• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.246-256
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• 2022

Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400^th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• Fashion & Textile Research Journal
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• v.24 no.4
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• pp.386-398
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• 2022

This study was conducted to corroborate the factors that influence consumer characteristics and technology acceptance on online luxury platforms, which are rapidly emerging as distribution channels for luxury brands. To this end, the relationship between the degree of technology acceptance and behavioral intention of fashion consumers on online luxury platforms and the effect on specific factors such as age and gender was investigated to see if there was a difference in behavior and use behavior. A survey was conducted on Korean consumers between the age of 20 and 40 who have used online luxury platforms and then, a statistical analysis was conducted. As a result of the study, performance expectancy and facilitating conditions, hedonic motivation, price value, and habit were found to have a significant effect on platform behavioral intention, but effort expectancy and social influence did not have a significant effect. Additionally, both facilitating conditions and habit were found to have a directly significant effect on the platform use behavior, and it was confirmed that the platform behavior intention also had a significant effect on the use behavior. As a result of confirming the moderating effect of gender and age, there was no difference based on gender, but only the relationship between price value and behavioral intention was found to have a moderating effect. It is hoped that domestic online luxury platforms will grow into channels with distinct characteristics and continue to develop in the luxury market by utilizing specific affect factors of this study.

• Journal of the Korean Geotechnical Society
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• v.24 no.12
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• pp.33-40
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• 2008

The load distribution and deformation of rock-socketed drilled shafts subjected to axial loads are evaluated by a load-transfer method. The emphasis is on quantifying the effect of coupled soil resistance in rock-socketed drilled shafts using the 2D elasto-plastic finite element analysis. Slippage and shear load transfer behavior at the pile-soil interface are investigated by using a user-subroutine interface model (FRlC). It is shown that the coupled soil resistance provides the influence of pile toe settlement as the shaft resistance is increased to an ultimate limit state. The results show that the coupling effect is closely related to the value of pile diameter over rock mass modulus (D/$E_{mass}$) and the ratio of total shaft resistance against total applied load ($R_s$/Q). Through comparisons with field case studies, the 2D numerical analysis reseanably presented load transfer of pile and coupling effect due to the transfer of shaft shear loading, and thus represents a significant improvement in the prediction of load deflections of drilled shafts.

• Design Convergence Study
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• v.15 no.2
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• pp.169-184
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• 2016

Using geospatial information in the early design phase is crucial because it requires considerable time, money, and effort. We use VWorld, part of the National Spatial Information Distribution system provided by the Korean Ministry of Land, Infrastructure and Transportation, for providing geospatial information to building designers. We provide methods to adopt VWorld geospatial information to building design and develop plugins for a BIM authoring tool to transform and construct necessary BIM data in a user-friendly format. BIM users are benefitted from extra design information supplied from sibling disciplines such as urban design. GIS users are benefited by feedback building information continuously supplied from building projects based upon standard GIS coordinates. It is clear that an architectural designer with BIM tool can save time and efforts to obtain the geospatial information related a project using the developed system as result of this research.

• Design Convergence Study
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• v.15 no.2
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• pp.223-236
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• 2016

The infrastructure of public transportation of Seoul which has been developed in parallel with the progress of modernization receives successful performance evaluation at home and abroad, currently representing the highest transport distribution ratio. In spite of this fact, the public transportation of Seoul, which has entered into advanced phase of services, still leaves much to be desired, in particular, the mobility considering the transportation vulnerable is not well assured. It is time to provide proper supports for the efficient mobility of public transportation in accordance with the social changes present in the aging and multicultural society. This study inquired about the current status of public transportation and that of its users. In addition, the main inquiry target was oriented to the elderly and foreigners for observation and investigation, as well as for the analysis of their behavior. Furthermore, through in-depth interviews, inconvenient factors have been found according to public transportation means and its usage phase, by carrying out detailed evaluations of public transportation services. Based on this, the enhancement elements were defined and the corresponding concept was designed through a series of idea workshops, and this study intended to contribute to improving future public transportation services by proposing the improvement scheme applicable to the upcoming public transportation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.1
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• pp.45-50
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• 2023

Roblox, the world's No. 1 metaverse platform, has more than 3 billion subscription accounts and more than 150 millionmonthly active users (MAU). Despite such high interest in metaverse, existing studies on analyzing the risk of cyberattacks and security in the metaverse environment is insufficient. Therefore, in this paper, we propose a new steganography-basedcovert communication method in Roblox. In our proposed method, a secret message is hidden into an image by using a function provided in the Roblox Experience environment and then the image is automatically stored in the RobloxExperience participants' devices (PC or Smartphone) so that a malicious software can extract the hidden message fromthe image. By our experiments in the Roblox metaverse environment, we validated our proposed method works and thus want to inform our proposed method can be used in various cyberattacks and crimes such as the spread of secret commands, the establishment of a steganography botnet, and the mass distribution of malicious malware in metaverse platforms.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.57-66
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• 2023

In this study, we propose a novel research framework for the recommendation system that can estimate the user's emotional state and reflect it in the recommendation process by applying deep learning techniques and emotion AI (artificial intelligence). To this end, we build an emotion classification model that classifies each of the seven emotions of angry, disgust, fear, happy, sad, surprise, and neutral, respectively, and propose a model that can reflect this result in the recommendation process. However, in the general emotion classification data, the difference in distribution ratio between each label is large, so it may be difficult to expect generalized classification results. In this study, since the number of emotion data such as disgust in emotion image data is often insufficient, correction is made through augmentation. Lastly, we propose a method to reflect the emotion prediction model based on data through image augmentation in the recommendation systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.125-132
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• 2024

Optical satellite images are being used for national security and collection of information, and their utilization is increasing. However, it acquires low-quality images that are not suitable for the user's requirement due to weather conditions and time constraints. In this paper, a deep learning-based conversion of image and colorization model referring to high-resolution SAR images was created to simulate the occluded area with clouds of optical satellite images. The model was experimented according to the type of algorithm applied and input data, and each simulated images was compared and analyzed. In particular, the amount of pixel value information between the input black-and-white image and the SAR image was similarly constructed to overcome the problem caused by the relatively lack of color information. As a result of the experiment, the histogram distribution of the simulated image learned with the Gray-scale image and the high-resolution SAR image was relatively similar to the original image. In addition, the RMSE value was about 6.9827 and the PSNR value was about 31.3960 calculated for quantitative analysis.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.61-69
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• 2009

This paper presents an improved method measuring inter-utterance similarity in an example-based dialogue system, which searches the most similar utterance in a dialogue database to generate a response to a given user utterance. Unlike general inter-sentence similarity measures, the inter-utterance similarity measure for example-based dialogue system should consider not only word distribution but also various linguistic features, such as affirmation/negation, tense, modality, sentence type, which affects the natural conversation. However, previous approaches do not sufficiently reflect these features. This paper proposes a new utterance similarity measure by analyzing and reflecting various linguistic features to improve performance in accuracy. Also, by considering substitutability of the features, the proposed method can utilize limited number of examples. Experimental results show that the proposed method achieves 10%p improvement in accuracy compared to the previous method.