• Journal of the Korea Convergence Society
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• v.10 no.5
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• pp.149-156
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• 2019

This study adopts 'intersectionality' as a key concept of Sheila Levrant de Bretteville's design works. As a method of research, this research suggests the definition of intersectionality, from the idea of black feminism. Analysis of the features are such as 1) Typography of speech, 2) Collection of narrative, and 3) site specific installation. The inclusion of the various situations of the individuals reflected in the design throughout de Bretteville's works has made it possible to guarantee the intersectionality. De Bretteville overthrows the context of the power in which the design is placed, embracing forgotten or less illuminated positions. As a result, this research could derive three implications such as 1) visualization of invisibility, 2) subjectification of object, and 3) demarginalization of marginality. The perspective of the intersectionality are in line with the values of contemporary Korean society and might be an insight for researchers who want to establish a design philosophy.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.636-650
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• 2020

A modeling system that can consider the overall water environment and be used to integrate hydrology, water quality, and aquatic ecosystem on a watershed scale is essential to support decision-making in integrated water resources management (IWRM). In adapting imported models for evaluating the unique water environment in Korea, a platform perspective is becoming increasingly important. In this study, a modeling platform is defined as an ecosystem that continuously grows and provides sustainable values through voluntary participation- and interaction-of all stakeholders- not only experts related to model development, but also model users and decision-makers. We assessed the conceptual values provided by the IWRM modeling platform in terms of openness, transparency, scalability, and sustainability. I We also reviewed the technical aspects of functional and spatial integrations in terms of socio-economic factors and user-centered multi-scale climate-forecast information. Based on those conceptual and technical aspects, we evaluated potential modeling platforms such as Source, FREEWAT, Object Modeling System (OMS), OpenMI, Community Surface-Dynamics Modeling System (CSDMS), and HydroShare. Among them, CSDMS most closely approached the values suggested in model development and offered a basic standard for easy integration of existing models using different program languages. HydroShare showed potential for sharing modeling results with the transparency expected by model user-s. Therefore, we believe that can be used as a reference in development of a modeling platform appropriate for managing the unique integrated water environment in Korea.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.577-583
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• 2020

The learning and cognition of preschool children begins with the color of the object, and the game interface is the child's first impression of the game, so reasonable color design is needed. This article selects 10 educational mobile game for preschool children, extracts colors from the game interface and startup icons, and puts them into Photoshop to analyze the three elements of color hue, lightness, and saturation. Finally, three suggestions are put forward for the color design of game UI. 1.Choose a color similar to the actual color of the thing. 2. Choose warm colors according to your child's preferences. 3. When using contrasting colors, please reduce the brightness or purity of the colors. It is hoped that the research conclusions can provide reference materials for the color design of educational game UI for preschool children.

• Journal of radiological science and technology
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• v.44 no.4
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• pp.327-333
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• 2021

Magnetic resonance imaging(MRI) uses strong magnetic field to image the cross-section of human body and has excellent image quality with no risk of radiation exposure. Because of above-mentioned advantages, MRI has been widely used in clinical fields. However, the noise generated in MRI degrades the quality of medical images and has a negative effect on quick and accurate diagnosis. In particular, examining a object with a detailed structure such as brain, image quality degradation becomes a problem for diagnosis. Therefore, in this study, we acquired T2 weighted 3D data of multiple sclerosis disease using BrainWeb simulation program, and used quantitative evaluation factors to find appropriate slice thickness among 1, 3, 5, and 7 mm. Coefficient of variation and contrast to noise ratio were calculated to evaluate the noise level, and root mean square error and peak signal to noise ratio were used to evaluate the similarity with the reference image. As a result, the noise level decreased as the slice thickness increased, while the similarity decreased after 5 mm. In conclusion, as the slice thickness increases, the noise is reduced and the image quality is improved. However, since the edge signal is lost due to overlapped signal, it is considered that selecting appropriate slice thickness is necessary.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.389-396
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• 2022

Deep Learning is based on a perceptron, and is currently being used in various fields such as image recognition, voice recognition, object detection, and drug development. Accordingly, a variety of learning algorithms have been proposed, and the number of neurons constituting a neural network varies greatly among researchers. This study analyzed the learning characteristics according to the number of neurons of the currently used SGD, momentum methods, AdaGrad, RMSProp, and Adam methods. To this end, a neural network was constructed with one input layer, three hidden layers, and one output layer. ReLU was applied to the activation function, cross entropy error (CEE) was applied to the loss function, and MNIST was used for the experimental dataset. As a result, it was concluded that the number of neurons 100-300, the algorithm Adam, and the number of learning (iteraction) 200 would be the most efficient in deep learning learning. This study will provide implications for the algorithm to be developed and the reference value of the number of neurons given new learning data in the future.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.143-153
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• 2022

Any kind of animation film are almost inseparable from the role of characters, with distinct personalities, and well-created characters are not only the expressors of narrative and themes, but also the ones who communicate with the audience and form resonance. Nowadays, with the improvement of the public's aesthetics, the production of excellent animation, the characters with a single personality have been almost eliminated. So how to create a profound role has become a topic worthy of study. This paper is based on Freud's theory of personality structure and ego defense mechanism. The main research object is the main character of the animation film "The Tale of The Princess Kaguya". At the end of the thesis, by analyzing Kaguya's image characteristics and individual pursuits, it explores director Isao Takahata's understanding of character shaping. In this way, it also provides a reference to produce animation works.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.85-92
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• 2022

In this study, we aim to design an action game that increases the user experience. In order to increase the immersion of the game, the characteristics of the game used by the user were analyzed, and the systemic and visual characteristics of the game were designed with reference to each characteristic. The proposed method uses Unity 3D to implement an interaction system between objects in the game and is designed in a way that allows users to immerse themselves in the game. To induce immersion through the visual elements of the game, 2D objects and players are placed in a 3D space, and a 2D dynamic light shader is added. It is composed of inter-combat rules and monster behavior pattern collision detection and event detection. The proposed method contained the user experience with the implementation thesis, and showed the game's possibility of leading the user's affordance.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1167-1174
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• 2022

With the sustainable development and transformation of the city, public art as a business card of the famous city of culture has become a hot topic of research. The intervention of public art in public space not only brings users a sense of space experience, but also becomes a unique carrier of urban and rural image making. Although there is much research on the classification, aesthetics and function of public art, there is few quantitative research on user satisfaction. This paper takes the basic features of airport public art as a research object and the basic features of airport public art as the theoretical basis to study the impact of the basic characteristics of airport public art on user satisfaction. Research methods were based on questionnaire data of 247 people, in which models and hypotheses were tested using SPSS 21.0 software, based on the induction and extraction of nine influential factors in the basic characteristics of public art. The study found that public interpretation, media patterns, color perception, modeling form, place perception, city image and memory have significant positive effects on user satisfaction. The sharedness of public art, cognition and communication in public culture and spatial relations do not affect satisfaction. Conclusion, inspiration and prospect provide suggestions for designers and reference data and theoretical support for public art evaluation.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.