• Journal of Advanced Technology Convergence
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• v.1 no.1
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• pp.15-24
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• 2022

This paper tried to investigate the moderating effect of chemyon sensitivity and usage situation in the relationship between self-presentation and brand preference. Data were collected from students of universities located in Chungnam. The analysis results can be summarized as follows. First of all, the effect of self-presentation on symbolic brand preference was not significant in both public and private use situations. On the other hand, the effect of self-presentation on functional brand preference was found to be significant in both situations. Second, the main effect of chemyon sensitivity was significant only when it had a negative effect on functional brand preference in public situations, but was not significant in other cases. Third, looking at the interaction effect of self-presentation and chemyon sensitivity, the brand preference did not show significant changes in those with relatively low chemyon sensitivity, regardless of the level of self-presentation, whether in public or private situations. This study is meaningful in that it reveals that chemyon sensitivity affects brand preference through interaction with self-presentation, whether the consumption situation is public or private.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.267-278
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• 2021

This study differentiated it from previous studies by selecting Chinese lifestyle shops in the current situation where lifestyle shops are rapidly emerging due to the increase in single-person households in China and changes in consumption patterns. The purpose of this study is to present basic data for establishing VMD strategies for domestic lifestyle shops wishing to enter China through the analysis of the characteristics of VMD elements. The results of this study are as follows.The research results are as follows. In the display elements of the VMD of Chinese lifestyle shops-GAROSU, CH'IN, and Nome, the appliances and props used differentiated shapes and materials according to the product concept and design. There seemed to be a difference depending on the concept of the lifestyle shop. Also, there were differences in the form of VP and the presentation method of PP and IP in VP, PP, and IP according to the store product group and the amount of products displayed in the presentation element. In a follow-up study, it is considered meaningful to conduct a study on domestic lifestyle shops and a comparative analysis of VMD between Chinese and domestic lifestyle shops.

• Science of Emotion and Sensibility
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• v.25 no.3
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• pp.117-126
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• 2022

This study seeks to identify usage behaviors and improvement factors to increase the academic and practical application of value the of color image scales. For this purpose, the authors discuss the positive and negative perspectives on the evaluation of previous studies on color image scales. Furthermore, a survey was conducted with 25 color experts who have been working in the field for over five years, and in-depth interviews were conducted with five of them. The contents of the survey are usage behaviors, evaluation, and the improvement of Kobayashi and IRI color image scales. In this process, emotional adjectives that need improvement were derived, and the opinions of experts related to improvements were collected. The analysis results are as follows. 1) As a result of the usage behaviors, 92% were aware of both color image scales. Moreover, 44% used both, and 56% used only one. 2) Regarding familiarity and trust, IRI was higher than Kobayashi. 3) A total of 88% of respondents stated that color image scales were necessary. A total of 43.6% of respondents, the largest group of respondents, indicated that color image scales are necessary in the field of practice. 4) Regarding the need for improvement, 88% responded that IRI color image scales need improvement. 5) The highest response to the factors requiring improvement was the reflection of the times, which was 31.9% for Kobayashi and 30.9% for IRI. 6) When improving color image scales, the adjectives that need to be treated as the most important were shown to be modern (15.8%) → natural, romantic, wild (8.8%) → dynamic (7.0%) → classic, casual, chic (5.3%). In conclusion, limitations were identified in the use of color image scales in practice and in the research areas, and there was a demand for correction and supplementation. The results of this study will serve as a foundational study related to color image scales, and it is expected that subsequent research related to color image scales will follow.

