• Journal of Korean Society for Atmospheric Environment
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• v.28 no.4
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• pp.396-410
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• 2012

The purpose of this study is to quantify the contribution of high emitting vehicles to mobile emission inventories. Analyzed emission data include $NO_x$, HC, and CO results, which were measured through the vehicle Inspection and Maintenance (I/M) program in Seoul metropolitan area. The high emitting vehicles were identified as the top 5% worst polluting cars of the fleet. We estimated that 5% of the gasoline passenger car fleet, which is high emitters, generated 25.5% of $NO_x$, 34.5% of HC, and 66.1% of CO emissions of total inventories for gasoline passenger car fleet in year 2010. In the study, we identified that the older vehicles (older than ten years) and high mileage vehicles (more than 120,000 km driven) comprised high emitter fleet with 70.9% and 71.2%, respectively. The emission contribution of high emitters became larger in younger fleet than in the older fleet. This is due to the reduced emission rates in newly manufactured vehicles, which were developed under the more stringent emission regulation limits. This analysis implies that high emitters could be responsible for an even larger fraction of total vehicular emissions as more advanced technology vehicles are being incorporated into the current vehicle fleet. The findings suggested that the high emitting vehicles should be primarily considered for in-use vehicle emission management program, such as I/M, accelerated vehicle retirement, or catalytic converter replacement, in order to enhance the effectiveness of selected program.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.40 no.2
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• pp.102-107
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• 2007

A remarkable sea surface cooling (SSC) event was observed in the eastern sea of Korean peninsula based on new generation sea surface temperature (NGSST) satellite images in September 2005, when typhoon Nabi passed over the East Sea. The degree of SSC ranged from $1^{\circ}C\;to\;4^{\circ}C$, and its maximum was observed in the southeastern sea area. Daily variations in sea surface temperature at a longitudinal line $(35^{\circ}-41^{\circ}N,\;132^{\circ}E)$, derived from satellite data for September 1-13, 2005, showed that the SSC lasted about 3 days after the typhoon passed in the south of $39^{\circ}N$, whereas it was unclear in the north of$39^{\circ}N$. Water temperature measured by a mooring buoy suggested that the SSC was caused mainly by a vertical mixing of the water column driven by the typhoon, rather than by coastal upwelling.

• Quality Improvement in Health Care
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• v.7 no.2
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• pp.204-216
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• 2000

Background : There has been a concern that the quality of care provided to end-stage renal disease (ESRD) patients in the United States may not be as good as recommended. This paper illustrates a composite measure to assess, the quality of care received by ESRD patients undergoing in-center hemodialysis by incorporating outcomes for 4 major treatment areas. The 4 treatment areas are: dialysis treatments, anemia control, nutritional management, and blood pressure control. Methods : The major data source for the study was the United States Renal Data System (USRDS) Dialysis Morbidity and Mortality Study Wave 1 (DMMS-1) d Sixteen categories of a composite quality indicator were constructed by combining 4 dichotomous variables (16=2*2*2*2). representing the optimal vs. less than optimal level of outcome for each of the 4 treatment outcome measure respectively. Optimal outcome level for each treatment area was defined based on the recommendation from the National Kidney Foundation: (a) delivered dialysis doses (Kt/V) ${\geq}$ 1.2; (b) hematocrit level ${\geq}$ 30%; (c) serum albumin concentration ${\geq}$ 3.8g/dl ; and (d) blood pressure of <140 / <90mmHg. The 16 quality indicator were ranked according to their relative quality weights, which were estimated from its association with the relative risk of survival, adjusting for patient's baseline severity and dialysis facility characteristics. Results : Out of the entire sample of 2,179 patients, only 229 (10%) meet th recommended outcome levels for all 4 treatment areas. Overall, the study patients were distributed evenly over the 16 quality indicators, indicating a great variation in the quality of ESRD care. It appears that the rank of the 16 quality-indicators is driven by serum albumin concentration, suggesting that serum albumin concentration may be the most powerful predictor of ESRD patient survival among the 4 outcome measures. Conclusion : The developed quality indicator has the advantage of describin a range of care for dialysis patients and thus providing a more complete picture of care as compared to previous studies that have focused on only single or few components of the ESRD care.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.173-182
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• 2016

AI (Artificial Intelligence) has attracted interest as a key element for technological advancement in various fields. In Korea, internet companies are leading the development of AI business technology. Active government funding plans for AI technology has also drawn interest. But not everyone is optimistic about AI. Both positive and negative opinions coexist about AI. However, attempts on analyzing people's opinions about AI in a quantitative way was scarce. In this study, we used text mining on SNS (Social Networking Service) to collect opinions about AI. And then we performed a comparative analysis about whether people view it as a positive thing or a negative thing and performed a comparative analysis to recognize popular key-words. Based on the results, it was confirmed that the change of key-words and negative posts have increased through time. And through these results, we were able to predict trend about AI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.36-43
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• 2021

