• (The) Korean Journal of Educational Psychology
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• v.32 no.3
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• pp.571-596
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• 2018

Objectives: This study investigated the challenges of young cross-cultural individuals (CCIs) through the cultural homelessness (CH) framework. Methods: Through a survey of 151 CCIs, the study empirically examined the relationship between CH and psychological well-being (PWB), as well as the moderating role of emotional clarity (EC). Results: Results indicated that CH was significantly and negatively associated with PWB, especially on the Positive Relations with Others and Environmental Mastery dimensions. Individuals with high CH tended to have less satisfactory relationships and a reduced sense of control over daily life situations, regardless of their EC level. A significant interaction effect between CH and EC was found, specifically in Positive Relations with Others (PR) and Personal Growth (PG). For individuals with high CH, however, satisfactory relationships were dependent on their EC level; they reported more positive relationships with others when their EC levels were high. Interestingly, individuals with high CH were likely to report a high desire for personal growth regardless of their EC level, indicating that they may appear ambitious but may be experiencing unclear emotions. Conclusions: These findings suggest that CH and EC are issues that need to be dealt with simultaneously. As individuals' PWB depends not only on their CH level, but also on their EC, reducing the level of CH should not be the only goal in promoting the well-being of CCIs. Increasing individuals' EC would be just as important, as high EC, along with low CH, predicts important dimensions of PWB.

• 한국사회정책
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• v.23 no.2
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• pp.49-81
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• 2016

This study agrees with the idea that a situation centered perspective provides a useful contribution in understanding women's attitude on organizations. Women's occupational experiences are less related to their "femaleness" than to the structural constraints inherent in the occupational positions women fill. So characteristics of the organizational situation including gender composition and hierarchical status may "shape and define" women's experience on the job. The present study examined the managerial level's gender gap and "glass ceiling" of the corporation. According to Kanter, if the ratio of women to men in organizations begins to shift, as affirmative action and new hiring and promotion policies promised, forms of relationships and corporate culture should also change. However, the mere presence of women on workplace may not, in itself, result in women-friendly work condition. This study analyzes "Korean Women Manger Panel survey(2010 3rd. wave)" to examine how much gender gap of the managerial level persists and when the glass ceiling effect emerges. Using t-test and ANOVA, various aspects of the gender gap within managerial level were verified. The most significant finding is the glass ceiling effect starts from very low level of management. Policy implications from the statistical analysis of the Panel survey are: 1) We need to increase the absolute number of the women managers for securing middle level women leadership pipe line. 2) We need to confront the fact that the glass ceiling starts from the very low managerial level, and to explore more realistic way to break up the vicious circle for the tokenism. and 3) We need to looking beyond numbers in approaching women's matter at work. At the cultural and institutional level, work-family programs and policies, women's ratings of their competence, and family-friendly organization's climate should be considered.

• Knowledge Management Research
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• v.22 no.2
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• pp.119-144
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• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.1-10
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• 2022

Irrigation water supplied to the paddy field is consumed in the amount of evapotranspiration, underground infiltration, and natural and artificial drainage from the paddy field. Irrigation return flow is defined as the excess of irrigation water that is not consumed by evapotranspiration and crop, and which returns to an aquifer by infiltration or drainage. The research on estimating the return flow play an important part in water circulation management of agricultural watershed. However, the return flow rate calculations are needs because the result of calculating return flow is different depending on irrigation channel water loss, analysis methods, and local characteristics. In this study, the irrigation return flow rate of agricultural watershed was estimated using the monitoring and SWMM (Storm Water Management Model) modeling from 2017 to 2020 for the Heungeop reservoir located in Wonju, Gangwon-do. SWMM modeling was performed by weather data and observation data, water of supply and drainage were estimated as the result of SWMM model analysis. The applicability of the SWMM model was verified using RMSE and R-square values. The result of analysis from 2017 to 2020, the average annual quick return flow rate was 53.1%. Based on these results, the analysis of water circulation characteristics can perform, it can be provided as basic data for integrated water management.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.249-254
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• 2022

With the rapid advance of the semiconductor and Information and communication technologies, remote environment monitoring technology, which can detect and analyze surrounding environmental conditions with various types of sensors and wireless communication technologies, is also drawing attention. However, since the conventional remote environmental monitoring systems require external power supplies, it causes time and space limitations on comfortable usage. In this study, we proposed the concept of the self-powered remote environmental monitoring system by supplying the power with the levitation-electromagnetic generator (L-EMG), which is rationally designed to effectively harvest biomechanical energy in consideration of the mechanical characteristics of biomechanical energy. In this regard, the proposed L-EMG is designed to effectively respond to the external vibration with the movable center magnet considering the mechanical characteristics of the biomechanical energy, such as relatively low-frequency and high amplitude of vibration. Hence the L-EMG based on the fragile force equilibrium can generate high-quality electrical energy to supply power. Additionally, the environmental detective sensor and wireless transmission module are composed of the micro control unit (MCU) to minimize the required power for electronic device operation by applying the sleep mode, resulting in the extension of operation time. Finally, in order to maximize user convenience, a mobile phone application was built to enable easy monitoring of the surrounding environment. Thus, the proposed concept not only verifies the possibility of establishing the self-powered remote environmental monitoring system using biomechanical energy but further suggests a design guideline.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.27-40
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• 2022

