• Journal of Popular Narrative
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• v.25 no.4
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• pp.397-428
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• 2019

Fantasy emerges from the cracks and crevices of rational reality. Italo Calvino says, "Fantasy is possible when the reader stays at a certain distance without falling into the text." Fantasy does not form farthest from reality. It comes from the confusion between reality and fiction. In short, fantasy does not exist on the contrary of reality, but on the boundary of reality. Reality and fantasy are also structurally intertwined. We can't distinguish the reality from fantasy clearly. In fact, in this case, the reader or audience is confused about whether what I see is real or not. Todorov calls this case "hesitation." Hesitation is a key element of fantasy. Two texts that expressed "hesitation" are Kim Young-ha's short novel Vampire (1997) and Wes Anderson's film The Grand Budapest Hotel (2014). On the surface, these two texts seem to have nothing to do with narrative structural similarities. And both also arouse readers' and audiences' interest by letting confuse reality to fantasy. In Kim Young-ha's Vampire, we can look at the process of confusion of reality called "narrative infection" when a text is read to the reader. In the movie The Grand Budapest Hotel, we can find a strategy to make an unreal story feel like a fact in history. And we can also find a process in which the success stories of alienated characters become reality through 'solidarity' in the film. This paper is a study of how fantasy creates "reality", makes readers feel fantasy, and how it spreads through these two texts.

• Communications of Mathematical Education
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• v.37 no.1
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• pp.65-84
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• 2023

The method of Lagrange multipliers, one of the most fundamental algorithms for solving equality constrained optimization problems, has been widely used in basic mathematics for artificial intelligence (AI), linear algebra, optimization theory, and control theory. This method is an important tool that connects calculus and linear algebra. It is actively used in artificial intelligence algorithms including principal component analysis (PCA). Therefore, it is desired that instructors motivate students who first encounter this method in college calculus. In this paper, we provide an integrated perspective for instructors to teach the method of Lagrange multipliers effectively. First, we provide visualization materials and Python-based code, helping to understand the principle of this method. Second, we give a full explanation on the relation between Lagrange multiplier and eigenvalues of a matrix. Third, we give the proof of the first-order optimality condition, which is a fundamental of the method of Lagrange multipliers, and briefly introduce the generalized version of it in optimization. Finally, we give an example of PCA analysis on a real data. These materials can be utilized in class for teaching of the method of Lagrange multipliers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.917-926
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• 2006

Transportation Economies of scale are the essential properties of hub networks. One critical property of the hub network design problem is to quantify cost savings which stem from economies of scale, the costs of operating hub facilities and opportunity costs associated with delays stemming from consolidation of traffic flows. Due to the NP-complete property of the hub location problem, however, most previous researchers have focused on the development of heuristic algorithms for approximate solutions. The purpose of this paper is to develop a hub network design model considering transportation economies of scale from the consolidation of traffic flows. The model is designed to consider the uniqueness of hub networks and to determine several cost components. The heuristic algorithms for the developed model are suggested and the results of the model are compared with recently published studies using real data. Results of the analysis show that the proposed model reflects transportation economies of scale due to consolidation of flows. This study can form not only the theoretical basis of an effective and rational hub network design but contribute to the assessment of existing and planned logistics systems.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.151-156
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• 2019

In recent years, the Korean realistic theme of the film momentum gradually rising. Realistic films do not stick to the business and market, and do not simply cater to the audience's needs for watching movies. They reflect social violence and cruel reality, allowing the audience to observe the structural contradictions in reality and think about the direction when watching movies. At the recent cannes film festival, "parasite" won the top prize palm in cannes by an overwhelming margin, with the highest score of 3.3 issues. Although this film is positioned as a thriller with comedy elements, it presents the opposite life images of Korean classes to the audience in a parasitic way, which not only expands the possibility and artistry of realistic film aesthetics, but also enhances the appreciation of the film and gives play to its own aesthetic value. Focusing on the technical and literary nature of the film, and having a high degree of attention to real life, it is an excellent work that tells about class opposition and thinking about reality. This paper considers and analyzes the content, form and creation method of parasite, and discusses the continuous exploration and attempt of realistic film to image language under the demand of market and system, evolving into new aesthetic expression.

