The Journal of the Convergence on Culture Technology
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v.8
no.6
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pp.971-978
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2022
As a marketing method in a non-face-to-face society, the purpose of this study is to test how AR experience affects purchase intention in the process of consumers recognizing product information to purchase products and to secure the basis for the effectiveness of developing and introducing augmented reality functions in future product brand applications. Literary research methods and empirical research methods were used to verify the research purpose, and to measure this, an application of domestic tableware brand 'Odense', which implements augmented reality functions, was produced and used as an experimental tool. Also, a direct causal relationship was attempted by constituting a questionnaire by deriving a measurement scale for perceived usefulness, perceived ease, perceived pleasure, and purchase, which are factors of technology acceptance theory (TAM), and empirical analysis was conducted using the SPSS 25.0 statistical package to achieve the purpose of the study. As a result of the study, significant results were derived from all factors in the effect of perceived usefulness, ease, and pleasure on purchase intention, and several significant differences were found among factors according to gender, age, and internet shopping usage time in general characteristics. In conclusion, the user experience of the medium in which the augmented reality function is introduced in the information recognition stage of the product has a positive effect on purchase compared to the user experience of existing applications.
Purpose: With the rapid changes in the technical development and the trend of consumption trend, the convenience store industry is facing an unprecedented competitive situation in the consumption environment where the boundary between online and offline is broken due to the stagnation of offline distribution channels and the spread of online shopping. The biggest innovation strategy of the major convenience store brands in recent years are introducing the O2O (Online to Offline) platform and presenting new products and services beyond the boundaries of online and offline to transform themselves into Omni Channel stores. The study is designed to analyze the effect of innovativeness of convenience store as a stimulus in O2O platform which customers perceive on store loyalty, the final response to external stimuli, through customer engagement with convenience store brands. Specifically, the innovativeness of convenience stores was divided into types of core activities in corporate marketing and focused on innovations in services, products(proposals), promotions and experiences. Research design, data, and methodology: Various hypotheses have been developed to achieve this research purpose. The data were collected from 1,128 questionnaires the age between 15 and 60 who had experience using retail store apps and delivery apps and were analyzed using SPSS 22.0 and SmartPLS 3.3.7 program. Measurement model analysis was carried out to assess convergent and discriminant validity. Also, common method bias was tested using the values of VIF (variance inflation factor). The hypotheses were tested using structural equation modeling with SmartPLS 3.3.7 program. Results: First, service innovation has a positive effect on cognitive engagement. Second, product, promotion and experience innovation have a positive effect on cognitive and affective engagement. Third, cognitive influences affective engagement. Finally, both cognitive and affective engagement affect store loyalty, but affective engagement has a stronger effect on store loyalty than cognitive engagement. Conclusions: All four types of innovation and cognitive engagement have a positive effect on emotional engagement, which has a stronger effect on store loyalty than cognitive engagement. Thus, while innovation can build loyalty through emotional engagement, innovation strategies must be designed and pursued with caution in terms of impact through cognitive engagement may not achieve the planned goals.
Safety education delivered to construction workers in a lecture manner has limitations in concentration and immersion, so delivery power and interest are low. In order to improve unstable behavior through education and prevent safety accidents, it is necessary to change the paradigm to hands-on education. Purpose: Experiential safety education aims to contribute to preventing accidents for construction workers by quickly recognizing risks, improving emergency response skills, and verifying the effectiveness of pre- and post-learning. Method: Based on a survey of workers who experienced the same work environment as the actual construction site, an opinion survey on the pre- and post-safety experience education and a variable measurement tool were planned, and a research hypothesis was established. Results: The Bayesian theory and MC simulation analysis were used to analyze the structural equation model, and the change in construction worker behavior was confirmed through the intended safety (A), non-experiential education in the sub-area of anxiety (B), average, standard deviation, and minimum and maximum values. Conclusion: The effect of education and industrial accidents are reduced only when construction workers are motivated to participate.
Chan-hwi, Shin;Gyeong-jo, Min;Gyeong-Gyu, Kim;PuReun, Jeon;Hoon, Park;Sang-Ho, Cho
Explosives and Blasting
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v.40
no.4
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pp.15-26
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2022
With the recent increase in old and dangerous buildings, the demand for technology in the field of structure demolition is rapidly increasing. In particular, in the case of structures with severe deformation of damage, there is a risk of deterioration in stability and disaster due to changes in the load distribution characteristics in the structure, so rapid structure demolition technology that can be efficiently dismantled in a short period of time is drawing attention. However, structural deformation such as unauthorized extension or illegal remodeling occurs frequently in many old structures, which is not reflected in structural information such as building drawings, and acts as an obstacle in the demolition design process. In this study, as an effective way to overcome the discrepancy between the structural information of old structures and the actual structure, access to actual structures through 3D modeling was considered. 3D point cloud data inside and outside the building were obtained through LiDAR and drone photography for buildings scheduled to be blasting demolition, and precision matching between the two spatial data groups was performed using an open-source based spatial information construction system. The 3D structure model was completed by importing point cloud data matched with 3D modeling software to create structural drawings for each layer and forming each member along the structure slab, pillar, beam, and ceiling boundary. In addition, the modeling technique proposed in this study was verified by comparing it with the actual measurement value for selected structure member.
