• Title/Summary/Keyword: Human Attention

Search Result 1,522, Processing Time 0.034 seconds

Analysis of the Effect on Attention and Relaxation Level by Correlated Color Temperature and Illuminance of LED Lighting using EEG Signal (뇌파 분석을 통한 LED조명의 색온도와 조도가 집중도와 이완도에 미치는 영향 분석)

  • Shin, Ji-Yea;Chun, Sung-Yong;Lee, Chan-Su
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
    • /
    • v.27 no.5
    • /
    • pp.9-17
    • /
    • 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).

The Effect of Coordination of Earring, Neckline, and Hairstyle on Image (귀걸이, 네크라인, 헤어스타일의 코디네이션이 이미지에 미치는 영향)

  • Jung, Su-Jin;Choi, Su-Koung
    • Korean Journal of Human Ecology
    • /
    • v.18 no.2
    • /
    • pp.535-545
    • /
    • 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.

Study on Dietary Factors Associated with Characteristics of Attention Deficit Hyperactivity Disorder (일부 초등학생에서 주의력결핍 과잉행동 성향과 관련된 식이요인)

  • Koo, Nam-Sun;Koo, Kyeong-Ok;Chung, Jayong
    • Journal of the Korean Society of Food Culture
    • /
    • v.27 no.5
    • /
    • pp.544-551
    • /
    • 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.

A Review of Cognitive Aspects of Air Traffic Controllers from a Psychological Perspective (심리학으로 바라본 항공교통관제사 인지능력)

  • Kwon, Hyuk-Jin
    • Journal of the Korean Society for Aviation and Aeronautics
    • /
    • v.22 no.4
    • /
    • pp.34-41
    • /
    • 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.

Attention-LSTM based Lane Change Possibility Decision Algorithm for Urban Autonomous Driving (도심 자율주행을 위한 어텐션-장단기 기억 신경망 기반 차선 변경 가능성 판단 알고리즘 개발)

  • Lee, Heeseong;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
    • /
    • v.14 no.3
    • /
    • pp.65-70
    • /
    • 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.

Multimodal Attention-Based Fusion Model for Context-Aware Emotion Recognition

  • Vo, Minh-Cong;Lee, Guee-Sang
    • International Journal of Contents
    • /
    • v.18 no.3
    • /
    • pp.11-20
    • /
    • 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.

SERADE: Section Representation Aggregation Retrieval for Long Document Ranking (SERADE : 섹션 표현 기반 문서 임베딩 모델을 활용한 긴 문서 검색 성능 개선)

  • Hye-In Jung;Hyun-Kyu Jeon;Ji-Yoon Kim;Chan-Hyeong Lee;Bong-Su Kim
    • Annual Conference on Human and Language Technology
    • /
    • 2022.10a
    • /
    • pp.135-140
    • /
    • 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.

  • PDF

Participation by Community Volunteers and Strategies for the Efficient Use of Human Resources

  • Cho, Woo-Hong
    • Journal of the Korea Society of Computer and Information
    • /
    • v.22 no.2
    • /
    • pp.127-132
    • /
    • 2017
  • Volunteer services in communities work to provide human and material resources needed in social welfare centers and help the centers efficiently and effectively respond to diverse needs in society as well as provide quality services to clients. With this in mind, this study presents a few political suggestions on their utilization. First, potential volunteer development should be done in communities. Second, users of diverse volunteering services should be developed. Third, centers should pay attention to promotion of volunteers and the volunteers should be completely educated before services are rendered.

Improved Inference for Human Attribute Recognition using Historical Video Frames

  • Ha, Hoang Van;Lee, Jong Weon;Park, Chun-Su
    • Journal of the Semiconductor & Display Technology
    • /
    • v.20 no.3
    • /
    • pp.120-124
    • /
    • 2021
  • Recently, human attribute recognition (HAR) attracts a lot of attention due to its wide application in video surveillance systems. Recent deep-learning-based solutions for HAR require time-consuming training processes. In this paper, we propose a post-processing technique that utilizes the historical video frames to improve prediction results without invoking re-training or modifying existing deep-learning-based classifiers. Experiment results on a large-scale benchmark dataset show the effectiveness of our proposed method.

A Saliency-Based Focusing Region Selection Method for Robust Auto-Focusing

  • Jeon, Jaehwan;Cho, Changhun;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
    • /
    • v.1 no.3
    • /
    • pp.133-142
    • /
    • 2012
  • This paper presents a salient region detection algorithm for auto-focusing based on the characteristics of a human's visual attention. To describe the saliency at the local, regional, and global levels, this paper proposes a set of novel features including multi-scale local contrast, variance, center-surround entropy, and closeness to the center. Those features are then prioritized to produce a saliency map. The major advantage of the proposed approach is twofold; i) robustness to changes in focus and ii) low computational complexity. The experimental results showed that the proposed method outperforms the existing low-level feature-based methods in the sense of both robustness and accuracy for auto-focusing.

  • PDF