Climate change has significantly affected the rainfall characteristics which can influence the pollutant build-up and wash-off patterns from the catchment. Therefore, this study explored the influence of varying rainfall characteristics on urban and agricultural runoff pollutant export using statistical approaches. For this purpose, Mann-Kendall and Pettitt's test were applied to detect the trend and breakpoint in rainfall characteristics time series. In addition, double mass curve and correlation analysis were used to drive the relationship between rainfall-runoff and pollutant exports from both catchments. The results indicate a significant decreased in total rainfall and average rainfall intensity, while a significant increased trend for antecedents dry days and total storm duration over the study periods. The breakpoint was determined to be 2013 which shows remarkable trend shifts for total rainfall, average rainfall intensity and antecedents dry days except total duration. Double mass curve exhibited a straight line with significant rainfall-runoff relationship indicates a climate change effect on both sites. Overall, higher pollutant exports were observed at both sites during the baseline period as compared to change periods. In agricultural site, most of the pollutants exhibited significant (p< 0.05) association with total rainfall, average rainfall intensity and total storm duration. In contrast, pollutants from urban site significantly correlated with antecedent dry days and average rainfall intensity. Thus, total rainfall, average rainfall intensity and total duration were the significant factors for the agricultural catchment while, antecedents dry days and average rainfall intensity were key factors in build-up and wash-off from the urban catchment.
Bala, Renu;Srivastava, Amit;Ningthoujam, Gouri Devi;Potsangbam, Thadoi;Oinam, Amita;Anal, Ch Lily
Journal of Preventive Medicine and Public Health
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v.54
no.1
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pp.22-30
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2021
Objectives: The coronavirus disease 2019 (COVID-19) pandemic is a public health emergency posing unprecedented challenges for health authorities. Social media may serve as an effective platform to disseminate health-related information. This study aimed to assess the extent of social media use, its impact on preventive behavior, and negative health effects such as cyberchondria and information overload. Methods: A cross-sectional observational study was conducted between June 10, 2020 and August 9, 2020 among people visiting the outpatient department of the authors' institution, and participants were also recruited during field visits for an awareness drive. Questions were developed on preventive behavior, and the Short Cyberchondria Scale and instruments dealing with information overload and perceived vulnerability were used. Results: The study recruited 767 participants with a mean age of about 45 years. Most of the participants (>90%) engaged in preventive behaviors, which were influenced by the extent of information received through social media platforms (β=3.297; p<0.001) and awareness of infection when a family member tested positive (β=29.082; p<0.001) or a neighbor tested positive (β=27.964; p<0.001). The majority (63.0%) of individuals often searched for COVID-19 related news on social media platforms. The mean±standard deviation scores for cyberchondria and information overload were 9.09±4.05 and 8.69±2.56, respectively. Significant and moderately strong correlations were found between cyberchondria, information overload, and perceived vulnerability to COVID-19. Conclusions: This study provides evidence that the use of social media as an information- seeking platform altered preventive behavior. However, excessive and misleading information resulted in cyberchondria and information overload.
Martakis, Panagiotis;Movsessian, Artur;Reuland, Yves;Pai, Sai G.S.;Quqa, Said;Cava, David Garcia;Tcherniak, Dmitri;Chatzi, Eleni
Smart Structures and Systems
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v.29
no.1
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pp.251-266
/
2022
Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.
