• The Journal of the Korea Contents Association
• /
• v.22 no.6
• /
• pp.596-605
• /
• 2022

This study aimed to introduce research on coerced debt victimization and interventions in the context of domestic violence. To achieve the aim, this study reviewed existing studies on coerced debt conducted in the US. This study discussed the followings: First, coerced debt was theorized by coerced control theory of domestic violence and control mechanisms of economic abuse and conceptualized as fraud and force. Second, the effects of coerced debt included credit damage, economic dependence, and barriers to housing, employment, and safety. Third, to intervene the victimization, service providers should endure uncertainty and its time consuming process of recovering, provide an intense and personalized advocacy, and overcome the problems of absence of policies to support the victims. Finally, service providers should have educations and training programs on the assessment and intervention skills of coerced debt acknowledging empowerment and safety of the victims as the most important.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.275-275
• /
• 2021

A fixed Z-R relationship approach, such as the Marshall-Palmer relationship, for an entire year and for different seasons can be problematic in cases where the relationship varies spatially and temporally throughout a region. From this perspective, this study explores the use of long-term radar reflectivity for South Korea to obtain a nationwide calibrated Z-R relationship and the associated uncertainties within a Bayesian regression framework. This study also investigates seasonal differences in the Z-R relationship and their roles in reducing systematic error. Distinct differences in the Z-R parameters in space are identified, and more importantly, an inverse relationship between the parameters is clearly identified with distinct regimes based on the seasons. A spatially structured pattern in the parameters exists, particularly parameter α for the wet season and parameter β for the dry season. A pronounced region of high values during the wet and dry seasons may be partially associated with storm movements in that season. Finally, the radar rainfall estimates through the calibrated Z-R relationship are compared with the existing Z-R relationships for estimating stratiform rainfall and convective rainfall. Overall, the radar rainfall fields based on the proposed modeling procedure are similar to the observed rainfall fields, whereas the radar rainfall fields obtained from the existing Marshall-Palmer Z-R relationship show a systematic underestimation. The obtained Z-R relationships are validated by testing the predictions on unseen radar-gauge pairs in the year 2018, in the context of cross-validation. The cross-validation results are largely similar to those in the calibration process, suggesting that the derived Z-R relationships fit the radar-gauge pairs reasonably well.

• Journal of Korean Elementary Science Education
• /
• v.43 no.1
• /
• pp.81-94
• /
• 2024

This study explores and conducts an in-depth comparison of the epistemic characteristics in different data types utilized in the science inquiries of preservice teachers regarding noise as a risk in everyday life. Focusing on primary and secondary data in the context of science inquiries about noise, we examined how these data types differ in science inquires in terms of inquiry design, data collection, and analyses. The findings reveal that sensor-based primary data enable direct measurement and observation of key phenomena. Conversely, secondary data rely on predetermined measurement methods within a public data system. These differences require different epistemic considerations during the inquiry process. Based on these findings, we discuss the educational implications concerning teaching approaches for science inquiries, teacher education for inquiry teaching, and the development of risk response competencies in preparation for the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) era.

• Journal of Daesoon Thought and the Religions of East Asia
• /
• v.3 no.2
• /
• pp.71-92
• /
• 2024

