• Tunnel and Underground Space
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• v.33 no.3
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• pp.189-207
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• 2023

In the present study, the thermoshearing experiment on a rough rock fracture were modeled using a three-dimensional grain-based distinct element model (GBDEM). The experiment was conducted by the Korea Institute of Construction Technology to investigate the progressive shear failure of fracture under the influence of thermal stress in a critical stress state. The numerical model employs an assembly of multiple polyhedral grains and their interfaces to represent the rock sample, and calculates the coupled thermo-mechanical behavior of the grains (blocks) and the interfaces (contacts) using 3DEC, a DEM code. The primary focus was on simulating the temperature evolution, generation of thermal stress, and shear and normal displacements of the fracture. Two fracture models, namely the mated fracture model and the unmated fracture model, were constructed based on the degree of surface matedness, and their respective behaviors were compared and analyzed. By leveraging the advantage of the DEM, the contact area between the fracture surfaces was continuously monitored during the simulation, enabling an examination of its influence on shear behavior. The numerical results demonstrated distinct differences depending on the degree of the surface matedness at the initial stage. In the mated fracture model, where the surfaces were in almost full contact, the characteristic stages of peak stress and residual stress commonly observed in shear behavior of natural rock joints were reasonably replicated, despite exhibiting discrepancies with the experimental results. The analysis of contact area variation over time confirmed that our numerical model effectively simulated the abrupt normal dilation and shear slip, stress softening phenomenon, and transition to the residual state that occur during the peak stress stage. The unmated fracture model, which closely resembled the experimental specimen, showed qualitative agreement with the experimental observations, including heat transfer characteristics, the progressive shear failure process induced by heating, and the increase in thermal stress. However, there were some mismatches between the numerical and experimental results regarding the onset of fracture slip and the magnitudes of fracture stress and displacement. This research was conducted as part of DECOVALEX-2023 Task G, and we expect the numerical model to be enhanced through continued collaboration with other research teams and validated in further studies.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.189-217
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• 2023

The metaverse is a virtual world where individuals engage in social, economic, and cultural activities using avatars, which represent an alternate version of oneself within the virtual realm. While the metaverse has garnered global attention recently, research exploring the identity manifested through avatars within the metaverse remains limited. This study investigates the influence of four IT artifact characteristics related to avatar usage in the metaverse-avatar representation, avatar copresence, avatar profiling, and avatar-space interaction-on perceived avatar identity verification. A survey was conducted with 196 experienced users of the Zepeto platform, and hypotheses were tested using structural equation modeling. The analysis results indicate that the use of IT artifacts enabling avatar representation, avatar copresence, and avatar-space interaction has a positive impact on perceived avatar identity verification. This achieved self-verification indirectly influences the satisfaction and subsequent intention to continue using the metaverse. This study contributes to the academic field by empirically verifying the metaverse technological factors that influence the projected identity onto avatars within the metaverse. Furthermore, it is expected to provide effective guidelines for metaverse platform companies in designing and implementing the metaverse.

• The Journal of Bigdata
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• v.6 no.2
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• pp.61-70
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• 2021

The objective of this study was to describe specific approaches for data extraction from graph when statistical information is not directly reported in some articles, enabling data intergration and meta-analysis for quantitative data synthesis. Particularly, meta-analysis is an important analysis tool that allows the right decision making for evidence-based medicine by systematically and objectively selects target literature, quantifies the results of individual studies, and provides the overall effect size. For data integration and meta-analysis, we investigated the strength points about the introduction and application of Adobe Acrobet Reader and Python-based Jupiter Lab software, a computer tool that extracts accurate statistical figures from graphs. We used as an example data that was statistically verified throught an previous studies and the original data could be obtained from ClinicalTrials.gov. As a result of meta-analysis of the original data and the extraction values of each computer software, there was no statistically significant difference between the extraction methods. In addition, the intra-rater reliability of between researchers was confirmed and the consistency was high. Therefore, In terms of maintaining the integrity of statistical information, measurement using a computational tool is recommended rather than the classically used methods.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.320-328
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• 2023