In this research, the accuracy of YOLO v3 algorithm in object detection during AGV (Automated Guided Vehicle) operation was investigated. First of all, AGV with 2D LiDAR and stereo camera was prepared. AGV was driven along the route scanned with SLAM (Simultaneous Localization and Mapping) using 2D LiDAR while front objects were detected through stereo camera. In order to evaluate the accuracy of YOLO v3 algorithm, recall, AP (Average Precision), and mAP (mean Average Precision) of the algorithm were measured with a degree of machine learning. Experimental results show that mAP, precision, and recall are improved by 10%, 6.8%, and 16.4%, respectively, when YOLO v3 is fitted with 4000 training dataset and 500 testing dataset which were collected through online search and is trained additionally with 1200 dataset collected from the stereo camera on AGV.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.154-162
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• 2022

Digital marketing tools are actively used in managing the development of park and recreation complexes to familiarize the population with the objects of natural heritage. This article aims to empirically evaluate digital marketing tools for popularizing the park and recreational complexes. The methodology was based on the concept of ecosystem value of park and recreation complexes as a natural heritage site. These methods included: identifying and selecting websites with information about park and recreation complexes in Slovakia and Ukraine. structural analysis of the main channels of online details about natural parks. Assessing the current state of online identity of the studied sites from the perspective of Internet users. The results indicate that to manage the development of park and recreational complexes developed their driven official websites in the Internet space, on which sections structure the information with the allocation of data on tourism and recreational potential. The article identifies additional digital marketing tools for managing the development of park and recreation complexes, particularly social networks and tourist websites. There is a sufficient amount of information about tourist recreation sites within these natural parks and tourist routes. Among the main problems of the websites: the information on the websites is entirely textual, there is a lack of sufficient data on social networks, despite the created official pages, there is no video content, which was more attracted tourists and visitors, allowing a visual assessment of the tourist potential; there is a problem of many communication channels to present the natural heritage of the countries. The research proves that the website is the primary and most common digital marketing tool for natural heritage, structuring information about tourism potential and recreation.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 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.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.1-22
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• 2024

Purpose - The Chinese fan community includes a significant number of young and middle-aged individuals, playing a crucial role in emotional mobilization and social engagement. In recent years, the impact of Celebrity Pairing or Character Pairing (CP) on Weibo has grown notably, partly due to features like Super Topics and Hot Searches. This phenomenon has enhanced fan engagement, resulting in heightened participation in discussions and interactions on the platform. Our study targets CP fans of movies and television dramas on Weibo and aims to identify the factors that drive their emotional sharing. Design/methodology/approach - The research methodology integrates Self-Determination Theory and Social Sharing of Emotion Theory within the EASI (Emotion, Attachment, and Social Integration) model. This approach aims to uncover how CP fans meet their emotional needs via social media and determine the factors influencing their sharing intentions and behaviours. Data were collected through online surveys, yielding 504 valid responses Findings - The analysis, performed with SPSS and Smart PLS software, reveals that self-determination, interpersonal relationships, and social media tolerance significantly affect fans' intentions to share content. Specifically, intrinsic motivation, driven by self-determination, is a critical factor in CP fans' propensity to share content, highlighting the importance of 'inward socialization.' Additionally, the study finds that external factors, like the social media environment, play a more minor role than internal motivators. Research implications or Originality - This research enhances quantitative research methodologies by identifying intrinsic and extrinsic motivations that satisfy the emotional needs of CP fans. It distinguishes between individual, interpersonal, and collective/social factors as motivational elements, providing insights into the emotional and psychological needs of the Chinese movie and TV drama fan community.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.513-520
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• 2024

This study investigates the changes in teachers' roles as the impact of AI on school education expands. Traditionally, teachers have been responsible for core aspects of classroom instruction, curriculum development, assessment, and feedback. AI can automate these processes, particularly enhancing efficiency through personalized learning. AI also supports complex classroom management tasks such as student tracking, behavior detection, and group activity analysis using integrated camera and microphone systems. However, AI struggles to automate aspects of counseling and interpersonal communication, which are crucial in student life guidance. While direct conversational replacement by AI is challenging, AI can assist teachers by providing data-driven insights and pre-conversation resources. Key competencies required for teachers in the AI era include expertise in advanced instructional methods, dataset analysis, personalized learning facilitation, student and parent counseling, and AI digital literacy. Teachers should collaborate with AI to emphasize creativity, adjust personalized learning paths based on AI-generated datasets, and focus on areas less amenable to AI automation, such as individualized learning and counseling. Essential skills include AI digital literacy and proficiency in understanding and managing student data.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.569-582
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• 2020

Recently, Korea has faced a change in the pattern of water use due to urbanization, which has caused difficulties in understanding the rainfall-runoff process and optimizing the allocation of available water resources. In this perspective, spatially downscaled analysis of the water balance is required for the efficient operation of water resources in the National Water Management Plan and the River Basin Water Resource Management Plan. However, the existing water balance analysis does not fully consider water circulation and availability in the basin, thus, the obtained results provide limited information in terms of decision making. This study aims at developing a novel water circulation analysis model that is designed to support a quasi-real-time assessment of water availability along the river. The water circulation model proposed in this study improved the problems that appear in the existing water balance analysis. More importantly, the results showed a significant improvement over the existing model, especially in the low flow simulation. The proposed modeling framework is expected to provide primary information for more realistic hydrological drought monitoring and drought countermeasures by providing streamflow information in quasi-real-time through a more accurate natural flow estimation approach with highly complex network.