• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.2
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• pp.53-66
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• 2023

Role models are also known to influence an individual's job or career choice. The positive effect of role models on entrepreneurship has already been revealed through many precious researches. It is said that people choose not only family members who are related by blood, such as parents, siblings, and relatives, but also acquaintances whom they have met through social relationships as role models. In this study, we divided into entrepreneurs with no role models other than themselves and entrepreneurs with role models. In addition, we classified parental siblings and relative role models as role models with strong ties, and acquaintance role models as role models with weak ties. We analyzed the differences in personal attributes, entrepreneurial orientation factors, and learning orientation between the entrepreneurs with role models and those without role models. Also, the differences in personal attributes, innovativeness, proactiveness, risk-taking propensity, and learning orientation between the entrepreneurs with strong ties role models and those with weak ties role models were examined. The empirical analysis results are as follows. First, it was found that the proportion of women entrepreneurs without role models is higher. Second, the entrepreneurs with role models with weak ties tend to run larger scale start-ups. Third, it was found that the entrepreneurs with role models of weak ties tend to have higher learning orientation. Fourth, gender shows the greatest influence on th absence or presence of role models. Fifth, it was found that learning orientation and startup size have the greatest influence on the decision of the role model with weak ties or that with strong ties.

• Smart Media Journal
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• v.13 no.3
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• pp.18-26
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• 2024

Road surface monitoring is essential for maintaining road environment safety through managing risk factors like rutting and crack detection. Using autonomous driving-based UGVs with high-performance 2D laser sensors enables more precise measurements. However, the increased energy consumption of these sensors is limited by constrained battery capacity. In this paper, we propose a fusion sensor system for efficient surface monitoring with UGVs. The proposed system combines color information from cameras and depth information from line laser sensors to accurately detect surface displacement. Furthermore, a dynamic sampling algorithm is applied to control the scanning frequency of line laser sensors based on the detection status of monitoring targets using camera sensors, reducing unnecessary energy consumption. A power consumption model of the fusion sensor system analyzes its energy efficiency considering various crack distributions and sensor characteristics in different mission environments. Performance analysis demonstrates that setting the power consumption of the line laser sensor to twice that of the saving state when in the active state increases power consumption efficiency by 13.3% compared to fixed sampling under the condition of λ=10, µ=10.

• Information Systems Review
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• v.22 no.4
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• pp.185-203
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• 2020

With the advent of 4th industrial revolution, the manufacturing industry is converging with ICT and changing into the era of smart manufacturing. In the smart factory, all machines and facilities are connected based on ICT, and thus security should be further strengthened as it is exposed to complex security threats that were not previously recognized. To reduce the risk of security incidents and successfully implement smart factories, it is necessary to identify key security factors to be applied, taking into account the characteristics of the industrial environment of smart factories utilizing ICT. In this study, we propose a 'hierarchical classification model of security factors in smart factory' that includes terminal, network, platform/service categories and analyze the importance of security factors to be applied when developing smart factories. We conducted an assessment of importance of security factors to the groups of smart factories and security experts. In this study, the relative importance of security factors of smart factory was derived by using AHP technique, and the priority among the security factors is presented. Based on the results of this research, it contributes to building the smart factory more securely and establishing information security required in the era of smart manufacturing.

• Applied Chemistry for Engineering
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• v.35 no.1
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• pp.54-60
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• 2024

The present study was aimed to evaluate the removal of the trace pollutants (heavy metals and microplastics) in the sewage treatment plant by using the jellyfish Extract at Immunity reaction (JEI) of Aurelia coerulea. The experiment was conducted on two different scales: the lab scale using a Jar-tester and the Pilot system scale equipped with two newly developed devices in the laboratory, the active tube connection mixed system and the concentration integrated separation device. Compared to anionic polymers currently used in the field, JEI showed similar or higher efficiency to remove the trace pollutants. When JEI was added to the effluent through the Pilot system, the combination of JEI and the trace pollutants was maximized through two mixing processes, and as a result, the removal rate of the trace pollutants was greatly improved. Based on these results, we propose the present technology as an alternative to removing trace pollutants that can reduce ecosystem risk and minimize the generation of inorganic waste, away from the existing method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.173-188
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• 2024

