• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.496-498
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• 2023

Brain tumor segmentation problem has challenges in the tumor diversity of location, imbalance, and morphology. Attention mechanisms have recently been used widely to tackle medical segmentation problems efficiently by focusing on essential regions. In contrast, the fusion approaches enhance performance by merging mutual benefits from many models. In this study, we proposed a 3D dual fusion attention network to combine the advantages of fusion approaches and attention mechanisms by residual self-attention and local blocks. Compared to fusion approaches and related works, our proposed method has shown promising results on the BraTS 2018 dataset.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.731-751
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• 2019

This study examined the impact of various product photo features on the attention of potential consumers in online apparel retailers' environment. Recently, the method of apparel's product photo representation in online shopping stores has been changed a lot from the classic product photos in the early days. In order to investigate if this shift is effective in attracting consumers' attention, we examined the related theory and verified its effect through laboratory experiments. In particular, experiment data was collected and analyzed using eye tracking technology. According to the results of this study, it was shown that the product photos with asymmetry are more attractive than symmetrical photos, well emphasized object within a photo more attractive than partially emphasized, smiling faces are more attractive for customer than emotionless and sad, and photos with uncentered models focus more consumer's attention than photos with model in the center. These results are expected to help design internet shopping stores to gaze more customers' attention.

• Korean Institute of Interior Design Journal
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• v.25 no.2
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• pp.50-58
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• 2016

The design of children's hospitals is highly dependent on color schemes. As a space shared together by both adults and children, the design of children's hospitals require color coordination that takes account of the users' characteristics. Visual perception tracking experiment was conducted on the 2 chosen experimental images with a target group made up of adults and children, the following results were found. First, visual attention characteristics of spatial elements' colors were found. The contrast of colors were discovered to effect attention, especially the information desk region showed highest attention. Pillars are subjected to a higher attention relative to other spatial elements, it is suggested when using accent colors to use it only when it is absolutely necessary in partial areas. In contrast, floor patterns were found to be subjected to very low attention relative to other elements. Second, effects of color contrast on visual attention were uncovered. Although color contrast effects attention for both adults and children, children were found to be more effected by color contrast than adults. Especially, children's tendency to rely on color contrast for visual recognition was higher than adults. Since when using only one type on a wide surface children show higher attention on the < vivid > colors than adults, when planning a color coordination for children using < pale > colors instead of < vivid > ones in background for a large surface is seen as a more desired method to increase attention by putting emphasis on the [sharply contrasting] colors.

• Journal of the Korean Institute of Educational Facilities
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• v.26 no.3
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• pp.15-23
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• 2019

This study aims to suggest a Biophilic classroom design of high school to obtain attention restoration for students. The learning space for youth in the modern society is composed of dry artificial structures. This space is considered to be a space that can not relieve stress caused by learning. "The Attention Restoration Theory" is divided into "Directed Attention" of humans, which is the cause of fatigue and stress, and "Involuntary Attention" as a solution to it. "Involuntary Attention" takes place in a rest state and helps the brain recover when exposed to nature. And the core of "Biophilic-Design Theory" is that humans can recover physical and mental conditions when exposed to nature. The purpose of this study is to apply "The Biophilic-Design Theory" that emphasizes the importance of exposure to nature to the educational space and plan the space where the 'Attention Restoration' can be achieved. The research method is as follows. First, we review previous studies related to "The Biophilic-Design Theory" and "The Attention Restoration Theory". Second, we analyze the application examples of "The Biophilic-Design Theory" and "The Attention Restoration Theory" in domestic and foreign educational spaces. Third, the concept of educational space is set up based on the elements derived from previous studies. Finally, we propose the planning direction of classroom design based on Biophilic-Design. The following conclusions were drawn. First, The creation of the education space to restore the learner's attention requires a visual space plan that utilizes natural elements such as natural light, artificial light, plants, and natural materials that can directly experience nature. Second, the direction in which students in the classroom can be "The Attention Restoration Theory" should consider the use of indirect natural elements that bring the surrounding natural landscape into the interior. This study will be used as the baseline data for the spatial design and planning of education facilities based on Biophilic-Design.

