRI technique was used in this study for examining the language switching mechanisms between the first language (L1) and the second language (L2). Language switching mechanism is regarded as a complex task that involves an interaction between L1 and L2. The aim of study is to find out the brain activation patterns during the phonological process of reading real English words and English words written in Korean characters in a bilingual person. Korean-English bilingual subjects were examined while they covertly read four types of words native Korean words, Korean words of a foreign origin, English words written in Korean characters, and English words. The fMRI results reveal that the left hemispheric language-related regions at the brain, such as the left inferior frontal, superior temporal, and parietal cortices, have a greater response to the presentation of English words written in Korean characters than for the other types of words, in addition, a slight difference was observed in the occipital-temporal lobe. These results suggest that a change in the brain circuitry underlying the relational processes of language switching is mainly associated with general executive processing system in the left prefrontal cortex rather than with a similarity-based processing system in the occipital-temporal lobes.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.838-842
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• 2007

A brain-computer interface(BCI) system is a communication channel which transforms a subject's thought process into command signals to control various devices. These systems use electroencephalographic signals or the neuronal activity of many single neurons. The presented study deals with an efficient analysis method of neuronal signals from a BCI System using an independent component analysis(ICA) algorithm. The BCI system was implemented to generate event signals coding movement information of the subject. To apply the ICA algorithm, we obtained the perievent histograms of neuronal signals recorded from prefrontal cortex(PFC) region during target-to-goal(TG) task trials in the BCI system. The neuronal signals were then smoothed over 5ms intervals by low-pass filtering. The matrix of smoothed signals was then rearranged such that each signal was represented as a column and each bin as a row. Each column was also normalized to have a unit variance. As a result, we verified that different patterns of the neuronal signals are dependent on the target position and predefined event signals.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2010.05a
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• pp.48-54
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• 2010

INTRODUCTION Interaction between temporal events at the millisecond level is important for visual and tactile interaction. OBJECT The aim of the present study is to identify any neural signature, as reflected in event-related potentials (ERP), for the integrative processes when the two sensory modalities are stimulated in synchrony as opposed to when they are stimulated separately. METHOD The basic strategy was to compare ERP signals obtained with simultaneous visual and tactile stimulation with a linear summation of ERP patterns obtained with each modality stimulated separately. Condition were presented, paired with various stimulus-onset-asynchronies (SOA) ranging from - 300 ms (tactile-first) to 300 ms (visual-first), and in trials where only one modality was stimulated alone. RESULT A positive deviation was located in observed ERP at C4 electrode (contralateral to the stimulated hand) at 200-400 ms, in comparison to the predicted ERP. The deviation was present at all SOAs other than -300ms (tactile-first) and 300 ms (visual-first). There was also a positive deviation at occipital leads at the 50-ms SOA (visual-first) trials. DISCUSSION It suggested that neural signatures of cross-modal integration occur within a limited time-window. The deviations were specifically localized at the contralateral somatosensory and visual cortices, indicating that the integration happens at or before the level of the primary cortices.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.147-156
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• 2006

Event logging plays increasingly an important role in system and network management, and syslog is a de-facto standard for logging system events. However, due to the semi-structured features of Common Log Format data most studies on log analysis focus on the frequent patterns. The extensible Markup Language can provide a nice representation scheme for structure and search of formatted data found in syslog messages. However, previous XML-formatted schemes and applications for system logging are not suitable for semantic approach such as ranking based search or similarity measurement for log data. In this paper, based on ranked keyword search techniques over XML document, we propose an XML tree structure through a new data modeling approach for syslog data. Finally, we show suitability of proposed structure for semantic retrieval.

• 한국신재생에너지학회:학술대회논문집
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• 2011.11a
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• pp.149.1-149.1
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• 2011

신재생에너지 산업의 인수합병은 2010년, 전년 대비 70%가 증가하였고 이런 추이는 2011년에도 계속되고 있어 신재생에너지 인수합병 효과에 대한 심도 있는 분석과 이를 바탕으로 한 적절한 정책과 전략이 요구되고 있다. 본 연구에서는 인수합병 유형이 신재생에너지 기업의 가치에 미치는 영향을 주가를 이용하여 한 사건이 기업의 가치에 미치는 영향을 평가하는 통계학적 방법인 사건연구(event study) 방법을 통해 분석하였다. 인수합병 유형의 구분은 (1) 같은 신재생에너지원 산업 내 인수합병(수직형 기업결합), (2) 다른 신재생에너지원 산업의 기업 간 인수합병(수평형 기업결합), (3) 대형에너지 기업과 신재생에너지 기업 간 인수합병(수평형 기업결합), (4) 관련이 없는 이종 기업 간 이루어지는 인수합병(혼합형 기업결합) 총 네 유형으로 구분하였다. 분석결과 수평형 기업결합 ( horizontal merger)은 두 경우 모두 인수합병의 효과가 통계적으로 유의하지 않은 것으로 파악되었으며 혼합형 기업결합(conglomerate merger)과 수직형 기업결합(vertical merger)이 유의한 효과가 있는 것으로 나타났다. 특히 에너지산업 외부의 기업이 신재생에너지 기업을 인수하였을 때 그 효과가 가장 큰 것으로 나타났는데 이는 변동성이 매우 큰 신재생에너지 산업에 특성이 반영된 결과인 것으로 판단된다.