• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.87-96
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• 2020

To use a hydraulic structure effectively, the velocity of a river should be known in detail. In reality, velocity measurements are not conducted sufficiently because of their high cost. The formulae to yield the flux and velocity of the river are commonly called the Manning and Chezy formulae, which are empirical equations applied to uniform flow. This study is based on Chiu (1987)'s paper using entropy theory to solve the limits of the existing velocity formula and distribution and suggests the velocity and distance formula derived from information entropy. The data of a channel having records of a spot's velocity was used to verify the derived formula's utility and showed R2 values of distance and velocity of 0.9993 and 0.8051~0.9483, respectively. The travel distance and velocity of a moving spot following the streamflow were calculated using some flow information, which solves the difficulty in frequent flood measurements when it is needed. This can be used to make a longitudinal section of a river composed of a horizontal distance and elevation. Moreover, GIS makes it possible to obtain accurate information, such as the characteristics of a river. The connection with flow information and GIS model can be used as alarming and expecting flood systems.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.561-580
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• 2021

This study analyses the historical and cultural streets at Pinggang Road in the city of Suzhou, by understanding the development and conservation of the area, and uses the following ways to investigate its development, re-organization, and current state. This paper comprehensively compares, collates and investigates 4 different historical and cultural areas in Insadong and Samcheong-dong in South Korea, and South Luogu Lane in China. From initial research and analysis, this paper gathers the cultural, economic, and societal perspectives as non-physical measures, and spatial structure, road structure, and building maintenance as physical factor framework. It is significant in that it can provide an evaluation model for the preservation and regeneration of historical and cultural streets by presenting the viewpoint of complex development of non-physical and physical elements in Pyeonggang-ro. In addition, it is necessary to conduct optimization and specific research on insufficient areas, such as maintenance and development of programs and signature systems for visitors, and continuous development of historical and cultural network platforms by combining on-site surveys. Basic data should be provided for reference on the street.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.35-48
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• 2021

In Suwon, the overall hygiene of the city is threatened by the emergence of the rook(Corvus fugilegus) in the city. Rooks began to appear in November of 2016 and has continued to appear from November to March every year. In order to eradicate or to prepare an alternative habitat for rooks, this study aimed to identify the preferred habitat and specific environmental variables. Therefore, in this work, we aim to understand the predicted distribution of rooks in Suwon City with citizen science and through MaxENT, the most widely utilized habitat modeling using citizen science to analyze the preferred habitat of harmful tides appearing in urban areas. In this study, seven environmental variables were chosen: biotope group complex, building floor, vegetation, euclidean distance from farmland, euclidean distance from streetlamp, and euclidean distance from pole and DEM. Among the estimated models, after the time period of sunrise (08:00~18:00) the contribution percentage were as following: euclidean distance from arable land(39.2%), DEM(25.5%), euclidean distance from streetlamp(22.3%), euclidean distance from pole(7.1%), biotope group complex(4.9%), building floor(1%), vegetation(0%). In the time period after sunset(18:00~08:00) the contribution percentage were as following: biotope group complex(437.4%), euclidean distance from pole(26.8%), DEM(13.4%), euclidean distance from streetlamp(11.8%), euclidean distance from farmland(7.9%), building floor(1.4%), vegetation(1.3%).

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.2
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• pp.73-78
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• 2022

Since Traditional Korean medicine (TKM) doctors use various knowledge systems during treatment, diagnosis results may differ for each TKM doctor. However, it is difficult to explain all the reasons for the diagnosis because TKM doctors use both explicit and implicit knowledge. In this study, an upgraded random forest (RF)-based evaluation tool was proposed to extract clinical knowledge of TKM doctors. Also, it was confirmed to what extent the professor's clinical knowledge was delivered to the trainees by using the evaluation tool. The data used to construct the evaluation tool were targeted at 106 people who visited the Sasang Constitutional Department at Kyung Hee University Korean Medicine Hospital at Gangdong. For explicit knowledge extraction, four TKM doctors were asked to express the importance of symptoms as scores. In addition, for implicit knowledge extraction, importance score was confirmed in the RF model that learned the patient's symptoms and the TKM doctor's constitutional determination results. In order to confirm the delivery of clinical knowledge, the similarity of symptoms that professors and trainees consider important when discriminating constitution was calculated using the Jaccard coefficient. As a result of the study, our proposed tool was able to successfully evaluate the clinical knowledge of TKM doctors. Also, it was confirmed that the professor's clinical knowledge was delivered to the trainee. Our tool can be used in various fields such as providing feedback on treatment, education of training TKM doctors, and development of AI in TKM.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.263-278
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• 2022

