• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.171-189
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• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• Journal of Ginseng Research
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• v.46 no.2
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• pp.235-247
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• 2022

Background: Ginsenoside Rg3 is one of the main active ingredients in ginseng. Here, we aimed to confirm its protective effect on the heart function in transverse aortic coarctation (TAC)-induced heart failure mice and explore the potential molecular mechanisms involved. Methods: The effects of ginsenoside Rg3 on heart and mitochondrial function were investigated by treating TAC-induced heart failure in mice. The mechanism of ginsenoside Rg3 for improving heart and mitochondrial function in mice with heart failure was predicted through integrative analysis of the proteome and plasma metabolome. Glucose uptake and myocardial insulin sensitivity were evaluated using micro-positron emission tomography. The effect of ginsenoside Rg3 on myocardial insulin sensitivity was clarified by combining in vivo animal experiments and in vitro cell experiments. Results: Treatment of TAC-induced mouse models with ginsenoside Rg3 significantly improved heart function and protected mitochondrial structure and function. Fusion of metabolomics, proteomics, and targeted metabolomics data showed that Rg3 regulated the glycolysis process, and Rg3 not only regulated glucose uptake but also improve myocardial insulin resistance. The molecular mechanism of ginsenoside Rg3 regulation of glucose metabolism was determined by exploring the interaction pathways of AMPK, insulin resistance, and glucose metabolism. The effect of ginsenoside Rg3 on the promotion of glucose uptake in IR-H9c2 cells by AMPK activation was dependent on the insulin signaling pathway. Conclusions: Ginsenoside Rg3 modulates glucose metabolism and significantly ameliorates insulin resistance through activation of the AMPK pathway.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.85-100
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• 2022

Purpose: This study is aimed to examine the association between initial enteral nutrition (EN) and the clinical prognosis among patients with severe and multiple traumatic injuries, and to investigate whether this association is modified by the patients' catabolic status. Methods: This was a retrospective study of 302 adult patients with severe and multiple traumatic injuries admitted between January 2017 and September 2020 at Ajou University hospital in Suwon, Korea. The initial nutritional support by EN and parenteral nutrition were monitored up to day 7 after admission. Patients were classified into "No", "Low", and "High" EN groups according to the level of initial EN. Multivariable-adjusted logistic regression and linear regression models were used to estimate the association of the initial EN levels at hospital admission with the risk of mortality, morbidities, and levels of nutrition-associated biochemical markers. Results: High EN support was associated with reduced mortality (odds ratio, 0.07; 95% confidence interval [CI], 0.02, 0.32) and lower levels of C-reactive protein (β, -0.22; 95% CI, -8.66, 1.48), but longer stay in the intensive care unit (β, 0.19; 95% CI, 1.82, 11.32). In analyses stratified by catabolic status, there were fewer incidences of hospital-acquired infections with increasing EN levels in the moderate or higher nitrogen balance group than in the mild nitrogen balance group. Conclusion: Our observation of the inverse association between levels of initial EN administration with mortality risk and inflammatory markers may indicate the possible benefits of active EN administration to the recovery process of severe and multiple trauma patients. Further studies are warranted on whether the catabolic status modifies the association between the initial EN and prognosis.

• Korean Association of Arts Management
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• no.56
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• pp.5-38
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• 2020

This study begins with the question of how culture-based communities can form a community culture and become a community of sustainable development. Based on the concept of community, community development factors and stage of development, cultural activities, and policy implementation theory, policy execution analysis models suitable for culture-based community projects were derived. A qualitative case study method was adopted as a research method, and success stories of culture-based village communities were selected as the 'Gamgol Community' in Sadong, Ansan, 'Sangdong Community' in Daebu-dong, Ansan, and 'Grimae Village' in Sinse-dong, Andong. Through in-depth interviews, literature analysis, and direct observation, the research analysis used pattern matching, explanation, chronicle analysis, and case integration analysis methods presented by Yin (2009). As a result of the study, first, the characteristics of the policy implementation strategy were taking place in the process of step-by-step development. The main factors in the community development phase were the improvement of community consciousness through the emotional change of participants and the change of capacity within the community. Second, it was understood that cultural activities played a major role in strengthening community consciousness and community capacity, and could be understood as various creative activities. Based on the ecological approach study on culture-based community, this study derived the policy execution analysis model, analyzed the case of culture-based village community, presented the direction of development of community and presented practical implications.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.279-284
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• 2022

As a study of the blended learning method on design education through the blended learning method, I would like to propose that more advanced learner-led customized design education is possible. Understanding in face-to-face classes and advantages in non-face-to-face classes can be supplemented in an appropriate way in remote classes. Advanced artificial intelligence and big data technology can provide personalized and subdivided learning materials and effective learning methods tailored to learners' levels and interests based on quantified data in design classes. In this paper, it was proposed to maximize the efficiency of the class by applying a method that exceeds the limitations of time and space through the proposal of the A La Carte model (A La Carte). It is a remote class that can be heard anytime, anywhere, and it is also possible to bridge the educational quality and educational gap provided to students living in underprivileged areas. As the goal of fostering creative convergence-type future talents, it is changing with a rapid technological development speed. It is necessary to adapt to the change in learning methods in line with this. An analysis of the infographic virtual space design and construction process through the A La Carte model (A La Carte) proposal was presented. Rather than simply acquiring knowledge, it is expected that knowledge can be sorted, distinguished, learned, and easily reborn with its own knowledge.

