• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2334-2347
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• 2023

Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.

• MALSORI
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• no.62
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• pp.85-96
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• 2007

In this paper, we carried out recognition experiments for noisy speech having various levels of car noise and output of an audio system using the speech interface. The speech interface consists of three parts: pre-processing, acoustic echo canceller, post-processing. First, a high pass filter is employed as a pre-processing part to remove some engine noises. Then, an echo canceller implemented by using an FIR-type filter with an NLMS adaptive algorithm is used to remove the music or speech coming from the audio system in a car. As a last part, the MMSE-STSA based speech enhancement method is applied to the out of the echo canceller to remove the residual noise further. For recognition experiments, we generated test signals by adding music to the car noisy speech from Aurora 2 database. The HTK-based continuous HMM system is constructed for a recognition system. Experimental results show that the proposed speech interface is very promising for robust speech recognition in a noisy car environment.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.639-642
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• 2000

본 논문에서는 구름이나 연기와 같은 non-rigid object에 대한 영역 분할 방식에 대해 연구하였다. Non-rigid object의 효과적인 영역 분할을 위해서 object의 윤곽선을 정확히 파악해 낼 수 있는 장점을 가진 watershed 알고리즘을 사용하였다. 하지만 이 알고리즘은 object가 많은 영역으로 분할되는 oversegmentation 현상이 발생하여 본 논문에서는 pre, post-processing을 통해 이 oversegmentation 현상을 극복하고자 하였다. Pre-processing에서는 noise를 제거하고 영상을 단순화하면서 정확한 gradient magnitude를 구할 수 있는 방법에 대해서, post-processing에서는 통계적인 분석을 통한 region merging을 이용하여 object를 최적화 상태로 찾아줄 수 있는 방법에 대하여 연구하였다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.219-222
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• 2007

Today, use of high resolution satellite image with at least 1m resolution is expanding into many more areas including forest, river way, city, seashore and so forth for disaster prevention. Interest in this medium is increasing among the general public due to the roll-out to the private sector as Google earth, Virtual Earth and so forth. However, pre-processing process that revises the geometrical distortion that result at the time of photographing is required in order to use high resolution satellite image. The purpose of this research is to search the most accurate GCP(Ground Control Point) information acquisition method that is used for the revision of high resolution satellite image's geometrical distortion through automated processing. Through this, it is possible to contribute to increasing the level of accuracy at the time of high resolution satellite image revision and to secure promptness.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.271-276
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• 2003

The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) of Terra and Aqua satellites, launched in December 1999 and May 2002, has been directly received by Korea Aerospace Research Institute (KARI) ground station facility from July 2002. MODIS scans a swath width of 2330 km that is sufficiently wide to cover Korean peninsular, Yellow and East Sea at once. The MODIS has 36 spectral bands between 0.415 $\mu\textrm{m}$ and 14.235 $\mu\textrm{m}$, i.e., through the visible into the thermal infrared. MODIS has been observed active fires, floods, smoke transport, dust storms, severe storms since February of 2000. The satellite imagery obtained through the MODIS will be utilized for many application such as national territorial management, agriculture, natural environment, atmosphere and ocean, etc. In this study is to introduce various application field of MODIS imagery and data processing system.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.84-89
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• 2023

In water resource management, data prediction is performed using artificial intelligence, and companies, governments, and institutions continue to attempt to efficiently manage resources through this. LSTM is a model specialized for processing time series data, which can identify data patterns that change over time and has been attempted to predict groundwater level data. However, groundwater level data can cause sen-sor errors, missing values, or outliers, and these problems can degrade the performance of the LSTM model, and there is a need to improve data quality by processing them in the pretreatment stage. Therefore, in pre-dicting groundwater data, we will compare the LSTM model with the MSE and the model after normaliza-tion through distribution, and discuss the important process of analysis and data preprocessing according to the comparison results and changes in the results.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.1 s.145
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• pp.87-95
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• 2006

There are hundreds of ship blocks which are under the block assembly, painting, and outfitting assembly works in the pre-erection shops of shipyard. Generally, each block is planned to be processed in a pre-erection shop according to the block type by the long-term production-scheduling before six months. However, many blocks can't be processed in the planned time and the planned shop since the before and after block-processing changes or delays the planned sequential works in pre-erection shops. Therefore, it is essential to monitor the current location of each block and work in process to cope with the changed situation of pre-erection shops. Present study integrates PDA, GPS, and CDMA not only to chase the location of each block but also to exchange the pre-erection work order and the work report between the production-scheduling server and the production managers in the pre-erection shops. This study shows a prototype for the block tracing and process monitoring in the pre-erection shops.

• Food Science of Animal Resources
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• v.37 no.2
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• pp.288-296
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• 2017

We investigated the effects of fermented red beet extract and ascorbic acid on color development in meat emulsions. The pH of meat emulsions containing red beet extract decreased with an increase in the amount of extract added. The redness of the treated meat emulsions was higher than that of the control with no added nitrite or fermented red beet extract (p< 0.05), though the redness of the meat emulsions treated with fermented red beet extract only was lower than in that treated with both fermented red beet extract and ascorbic acid (p<0.05). The highest VBN, TBARS, and total viable count values were observed in the control, and these values in the meat emulsions treated with fermented red beet extract were higher than in that treated with both fermented red beet extract and ascorbic acid (p<0.05). E. coli and coliform bacteria were not found in any of the meat emulsions tested. Treatment T2, containing nitrite and ascorbic acid, had the highest overall acceptability score (p<0.05); however, there was no significant difference between the T2 treatment and the T6 treatment, which contained 10% pre-converted nitrite from red beet extract and 0.05% ascorbic acid (p>0.05). The residual nitrite content of the meat emulsions treated with ascorbic acid was lower than in those treated without ascorbic acid (p<0.05). Thus, the combination of fermented red beet extract and ascorbic acid could be a viable alternative to synthetic nitrite for the stability of color development in meat emulsions.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.31-39
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• 2010

In this study, we prepared the real environmental sound data sets arising from people's movement comprising 9 different environment types. The environmental sounds are pre-processed with pre-emphasis and Hamming window, then go into the classification experiments with the extracted features using MFCC (Mel-Frequency Cepstral Coefficients). The GMM (Gaussian Mixture Model) classifier without post processing tends to yield abruptly changing classification results since it does not consider the results of the neighboring frames. Hence we proposed the post processing methods which suppress abruptly changing classification results by taking the probability or the rank of the neighboring frames into account. According to the experimental results, the method using the probability of neighboring frames improve the recognition performance by more than 10% when compared with the method without post processing.

• Water for future
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• v.26 no.3
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• pp.87-101
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• 1993

A finite element model RIV-FEM2 for the hydrodynamic study in a river is developed based on two-dimensional shallow water wave equation and dissipative Galerkin's method. RIV-FEM2 consists of pre-processing, analysis processing and post-processing. Pre- and analysis processing is programmed with Fortran-77 and post-processing with turbo-Pascal respectively. The model is tested with two dimensional problems, including flow through bends, bridges, and symmetric contraction. The two dimensional tests shows stable and efficient results for various situations. Applicability of the model is verified by applying to natural river. The model will provide a basic contribution to the hydrodynamic analysis in a river.