• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.757-763
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• 2019

Recently, Following the recent development of flat panel detector with wide dynamic ranges, increasing numbers of healthcare providers have begun to use digital radiography. As a result, filter thickness standards should be reestablished, as current clinical practice requires the use of thicknesses recommended by the National Council on Radiation Protection and Measurements, which are based on information, acquired using conventional analog systems. Here we investigated the possibility of minimizing dose creep and optimizing patient dose using Al filters in digital radiography. The use of thicker Al filters resulted in a maximum 19.3% reduction in the entrance skin exposure dose when medical images with similar sharpness values were compared. However, resolution, which is a critical factor in imaging, had a significant change of 1.01 lp/mm. This change in resolution is thought to be due to the increased amount of scattered rays generated from the object due to the X-ray beam hardening effect. The increase in the number of scattered rays was verified using the scattering degradation factor. However, the FPD, which has recently been developed and is widely used in various areas, has greater response to radiation than analog devices and has a wide dynamic range. Therefore, the FPD is expected to maintain an appropriate level of resolution corresponding to the increase in the scattered-ray content ratio, which depends on filter thickness. Use of the FPD is also expected to minimize dose creep by reducing the exposure dose.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.155-168
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• 2020

Open source is a key growth engine of the 4th industrial revolution, and the continuous development and use of various algorithms for image processing is expected. The purpose of this study is to examine the effectiveness of the UAS image processing open source based algorithm by comparing and analyzing the water reproduction and moving object filtering function and the time required for data processing in 3D reproduction. Five matching algorithms were compared based on recall and processing speed through the 'ANN-Benchmarks' program, and HNSW (Hierarchical Navigable Small World) matching algorithm was judged to be the best. Based on this, 108 algorithms for image processing were constructed by combining each methods of triangulation, point cloud data densification, and surface generation. In addition, the 3D reproduction and data processing time of 108 algorithms for image processing were studied for UAS (Unmanned Aerial System) images of a park adjacent to the sea, and compared and analyzed with the commercial image processing software 'Pix4D Mapper'. As a result of the study, the algorithms that are good in terms of reproducing water and filtering functions of moving objects during 3D reproduction were specified, respectively, and the algorithm with the lowest required time was selected, and the effectiveness of the algorithm was verified by comparing it with the result of 'Pix4D Mapper'.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.591-598
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• 2020

The all revision of the Road Name Address Act, which contains the contents to be used by expanding the road name address as a means of indicationg the location, has been resloved by the National Assembly. Addresses will be assigned to large-sized facilities (3D mixed-use complex spaces). Here, the 3D (Three-dimensional) address is assigned an indoor path section in the inner passage, dividing the section at intervals. The 3D address will be built on the address information map. For 3D address, data should be built and managed for a 3D complex space(indoor space). Therefore, in this study, the object of the 3D address is defined based on the address conceptual model defined in the international standard, and the 3D address data model is proposed based on IndoorGML. To this, it is proposed as a method of mapping the Core and Navigation module of IndoorGML so that the entity of the 3D address can be expressed in IndoorGML. This study has a limitation in designing a 3D address data model only, but it is meaningful that it suggested a standard for constructing 3D address data in the future.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.19-30
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• 2018

Visual information understanding is known as one of the most difficult and challenging problems in the realization of machine intelligence. This paper proposes deriving visual verb and construction of ActionNet database as a video database for video semantic understanding. Even though development AI (artificial intelligence) algorithms have contributed to the large part of modern advances in AI technologies, huge amount of database for algorithm development and test plays a great role as well. As the performance of object recognition algorithms in still images are surpassing human's ability, research interests shifting to semantic understanding of video contents. This paper proposes candidates of visual verb requiring in the construction of ActionNet as a learning and test database for video understanding. In order to this, we first investigate verb taxonomy in linguistics, and then propose candidates of visual verb from video description database and frequency of verbs. Based on the derived visual verb candidates, we have defined and constructed ActionNet schema and database. According to expanding usability of ActionNet database on open environment, we expect to contribute in the development of video understanding technologies.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.23-32
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• 2021

The high-level Space Situational Awareness (SSA) objective is to provide to the users dependable, accurate and timely information in order to support risk management on orbit and during re-entry and support safe and secure operation of space assets and related services. Therefore the risk assessment for the re-entry of space objects should be managed nationally. In this research, the Software for Re-Entry Prediction of space objects (SREP) was developed for national SSA system. In particular, the rate of change of the drag coefficient is estimated through a newly proposed Drag Scale Factor Estimation (DSFE), and is used for high-precision orbit propagator (HPOP) up to an altitude of 100 km to predict the re-entry time and position of the space object. The effectiveness of this re-entry prediction is shown through the re-entry time window and ground track of space objects falling in real events, Grace-1, Grace-2, Tiangong-1, and Chang Zheng-5B Rocket body. As a result, through analysis 12 hours before the final re-entry time, it is shown that the re-entry time window and crash time can be accurately predicted with an error of less than 20 minutes.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.229-242
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• 2021

The purpose of this study is an empirical case study that focuses on bring about changes in clients through narrative therapy using scaffolding. Through this, the purpose was to find the preferred values and hopes of the future among the stories that the client's has lived in. As the research method, we proceed through unstructured interview and loose structures in qualitative research. On this premise, the counselor did not diagnose or explain the 'decentralized but influential' attitudes and problem. And there was no order in the conversation, and I didn't decide in advance how to react to it before the client made any expressions. This study has the following significance on a practical and academic level: First of all, counseling through scaffolding further enrich the curiosity, temperament, and wishes of the client. Second, the scaffolding provides a concrete picture of the relationship between a counselor and a client in narrative therapy. Third, the scaffolding made in therapeutic dialogue presents a 'learning tasks'. Fourth, counseling through scaffolding has an active meaning that it can develop the higher mental function of clients in charge. Finally, we presented an application of narrative therapy in Vygotsky's theory through analysis of empirical cases. Based on this information, this study did not simply intend to position the client as a research object in narrative therapy. It is meaningful that they have identified the factors necessary to become the subject of narrative therapy and the role of the counselor in the process. In addition, this study has implications in that it contributed to the expansion and substantialization of the research scope of narrative therapy in that it utilized the concept of scaffolding, which has not received much attention in the domestic research.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1871-1877
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• 2022

In the past, satellite development required enormous budget and time, so only some developed countries possessed satellites. However, with the recent emergence of low-budget satellites such as micro-satellites, many countries around the world are participating in satellite development. Low-orbit and geostationary-orbit satellites are used in various fields such as environment and weather monitoring, precise change detection, and disasters. Recently, it has been actively used for monitoring through deep learning-based object-of-interest detection. Until now, Korea has developed satellites for national demand according to the space development plan, and the satellite image obtained through this is used for various purpose in the public and private sectors. Interest in satellite image is continuously increasing in Korea, and various contests are being held to discover ideas for satellite image application and promote technology development. In this special issue, we would like to introduce the topics that participated in the recently held 2022 Satellite Information Application Contest and research on the processing and utilization of KOMPSAT image data.