• Science of Emotion and Sensibility
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• v.25 no.3
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• pp.127-134
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• 2022

This study sought to identify the voice user interface (VUI) design parameters that evoked positive user emotions. Six VUI design parameters that could affect emotional user satisfaction were considered. The moderating effects of user gender and the design parameters were analyzed to determine the appropriate conditions for user satisfaction when interacting with the VUI. An interactive VUI system that could modify the six parameters was implemented using the Wizard of OZ experimental method. User emotions were assessed from the users' facial expression data, which was then converted into a valence score. The frequency analysis and chi-square test found that there were statistically significant moderating gender and AI effects. These results implied that it is beneficial to consider the users' gender when designing voice-based interactions. Adult/male/high-tone voices for males and adult/female/mid-tone voices for females are recommended as general guidelines for future VUI designs. Future analyses that consider various human factors will be able to more delicately assess human-AI interactions from a UX perspective.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.140-161
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• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.79-89
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• 2023

A multi-view display is regarded as the most practical technology to provide a three-dimensional effect to a viewer because it can provide an appropriate viewpoint according to the observer's position. But, most multi-view displays with flat shapes have a disadvantage in that a viewer watches 3D images only within a limited front viewing angle. In this paper, we proposed a spherical display using a ball lens with spherical symmetry that provides perfect parallax by extending the viewing zone to 360 degrees. In the proposed system, each projection lens is designed to be packaged into a small modular array, and the module array is arranged in a spherical shape around a ball lens to provide vertical and horizontal parallax. Through the applied optical module, the image is formed in the center of the ball lens, and 3D contents are clearly imaged with the size of about 0.65 times the diameter of the ball lens when the viewer watches them within the viewing window. Therefore, the feasibility of a 360-degree full parallax display that overcomes the spherical aberration of a ball lens and provides a wide field of view is confirmed experimentally.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.101-114
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• 2023

The data augmentation technique is effectively used to solve the problem of overfitting the model by allowing the training dataset to be viewed from various perspectives. In addition to image augmentation techniques such as rotation, cropping, horizontal flip, and vertical flip, occlusion-based data augmentation methods such as Cutmix and Cutout have been proposed. For models based on speech data, it is possible to use an occlusion-based data-based augmentation technique after converting a 1D speech signal into a 2D spectrogram. In particular, SpecAugment is an occlusion-based augmentation technique for speech spectrograms. In this study, we intend to compare and study data augmentation techniques that can be used in the problem of false-voice detection. Using data from the ASVspoof2017 and ASVspoof2019 competitions held to detect fake audio, a dataset applied with Cutout, Cutmix, and SpecAugment, an occlusion-based data augmentation method, was trained through an LCNN model. All three augmentation techniques, Cutout, Cutmix, and SpecAugment, generally improved the performance of the model. In ASVspoof2017, Cutmix, in ASVspoof2019 LA, Mixup, and in ASVspoof2019 PA, SpecAugment showed the best performance. In addition, increasing the number of masks for SpecAugment helps to improve performance. In conclusion, it is understood that the appropriate augmentation technique differs depending on the situation and data.

• Journal of IKEEE
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• v.27 no.3
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• pp.340-344
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• 2023

In this paper, we propose a study on the development of deep learning structure to secure visibility of outdoor LED display board according to weather change. The proposed technique secures the visibility of the outdoor LED display board by automatically adjusting the LED luminance according to the weather change using deep learning using an imaging device. In order to automatically adjust the LED luminance according to weather changes, a deep learning model that can classify the weather is created by learning it using a convolutional network after first going through a preprocessing process for the flattened background part image data. The applied deep learning network reduces the difference between the input value and the output value using the Residual learning function, inducing learning while taking the characteristics of the initial input value. Next, by using a controller that recognizes the weather and adjusts the luminance of the outdoor LED display board according to the weather change, the luminance is changed so that the luminance increases when the surrounding environment becomes bright, so that it can be seen clearly. In addition, when the surrounding environment becomes dark, the visibility is reduced due to scattering of light, so the brightness of the electronic display board is lowered so that it can be seen clearly. By applying the method proposed in this paper, the result of the certified measurement test of the luminance measurement according to the weather change of the LED sign board confirmed that the visibility of the outdoor LED sign board was secured according to the weather change.