Underwater active target detection is vital for defense systems, requiring accurate detection and estimation of distance and velocity. Sequential transmission is necessary at each beam angle, but divided pulse length leads to range ambiguity. Multi-frequency transmission results in time-bandwidth product losses when bandwidth is divided. To overcome these problem, we propose a novel method using Generalized Sinusoidal Frequency Modulation (GSFM) for rapid target detection, enabling low-correlation pulses between subpulses without bandwidth division. The proposed method allows for rapid updates of the distance and velocity of target by employing GSFM with minimized pulse length. To evaluate our method, we simulated an underwater environment with reverberation. In the simulation, a linear frequency modulation of 0.05 s caused an average distance estimation error of 50 % and a velocity estimation error of 103 % due to limited frequency band. In contrast, GSFM accurately and quickly tracked targets with distance and velocity estimation errors of 10 % and 14 %, respectively, even with pulses of the same length. Furthermore, GSFM provided approximate azimuth information by transmitting highly orthogonal subpulses for each azimuth.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.303-314
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• 2023

Voice conversion, a technology that allows an individual's speech data to be regenerated with the acoustic properties(tone, cadence, gender) of another, has countless applications in education, communication, and entertainment. This paper proposes an approach based on the StarGAN-VC model that generates realistic-sounding speech without requiring parallel utterances. To overcome the constraints of the existing StarGAN-VC model that utilizes one-hot vectors of original and target speaker information, this paper extracts feature vectors of target speakers using a pre-trained version of Rawnet3. This results in a latent space where voice conversion can be performed without direct speaker-to-speaker mappings, enabling an any-to-any structure. In addition to the loss terms used in the original StarGAN-VC model, Wasserstein distance is used as a loss term to ensure that generated voice segments match the acoustic properties of the target voice. Two Time-Scale Update Rule (TTUR) is also used to facilitate stable training. Experimental results show that the proposed method outperforms previous methods, including the StarGAN-VC network on which it was based.

• Asia Marketing Journal
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• v.16 no.1
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• pp.1-12
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• 2014

The goal-gradient hypothesis states that the tendency to approach a goal increases with the increasing proximity of the goal (Hull 1932). It was initially supported with an evidence of animal experiments and since then, several papers have investigated the goal-gradient hypothesis in humans. Although there are some evidences related to the goal-gradient hypothesis in human behaviors, none of previous studies can properly explain its underlying mechanism, and what's more, they were not able to suggest useful managerial applications in human behaviors. From these perspectives, this work points out that there are some theoretical weaknesses to apply the goal-gradient hypothesis into the complicated human decision-making behaviors and proposes an alternative theoretical mechanismthat underlies the goal-gradient hypothesis in human. Finally, it offers insights into managerial implications of the goal-gradient hypothesis in the marketing field. This study focuses on the changes in motivations for achieving goals, in terms of how approaches to goals vary according to temporal distance from those goals. Specifically, the temporal construal theory (Liberman and Trope 1998) is considered as the underlying mechanism of the goal-gradient in that the temporal construal theory argues how the temporal distance from a goal makes people change their associated values regarding to that goal. According to the temporal construal theory, the value of distant future outcomes (near future outcomes) is construed on the basis of abstract and central features (concrete and peripheral features), and it argues that distant future situations are construed on a higher level than near future situations. This means that the value associated with the high-level construal is enhanced over delay, whereas the value associated with the low-level construal is discounted over delay. Our propositions suggest that the goal-gradient behavior in human can be motivated by the different aspects or characteristics of the goal as time changes based on the temporal construal theory. Thus, the following propositions are proposed. P 1-1: If the goal is far away, consumers put more value on the central features that are more associated with the desirability of the goal. P 1-2: If the goal is far away, consumers put more effort into accomplishing the goal that has more central features, regardless of its peripheral features. P 2-1: If a goal is near, consumers put more value on the peripheral features that are more associated with the feasibility of the goal. P 2-2: If a goal is near, consumers put more effort into accomplishing the goal that has more peripheral features, regardless of its central features. We hope to provide sufficient managerial implications for the companies as our research aims to show how consumers react differently as they progress toward the goal. Proposed propositions may provide guidance for companies developing a loyalty program, enabling them to understand what kinds of benefits or services they should provide or emphasize to consumers in loyalty programs on the basis of the time-dependent changes in outcome values (such as gifts, reward coupons). The effects of temporal distance from a goal should inform companies' marketing activities and help themto determine where emphasis should be placed in designing the benefits of their loyalty program.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.953-964
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• 2023

