• The Research Journal of the Costume Culture
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• v.29 no.3
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• pp.422-436
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• 2021

The fashion industry analyzes the value of its essence with ecological design and is expressed as an innovative sculpture using digital technology. Accordingly, this study explores ecological images and digital technologies, categorizes types and derives their meanings through analysis of ecological images shown in modern digital fashion. A literature survey was conducted on ecological images and digital technology as a theoretical background. To analyze the expression type and internal meanings of ecological images, designs with ecological formability were selected and analyzed from related journals, books, and internet sites. The finding are as follows: The expression type was first identified as organic curved garment silhouettes of a non-material liquid with digital retouching. Second, ecological fashion design includes structural shape that applies the silhouette of an organism and patterning of the ecosystem. Third, ecosystems consist of interactions between components of an ecosystem that appear in the interactive type. Accordingly, the internal meanings of ecological images in modern digital fashion are: first, digital fashion can encircle the inherent concepts of nature as organic collections of individuals; second, digital ecological images emphasize a sense of community with coexistence and harmony, playing a complementary role; and finally, the images express perceptual features by providing people with transcendent experiences. This study is significant as it analyzes new formative features based on ecological systems in the digital fashion environment, establishes an aesthetic system through internal meanings, and enhances awareness of human-natural relationships.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.881-895
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• 2023

Modern image inpainting techniques based on deep learning have achieved remarkable performance, and more and more people are working on repairing more complex and larger missing areas, although this is still challenging, especially for facial image inpainting. For a face image with a huge missing area, there are very few valid pixels available; however, people have an ability to imagine the complete picture in their mind according to their subjective will. It is important to simulate this capability while maintaining the identity features of the face as much as possible. To achieve this goal, we propose a three-stage network model, which we refer to as the identity and structure feature refinement network (ISFRNet). ISFRNet is based on 1) a pre-trained pSp-styleGAN model that generates an extremely realistic face image with rich structural features; 2) a shallow structured network with a small receptive field; and 3) a modified U-net with two encoders and a decoder, which has a large receptive field. We choose structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), L1 Loss and learned perceptual image patch similarity (LPIPS) to evaluate our model. When the missing region is 20%-40%, the above four metric scores of our model are 28.12, 0.942, 0.015 and 0.090, respectively. When the lost area is between 40% and 60%, the metric scores are 23.31, 0.840, 0.053 and 0.177, respectively. Our inpainting network not only guarantees excellent face identity feature recovery but also exhibits state-of-the-art performance compared to other multi-stage refinement models.

• Journal of the Korea Institute of Building Construction
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• v.23 no.5
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• pp.595-605
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• 2023

With the escalating prevalence of modular construction projects, there is a concurrent surge in scholarly and industrial intrigue in this domain, leading to a broadened spectrum of its applications. Modular construction, inherently facilitated by controlled factory settings, boasts the capability to consistently deliver edifices of superior quality. To optimize this advantage, the judicious integration of quality assurance methodologies during the site-specific phases of lifting and assembly is non-negotiable. This research embarked on a survey directed at project stakeholders, aiming to gauge the perceived significance and efficaciousness of prevailing quality preservation and oversight protocols during the aforementioned site stages, subsequently employing the Importance-Performance Analysis(IPA) for data interpretation. The findings elucidated that, while a majority of quality assurance procedures were adeptly executed, perceptual disparities existed among stakeholders regarding certain aspects, prompting recommendations for enhancement. This investigative endeavor lays a foundation, aiding future studies in amplifying the quality assurance cognizance among professionals during modular construction's site-assembly phase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.980-997
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• 2024

To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.113-145
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• 2009

Recently, due to the globalization of the IT(Information Technology) market, devices and systems designed in one country are used in other countries as well. This phenomenon is becoming the key factor for increased interest on cross-cultural, or cross-national, research within the IT area. However, as the IT market is becoming bigger and more globalized, a great number of IT practitioners are having difficulty in designing and developing devices or systems which can provide optimal experience. This is because not only tangible factors such as language and a country's economic or industrial power affect the user experience of a certain device or system but also invisible and intangible factors as well. Among such invisible and intangible factors, the cultural characteristics of users from different countries may affect the user experience of certain devices or systems because cultural characteristics affect how they understand and interpret the devices or systems. In other words, when users evaluate the quality of overall user experience, the cultural characteristics of each user act as a perceptual lens that leads the user to focus on a certain elements of experience. Therefore, there is a need within the IT field to consider cultural characteristics when designing or developing certain devices or systems and plan a strategy for localization. In such an environment, existing IS studies identify the culture with the country, emphasize the importance of culture in a national level perspective, and hypothesize that users within the same country have same cultural characteristics. Under such assumptions, these studies focus on the moderating effects of cultural characteristics on a national level within a certain theoretical framework. This has already been suggested by cross-cultural studies conducted by scholars such as Hofstede(1980) in providing numerical research results and measurement items for cultural characteristics and using such results or items as they increase the efficiency of studies. However, such national level culture has its limitations in forecasting and explaining individual-level behaviors such as voluntary device or system usage. This is because individual cultural characteristics are the outcome of not only the national culture but also the culture of a race, company, local area, family, and other groups that are formulated through interaction within the group. Therefore, national or nationally dominant cultural characteristics may have its limitations in forecasting and explaining the cultural characteristics of an individual. Moreover, past studies in psychology suggest a possibility that there exist different cultural characteristics within a single individual depending on the subject being measured or its context. For example, in relation to individual vs. collective characteristics, which is one of the major cultural characteristics, an individual may show collectivistic characteristics when he or she is with family or friends but show individualistic characteristics in his or her workplace. Therefore, this study acknowledged such limitations of past studies and conducted a research within the framework of 'theoretically integrated model of user satisfaction and emotional attachment', which was developed through a former study, on how the effects of different experience elements on emotional attachment or user satisfaction are differentiated depending on the individual cultural characteristics related to a system or device usage. In order to do this, this study hypothesized the moderating effects of four cultural dimensions (uncertainty avoidance, individualism vs, collectivism, masculinity vs. femininity, and power distance) as suggested by Hofstede(1980) within the theoretically integrated model of emotional attachment and user satisfaction. Statistical tests were then implemented on these moderating effects through conducting surveys with users of four digital devices (mobile phone, MP3 player, LCD TV, and refrigerator) in three countries (US, Germany, and Russia). In order to explain and forecast the behavior of personal device or system users, individual cultural characteristics must be measured, and depending on the target device or system, measurements must be measured independently. Through this suggestion, this study hopes to provide new and useful perspectives for future IS research.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.230-235
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• 2005

