• Journal of Digital Convergence
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• v.19 no.5
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• pp.93-103
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• 2021

The special means of transportation introduced to improve the mobility of the transportation vulnerable met the number of legal standards in 2016, but lack of development in terms of quality, such as the existence of long waiting times. In order to streamline the operation of special means of transportation, long-term standby traffic, which is the top 25% of the wait time, was extracted from the Daegu Metropolitan Government's special transportation history data, and spatial autocorrelation analysis and social network analysis were conducted. As a result of the analysis, the correlation between the average waiting time of special transportation users and the space was high. As a result of the analysis of internal degree centrality, the peak time zone is mainly visited by general hospitals, while the off-peak time zone shows high long-term waiting demand for visits by lawmakers. The analysis of external degree centrality showed that residential-based traffic demand was high in both peak and off-peak hours. The results of this study are considered to contribute to the improvement of the quality of the operation of special transportation means, and the academic implications and limitations of the study are also presented.

• Journal of Aerospace System Engineering
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• v.15 no.3
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• pp.1-10
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• 2021

The electro-hydrostatic actuators (EHA) are widely used in various industrial fields since they can independently execute the function of the hydraulic power source and have high efficiency. Particularly, in the aviation field, the EHA is mainly designed as dual redundant asymmetric tandem actuator to mitigate failure and minimize installation space. However, aviation EHAs designed in the form of dual redundant asymmetric tandem actuator have the disadvantage of decreased durability performance due to the occurrence of force fighting. In this paper, the controller is designed based on backstepping technique to improve control performance and reduce force fighting for aviation EHA. The augmented state observer is proposed to estimate the states required for control. Through simulation, it was verified that the proposed controller had superior control performance and significantly reduces the force fighting compared to the general PI controller.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.495-507
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• 2021

With the recent industrial development, accidental pollution in riverine environments has frequently occurred. It is thus necessary to simulate pollutant transport and dispersion using water quality models for predicting pollutant residence times. In this study, we conducted a field experiment in a meandering reach of the Sum River, South Korea, to validate the field applicability and prediction accuracy of RAMS+ (River Analysis and Modeling System+), which is a two-dimensional (2D) stream flow/water quality analysis program. As a result of the simulation, the flow analysis model HDM-2Di and the water quality analysis model CTM-2D-TX accurately simulated the 2D flow characteristics, and transport and mixing behaviors of the pollutant tracer, respectively. In particular, CTM-2D-TX adequately reproduced the elongation of the pollutant cloud, caused by the storage effect associated with local low-velocity zones. Furthermore, the transport model effectively simulated the secondary flow-driven lateral mixing at the meander bend via 2D dispersion coefficients. We calculated the residence time for the critical concentration, and it was elucidated that the calculated residence times are spatially heterogeneous, even in the channel-width direction. The findings of this study suggest that the 2D water quality model could be the accidental pollution analysis tool more efficient and accurate than one-dimensional models, which cannot produce the 2D information such as the 2D residence time distribution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.537-542
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• 2021

This paper improves the possibility of recognizing fast-moving objects through the YOLO (You Only Look Once) deep learning recognition model in an application environment for object recognition in images. The purpose was to study the method of collecting semantic data through processing. In the recognition model, the moving object recognition error was identified as unrecognized because of the difference between the frame rate of the camera and the moving speed of the object and a misrecognition due to the existence of a similar object in an environment adjacent to the object. To minimize the recognition errors by compensating for errors, such as unrecognized and misrecognized objects through the proposed data collection method, and applying vision processing technology for the causes of errors that may occur in images acquired for sports (tennis games) that can represent real similar environments. The effectiveness of effective secondary data collection was improved by research on methods and processing structures. Therefore, by applying the data collection method proposed in this study, ordinary people can collect and manage data to improve their health and athletic performance in the sports and health industry through the simple shooting of a smart-phone camera.

• Korean small business review
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• v.42 no.4
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• pp.47-67
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• 2020

This study analyzed the papers provided by Asia Pacific Journal of Small Business (APJSB) for 40 years. The purpose of this study is looking at the research trends about small and medium business. We tried to identify some stream and feature without manipulation. Textmining and Frequency analysis are executed on topics of every published paper in APJSB to 2019 from 1979. The result suggest that important keyword and feature of research topics in APJSB. And the result show the period feature as well as the whole of research trend in APJSB for 40 years. Futhermore, we suggest some implications derived from the results by adapting business ecosystem model and business managerial system model.