With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.349-357
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• 2021

Recently, drones are rapidly becoming common and expanding. There is a great need for diversity in whether drone flight data can be used as entertainment technology analysis data. In particular, it is necessary to check whether it is possible to analyze and utilize the flight and operation process of entertainment drones, which are developing through autonomous and intelligent methods, through data analysis and machine learning. In this paper, it was confirmed whether it can be used as a machine learning technology by using FC data in the evaluation of drones for entertainment. As a result, FC data from DJI and Parrot such as Mavic2 and Anafi were unable to analyze machine learning for entertainment. It is because data is collected at intervals of 0.1 second or more, so that it is impossible to find correlation with other data with GCS. On the other hand, it was found that machine learning technologies can be applied in the case of Fixhawk, which used an ARM processor and operates with the Nuttx OS. In the future, it is necessary to develop technologies capable of analyzing the characteristics of entertainment by dividing fixed-wing and rotary-wing flight information. For this, a model shoud be developed, and systematic big data collection and research should be conducted.

• 한국노년학
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• v.40 no.4
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• pp.747-760
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• 2020

The purpose of this study is to prepare basic data necessary for the development of services or systems that can enhance the accessibility of health and medical services or enhance the efficiency of health and medical use of senior citizens by identifying factors for predicting health and medical use behavior of senior citizens in Incheon Metropolitan City through the Korea health panel data(version 1.5). Through the structural equation model established through the SPSS and AMOS, it was confirmed that the predisposing factors, health behaviors and needs factors had significant direct and indirect effects on the use of health care services. Since the imbalance in demand and supply of health and medical services is more severe than in other regions, the results of this study can be used as basic data when checking whether the current health and medical system in Incheon Metropolitan City can operate effectively in an aged society and discussing how to provide health and medical services to the elderly in Incheon.

• The Korean Journal of Archival Studies
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• no.71
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• pp.237-272
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• 2022

In 2019, the pilot project to establish a record management system for administrative information datasets started in earnest under the leadership of the National Archives. Based on the results of the three-year project by 2021, the improved administrative information dataset management plan will be reflected in public records-related laws and guidelines. Through this, the administrative information dataset becomes the target of full-scale public record management. Although public records have been converted to electronic documents and even the datasets of administrative information systems have been included in full-scale public records management, research on the quality requirements of data itself as raw data constituting records is still lacking. If data quality is not guaranteed, all four properties of records will be threatened in the dataset, which is a structure of data and an aggregate of records. Moreover, if the reliability of the quality of the data of the administrative information system built by reflecting the various needs of the working departments of the institution without considering the standards of the standard records management system is insufficient, the reliability of the public records itself can not be secured. This study is based on the administrative information dataset management plan presented in the "Administrative Information Dataset Recorded Information Service and Utilization Model Study" conducted by the National Archives of Korea in 2021. A study was conducted. By referring to various data, especially public data-related policies and guides, which are being promoted across the government, we would like to derive quality evaluation requirements in terms of records management and present specific indicators. Through this, it is expected that it will be helpful for record management of administrative information dataset which will be in full swing in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.373-380
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• 2022

This paper presents a deep learning based group synchronization that supports networked immersive interactions between remote users. The goal of group synchronization is to enable all participants to synchronously interact with others for increasing user presence Most previous methods focus on NTP-based clock synchronization to enhance time accuracy. Moving average filters are used to control media playout time on the synchronization server. As an example, the exponentially weighted moving average(EWMA) would be able to track and estimate accurate playout time if the changes in input data are not significant. However it needs more time to be stable for any given change over time due to codec and system loads or fluctuations in network status. To tackle this problem, this work proposes the Deep Group Synchronization(DeepGroupSync), a group synchronization based on deep learning that models important features from the data. This model consists of two Gated Recurrent Unit(GRU) layers and one fully-connected layer, which predicts an optimal playout time by utilizing the sequential playout delays. The experiments are conducted with an existing method that uses the EWMA and the proposed method that uses the DeepGroupSync. The results show that the proposed method are more robust against unpredictable or rapid network condition changes than the existing method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.