In this paper, we propose an algorithm that improves a tone quality of a noisy audio signal in order to enhance a performance of perceptual filter using intelligent estimation of noise pattern from a band degraded by additive noise. The proposed method doesn't use the estimated noise which is obtained from silent range. Instead new estimated noise according to the power of signal and effect of noise variation is considered for each frame. So the noisy audio signal is enhanced by the method which controls a estimation of noise Pattern effectively in a noise corruption band. To show the performance of the proposed algorithm, various input signals which had a different signal-to-noise ratio(SNR) such as $5\cal{dB},\;10\cal{dB},\;15\cal{dB}\;and\;20\cal{dB}$ were used to test the proposed algorithm. we carry out SSNR and NMR of objective measurement and MOS test of subjective measurement. An approximate improvement of $7.4\cal{dB},\;6.8\cal{dB},\;5.7\cal{dB},\;5.1\cal{dB}$ in SSNR and $15.7\cal{dB},\;15.5\cal{dB},\;15.2\cal{dB},\;14.8\cal{dB}$ in NMR is achieved with the input signals, respectively. And we confirm the enhancement of tone quality in terms of mean opinion score(MOS) test which is result of subjective measurement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.71-82
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• 2020

The existing transportation system, which is based on internal combustion engines, is rapidly being converted to electrification. Thus, eco-friendly public transportation with high transportation efficiency will continue to spread throughout the market in the near future. The purpose of this study is to compare and analyze the cognitive characteristics of passengers redgarding the technical and social factors of various public transportation means to help a successful introduction of eco-friendly public transit. Through a survey questionnaire (N=485), seven factors of seven transportation modes were evaluated and analyzed using principal component analysis. As a result, it is confirmed that potential passengers have high expectations for the eco-friendliness and city image of the eco-friendly buses. Also, it is confirmed that eco-friendly buses are superior in cleanliness and ride comfort than diesel buses. Given the study's results, this study identifies the cognitive characteristics of passengers regarding eco-friendly public transportation. We hope that these results will be used as basic information for image positioning and improved service with the use of eco-friendly transportation.

• Information Systems Review
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• v.8 no.2
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• pp.155-172
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• 2006

The importance and meaning of smell/taste information on online shopping are studied. The first hypothesis deals with this issue directly. We measure the perceived quality and purchase intention at the context of online shopping with/without smell and taste information. As expected, subjects show higher perceived quality/stronger purchase intention of a bar soap and vitamin C product when smell and taste information are provided. Following Peck and Childers(2003), the moderating effects of Need for Smell and Need for Taste are tested at the second hypothesis. Subjects with High in Need for Smell/Touch show stronger responses in terms of perceived quality and purchase intention. The level of trust about the online shopping mall provides interesting results. When the trust level of the online shopping mall is low, the smell/taste information play more important roles in improving the perceived quality and purchase intention. Subjects at the not-so-trusted shopping mall context result in higher perceived quality and purchase intention if perceptual information is provided. One of the theoretical contributions of this study includes the identification of critical information in online purchase decision making-smell and taste. On top of vision and hearing information, smell and taste information also can play critical roles when consumers do online shopping even at the shopping malls of low trust. In addition, managerial implications are provided.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.153-158
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• 2011

This paper presents subjective experimental results to understand how audio should be changed when a video clip is watched in 3D than 2D. This paper divided auditory perceptual information into two categories; distance and azimuth that a sound source contributes mostly, and spaciousness that scene or environment contribute mostly. According to the experiment for distance and azimuth, i.e. sound localization, we found that distance and azimuth of sound sources were magnified when heard with 3D than 2D video. This lead us to conclude 3D sound for localization should be designed to have more distance and azimuth than 2D sound. Also we found 3D sound are preferred to be played with not only 3D video clip but also 2D video clip. According to the experiment for spaciousness, we found people prefer sound with more reverberation when they watch 3D video clips than 2D video clips. This can be understood that 3D video provides more spacial information than 2D video. Those subjective experimental results can help audio engineer familiar with 2D audio to create 3D audio, and be fundamental information of future research to make 2D to 3D audio conversion system. Furthermore when designing 3D broadcasting system with limited bandwidth and with 2D TV supportive, we propose to consider transmitting stereoscopic video, audio with enhanced localization, and metadata for TV sets to generate reverberation for spaciousness.