• Smart Media Journal
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• v.12 no.7
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• pp.76-83
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• 2023

This study proposes a method to assist webtoon artists in the process of webtoon creation by utilizing a pretrained Text-to-Image model to generate webtoon images from text. The proposed approach involves fine-tuning a pretrained Stable Diffusion model using a webtoon dataset transformed into the desired webtoon style. The fine-tuning process, using LoRA technique, completes in a quick training time of approximately 4.5 hours with 30,000 steps. The generated images exhibit the representation of shapes and backgrounds based on the input text, resulting in the creation of webtoon-like images. Furthermore, the quantitative evaluation using the Inception score shows that the proposed method outperforms DCGAN-based Text-to-Image models. If webtoon artists adopt the proposed Text-to-Image model for webtoon creation, it is expected to significantly reduce the time required for the creative process.

• Smart Media Journal
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• v.12 no.4
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• pp.27-40
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• 2023

Many researchers have investigated ways to enhance recommender systems by integrating heterogeneous data to address the data sparsity problem. However, only a few studies have successfully integrated heterogeneous data using knowledge graph. Additionally, most of the knowledge graphs built in these studies only incorporate explicit relationships between entities and lack additional information. Therefore, we propose a method for expanding knowledge graphs by using deep learning to model latent relationships between heterogeneous data from multiple knowledge bases. Our extended knowledge graph enhances the quality of entity features and ultimately increases the accuracy of predicted user preferences. Experiments using real music data demonstrate that the expanded knowledge graph leads to an increase in recommendation accuracy when compared to the original knowledge graph.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.434-442
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• 2023

The relationship between acute kidney injury (AKI) prediction and nephrotoxic drugs, or drugs that adversely affect kidney function, is one that has yet to be explored in the critical care setting. One contributing factor to this gap in research is the limited investigation of drug modalities in the intensive care unit (ICU) context, due to the challenges of processing prescription data into the corresponding drug representations and a lack in the comprehensive understanding of these drug representations. This study addresses this gap by proposing a novel approach that leverages patient prescription data as a modality to improve existing models for AKI prediction. We base our research on Electronic Health Record (EHR) data, extracting the relevant patient prescription information and converting it into the selected drug representation for our research, the extended-connectivity fingerprint (ECFP). Furthermore, we adopt a unique multimodal approach, developing machine learning models and 1D Convolutional Neural Networks (CNN) applied to clinical drug representations, establishing a procedure which has not been used by any previous studies predicting AKI. The findings showcase a notable improvement in AKI prediction through the integration of drug embeddings and other patient cohort features. By using drug features represented as ECFP molecular fingerprints along with common cohort features such as demographics and lab test values, we achieved a considerable improvement in model performance for the AKI prediction task over the baseline model which does not include the drug representations as features, indicating that our distinct approach enhances existing baseline techniques and highlights the relevance of drug data in predicting AKI in the ICU setting.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.177-188
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• 2024

As technology evolves, Internet usage continues to grow, resulting in a geometric increase in network traffic and communication volumes. The network path selection process, which is one of the core elements of the Internet, is becoming more complex and advanced as a result, and it is important to effectively manage and analyze it, and there is a need for a representation and visualization method that can be intuitively understood. To this end, this study designs a framework that analyzes network data using BGP, a network path selection method, and applies it to the cyber common operating picture for situational awareness. After that, we analyze the visualization elements required to visualize the information and conduct an experiment to implement a simple visualization. Based on the data collected and preprocessed in the experiment, the visualization screens implemented help commanders or security personnel to effectively understand the network situation and take command and control.

• Ocean Systems Engineering
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• v.14 no.1
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• pp.85-99
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• 2024

Ocean surface currents have an essential role in the Earth's climate system and significantly impact the marine ecosystem, weather patterns, and human activities. However, predicting ocean surface currents remains challenging due to the complexity and variability of the oceanic processes involved. This review article provides an overview of the current research status, challenges, and opportunities in the prediction of ocean surface currents. We discuss the various observational and modelling approaches used to study ocean surface currents, including satellite remote sensing, in situ measurements, and numerical models. We also highlight the major challenges facing the prediction of ocean surface currents, such as data assimilation, model-observation integration, and the representation of sub-grid scale processes. In this article, we suggest that future research should focus on developing advanced modeling techniques, such as machine learning, and the integration of multiple observational platforms to improve the accuracy and skill of ocean surface current predictions. We also emphasize the need to address the limitations of observing instruments, such as delays in receiving data, versioning errors, missing data, and undocumented data processing techniques. Improving data availability and quality will be essential for enhancing the accuracy of predictions. The future research should focus on developing methods for effective bias correction, a series of data preprocessing procedures, and utilizing combined models and xAI models to incorporate data from various sources. Advancements in predicting ocean surface currents will benefit various applications such as maritime operations, climate studies, and ecosystem management.