• Korean Journal of Schizophrenia Research
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• v.19 no.1
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• pp.10-16
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• 2016

Objectives : This article aims to describe the development of smartphone application for the case management of patients with schizophrenia. Methods : Gwangju Bukgu-Community Mental Health Center developed and launched a smartphone application (HYM) for cognitive-behavioral case management and symptom monitoring. The development of the application involved psychiatrists, nurses, social workers, psychologists, and software technicians from a software development company (Goosl Corp.). Results : The HYM application for clients includes six main modules including Thought record, Symptom record, Daily life record, Official notices, Communication, and Scales. The key module is the 'Thought Record' for self-directed cognitive-behavioral treatment (CBT). When the client writes and sends the self-CBT sheet to the case manager, the latter receives a notification and can provide feedback in real time. 'Communication' and 'Official notices' are useful for promoting communication between case managers and clients with schizophrenia. Ratings in 'Symptom record', 'Daily life record', and 'Scales' modules are stored in graphic or table form representing changes in them and shared with case managers. Conclusion : The interactive function of this application is the key characteristics that distinguishes it from other mobile self-treatment tools. This smartphone application may contribute to the development of a youth- and customer-friendly case management system for individuals with early psychosis.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.29-42
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• 2023

In this paper, we propose a method to enhance the prediction accuracy of solar irradiance for three major South Korean cities: Seoul, Busan, and Incheon. Our method entails the development of five generative models-vanilla GAN, CTGAN, Copula GAN, WGANGP, and TVAE-to generate independent variables that mimic the patterns of existing training data. To mitigate the bias in model training, we derive values for the dependent variables using random forests and deep neural networks, enriching the training datasets. These datasets are integrated with existing data to form comprehensive solar irradiance prediction models. The experimentation revealed that the augmented datasets led to significantly improved model performance compared to those trained solely on the original data. Specifically, CTGAN showed outstanding results due to its sophisticated mechanism for handling the intricacies of multivariate data relationships, ensuring that the generated data are diverse and closely aligned with the real-world variability of solar irradiance. The proposed method is expected to address the issue of data scarcity by augmenting the training data with high-quality synthetic data, thereby contributing to the operation of solar power systems for sustainable development.

• Analyses & Alternatives
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• v.7 no.3
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• pp.115-144
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• 2023

Under the Trump administration, the U.S. has made clear that "China is America's strategic competitor, revisionist power and a major challenge to America's prosperity and security." The Biden administration has largely inherited this perception of China. China has also responded without backing down. Therefore, the U.S.-China strategic competition has become the most important background factor in the international system and has a great impact on the security situation in Northeast Asia. Nevertheless, if you look at the recent process of establishing trilateral security cooperation among ROK, the U.S. and Japan, we can find that ROK's foreign strategy adjustment has played a key role. This is because establishing trilateral security cooperation among ROK, the U.S. and Japan depends on improving ROK-Japan relations. And the Yoon Suk Yeol government is pushing for rapid improvement in ROK-Japan relations regardless of domestic political constraints. The trilateral summit at Camp David laid the groundwork for future cooperation among ROK, the U.S. and Japan in security and other broader areas. China is strongly dissatisfied with the formation of trilateral security cooperation among ROK, the U.S. and Japan. However, this paper argues that although ROK agrees to form trilateral security cooperation with the U.S. and Japan, ROK's strategic objectives are not exactly the same as those of the U.S. and Japan. For example, looking back at the development of the U.S.-Japan alliance after the end of the Cold War, both the U.S. and Japan share similar views and perceptions of China's rise. The real goal of the strengthening of the U.S.-Japan alliance in recent years is also how to cope with China's rise. On the other hand, ROK's previous administrations have been negative about trilateral security cooperation with the U.S. and Japan. This is because ROK's main strategic goal is to reduce or eliminate threats from DPRK rather than respond to China. Faced with increasing DPRK's provocations and threats, more than half of South Koreans are in favor of reinforcing trilateral security cooperation with the U.S. and Japan to contain or mitigate threats from DPRK. As a result, if North Korea's nuclear and missile threats to ROK continue, then ROK's foreign strategy is likely to be to strengthen trilateral security cooperation between the U.S. and Japan to ensure its own safety and survival. If China wants to reduce the strategic pressure from the trilateral security cooperation among ROK, the U.S. and Japan, the best way is to reduce DPRK's provocations and threats to ROK and play a more substantive role in getting DPRK to give up its nuclear program.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.31-37
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• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.