• Smart Media Journal
• /
• v.13 no.6
• /
• pp.9-15
• /
• 2024

In recent trends, there has been an increase in 'Qshing' attacks, a hybrid form of phishing that exploits fake QR (Quick Response) codes impersonating government agencies to steal personal and financial information. Particularly, this attack method is characterized by its stealthiness, as victims can be redirected to phishing pages or led to download malicious software simply by scanning a QR code, making it difficult for them to realize they have been targeted. In this paper, we have developed a classification technique utilizing machine learning algorithms to identify the maliciousness of URLs embedded in QR codes, and we have explored ways to integrate this with existing QR code readers. To this end, we constructed a dataset from 128,587 malicious URLs and 428,102 benign URLs, extracting 35 different features such as protocol and parameters, and used AutoML to identify the optimal algorithm and hyperparameters, achieving an accuracy of approximately 87.37%. Following this, we designed the integration of the trained classification model with existing QR code readers to implement a service capable of countering Qshing attacks. In conclusion, our findings confirm that deriving an optimized algorithm for classifying malicious URLs in QR codes and integrating it with existing QR code readers presents a viable solution to combat Qshing attacks.

• Food Science and Preservation
• /
• v.30 no.3
• /
• pp.459-471
• /
• 2023

The Bayesian network (BN) model was applied to analyze the characteristic variables that affect compliance with safety inspections of farmed eel during the production stage, using the data from 30,063 cases of eel aquafarm safety inspection in the Integrated Food Safety Information Network (IFSIN) from 2012 to 2021. The dataset for establishing the BN model included 77 non-conforming cases. Relevant HACCP data, geographic information about the aquafarms, and environmental data were collected and mapped to the IFSIN data to derive explanatory variables for nonconformity. Aquafarm HACCP certification, detection history of harmful substances during the last 5 y, history of nonconformity during the last 5 y, and the suitability of the aquatic environment as determined by the levels of total coliform bacteria and total organic carbon were selected as the explanatory variables. The highest achievable eel aquafarm noncompliance rate by manipulating the derived explanatory variables was 24.5%, which was 94 times higher than the overall farmed eel noncompliance rate reported in IFSIN between 2017 and 2021. The established BN model was validated using the IFSIN eel aquafarm inspection results conducted between January and August 2022. The noncompliance rate in the validation set was 0.22% (15 nonconformances out of 6,785 cases). The precision of BN model prediction was 0.1579, which was 71.4 times higher than the non-compliance rate of the validation set.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.28 no.1
• /
• pp.82-89
• /
• 2024

Black ice is very difficult to recognize and reduces the friction of the road surface, causing automobile accidents. Since black ice is difficult to detect, there is a need for a system that identifies black ice in real time and warns the driver. Various studies have been conducted to prevent black ice on road surfaces, but there is a lack of research on systems that identify black ice in real time and warn drivers. In this paper, an real-time image-based analysis system was developed to identify the condition of asphalt road surface, which is widely used in Korea. For this purpose, a dataset was built for each asphalt road surface image, and then the road surface condition was identified as dry, wet, black ice, and snow using deep learning. In addition, temperature and humidity data measured on the actual road surface were used to finalize the road surface condition. When the road surface was determined to be black ice, the salt spray equipment installed on the road was automatically activated. The surface condition recognition system for the asphalt concrete pavement and black ice automatic prevention system developed in this study are expected to ensure safe driving and reduce the incidence of traffic accidents.

• Information Systems Review
• /
• v.20 no.4
• /
• pp.59-78
• /
• 2018

With the advent of the various device types and marketing communication, customer's search and purchase behavior have become more complex and segmented. However, extant research on multichannel marketing effects of the purchase funnel has not reflected the specific features of device User Interface (UI) and User Experience (UX). In this study, we analyzed the marketing channel effects of multi-device shoppers using a unique click stream dataset from global online retailers. We examined device types that activate online shopping and compared the differences between marketing channels that promote visits. In addition, we estimated the direct and indirect effects on visits and purchase revenue through customer's accumulated experience and channel conversions. The findings indicate that the same customer selects a different marketing channel according to the device selection. These results can help retailers gain a better understanding of customers' decision-making process in multi-marketing channel environment and devise the optimal strategy taking into account various device types. Our empirical analyses yield business implications based on the significant results from global big data analytics and contribute academically meaningful theoretical framework using an economic model. We also provide strategic insights attributed to the practical value of an online marketing manager.