With the advancement of autonomous vehicle (AV) technology, autonomous driving on real roads has become feasible. However, there are challenges in achieving complete autonomy due to perceptual blind areas, which occur when the AV's sensory range or capabilities are limited or impaired by surrounding objects or environmental factors. This study aims to analyze AV accident patterns and safety issues of perceptual blind area that may occur in urban areas, with the goal of developing test scenarios for Level 4+ autonomous driving. It utilized AV accident data from the California Department of Motor Vehicles (DMV) to compare accident patterns and characteristics between AVs and conventional vehicles based on activation status of autonomous mode. It also categorized AV disengagement data to identify types and real-world cases of disengagements caused by perceptual blind areas. The analysis revealed that AVs exhibit different accident types due to their safe driving maneuvers, and three types of perceptual blind area scenarios were identified. The findings of this study serve as crucial foundational data for developing Level 4+ autonomous driving test scenarios, enabling the design of efficient strategies to mitigate perceptual blind areas in various scenarios. This, in turn, is expected to contribute to the effective evaluation and enhancement of AV driving safety on real roads.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.12-28
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• 2024

This study aims to identify the trend of changes in tourist floating population before and after COVID-19 in major tourist destinations in Jeju Island through spatial analysis. Seongsan-eup and Andeok-myeon in Jeju Island were selected as the research area, and the research period was set at 1 year before and 2 years after the COVID-19 outbreak. For the analysis, mobile floating population data was refined and processed to calculate floating population distribution and floating population increase/decrease data. This was converted into spatial data and an overlay analysis was performed with location data of major tourist attractions. As a result of the analysis, it was confirmed that the floating population of indoor tourist attractions and small facilities decreased immediately after COVID-19, and that in open coastal areas or large facilities, the floating population decreased less or actually increased. In conclusion, in tourism development, it is necessary to identify changes in floating population according to the characteristics of tourist facilities, and it is necessary to develop tourism facilities and strategies that can respond to risk situations such as pandemics when developing tourist destinations.

• Journal of Ecology and Environment
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• v.48 no.1
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• pp.96-109
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• 2024

Background: Khyber Pakhtunkhwa government initiated the Billion Tree Tsunami Afforestation Project including regeneration and afforestation approaches. An effort was made to assess the distribution characteristics of afforested species under present and future climatic scenarios using ecological niche modelling. For sustainable forest management, landscape ecology can play a significant role. A significant change in the potential distribution of tree species is expected globally with changing climate. Ecological niche modeling provides the valuable information about the current and future distribution of species that can play crucial role in deciding the potential sites for afforestation which can be used by government institutes for afforestation programs. In this context, the potential distribution of 8 tree species, Cedrus deodara, Dalbergia sissoo, Juglans regia, Pinus wallichiana, Eucalyptus camaldulensis, Senegalia modesta, Populus ciliata, and Vachellia nilotica was modeled. Results: Maxent species distribution model was used to predict current and future distribution of tree species using bioclimatic variables along with soil type and elevation. Future climate scenarios, shared socio-economic pathways (SSP)2-4.5 and SSP5-8.5 were considered for the years 2041-2060 and 2081-2100. The model predicted high risk of decreasing potential distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios for years 2041-2060 and 2081-2100, respectively. Recent afforestation conservation sites of these 8 tree species do not fall within their predicted potential habitat for SSP2-4.5 and SSP5-8.5 climate scenarios. Conclusions: Each tree species responded independently in terms of its potential habitat to future climatic conditions. Cedrus deodara and P. ciliata are predicted to migrate to higher altitude towards north in present and future climate scenarios. Habitat of D. sissoo, P. wallichiana, J. regia, and V. nilotica is practiced to be declined in future climate scenarios. Eucalyptus camaldulensis is expected to be expanded its suitability area in future with eastward shift. Senegalia modesta habitat increased in the middle of the century but decreased afterwards in later half of the century. The changing and shifting forests create challenges for sustainable landscapes. Therefore, the study is an attempt to provide management tools for monitoring the climate change-driven shifting of forest landscapes.

