• Journal of The Geomorphological Association of Korea
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• v.26 no.2
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• pp.1-14
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• 2019

This study analyzed the relativity between block stream and talus distributions by employing a likelihood ratio approach. Possible distribution sites for each debris slope landform were extracted by applying a spatial integration model, in which we combined fuzzy set model, Bayesian predictive model, and logistic regression model. Moreover, to verify model performance, a success rate curve was prepared by cross-validation. The results showed that elevation, slope, curvature, topographic wetness index, geology, soil drainage, and soil depth were closely related to the debris slope landform sites. In addition, all spatial integration models displayed an accuracy of over 90%. The accuracy of the distribution potential area map of the block stream was highest in the logistic regression model (93.79%). Eventually, the accuracy of the distribution potential area map of the talus was also highest in the logistic regression model (97.02%). We expect that the present results will provide essential data and propose methodologies to improve the performance of efficient and systematic micro-landform studies. Moreover, our research will potentially help to enhance field research and topographic resource management.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.706-708
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• 2023

In this study, we embark on a journey to uncover the essence of emotions by exploring the depths of transfer learning on three pre-trained transformer models. Our quest to classify five emotions culminates in discovering the KLUE (Korean Language Understanding Evaluation)-BERT (Bidirectional Encoder Representations from Transformers) model, which is the most exceptional among its peers. Our analysis of F1 scores attests to its superior learning and generalization abilities on the experimental data. To delve deeper into the mystery behind its success, we employ the powerful SHAP (Shapley Additive Explanations) method to unravel the intricacies of the KLUE-BERT model. The findings of our investigation are presented with a mesmerizing text plot visualization, which serves as a window into the model's soul. This approach enables us to grasp the impact of individual tokens on emotion classification and provides irrefutable, visually appealing evidence to support the predictions of the KLUE-BERT model.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.298-299
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• 2022

Digital Transformation in the maritime transportation sector means "by utilizing digital technologies such as artificial intelligence, big data, Internet of Things, block chain, and cloud to create new business models, products, and services for maritime transportation-related companies. It can be defined as a continuous process that adapts to or drives disruptive changes in the market" (Chang, 2021). In a situation where various digital conversion technologies are applied and started to be used in the domestic port logistics field, active acceptance by members can bring about the success of digital conversion. Therefore, in this study, in order to investigate the acceptability of digital transformation in the domestic port logistics sector,

• Educational Technology International
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• v.15 no.2
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• pp.71-88
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• 2014

A variety of studies to predict students' performance have been conducted since educational data such as web-log files traced from Learning Management System (LMS) are increasingly used to analyze students' learning behaviors. However, it is still challenging to predict students' learning achievement in blended learning environment where online and offline learning are combined. In higher education, diverse cases of blended learning can be formed from simple use of LMS for administrative purposes to full usages of functions in LMS for online distance learning class. As a result, a generalized model to predict students' academic success does not fulfill diverse cases of blended learning. This study compares two blended learning classes with each prediction model. The first blended class which involves online discussion-based learning revealed a linear regression model, which explained 70% of the variance in total score through six variables including total log-in time, log-in frequencies, log-in regularities, visits on boards, visits on repositories, and the number of postings. However, the second case, a lecture-based class providing regular basis online lecture notes in Moodle show weaker results from the same linear regression model mainly due to non-linearity of variables. To investigate the non-linear relations between online activities and total score, RF (Random Forest) was utilized. The results indicate that there are different set of important variables for the two distinctive types of blended learning cases. Results suggest that the prediction models and data-mining technique should be based on the considerations of diverse pedagogical characteristics of blended learning classes.