Sang Hee Lee;So Young Shin;Deok Gyu Choi;Won-Kyung Kim;Seok Pyo Moon;Chang Uk Cheon;Seok Ho Park;Youn Koo Kang;Sung Hyuk Jang
Journal of Drive and Control
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v.21
no.2
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pp.36-43
/
2024
The yield is basic and necessary information in precision agriculture that reduces input resources and enhances productivity. Yield information is important because it can be used to set up farming plans and evaluate farming results. Yield monitoring systems are commercialized in the United States and Japan but not in Korea. Therefore, such a system must be developed. This study was conducted to develop a yield monitoring system that improved performance by correcting a previously developed flow sensor using a grain tank-weighing system. An impact-plated type flow sensor was installed in a grain tank where grains are placed, and grain tank-weighing sensors were installed under the grain tank to estimate the weight of the grain inside the tank. The grain flow rate and grain weight prediction models showed high correlations, with coefficient of determinations (R2) of 0.9979 and 0.9991, respectively. A main controller of the yield monitoring system that calculated the real-time yield using a sensor output value was also developed and installed in a combine harvester. Field tests of the combine harvester yield monitoring system were conducted in a rice paddy field. The developed yield monitoring system showed high accuracy with an error of 0.13%. Therefore, the newly developed yield monitoring system can be used to predict grain weight with high accuracy.
While creativity and innovation is the key to drive the creative economy in the South Korea, the development of analysis framework to evaluate the size and performance is limited. The present study suggests a framework and a method to assess economic impact of the creative economy using inter-industry analysis which employs input-output efficiencies populated by the Korean Bank and empirical data from the national informatization survey conducted by the National Information-society Agency(NIA). The results indicated that, as of 2013, despite of economy downturn, the creative innovation based on the information communication technology(ICT) had been significantly led the production, value-added, and employment inducement. The effect is predominant in the creative industry in an broad sense, that is, technology intensive manufacturing industry. Theoretical and policy implications are discussed.
For a few people's leisure, the natural environment have being deteriorated ceaseless. The plan of the Chungchongpuk Province and the Yungdong District in Chungchongpuk-do which drive foreword the sport and leasure complex designed to construct ski slopes, golf course, and resort hotel in 6,000,000 $m^2$ of natural ecosystem around the Mulhan Valley at Mulhan-ri Sangchon-myon Yungdong-kun Chung-chcngbuk-do by Dongsin Leisure have concerned decrease on biological diversity serious. This study carried out by census Amphibia and Reptilia fauna in the Mulhan Valley to expect the impact of animal diversity by construction of leasure complex and to call attention to understand that impact. 8 species in 5 Families of 2 Orders in Amphibia and 5 species in 2 Families of 1 Order in Reptilia were observed in the Mulhan Valley during June 24, 1994 to June 25, 1994 which showed to be similar to the Natural Park in Korea. 4 of 8 species in Amphibia(Hynobius leechii, Onychodactylus fischeri, Bufo bufo gargarizans, and Rana dybowskii) and 3 of 5 species in Reptilia(Eluphe rufodorsata, Dinodon rufodonatum rufodonatum, and Agkistrodon saxatilus) were revealed the Special Wild Animal recorded by the Ministry of Environment in 1993. Therefore, the Minjujisan seems to have highly reason to conservation by these animal diversity. Around the Minjujisan province was significant connecting the Taebaek Mountains and the Sobaek Mountains on biogeographically with Dokyusan National Park. The plan of Leasure complex in the Mulhan Valley should be cancel in consideration of destruction around the Dokyusan National Park severely by the Muju Resort, Ski slopes, etc. The Minjujisan must be conserve to the Zone of Natural Environment on Amphibia and Reptilia diversity and animal migration route.
The purpose of this study is to examine the impact of enterprise R&D investment on inter-industry technology spillover in Korea under the new Normal Era. In order to do this, we tested the effect of production inducement, backward and forward linkage effects, and the effect of technology spillover such as technology intensity effects and technology diffusion effects based on an input-output framework. The results show that the high index industries of the production inducement effect were professional, scientific and technical activities, manufacture of metal products, and general machinery. Some manufacturers of other non-metallic mineral products and transport equipment sectors appeared to have the strong effect of forward and backward linkages that were almost equivalent to high-tech manufacturing industries. In particular, the industries of professional, scientific and technical activities appeared to have the strong effect of both forward and backward linkages. Therefore, we need to drive a strong policy support to higher enterprise R&D investment in the those particular industries not only to increase global competitiveness, but also to widen up the technology spillover effect on other industries.