In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.
Journal of Korean Home Economics Education Association
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v.35
no.2
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pp.111-132
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2023
The objective of this research is to conceptualize care competences for adolescents and to develop a valid measurement tool based on this conceptualization. The primary aim is to establish a solid foundation for effective communication in teaching care competences within the domain of home economics education. To achieve this, a comprehensive review of relevant literature and previous studies was conducted, and consultations with experts were undertaken to assess content and criterion-related validity. Furthermore, exploratory and confirmatory factor analyses were performed. The findings from these analyses resulted in a set of 34 items, which were categorized into five distinctive factors representing care competences in adolescents. These factors encompassed four items of care thinking, seven items of care emotion, six items of care behavior, seven items of self-care and ten items of community-care. Additionally, a reliability analysis was performed on the model, confirming the stability and consistency of the five factor structure and the 34 item scale, which assess care competences in adolescents.
Journal of The Geomorphological Association of Korea
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v.17
no.1
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pp.49-57
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2010
To evaluate physical characteristics of open rainfall in Korea, terminal velocity of raindrop and drop size distributions (DSD) were continuously measured using by laser-optical disdrometer around Gosam reservoir, Anseong-si, Gyeonggi-do during three rainfall events from 2008 to 2009. The relationships between kinetic energies (KE, Jm-2mm-1; KER, Jm-2h-1) and rainfall intensity were obtained, respectively. Moreover, we compared the rainfall intensity from a disdrometer with the rainfall intensity from a tipping bucket raingauge to transform the kinetic energy of rainfall using the data from a tipping bucket raingauge. Therefore, the established relationships between kinetic energies (KE and KER) and rainfall intensity could be a useful model to consider the kinetic energy of raindrop using the rainfall intensity below 40mmh-1 of max 5-min rainfall intensity in the middle of South Korea. However, to better examine the relationship between kinetic energy and rainfall intensity, further measurement will be required.
The Ministry of Land, Infrastructure and Transport has also been promoting the commercialization of land transport technology to commercialize the technologies owned by small and medium-sized venture companies, and to support the transfer and commercialization of public technologies. At this point, in order to improve the investment effect of subsequent new projects and to select excellent research institutes, it is necessary to establish a valid evaluation index system suitable for the purpose of the project. The evaluation index system for subsequent new projects should be linked to the project objectives and goals of the preceding project, and should be selected in consideration of existing evaluation indicators to prevent interruption of research results. Therefore, this thesis sets the evaluation index system into multiple scenarios through hierarchical cluster analysis using the evaluation result data for each evaluation committee for small and medium venture companies participating in the land transportation technology commercialization support project, and then analyzes the structural equation model. As a result of scenario analysis, considering the measurement effect of each path representing the causal relationship between evaluation indicators and the effect of each evaluation index on evaluation items, the scenario with the highest impact on the evaluation result was selected as an improvement plan.
In this study, the acoustic performance was analyzed by architectural shapes of the hall. There are four architectural shapes of halls. They are rectangular, horseshoe, surround, and fan-shape. Eight acoustic parameters were used to determine the acoustic performance. These are RT60, EDT, C80, BQI, LF, Gmid, G125 and ITDG. First, measurement data of famous concert halls around the world were analyzed. The correlation coefficient R was obtained by regression analysis of the relationship between the subjective ranking of the halls and the acoustic parameters. It was found that BQI, G, and ITDG have higher correlation coefficients R. Also the average of acoustic parameters for each architectural shape were obtained. The total acoustic performance for each shape was calculated by using the correlation coefficient R as a weight for each acoustic parameters. As a result, rectangular halls and horseshoe halls showed good acoustical performances. Second, 3D models of each architectural shape were created and acoustic simulation had been performed. The simulation was performed by creating 3D models of each four shapes of concert halls with the same volume and sound absorption coefficient. Listening test was carried out using the sound source which is created from impulse responses of 3D model. As a result, rectangular hall and horseshoe hall showed the best performance however surround hall and fan-shaped hall showed relatively poor performance.
This study was conducted to identify the optimal lotion manufacturing conditions with decursin and decursinol angelate of Angelica gigas Nakai extraction. Lotion was confirmed that it had viscosity (5,208±112 cPs), assay (99.71±1.01%), and pH (5.62) for 3 months. The optimization of manufacturing conditions of mixing 4 for lotion formulation were made by 22+3 full factorial design. Mixing temperature (40-80℃) and mixing time (10-30 min) were used as independent variables with three responses(assay, pH, and weight variation) as critical quality attributes (CQAs). The model for assay and weight variation identified a proper fit having a determination coefficient of the regression equation (about 0.9) and a p-value less than 0.05. Estimated conditions for the optimal manufacturing process of lotion were 61.93℃ in mixing temperature and 15.85 min in mixing time. Predicted values at the mixing temperature (60℃) and mixing time (20 min) were 100.69% of assay, 5.57 of pH, and 98.07% of weight variation. In the verification of the actual measurement the obtained values showed 100.29±0.98% of assay, 5.57±0.02 of pH, and 98.27±0.89% of weight variation, respectively, in good agreement with predicted values.
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