• Information Systems Review
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• v.22 no.2
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• pp.43-52
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• 2020

The mobile game industry has become the one of the fastest growing industries with its astonishing market size. Despite its industrial importance, a few studies empirically considered actual purchasing behavior in mobile games rather than the intention to purchase. Therefore, this paper investigates the key drivers of in-app purchase by analyzing the game-log dataset provided from a mobile game company in Korea. Specifically, the effects of goal-directed, habitual and social-interacted playing behavior are analyzed on in-app purchase. Furthermore, the recursive relationship with playing and purchasing behaviorsis also considered. The result shows that all suggested factors have positive impacts on in-app purchase in the current period. In addition, the effect of previous habitual playing has a positive impact, but the effect of social-interacted playing and in-app purchase in the previous period have negative impacts on in-app purchase of the current period. These findings can improve our understanding of the impact of game playing on in-app purchase in mobile games, and provide meaningful insights for researchers and practitioners.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.41-51
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• 2024

In this paper, we explore the enhancement of target detection accuracy in the guided weapon using deep learning object detection on infrared (IR) images. Due to the characteristics of IR images being influenced by factors such as time and temperature, it's crucial to ensure a consistent representation of object features in various environments when training the model. A simple way to address this is by emphasizing the features of target objects and reducing noise within the infrared images through appropriate pre-processing techniques. However, in previous studies, there has not been sufficient discussion on pre-processing methods in learning deep learning models based on infrared images. In this paper, we aim to investigate the impact of image pre-processing techniques on infrared image-based training for object detection. To achieve this, we analyze the pre-processing results on infrared images that utilized global or local information from the video and the image. In addition, in order to confirm the impact of images converted by each pre-processing technique on object detector training, we learn the YOLOX target detector for images processed by various pre-processing methods and analyze them. In particular, the results of the experiments using the CLAHE (Contrast Limited Adaptive Histogram Equalization) shows the highest detection accuracy with a mean average precision (mAP) of 81.9%.

• Knowledge Management Research
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• v.25 no.2
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• pp.135-153
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• 2024

With the recent emergence of smart tourist cities, premium mobility is being considered an important means of transportation in the tourism. However, there has been insufficient research conducted on the experience of premium mobility among its users. Accordingly, this study used CIT to analyze the components of the user experience of customers who used premium mobility. In order to specifically identify the factors that make up the premium mobility experience, 366 cases of satisfaction and 13 cases of dissatisfaction were collected through a total of 273 online surveys. As a result of the study, based on the customer's experience using premium mobility, CIT was applied to derive 6 categories and 9 sub-factors that constitute the perception of premium mobility. In particular, this study is different from existing studies in that convenience was added as a new category out of the 6 categories, and wide ride comfort and high price were derived as new sub-factors among the 9 sub-factors. Because of this, it has academic significance. Therefore, if scales suitable for quantitative research are developed based on the derived constructs, they could be widely applied to various topics related to premium mobility in the tourism field.

• Food Science and Preservation
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• v.30 no.4
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• pp.716-728
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• 2023

The anti-adipogenic activity of Glycyrrhiza uralensis was investigated by examining the effects of its ethanol extract (GUE) on a mouse model with a high-fat diet (HFD) and 3T3-L1 preadipocytes during adipocyte differentiation. GUE administration for eight weeks significantly reduced weight gain in mice fed an HFD. GUE effectively inhibited 3T3-L1 preadipocyte differentiation and lipid droplet accumulation. This inhibitory effect is associated with the downregulation of key adipogenic regulators, including PPARγ and C/EBPα, and the modulation of adipose metabolism regulators, such as Fasn and Fabp4. LC-Q-TOF-MS analysis identified twelve phenolic and flavonoid compounds, including liquiritigenin and licorice saponin, in the GUE. These findings demonstrate that the anti-obesity effect of the GUE is attributed to the biological activity of its phenolic and flavonoid compounds. Therefore, the GUE has potential anti-obesity activity. Moreover, further studies on the isolation of bioactive components from the GUE and the investigation of the underlying molecular mechanisms of the GUE are required to establish its efficacy in metabolic disorders, including obesity.