• Korean Journal of Clinical Pharmacy
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• v.25 no.4
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• pp.286-295
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• 2015

Objective: This experiment is to study how elderly group and their various lifestyles interact with health functional foods, according to their selection behavior. Different lifestyles will be observed closely, as well as how different health conditions and consumer involvements will affect critical decision making in selecting health functional foods. Method: Theories and discoveries from original advanced research were compared parallel to the new study. Results: First, cluster analysis and exploratory analysis were performed amongst different elder lifestyles. Lifestyle exploratory analysis was used for healthy, unique, leisure, and economical-style elders. Cluster analysis was used for material trend oriented, health oriented, complacent oriented-style elders. Health Functional Foods' selection trait Exploratory Factor Analysis showed that product's originality (function, uniqueness, specialty, compatibility, distributor, expiration date), quality (amount, daily dose, visual representation, accessibility, portability, natural ingredients), and popularity (product container, brand image, taste and smell, advertised product, domestic or import, well-known function) were the three main causes. Secondly, the amount of benefits for the elderly group health lifestyle were affected by 'Interest in health', 'Notability of the health functional food', and 'Functionality approved mark'. Specifically, the importance of, 'Interest in health', 'Notability of health functional food', and 'Functionality approved mark' were noticeably high within health oriented elders. Lastly, after examining the data from elder lifestyle's relationship with health functional food selection trait, all three different results showed equal importance. If you closely examine material trend oriented elderly group, selection trait showed distinctively high regards in 'Fundamental Attribute', 'Typical Attribute', and 'Cognitive Attribute'. Health oriented elders showed their distinctively high regards in 'Natural Attribute', and less consideration in 'Typical Attribute' and 'Cognitive Attribute'. Complacent oriented-style elderly group showed less focus on 'Fundamental Attribute', and even less in 'Typical Attribute', and 'Cognitive Attribute'. Health oriented elderly group concluded with above data from the fact that they showed most importance and involvement in health beneficial products that are scientifically proven. Material trend oriented elderly group showed balanced traits in their concluded data, showing that they prefer function, safety, as well as the brand image and their reputation. Also, they consider the products' outer elements, such as design and product name, in order to sense inner functions. Conclusion: So, Silver Business corporations must develop products to fulfill the market demands, and strategize marketing plans to better target the correct audience.

• Cartoon and Animation Studies
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• s.16
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• pp.223-243
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• 2009

Computer graphic where the most useful and effective production methods are used for animation or films has expanded into actors' performance beyond object expression, background expression and special effect. Unlike 2D drawing software focusing on user's sense, 3D mainly depends on hardware performance and software functions. Therefore, for 3D users, learning 3D functions is directly related to new expression, and quick learning and effective representation are keys to productivity growth in animation industry. In line with industrial needs, basic 3D animation software training is provided in school. Unfortunately, however, many problems such as lack of professional instructors, time allocation and education environment prevent various 3D animation software from being taught. Moreover, functional use does not live up to industrial rapid trends. In order to improve effects of software functional education in restricted education fields, this research aims to find out what functions of 3D animation software are used in industries, what are those function used for, and how schools provide 3D animation software training.

• Journal of the Korean School Mathematics Society
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• v.10 no.1
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• pp.27-43
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• 2007

The aim of this paper is to develop a web-based learning system in order to motivate college students in the area of science and engineering to study college calculus. We designed and developed web-based contents, named MathBooster, using Mathematica, webMathematica and phpMath taking advantages of rapid computation and symbolic computation. The features of MathBooster consists of four parts: graphical representation of calculus concepts, textual illustrations of conceptual understanding, example-based step-by-step learning with phpMath, and quizzes with diagnostic feedback. After the MathBooster was practiced with engineering students, the formative evaluation was conducted with survey items composed in four categories: user responses, screen layout, practicing examples and diagnostic feedback in solving quizzes. The overall level of user satisfaction was statistically measured using SPSS. Those results indicate which parts of MathBooster are needed for future enhancement.

• School Mathematics
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• v.7 no.2
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• pp.139-168
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• 2005

The purpose of this study is to investigate children's informal knowledge of the fractional multiplication and to develop a teaching material connecting the informal and the formal knowledge. Six lessons of the pre-teaching material are developed based on literature reviews and administered to the 7 students of the 4th grade in an elementary school. It is shown in these teaching experiments that children's informal knowledge of the fractional multiplication are the direct modeling of using diagram, mathematical thought by informal language, and the representation with operational expression. Further, teaching and learning methods of formalizing children's informal knowledge are obtained as follows. First, the informal knowledge of the repeated sum of the same numbers might be used in (fractional number)$\times$((natural number) and the repeated sum could be expressed simply as in the multiplication of the natural numbers. Second, the semantic meaning of multiplication operator should be understood in (natural number)$\times$((fractional number). Third, the repartitioned units by multiplier have to be recognized as a new units in (unit fractional number)$\times$((unit fractional number). Fourth, the partitioned units should be reconceptualized and the case of disjoint between the denominator in multiplier and the numerator in multiplicand have to be formalized first in (proper fractional number)$\times$(proper fractional number). The above teaching and learning methods are melted in the teaching meterial which is made with corrections and revisions of the pre-teaching meterial.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.12
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• pp.894-906
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• 2006

There are many difficulties to develop a mobile contents due to many constraints on mobile environments. It is difficult to make a good mobile contents with only visual reduction of existing contents on wire Internet. Therefore, it is essential to devise the data representation and to develop the authoring tool to meet the needs of the mobile contents market. We suggest the compact mobile contents to learn Chinese characters and developed its authoring tool. The animation which our system produces is realistic as if someone writes letters with pen or brush. Moreover, our authoring tool makes a user generate a Chinese character animation easily and rapidly although she or he has not many knowledge in computer graphics, mobile programming or Chinese characters. The method to generate the stroke animation is following: We take basic character shape information represented with several contours from TTF(TrueType Font) and get the information for the stroke segmentation and stroke ordering from simple user input. And then, we decompose whole character shape into some strokes by using polygonal approximation technique. Next, the stroke animation for each stroke is automatically generated by the scan line algorithm ordered by the stroke direction. Finally, the ordered scan lines are compressed into some integers by reducing coordinate redundancy As a result, the stroke animation of our system is even smaller than GIF animation. Our method can be extended to rendering and animation of Hangul or general 2D shape based on vector graphics. We have the plan to find the method to automate the stroke segmentation and ordering without user input.