• Journal of the Korean earth science society
• /
• v.45 no.3
• /
• pp.192-202
• /
• 2024

Ocean reanalysis data are extensively used in ocean circulation and climate research by integrating observational data with numerical models. This approach overcomes the spatial and temporal limitations of observational data and provides high-resolution gridded information that considers the physical interactions between ocean variables. In this study, I extended the previously produced 12-year (2011-2022) Northwest Pacific regional ocean reanalysis data to create a long-term reanalysis dataset (K-ORA22E) with a horizontal resolution of 1/24° spanning 30 years (1993-2022). These data were analyzed to diagnose long-term ocean climate change in the Korean marginal seas. Analysis of the K-ORA22E data revealed that the axis of the Kuroshio extension has shifted northward by approximately 6 km per year over the past 30 years, with a significant increase in sea surface temperature north of the Kuroshio axis. Among the waters surrounding the Korean Peninsula, the East Sea exhibited the most significant temperature increase. In the East Sea, the temperature increase was more pronounced in the middle layer than in the surface layer, with the East Korea Warm Current showing a rate two to three times higher than the global average. In the central Yellow Sea, where the Yellow Sea Bottom Cold Water appears, temperatures increased over the long-term, but decreased along the west and south coasts of the Korean Peninsula. These spatial differences in long-term temperature changes appear to be closely related to the heat transport pathways of warm water from the Kuroshio Current. High-resolution regional ocean reanalysis data, such as the K-ORA22E produced in this study, are essential foundational data for understanding long-term variability in the Korean marginal seas and analyzing the impacts of climate change.

• Journal of Korea Port Economic Association
• /
• v.39 no.4
• /
• pp.243-254
• /
• 2023

This study investigates the factors contributing to price fluctuations in the shipscrapping market, the final stage in a vessel's life cycle. Shipping companies make decisions on ship dismantling based on factors such as declining freight rates, increasing vessel age leading to higher costs, or compliance with new environmental regulations. Utilizing the FMOLS (Fully Modified Ordinary Least Squares) and VECM (Vector Error Correction Model) methodologies, the research explores the long-term elasticities of factors influencing shipscrapping prices and examines short-term causal relationships. Using a time series dataset spanning from December 2015 to April 2023, covering a total of 90 months, the study focuses on the shipscrapping prices of Capesize vessels in India and Bangladesh, which constitute a significant portion of the shipbreaking market. The findings indicate that, in the long term, shipscrapping prices are closely related to global scrap prices, 20-year-old secondhand Capesize vessel prices, newbuilding prices, and exchange rates. In terms of short-term causal relationships, an increase in global scrap prices induces a rise in shipscrapping prices, while the remaining variables do not contribute to such increases. Specifically, an escalation in shipscrapping prices is associated with increased prices of 20-year-old secondhand vessels, newbuilding prices, and exchange rates. However, the other variables do not show a significant influence on short-term increases in shipscrapping prices.

• Oncology Letters
• /
• v.42 no.1
• /
• pp.453-460
• /
• 2019

The present study aimed to identify novel methylation markers of clear cell renal cell carcinoma (ccRCC) using microarray methylation analysis and evaluate their prognostic relevance in patient samples. To identify cancer-specific methylated biomarkers, microarray profiling of ccRCC samples from our institute (n=12) and The Cancer Genome Atlas (TCGA) database (n=160) were utilized, and the prognostic relevance of candidate genes were investigated in another TCGA dataset (n=153). For validation, pyrosequencing analyses with ccRCC samples from our institute (n=164) and another (n=117) were performed and the potential clinical application of selected biomarkers was examined. We identified 22 CpG island loci that were commonly hypermethylated in ccRCC. Kaplan-Meier analysis of TCGA data indicated that only 4/22 loci were significantly associated with disease progression. In the internal validation set, Kaplan-Meier analysis revealed that hypermethylation of two loci, zinc finger protein 492 (ZNF492) and G protein-coupled receptor 149 (GPR149), was significantly associated with shorter time-to-progression. Multivariate Cox regression models revealed that hypermethylation of ZNF492 [hazard ratio (HR), 5.44; P=0.001] and GPR149 (HR, 7.07; P<0.001) may be independent predictors of tumor progression. Similarly, the methylation status of these two genes was significantly associated with poor outcomes in the independent external validation cohort. Collectively, the present study proposed that the novel methylation markers ZNF492 and GPR149 could be independent prognostic indicators in patients with ccRCC.

• International Journal of Stem Cells
• /
• v.15 no.3
• /
• pp.324-333
• /
• 2022

