• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.486-503
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• 2023

Logs play an important role in mastering the health of the system, experienced operation and maintenance engineer can judge which part of the system has a problem by checking the logs. In recent years, many system architectures have changed from single application to distributed application, which leads to a very huge number of logs in the system and manually check the logs to find system errors impractically. To solve the above problems, we propose a method based on Message Middleware and ATT-GRU (Attention Gate Recurrent Unit) to detect the logs anomaly of distributed systems. The works of this paper mainly include two aspects: (1) We design a high-performance distributed logs collection architecture to complete the logs collection of the distributed system. (2)We improve the existing GRU by introducing the attention mechanism to weight the key parts of the logs sequence, which can improve the training efficiency and recognition accuracy of the model to a certain extent. The results of experiments show that our method has better superiority and reliability.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.40-43
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• 2018

대화 발화 예측(Next Utterance Classification)은 Multi-turn 대화에서 마지막에 올 발화를 정답 후보들 중에서 예측을 하는 연구이다. 기존에 제안된 LSTM 기반의 Dual Encoder를 이용한 모델에서는 대화와 정답 발화에 대한 관계를 고려하지 않는 문제와 대화의 길이가 너무 길어 중간 정보의 손실되는 문제가 존재한다. 본 연구에서는 이러한 두 문제를 해결하기 위하여 ESIM구조를 통한 단어 단위의 attention, 대화의 turn별 문장 단위의 attention을 제안한다. 실험 결과 총 5000개의 검증 대화 데이터에 대하여 1 in 100 Recall@1의 성능이 37.64%로 기존 모델 대비 약 2배 높은 성능 향상을 나타내었다.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.31-34
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• 2018

대화 시스템에서 사람과 기계와의 모든 발화에서 발생하는 상황들을 모두 규칙화할 수 없기 때문에 자연스러운 대화가 단절되는 breakdown 현상이 빈번하게 일어날 수 있다. 이런 현상이 발생하는 이유는 다음과 같다. 첫째, 대화에서는 다양한 도메인이 등장하기 때문에 시스템이 커버할 수 있는 리소스가 부족하며, 둘째, 대화 데이터에서 학습을 위한 annotation되어 있는 많은 양의 코퍼스를 보유하기에는 한계가 있으며, 모델에 모든 대화 흐름의 히스토리를 반영하기 어렵다. 이런 한계점이 존재함에도 breakdown detection은 자연스러운 대화 시스템을 위해서는 필수적인 기능이다. 본 논문은 이런 이슈들을 해소하기 위해서 memory attention기반의 새로운 모델을 제안하였다. 제안한 모델은 대화내에 발화에 대해 memory attention을 이용하여 과거 히스토리가 반영되기 때문에 자연스러운 대화흐름을 잘 detection할 수 있으며, 기존 모델과의 성능비교에서 state-of-the art 결과를 도출하였다.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2010.05a
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• pp.13-17
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• 2010

Consciousness is really regarded as too ambiguous a concept to be understood and accepted as a mental construct without the inclusion of memory and attention in any conceptualization. However we need one criterion to count satisfactorily as an explanation of consciousness in information processing. An operational working definition of consciousness could be made in comparison of memory and attention: Consciousness would be a subjective awareness of momentary experience and also have the characteristics of an operating system performing control and consolidation information processing. This could be called a cognitive consciousness. It is possible that some distinctions between consciousness, memory and attention can be made conceptually and functionally from the perspectives of information processing.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.3
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• pp.219-230
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• 2022

In implementing a robust automatic target recognition(ATR) system with synthetic aperture radar(SAR) imagery, one of the most important issues is accurate classification of target variants, which are the same targets with different serial numbers, configurations and versions, etc. In this paper, a deep learning network with channel attention modules is proposed to cope with the recognition problem for target variants based on the previous research findings that the channel attention mechanism selectively emphasizes the useful features for target recognition. Different from other existing attention methods, this paper employs the channel attention modules without dimensionality reduction along the channel direction from which direct correspondence between feature map channels can be preserved and the features valuable for recognizing SAR target variants can be effectively derived. Experiments with the public benchmark dataset demonstrate that the proposed scheme is superior to the network with other existing channel attention modules.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.306-308
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• 2006

We propose an attention based object recognition system, to recognize object fast and robustly. For this we calculate visual stimulus degrees and make saliency maps. Through this map we find a strongly attentive part of image by stimulus degrees, where local features are extracted to recognize objects.