This study examined the impact of learning organization activities on burnout and the moderating effect of supervisor trust in a learning organization. The results of the study shows that among the activities of a learning organization, independent variables in this study, promoting inquiry and dialogue as well as encouraging collaboration and team learning affect burnout. In other words, the dedication of an organization to creating a culture in which various learning approaches are experimented through questioning and giving feedback as well as collaborative learning that can reinforce the effective use of team resources have an impact on reducing emotional exhaustion, which is considered to be at the core of burnout. Plus, these factors reduce impersonalization, which is activated to prevent further emotional exhaustion by dealing with customers, colleagues and jobs in a cold, negative and perfunctory way. In this study, the dimensions of promoting inquiry and dialogue as well as encouraging collaboration and team learning were found to reduce the decline in personal sense of achievement of an employee with a negative assessment of himself or herself derived from a lack of achievement in his or her job. Supervisor trust (integrity, benevolence and ability) had a moderating effect on the relationship between strategic learning leadership and impersonalization/emotional exhaustion. This suggests that the trust of supervisor helps mediate and moderate the emotional exhaustion and impersonalization of organizational members by encouraging leaders to drive change and take the organization to a new direction. The study has provided implications that communication plays an important role in reducing burnout in the learning context such as positive, appreciative inquiry and feedback analysis to identify strength, and that supervisor trust is critical in order to ensure strategic learning leadership exerts greater influence on the organization.
Journal of the Korean Society of Earth Science Education
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v.13
no.3
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pp.284-296
/
2020
This study investigates the effect of SSI debate on first-year high school student's opinions about environmental issue, their judgment grounds, and solutions to regional environmental problems. The SSI debate was about white heron habitats near the village where students live. As the main data of the study, environmental perception questionnaires, and students' workbook including open-ended questions were collected before and after class. The environmental perception questionnaire was analyzed by descriptive statistics, and the response of the open-ended questions was analyzed through inductive qualitative research methods. First, the results of this study shows that the SSI debate has a statistically significant impact on students' environmental attitude. Second, a majority of students agreed on the idea that villagers should drive the birds out of town and they did not change their after the discussion class. However, after the discussion class, students' solutions about the issue were changed in a way that more short-term, feasible, concrete, and less time-consuming solutions to the problem. Based on the results of this study, this study implies that SSI issue debate using local problem should be used more often in science classroom so the students recognize local SSI and improve real world problem solving skills.
Bo Min Bae;Dae Wi Jung;Dong Hyung Ryu;Jang Hyeon An;Se O Choi;Yeon Soo Kim;Sang Dae Lee;Seung Je Cho
Journal of Drive and Control
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v.20
no.4
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pp.115-122
/
2023
This study utilized a discrete element method (DEM) simulation, as one of the virtual field trials, to predict the impact of tillage depth on the rotary blade shaft during rotavator tilling. The virtual field for the simulation was generated according to soil properties observed in an actual field. Following the generation of particles for the virtual field, a sequence of calibration steps followed to align the mechanical properties more closely with those of real soil. Calibration was conducted with a focus on bulk density and shear torque, resulting in calibration errors of just 0.02% for bulk density and 0.52% for shear torque. The prediction of the load on a rotary tiller's blade shaft involved a three-pronged approach, considering shaft torque, draft force, and vertical force. In terms of shaft torque, the values exhibited significant increases of 42.34% and 36.91% for every 5-centimeter increment in tillage depth. Similarly, the vertical force saw substantial growth by 40.41% and 36.08% for every 5-centimeter increment. In contrast, the variation in draft force based on tillage depth was comparatively lower at 18.49% and 0.96%, indicating that the effect of tillage depth on draft force was less pronounced than its impact on shaft torque and vertical force. From a perspective of agricultural machinery research, this study provides valuable insights into the DEM soil modeling process, accounting for changes in soil properties with varying tillage depths. These findings are expected to be instrumental in future agricultural machinery design studies.
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