The world we live in is becoming more convenient thanks to the inventions of science and technology. Still, the world is also becoming more and more unpredictable with the current situation of VUCA (Volatility, Uncertainty, Complexity, Ambiguity). The Covid-19 pandemic brought the biggest global disaster ever with 774,631,444 infected people and 7,031,216 deaths (WHO on February 11, 2024) but it seems that humanity is gradually forgetting this disaster. Meanwhile the economic stimulus packages worth trillions of dollars from governments after the pandemic have further caused the world debt bubble to swell. The bubble burst scenario is something that many economic experts fear. Apparently, in the transitional period of the early decades of the 21st century, the world's economic, cultural, political, social, natural, and environmental aspects have undergone profound transformations: from the real estate and finance crises in the United States since 2008; through the melting of the Arctic ice over the past several decades; to the double disaster of the earthquake and tsunami in Japan in 2011. Especially, in the context of the world economic crisis after the COVID-19 pandemic, the human achievements of the past thousands of years are in jeopardy of being wiped out in an instant. Many people are predicting a bad scenario for a chain collapse. Facing the signals of an imminent economic catastrophe based on the appearance of "the Gray Rhino, Black Swan and White Elephant," many drawn in by Eschatological thought declare that Doomsday will occur shortly. This is the time for many other people to hope for the incoming Messiah. The Messiah is said to appear when people feel despair or suffer a great disaster because faith in the Savior can help them overcome adversity mentally. This research will find out how adherents of Buddhism view and deal with civilizational crises by examining history via symbols associated with Maitreya as based upon the Buddhist Messiah, Maitreya.

• Geomechanics and Engineering
• /
• v.39 no.1
• /
• pp.1-11
• /
• 2024

Geotechnical parameter estimation is critical to the design, performance, safety, and cost and schedule management in Tunnel Boring Machine projects. Since these parameters vary within a certain range, relying on mean values for evaluation introduces significant risks to the project. Due to the non-homogeneous characteristics of geological formation, data may not exhibit a normal distribution and the presence of outliers might be deceptive. Therefore, the use of reliable analyses and simulation models is inevitable in the course of the data evaluation process. Advanced modeling techniques enable comprehensive analysis of the project data and allowing to model the uncertainty in geotechnical parameters. This study involves using Monte Carlo Simulation method to predict probabilistic distributions of field data, and therefore, establish a basis for designs and in turn to minimize project risks. In the study, 166 sets of geotechnical data Obtained from 35 boreholes including Standard Penetration Test, Limit Pressure, Liquid Limit, and Plastic Limit values, which are mostly utilized parameters in estimating project requirements, were used to estimate the geotechnical data distribution of the study field. In this context, firstly, the data was subjected to multi-parameter linear regression and variance analysis. Then, the obtained equations were implemented into a Monte Carlo Simulation, and probabilistic distributions of the geotechnical data of the field were simulated and corresponding to the 90% probability range, along with the minimum and maximum values at the 5% probability levels presented. Accordingly, while the average SPT N30 value is 42.86, but the highest occurrence rate is 50.81. For Net Limit Pressure, the average field data is 17.07 kg/cm², with the maximum occurrence between 9.6 kg/cm² and 13.7 kg/cm². Similarly, the average Plastic Limit value is 22.32, while the most probable value is 20.6. The average Liquid Limit value is 56.73, with the highest probability at 54.48, as indicated in the statistical data distribution. Understanding the percentage distribution of data likely to be encountered in the project allows for accurate forecasting of both high and low probability scenarios, offering a significant advantage, particularly in ordering TBM requirements.

• Asia pacific journal of information systems
• /
• v.21 no.4
• /
• pp.1-25
• /
• 2011

Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

• Journal of KIISE:Software and Applications
• /
• v.29 no.12
• /
• pp.966-978
• /
• 2002

There are two important problems in improving text classification systems based on machine learning approach. The first one, called "selection problem", is how to select a minimum number of informative documents from a given document collection. The second one, called "composition problem", is how to reorganize selected training documents so that they can fit an adopted learning method. The former problem is addressed in "active learning" algorithms, and the latter is discussed in "boosting" algorithms. This paper proposes a new learning method, called AdaBUS, which proactively solves the above problems in the context of Naive Bayes classification systems. The proposed method constructs more accurate classification hypothesis by increasing the valiance in "weak" hypotheses that determine the final classification hypothesis. Consequently, the proposed algorithm yields perturbation effect makes the boosting algorithm work properly. Through the empirical experiment using the Routers-21578 document collection, we show that the AdaBUS algorithm more significantly improves the Naive Bayes-based classification system than other conventional learning methodson system than other conventional learning methods