• Korean small business review
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• v.43 no.3
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• pp.75-90
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• 2021

Organization and management scholars have researched social enterprises as hybrid organizations. However, research on the organizational uniqueness of social enterprises as hybrids is limited, especially comparing their organizational characteristics with other traditional types of organizations. Thus, this study attempted to compare social enterprises with traditional for-profit and not-for-profit organizations in the aspect of their organizational hybridity by using the data of the Social Value Survey. The results showed that the orientation of social enterprises in pursuing dual values is weaker than the other two types of organizations. Meanwhile, the results revealed that the extent to which an organization operates for realizing dual values is strongest in social enterprises among the three types of organizations. These findings add to the understanding of social enterprises' organizational hybridity in organization and management studies.

• Journal of the Korea Society of Computer and Information
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• v.26 no.11
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• pp.21-31
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• 2021

As the COVID-19 pandemic rapidly changes healthcare around the globe, the need for smart healthcare that allows for remote diagnosis is increasing. The current classification of respiratory diseases cost high and requires a face-to-face visit with a skilled medical professional, thus the pandemic significantly hinders monitoring and early diagnosis. Therefore, the ability to accurately classify and diagnose respiratory sound using deep learning-based AI models is essential to modern medicine as a remote alternative to the current stethoscope. In this study, we propose a deep learning-based respiratory sound classification model using data collected from medical experts. The sound data were preprocessed with BandPassFilter, and the relevant respiratory audio features were extracted with Log-Mel Spectrogram and Mel Frequency Cepstral Coefficient (MFCC). Subsequently, a Parallel CNN network model was trained on these two inputs using stacking ensemble techniques combined with various machine learning classifiers to efficiently classify and detect abnormal respiratory sounds with high accuracy. The model proposed in this paper classified abnormal respiratory sounds with an accuracy of 96.9%, which is approximately 6.1% higher than the classification accuracy of baseline model.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.77-100
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• 2022

In the era of low growth, many provincial cities are experiencing population decline and aging. Population decline phenomena such as reduction of productive manpower, reduction of finances, deterioration of quality of life, and collapse of the community base are occurring in a chain and are being pushed to the brink of extinction of the cities. This study aims to propose a methodology to objectively estimate the employment creation centers and setting the basic unit of industrial-centered zoning by applying spatial statistical techniques and GIS for the application of the compact city plan as an efficient spatial management policy in a city with a declining population. In details, based on reviewing previous studies on compact city, 'employment complex index(ECI)' were defined considering the number of workers, the number of settlers, and the area of development land, the employment creation center was estimated by applying the 'Local Moran's I' and 'Getis-Ord's Hot-Spot Analysis'. As a case study, changes in the four years of 2013, 2015, 2017, and 2019 were compared and analyzed for Changwon City. As a result, it was confirmed that the employment creation center is becoming compacted and polycentric, which is a significant result that reflects the actual situation well. This results provide the basic data for functional and institutional territorial governance for the regional revitalization platform, and provide meaningful information necessary for spatial policy decision-making, such as population reduction, regional gross domestic product, and public facility arrangement that can respond to energy savings, transportation plans, and medical and health plans.

• Journal of the Korean Geosynthetics Society
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• v.21 no.4
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• pp.55-67
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• 2022

In this paper, fundamentals and recent development of the interferometric synthetic aperture radar, known as InSAR, technique for measuring ground deformation through satellite image analysis are presented together with case histories illustrating its applicability to urban ground deformation monitoring. A study area in Korea was selected and processed based on the muti-temporal time series InSAR analysis, namely SBAS (Small Baseline Subset)-InSAR and PS (Persistent Scatterers)-InSAR using Sentinel-1A SAR images acquired from the year 2014 onward available from European Space Agency Copernicus Program. The ground settlement of the study area for the temporal window of 2014-2022 was evaluated from the viewpoint of the applicability of the InSAR technique for urban infrastructure settlement monitoring. The results indicated that the InSAR technique can reasonably monitor long-term settlement of the study area in millimetric scale, and that the time series InSAR technique can effectively measure ground settlement that occurs over a long period of time as the SAR satellite provides images of the Korean Peninsula at regular time intervals while orbiting the earth. It is expected that the InSAR technique based on higher resolution SAR images with small temporal baseline can be a viable alternative to the traditional ground borne monitoring method for ground deformation monitoring in the 4^th industrial era.

• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.35-44
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• 2022

This study aims to evaluate the stress and life of cylindrical roller bearings used in aircraft gearboxes, and to select a roller profile that minimises the contact stress between bearing rollers and raceways. The mounting clearance of four points contact ball bearing was determined, so that cylindrical roller bearings support all radial loads, and the bearing mounting position was determined to maximise the bearing lives. In addition, the static safety factor and dynamic life of bearing were predicted according to ISO 76 & ISO/TS 16281 using the load spectrum determined based on the operating load cases of aircraft gearboxes. Furthermore, the optimal roller profile was selected by analysing the contact stress according to the roller profile shape, and the safety of each roller was evaluated. The results stated that the required safety factor and lifetime were satisfied, and Johns Gohar roller profile was optimal.