• Information Systems Review
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• v.25 no.1
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• pp.129-143
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• 2023

In the era of big data, the field of artificial intelligence is showing remarkable growth, and in particular, the image classification learning methods by deep learning are becoming an important area. Various studies have been actively conducted to further improve the performance of CNNs, which have been widely used in image classification, among which a representative method is the Convolutional Recurrent Neural Network (CRNN) algorithm. The CRNN algorithm consists of a combination of CNN for image classification and RNNs for recognizing time series elements. However, since the inputs used in the RNN area of CRNN are the flatten values extracted by applying the convolution and pooling technique to the image, pixel values in the same phase in the image appear in different order. And this makes it difficult to properly learn the sequence of arrangements in the image intended by the RNN. Therefore, this study aims to improve image classification performance by proposing a novel hybrid method of CNN and RNN applying the concepts of encoder and decoder. In this study, the effectiveness of the new hybrid method was verified through various experiments. This study has academic implications in that it broadens the applicability of encoder and decoder concepts, and the proposed method has advantages in terms of model learning time and infrastructure construction costs as it does not significantly increase complexity compared to conventional hybrid methods. In addition, this study has practical implications in that it presents the possibility of improving the quality of services provided in various fields that require accurate image classification.

• Korean Journal of Radiology
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• v.23 no.4
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• pp.446-454
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• 2022

Objective: To evaluate whether hyperoxia-induced ΔR₁ (hyperO₂ΔR₁) can accurately identify histological infarction in an acute cerebral stroke model. Materials and Methods: In 18 rats, MRI parameters, including hyperO₂ΔR₁, apparent diffusion coefficient (ADC), cerebral blood flow and volume, and ¹⁸F-fluorodeoxyglucose uptake on PET were measured 2.5, 4.5, and 6.5 hours after a 60-minutes occlusion of the right middle cerebral artery. Histological examination of the brain was performed immediately following the imaging studies. MRI and PET images were co-registered with digitized histological images. The ipsilateral hemisphere was divided into histological infarct (histological cell death), non-infarct ischemic (no cell death but ADC decrease), and nonischemic (no cell death or ADC decrease) areas for comparisons of imaging parameters. The levels of hyperO₂ΔR₁ and ADC were measured voxel-wise from the infarct core to the non-ischemic region. The correlation between areas of hyperO₂ΔR₁-derived infarction and histological cell death was evaluated. Results: HyperO₂ΔR₁ increased only in the infarct area (p ≤ 0.046) compared to the other areas. ADC decreased stepwise from non-ischemic to infarct areas (p = 0.002 at all time points). The other parameters did not show consistent differences among the three areas across the three time points. HyperO₂ΔR₁ sharply declined from the core to the border of the infarct areas, whereas there was no change within the non-infarct areas. A hyperO₂ΔR₁ value of 0.04 s^-1 was considered the criterion to identify histological infarction. ADC increased gradually from the infarct core to the periphery, without a pronounced difference at the border between the infarct and non-infarct areas. Areas of hyperO₂ΔR₁ higher than 0.04 s^-1 on MRI were strongly positively correlated with histological cell death (r = 0.862; p < 0.001). Conclusion: HyperO₂ΔR₁ may be used as an accurate and early (2.5 hours after onset) indicator of histological infarction in acute stroke.

• Information Systems Review
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• v.19 no.3
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• pp.69-89
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• 2017

In the information age, the rapid development of information technology provides people with an enriching experience yet also causes them harm because of information security (IS) issues. The IS of smartphones faces great challenges. Although many studies on IS awareness have been conducted, most of them have focused on PCs and do not consider the security issues of smartphones. In this study, we focus on those factors that affect IS awareness for both PCs and smartphones. We also analyze the differences in the impacts of certain factors on PCs and smartphones based on the proposed research model. The results are summarized as follows. First, the understanding of security technique, understanding of IS threat, and IS education have significant impacts on IS awareness for PCs and smartphones, while IS intention has a significant impact on IS awareness for PCs but not for smartphones. Moreover, IS policy has no significant impact on IS awareness. Second, PCs and smartphones show no significant differences in IS awareness, IS threat, and IS intention, but show significant differences in understanding of security technique, IS education, and IS policy.

• IMMUNE NETWORK
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• v.21 no.5
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• pp.34.1-34.16
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• 2021