Background and Objectives: This study was to investigate the role of microRNA-29a-3p (miR-29a-3p) in human bone marrow mesenchymal stem cells (hBMSCs), and its relationship with steroid-associated osteonecrosis. Methods and Results: The online tool GEO2R was used to screen out the differentially expressed genes (DEGs) in GSE123568 dataset. Quantitative real time-polymerase chain reaction (qRT-PCR) was performed to detect the expression of miR-29a-3p, forkhead box O3 (FOXO3), alkaline phosphatase (ALP), bone gamma-carboxyglutamate protein (OCN) and RUNX family transcription factor 2 (Runx2) in the hBMSCs isolated from the patients with steroid-associated osteonecrosis. CCK-8 assay was executed to measure cell viability; western blot assay was utilized to detect FOXO3, ALP, Runx2, OCN and β-catenin expression. Cell apoptosis and cell cycle were detected by flow cytometry. Immunofluorescence assay was used to detect the sub-cellular localization of β-catenin. Bioinformatics analysis and luciferase reporter gene assay were performed to confirm whether miR-29a-3p can combine with FOXO3 3'UTR. MiR-29a-3p was markedly up-regulated in the hBMSCs of patients with steroid-associated osteonecrosis, while FOXO3 mRNA was significantly down-regulated. Transfection of miR-29a-3p mimics significantly inhibited the hBMSCs' proliferation, osteogenic differentiation markers' expressions, including ALP, Runx2, OCN, and repressed the ALP activity, as well as promoted cell apoptosis and cell-cycle arrest. FOXO3 was identified as a target gene of miR-29a-3p, and miR-29a-3p can inhibit the expression of FOXO3 and β-catenin, and inhibition of miR-29a-3p promoted translocation of β-catenin to the nucleus. Conclusions: MiR-29a-3p can modulate FOXO3 expression and Wnt/β-catenin signaling to inhibit viability and osteogenic differentiation of hBMSCs, thereby promoting the development of steroid-associated osteonecrosis.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.20 no.1
• /
• pp.1-15
• /
• 2015

Impacts of Sea Surface Temperature (SST) assimilation to the prediction of upper ocean temperature is investigated by using a regional ocean forecasting system, in which 3-dimensional optimal interpolation is applied. In the present study, Sea Surface Temperature and Sea Ice Analysis (OSTIA) dataset is adopted for the daily SST assimilation. This study mainly compares two experimental results with (Exp. DA) and without data assimilation (Exp. NoDA). When comparing both results with OSTIA SST data during Sept. 2011, Exp. NoDA shows Root Mean Square Error (RMSE) of about $1.5^{\circ}C$ at 24, 48, 72 forecast hour. On the other hand, Exp. DA yields the relatively lower RMSE of below $0.8^{\circ}C$ at all forecast hour. In particular, RMSE from Exp. DA reaches $0.57^{\circ}C$ at 24 forecast hour, indicating that the assimilation of daily SST (i.e., OSTIA) improves the performance in the early SST prediction. Furthermore, reduction ratio of RMSE in the Exp. DA reaches over 60% in the Yellow and East seas. In order to examine impacts in the shallow costal region, the SST measured by eight moored buoys around Korean peninsula is compared with both experiments. Exp. DA reveals reduction ratio of RMSE over 70% in all season except for summer, showing the contribution of OSTIA assimilation to the short-range prediction in the coastal region. In addition, the effect of SST assimilation in the upper ocean temperature is examined by the comparison with Argo data in the East Sea. The comparison shows that RMSE from Exp. DA is reduced by $1.5^{\circ}C$ up to 100 m depth in winter where vertical mixing is strong. Thus, SST assimilation is found to be efficient also in the upper ocean prediction. However, the temperature below the mixed layer in winter reveals larger difference in Exp. DA, implying that SST assimilation has still a limitation to the prediction of ocean interior.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.6 no.1
• /
• pp.109-132
• /
• 2011

While the resource-based view suggests that a firm's competitive advantage rests on a set of valuable, rare and inimitable resources more generally (Barney, 1991), research in new firms has more specially indicated a link between initial resources and early performance and survival (Bruderl and Schussler, 1990; Fichman and Levinthal, 1991; Carroll et al., 1996). The RBV primarily focuses on the particular resources, and their characteristics, that provide the potential for advantage (Conner, 1991). Yet in order to realize this advantage, organizations must not only develop their resources, but also effectively deploy them (Admit and Shoemaker, 1993). This suggests that advantage from resources may reside in both the input (resource development) side and the output (resource deployment) side. This research looks at venture survival as a function of both the resources a firm owns, and the resources it can access from others. We focus more specifically on technology resources, which are among a technology-based firm's most critical resources (Itami, 1987). In addition, technological knowledge can contribute a large portion of the value of a firm's products (Goodman and Lawless, 1994). We look at both the input and output side: the pool of technology resources that serve as an input to a firm's activities, and the market that values and purchases the output of this activity. We take an international perspective, examining whether resources explain internationalization on the input and output side, and in turn, whether this internationalization can explain survival. We explore three sets of questions. First, can survival in entrepreneurial firms be explained as a function of the resources a firm owns, and beyond that, to those the firm can access, and still further, to those the firm can access internationally? Second, do resources explain internationalization on both the input and output side? And finally, does internationalization explain survival? Implications for theory include extending the RBV to not only include a firm's resources, but its access to the resources of other entities. In addition, examining internationalization on both the input and output side enables us to understand not just the potential advantage of resources, but the manner in which they are deployed as a source of advantage. This research also contributes to the literature on international entrepreneurship by examining whether internationalization can explain survival for early stage firms. For practitioners, this research will provide insights on the importance of building alliances and, in so doing, broadening an organization's perspective about the technology resources available to the firm on the input side. The study will also inform practitioners about the value of maximizing the market for a firm's valuable resources. In addition, this research provides an extraordinary opportunity to access a large, comprehensive, and longitudinal dataset on technology-based ventures in Korea.