• Journal of Oriental Neuropsychiatry
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• v.21 no.4
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• pp.79-97
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• 2010

Objectives : The objective of this study is to investigate the effects of Jajun-maum-dom-movement program on the attention and hyperactivity of middle school students, Methods: Jajun-maum-dom-movement program was applied to 14 middle school students for 8 weeks, To measure the improvement of attention and decrease of hyperactivity, these tests were used - ADHD Diagnostic System(hereinafter ADS), Parent's Abbreviated Conners Rating Scale(hereinafter ACRS), Teacher's Korean ADHD Rating Scale(hereinafter K-ARS). For each variable in the 3 test methods, the results of before and after program were measured and then, the results were assessed by paired t-test, Interrelations between the resulted values of 10 variables were analyzed in these three groups: scores before program, scores after program, and change in scores before and after program, Among 10 variables, for variable showing significant difference by t-test, it was assessed by ANCOVA whether change in scores before and after program is affected by the grade and gender. Results: As for the changed score between before-the-program and after-the-program, in the ADS test, it was found that there is a significant effect in the "commission error" which is one of the indices showing the degree of hyperactivity, and "sensitivity(d')" which is one of the indices showing attention, and it was found that there is a significant effect in ACRS and K -ARSC total), Among the correlations of the 4 variables, "ACRS" and "K-ARSC total) ", which show the comprecessive criteria, have the positive correlation of significance in before-the-program, after-the-program and the changed score between before-the-program and after-the-program, However, there was no specific correlations among sub-variables about attention or hyperactivity, and in all of 4 variables, there was no significant degree of change according to grade or gender. Conclusions : As the results of assessment by ADHD Diagnostic System, Parent's Abbreviated Conners Rating Scale, Teacher's Korean ADHD Rating Scale to study the effects of Jajun-maum-dom-movement program on attention and hyperactivity, it is known that the program is helpful for improvement of attention and decrease of hyperactivity for the participated students.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.501-506
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• 2024

Humans have been shown to engage in multitasking behavior when searching for information on two or more topics or searching an information system at the same time. When processing multiple information tasks, priorities must be established as there are cognitive and physical limitations in processing multiple information tasks at once. The level of cognitive attention involved in multitasking behavior can vary depending on the complexity and importance of the information task. The objectives of this study are to understand: (a) the relationship between attention and information task prioritization behavior when people interact with information retrieval systems to find information for multiple tasks; (b) The effect of the degree of attention on information task prioritization behavior when people interact with an IR system to find information for multiple tasks. A review of the relevant literature shows that when people interact with information retrieval systems to find information for multiple tasks, their level of attention affects how they prioritize multiple information tasks. It should be noticed that people pay more attention to things they find interesting or important. Human-centered system design based on a conceptual understanding of multitasking is discussed.

• Journal of Korean Physical Therapy Science
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• v.13 no.3
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• pp.77-84
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• 2006

The purpose of this study is to introduce the effect of attentional focus on performance of task. Previous studies has shown that motor learning can be enhanced by directing performers's attention to the effects of their movements(external focus), rather than to the body movement producing the effects(internal focus). Wulf and colleagues have invoked the 'constrained action hypothesis' to explain the comparative benefits of adopting an external rather than an internal focus of attention. This hypothesis proposed that when performers utilize an internal focus of attention, they may actually constrain or interfere with automatic control processes that would normally regulate the movement, whereas an external focus of attention allows the motor system to more naturally self-organize. Electromyography(EMG) was used to determine neuromuscular correlates of external versus internal focus differences. EMG activity was lower with an external relative to an internal focus. This suggest that an external focus of attention enhances movement economy, and presumably reduces 'noise' in the motor system that hampers fine movement control. Focusing on a more remote effect seems to facilitate the discriminability of the effect from the body movements that produced it and to be more beneficial than focusing on a very close effects. There might be an optimal distance of the effect, at which ti wis easily distinguishable from the body movement but at which it is also still possible for the performer to relate this effect to the movement techniques. Future Studies of motor learning of patient need to accommodate these new finding and account for the role of the learner's attentional focus and its influencing on learning.

• Journal of Sensor Science and Technology
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• v.13 no.2
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• pp.144-151
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• 2004

In this paper, we propose an active stereo surveillance system with human-like convergence function. The proposed system uses a bottom-up saliency map model with the human-like selective attention visual function to select an interesting region in each camera. and this system compares the landmarks whether the selective region in each camera finds a same region. If the left and right cameras successfully find a same landmarks, the implemented vision system focuses on the landmark. Using the motor encoder information, we can automatically obtain the depth information and resultantly construct a depth map using the depth information. Computer simulation and experimental results show that the proposed convergence method is very effective to implement the active stereo surveillance system.