• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.409-416
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• 2013

Attention is one of important cognitive functions in human affecting on the selectional concentration of relevant events and ignorance of irrelevant events. The discrimination of attentional and inattentional status is the first step to manage human's attentional capability using computer assisted device. In this paper, we newly combine the non-linear recurrence pattern analysis and spectrum analysis to effectively extract features(total number of 13) from the electroencephalographic signal used in the input to classifiers. The performance of diverse types of attention-inattention classifiers, including supporting vector machine, back-propagation algorithm, linear discrimination, gradient decent, and logistic regression classifiers were evaluated. Among them, the support vector machine classifier shows the best performance with the classification accuracy of 81 %. The use of spectral band feature set alone(accuracy of 76 %) shows better performance than that of non-linear recurrence pattern feature set alone(accuracy of 67 %). The support vector machine classifier with hybrid combination of non-linear and spectral analysis can be used in later designing attention-related devices.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.124-130
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• 2017

This study is aimed to find out whether there is difference in the physiological change of a human body according to the illumination and color of interior space or not and to specify the effect of the condition of illumination and color, respectively on the attention. In order to do so, White and Green were selected for colors and 4,000k, 5,000k, and 6000k were done for color temperature, and then attention was identified. Examining the results, the more color temperature increased, the more attention improved (P < 0.05), and in the case of EEG, ${\alpha}$ wave decreased while performing the task of attention (P < 0.01), and ${\beta}$ wave decreased more in Green than White in color condition, and it increased more in 4,000k than 5,000k and 6,000k (p < 0.05) in color temperature condition. To sum up, color condition didn't contribute to the attention much, in the case of color temperature, when it is 6,000k, it is judged that it helped to improve attention. It is considered that relaxation contributed to improving attention, as ${\beta}$ wave and sympathetic nerve decreased in 6,000k (p < 0.05). It is judged that the relaxation of tensions which happened due to a beta wave and the reduction of sympathetic nervous system activity in 6,000k, a condition of high color temperature, contributed to the improvement of concentration. In further researches, it is intended that a test will be conducted for the subjects of different ages, and the correlation between color temperature and color stimulation and the influence of them on human body would be observed in subdivided, various test conditions through various color temperature and color stimulation.

• ETRI Journal
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• v.36 no.2
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• pp.253-263
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• 2014

In the near future, traditional narrow and fixed viewpoint video services will be replaced by high-quality panorama video services. This paper proposes a visual-attention-aware progressive region of interest (RoI) trick mode streaming service (VA-PRTS) that prioritizes video data to transmit according to the visual attention and transmits prioritized video data progressively. VA-PRTS enables the receiver to speed up the time to display without degrading the perceptual quality. For the proposed VA-PRTS, this paper defines a cutoff visual attention metric algorithm to determine the quality of the encoded video slice based on the capability of visual attention and the progressive streaming method based on the priority of RoI video data. Compared to conventional methods, VA-PRTS increases the bitrate saving by over 57% and decreases the interactive delay by over 66%, while maintaining a level of perceptual video quality. The experiment results show that the proposed VA-PRTS improves the quality of the viewer experience for interactive panoramic video streaming services. The development results show that the VA-PRTS has highly practical real-field feasibility.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.5
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• pp.9-17
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• 2013

Preferred combinations of illuminance and color temperature of lighting depend on daily living activities. We investigated whether the illumination stimuli of LED lighting can enhance attention and relaxation level by controlling color temperature and illuminance level according to activities. Illuminations and color temperatures of LED flat panels are controlled in accordance with activities such as office work and resting. The attention and relaxation level under the task specific lightings are compared with those under normal lighting condition. Single channel EEG signals from the NeuroSky's Mindset are used to estimate attention and relaxation level of human subjects under different lighting conditions. Experiment results show that high color temperature with high illuminance of LED lightings (6600K, 800lx) shows improved attention level compared with conventional lighting conditions (4000K, 500lx).

• Korean Journal of Human Ecology
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• v.18 no.2
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• pp.535-545
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• 2009

The purpose of this study is to investigate the effect of earring(nothing, small, medium, large), neckline(round, low), and hairstyle(bound, unbound) on image formation. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 16 pictures manipulated with the combination of earring, neckline, and hairstyle. The objects of the study were 192 female undergraduates living in Gyeongsangnam-do. The results of this study were as follows. Image factor of the stimulus was composed of 4 different components, concentration of attention, attractiveness, gracefulness, and cuteness. In the concentration of attention, earring and neckline showed independent effect. In the attractiveness, neckline showed independent effect. In the gracefulness, earring and hairstyle showed independent effect. Significant interaction effects of earring and neckline on concentration of attention, attractiveness and gracefulness were found. Interaction effects of neckline and hairstyle on cuteness were found. The study results are highly expected to be used as useful sources in developing total coordination.