• Korean Journal of Culture and Social Issue
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• v.28 no.2
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• pp.107-131
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• 2022

This study was conducted with the aim of developing and validating a measure of the workplace bullying bystander behavior. For the purpose, items were developed by referring to previous studies related to workplace bullying, and behavior subtypes were defined as pro-bullying, defending, and bystander behaviors. After confirming the content validity with the help of experts, a total of 31 preliminary items were composed. The final 26 items were selected by conducting an exploratory factor analysis and verifying the validity and reliability of the scale with a survey of 288 office workers who have directly or indirectly witnessed workplace bullying over the past three years. In this process, it was confirmed that defense behavior was distinguished into two types: Active and supportive. Confirmatory factor analysis was conducted with data from 518 office workers who have directly or indirectly witnessed workplace bullying over the past year, and the validity and reliability of the developed scale were confirmed. As a result of comparing the competing models to reconfirm the subtypes, it was confirmed again that active defense behavior and supportive defense behavior were distinguished. The criterion-related validity of all subtypes was confirmed by setting the criterion variables for workplace bullying behavior, altruistic behavior, pro-social behavior, fear of intervention, moral disengagement, guilt, and moral identity. Based on the result of this study, follow-up research tasks related to workplace bullying bystander behavior scale were suggested and the methods to prevent and intervene in workplace bullying while utilizing workplace bullying bystander behaviors were discussed.

• 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.

• Journal of Ginseng Research
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• v.47 no.2
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• pp.302-310
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• 2023

Background: The most common type of dementia, Alzheimer's disease (AD), is marked by the formation of extracellular amyloid beta (Aβ) plaques. The impairments of axons and synapses appear in the process of Aβ plaques formation, and this damage could cause neurodegeneration. We previously reported that non-saponin fraction with rich polysaccharide (NFP) from Korean Red Ginseng (KRG) showed neuroprotective effects in AD. However, precise molecular mechanism of the therapeutic effects of NFP from KRG in AD still remains elusive. Methods: To investigate the therapeutic mechanisms of NFP from KRG on AD, we conducted proteomic analysis for frontal cortex from vehicle-treated wild-type, vehicle-treated 5XFAD mice, and NFP-treated 5XFAD mice by using nano-LC-ESI-MS/MS. Metabolic network analysis was additionally performed as the effects of NFP appeared to be associated with metabolism according to the proteome analysis. Results: Starting from 5,470 proteins, 2,636 proteins were selected for hierarchical clustering analysis, and finally 111 proteins were further selected for protein-protein interaction network analysis. A series of these analyses revealed that proteins associated with synapse and mitochondria might be linked to the therapeutic mechanism of NFP. Subsequent metabolic network analysis via genome-scale metabolic models that represent the three mouse groups showed that there were significant changes in metabolic fluxes of mitochondrial carnitine shuttle pathway and mitochondrial beta-oxidation of polyunsaturated fatty acids. Conclusion: Our results suggested that the therapeutic effects of NFP on AD were associated with synaptic- and mitochondrial-related pathways, and they provided targets for further rigorous studies on precise understanding of the molecular mechanism of NFP.

• Journal of Platform Technology
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• v.10 no.4
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• pp.47-55
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• 2022

Recently, diverse devices using different wireless technologies are gradually increasing in the IoT environment. In particular, it is essential to design an efficient feature extraction approach and detect the exact types of radio signals in order to accurately identify various radio signal modulation techniques. However, it is difficult to gather labeled wireless signal in a real environment due to the complexity of the process. In addition, various learning techniques based on deep learning have been proposed for wireless signal classification. In the case of deep learning, if the training dataset is not enough, it frequently meets the overfitting problem, which causes performance degradation of wireless signal classification techniques using deep learning models. In this paper, we propose a generative adversarial network(GAN) based on data augmentation techniques to improve classification performance when various wireless signals exist. When there are various types of wireless signals to be classified, if the amount of data representing a specific radio signal is small or unbalanced, the proposed solution is used to increase the amount of data related to the required wireless signal. In order to verify the validity of the proposed data augmentation algorithm, we generated the additional data for the specific wireless signal and implemented a CNN and LSTM-based wireless signal classifier based on the result of balancing. The experimental results show that the classification accuracy of the proposed solution is higher than when the data is unbalanced.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.23-31
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• 2023

Software development involves a series of stages, including requirements analysis, design, implementation, unit testing, and integration testing, similar to those used in the system engineering process. This study utilized MathWorks' model-based design platform to develop multi-function radar software and evaluated its feasibility and efficiency. Because the development of conventional radar software is performed by a unit algorithm rather than in an integrated form, it requires additional efforts to manage the integrated software, such as requirement analysis and integrated testing. The mode-based platform applied in this paper provides an integrated development environment for requirements analysis and allocation, algorithm development through simulation, automatic code generation for deployment, and integrated requirements testing, and result management. With the platform, we developed multi-level models of the multi-function radar software, verified them using test harnesses, managed requirements, and transformed them into hardware deployable language using the auto code generation tool. We expect this Model-based integrated development to reduce errors from miscommunication or other human factors and save on the development schedule and cost.