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유아의 가장 개념과 틀린 믿음 이해의 발달 및 그 상호관계 연구 (The Development of False Beliefs and Concepts of Pretense in Young Children)

  • 이종숙;이영자;신은수
    • 아동학회지
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    • 제23권4호
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    • pp.1-20
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    • 2002
  • The subjects of this study of the development of concepts of pretense and of false beliefs were 168 3-, 4-, 5-, and 6-year-olds. There were 2 significant main effects for age and type of task both for pretend and false belief tasks. The older children performed pretend tasks and false belief tasks at a higher level than the younger children. Performance on pretend tasks was higher with alternatives than without them. On false belief tasks, there were differences in performance among the change of location, the change of content and the second order false belief tasks. Correlations between understanding of pretense and false beliefs were relatively high. These results suggest that the relationship between children's understanding of pretense and false belief varied by types of tasks.

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Framework for False Alarm Pattern Analysis of Intrusion Detection System using Incremental Association Rule Mining

  • Chon Won Yang;Kim Eun Hee;Shin Moon Sun;Ryu Keun Ho
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.716-718
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    • 2004
  • The false alarm data in intrusion detection systems are divided into false positive and false negative. The false positive makes bad effects on the performance of intrusion detection system. And the false negative makes bad effects on the efficiency of intrusion detection system. Recently, the most of works have been studied the data mining technique for analysis of alert data. However, the false alarm data not only increase data volume but also change patterns of alert data along the time line. Therefore, we need a tool that can analyze patterns that change characteristics when we look for new patterns. In this paper, we focus on the false positives and present a framework for analysis of false alarm pattern from the alert data. In this work, we also apply incremental data mining techniques to analyze patterns of false alarms among alert data that are incremental over the time. Finally, we achieved flexibility by using dynamic support threshold, because the volume of alert data as well as included false alarms increases irregular.

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점진적 마이닝 기법을 적용한 침입탐지 시스템의 오 경보 분석 프레임워크 설계 (A Design of false alarm analysis framework of intrusion detection system by using incremental mining method)

  • 김은희;류근호
    • 정보처리학회논문지C
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    • 제13C권3호
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    • pp.295-302
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    • 2006
  • 침입탐지 시스템은 실시간으로 공격행위에 대하여 다량의 경보를 기록한다. 이들 경보 중에는 실제 공격 경보뿐만 아니라 공격으로 잘못 탐지하여 발생된 오 경보들도 있다. 오 경보는 침입탐지 시스템의 효율성을 저하시키는 주요요인이 되므로, 이 논문에서는 오경보 분석을 위한 프레임워크를 제안한다. 또한 지속적으로 증가하는 오 경보를 분석하기 위해 점진적 데이터 마이닝 기법을 적용한다. 제안한 오경보 분석 프레임워크는 GUI, DB Manager, Alert Preprocessor, False Alarm Analyzer로 구성되어 있다. 우리는 실험을 통해 증가하는 오경보를 분석하고, 분석된 오경보 규칙을 침입탐지 시스템에 적용하여 오 경보가 감소됨을 확인하였다.

침입탐지 시스템에서 Alert 의 패턴 학습을 이용한 False Positive 감소에 대한 연구 (Research on False Positive Alert reduction using pattern matching technique)

  • 심철준;곽주현;원일용;이창훈
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2003년도 춘계학술발표논문집 (하)
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    • pp.1997-2000
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    • 2003
  • False Positive Alert 은 IDS 가 공격이 아닌 것을 공격으로 잘못 판단하는 것이다 이러한 false Positive 는 시스템에 직접적인 피해를 주지는 않으나, 시스템 관리자가 적절한 대처를 하기 어렵게 하므로 IDS의 새로운 문제점으로 대두되고 있다. 본 논문에서는 이러한 false Positive를 줄이기 위해 IDS 에서 나오는 Alert 중 False Positive를 필터링 하는 방법에 대해 제시한다. 공격에 대한 Alert과 False Positive Alert의 시간 패턴을 각각 분석, 학습함으로써 그 후의 Alert의 False Positive 여부를 판별한다.

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발성시 가성대 형태와 양성 성대 질환의 연관성에 대한 연구 (The Relationship between Movements of False Vocal Folds on Phonation and Benign Vocal Folds Lesions)

  • 안철민;최영화;김향초
    • 대한후두음성언어의학회지
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    • 제13권1호
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    • pp.40-44
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    • 2002
  • Background and Objectives : Vocal abuse and misuse and muscle tension dysphonia that have various movements of false vocal folds may be related to the development of benign vocal folds lesions, such as vocal nodules, polyps, and cysts. This study was designed to determine whether benign vocal folds lesions were related with movements of false vocal folds on phonation. Material and Methods : One Hundred and seventy eight subjects were studied. All subjects received otolaryngological evaluation including videostroboscopy, objective voice measures. Patients were diagnosed as normal shape of vocal folds (group a), approximation of bilateral false vocal folds (group b), approximation of unilateral false vocal folds (group c), lateralized extension of false vocal folds (group d), and medialized approximation of posterior false vocal folds (group e). We analyzed the results of benign vocal folds lesions in each group. Results : Differences were found between the normal shaped group and the abnormal shaped group. No differences were found between each abnormal groups except group d and e. Conclusion : The shape of false vocal folds was related to the benign vocal folds lesions.