• Journal of Distribution Science
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• v.21 no.10
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• pp.11-19
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• 2023

Purpose: Personality qualities are essential to the prosperity of any contemporary company because they foster the growth of pleasant emotions in telecommunications distribution employees. Research design, data and methodology: Thus improving their overall psychological well-being and productivity. Talent retention is facilitated by mutual respect between management and staff. The success of the company as a whole, including the development and maintenance of emotions with customers, also depends on the psychological well-being of employees. The aim is to demonstrate how a positive and satisfied emotional workforce contributes to psychological well-being in the 21st century. Result: The research aims to better understand the personality traits that influence the psychological well-being of employees. In addition, between January and March 2023, a total of 179 employees in the telecommunications distribution industry in the Peruvian city of Chiclayo were surveyed using structural modelling methods to measure employee satisfaction. It also shows how various ideas, approaches and models can be used in the real world. Conclusion: The significance of the model on the perception of telecommunications workers in Peru is demonstrated by the results, which indicate an R² value of 0.681 for positive emotions and an R² value of 0.792 for employees' psychological well-being.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.73-81
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• 2024

Recently, mobile manipulators have been utilized in agriculture industry for weed removal and harvest automation. This paper proposes a domain adaptive fruit detection method for harvest automation, by utilizing OWL-ViT model which is an open-vocabulary object detection model. The vision-language model can detect objects based on text prompt, and therefore, it can be extended to detect objects of undefined categories. In the development of deep learning models for real-world problems, constructing a large-scale labeled dataset is a time-consuming task and heavily relies on human effort. To reduce the labor-intensive workload, we utilized a large-scale public dataset as a source domain data and employed a domain adaptation method. Adversarial learning was conducted between a domain discriminator and feature extractor to reduce the gap between the distribution of feature vectors from the source domain and our target domain data. We collected a target domain dataset in a real-like environment and conducted experiments to demonstrate the effectiveness of the proposed method. In experiments, the domain adaptation method improved the AP50 metric from 38.88% to 78.59% for detecting objects within the range of 2m, and we achieved 81.7% of manipulation success rate.

• Asia pacific journal of information systems
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• v.30 no.1
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• pp.188-213
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• 2020

Various information and communication technologies (ICT) and electronic government (e-Government) projects have been planted in hopes of economic and social growth in developing economies. These types of ventures usually involve working in societies with their own unique cultures in various aspects that often cause "custom ways" of planning, implementing, coordinating, and controlling in IT projects, thus playing a grand role in determining the success of IT projects. Due to a lack of understanding of local cultural factors and a deficiency of cultural risk evaluation models, however, many IT projects especially in the context of developing economies face failure. This study investigates the major cultural factors involved in IT projects and their effects on IT projects in developing economies. The framework is validated using the United Nations Development Programme's (UNDP) information and communication technology (ICT) and e-Government project cases of two countries in Central Asia, Uzbekistan and Kazakhstan. This study will help project managers develop management practices and strategies associated with the cultural factors they face during the various stages of their IT projects in their specific contexts.

• Journal of Distribution Science
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• v.22 no.6
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• pp.33-44
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• 2024

Purpose: This study aims to measure how information quality, system quality, security, usefulness, and ease of use of Augmented Reality (VR) and Virtual Reality (AR) influence user satisfaction, motivating intelligent travel technology developers to improve VR/AR quality to meet customer requirements. Research design, data and methodology: This study investigates users interested in travelling in Ho Chi Minh City and Nha Trang City, Vietnam. The research model was implemented using an online questionnaire and face-to-face from 405 valid samples. To evaluate the scale's reliability, the study used the software SPSS 20. Test research hypotheses and evaluate measurement and structural models. This research uses AMOS 20 software. The proposed model is firmly grounded in the Information System Success model (ISS) and the Technology Acceptance Model (TAM), providing a solid theoretical foundation for our research. Results: Results show that consumer perceptions of information quality, system quality, security, usefulness, and ease of use have a positive impact on the perceived quality of VR/AR, thereby influencing tourists' travel intention. Conclusions: The results of this research enrich the theoretical understanding of consumer behaviour toward intelligent technology products in tourism, providing management implications for manufacturers to improve the quality of tourism products and satisfy user requirements in experience before considering choosing a destination.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.17-32
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• 2023

