• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.1-12
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• 2022

Since the early 20th century, along with the interest and development of alternative psychotherapy, the field of art therapy has also been developed and expanded. In particular, the recent development of technology and the untact era brought about by the COVID-19 Pandemic is accelerating the development of new digital art therapy contents. Among them, the hot interest in virtual reality is raising expectations and questions about the effectiveness of psychotherapy given by new media beyond traditional art therapy. In this study, the characteristics of VRAT (Virtual Reality Art Therapy) content therapeutic factors were investigated through qualitative literature analysis based on the conceptual framework and therapeutic components of ETC (Expressive Therapies Continumm), an integrated art therapy theory. As a result of the study, VRAT contents showed mostly therapeutic factors in the left hemisphere that triggered the user's dynamic, perceptual, and cognitive factors, and the therapeutic factors in the right hemisphere, which focused on sensory, emotional, and symbolic factors, were relatively few. The reason seems to be due to the nature of the experimental stage, the absence of active intervention by the therapist and long-term session composition, and the fear, clumsiness, and unfamiliarity of users about VRAT in addition to the characteristics and technical limitations of the VRAT medium. The limitations of the study include the small number of documents to be analyzed and the insufficient form of current VRAT to be called art therapy. It is expected that the characteristics of the therapeutic factors of VRAT content media and environment derived as a result of this study will be usefully used for the appropriate development of VRAT content in the future.

• Korean Journal of Cognitive Science
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• v.33 no.2
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• pp.95-107
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• 2022

Facial processing of different racial origin has been investigated at various levels including perceptual, emotional, and socio-cultural processing. Particularly, a good deal of studies have been conducted to show "other race effect (ORE)" to indicate that subtle facial information such as identity or emotional expressions are often under-processed in racial out-group members. However, few studies have investigated whether attentional modulation toward racial out-group faces could explain ORE. We investigated whether novelty-driven attentional mechanism is involved in face perception using event-related potential (ERP). Twenty-two Korean (KR) and nine Caucasian-American (AM) participants were presented with emotional faces from the two racial origins while they performed a gender categorization task. KRs showed significantly greater P3 amplitudes to AM than to KR faces indicating that the early attentional processing underlies differential perception of racial out-group faces. Interestingly, P3 was not up-regulated in the AM subjects when they were presented with KR faces, perhaps due to massive habituation to KR faces during everyday social interaction. These results indicate that racial out-group faces are highly salient stimuli which automatically occupy attentional resources, but easily habituated with repeated exposure to the racial-out group.

• Clean Technology
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• v.29 no.2
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• pp.118-125
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• 2023

Once a site is contaminated with polychlorinated biphenyls (PCBs), serious environmental and human health risks are inevitable. Therefore, innovative but economical in situ remediation technologies must be immediately applied to the contaminated site. Recently, nanoscale zero-valent iron (nano-ZVI) particles have successfully been applied for the dechlorination of various chlorinated organic compounds like TCE, PCE and DDT, and they are considered to be environmentally safe due to the high abundance of iron in the earth's crust. Nano-ZVIs are much more reactive than granular ones, but tend to agglomerate due to their high surface energy and magnetic properties. In order to prevent them from being agglomerated toward larger particles, TiO₂ was used as a support to immobilize the nano-ZVI particles as much as possible. 10wt% ZVI/TiO₂ was prepared by adding NaBH₄ slowly into an FeSO₄/TiO₂ aqueous slurry. In spite of their non-uniformity in size, the nano-ZVI particles were quite successfully dispersed onto the exterior surface of a non-porous TiO₂ powder. The ZVI/TiO₂ was then employed to degrade Aroclor 1242, a kind of PCBs standard, in spiked soil, and its reactivity towards the degradation of Aroclor 1242 was investigated. The fabricated ZVI/TiO₂ degraded Aroclor 1242 in soil quite effectively, but the creation of remaining dechlorinated compounds, possibly high molecular weight hydrocarbons, in the soil was unavoidable.

• Asia Marketing Journal
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• v.11 no.2
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• pp.149-172
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• 2009

Prior research has investigated different effects of brand performance information such as premium price information and market share information on brand equity components - quality perception and brand preference. It was shown that the differential effects of brand performance information could depend on product-related variables like product category concept and quality variation in the product category. In this study, we conducted an experiment to find out how personal characteristics such as self-construal, price perception and brand commitment could influence the effects of different types of brand performance information. The results show that individuals who have independent self-construal, favorable price perception and emotional commitment with the brand develop more favorable evaluation of the premium price performance information resulting in more positive evaluations of the brand. However, individuals who have interdependent self-construal, unfavorable price perception and cognitive commitment with the brand develop more favorable evaluation of the market share performance information resulting in more positive evaluations of the brand. We discuss the theoretical and practical implications of this study and its limitations, along with future research interests.

