1,672 research outputs found
Success Story of Professional Laundry Service in Korea
The purpose of this study is to analyze a professional laundry service company, Cleantopia, comprising a nearly 80% market share in Korea. The key to Cleantopia’s success relates to its management policy of “principle and innovation.” Cleantopia adopted various marketing strategies to realize its management philosophy: cultivating talented personnel, customer satisfaction, and social contribution. Another success factor is its active engagement in technological exchanges with developed countries and industrial-academic cooperation
A Review on Recent Deep Learning-Based Semantic Segmentation for Urban Greenness Measurement
Accurate urban green space (UGS) measurement has become crucial for landscape analysis. This paper reviews the recent technological breakthroughs in deep learning (DL)-based semantic segmentation, emphasizing efficient landscape analysis, and integrating greenness measurements. It explores quantitative greenness measures applied through semantic segmentation, categorized into the plan view- and the perspective view-based methods, like the Land Class Classification (LCC) with green objects and the Green View Index (GVI) based on street photographs. This review navigates from traditional to modern DL-based semantic segmentation models, illuminating the evolution of the urban greenness measures and segmentation tasks for advanced landscape analysis. It also presents the typical performance metrics and explores public datasets for constructing these measures. The results show that accurate (semantic) segmentation is inevitable not only for fine-grained greenness measures but also for the qualitative evaluation of landscape analyses for planning amidst the incomplete explainability of the DL model. Also, the unsupervised domain adaptation (UDA) in aerial images is addressed to overcome the scale changes and lack of labeled data for fine-grained greenness measures. This review contributes to helping researchers understand the recent breakthroughs in DL-based segmentation technology for challenging topics in UGS research
Brand Image and Evaluation Factors of Fashion Product Advertisement
Brand image is a collection of things related with brand that consumers have in the memory (Keller, 1993) and corporations are making much efforts to build a brand image and advertisement has been used as a major method to inform the brand image. Advertisement is communication message performed for the purpose of positively change the consumer’s emotion for corporations, brands and trademarks
Adverse childhood experiences and the associations with depression and anxiety in adolescents
Objectives There has been increasing attention to adverse childhood experiences (ACEs) among adolescents in the U.S because ACEs may result in severe mental health issues. Although associations between ACEs and mental health have been explored, research on how different types or combinations of ACEs render different impacts on adolescents is limited. Therefore, this study aims to (a) examine latent classes of ACEs among adolescents who have experienced at least one ACE and (b) investigate associations of each latent group of ACEs with mental health problems, depression and anxiety. Method Questionnaires on ACEs and depression/anxiety from the 2016 National Survey of Children’s Health (NSCH) were used, and a total of 11,437 adolescents aged 10–17 years were included in this study. For analyses, latent class analysis (LCA) was implemented to identify the number and types of classes, which are pertinent to represent the heterogenous combinations of ACEs. Moreover, chi-square tests and ordinal regression were performed to investigate the associations of class memberships within ACEs with depression/anxiety. Results The LCA found four class memberships within ACEs: Multiple High-Risk, Broken Family, Income Hardship, and Multiple Low-Risk. These classes displayed differences in depression/anxiety. For both pre-existing and current conditions of depression/anxiety, the most prominence has been found in the Multiple High-Risk, followed by the Multiple Low-Risk, the Broken Family, and the Income Hardship, in order. Conclusions These differences among the classes indicate that understanding of ACEs and interventions should be based on considering latent classes of ACEs
The Effects of Furnishings and Technology on Pedagogical Agility and Student Engagement Across Flexible Learning Spaces
We explored how furnishings and technology impact pedagogical agility and student engagement across three flexible learning spaces. We collected various data sources from students and faculty teaching in multiple learning spaces, such as focus group interviews with students, faculty responses to reflection prompts, and pre-and post-occupancy surveys with faculty and students. Flexible furniture configuration was found to support various instructional strategies and facilitate interaction between student-student and student-instructor. A writable surface is beneficial to facilitate student engagement during group activities. Digital displays with content sharing capabilities promote collaborative learning. Specific recommendations for learning space designs and faculty development are provided
Development and Validation of a Postpartum Care Mobile Application for First-time Mothers
PURPOSE: The aims of the study were to develop mobile application for postpartum care of first-time mothers and to validate it's effect.
METHODS: Using a nonequivalent control group pretest-posttest design, 52 first-time mothers were recruited (26 each in experimental and control) and the experimental group used the mobile application for 6 weeks after delivery. Postpartum self-care knowledge and confidence, infant care knowledge and confidence, and postpartum depressive mood (Edinburgh Postnatal Depression Scale) were measured before discharge from the hospital and 6 weeks later.
RESULTS: Women who have used the postpartum care mobile application reported higher levels of postpartum self-care knowledge (p=.030) and confidence (p=.023) infant care knowledge (p=.001) and confidence (p=.004), while scores of postpartum depression (p=.021) were lower than those in the control group.
CONCLUSION: The postpartum-care mobile application developed in this research may be effective in reinforcing knowledge and confidence for postpartum self-care and infant care and in reducing postpartum depressive mood
Development of High Performance Firefighting Gloves Prototype Applied to Ergonomic Design
The aim of this paper is to clarify firefighters’ design needs for their firefighting gloves and to determine ergonomic design elements which could provide the best compromise between protection and comfort
Machine Learning in Additive Manufacturing: A Review
In this review article, the latest applications of machine learning (ML) in the additive manufacturing (AM) field are reviewed. These applications, such as parameter optimization and anomaly detection, are classified into different types of ML tasks, including regression, classification, and clustering. The performance of various ML algorithms in these types of AM tasks are compared and evaluated. Finally, several future research directions are suggested
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