• Journal of Korean society of Dental Hygiene
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• v.15 no.5
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• pp.805-811
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• 2015

Objectives: The purpose of the study is to investigate the relationship between self-efficacy and learning attitude according to smoking experience in the middle school students. Methods: A self-reported questionnaire was completed by 608 middle school students in Gyeongnam from July 1 to 23, 2013. The questionnaire consisted of general characteristics of the subjects, smoking behavior, self-efficacy, and learning attitude. The questionnaire was adapted and modified from Kang, Park, and Koh. The self-efficacy was divided into general efficacy and social efficacy. The learning attitude was divided into attention concentration, learning method, and self learning. Data were analyzed using SPSS Win 21.0 program. Results: The nonsmoking students tended to have higher general efficacy and social efficacy than the smokers (p<0.01). The nonsmokers had more attention concentration in learning attitude than the smokers (p<0.001). The learning method (p<0.001) and self learning (p<0.001) showed the same results between the two groups. The smoking experience had the negative correlation with general efficacy (r=-0.164) and social efficacy(r=-0.154). The general efficacy is positively related to social efficacy (r=0.568). The smoking experience had the negative correlation to attention concentration (r=-0.235), learning method (r=-0.211) and self learning (r=-0.148). The attention concentration was positive relation with learning method (r=0.690) and self learning(r=0.662. The learning method had positive relation to self learning (r=0.764). Conclusions: The smoking students tended to have lower self-efficacy and learning attitude, so it is necessary to implement the smoking prevention program in the middle school students.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1819-1824
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• 2018

This paper proposes a control method of ASMR(autonomous sensory meridian response) contents to relieve user's stress and improve his attention. The proposed method measures EEG(electroencephalography), attention, meditation, and eyeblink data from an EEG device and sends them to an oneM2M-compliant IoT(internet of things) server platform through an Android IoT Application. Then a SVM(support vector machine) model is built to classify user's mental health status by using EEG, attention and meditation data collected in the server platform. The ASMR contents are controlled by the mental health status classified by a SVM model and the eyeblink data. When comparing the SVM models according to types of data used, the SVM model with attention and meditation data showed accuracy of 85.7%. It was verified that the proposed control algorithm of ASMR contents properly worked as the mental health status from the SVM model and the eyeblink data changed.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.9
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• pp.349-358
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• 2021

Recently, a method of finding the attention area or localization area for an object of an image using CAM (Class Activation Map)[1] has been variously carried out as a study of WSOL (Weakly Supervised Object Localization). The attention area extraction from the object heat map using CAM has a disadvantage in that it cannot find the entire area of the object by focusing mainly on the part where the features are most concentrated in the object. To improve this, using CAM and Selective Search[6] together, we first expand the attention area in the heat map, and a Gaussian smoothing is applied to the extended area to generate retraining data. Finally we train the data to expand the attention area of the objects. The proposed method requires retraining only once, and the search time to find an localization area is greatly reduced since the selective search is not needed in this stage. Through the experiment, the attention area was expanded from the existing CAM heat maps, and in the calculation of IOU (Intersection of Union) with the ground truth for the bounding box of the expanded attention area, about 58% was improved compared to the existing CAM.

• Journal of the Ergonomics Society of Korea
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• v.29 no.5
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• pp.735-739
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• 2010

Driving workload is increasing according to developing new in-vehicle devices and introducing driving information systems. In this research using a driving simulator, EFRP (Eye Fixation Related Potential) was measured for evaluating driving attention and distraction while tasking cognitive workload, n-back tasks. The result of EFRP was compared with driver behaviors. Results suggest that EFRP is able to use for a method of evaluating driving workload, however, the analysis of driver behavior is difficult to find driving attention and distraction in the case of free flow of traffic situation.

• Journal of Fashion Business
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• v.24 no.6
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• pp.63-79
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• 2020

This study analyze consumers' unconscious visual attention to color and images of internet shopping malls by using eye-tracking method. Twenty-nine participants, including 15 females and 14 males, participated. The average ages of the male and female participants were 27.3 years and 27.7 years, respectively. Ten images of five layouts (multi-composition images, single-model images, gender-composed images, videos, and moving banner images) of internet shopping malls were shown on an eye-tracker computer screen. Quantitative analyses of the eye-tracking responses were conducted. SPSS was used to analyze the descriptive characteristics and to conduct an independent-sample t-test, along with an ANOVA. The data analysis showed that the image area generally had the shortest time to first fixation (TFF), the longest duration of fixation (DOF), the highest number of fixations (NOF), and the highest numbers of revisits(NOR).Notably, visual attention towards female models was high among various images. The results can be used to improve credibility and design online shopping layout with a scientific evidence that helps consumers through their purchase decisions.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.98-108
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• 2023

This paper is an attempt to design segmentation method based on fully convolutional networks (FCN) and attention mechanism. The first five layers of the Visual Geometry Group (VGG) 16 network serve as the coding part in the semantic segmentation network structure with the convolutional layer used to replace pooling to reduce loss of image feature extraction information. The up-sampling and deconvolution unit of the FCN is then used as the decoding part in the semantic segmentation network. In the deconvolution process, the skip structure is used to fuse different levels of information and the attention mechanism is incorporated to reduce accuracy loss. Finally, the segmentation results are obtained through pixel layer classification. The results show that our method outperforms the comparison methods in mean pixel accuracy (MPA) and mean intersection over union (MIOU).