• Korean Journal of Culture and Social Issue
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• v.11 no.3
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• pp.1-21
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• 2005

Many researches have argued the most important dimension of perception or evaluation of person is morality and competence in Korean culture. This study was to investigate the cultural characteristics of the criteria of personhood. Two studies were conducted to investigate the criteria used to evaluate person by qualitative approach and the differences of evaluation of wrongdoer who violates interpersonal norm or individual autonomy by experimental method. In addition, anger as emotional response to wrongdoer is conceptualized in terms of moral and self-conscious emotion. Expression of anger is less an outpouring of emotion and more a culturally regulated and normative mode of managing and putting into practice our society's system of rights and obligations - its moral code. According to results of qualitative data by interview and focus group interview, the most important criteria used to evaluate personhood was interpersonal concern, esp, expectation and norm. The results of experiment revealed that violation of interpersonal norm domain evoked angrier towards violator than autonomy domain. The subjects ascribed more blame and responsibility to interpersonal norm violator than autonomy keeper. Also function of behavior inhibition of anger was higher in interpersonal norm domain than autonomy domain.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.57-67
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• 2024

This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.

• Knowledge Management Research
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• v.25 no.2
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• pp.49-68
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• 2024

Increasing concerns regarding personal data privacy have complicated the acquisition of customer data through online marketing. This study investigates factors influencing customers' willingness to disclose information via a generative AI-based chatbot. Drawing on privacy calculus theory and regulatory focus theory, we explore how customer regulatory focus and familiarity with the generative AI-based chatbot shape disclosure intentions. Our study, involving 473 participants, reveals that low familiarity with the chatbot leads individuals with a prevention focus to perceive higher privacy risks and lower perceived usefulness compared to those with a promotion focus. However, with high familiarity, these differences diminish. Moreover, individuals with a promotion focus show a greater inclination to disclose information when familiarity with the generative AI-based chatbot is low, whereas this regulatory focus does not significantly impact disclosure intentions when familiarity is high. Perceived privacy risks mediate these relationships, underscoring the importance of understanding familiarity with the generative AI-based chatbot in facilitating personal information disclosure.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.91-107
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• 2024

Single-channel seismic exploration has proven effective in delineating subsurface geological structures using small-scale survey systems. The seismic data acquired through zero- or near-offset methods directly capture subsurface features along the vertical axis, facilitating the construction of corresponding seismic sections. However, substantial noise in single-channel seismic data hampers precise interpretation because of the low signal-to-noise ratio. This study introduces a novel approach that integrate noise reduction and signal enhancement via matrix rank optimization to address this issue. Unlike conventional rank-reduction methods, which retain selected singular values to mitigate random noise, our method optimizes the entire singular value spectrum, thus effectively tackling both random and erratic noises commonly found in environments with low signal-to-noise ratio. Additionally, to enhance the horizontal continuity of seismic events and mitigate signal loss during noise reduction, we introduced an adaptive weighting factor computed from the eigenimage of the seismic section. To access the robustness of the proposed method, we conducted numerical experiments using single-channel Sparker seismic data from the Chukchi Plateau in the Arctic Ocean. The results demonstrated that the seismic sections had significantly improved signal-to-noise ratios and minimal signal loss. These advancements hold promise for enhancing single-channel and high-resolution seismic surveys and aiding in the identification of marine development and submarine geological hazards in domestic coastal areas.

• Science of Emotion and Sensibility
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• v.27 no.2
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• pp.25-36
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• 2024

Past research reported mixed results on the effects of social exclusion on prosocial behavior. Whereas some studies reported an increase in prosocial motivation and behavior, others proposed that social exclusion causes a decrease in prosocial behavior along with negative reactions such as anger and aggression. These conflicting results may have arisen because prosocial behavior does not in itself always produce social reconnection. That is, although prosocial behavior is a major means of promoting social relationships, the excluded person does not need to act prosocially to benefit others unless the behavior leads to the restoration of the relationship. Unlike past research that assumed dichotomous situations of exclusion or belonging, the present research tested prosocial behavior in a social exclusion risk situation where the possibility of reconnection exists. In addition, we used the ability to potentially contribute to the group as another independent variable. We used a simulation game titled "Becoming a Union Member" to manipulate each participant's social exclusion risk and ability. Participants responded to a simple survey named member personality test and gave preliminary votes to one another, and exclusion risk was manipulated by the number of votes received. Later, ability was manipulated by disclosing perception test scores in the named member ability test. In both Experiments 1 and 2, participants who scored high in terms of social exclusion risk and low in the ability to potentially contribute showed prosocial behavior in stipulating larger donations. These results demonstrate that probable social reconnection defined by exclusion risk and ability is the key to explaining prosocial behavior following social exclusion.