Building self-sustainable rural infrastructure and environment through smart digital agriculture technology innovation is one of the major goals of the Korean agricultural administration as a part of the nation's 4^th industry revolution. To identify areas for improving and effectively investing in the acceleration of rural development, 207 experts in the areas of crop science and smart digital agriculture technology were interviewed for their opinions and suggestions on 22 questions designed to recognize fundamental agricultural issues to be addressed and solutions to advance technology innovation and rural development. Majority of the participants expected smart digital agriculture technologies to resolve major agricultural issues and help build a better rural environment. To overcome technology gaps and resolve issues more effectively, further investment in training new technology experts and building stronger agricultural technology infrastructure is urgent, and persistent and systematic support from agricultural administration appears to be the key for accelerating the process. While the leading global groups of both public and private sectors have advanced their technologies beyond the field application stage, most of the Korean technologies remain at the early pilot stage. Aging population and lack of labor in rural areas, unknown future climate change, and challenges in sustainable rural development are expected to be resolved by smart digital agriculture technologies. Technological innovations by research institutes should be promptly deployed in the crop production field, and farm training systemically organized by local technology centers can accelerate farming revolution. Standardization of equipment and data systems is another key to the success of digitalization of food crop production and food supply chains nationwide.

• Korean Journal of Cognitive Science
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• v.33 no.1
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• pp.51-75
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• 2022

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation that is able to alter neuronal activity in particular brain regions. Many studies have researched how tDCS modulates neuronal activity and reorganizes neural networks. However it is difficult to conclude the effect of brain stimulation because the studies are heterogeneous with respect to the stimulation parameter as well as individual difference. It is not fully in agreement with the effects of brain stimulation. In particular few studies have researched the reason of variability of brain stimulation in response to time so far. The study investigated individual variability of brain stimulation based on circadian rhythm and chronotype. Participants were divided into two groups which are morning type and evening type. The experiment was conducted by Zoom meeting which is video meeting programs. Participants were sent experiment tool which are Muse(EEG device), tdcs device, cell phone and cell phone holder after manuals for experimental equipment were explained. Participants were required to make a phone in frount of a camera so that experimenter can monitor online EEG data. Two participants who was difficult to use experimental devices experimented in a laboratory setting where experimenter set up devices. For all participants the accuracy of 98% was achieved by SVM using leave one out cross validation in classification in the the effects of morning stimulation and the evening stimulation. For morning type, the accuracy of 92% and 96% was achieved in classification in the morning stimulation and the evening stimulation. For evening type, it was 94% accuracy in classification for the effect of brain stimulation in the morning and the evening. Feature importance was different both in classification in the morning stimulation and the evening stimulation for morning type and evening type. Results indicated that the effect of brain stimulation can be explained with brain state and trait. Our study results noted that the tDCS protocol for target state is manipulated by individual differences as well as target state.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.13-34
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• 2022

Soil moisture data have been collected at 11 agrometeorological stations operated by The Korea Meteorological Administration (KMA). This study aimed to verify the accuracy of soil moisture data of KMA and develop a correction formula to be applied to improve their quality. The soil of the observation field was sampled to analyze its physical properties that affect soil water content. Soil texture was classified to be sandy loam and loamy sand at most sites. The bulk density of the soil samples was about 1.5 g/cm³ on average. The content of silt and clay was also closely related to bulk density and water holding capacity. The EnviroSCAN model, which was used as a reference sensor, was calibrated using the self-manufactured "reference soil moisture observation system". Comparison between the calibrated reference sensor and the field sensor of KMA was conducted at least three times at each of the 11 sites. Overall, the trend of fluctuations over time in the measured values of the two sensors appeared similar. Still, there were sites where the latter had relatively lower soil moisture values than the former. A linear correction formula was derived for each site and depth using the range and average of the observed data for the given period. This correction formula resulted in an improvement in agreement between sensor values at the Suwon site. In addition, the detailed approach was developed to estimate the correction value for the period in which a correction formula was not calculated. In summary, the correction of soil moisture data at a regular time interval, e.g., twice a year, would be recommended for all observation sites to improve the quality of soil moisture observation data.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.295-304
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• 2022

The purpose of this study is to detect the sorghum panicle using YOLOv5 based on RGB images acquired by a unmanned aerial vehicle (UAV) system. The high-resolution images acquired using the RGB camera mounted in the UAV on September 2, 2022 were split into 512×512 size for YOLOv5 analysis. Sorghum panicles were labeled as bounding boxes in the split image. 2,000images of 512×512 size were divided at a ratio of 6:2:2 and used to train, validate, and test the YOLOv5 model, respectively. When learning with YOLOv5s, which has the fewest parameters among YOLOv5 models, sorghum panicles were detected with mAP@50=0.845. In YOLOv5m with more parameters, sorghum panicles could be detected with mAP@50=0.844. Although the performance of the two models is similar, YOLOv5s ( 4 hours 35 minutes) has a faster training time than YOLOv5m (5 hours 15 minutes). Therefore, in terms of time cost, developing the YOLOv5s model was considered more efficient for detecting sorghum panicles. As an important step in predicting sorghum yield, a technique for detecting sorghum panicles using high-resolution RGB images and the YOLOv5 model was presented.