Sjögren's syndrome (SS) is an autoimmune disease characterized by dryness of the mouth and eyes. The glandular dysfunction in SS involves not only T cell-mediated destruction of the glands but also autoantibodies against the type 3 muscarinic acetylcholine receptor or aquaporin 5 (AQP5) that interfere with the secretion process. Studies on the breakage of tolerance and induction of autoantibodies to these autoantigens could benefit SS patients. To break tolerance, we utilized a PmE-L peptide derived from the AQP5-homologous aquaporin of Prevotella melaninogenica (PmAqp) that contained both a B cell "E" epitope and a T cell epitope. Repeated subcutaneous immunization of C57BL/6 mice with the PmE-L peptide efficiently induced the production of Abs against the "E" epitope of mouse/human AQP5 (AQP5E), and we aimed to characterize the antigen specificity, the sequences of AQP5E-specific B cell receptors, and salivary gland phenotypes of these mice. Sera containing anti-AQP5E IgG not only stained mouse Aqp5 expressed in the submandibular glands but also detected PmApq and PmE-L by immunoblotting, suggesting molecular mimicry. Characterization of the AQP5E-specific autoantibodies selected from the screening of phage display Ab libraries and mapping of the B cell receptor repertoires revealed that the AQP5E-specific B cells acquired the ability to bind to the Ag through cumulative somatic hypermutation. Importantly, animals with anti-AQP5E Abs had decreased salivary flow rates without immune cell infiltration into the salivary glands. This model will be useful for investigating the role of anti-AQP5 autoantibodies in glandular dysfunction in SS and testing new therapeutics targeting autoantibody production.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.27.1-27.12
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• 2023

Background: Environmental exposure is characterized by low concentration, chronic, and complex exposure. Traditional epidemiological studies show limitations in reflecting these characteristics since they usually focus on a single or very limited number of exposure factors at a time. In this study, we adopted the methodology of environment-wide association study (EWAS) to figure out the association of human liver function with various environmentally hazardous substances. Methods: We analyzed 2,961 participants from the Korean National Environmental Health Survey Cycle 4 (2018-2020). Using generalized linear model (GLM) analysis, we analyzed the association of 72 variables with 3 liver function indices (aspartate aminotransferase [AST], alanine aminotransferase [ALT], and gamma glutamyl transferase [GGT]). Finally, we visualized our results with Manhattan plot. Results: In GLM analysis, perfluorooctanesulfonate were positively associated with ALT (odds ratio [OR]: 2.2; 95% confidence interval [CI]: 1.39-3.46; p_adjusted = 0.0147) and perfluorodecanoic acid showed positive association with GGT (OR: 2.73; 95% CI: 1.36-5.5; p_adjusted = 0.0256). Plasma mercury showed positive association with GGT (OR: 1.45; 95% CI: 1.14-1.84; p_adjusted = 0.0315). Using a plastic container while keeping food in the refrigerator was associated with elevated GGT compared to using a glass container (OR: 1.51; 95% CI: 1.16-1.95; p_adjusted = 0.0153). 2-ethyl-5-oxohexyl phthalate, showed a negative trend with all 3 indices, with AST (OR: 0.54; 95% CI: 0.39-0.73; p_adjusted = 0.00357), ALT (OR: 0.5; 95% CI: 0.34-0.75; p_adjusted = 0.036), GGT (OR: 0.55; 95% CI: 0.4-0.76; p_adjusted = 0.00697). Bisphenol S and frequent use of sunblock cream showed negative association with ALT (OR: 0.77; 95% CI: 0.66-0.89), and GGT (OR: 0.25; 95% CI: 0.11-0.55), respectively. Conclusions: We conducted an exploratory study on environmental exposure and human liver function. By using EWAS methodology, we identified 7 factors that could have potential association with liver function.

• Journal of Plant Biotechnology
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• v.50
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• pp.142-154
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• 2023

Plant abscission is a natural process in which plant organs or tissues undergo detachment, a strategy selected by nature for the disposal of nonessential organs and widespread dissemination of seeds and fruits. However, from an agricultural perspective, the abscission of seeds or fruits represents a major factor that reduces crop productivity and product quality. Therefore, during the crop domestication process in traditional agriculture, mutants exhibiting suppressed abscission were selected and crossbred, thereby enabling the production of modern crop varieties such as rice, tomatoes, canola, and soybeans. These crops possess a unique trait of retaining ripe fruits or seeds in contrast to disposal via abscission. During the previous century, research on quantitative trait loci along with genetic and molecular biological studies on Arabidopsis thaliana have elucidated various cell biological mechanisms, signaling pathways, and transcription regulators involved in abscission. Additionally, it has been revealed that various hormone signals, which are involved in plant growth, play crucial roles in modulating abscission activity. Researchers have developed several chemical treatments that target these hormones and signal transduction pathways to enhance crop yields. This review aimed to introduce the previously identified signal transduction pathways and pivotal regulators implicated in abscission activity. Moreover, this review will discuss the future direction of research required to investigate crop abscission mechanisms for their potential application in smart farming and other areas of agriculture, as well as areas within model systems that require extensive research.