• Journal of the Korean Society of Radiology
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• v.84 no.3
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• pp.676-685
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• 2023

Purpose To investigate the incidence, outcomes, and imaging characteristics of clustered microcysts detected on breast US in asymptomatic women, and suggest appropriate management guidelines. Materials and Methods We identified and reviewed the lesions recorded as "clustered microcysts" on breast US performed in asymptomatic women between August 2014 and December 2019. The final diagnosis was based on pathology and imaging follow-up results for at least 12 months. Results The incidence was 1.5% and 100 patients with 117 lesions were included. Among 117 lesions, 3 (2.6%), 2 (1.7%), and 112 (95.7%) were malignant, high-risk benign, and benign lesions, respectively. The malignant lesions included two cases of ductal carcinoma in situ and one invasive ductal carcinoma. Two of them were assessed as category 4, showing mammographic suspicious microcalcifications and internal vascularity on Doppler US. The remainder was a false negative case and showed echo pattern change on the 12-month follow-up US. Conclusion The incidence of clustered microcysts on breast US in asymptomatic women was 1.5% and malignancy rate was 2.6% (3 of 117). Knowledge of outcomes and imaging features of benign and malignant clustered microcysts may be helpful for radiologists, thereby aiding categorization and management recommendations.

• Information Systems Review
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• v.23 no.3
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• pp.97-125
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• 2021

Blockchain is a core technology to solve personal information leakage and data management issues, which are limitations of existing Genomic Sequencing services. Due to continuous cost reduction and deregulation, the market size of Genomic Sequencing has been increasing, also the potential of services is expected to increase when Blockchain's security and connectivity are combined. We created our research model by combining the Technology Acceptance Model (TAM) and the Innovation Resistance Theory also analyzed the factors affecting the acceptance intention and innovation resistance of the Blockchain Based Genomic Sequencing Information Platform. A survey was conducted on 150 potential users of Blockchain and Genomic Sequencing services. The analysis was conducted by setting the four Blockchain variables: Security, transparency, availability, and diversity). Also, we set the Perceived Usefulness, Perceived risk, and Perceived Complexity for Technology Acceptance and Innovation Resistance variables and analyzed the effect of the characteristics of the Blockchain on acceptance intention and innovation resistance through these variables. Through this analysis, key variables that need to be considered important to reduce resistance and increase acceptance intention could be identified. This study presents innovation factors that should be considered in companies preparing a new Blockchain Based Genomic Sequencing Information Platform.

• Pediatric Infection and Vaccine
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• v.31 no.1
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• pp.94-101
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• 2024

Purpose: Coronavirus disease 2019 (COVID-19) has posed a significant burden to infant and toddler's care globally, while the disease severity is generally mild in this age group. In this study, we aimed to assess epidemiological and clinical aspects of COVID-19 in infants and toddlers in Seoul, South Korea. Methods: We used Seoul Metropolitan Government's epidemiological investigation database to describe the epidemiological and clinical characteristics of COVID-19 in infants and toddlers, between March 2020 to December 2021. Results: A total of 5,025 infants and toddlers aged <5 years was diagnosed between the observed period. 2,720 (54.1%) had symptoms, and fever was the most common symptom in 1,941 (74.1%). Of the diagnosed cases, 96.4% did not have underlying diseases. In a district level, extended opening of childcare facility was associated with increased risk of COVID-19 in infants and toddlers. Conclusions: An efficient monitoring system, resembling routine clinical care, is crucial, considering the low rates of severe progression and fatality among infants and toddlers. Moreover, a well-grounded intervention based on scientific evidence, rather than unconditional closures, is necessary to establish a suitable childcare policy that ensures safety from infectious diseases while not overlooking the developmental aspects of social skills.