The entrepreneurial activities of college students play a significant role in modern economic and social development, particularly as a solution to the changing economic landscape and youth unemployment issues. Introducing innovative ideas and technologies into the market through entrepreneurship can contribute to sustainable economic growth and social value. Additionally, the entrepreneurial intentions of college students are shaped by various factors, making it crucial to deeply understand and appropriately support these elements. To this end, this study systematically explores the importance and impact of role models through a multiple serial mediation analysis. Through a survey of 300 college students, the study analyzed how two psychological variables, growth mindset and entrepreneurial self-efficacy, mediate the influence of role models on entrepreneurial intentions. The presence and success stories of role models were found to enhance the growth mindset of college students, which in turn boosts their entrepreneurial self-efficacy and ultimately strengthens their entrepreneurial intentions. The analysis revealed that exposure to role models significantly influences the formation of a growth mindset among college students. This mindset fosters a positive attitude towards viewing challenges and failures in entrepreneurship as learning opportunities. Such a mindset further enhances entrepreneurial self-efficacy, thereby strengthening the intention to engage in entrepreneurial activities. This research offers insights by integrating various theories, such as mindset theory and social learning theory, to deeply understand the complex process of forming entrepreneurial intentions. Practically, this study provides important guidelines for the design and implementation of college entrepreneurship education. Utilizing role models can significantly enhance students' entrepreneurial intentions, and educational programs can strengthen students' growth mindset and entrepreneurial self-efficacy by sharing entrepreneurial experiences and knowledge through role models. In conclusion, this study provides a systematic and empirical analysis of the various factors and their complex interactions that impact the entrepreneurial intentions of college students. It confirms that psychological factors like growth mindset and entrepreneurial self-efficacy play a significant role in shaping entrepreneurial intentions, beyond mere information or technical education. This research emphasizes that these psychological factors should be comprehensively considered when developing and implementing policies and programs related to college entrepreneurship education.

• The Journal of Korean Academy of Prosthodontics
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• v.40 no.5
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• pp.507-524
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• 2002

Load transfer of implant overdenture varies depending on anchorage systems that are the design of the superstructure and substructure and the choice of attachment. Overload by using improper anchorage system not only will cause fracture of the framework or screw but also may cause failure of osseointegration. Choosing anchorage system in making prosthesis, therefore, can be considered to be one of the most important factors that affect long-term success of implant treatment. In this study, in order to determine the effect of anchorage systems on load transfer in mandibular implant overdenture in which 4 implants were placed in the interforaminal region, patterns of stress distribution in implant supporting bone in case of unilateral vertical loading on mandibular left first molar were compared each other according to various types of anchorage system using three-dimensional photoelastic stress analysis. The five photoelastic overdenture models utilizing Hader bar without cantilever using clips(type 1), cantilevered Hader bar using clips(type 2), cantilevered Hader bar with milled surface using clips(type 3), cantilevered milled-bar using swivel-latchs and frictional pins(type 4), and Hader bar using clip and ERA attachments(type 5), and one cantilevered fixed-detachable prosthesis(type 6) model as control were fabricated. The following conclusions were drawn within the limitations of this study, 1. In all experimental models. the highest stress was concentrated on the most distal implant supporting bone on loaded side. 2. Maximum fringe orders on ipsilateral distal implant supporting bone in a ascending order is as follows: type 5, type 1, type 4, type 2 and type 3, and type 6. 3. Regardless of anchorage systems. more or less stresses were generated on the residual ridge under distal extension base of all overdenture models. To summarize the above mentioned results, in case of the patients with unfavorable biomechanical conditions such as not sufficient number of supporting implants, short length of the implant and unfavorable antero-posterior spread. selecting resilient type attachment or minimizing distal cantilever bar is considered to be appropriate methods to prevent overloading on implants by reducing cantilever effect and gaining more support from the distal residual ridge.