When reading interesting content or searching for information on a website, the appearance of a pop-up advertisement in the middle of the screen is perceived as irritating by a recipient. Interrupted cognitive processes are considered unwanted by the user but desired by advertising providers. Diverting visual attention away from the main content is intended to focus the user on the appeared disruptive content. Is the attempt to reach the user by any means justified? In this study, we examined the impact of pop-up emotional content on user reactions. For this purpose, a cognitive experiment was designed where a text-reading task was interrupted by two types of affective pictures: positive and negative ones. To measure the changes in user reactions, an eye-tracker (for analysis of eye movements and changes in gaze points) and an iMotion Platform (for analysis of face muscles' movements) were used. The results confirm the impact of the type of emotional content on users' reactions during cognitive process interruptions and indicate that the negative impact of cognitive process interruptions on the user can be reduced. The negative content evoked lower cognitive load, narrower visual attention, and lower irritation compared to positive content. These results offer insight on how to provide more efficient Internet advertising.
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http://dx.doi.org/10.3390/s22020547 | DOI Listing |
Sci Rep
December 2024
School of Construction Machinery, Shandong Jiaotong University, Jinan, 250023, China.
Injection molded parts are increasingly utilized across various industries due to their cost-effectiveness, lightweight nature, and durability. However, traditional defect detection methods for these parts often rely on manual visual inspection, which is inefficient, expensive, and prone to errors. To enhance the accuracy of defect detection in injection molded parts, a new method called MRB-YOLO, based on the YOLOv8 model, has been proposed.
View Article and Find Full Text PDFBackground: The symptom network can provide a visual insight into the symptom mechanisms. However, few study authors have explored the multidimensional symptom network of patients with atrial fibrillation (AF).
Objectives: We aimed to identify the core symptom and symptom clusters of patients with AF by generating a symptom network.
Med Phys
December 2024
School of Physics and Optoelectronic Engineering, Foshan University, Foshan, China.
Background: In clinical practices, doctors usually need to synthesize several single-modality medical images for diagnosis, which is a time-consuming and costly process. With this background, multimodal medical image fusion (MMIF) techniques have emerged to synthesize medical images of different modalities, providing a comprehensive and objective interpretation of the lesion.
Purpose: Although existing MMIF approaches have shown promising results, they often overlook the importance of multiscale feature diversity and attention interaction, which are essential for superior visual outcomes.
Sleep Breath
December 2024
Department of Anatomy, Faculty of Medicine, Istanbul Medeniyet University, Istanbul, Türkiye.
Objective: This study investigated the effects of sleep deprivation (SD) on balance after normal sleep, 24 h of SD, and subsequent rest under eyes-open (EO) and eyes-closed (EC) conditions. Our aim was to ascertain whether the reduced efficiency of balance control following SD is generalized or selective.
Method: Nineteen participants (12 females, 7 males) completed the Pittsburgh Sleep Quality Index (PSQI).
Membranes (Basel)
November 2024
Civil and Environmental Engineering, Kookmin University, 77 Jeongneung-ro, Seongbuk-gu, Seoul 136-702, Republic of Korea.
To overcome the limitations of traditional Reverse Osmosis (RO) desalination, Membrane Distillation (MD) has gained attention as an effective solution for improving the treatment of seawater and RO brine. Despite its potential, the formation of inorganic scales, particularly calcium sulfate (CaSO), continues to pose a major challenge. This research aims to explore the scaling mechanisms in MD systems through a combination of experimental analysis and dynamic modeling.
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