• Journal of the Korean association of regional geographers
• /
• v.20 no.1
• /
• pp.49-69
• /
• 2014

The theory of creative city can be seen as one that reflects a relationship between recent change of economic environment and socio-spatial reconstruction in the so-called 'cultural turn' to deindustrialization. This paper considers approaching methods to knowledge-based economy or cultural economy as a context of development of theory of creative city, and suggests types of conceptualization of creative city. Then it reviews creative perspectives which can be found in recent domestic and oversea research trends on creative city, especially relating its nature with neoliberalism. Finally this paper discusses critically the concept of creative class as a social constitution of creativity or creative economy, and that of creative city as its spatial constitution. The concept of creative class can be criticized in terms of ambiguity of the concept of class, class-biased and economy-privileged idea, market valorization of culture, individualization against community, normalization of flexible labor market, and uncertainty of economic success of creative city. The concept of creative city can be criticized in terms of limitation of interests to city, ignorance of national and global dimensions, decontextual normative vision, legitimation of neoliberal city, lack of proof of causality between creative class and economic success, polarization of within and between cities.

• The Journal of Small Business Innovation
• /
• v.19 no.3
• /
• pp.57-74
• /
• 2016

This paper analyzes the role of strategic fit, cooperation, and performance in small-sized subpart suppliers' interactions with large businesses. For this purpose, this paper analyzes survey data from 90 first-tier suppliers of Samsung Electronics and evaluates how strategic fit and cooperative relationships affect their performance. Empirical analysis suggests that strategic fit positively affects small companies' business and innovation performance. This finding aligns with theories arguing for strategies that accommodate specific business environments. In addition, strategic fit is crucial for innovativeness of SMEs (Small and Medium-sized Enterprises). With regard to forming relationships with large companies, findings also show that high quality technological and personnel cooperation boosts subpart suppliers' productivity and efficiency as notably reflected in SMEs' business performance. Moreover, such cooperation between small and large companies reinforces the benefits associated with strategic fit and innovation. This means that if the business environment of small-sized subpart suppliers is uncertain, harnessing differentiated strategies and pursuing collaborations with prime companies will produce innovative outcomes (e.g., increased patent publications). On the other hand, when degree of uncertainty is small, pursuing cost leadership strategies and collaborating with prime companies in areas, such as technology and personnel, will help small-sized subpart suppliers produce innovative outcomes. Based on these findings, this paper argues that choosing the right competitive strategy for a specific business context is intrinsically tied to (1) augmenting technological and human collaborations with prime companies, (2) improving the quality of these interactions, and (3) generating competitiveness among small subpart suppliers. Both competition and cooperation are necessary for strengthening the competitiveness of small companies.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.2
• /
• pp.249-259
• /
• 2018

More than half of annual rainfall occurs in summer season in Korea due to its climate condition and geographical location. A frequency analysis is mostly adopted for designing hydraulic structure under the such concentrated rainfall condition. Among the various distributions, univariate Gumbel distribution has been routinely used for rainfall frequency analysis in Korea. However, the distributional changes in extreme rainfall have been globally observed including Korea. More specifically, the univariate Gumbel distribution based rainfall frequency analysis is often fail to describe multimodal behaviors which are mainly influenced by distinct climate conditions during the wet season. In this context, we purposed a Gumbel mixture distribution based rainfall frequency analysis with a Bayesian framework, and further the results were compared to that of the univariate. It was found that the proposed model showed better performance in describing underlying distributions, leading to the lower Bayesian information criterion (BIC) values. The mixed Gumbel distribution was more robust for describing the upper tail of the distribution which playes a crucial role in estimating more reliable estimates of design rainfall uncertainty occurred by peak of upper tail than single Gumbel distribution. Therefore, it can be concluded that the mixed Gumbel distribution is more compatible for extreme frequency analysis rainfall data with two or more peaks on its distribution.