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현실에 대한 정보가 3, 4, 5세 유아의 틀린 믿음 과제 수행 및 정당화 추론에 미치는 영향 (False Belief Understanding and Justification Reasoning according to Information of Reality amongst Children Aged 3, 4 and 5)

  • 김유미;이순형
    • 아동학회지
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    • 제36권5호
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    • pp.135-153
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    • 2015
  • The purpose of this study was to investigate false belief understanding and justification reasoning according to information of reality amongst children aged 3, 4 and 5. Children aged 3 to 5 years (N = 176) participated in this study. Each child was interviewed individually and responded to questions designed to measure his/her false belief understanding. Every child responded to the false belief task under two different information conditions of reality(reality known vs reality unknown). For more specific analysis, children's reasoning responses were also recorded. The major findings of this study are as follows. Children could understand false belief more easily under reality unknown conditions. Specifically, the influences of information conditions were crucial to 3-year-olds but not to 4- and 5-year-olds. Although 3 year olds were able to avoid the systematical errors inherent in the false belief task, they still did not understand the false belief itself. This study provides specific aspects of false belief understanding and its relevance to general changes in cognitive development.

갑상연골 내굴곡에 인한 가성대의 비대 (False Vocal Fold Hypertrophy Caused by Thyroid Cartilage Inward Bowing)

  • 권진호;최병일;홍현준;최홍식
    • 대한후두음성언어의학회지
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    • 제24권1호
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    • pp.51-54
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    • 2013
  • False vocal fold hypertrophy caused by diverse pathologic lesion, such as laryngeal amyloidosis, laryngeal lipidosis, laryngocele, saccular cyst and sulcus vocalis. False vocal fold hypertrophy, however, is also caused laryngeal structure deformity, irrespective of pathologic lesions. In this article, we report some cases of false vocal fold hypertrophy caused by inward bowing of thyroid cartilage. At the clinic of the department of otorhinolaryngology in Gangnam Severance Hospital, with 3 male complained of hoarseness as subjects, and comfirmed of false vocal fold hypertrophy using the stroboscopy and larynx CT we checked vocal fold and laryngeal structure. Three patients with apparent hypertrophy of false vocal fold were investigated with computerized tomography (CT). In all patients, marked concavity of thyroid cartilage was revealed in CT scan at the level of the false vocal fold, and this deformity of the thyroid cartilage seemed to cause a protrusion of false vocal fold which taken as hypertrophy in stroboscopy. Careful palpation of the larynx and a CT scan taken at the level of the false vocal fold should be useful in determining whether hypertrophy of the false vocal fold is pathologic. For the next articles, It is necessary to discuss for the cause, diagnosis, treatment and prevention of inward bowing of thyroid cartilage.

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온사이트 지진조기경보를 위한 딥러닝 기반 실시간 오탐지 제거 (Deep Learning-Based, Real-Time, False-Pick Filter for an Onsite Earthquake Early Warning (EEW) System)

  • 서정범;이진구;이우동;이석태;이호준;전인찬;박남률
    • 한국지진공학회논문집
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    • 제25권2호
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    • pp.71-81
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    • 2021
  • This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

유아의 다양한 마음 상태에 대한 이해 발달과 과제 유형에 따른 틀린 믿음 이해 (Children's Understanding of Various Mental States and False-Belief by Types of Tasks)

  • 송영주
    • 아동학회지
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    • 제29권1호
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    • pp.257-273
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    • 2008
  • This study examined the development of children's theory of mind by types of false-belief tasks and various mental states. Seventy six 3-, 4-, 5- and 6-year olds were asked to infer others' minds or choose other's behaviors. Ten tasks, including two picture book tasks, were used to tap the children's understanding of various mental states. Results showed that children did well in their understanding of diverse perception and desire, but they did poorly in emotional inference based on false-belief, and second order false-belief. Children performed better in picture book tasks than in classical tasks for the understanding of false-belief and false-belief based emotion.

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The network model for Detection Systems based on data mining and the false errors

  • Lee Se-Yul;Kim Yong-Soo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권2호
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    • pp.173-177
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    • 2006
  • This paper investigates the asymmetric costs of false errors to enhance the detection systems performance. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of probe detection is enhanced by considering the costs of false errors.