Climate change is undeniably the most urgent challenge that humanity faces today. Despite this, the level of public awareness and understanding of climate change remains insufficient, indicating a need for more proactive education and the development of supportive content. In particular, it is crucial to intensify climate change education during elementary and secondary schooling when values and ethical consciousness begin to form. However, there is a significant lack of age-appropriate, experiential educational content. To address this, our study has developed an innovative 3D simulator, enabling learners to indirectly experience the effects of climate change, specifically sea-level rise. This simulator considers not only sea-level rise caused by climate change but also storm surges, which is a design based on the analysis of long-term wave observation big data. To make the simulator accessible and engaging for students, we utilized the 'Unity' game engine. We further propose using this simulator as a part of a comprehensive educational program on climate change.

• Therapeutic Science for Rehabilitation
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• v.12 no.4
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• pp.53-65
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• 2023

Objective : This study aimed to identify the experiences and practices of occupational therapists in mental health and provide interventions for improving body function in individuals with mental illness. Methods : Data were collected from mental health therapists between November 7 and November 14, 2022. A survey was distributed via email and 46 responses were analyzed using descriptive statistics and correlations. Results : The majority were female (58.7%), aged 20-30 years (84.8%), working in mental health centers (41.3%), and undergoing mental health occupational therapy training (91.3%). They had 1-3 years of mental health experience (65.2%) and were commonly involved in programs (71.1%), case management (62.2%), and administration (57.8%). Interventions for physical functioning were common (73.9%), including group interventions (41.2%), such as stretching, aerobic exercise, and walk training, and individual interventions (38.1%), such as walking, stretching, and aerobic exercise. Conclusion : Occupational therapists play a crucial role in enabling individuals with mental illness to engage in daily life activities. However, relevant studies in this field are lacking. This study emphasizes the importance of mental health occupational therapy and the need for evidence-based services for physical function improvement interventions to provide more effective treatments for mental illnesses.

• Journal of the Korea Computer Graphics Society
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• v.29 no.5
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• pp.11-20
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• 2023

In this paper, we propose a novel deep learning-based motion reconstruction approach that facilitates the generation of full-body motions, including finger motions, while also enabling the online adjustment of motion generation delays. The proposed method combines the Vive Tracker with a deep learning method to achieve more accurate motion reconstruction while effectively mitigating foot skating issues through the use of an Inverse Kinematics (IK) solver. The proposed method utilizes a trained AutoEncoder to reconstruct character body motions using tracker data in real-time while offering the flexibility to adjust motion generation delays as needed. To generate hand motions suitable for the reconstructed body motion, we employ a Fully Connected Network (FCN). By combining the reconstructed body motion from the AutoEncoder with the hand motions generated by the FCN, we can generate full-body motions of characters that include hand movements. In order to alleviate foot skating issues in motions generated by deep learning-based methods, we use an IK solver. By setting the trackers located near the character's feet as end-effectors for the IK solver, our method precisely controls and corrects the character's foot movements, thereby enhancing the overall accuracy of the generated motions. Through experiments, we validate the accuracy of motion generation in the proposed deep learning-based motion reconstruction scheme, as well as the ability to adjust latency based on user input. Additionally, we assess the correction performance by comparing motions with the IK solver applied to those without it, focusing particularly on how it addresses the foot skating issue in the generated full-body motions.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.363-374
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• 2023

The limitation in deriving the species richness representing the entire country of South Korea lies in its relatively short history of species field observations and the scattered observation data, which has been collected by various organizations in different fields. In this study, a comprehensive compilation of the observation data for plants held by agencies under the Ministry of Environment was conducted, enabling the construction of a time series dataset spanning over 100 years. The data integration was carried out using minimal criteria such as species name, observed location, and time (year) followed by data verification and correction processes. Based on the integrated plant species data, the comprehensive collection of plant species in South Korea has occurred predominantly since 2000, and the number of plant species explored through these surveys appears to be converging recently. The collection of species survey data necessary for deriving national-level biodiversity information has recently begun to meet the necessary conditions. Applying the Chao 2 method, the species richness of indigenous plants estimated at 3,182.6 for the 70-year period since 1951. A minimum cumulative period of 7 years is required for this estimation. This plant species richness from this study can be a baseline to study future changes in species richness in South Korea. Moreover, the integrated data with the estimation method for species richness used in this study appears to be applicable to derive regional biodiversity indices such as for local government units as well.