• Journal of the Korean Society of Food Culture
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• v.27 no.5
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• pp.544-551
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• 2012

The purpose of this study was to investigate the dietary factors associated with characteristics of attention deficit hyperactivity disorder (ADHD) in upper-grade elementary school students. The study subjects were 397 students, and 52% of total study subjects were boys. The risk for developing ADHD was assessed by using a DSM-IV questionnaire. Boy's ADHD score was higher than that of girls (p<0.001). Subjects were divided into two groups according to the median of the ADHD score in boys and girls. The high ADHD score group showed higher frequency of skipping breakfast and a lower score for good dietary habits, as compared to the normal group. Further, the high ADHD score group showed higher frequency of processed food intake with lower frequency of vegetable intake, as compared to the normal group. These results suggest that undesirable eating habits and frequent intake of processed foods may be associated with higher risk of developing ADHD in elementary school students.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.4
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• pp.34-41
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• 2014

Aviation safety issues have drawn much attention from the international community due to the growing demand for air travel. Although it is a widely accepted fact that human-related factors are closely linked to aviation safety, there is lack of understanding what roles those factors play in aviation, in the field of air traffic control in particular. It has been reported that the role of air traffic controllers significantly affects air safety. This review will discuss cognitive aspects of expertise in air traffic control including time perception, working memory, reasoning, perception, attention, scanning/vigilance, decision making, and planning with examples of how each aspect can be dealt with in performing air traffic control duties. The relevant studies in psychology have also been briefly reviewed in the interest of enhancing understanding of characteristics of air traffic control tasks and the related human factors. This review concludes with a call for more in-depth research into cognitive factors in air traffic control.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.65-70
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• 2022

Lane change in urban environments is a challenge for both human-driving and automated driving due to their complexity and non-linearity. With the recent development of deep-learning, the use of the RNN network, which uses time series data, has become the mainstream in this field. Many researches using RNN show high accuracy in highway environments, but still do not for urban environments where the surrounding situation is complex and rapidly changing. Therefore, this paper proposes a lane change possibility decision network by adopting Attention layer, which is an SOTA in the field of seq2seq. By weighting each time step within a given time horizon, the context of the road situation is more human-like. A total 7D vectors of x, y distances and longitudinal relative speed of side front and rear vehicles, and longitudinal speed of ego vehicle were used as input. A total 5,614 expert data of 4,098 yield cases and 1,516 non-yield cases were used for training, and the performance of this network was tested through 1,817 data. Our network achieves 99.641% of test accuracy, which is about 4% higher than a network using only LSTM in an urban environment. Furthermore, it shows robust behavior to false-positive or true-negative objects.

• International Journal of Contents
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• v.18 no.3
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• pp.11-20
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• 2022

Human Emotion Recognition is an exciting topic that has been attracting many researchers for a lengthy time. In recent years, there has been an increasing interest in exploiting contextual information on emotion recognition. Some previous explorations in psychology show that emotional perception is impacted by facial expressions, as well as contextual information from the scene, such as human activities, interactions, and body poses. Those explorations initialize a trend in computer vision in exploring the critical role of contexts, by considering them as modalities to infer predicted emotion along with facial expressions. However, the contextual information has not been fully exploited. The scene emotion created by the surrounding environment, can shape how people perceive emotion. Besides, additive fusion in multimodal training fashion is not practical, because the contributions of each modality are not equal to the final prediction. The purpose of this paper was to contribute to this growing area of research, by exploring the effectiveness of the emotional scene gist in the input image, to infer the emotional state of the primary target. The emotional scene gist includes emotion, emotional feelings, and actions or events that directly trigger emotional reactions in the input image. We also present an attention-based fusion network, to combine multimodal features based on their impacts on the target emotional state. We demonstrate the effectiveness of the method, through a significant improvement on the EMOTIC dataset.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.135-140
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• 2022

최근 Document Retrieval을 비롯한 대부분의 자연어처리 분야에서는 BERT와 같이 self-attention을 기반으로 한 사전훈련 모델을 활용하여 SOTA(state-of-the-art)를 이루고 있다. 그러나 self-attention 메커니즘은 입력 텍스트 길이의 제곱에 비례하여 계산 복잡도가 증가하기 때문에, 해당 모델들은 선천적으로 입력 텍스트의 길이가 제한되는 한계점을 지닌다. Document Retrieval 분야에서는, 문서를 특정 토큰 길이 단위의 문단으로 나누어 각 문단의 유사 점수 또는 표현 벡터를 추출한 후 집계함으로서 길이 제한 문제를 해결하는 방법론이 하나의 주류를 이루고 있다. 그러나 논문, 특허와 같이 섹션 형식(초록, 결론 등)을 갖는 문서의 경우, 섹션 유형에 따라 고유한 정보 특성을 지닌다. 따라서 문서를 단순히 특정 길이의 문단으로 나누어 학습하는 PARADE와 같은 기존 방법론은 각 섹션이 지닌 특성을 반영하지 못한다는 한계점을 지닌다. 본 논문에서는 섹션 유형에 대한 정보를 포함하는 문단 표현을 학습한 후, 트랜스포머 인코더를 사용하여 집계함으로서, 결과적으로 섹션의 특징과 상호 정보를 학습할 수 있도록 하는 SERADE 모델을 제안하고자 한다. 실험 결과, PARADE-Transformer 모델과 비교하여 평균 3.8%의 성능 향상을 기록하였다.